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The existence of common rail separates the fuel supply process and fuel injection process of high-pressure common rail fuel injection system. The high pressure fuel pump only provides high pressure fuel to the common rail according to the working condition of the system. The electrical control unit (ECU) drives the high speed solenoid valve to control the injector to inject high pressure fuel into the cylinder. The two parts work independently. This is the main characteristic of high-pressure common rail fuel injection system different from traditional fuel injection systems [6, 7, 8, 9, 10, 11]. The flow characteristics of high pressure fuel in high-pressure common rail fuel injection systems have an important effect on cycle fuel injection volume. The fuel injector is the main executing part of the fuel injection system. Due to the fuel inertia, fuel in the control chamber and nozzle volume does not immediately stop flowing when the control valve and needle of the injector are suddenly closed. The fuel kinetic energy near the control valve and needle is converted into local pressure gain, then this conversion propagates at the speed of sound to the control chamber and nozzle volume. Finally, the fuel compression wave or expansion wave is reflected back. Because of the energy imbalance, the dynamic pressure wave propagates and oscillates repeatedly in the system until the system reaches a stable state again due to the dissipative effect [12, 13, 14, 15, 16, 17, 18].
The pressure fluctuation has a significant effect on fuel injection rate, which affects the cycle fuel injection volume of the high-pressure common rail fuel injection system. Reference [19] proposed a simplified physical model to predict the fluctuation of fuel injection pressure. Reference [20] designed a fuel acceleration pipeline at the nozzle and two sets of control systems were added to control the fuel flow state in the pipeline. A numerical model was established to predict the fluctuation of fuel injection pressure in theory. To explore the relationship between pressure fluctuation frequency and system structure during fuel injection, Ref. [21] established an LC zero-dimensional equivalent model of common rail, high pressure fuel pipeline and injector. Aiming at the influence of pressure fluctuation of high-pressure common rail fuel injection system on cycle fuel injection volume characteristics, Ref. [22] studied the interrelationship between geometrical dimensions of high pressure fuel pipeline between common rail and injector and pressure fluctuation characteristics and cycle fuel injection volume. The research results show that the size change of high pressure pipeline has a significant impact on the characteristics of single injection cycle fuel injection volume. Reference [23] analyzed the characteristics of cycle fuel injection volume of high-pressure common rail fuel injection system under two working conditions. The research results show that the fuel pressure fluctuation in the injector internal pipeline has a more significant effect on the change of cycle fuel injection volume compared with the pressure fluctuation in the common rail. Reference [24] established a simulation model of high-pressure common rail fuel injection system. The simulation analysis shows that the pressure fluctuation in the fuel chamber during fuel injection is the main reason for the high frequency characteristics of fuel injection rate variation. However, the low frequency characteristics of fuel injection rate variation are determined by the fluctuation of fuel injection pressure.
Multiple injections is one of the main technical means for diesel engines to meet increasingly strict emission regulations. Many scholars have studied the influence of pressure fluctuation on multiple injection cycle fuel injection volume characteristics of high-pressure common rail fuel injection systems. Reference [25] studied the characteristics of cycle fuel injection volume under different injection modes of high-pressure common rail fuel injection systems. The research results show that the fuel pressure fluctuation has an important influence on cycle fuel injection volume because it affects the injection timing of pilot injection, main injection and post-injection. Pressure fluctuation generated after the main injection will cause the needle to be difficult to open during post-injection, which results in post-injection volume fluctuations. Reference [26] changed the injection interval between pilot injection and main injection of high-pressure common rail fuel injection system. It is found that the pulse width of the main injection fluctuates periodically with the increase of the injection interval between pilot injection and main injection when the actual pilot injection cycle fuel injection volume and the actual main injection cycle fuel injection volume are fixed. The pulse width fluctuation frequency only depends on the structural parameters and is independent of diesel engine speed, cycle fuel injection volume, fuel injection pulse width and fuel injection pressure. Reference [27] simulated and analyzed the influence of different fuel properties on the pressure wave and cycle fuel injection volume in high pressure fuel pipeline during three injection processes of high-pressure common rail fuel injection system. The results show that the post-injection fuel volume is affected by the pressure fluctuation caused by the main injection. The change of fuel properties leads to the different phases of pressure fluctuation, which affects the opening of the needle. Thus, the cycle fuel injection volume decreases with the increase of the bulk modulus of elasticity of the fuel. Reference [28] studied the influence of pilot injection timing and pilot injection fuel volume on soot, NOx, combustion noise and fuel consumption rate of diesel engines. The results show that the pressure wave caused by specific pilot injection timing in common rail and high pressure fuel pipeline leads to the dramatic change of main injection cycle fuel injection volume, especially when the injection interval between pilot injection and main injection changes. It has important influence on soot and NOx. In order to reduce the repeated reflection and propagation of fuel pressure fluctuation in high pressure fuel circuits, Ref. [29, 30, 31] designed a pressure storage chamber at the outlet end of high pressure fuel pump and developed a new type of high-pressure common rail fuel injection system. By studying the cycle fuel injection volume of the system and the conventional high-pressure common rail fuel injection system under different common rail pressures, it was found that the different arrangement of the two fuel injection systems leads to the difference in fuel pressure wave propagation and reflection, which leads to the variation of fuel pressure fluctuation characteristics and causes the cycle fuel injection volume to be different.
In this chapter, the pressure fluctuation of high-pressure common rail fuel injection system will be investigated theoretically. The dynamic pressure wave fluctuation mechanism of the system will be analyzed through the experiments. On this basis, the influence of different parameters on dynamic pressure wave during fuel injection will be studied. The results will provide the support for revealing the cycle fuel injection volume fluctuation and its generation mechanism of high-pressure common rail fuel injection system.
High-pressure common rail fuel injection system is mainly composed of the low pressure fuel supply part, including tank, low pressure pump, the high pressure fuel injection part, including high pressure pump, common rail, electrical control injector, the fuel return circuit, which transfers excess fuel from each part back to the tank, the electrical control part, including ECU and various sensors, as shown in Figure 1. During the work process of high-pressure common rail fuel injection system, the plunger of high pressure pump moves downward with the rotation of the camshaft under the action of spring. Fuel is sucked into the high pressure pump plunger chamber from the tank by the low pressure pump through the fuel filter to complete the fuel absorption process. The plunger of the high pressure pump moves upward with the rotation of the camshaft driven by the cam. Fuel in the plunger chamber is compressed and the pressure increases. The pressurized fuel is pumped to the common rail through the high pressure pipeline to complete the process of fuel pressurization and fuel supply. The high pressure fuel in the common rail is distributed to the injector of each cylinder by the high pressure pipeline. Fuel is injected into the cylinder through the nozzle when the solenoid valve coil of the injector is energized. The needle closes the nozzle hole to finish fuel injection when the coil is de-energized, which completes a fuel injection process. The fuel metering valve on high pressure pump connects the plunger chamber of the low pressure pump and high pressure pump, which is opened a triangle fuel metering hole. The ECU controls fuel supply volume by adjusting the opening of the fuel metering hole through outputs pulse width modulation signal, thus realizing the adjustment of common rail pressure. Through the feedback signals of various sensors, ECU outputs corresponding control signals according to the working state of the diesel engine and drives the high speed solenoid valve on the injector to realize the control of injection timing, injection duration and injection times, to complete the real-time control of the fuel injection system.
Schematic diagram of the high-pressure common rail fuel injection system.
The fluctuation characteristics of fuel pressure in the pipeline of high-pressure common rail fuel injection system can be represented as one-dimensional partial differential equations of unstable compressible flow, as shown in Eq. (1).
where
The above-mentioned partial differential equations can be converted into ordinary differential equations as follows.
where (d
While the left–traveling wave is represented by d
The pressure wave in the pipeline of high-pressure common rail fuel injection system is divided into left-traveling wave and right-traveling wave according to the direction of propagation and divided into compression wave and expansion wave according to the change of fuel pressure caused by propagation. Therefore, pressure waves in the pipeline can be divided into the following four types.
Right-traveling compression wave
This kind of fuel pressure wave propagates along the positive direction of
Right-traveling expansion wave
This kind of fuel pressure wave propagates along the positive direction of the
Left-traveling compression wave
This kind of fuel pressure wave propagates backward along the
Left-traveling expansion wave
This kind of fuel pressure wave propagates backward along the
Supposing the right-traveling wave arriving at
where d
When the pressure wave propagates to the boundary surface, another returned pressure wave can be obtained based on the pressure wave and the boundary condition at the moment, which is the reflected wave. Assuming that the right end of the high-pressure common rail fuel injection system is closed, the boundary condition is
There are three boundary conditions for pressure wave propagation and reflection in the pipeline of high-pressure common rail fuel injection system. The boundary type at common rail and high pressure fuel pipeline is outlet isobaric end (outlet opening end). The boundary type is the closed-end when the nozzle needle valve is closed. The boundary type is the orifice flow ends when the needle opening nozzle and injector injection.
Outlet isobaric end
There are the following equations when the right-traveling wave d
Thus, d
It can be seen that the signs of the incident pressure wave and reflected pressure wave are opposite when the pressure wave propagates to the common rail. However, the absolute value of the amplitude of the pressure wave is the same and the wave velocity is the same. The changing of the pressure at the pipeline end is zero and the changing of the velocity is twice that of the incident pressure wave. The reflection with the property of incident wave and reflected wave is opposite (an expansion wave, the other is compression wave) and the absolute value of the amplitude of the pressure wave is the same is called complete negative reflection. Therefore, the pressure wave reflection at common rail and high pressure fuel pipelines is a complete negative reflection.
Closed-end
There are the following equations when the right-traveling wave d
Thus, d
It can be seen that the amplitude of the incident pressure wave and reflected pressure wave is the same after the pressure wave propagates to the nozzle when the needle is closed. However, the velocity disturbance value is the opposite. The velocity change at the nozzle is zero and the pressure variation is twice the amplitude of the incident pressure wave. The reflection with the property of incident wave and reflected wave is the same, that is, an expansion wave or a compression wave at the same time, and the amplitude of pressure disturbance is the same is called complete positive reflection. Therefore, the pressure wave reflection when the needle valve is closed is a complete positive reflection.
Orifice flow end
As shown in Figure 2, the fuel flow from the C-C boundary surface of the pipeline with section
Schematic of the orifice flow end.
where
Thus,
where,
The above equation is the boundary condition equation of the orifice outflow of the high-pressure common rail fuel injection system. It can be seen from the above equation that when
The test bench mainly includes the high pressure common rail injection system test stand, the operation stand and the water-cooling unit. It can measure the dynamic injection characteristics of a six-cylinder engine, such as the fuel injection rate, the fuel injection volume and the fuel injection duration for each cycle at most. The main functions of the high-pressure common rail fuel injection system test bench are to drive high pressure fuel pump, supply fuel to high pressure fuel pump at specified temperature and pressure, drive fuel injection system and real-time measure the dynamic injection characteristics of the system. The operation stand includes monitoring system, electronic control device for single injection instrument, driving equipment of fuel injector, programmable synchronous timing pulse generator, common rail pressure regulator, torque analyzer and DC power supply, etc. It can realize the real-time control and monitor of the experimental process. All of the experimental data results and the environmental parameters of each injector can be recorded after the experiment.
The high-pressure common rail fuel injection system test bench is shown in Figure 3. It consists of a driving motor, high pressure fuel pump, common rail, common rail pressure sensor, oscilloscope, single injection instrument, mechanical part of injection flow and rate (IFR), injector, pressure sensor, high pressure pipeline, electronic part of IFR, ECU, computer terminal and tank. The high pressure fuel pump is driven by the driving motor, which can provide a stable speed input for the system. The common rail pressure sensor installed on the common rail measures the common rail pressure in real-time and feeds the common rail pressure signal back to the ECU. The ECU adjusts the fuel flow into the common rail by adjusting the flow control valve on the high pressure fuel pump to stabilize the common rail pressure. In order to measure the dynamic pressure fluctuation at the injector inlet, a piezoresistive high pressure sensor is installed near the injector end on the high pressure pipeline between the common rail and the injector. The oscilloscope receives the pressure signal at the injector inlet measured by the pressure sensor and the common rail pressure signal measured by the common rail pressure sensor and stores the signal data. The ECU provides control current to the injector according to experiment conditions to complete fuel injection under different conditions.
Schematic diagram of the high-pressure common rail fuel injection system test bench. 1. Drive motor 2. High pressure fuel pump 3. Common rail 4. Common rail pressure sensor 5. Oscilloscope 6. Mechanical part of IFR 7. Injector 8. Pressure sensor 9. High pressure pipeline 10. Electronic part of IFR 11. ECU 12. Computer terminal 13. Tank.
The fuel pressure wave reciprocating propagates within high-pressure common rail fuel injection system during fuel injection. The cycle fuel injection volume is affected by the fuel injection pressure. Therefore, it has important theoretical and practical significance on system optimization design and taking effective method to reduce the adverse impact of pressure fluctuations on cycle fuel injection volume characteristics by thorough analysis on the fluctuation mechanism and influence rule of dynamic pressure wave for high-pressure common rail fuel injection system. Theoretically, the fuel injection pressure refers to the fuel pressure near the nozzle hole. However, due to the fuel pressure in the nozzle is high and the size of the fuel cavity in the nozzle is small, it is difficult to install the pressure sensor near the nozzle hole. More importantly, the installation of a pressure sensor close to the nozzle hole will cause the change of flow field distribution in the nozzle, thus affecting the dynamic pressure fluctuation characteristics of the system. Since the fuel pressure wave propagation in the system with a limited speed, the fuel pressure of the injector inlet only slightly lags behind the nozzle volume pressure at time sequence (fuel injection pressure). It is easily measured and can actually represent the dynamic pressure fluctuation characteristics of the system. In this chapter, the fuel pressure of the injector inlet is used instead of injection pressure to analyze the dynamic pressure wave of the system [32].
Figure 4 shows the characteristics of solenoid valve drive current, fuel injection rate and injector inlet pressure before and after fuel injection of high-pressure common rail fuel injection system when the cycle fuel injection volume is 30 mm3. As shown in the figure, there is a delay characteristic between solenoid valve energized and fuel injection due to the hydraulic delay of the system. In addition, the fuel injection duration is longer than the solenoid valve energized time. The opening of the solenoid valve and needle causes the pressure drop at the injector inlet. The fuel injection duration is consistent with the opening time of the needle due to the dynamic response characteristics of the needle.
Drive current of the solenoid valve, injection rate and inlet pressure of the injector at a fuel injection volume of 30 mm3.
According to the various characteristics of driving current of the solenoid valve, fuel injection rate and injector inlet pressure at different moments, as shown in Figure 4, the curves can be divided into five different stages as follows.
1–2 stages. The solenoid valve coil of the injector is energized, the current gradually increases and the electromagnetic force increases. But the electromagnetic force of the solenoid valve is less than the pretightening force of the control valve reset spring. The control valve is pressed against the control seat and the outlet orifice is not open. The control chamber is filled with high pressure fuel. The resultant of fuel hydraulic pressure on the upper end surface of the needle and pretightening force of reset spring of the needle is larger than the fuel hydraulic pressure on the lower end surface of the needle. The needle is pressed against the needle seat and the injector does not injection fuel. Thus, the injector inlet pressure remains unchanged at 80 MPa.
2–3 stages. The injector inlet pressure drops. The reason is analyzed as follows. The control valve overcomes the pretightening force of the control valve reset spring and moves upward under the action of electromagnetic force of the solenoid valve, and the outlet orifice is opened. The high pressure fuel in the control chamber is discharged to the tank through the low pressure return fuel circuit. The fuel pressure in the control chamber drops rapidly. However, the resultant of fuel hydraulic pressure on the upper end surface of the needle and pretightening force of reset spring of the needle is still larger than the fuel hydraulic pressure on the lower end surface of the needle. The needle is still pressed against the needle seat. The nozzle hole is closed and the injector does not inject fuel. The control valve opens the outlet orifice suddenly arousing an instantaneous expansion wave, which starts between the control valve and the control valve seat.
3–4 stages. The injector inlet pressure continues to drop, but the pressure drop gradient increases. The reason is that the resultant of fuel hydraulic pressure on the upper end surface of the needle and pretightening force of reset spring of the needle is less than the fuel hydraulic pressure on the lower end surface of the needle as the decreasing of the control chamber fuel pressure. The needle moves upward and opens the nozzle hole. The injector starts fuel injection and the fuel injection rate appears. The sudden opening of the needle also arouses an instantaneous expansion wave, which starts between the needle and the needle seat and propagates upward. Due to the existence of the needle channel orifice on the injector body, the pressure drop at the injector inlet is not significant, however, the pressure drop gradient is larger than that when the control valve is opened alone.
4–5 stages. Complete fuel injection process. The expansion wave aroused by the moving parts working processes of the system propagates upward along the fuel circuit in the injector. When it propagates to the common rail, reflecting back a compression wave. This compression wave attempts to recover the fuel pressure in the fuel circuit to the initial value. When it propagates to the injector inlet causes the inlet pressure increasing, as shown in Figure 4. In fact, there is no expansion wave generated between the needle and the needle seat when the needle reaches its maximum lift, and the size of the nozzle hole becomes the main factor limiting fuel injection.
Stage after 5. The nozzle hole is closed by the needle and fuel injection is stopped. The closing of the needle will cause a water hammer effect in the system, a compression wave in the nozzle aroused and propagates upward along the fuel circuit in the injector. The inlet pressure increases when it propagates to the injector inlet, as shown in Figure 4. Since then, the needle and control valve shut down completely. The pressure wave propagates repeatedly in the system. Because the hydraulic shear resistance restrains the pressure wave oscillation, the amplitude of the fuel pressure wave decreases gradually, and the pressure at the injector inlet shows an attenuation oscillation characteristic.
It can be seen from the above analysis that the pressure fluctuation characteristic of the injector inlet before the opening of the needle is independent of the energized time of the solenoid valve coil or the fuel injection duration since this phenomenon will be caused whenever the control valve or the needle starts to move. The pressure fluctuation characteristic of the injector inlet caused by the water hammer effect is obviously dependent on the energized time of the solenoid valve coil since it is generated after the needle valve is closed. Therefore, when the energized time of the solenoid valve coil is shorter, the time interval between the two pressure peaks in Figure 4 is small, the third pressure peak and the subsequent pressure oscillation peak depend on the energized time of the solenoid valve coil due to the pressure wave interaction. As shown in Figure 5, the pressure fluctuation amplitude of the injector inlet is significant when the cycle fuel injection volume of the system is 3 mm3. The fusion of the two pressure peaks is called hydraulic resonance as shown in Figure 4.
Drive current of the solenoid valve, injection rate and inlet pressure of the injector at a fuel injection volume of 3 mm3.
According to the wave mechanism of dynamic pressure wave for high-pressure common rail fuel injection system, the fuel injection rate and fuel injection duration are different with different fuel injection pulse widths, which results in different cycle fuel injection volumes. The change of injection pulse width has a different influence on pressure fluctuation characteristics in the system when the fuel is injected. In addition, the cycle fuel injection volume is different even if the injection pulse width is the same when the high-pressure common rail fuel injection system is under different common rail pressures. Therefore, this section mainly analyzes the influence rule of two key control parameters of the system, namely injection pulse width, and common rail pressure, on the dynamic pressure wave in the system, which provides support for the study of the fluctuation characteristics of cycle fuel injection volume of the system.
Figure 6 shows the pressure fluctuation characteristics of injector inlet during fuel injection of high-pressure common rail fuel injection system with injection pulse width of 400, 600, 800 and 1000 μs, respectively. It can be seen from the figure that under the same high pressure pipeline size and common rail pressure, the injector inlet pressure with different injection pulse widths shows attenuation fluctuation characteristics. The smaller the injection pulse width, the larger the pressure fluctuation amplitude during the injection duration. With the increase of injection pulse width from 400 μs to 1000 μs, the change rate of pressure fluctuation amplitude at injector inlet decreases, and the average injector inlet pressure increases after injection. This is because the system circulates less fuel injection with small pulse width under the same common rail pressure. After the needle is seated and the nozzle is closed, the high pressure fuel in common rail immediately flows through the high pressure pipeline to replenish that injected in the injector. The larger the injection pulse width, the more fuel needed to replenish and the longer the time required. In addition, with the increase of injection pulse width, the needle gradually reaches its maximum lift. At this time, the injection pulse width only affects the moment when the needle closes the nozzle but has no influence on the needle from opening to reaching its maximum lift. Therefore, as shown in the figure, there is no significant difference between the injector inlet pressure from the first trough to the first crest when the injection pulse width is 800 μs and 1000 μs.
Inlet pressure of the injector at different injection pulse widths.
Figure 7 shows the pressure fluctuation characteristics of injector inlet during fuel injection of high-pressure common rail fuel injection system with rail pressures of 40, 80, 120 and 160 MPa, respectively. Each point in the figure is the difference between the injector inlet pressure at specific common rail pressure and the set common rail pressure when the injection pulse width is 800 μs, which reflects the pressure fluctuation characteristics of the system under different common rail pressures more intuitively. As shown in the figure, the inlet pressure of the injector decreases to a certain extent under different common rail pressures when the size of the high pressure pipeline and injection pulse width is constant. The inlet pressure fluctuation of the injector under the common rail pressure of 40 MPa is obviously different from that under the other three common rail pressures. The average pressure fluctuation of the injector inlet under this common rail pressure is higher than that under the other three common rail pressures. The inlet pressure fluctuation rules are consistent when the common rail pressure increases from 80 MPa to 160 MPa. The higher the common rail pressure, the larger the inlet pressure drop amplitude and the lower the average value of pressure fluctuation. When the size of the high pressure pipeline and injection pulse width is the same, the injection pressure increases with the increase of common rail pressure, and the injection pulse width required by the needle to reach the maximum lift decreases. When the common rail pressure is 40 MPa, due to the low common rail pressure, the moment when the control valve fully opens outlet orifice lags behind, and the moment when the control valve closes outlet orifice is advanced. The fuel pressure relief time in the control chamber is shortened and the needle does not reach its maximum lift. The nozzle is closed again before it is fully opened. At this time, the maximum fuel injection rate and the fuel injection duration of the system are small. Therefore, the average value of pressure fluctuation at the injector inlet is high. With the increase of common rail pressure, the difference of control valve opening outlet orifice decreases. But the pressure difference between the control chamber and low pressure fuel circuit and nozzle volume and cylinder is larger when the common rail pressure is high. The fuel discharge rate of the control chamber and the fuel injection rate of the nozzle hole are accelerated, which results in the system pressure drop gradient increases. In addition, the higher the common rail pressure, the longer the needle is maintained at the maximum lift position. This is the main reason why the higher the common rail pressure, the larger the injector inlet pressure drop amplitude, the lower the average pressure fluctuation.
Inlet pressure fluctuation of the injector at different common rail pressures. (a) Common rail pressure at 40 MPa. (b) Common rail pressure at 80 MPa. (c) Common rail pressure at 120 MPa. (d) Common rail pressure at 160 MPa.
It can be seen from the above analysis that the dynamic pressure wave of the system shows different fluctuation characteristics under different injection pulse widths and common rail pressures when the size of the high pressure pipeline is constant. Therefore, the dynamic pressure fluctuation frequency and amplitude of the system are further analyzed with the injection pulse width of 400, 600, 800 and 1000 μs and common rail pressure of 40, 80, 120 and 160 MPa, respectively, to reveal the dynamic pressure wave variation rule of the system under different injection pulse width and common rail pressure.
The area enclosed below the power spectrum density curve represents the amount of energy generated by the fluctuation in the frequency range [33]. Figure 8 shows the power spectrum density obtained by the fast Fourier transform of injector inlet pressure fluctuation under different injector pulse widths and common rail pressures. As shown in Figure 8(a), when the common rail pressure is 40 MPa and the injection pulse width is 400, 600 and 1000 μs, the dynamic pressure wave energy of the system is mainly in the frequency band of 799 Hz–1199 Hz, and the crest characteristics of power spectrum density are significant, and all reach the main crest at the frequency of 999 Hz. At this time, the dynamic pressure wave in the system shows obvious periodic fluctuation characteristics, which mainly fluctuates in the frequency of the main crest. When the fuel injection pulse width is 800 μs, the crest characteristics of the dynamic pressure wave power spectrum density are not obvious, and the fuel pressure fluctuation does not show significant periodic fluctuation characteristics. The pressure wave mainly fluctuates at the frequency of 799, 1199 and 1998 Hz. This may be because the pressure wave frequency aroused by the control valve and needle movement in the system reaches the resonance frequency under this injection pulse width, and all kinds of pressure waves propagate repeatedly and superimpose in the system, which changes the pressure wave frequency characteristics. At this time, the fluctuation characteristic of the system is the most complex, and the influence on the dynamic injection characteristic of the system is the most serious.
Power spectrum density of the injector inlet pressure at different common rail pressures and injection pulse widths.
The injector inlet pressure power spectrum density differs greatly under the four injector pulse widths when the common rail pressure is 80 MPa. The dynamic pressure wave energy of the system is between the frequency band of 599 Hz to 1398 Hz and 799 Hz to 1398 Hz, respectively when the injection pulse width is 400 μs and 800 μs. The power spectrum densities of pressure waves at the injector inlet under the two injection pulse widths have significant crest characteristics, both of which show obvious periodic fluctuation characteristics at the main crest frequency of 1199 Hz. The dynamic pressure wave of the system does not show periodic fluctuation when the injection pulse width is 600 μs and 1000 μs, which shows multi-frequency characteristics. As shown in Figure 8(b), the pressure wave at the injector inlet mainly fluctuates at the frequency of 799 Hz and 1199 Hz when the injection pulse width is 600 μs. The dynamic pressure wave mainly fluctuates at the frequency of 199 Hz and 999 Hz when the injection pulse width is 1000 μs.
As shown in Figure 8(c), the power spectrum density of pressure wave at the injector inlet shows obvious crest characteristics when the common rail pressure is 120 MPa and the injection pulse width is 400, 600 and 800 μs, respectively. The main crest frequency of the pressure wave power spectrum density is 1199 Hz under three injection pulse widths. However, the energy frequency bands are different. The dynamic pressure wave energy is mainly between the frequency band of 799 Hz–1398 Hz when the injection pulse width is 400 μs and 800 μs. The main frequency band of the dynamic pressure wave becomes wider when the injection pulse width is 600 μs, ranges from 799 Hz to 1798 Hz. At the same time, the dynamic pressure wave of the system shows the characteristics of multi-frequency fluctuation when the injection pulse width is 1000 μs, which mainly fluctuates at the frequency of 199 Hz and 1398 Hz.
As shown in Figure 8(d), the variation rule of pressure wave power spectrum density at the injector inlet is similar to that of common rail pressure is 120 MPa when the common rail pressure is 160 MPa and the injection pulse width is 400, 600 and 800 μs, respectively. The dynamic pressure wave mainly fluctuates periodically at the main crest frequency of 1199 Hz. But the energy bands of dynamic pressure wave are different under three injection pulse widths, and the energy band of dynamic pressure wave becomes smaller with the increase of injection pulse width. The main energy bands of the dynamic pressure wave are 599 Hz–1598 Hz, 999 Hz–1798 Hz and 999 Hz–1398 Hz, respectively when the injection pulse width increases from 400 μs to 800 μs. The dynamic pressure wave of the system also shows the multi-frequency fluctuation characteristics when the injection pulse width is 1000 μs, which mainly fluctuates at the frequency of 199 Hz and 1598 Hz.
The fuel density increases with the increase of pressure, which results in the acceleration of pressure wave propagation in the system. Comparing the pressure wave power spectrum density of injector inlet at different common rail pressures under the same injection pulse width in Figure 8, it can be seen that the crest characteristics of pressure wave power spectrum density at injector inlet under different common rail pressures are significant, except for the pressure wave multi-frequency fluctuation operating points. The main crest frequency of the injector inlet pressure wave power spectrum density is the lowest when the common rail pressure is 40 MPa, that is, the pressure wave frequency in the system is low when the common rail pressure is low.
To sum up, the dynamic pressure wave of the system has different frequency characteristics under different injection pulse widths and common rail pressure when the size of the high pressure pipeline is constant. It either fluctuates at the main crest frequency or shows the characteristics of multi-frequency fluctuation. While the dynamic pressure wave of the system shows low frequency fluctuation under a low common rail pressure at the same injection pulse width.
As shown in Figures 6 and 7, the average injector inlet pressure varies with different common rail pressure and injection pulse width. The difference between average injector inlet pressure and setted common rail pressure not only reflects the decreased amplitude of injection pressure in the fuel injection process but also reflects the average amplitude of pressure fluctuation in the system after fuel injection. Therefore, the average pressure drop is defined in this chapter as the difference between the setted common rail pressure and the average injector inlet pressure which locating the moment of injector solenoid valve energized time coordinates from 0 to 10 ms. Figure 9 shows the average pressure drop with common rail pressure under different injection pulse widths. As shown in the figure, the average pressure drop increases linearly with the increase of common rail pressure from 40 MPa to 160 MPa when the size of the high pressure fuel pipeline and injection pulse width is constant. The larger the injection pulse width, the faster the average pressure drop increase rate. In addition, the average pressure drop increases with the increase of injection pulse width from 400 μs to 1000 μs when the size of high pressure fuel pipeline and common rail pressure are constant, and the average pressure drop amplitude increases with the increase of common rail pressure at the two same injection pulse widths. It can be seen that the higher the common rail pressure and the injection pulse width, the larger the average pressure drop.
Variation characteristics of the average pressure drop caused by common rail pressure at different injection pulse widths.
The first trough of the pressure wave at the injector inlet is the minimum pressure of the system after the fuel injection when the nozzle hole is opened, which reflects the maximum pressure drop after stable fuel injection. The first crest of injector inlet pressure is the maximum compression wave returned in the system when the injection pulse width is large. It reflects the pressure fluctuation amplitude of hydraulic resonance when the injection pulse width is small. Therefore, the first trough and the first crest of the injector inlet pressure are the characteristic parameters reflecting the dynamic pressure wave characteristics of the system. Tables 1 and 2 show the trough and crest values of injector inlet pressure fluctuation when the common rail pressure is 40, 80, 120 and 160 MPa and the injection pulse width is 400, 600, 800 and 1000 μs, respectively. For comparative analysis, all values in Table 1 are the difference between the setted common rail pressure and the injector inlet pressure wave trough, and all values in Table 2 are the difference between injector inlet pressure wave crest and setted common rail pressure.
Common rail pressure/MPa | Injection pulse width/μs | |||
---|---|---|---|---|
400 | 600 | 800 | 1000 | |
40 | 2.91 | 2.89 | 2.91 | 2.84 |
80 | 5.17 | 5.15 | 5.14 | 5.15 |
120 | 6.77 | 6.74 | 6.75 | 6.79 |
160 | 7.98 | 8.14 | 8.13 | 8.05 |
Trough of the injector inlet pressure fluctuation at different common rail pressures and injection pulse widths.
Common rail pressure/MPa | Injection pulse width/μs | |||
---|---|---|---|---|
400 | 600 | 800 | 1000 | |
40 | 5.34 | 2.32 | 0.98 | 0.10 |
80 | 7.82 | 3.06 | 0.96 | 1.04 |
120 | 6.12 | 3.77 | 1.83 | 1.87 |
160 | 6.75 | 3.84 | 2.46 | 2.50 |
Crest of the injector inlet pressure fluctuation at different common rail pressures and injection pulse widths.
As shown in Table 1, the troughs of injector inlet pressure fluctuation increase approximately linearly with the increase of common rail pressure under different injection pulse widths when the high pressure fuel pipeline size is constant. The change of injector pulse width has little effect on the trough of injector inlet pressure fluctuation under the same common rail pressure. The trough of injector inlet pressure fluctuation between four injector pulse widths has a maximum difference of 0.16 MPa under the same common rail pressure. It can be seen that the trough of dynamic pressure fluctuation is independent of injection pulse width, but increases with the increase of common rail pressure. The reasons are as follows. The higher the common rail pressure, the faster the opening response of the needle. The fuel injection rate increases after the needle is opened during the same time, the effective flow area at the nozzle hole increases and the fuel in nozzle volume injects through the nozzle hole more quickly. The pressure drop of the system increases and the trough of the pressure wave increases. The increase of injection pulse width under the same common rail pressure does not affect the early opening of the needle. That is, the needle motion state is the same before the injection pulse width is 400 μs. Therefore, the change of injection pulse width does not affect the trough of system pressure fluctuation.
As shown in Table 2, the crests of injector inlet pressure fluctuation increase with the increase of common rail pressure under the same injection pulse width when the size of high pressure fuel pipeline is constant. The smaller the injection pulse width, the higher the crest of injector inlet pressure fluctuation under the same common rail pressure. This is because the higher the common rail pressure with the same injection pulse width, the faster the fuel pressure wave propagates in the system. The superposition time of the large amplitude compression wave reflected from the common rail and the expansion wave aroused by the opening of the needle is advanced, which leads to the increase of the crest of pressure fluctuation at the injector inlet. The smaller the injection pulse width, the shorter the injection duration when the common rail pressure is the same. The short of opening and closing time of the needle will lead to a decrease in the encounter time of the first pressure crest and the third pressure crest as shown in Figure 4. The hydraulic resonance effect of the fuel pressure wave is more significant. Therefore, the crest of injector inlet pressure fluctuation decreases with the increase of injection pulse width at the same common rail pressure.
In this chapter, the pressure fluctuation of high-pressure common rail fuel injection system is studied theoretically. On the basis of revealing the wave mechanism of dynamic pressure wave, the influence of different parameters on the dynamic pressure wave of the fuel injection is investigated. The conclusions are as follows.
The theoretical study of pressure fluctuation for high-pressure common rail fuel injection systems shows that the reflected fuel pressure wave returned from the boundary surface of the pipeline end is the result of the coupling of boundary conditions and propagated pressure wave. The reflection of the pressure wave at common rail and high pressure fuel pipeline is a complete negative reflection. The reflection of the pressure wave when the needle closing is a complete positive reflection. The boundary condition type of needle opening nozzle hole is an orifice flow outlet end.
The dynamic pressure wave mechanism in high-pressure common rail fuel injection system is revealed. The results show that there is a delay characteristic from the solenoid valve energizing to fuel injection, and the fuel injection duration is longer than the solenoid valve energized time. The opening of the solenoid valve and needle causes the drop of injector inlet pressure. The fuel injection duration is consistent with the opening time of the needle. The fluctuation characteristics of injector inlet pressure before the opening of the needle are independent of the solenoid valve energized time or fuel injection duration. However, the fluctuation characteristics of injector inlet pressure caused by the water hammer effect when the needle closing obviously dependent on the solenoid valve energized time.
The influence rules of injection pulse width and common rail pressure on dynamic pressure wave of high-pressure common rail fuel injection system are analyzed. The results show that the inlet pressure of the injector fluctuates in attenuation mode when the injection pulse width is different. The smaller the injection pulse width, the larger the amplitude of pressure fluctuation during fuel injection duration. The change rate of inlet pressure fluctuation amplitude decreases with the increase of injection pulse width. The average injector inlet pressure increases after fuel injection. The inlet pressure of the injector decreases to some extent under different common rail pressure. The average inlet pressure fluctuation of the injector is higher than that of the other three common rail pressures when the common rail pressure is 40 MPa. The inlet pressure fluctuation rules are consistent when the common rail pressure increases from 80 MPa to 160 MPa. The higher the common rail pressure, the larger the injector inlet pressure drop amplitude and the lower the average pressure fluctuation. The dynamic pressure wave of the system has different frequency characteristics under different injection pulse widths and common rail pressure. It either fluctuates at the main crest frequency or shows the characteristics of multi-frequency fluctuation. However, the dynamic pressure wave of the system shows low frequency fluctuation characteristics under a low common rail pressure at the same injection pulse width. The average pressure drop increases linearly with the increase of common rail pressure, and the increase rate of average pressure drop is faster with the increase of injection pulse width. In addition, it increases with the increase of fuel injection pulse width, and the higher the common rail pressure between the two same fuel injection pulse widths, the larger the increased amplitude of the average pressure drop. Both the trough and crest of dynamic pressure waves increase with the increase of common rail pressure. The smaller the fuel injection pulse width, the higher the crest of the pressure wave at the injector inlet.
The authors gratefully acknowledge the financial support from Hebei Provincial Key Laboratory of Heavy Machinery Fluid Power Transmission and Control.
The authors declare no conflict of interest.
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\\n\\nIntechOpen ili njegovi suradnici niti u jednom slučaju neće biti odgovorni za štete (štete uključuju gubitak podataka ili profita, druge poslovne prekide, te sve ostale štete) koje nastanu zbog korištenja materijala na IntechOpenovoj stranici ili nemogućnosti da se iste koriste, čak i ako je IntechOpen ili njegov predstavnik o takvoj šteti obaviješten pismenim ili usmenim putem. Neke jurisdikcije ne dozvoljavaju ograničenja garancija ili ograničenja obveza za posljedične ili slučajne štete pa se u tom slučaju ova ograničenja možda ne odnose na vas.
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\\n\\nIntechOpen nije formalno povezan niti s jednom vanjskom stranicom čije poveznice vode na www.intechopen.com, osim ako to nije izravno navedeno. Iz tog razloga IntechOpen nije odgovoran za sadržaj koji se pojavljuje na takvim stranicama. Poveznica na IntechOpenovu stranicu ne implicira povezanost sa IntechOpenom. Korištenje takvih poveznica isključiva je odgovornost korisnika.
\\n\\nZadržavamo pravo vlasništva nad cjelokupnom stranicom www.intechopen.com i nad svim materijalom na toj stranici. Koristeći se našim uslugama, slažete se da maknete sve poveznice na našu stranicu odmah nakon što to od vas zatražimo. Također, zadržavamo pravo da ove Odredbe i uvjete, i politiku o poveznicama izmjenimo u bilo koje vrijeme. Koristeći se poveznicama na naše stranice slažete se s ovim Odredbama i uvjetima.
\\n\\nAko smatrate da je bilo koja poveznica na našoj stranici sumnjiva iz bilo kojeg razloga, molimo vas da nas kontaktirate. U tom slučaju razmotrit ćemo micanje poveznice s naše stranice, iako nismo obvezni to napraviti.
\\n\\nBez prethodne privole i izričite pisane dozvole, ne možete stvarati okvire oko naših stranica ili koristiti druge tehnike koje na bilo koji način mogu promijeniti prezentaciju ili izgled naše stranice.
\\n\\nIntechOpen može ove Odredbe izmijeniti u bilo koje vrijeme i bez prethodne obavijesti. Koristeći ovu stranicu vi se slažete s trenutnim Odredbama i uvjetima koje su na snazi.
\\n\\nOve Odredbe i uvjeti su sastavljeni u skladu s odredbama prava Ujedinjenog Kraljevstva, a za sve sporove nadležan je sud u Londonu, Ujedinjeno Kraljevstvo.
\\n"}]'},components:[{type:"htmlEditorComponent",content:"Pristupom na stranicu www.intechopen.com slažete se s ovim odredbama, sa svim primjenjivim zakonskim odredbama, te se slažete s poštovanjem svih lokalnih zakona. Korištenje i/ili pristup ovoj stranici temelji se na potpunom prihvaćanju ovih odredbi. Svi materijali na ovoj stranici zaštićeni su primjenjivim zakonima o autorskim pravima i žigu.
\n\nSljedeća terminologija odnosi se na Odredbe i uvjete, te na sve naše ugovore:
\n\nKlijent, stranka, vi, vaš odnosi se na vas, osobu koja pristupa ovoj stranici i prihvaća IntechOpenove Odredbe i uvjete;
\n\nKompanija, tvrtka, mi, naše odnosi se na tvrtku IntechOpen;
\n\nStranke, strane odnosi se na klijenta i na nas, ili samo na klijenta ili nas.
\n\nSve odredbe koje se odnose na ponudu, prihvat ili razmatranje plaćanja, a za koja mi pružamo asistenciju klijentu, bilo na ugovoreni ili fiksni način, a s ciljem da se ostvare potrebe i želje klijenta u svezi s našim uslugama, su podložne zakonskim odredbama Ujedinjenog Kraljevstva.
\n\nOsim ako nije suprotno navedeno, IntechOpen i/ili svi davatelji licence vlasnici su intelektualnog vlasništva nad svim materijalima na www.intechopen.com. Sva prava intelektualnog vlasništva su pridržana. Stranice sa www.intechopen.com možete gledati, preuzimati, dijeliti, dijeliti poveznice i printati za osobnu uporabu, a temeljem pravila sadržanih u ovim Odredbama i uvjetima.
\n\nMi koristimo kolačiće. Korištenjem IntechOpenove stranice slažete se s korištenjem kolačića u skladu s IntechOpenovom Politikom privatnosti. Većina modernih, interaktivnih stranica koristi kolačiće kako bi omogućila ponovno pronalaženje korisničkih detalja kod svakog posjeta. Na našoj stranici kolačići se uglavnom koriste kako bi omogućili funkcionalnost i olakšali posjetiteljima korištenje stranice.
\n\nIntechOpen ili njegovi suradnici niti u jednom slučaju neće biti odgovorni za štete (štete uključuju gubitak podataka ili profita, druge poslovne prekide, te sve ostale štete) koje nastanu zbog korištenja materijala na IntechOpenovoj stranici ili nemogućnosti da se iste koriste, čak i ako je IntechOpen ili njegov predstavnik o takvoj šteti obaviješten pismenim ili usmenim putem. Neke jurisdikcije ne dozvoljavaju ograničenja garancija ili ograničenja obveza za posljedične ili slučajne štete pa se u tom slučaju ova ograničenja možda ne odnose na vas.
\n\nMaterijali koji se pojavljuju na IntechOpenovoj stranici mogu sadržavati manje greške, tipfelere ili fotografske greške. IntechOpen može napraviti promjene na bilo kojem materijalu koji se nalazi na stranici u bilo koje vrijeme.
\n\nIntechOpen nije formalno povezan niti s jednom vanjskom stranicom čije poveznice vode na www.intechopen.com, osim ako to nije izravno navedeno. Iz tog razloga IntechOpen nije odgovoran za sadržaj koji se pojavljuje na takvim stranicama. Poveznica na IntechOpenovu stranicu ne implicira povezanost sa IntechOpenom. Korištenje takvih poveznica isključiva je odgovornost korisnika.
\n\nZadržavamo pravo vlasništva nad cjelokupnom stranicom www.intechopen.com i nad svim materijalom na toj stranici. Koristeći se našim uslugama, slažete se da maknete sve poveznice na našu stranicu odmah nakon što to od vas zatražimo. Također, zadržavamo pravo da ove Odredbe i uvjete, i politiku o poveznicama izmjenimo u bilo koje vrijeme. Koristeći se poveznicama na naše stranice slažete se s ovim Odredbama i uvjetima.
\n\nAko smatrate da je bilo koja poveznica na našoj stranici sumnjiva iz bilo kojeg razloga, molimo vas da nas kontaktirate. U tom slučaju razmotrit ćemo micanje poveznice s naše stranice, iako nismo obvezni to napraviti.
\n\nBez prethodne privole i izričite pisane dozvole, ne možete stvarati okvire oko naših stranica ili koristiti druge tehnike koje na bilo koji način mogu promijeniti prezentaciju ili izgled naše stranice.
\n\nIntechOpen može ove Odredbe izmijeniti u bilo koje vrijeme i bez prethodne obavijesti. Koristeći ovu stranicu vi se slažete s trenutnim Odredbama i uvjetima koje su na snazi.
\n\nOve Odredbe i uvjeti su sastavljeni u skladu s odredbama prava Ujedinjenog Kraljevstva, a za sve sporove nadležan je sud u Londonu, Ujedinjeno Kraljevstvo.
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Algorithms"},signatures:"Zhong-Hua Han and Ke-Shi Zhang",authors:[{id:"33820",title:"Dr.",name:"Ke-Shi",middleName:null,surname:"Zhang",slug:"ke-shi-zhang",fullName:"Ke-Shi Zhang"},{id:"107162",title:"Prof.",name:"Zhong-Hua",middleName:null,surname:"Han",slug:"zhong-hua-han",fullName:"Zhong-Hua Han"}]},{id:"40722",doi:"10.5772/52009",title:"SVM Classifiers – Concepts and Applications to Character Recognition",slug:"svm-classifiers-concepts-and-applications-to-character-recognition",totalDownloads:3731,totalCrossrefCites:5,totalDimensionsCites:16,abstract:null,book:{id:"2182",slug:"advances-in-character-recognition",title:"Advances in Character Recognition",fullTitle:"Advances in Character Recognition"},signatures:"Antonio Carlos Gay Thome",authors:[{id:"147034",title:"PhD.",name:"Antonio Carlos",middleName:null,surname:"Thomé",slug:"antonio-carlos-thome",fullName:"Antonio Carlos Thomé"}]},{id:"684",doi:"10.5772/5286",title:"Reinforcement Learning for Building Environmental Control",slug:"reinforcement_learning_for_building_environmental_control",totalDownloads:4237,totalCrossrefCites:7,totalDimensionsCites:15,abstract:null,book:{id:"2220",slug:"reinforcement_learning",title:"Reinforcement Learning",fullTitle:"Reinforcement Learning"},signatures:"Konstantinos Dalamagkidis and Dionysia Kolokotsa",authors:null},{id:"57282",doi:"10.5772/intechopen.71039",title:"Artificial Neural Networks (ANNs) for Spectral Interference Correction Using a Large-Size Spectrometer and ANN-Based Deep Learning for a Miniature One",slug:"artificial-neural-networks-anns-for-spectral-interference-correction-using-a-large-size-spectrometer",totalDownloads:1529,totalCrossrefCites:6,totalDimensionsCites:13,abstract:"Artificial neural networks (ANNs) are evaluated for spectral interference correction using simulated and experimentally obtained spectral scans. Using the same data set (where possible), the predictive ability of shallow depth ANNs was validated against partial least squares (PLS, a traditional chemometrics method). Spectral interference (in the form of overlaps between spectral lines) is a key problem in large-size, long focal length inductively coupled plasma-optical emission spectrometry (ICP-OES). Unless corrected, spectral interference can be sufficiently severe to the point of preventing precise and accurate analytical determinations. In miniaturized, microplasma-based optical emission spectrometry with a portable, short focal length spectrometer (having poorer resolution than its large-size counterpart), spectral interference becomes even more severe. To correct it, we are evaluating use of deep learning ANNs. Details are provided in this chapter.",book:{id:"6187",slug:"advanced-applications-for-artificial-neural-networks",title:"Advanced Applications for Artificial Neural Networks",fullTitle:"Advanced Applications for Artificial Neural Networks"},signatures:"Z. Li, X. Zhang, G. A. Mohua and Vassili Karanassios",authors:[{id:"60925",title:"Prof.",name:"Vassili",middleName:null,surname:"Karanassios",slug:"vassili-karanassios",fullName:"Vassili Karanassios"}]},{id:"57304",doi:"10.5772/intechopen.70791",title:"Data Assimilation by Artificial Neural Networks for an Atmospheric General Circulation Model",slug:"data-assimilation-by-artificial-neural-networks-for-an-atmospheric-general-circulation-model",totalDownloads:1715,totalCrossrefCites:8,totalDimensionsCites:13,abstract:"Numerical weather prediction (NWP) uses atmospheric general circulation models (AGCMs) to predict weather based on current weather conditions. The process of entering observation data into mathematical model to generate the accurate initial conditions is called data assimilation (DA). It combines observations, forecasting, and filtering step. This paper presents an approach for employing artificial neural networks (NNs) to emulate the local ensemble transform Kalman filter (LETKF) as a method of data assimilation. This assimilation experiment tests the Simplified Parameterizations PrimitivE-Equation Dynamics (SPEEDY) model, an atmospheric general circulation model (AGCM), using synthetic observational data simulating localizations of meteorological balloons. For the data assimilation scheme, the supervised NN, the multilayer perceptrons (MLPs) networks are applied. After the training process, the method, forehead-calling MLP-DA, is seen as a function of data assimilation. The NNs were trained with data from first 3 months of 1982, 1983, and 1984. The experiment is performed for January 1985, one data assimilation cycle using MLP-DA with synthetic observations. The numerical results demonstrate the effectiveness of the NN technique for atmospheric data assimilation. The results of the NN analyses are very close to the results from the LETKF analyses, the differences of the monthly average of absolute temperature analyses are of order 10–2. The simulations show that the major advantage of using the MLP-DA is better computational performance, since the analyses have similar quality. The CPU-time cycle assimilation with MLP-DA analyses is 90 times faster than LETKF cycle assimilation with the mean analyses used to run the forecast experiment.",book:{id:"6187",slug:"advanced-applications-for-artificial-neural-networks",title:"Advanced Applications for Artificial Neural Networks",fullTitle:"Advanced Applications for Artificial Neural Networks"},signatures:"Rosangela Saher Cintra and Haroldo F. de Campos Velho",authors:[{id:"215748",title:"Dr.",name:"Rosangela",middleName:null,surname:"Cintra",slug:"rosangela-cintra",fullName:"Rosangela Cintra"},{id:"215753",title:"Dr.",name:"Haroldo",middleName:null,surname:"Campos Velho",slug:"haroldo-campos-velho",fullName:"Haroldo Campos Velho"}]}],mostDownloadedChaptersLast30Days:[{id:"50071",title:"Retrieval of Optical Constant and Particle Size Distribution of Particulate Media Using the PSO-Based Neural Network Algorithm",slug:"retrieval-of-optical-constant-and-particle-size-distribution-of-particulate-media-using-the-pso-base",totalDownloads:1977,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"An improved neural network algorithm was proposed and applied to the inverse radiative problems. A multi-strategy particle swarm optimization was applied to improve the performance of the back propagation multi-layer feed-forward neural network algorithm. Three commonly used particle size distribution (PSD) functions in a one-dimensional particle system were retrieved using the proposed algorithm. In addition, the optical constant was also estimated, and the measurement errors were considered. Results show that the proposed algorithm can be applied to the retrieval of PSDs and optical constant even with measurement errors. Finally, the proposed algorithm was applied to the simultaneous estimation of the PSDs and optical constant using the multi-wavelength and multi-thickness method.",book:{id:"5127",slug:"new-applications-of-artificial-intelligence",title:"New Applications of Artificial Intelligence",fullTitle:"New Applications of Artificial Intelligence"},signatures:"Hong Qi, Ya-Tao Ren, Jun-You Zhang, Li-Ming Ruan and He-Ping\nTan",authors:[{id:"177857",title:"Prof.",name:"Hong",middleName:null,surname:"Qi",slug:"hong-qi",fullName:"Hong Qi"}]},{id:"50870",title:"Fuzzy Logic Control of Switched Reluctance Motor Drives",slug:"fuzzy-logic-control-of-switched-reluctance-motor-drives",totalDownloads:2397,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"In this chapter, the electromechanical behavior of switched reluctance motor (SRM) is first modeled by analyzing the related nonlinear differential equations. In the model, the estimation of rotor speed is also considered. After modeling, the effects of torque ripple, radial force, and acoustic noise are investigated. As we know, torque ripple and acoustic noise are two of the main disadvantages of a switched reluctance motor. Thus, a fuzzy logic current compensator is proposed both for reducing the peak of radial force and for decreasing acoustic noise effects. In the parts that torque reduces, the fuzzy logic current compensator injects additional current for each phase current to overcome the torque ripple. Also, the fuzzy logic current compensator reduces speed estimation error. The speed estimation is carried out using a hybrid sliding mode observer which estimates the rotor position and speed for a wide speed range. These new approaches have been simulated using MATLAB/SIMULINK for a nonlinear model of switched reluctance motor. The simulation results indicate that proposed methods decrease the maximum radial force and the torque ripple while the maximum torque is preserved. Also, these results show that proposed methods will estimate the rotor position and speed with high precision for all speeds from near zero speeds up to rated speed. These procedures have the advantages of simple implementation on the every switched reluctance motor drive without extra hardware, low cost, high reliability, low vibration, and excellent performance at long term.",book:{id:"5127",slug:"new-applications-of-artificial-intelligence",title:"New Applications of Artificial Intelligence",fullTitle:"New Applications of Artificial Intelligence"},signatures:"M. Divandari and B. Rezaie",authors:[{id:"155417",title:"Dr.",name:"Mohammad",middleName:null,surname:"Divandari",slug:"mohammad-divandari",fullName:"Mohammad Divandari"}]},{id:"57042",title:"Gait Generation of Multilegged Robots by using Hardware Artificial Neural Networks",slug:"gait-generation-of-multilegged-robots-by-using-hardware-artificial-neural-networks",totalDownloads:1345,totalCrossrefCites:4,totalDimensionsCites:5,abstract:"Living organisms can act autonomously because biological neural networks process the environmental information in continuous time. Therefore, living organisms have inspired many applications of autonomous control to small-sized robots. In this chapter, a small-sized robot is controlled by a hardware artificial neural network (ANN) without software programs. Previously, the authors constructed a multilegged walking robot. The link mechanism of the limbs was designed to reduce the number of actuators. The current paper describes the basic characteristics of hardware ANNs that generate the gait for multilegged robots. The pulses emitted by the hardware ANN generate oscillating patterns of electrical activity. The pulse-type hardware ANN model has the basic features of a class II neuron model, which behaves like a resonator. Thus, gait generation by the hardware ANNs mimics the synchronization phenomena in biological neural networks. Consequently, our constructed hardware ANNs can generate multilegged robot gaits without requiring software programs.",book:{id:"6187",slug:"advanced-applications-for-artificial-neural-networks",title:"Advanced Applications for Artificial Neural Networks",fullTitle:"Advanced Applications for Artificial Neural Networks"},signatures:"Ken Saito, Masaya Ohara, Mizuki Abe, Minami Kaneko and Fumio\nUchikoba",authors:[{id:"157327",title:"Dr.",name:"Ken",middleName:null,surname:"Saito",slug:"ken-saito",fullName:"Ken Saito"},{id:"157328",title:"Dr.",name:"Minami",middleName:null,surname:"Kaneko",slug:"minami-kaneko",fullName:"Minami Kaneko"},{id:"157330",title:"Prof.",name:"Fumio",middleName:null,surname:"Uchikoba",slug:"fumio-uchikoba",fullName:"Fumio Uchikoba"},{id:"219934",title:"Mr.",name:"Masaya",middleName:null,surname:"Ohara",slug:"masaya-ohara",fullName:"Masaya Ohara"},{id:"219935",title:"BSc.",name:"Mizuki",middleName:null,surname:"Abe",slug:"mizuki-abe",fullName:"Mizuki Abe"}]},{id:"67472",title:"Object Re-Identification Based on Deep Learning",slug:"object-re-identification-based-on-deep-learning",totalDownloads:1352,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"With the explosive growth of video data and the rapid development of computer vision technology, more and more relevant technologies are applied in our real life, one of which is object re-identification (Re-ID) technology. Object Re-ID is currently concentrated in the field of person Re-ID and vehicle Re-ID, which is mainly used to realize the cross-vision tracking of person/vehicle and trajectory prediction. This chapter combines theory and practice to explain why the deep network can re-identify the object. To introduce the main technical route of object Re-ID, the examples of person/vehicle Re-ID are given, and the improvement points of existing object Re-ID research are described separately.",book:{id:"8725",slug:"visual-object-tracking-with-deep-neural-networks",title:"Visual Object Tracking with Deep Neural Networks",fullTitle:"Visual Object Tracking with Deep Neural Networks"},signatures:"Xiying Li and Zhihao Zhou",authors:null},{id:"56981",title:"Advanced Process Control",slug:"advanced-process-control",totalDownloads:1359,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"The debutanizer column is an important unit operation in petroleum refining industries. The top product is liquefied petroleum gas and the bottom product is light naphtha. This system is difficult to handle. This is because due to its non-linear behavior, multivariable interaction and existence of numerous constraints on its manipulated variable. Neural network techniques have been increasingly used for a wide variety of applications. In this book, equation-based multi-input multi-output (MIMO) neural network has been proposed for multivariable control strategy to control the top and bottom temperatures of the column. The manipulated variables for column are reflux and reboiler flow rates, respectively. This neural network model are based on multivariable equation, instead of the normal black box structure. It has the advantage of being robust in nature while being easier to interpret in terms of its input-output variables. It has been employed for set point changes and disturbance changes. The results show that the neural network equation-based model for direct inverse and internal model approach performs better than the conventional proportional, integral and derivative (PID) controller.",book:{id:"6187",slug:"advanced-applications-for-artificial-neural-networks",title:"Advanced Applications for Artificial Neural Networks",fullTitle:"Advanced Applications for Artificial Neural Networks"},signatures:"Nasser Mohamed Ramli",authors:[{id:"209483",title:"Dr.",name:"Nasser",middleName:null,surname:"Mohamed Ramli",slug:"nasser-mohamed-ramli",fullName:"Nasser Mohamed Ramli"}]}],onlineFirstChaptersFilter:{topicId:"522",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:87,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:98,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:27,numberOfPublishedChapters:287,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:9,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:139,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:0,numberOfUpcomingTopics:2,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!1},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:107,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:10,numberOfPublishedChapters:103,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:0,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!1},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:10,numberOfOpenTopics:4,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"May 18th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:27,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:9,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"79367",title:"Dr.",name:"Ana Isabel",middleName:null,surname:"Flores",slug:"ana-isabel-flores",fullName:"Ana Isabel Flores",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRpIOQA0/Profile_Picture_1632418099564",institutionString:null,institution:{name:"Hospital Universitario 12 De Octubre",institutionURL:null,country:{name:"Spain"}}},{id:"328234",title:"Ph.D.",name:"Christian",middleName:null,surname:"Palavecino",slug:"christian-palavecino",fullName:"Christian Palavecino",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000030DhEhQAK/Profile_Picture_1628835318625",institutionString:null,institution:{name:"Central University of Chile",institutionURL:null,country:{name:"Chile"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",slug:"francisco-javier-martin-romero",fullName:"Francisco Javier Martin-Romero",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",institutionString:null,institution:{name:"University of Extremadura",institutionURL:null,country:{name:"Spain"}}}]},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. 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He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. 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His research interest focuses on computational chemistry and molecular modeling of diverse systems of pharmacological, food, and alternative energy interests by resorting to DFT and Conceptual DFT. He has authored a coauthored more than 255 peer-reviewed papers, 32 book chapters, and 2 edited books. He has delivered speeches at many international and domestic conferences. He serves as a reviewer for more than eighty international journals, books, and research proposals as well as an editor for special issues of renowned scientific journals.",institutionString:"Centro de Investigación en Materiales Avanzados",institution:{name:"Centro de Investigación en Materiales Avanzados",country:{name:"Mexico"}}},{id:"76477",title:"Prof.",name:"Mirza",middleName:null,surname:"Hasanuzzaman",slug:"mirza-hasanuzzaman",fullName:"Mirza Hasanuzzaman",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/76477/images/system/76477.png",biography:"Dr. Mirza Hasanuzzaman is a Professor of Agronomy at Sher-e-Bangla Agricultural University, Bangladesh. He received his Ph.D. in Plant Stress Physiology and Antioxidant Metabolism from Ehime University, Japan, with a scholarship from the Japanese Government (MEXT). Later, he completed his postdoctoral research at the Center of Molecular Biosciences, University of the Ryukyus, Japan, as a recipient of the Japan Society for the Promotion of Science (JSPS) postdoctoral fellowship. He was also the recipient of the Australian Government Endeavour Research Fellowship for postdoctoral research as an adjunct senior researcher at the University of Tasmania, Australia. Dr. Hasanuzzaman’s current work is focused on the physiological and molecular mechanisms of environmental stress tolerance. Dr. Hasanuzzaman has published more than 150 articles in peer-reviewed journals. He has edited ten books and written more than forty book chapters on important aspects of plant physiology, plant stress tolerance, and crop production. According to Scopus, Dr. Hasanuzzaman’s publications have received more than 10,500 citations with an h-index of 53. He has been named a Highly Cited Researcher by Clarivate. He is an editor and reviewer for more than fifty peer-reviewed international journals and was a recipient of the “Publons Peer Review Award” in 2017, 2018, and 2019. He has been honored by different authorities for his outstanding performance in various fields like research and education, and he has received the World Academy of Science Young Scientist Award (2014) and the University Grants Commission (UGC) Award 2018. He is a fellow of the Bangladesh Academy of Sciences (BAS) and the Royal Society of Biology.",institutionString:"Sher-e-Bangla Agricultural University",institution:{name:"Sher-e-Bangla Agricultural University",country:{name:"Bangladesh"}}},{id:"187859",title:"Prof.",name:"Kusal",middleName:"K.",surname:"Das",slug:"kusal-das",fullName:"Kusal Das",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSBDeQAO/Profile_Picture_1623411145568",biography:"Kusal K. Das is a Distinguished Chair Professor of Physiology, Shri B. M. Patil Medical College and Director, Centre for Advanced Medical Research (CAMR), BLDE (Deemed to be University), Vijayapur, Karnataka, India. Dr. Das did his M.S. and Ph.D. in Human Physiology from the University of Calcutta, Kolkata. His area of research is focused on understanding of molecular mechanisms of heavy metal activated low oxygen sensing pathways in vascular pathophysiology. He has invented a new method of estimation of serum vitamin E. His expertise in critical experimental protocols on vascular functions in experimental animals was well documented by his quality of publications. He was a Visiting Professor of Medicine at University of Leeds, United Kingdom (2014-2016) and Tulane University, New Orleans, USA (2017). For his immense contribution in medical research Ministry of Science and Technology, Government of India conferred him 'G.P. Chatterjee Memorial Research Prize-2019” and he is also the recipient of 'Dr.Raja Ramanna State Scientist Award 2015” by Government of Karnataka. He is a Fellow of the Royal Society of Biology (FRSB), London and Honorary Fellow of Karnataka Science and Technology Academy, Department of Science and Technology, Government of Karnataka.",institutionString:"BLDE (Deemed to be University), India",institution:null},{id:"243660",title:"Dr.",name:"Mallanagouda Shivanagouda",middleName:null,surname:"Biradar",slug:"mallanagouda-shivanagouda-biradar",fullName:"Mallanagouda Shivanagouda Biradar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243660/images/system/243660.jpeg",biography:"M. S. Biradar is Vice Chancellor and Professor of Medicine of\nBLDE (Deemed to be University), Vijayapura, Karnataka, India.\nHe obtained his MD with a gold medal in General Medicine and\nhas devoted himself to medical teaching, research, and administrations. He has also immensely contributed to medical research\non vascular medicine, which is reflected by his numerous publications including books and book chapters. Professor Biradar was\nalso Visiting Professor at Tulane University School of Medicine, New Orleans, USA.",institutionString:"BLDE (Deemed to be University)",institution:{name:"BLDE University",country:{name:"India"}}},{id:"289796",title:"Dr.",name:"Swastika",middleName:null,surname:"Das",slug:"swastika-das",fullName:"Swastika Das",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/289796/images/system/289796.jpeg",biography:"Swastika N. Das is Professor of Chemistry at the V. P. Dr. P. G.\nHalakatti College of Engineering and Technology, BLDE (Deemed\nto be University), Vijayapura, Karnataka, India. She obtained an\nMSc, MPhil, and PhD in Chemistry from Sambalpur University,\nOdisha, India. Her areas of research interest are medicinal chemistry, chemical kinetics, and free radical chemistry. She is a member\nof the investigators who invented a new modified method of estimation of serum vitamin E. She has authored numerous publications including book\nchapters and is a mentor of doctoral curriculum at her university.",institutionString:"BLDEA’s V.P.Dr.P.G.Halakatti College of Engineering & Technology",institution:{name:"BLDE University",country:{name:"India"}}},{id:"248459",title:"Dr.",name:"Akikazu",middleName:null,surname:"Takada",slug:"akikazu-takada",fullName:"Akikazu Takada",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/248459/images/system/248459.png",biography:"Akikazu Takada was born in Japan, 1935. After graduation from\nKeio University School of Medicine and finishing his post-graduate studies, he worked at Roswell Park Memorial Institute NY,\nUSA. He then took a professorship at Hamamatsu University\nSchool of Medicine. In thrombosis studies, he found the SK\npotentiator that enhances plasminogen activation by streptokinase. He is very much interested in simultaneous measurements\nof fatty acids, amino acids, and tryptophan degradation products. By using fatty\nacid analyses, he indicated that plasma levels of trans-fatty acids of old men were\nfar higher in the US than Japanese men. . He also showed that eicosapentaenoic acid\n(EPA) and docosahexaenoic acid (DHA) levels are higher, and arachidonic acid\nlevels are lower in Japanese than US people. By using simultaneous LC/MS analyses\nof plasma levels of tryptophan metabolites, he recently found that plasma levels of\nserotonin, kynurenine, or 5-HIAA were higher in patients of mono- and bipolar\ndepression, which are significantly different from observations reported before. In\nview of recent reports that plasma tryptophan metabolites are mainly produced by\nmicrobiota. He is now working on the relationships between microbiota and depression or autism.",institutionString:"Hamamatsu University School of Medicine",institution:{name:"Hamamatsu University School of Medicine",country:{name:"Japan"}}},{id:"137240",title:"Prof.",name:"Mohammed",middleName:null,surname:"Khalid",slug:"mohammed-khalid",fullName:"Mohammed Khalid",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/137240/images/system/137240.png",biography:"Mohammed Khalid received his B.S. degree in chemistry in 2000 and Ph.D. degree in physical chemistry in 2007 from the University of Khartoum, Sudan. He moved to School of Chemistry, Faculty of Science, University of Sydney, Australia in 2009 and joined Dr. Ron Clarke as a postdoctoral fellow where he worked on the interaction of ATP with the phosphoenzyme of the Na+/K+-ATPase and dual mechanisms of allosteric acceleration of the Na+/K+-ATPase by ATP; then he went back to Department of Chemistry, University of Khartoum as an assistant professor, and in 2014 he was promoted as an associate professor. In 2011, he joined the staff of Department of Chemistry at Taif University, Saudi Arabia, where he is currently an assistant professor. His research interests include the following: P-Type ATPase enzyme kinetics and mechanisms, kinetics and mechanisms of redox reactions, autocatalytic reactions, computational enzyme kinetics, allosteric acceleration of P-type ATPases by ATP, exploring of allosteric sites of ATPases, and interaction of ATP with ATPases located in cell membranes.",institutionString:"Taif University",institution:{name:"Taif University",country:{name:"Saudi Arabia"}}},{id:"63810",title:"Prof.",name:"Jorge",middleName:null,surname:"Morales-Montor",slug:"jorge-morales-montor",fullName:"Jorge Morales-Montor",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/63810/images/system/63810.png",biography:"Dr. Jorge Morales-Montor was recognized with the Lola and Igo Flisser PUIS Award for best graduate thesis at the national level in the field of parasitology. He received a fellowship from the Fogarty Foundation to perform postdoctoral research stay at the University of Georgia. He has 153 journal articles to his credit. He has also edited several books and published more than fifty-five book chapters. He is a member of the Mexican Academy of Sciences, Latin American Academy of Sciences, and the National Academy of Medicine. He has received more than thirty-five awards and has supervised numerous bachelor’s, master’s, and Ph.D. students. Dr. Morales-Montor is the past president of the Mexican Society of Parasitology.",institutionString:"National Autonomous University of Mexico",institution:{name:"National Autonomous University of Mexico",country:{name:"Mexico"}}},{id:"217215",title:"Dr.",name:"Palash",middleName:null,surname:"Mandal",slug:"palash-mandal",fullName:"Palash Mandal",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217215/images/system/217215.jpeg",biography:null,institutionString:"Charusat University",institution:null},{id:"49739",title:"Dr.",name:"Leszek",middleName:null,surname:"Szablewski",slug:"leszek-szablewski",fullName:"Leszek Szablewski",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49739/images/system/49739.jpg",biography:"Leszek Szablewski is a professor of medical sciences. He received his M.S. in the Faculty of Biology from the University of Warsaw and his PhD degree from the Institute of Experimental Biology Polish Academy of Sciences. He habilitated in the Medical University of Warsaw, and he obtained his degree of Professor from the President of Poland. Professor Szablewski is the Head of Chair and Department of General Biology and Parasitology, Medical University of Warsaw. Professor Szablewski has published over 80 peer-reviewed papers in journals such as Journal of Alzheimer’s Disease, Biochim. Biophys. Acta Reviews of Cancer, Biol. Chem., J. Biomed. Sci., and Diabetes/Metabol. Res. Rev, Endocrine. He is the author of two books and four book chapters. He has edited four books, written 15 scripts for students, is the ad hoc reviewer of over 30 peer-reviewed journals, and editorial member of peer-reviewed journals. Prof. Szablewski’s research focuses on cell physiology, genetics, and pathophysiology. He works on the damage caused by lack of glucose homeostasis and changes in the expression and/or function of glucose transporters due to various diseases. He has given lectures, seminars, and exercises for students at the Medical University.",institutionString:"Medical University of Warsaw",institution:{name:"Medical University of Warsaw",country:{name:"Poland"}}},{id:"173123",title:"Dr.",name:"Maitham",middleName:null,surname:"Khajah",slug:"maitham-khajah",fullName:"Maitham Khajah",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/173123/images/system/173123.jpeg",biography:"Dr. Maitham A. Khajah received his degree in Pharmacy from Faculty of Pharmacy, Kuwait University, in 2003 and obtained his PhD degree in December 2009 from the University of Calgary, Canada (Gastrointestinal Science and Immunology). Since January 2010 he has been assistant professor in Kuwait University, Faculty of Pharmacy, Department of Pharmacology and Therapeutics. His research interest are molecular targets for the treatment of inflammatory bowel disease (IBD) and the mechanisms responsible for immune cell chemotaxis. He cosupervised many students for the MSc Molecular Biology Program, College of Graduate Studies, Kuwait University. Ever since joining Kuwait University in 2010, he got various grants as PI and Co-I. He was awarded the Best Young Researcher Award by Kuwait University, Research Sector, for the Year 2013–2014. He was a member in the organizing committee for three conferences organized by Kuwait University, Faculty of Pharmacy, as cochair and a member in the scientific committee (the 3rd, 4th, and 5th Kuwait International Pharmacy Conference).",institutionString:"Kuwait University",institution:{name:"Kuwait University",country:{name:"Kuwait"}}},{id:"195136",title:"Dr.",name:"Aya",middleName:null,surname:"Adel",slug:"aya-adel",fullName:"Aya Adel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/195136/images/system/195136.jpg",biography:"Dr. Adel works as an Assistant Lecturer in the unit of Phoniatrics, Department of Otolaryngology, Ain Shams University in Cairo, Egypt. Dr. Adel is especially interested in joint attention and its impairment in autism spectrum disorder",institutionString:"Ain Shams University",institution:{name:"Ain Shams University",country:{name:"Egypt"}}},{id:"94911",title:"Dr.",name:"Boulenouar",middleName:null,surname:"Mesraoua",slug:"boulenouar-mesraoua",fullName:"Boulenouar Mesraoua",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94911/images/system/94911.png",biography:"Dr Boulenouar Mesraoua is the Associate Professor of Clinical Neurology at Weill Cornell Medical College-Qatar and a Consultant Neurologist at Hamad Medical Corporation at the Neuroscience Department; He graduated as a Medical Doctor from the University of Oran, Algeria; he then moved to Belgium, the City of Liege, for a Residency in Internal Medicine and Neurology at Liege University; after getting the Belgian Board of Neurology (with high marks), he went to the National Hospital for Nervous Diseases, Queen Square, London, United Kingdom for a fellowship in Clinical Neurophysiology, under Pr Willison ; Dr Mesraoua had also further training in Epilepsy and Continuous EEG Monitoring for two years (from 2001-2003) in the Neurophysiology department of Zurich University, Switzerland, under late Pr Hans Gregor Wieser ,an internationally known epileptologist expert. \n\nDr B. Mesraoua is the Director of the Neurology Fellowship Program at the Neurology Section and an active member of the newly created Comprehensive Epilepsy Program at Hamad General Hospital, Doha, Qatar; he is also Assistant Director of the Residency Program at the Qatar Medical School. \nDr B. Mesraoua's main interests are Epilepsy, Multiple Sclerosis, and Clinical Neurology; He is the Chairman and the Organizer of the well known Qatar Epilepsy Symposium, he is running yearly for the past 14 years and which is considered a landmark in the Gulf region; He has also started last year , together with other epileptologists from Qatar, the region and elsewhere, a yearly International Epilepsy School Course, which was attended by many neurologists from the Area.\n\nInternationally, Dr Mesraoua is an active and elected member of the Commission on Eastern Mediterranean Region (EMR ) , a regional branch of the International League Against Epilepsy (ILAE), where he represents the Middle East and North Africa(MENA ) and where he holds the position of chief of the Epilepsy Epidemiology Section; Dr Mesraoua is a member of the American Academy of Neurology, the Europeen Academy of Neurology and the American Epilepsy Society.\n\nDr Mesraoua's main objectives are to encourage frequent gathering of the epileptologists/neurologists from the MENA region and the rest of the world, promote Epilepsy Teaching in the MENA Region, and encourage multicenter studies involving neurologists and epileptologists in the MENA region, particularly epilepsy epidemiological studies. \n\nDr. Mesraoua is the recipient of two research Grants, as the Lead Principal Investigator (750.000 USD and 250.000 USD) from the Qatar National Research Fund (QNRF) and the Hamad Hospital Internal Research Grant (IRGC), on the following topics : “Continuous EEG Monitoring in the ICU “ and on “Alpha-lactoalbumin , proof of concept in the treatment of epilepsy” .Dr Mesraoua is a reviewer for the journal \"seizures\" (Europeen Epilepsy Journal ) as well as dove journals ; Dr Mesraoua is the author and co-author of many peer reviewed publications and four book chapters in the field of Epilepsy and Clinical Neurology",institutionString:"Weill Cornell Medical College in Qatar",institution:{name:"Weill Cornell Medical College in Qatar",country:{name:"Qatar"}}},{id:"282429",title:"Prof.",name:"Covanis",middleName:null,surname:"Athanasios",slug:"covanis-athanasios",fullName:"Covanis Athanasios",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/282429/images/system/282429.jpg",biography:null,institutionString:"Neurology-Neurophysiology Department of the Children Hospital Agia Sophia",institution:null},{id:"190980",title:"Prof.",name:"Marwa",middleName:null,surname:"Mahmoud Saleh",slug:"marwa-mahmoud-saleh",fullName:"Marwa Mahmoud Saleh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/190980/images/system/190980.jpg",biography:"Professor Marwa Mahmoud Saleh is a doctor of medicine and currently works in the unit of Phoniatrics, Department of Otolaryngology, Ain Shams University in Cairo, Egypt. She got her doctoral degree in 1991 and her doctoral thesis was accomplished in the University of Iowa, United States. Her publications covered a multitude of topics as videokymography, cochlear implants, stuttering, and dysphagia. She has lectured Egyptian phonology for many years. Her recent research interest is joint attention in autism.",institutionString:"Ain Shams University",institution:{name:"Ain Shams University",country:{name:"Egypt"}}},{id:"259190",title:"Dr.",name:"Syed Ali Raza",middleName:null,surname:"Naqvi",slug:"syed-ali-raza-naqvi",fullName:"Syed Ali Raza Naqvi",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259190/images/system/259190.png",biography:"Dr. Naqvi is a radioanalytical chemist and is working as an associate professor of analytical chemistry in the Department of Chemistry, Government College University, Faisalabad, Pakistan. Advance separation techniques, nuclear analytical techniques and radiopharmaceutical analysis are the main courses that he is teaching to graduate and post-graduate students. In the research area, he is focusing on the development of organic- and biomolecule-based radiopharmaceuticals for diagnosis and therapy of infectious and cancerous diseases. Under the supervision of Dr. Naqvi, three students have completed their Ph.D. degrees and 41 students have completed their MS degrees. He has completed three research projects and is currently working on 2 projects entitled “Radiolabeling of fluoroquinolone derivatives for the diagnosis of deep-seated bacterial infections” and “Radiolabeled minigastrin peptides for diagnosis and therapy of NETs”. He has published about 100 research articles in international reputed journals and 7 book chapters. Pakistan Institute of Nuclear Science & Technology (PINSTECH) Islamabad, Punjab Institute of Nuclear Medicine (PINM), Faisalabad and Institute of Nuclear Medicine and Radiology (INOR) Abbottabad are the main collaborating institutes.",institutionString:"Government College University",institution:{name:"Government College University, Faisalabad",country:{name:"Pakistan"}}},{id:"58390",title:"Dr.",name:"Gyula",middleName:null,surname:"Mozsik",slug:"gyula-mozsik",fullName:"Gyula Mozsik",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/58390/images/system/58390.png",biography:"Gyula Mózsik MD, Ph.D., ScD (med), is an emeritus professor of Medicine at the First Department of Medicine, Univesity of Pécs, Hungary. He was head of this department from 1993 to 2003. His specializations are medicine, gastroenterology, clinical pharmacology, clinical nutrition, and dietetics. His research fields are biochemical pharmacological examinations in the human gastrointestinal (GI) mucosa, mechanisms of retinoids, drugs, capsaicin-sensitive afferent nerves, and innovative pharmacological, pharmaceutical, and nutritional (dietary) research in humans. He has published about 360 peer-reviewed papers, 197 book chapters, 692 abstracts, 19 monographs, and has edited 37 books. He has given about 1120 regular and review lectures. He has organized thirty-eight national and international congresses and symposia. He is the founder of the International Conference on Ulcer Research (ICUR); International Union of Pharmacology, Gastrointestinal Section (IUPHAR-GI); Brain-Gut Society symposiums, and gastrointestinal cytoprotective symposiums. He received the Andre Robert Award from IUPHAR-GI in 2014. Fifteen of his students have been appointed as full professors in Egypt, Cuba, and Hungary.",institutionString:"University of Pécs",institution:{name:"University of Pecs",country:{name:"Hungary"}}},{id:"277367",title:"M.Sc.",name:"Daniel",middleName:"Martin",surname:"Márquez López",slug:"daniel-marquez-lopez",fullName:"Daniel Márquez López",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/277367/images/7909_n.jpg",biography:"Msc Daniel Martin Márquez López has a bachelor degree in Industrial Chemical Engineering, a Master of science degree in the same área and he is a PhD candidate for the Instituto Politécnico Nacional. His Works are realted to the Green chemistry field, biolubricants, biodiesel, transesterification reactions for biodiesel production and the manipulation of oils for therapeutic purposes.",institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"196544",title:"Prof.",name:"Angel",middleName:null,surname:"Catala",slug:"angel-catala",fullName:"Angel Catala",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/196544/images/system/196544.jpg",biography:"Angel Catalá studied chemistry at Universidad Nacional de La Plata, Argentina, where he received a Ph.D. in Chemistry (Biological Branch) in 1965. From 1964 to 1974, he worked as an Assistant in Biochemistry at the School of Medicine at the same university. From 1974 to 1976, he was a fellow of the National Institutes of Health (NIH) at the University of Connecticut, Health Center, USA. From 1985 to 2004, he served as a Full Professor of Biochemistry at the Universidad Nacional de La Plata. He is a member of the National Research Council (CONICET), Argentina, and the Argentine Society for Biochemistry and Molecular Biology (SAIB). His laboratory has been interested for many years in the lipid peroxidation of biological membranes from various tissues and different species. Dr. Catalá has directed twelve doctoral theses, published more than 100 papers in peer-reviewed journals, several chapters in books, and edited twelve books. He received awards at the 40th International Conference Biochemistry of Lipids 1999 in Dijon, France. He is the winner of the Bimbo Pan-American Nutrition, Food Science and Technology Award 2006 and 2012, South America, Human Nutrition, Professional Category. In 2006, he won the Bernardo Houssay award in pharmacology, in recognition of his meritorious works of research. Dr. Catalá belongs to the editorial board of several journals including Journal of Lipids; International Review of Biophysical Chemistry; Frontiers in Membrane Physiology and Biophysics; World Journal of Experimental Medicine and Biochemistry Research International; World Journal of Biological Chemistry, Diabetes, and the Pancreas; International Journal of Chronic Diseases & Therapy; and International Journal of Nutrition. He is the co-editor of The Open Biology Journal and associate editor for Oxidative Medicine and Cellular Longevity.",institutionString:"Universidad Nacional de La Plata",institution:{name:"National University of La Plata",country:{name:"Argentina"}}},{id:"186585",title:"Dr.",name:"Francisco Javier",middleName:null,surname:"Martin-Romero",slug:"francisco-javier-martin-romero",fullName:"Francisco Javier Martin-Romero",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSB3HQAW/Profile_Picture_1631258137641",biography:"Francisco Javier Martín-Romero (Javier) is a Professor of Biochemistry and Molecular Biology at the University of Extremadura, Spain. He is also a group leader at the Biomarkers Institute of Molecular Pathology. Javier received his Ph.D. in 1998 in Biochemistry and Biophysics. At the National Cancer Institute (National Institute of Health, Bethesda, MD) he worked as a research associate on the molecular biology of selenium and its role in health and disease. After postdoctoral collaborations with Carlos Gutierrez-Merino (University of Extremadura, Spain) and Dario Alessi (University of Dundee, UK), he established his own laboratory in 2008. The interest of Javier's lab is the study of cell signaling with a special focus on Ca2+ signaling, and how Ca2+ transport modulates the cytoskeleton, migration, differentiation, cell death, etc. He is especially interested in the study of Ca2+ channels, and the role of STIM1 in the initiation of pathological events.",institutionString:null,institution:{name:"University of Extremadura",country:{name:"Spain"}}},{id:"217323",title:"Prof.",name:"Guang-Jer",middleName:null,surname:"Wu",slug:"guang-jer-wu",fullName:"Guang-Jer Wu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217323/images/8027_n.jpg",biography:null,institutionString:null,institution:null},{id:"148546",title:"Dr.",name:"Norma Francenia",middleName:null,surname:"Santos-Sánchez",slug:"norma-francenia-santos-sanchez",fullName:"Norma Francenia Santos-Sánchez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/148546/images/4640_n.jpg",biography:null,institutionString:null,institution:null},{id:"272889",title:"Dr.",name:"Narendra",middleName:null,surname:"Maddu",slug:"narendra-maddu",fullName:"Narendra Maddu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/272889/images/10758_n.jpg",biography:null,institutionString:null,institution:null},{id:"242491",title:"Prof.",name:"Angelica",middleName:null,surname:"Rueda",slug:"angelica-rueda",fullName:"Angelica Rueda",position:"Investigador Cinvestav 3B",profilePictureURL:"https://mts.intechopen.com/storage/users/242491/images/6765_n.jpg",biography:null,institutionString:null,institution:null},{id:"88631",title:"Dr.",name:"Ivan",middleName:null,surname:"Petyaev",slug:"ivan-petyaev",fullName:"Ivan Petyaev",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Lycotec (United Kingdom)",country:{name:"United Kingdom"}}},{id:"423869",title:"Ms.",name:"Smita",middleName:null,surname:"Rai",slug:"smita-rai",fullName:"Smita Rai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Integral University",country:{name:"India"}}},{id:"424024",title:"Prof.",name:"Swati",middleName:null,surname:"Sharma",slug:"swati-sharma",fullName:"Swati Sharma",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Integral University",country:{name:"India"}}},{id:"439112",title:"MSc.",name:"Touseef",middleName:null,surname:"Fatima",slug:"touseef-fatima",fullName:"Touseef Fatima",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Integral University",country:{name:"India"}}},{id:"424836",title:"Dr.",name:"Orsolya",middleName:null,surname:"Borsai",slug:"orsolya-borsai",fullName:"Orsolya Borsai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca",country:{name:"Romania"}}},{id:"422262",title:"Ph.D.",name:"Paola Andrea",middleName:null,surname:"Palmeros-Suárez",slug:"paola-andrea-palmeros-suarez",fullName:"Paola Andrea Palmeros-Suárez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Guadalajara",country:{name:"Mexico"}}}]}},subseries:{item:{id:"27",type:"subseries",title:"Multi-Agent Systems",keywords:"Collaborative Intelligence, Learning, Distributed Control System, Swarm Robotics, Decision Science, Software Engineering",scope:"Multi-agent systems are recognised as a state of the art field in Artificial Intelligence studies, which is popular due to the usefulness in facilitation capabilities to handle real-world problem-solving in a distributed fashion. The area covers many techniques that offer solutions to emerging problems in robotics and enterprise-level software systems. Collaborative intelligence is highly and effectively achieved with multi-agent systems. Areas of application include swarms of robots, flocks of UAVs, collaborative software management. Given the level of technological enhancements, the popularity of machine learning in use has opened a new chapter in multi-agent studies alongside the practical challenges and long-lasting collaboration issues in the field. It has increased the urgency and the need for further studies in this field. We welcome chapters presenting research on the many applications of multi-agent studies including, but not limited to, the following key areas: machine learning for multi-agent systems; modeling swarms robots and flocks of UAVs with multi-agent systems; decision science and multi-agent systems; software engineering for and with multi-agent systems; tools and technologies of multi-agent systems.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/27.jpg",hasOnlineFirst:!1,hasPublishedBooks:!1,annualVolume:11423,editor:{id:"148497",title:"Dr.",name:"Mehmet",middleName:"Emin",surname:"Aydin",slug:"mehmet-aydin",fullName:"Mehmet Aydin",profilePictureURL:"https://mts.intechopen.com/storage/users/148497/images/system/148497.jpg",biography:"Dr. Mehmet Emin Aydin is a Senior Lecturer with the Department of Computer Science and Creative Technology, the University of the West of England, Bristol, UK. His research interests include swarm intelligence, parallel and distributed metaheuristics, machine learning, intelligent agents and multi-agent systems, resource planning, scheduling and optimization, combinatorial optimization. Dr. Aydin is currently a Fellow of Higher Education Academy, UK, a member of EPSRC College, a senior member of IEEE and a senior member of ACM. In addition to being a member of advisory committees of many international conferences, he is an Editorial Board Member of various peer-reviewed international journals. He has served as guest editor for a number of special issues of peer-reviewed international journals.",institutionString:null,institution:{name:"University of the West of England",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null,series:{id:"14",title:"Artificial Intelligence",doi:"10.5772/intechopen.79920",issn:"2633-1403"},editorialBoard:[{id:"275140",title:"Dr.",name:"Dinh Hoa",middleName:null,surname:"Nguyen",slug:"dinh-hoa-nguyen",fullName:"Dinh Hoa Nguyen",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRbnKQAS/Profile_Picture_1622204093453",institutionString:null,institution:{name:"Kyushu University",institutionURL:null,country:{name:"Japan"}}},{id:"20259",title:"Dr.",name:"Hongbin",middleName:null,surname:"Ma",slug:"hongbin-ma",fullName:"Hongbin Ma",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRhDJQA0/Profile_Picture_2022-05-02T08:25:21.jpg",institutionString:null,institution:{name:"Beijing Institute of Technology",institutionURL:null,country:{name:"China"}}},{id:"28640",title:"Prof.",name:"Yasushi",middleName:null,surname:"Kambayashi",slug:"yasushi-kambayashi",fullName:"Yasushi Kambayashi",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYOQxQAO/Profile_Picture_1625660525470",institutionString:null,institution:{name:"Nippon Institute of Technology",institutionURL:null,country:{name:"Japan"}}}]},onlineFirstChapters:{paginationCount:17,paginationItems:[{id:"81647",title:"Diabetes and Epigenetics",doi:"10.5772/intechopen.104653",signatures:"Rasha A. 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