Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 179 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\n
Throughout the years, the list has named a total of 252 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
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1. Introduction
Helically segmented finned tubes are used in compact heat recoveries in order to save energy in industrial applications. These equipments are small because the gas phase turbulence and the heat transfer surface are increased by the presence of fins; both are relevant in heat transfer. However, the gas phase pressure drop is elevated and consequently, operational problems such as backpressure can emerge. Therefore, a study focusing on finned tubes is important in order to understand the fluid dynamics and heat transfer phenomena. There are two main methods for the analysis; the first uses integral analysis (gross effects) and the second uses Computational Fluid Dynamics (CFD) techniques. Integral analyses allow a quick evaluation of thermo-physical phenomena with minimum computational infrastructure but only gross effects can be examined. These analyses are primarily used in the design of equipment because only inlet and outlet fluid properties are important. The CFD technique requires good computational support and long calculation times, but it provides complete and detailed information on the intricate thermo-physical phenomena. This modern analysis requires a correct implementation of boundary conditions in order to adequately represent the flow hydrodynamics and heat transfer phenomena.
The implementation of boundary conditions is relevant in differential analyses because predictions depend from it. The differential analyses can be developed by means of analytical solutions or by means of numerical methods. In the case of helically segmented finned tube bank analyses, the analytical solutions are not possible because the geometry is complex. Then, a numerical simulation of helically segmented finned tube bank is the best option. The numerical simulations can be carried out by means of three different CFD alternatives such as Direct Numerical Simulation (DNS), Large Eddy Simulation (LES), and Reynolds Average Navier-Stokes Equations (RANS). The DNS technique is limited to low Reynolds flows with simple configurations. The LES technique is less demanding than the DNS, but it takes considerable computing resources and computing time because the required calculations are always three-dimensional and unsteady. Finally, the RANS technique, which is widely used in industrial applications, considers average spatial and temporal scales of turbulent fluctuations and solves the transport equations as a function of these average variables. However, these equations are not closed and additional models (turbulence models) are indispensable to close the system. So, the numerical analysis on helically segmented finned tube bank (complex geometry) is proposed with the RANS technique.
In the open literature there are several papers have been focused on numerical analysis of small finned tube banks, the majority of them are restricted to numerical simulations on bare tube layout (symmetric tube layout). For example, Beale and Spalding [1], Comini and Croce [2] and Beale [3, 4] have performed simulations on laminar flow regimes exclusively. Other authors like Benhamadouche and Laurennce [5] and Salinas-Vazquez et al. [6] have conducted studies on turbulent flow regimes. These simulations have analyzed symmetric tube layout with periodic boundary conditions. On the other hand, there are few numerical simulations focused on helically segmented finned tubes (asymmetric finned tubes). The papers are focused on laminar flows with Dirichlet boundary conditions. For example, Hofmann [7] and Mcilwain [8, 9] conducted two-dimensional simulations on a single helically segmented finned tube. Afterwards, Lemouedda et al. [10] developed a three-dimensional numerical simulation in a small finned tube bank. There are no reports of numerical simulations of asymmetric finned tube layout (helically segmented finned tube bank) under periodic boundary conditions and the effect of inside fluid temperature has not been considered. Therefore, a methodology to calculate flow properties in different zones of finned tube bank is required in order to implement boundary conditions on a single isolated finned tube module. This methodology considers calculations in entire and partial finned tube layout and it is applied to calculate boundary conditions in a numerical simulation. Then, a compact heat recovery in staggered layout is represented as some single isolated finned tube modules in order to save computational resources. The single isolated finned tube module is simulated and predictions are compared with results from correlations available in the open literature.
2. Methodology
The differential analysis of compact heat recoveries with CFD techniques requires high calculation times because a full finned tube bank needs to be simulated. The dimensions of computational domain are high due to size of finned tubes and number of finned tubes used in the equipment. So, the necessity to reduce calculation times is relevant in numerical simulations because these times can be excessively-high. The only way to reduce calculation times is by reduction of computational domain but it requires a correct implementation of boundary conditions for representing adequately physical phenomena. A complete finned tube bank can be represented by a single isolated finned tube module in the fully developed flow region as shown in figure 1. The single isolated finned tube module consists of an arrangement of entire and partial finned tubes. This finned tube layout can allow a computational domain reduction of 99% but requires values of boundary conditions in intermediate regions of finned tube bank. The values of boundary conditions for velocity, pressure, and temperature should be calculated for entire and partial finned tubes in intermediate regions of finned tube bank. Then, a method to calculate those boundary conditions must be developed in order to represent the finned tube bank as a single isolated finned tube module (figure 1). This methodology is based on integral models which have been validated experimentally [22] with precision higher than 90% for pressure and 95% for temperature. So, a numerical simulation of single isolated finned tube module in the fully developed flow with periodic boundary conditions is done. Numerical predictions are compared with results obtained from best correlations available in the open literature, which are presented in section 2.2. So, the mean pressure drop, mean temperature difference, mean Nusselt number and mean friction factor are compared.
Figure 1.
Finned tube bank in staggered layout.
2.1. Finned tube bank analysis
The complete finned tube bank may be represented as a single isolated fined tube module in the fully developed flow as shown in figure 1. This finned tube layout requires values for velocity, pressure, and temperature in intermediate regions of finned tube layout for both outside and inside flows. These values are obtained by means of an integral analysis, which considers the Logarithmic Mean Temperature Difference method (LMTD). However, this method only can be applied for entire finned tubes in arrangement of two or more finned tube rows and two or more finned tubes per row. Then, the complete finned tube bank and the single isolated finned tube module should be analyzed in order to apply LMTD method, which is described in section 2.2. The finned tube bank can be divided in single isolated finned tube modules as shown in figure 2a. In this figure, a full finned tube bank (6 finned tube rows with 4 finned tubes per row) is composed by 12 single isolated finned tube modules (black and red boxes). Every finned tube module contains 2 finned tubes because there are one entire finned tube and 4 quarters of finned tube. Then, two single isolated finned tube modules like (red boxes) can be represented as an equivalent small finned tube bank (blue box) as shown in figure 2b. Therefore, the finned tube bank showed in figure 1 is represented as a single isolated finned tube modules arrangement as presented in figure 2a.
Figure 2b shows a small finned tube bank (blue box) composed of 2 finned tubes per row and 2 rows of finned tubes, which is arranged in order to obtain 2 single isolated finned tube modules (red box). Then, the analysis of single isolated finned tube modules must consider minimum arrangements of 2 finned tubes per row and 2 rows of finned tubes. This consideration does not affect predictions of friction factor and Nusselt number because these dimensionless parameters are not function of number of finned tubes involved in the arrangement if mass flow is corrected to the new finned tube layout, which is demonstrated in the sensitive analysis (section 4.1). So, models for evaluating heat transfer and pressure drop can be applied to the equivalent small finned tube bank (figure 2b). The pressure drop depends mainly of flow hydrodynamics, which shows similar velocity fields for every single isolated finned tube module as is discussed in results analysis (section 4.2). Therefore, the models for evaluating pressure drop can be applied directly in the equivalence small finned tube bank (figure 2b). However, the pressure drop cannot be considered as a boundary condition because only represents the pressure difference at the inlet and exit of single isolated finned tube modules. The pressure in the boundaries of single isolated finned tube module is obtained with the analysis of finned tube bank from figure 1. In this figure, the single isolated finned tube in the fully developed region (red box) is located near to the exit of module. This finned tube module has to the right a part of finned tube module (blue box) while at left has one and a part finned tube module (green box). In the case of an atmospheric discharge of flow gases (zero relative pressure), which is correct because flue gases of compact heat recoveries cannot be used in additional industrial process, the relative pressure drop in the last part of single isolated finned tube module (blue box, figure 1) is calculated as an proportional arithmetic mean pressure drop to the part of this finned tube module. The proportional part of this module corresponds to a value of 0.75. Therefore, the relative pressure at the exit of the single isolated finned tube module in the fully developed flow (red box, figure 1) corresponds to the value calculated previously. Finally, the relative pressure at the inlet of the single isolated finned module (red box, figure 1) is calculated from the sum of the pressure drop in this finned tube module and the proportional part (0.25) of the left finned tube module (green box, figure 1).
Figure 2.
Single isolated finned tube modules in the finned tube bank.
The direct application of LMDT method for heat transfer in the equivalent small finned tube bank (blue box, figure 2b) is not recommended because the outside flow, in the single isolated finned tube module (red box, figure 2b), is cooled by tree different cooling sources (inside fluid temperature). While the equivalent small finned tube bank (blue box, figure 2) only has the influence of two cooling sources. One way to solve this problem is by means of temperature evaluation of outside flow for small finned tube layouts. The finned tube layouts considered have an initial arrangement of two finned tube rows, which are evaluated. Later, calculations over initial finned tube bank with additional finned tube rows are proposed (see section 2.3). This procedure is iterative because only initial conditions at the inlet of gas-phase flow and inside fluid in the complete finned tube bank (figure 1) are known. Once temperature evaluation for each finned tube layout is done, the inside fluid temperatures for each finned tube row are defined. The sensitivity analysis (section 4.1) of a finned tube bank shows that consideration applied for evaluating boundary conditions are satisfactory. These boundary conditions are employed in a numerical analysis of the finned tube bank showed in figure 1, which is described in section 2.3. Numerical predictions are compared with results from models for heat transfer and pressure drop in helically segmented finned tubes presented in section 2.2. The comparative analysis show close values between models and numerical results as discussed in results (section 4).
2.2. Logarithmic Mean Temperature Difference (LMTD) method
The methodology for calculating boundary conditions in the single isolated finned tube module is based on the Logarithmic Mean Temperature Difference method. This method allows the evaluation of heat transfer coefficients and friction factors for different geometries, according to models available in the open literature. These parameters permit the global evaluation of heat transfer and flow hydrodynamics of finned tube bank. The LMTD method considers the evaluation of overall heat transfer coefficient (U), which is based on the outside finned tube and is defined with the following equation:
where ho, hi, and hr are mean outside convective coefficient, mean inside convective coefficient, and radiation heat transfer coefficient, respectively. In the case of flue gas temperatures lower than 300ºC, the value of hr could be negligible [11], and so this value is considered zero. Rfo and Rfi, are the outside and inside fouling factors, respectively. ηf, Af, At, Ao, and Ai are fin efficiency, fin surface area, bare tube surface area, total surface area, and inside surface area, respectively. Finally, ew and kw are tube wall thickness and tube material thermal conductivity, respectively.
The mean convective coefficients are calculated for the inside and outside of finned tubes. The mean inside convective coefficient (hi) considered in the evaluation of U is the Gnielinski’s correlation [12]. This model has been validated with satisfactory results by Rane, et al. [13] and according to Bejan [14] is the best available in the open literature. The Gnielinski’s correlation [12] is valid for 0.5 ≤ Pr ≤ 2000 and 3000 ≤ Re ≤ 5x106, which is shown in the following equation:
where di and k are inside diameter of tube and thermal conductivity of fluid. Re and Pr are the Reynolds Number and Prandtl Number. Finally, fi is the friction factor, which is defined in the following equation:
fi=1(1.82log10Re−1.64)2E3
\n\t\t\t\t
There are many mean outside convective heat transfer coefficients (ho) in the open literature such as models proposed by Weierman [15], ESCOA [16], Nir [17], and Kawaguchi et al. [18]. The models attributable to Weierman [15] and Kawaguchi et al. [18] are recommended by Martinez et al. [19], but Kawaguchi´s et al. [18] model is adopted. The model of Kawaguchi, et al. [18] is valid for 7000 ≤ Rev ≤ 50000 and 0.112 ≤ sf/dv ≤ 0.198, which is shown in the next equation:
Nu=A2Rev0.784Pr1/3(sf/dv)−0.062=hodvkgE4
\n\t\t\t\t
where Rev is the Reynolds number based on the volume-equivalent diameter. The terms A2, sf, and dv are the experimental coefficients for tube rows, fin gap, and volume-equivalent diameter, respectively. The coefficient A2 is obtained from Kawaguchi´s, et al. [18] model. Finally, kg is the thermal conductivity of gases.
The volume-equivalent diameter, dv, is defined by the following equation:
dv=[tfnf{(do+2lf)2−do2}+do2]1/2E5
\n\t\t\t\t
where nf, tf, lf, and do are fin number per unit length, fin thickness, fin height, and outside diameter of bare tube, respectively.
Gas phase pressure drop can be calculated with models proposed by Weierman [15], ESCOA [16], Nir [17], and Kawaguchi et al. [18]. The model of Weierman [15] has been validated with satisfactory results by Martinez, et al. [19] and as a consequence, is adopted. In the analysis of compact heat recoveries a maximum pressure drop of 248.9 Pa [20] (1 inch (in) of water column (wc)) is considered in order to avoid technical problems such as backpressure. The pressure drop is calculated with the following empirical equation:
ΔPg=(fo+(1+B2)ρgp4Nr)Go2Nr1.083x109ρgpE6
\n\t\t\t\t
where B, Go, Nr, fo, and ρgp are the contraction factor, the gas mass flux, the number of tube rows, the friction factor, and the gas-phase density at the average outside temperature, respectively.
The gas phase friction factor (fo) is calculated with Weierman´s model [15], which is valid for tube diameters between 38.1-60.96 mm and mass velocity of the gas between 0.67-40.36 kg/m2s. The Weierman´s model [15] is shown in the following equation:
where Reo is the Reynolds number based on the outside bare and cp is the specific heat capacity at constant pressure. Also, df and do are the outside diameter of the finned tube and the outside diameter of the bare tube, respectively. The terms Sl and St indicate the longitudinal pitch and the transverse pitch, respectively.
For more details about thermal evaluation of helically segmented finned tube banks see reference [21].
2.3. Sensitive analysis of finned tube bank
The methodology is based on the equivalence of a finned tube bank with single isolated finned tubes modules layouts. This methodology, which is based on the LMTD method, requires that predictions of friction factor and Nusselt number be independent of finned tube layout and number of finned tubes involved in compact heat recoveries. Then, a sensitive analysis of the finned tube bank is required in order to validate considerations in the methodology. The sensitive analysis is done for a small heat recovery (figure 1), in which results of friction factor and Nusselt number are compared for different finned tube layouts and finned tube lengths. The geometric characteristics of helically segmented finned tube and finned tube layout are shown in figure 3. In this figure, a front and side views of the finned tube used in this study and its staggered configuration is presented. The finned tube bank analyzed corresponds to the layout shown in figure 1, which is composed by 4 finned tubes per row and 6 finned tube rows. The small heat recovery (figure 1) is analyzed with LMTD method for different finned tube configurations.
The finned tube configurations used in the sensitive analysis considers an initial finned tube layout of 2 finned tubes per row and 2 finned tubes rows (red polygon in figure 4). Subsequently, one finned tube row is added to reach 6 finned tube rows (red dash boxes in figure 4). Then, another finned tube is added to the row (blue polygon, figure 4) in order to obtain 3 finned tubes per row and 2 finned tube rows. Previous procedures in initial finned tube layout are done until 6 finned tube rows (blue dash boxes, figure 4) are reached. Finally, one last finned tube row is added (green polygon in figure 4) in order to get 4 finned tubes per row and 2 finned tube rows. The same procedure for previous finned tube layouts are done until full finned tube bank (gray dashed box) is reached. Once finned tube bank layout analysis is done, a similar study is proposed for different finned tube length. The procedure is the same as previous analysis but at different finned tube length. The finned tube lengths proposed are 1m, 0.5 m, and 0.05194 m. The last finned tube length corresponds to the value used in the numerical simulation. The results (section 4.1) show variations lower than 1% for Nusselt number and 3.6% lower for friction factor. These results confirm that considerations employed in this methodology (boundary condition calculation) are appropriate. The analysis is obtained with the thermodynamic conditions presented in table 1 for different finned tubes per row and finned tubes length which, shows deviations on Reynolds number based in the outside diameter tube (Reo) lower than 0.4%. The variations in Reo are due to adjustment of mass flow at different finned tube configurations.
Figure 3.
Geometric characteristics of finned tubes and finned tube layout.
Figure 4.
Finned tube layout configurations in sensitive analysis.
Finned tube length: 1 m
Finned tubes per row
Parameter
2
3
4
mass flow (kg/s)
0.3624
0.05436
0.7248
Reo
8562
8562
8562
Ma
< 0.03
< 0.03
< 0.03
Temperature (ºC)
60
60
60
Finned tube length: 0.5 m
Finned tubes per row
Parameter
2
3
4
mass flow (kg/s)
0.1812
0.2718
0.3624
Reo
8567
8567
8567
Ma
< 0.03
< 0.03
< 0.03
Temperature (ºC)
60
60
60
Finned tube length: 0.05194 m
Finned tubes per row
Parameter
2
3
4
mass flow (kg/s)
9.411x10-3
14.116x10-3
18.822x10-3
Reo
8599
8599
8599
Ma
< 0.03
< 0.03
< 0.03
Temperature (ºC)
60
60
60
Table 1.
Thermodynamic conditions.
3. Numerical simulation
In this section, the methodology for calculating boundary conditions in a single isolated finned tube module is employed in a numerical simulation of helically segmented finned tube bank in staggered layout. The objective is to apply the methodology in a numerical model that represents the interaction between the hydrodynamics and the heat transfer of a turbulent gas flow in complex systems. The simulation allows detailed analysis on compact heat recoveries that can be used for improving thermal behaviour. So, a correct implementation of boundary conditions in order to represent adequately physical phenomena is essential. The numerical model is focused to the outside finned tube, because the gas phase dominates the heat transfer [22] and also the pressure drop is critical [22]. However, the effect of the internal fluid is considered by means of an average inside temperature in each finned tube. Thus, the boundary conditions for outside flow and inside fluid are calculated with methodology described in section 2. In this numerical simulation, periodic boundary conditions are proposed for the single isolated finned tube module in the fully developed flow (Figure 1). Numerical predictions of Nusselt number and friction factor are compared with results obtained from correlations of Kawaguchi et al. [18] and Weierman [15], respectively in order to verify numerical results that depend on boundary conditions values.
3.1. Governing equations
The analysis of turbulent flows is complex, because fluid properties are irregular in space and time. Instantaneous variables (φ) are represented as a function of two terms: the mean (φ˜) and its fluctuation(φ″). These terms are used in the transport equations that govern the flow movement and the heat exchange. The transport equations are averaged by means of Favre [23] method, which are solved for mean values of the fluid properties. Thereby, the set of mass, momentum, and energy transport equations in Cartesian system is defined as follows:
whereρ¯, V→˜, V→″, and h˜ are the mean density, instantaneous velocity, fluctuating velocity, and mean enthalpy, respectively. µ and g→¯ are the viscosity and the gravitational acceleration, respectively. The terms ρ¯V→″V→″˜ and ρ¯V→″h″˜ are the apparent Reynolds stress tensor and the turbulent heat flux, respectively. P¯¯is the pressure tensor. Finally, ∇⋅J→˜his the diffusive heat flux, which is modeled with Fourier´s law.
Equations (2) and (3) demand additional mathematical expressions to model V″φ″˜ term. The closure of these equations requires modeling of Reynolds stress tensor and of the turbulent heat flux. Then, the Reynolds stress tensor is closed with turbulence models. In this work, the k-ε RNG (Renormalization Group) turbulence model developed by Yakhot and Orzag [24] is considered. The turbulent heat flux vector is obtained by means of an analogy between momentum transfer and thermal energy transfer. Under this concept, it is possible to establish a suitable articulation between the turbulent heat flux vector and the turbulent flow viscosity.
3.2. Boundary conditions
The implementation of periodic boundary conditions alleviates the computational resources, because the computational domain is reduced considerably. So, only a single isolated finned tube module in the fully developed flow region needs to be simulated (figure 1). Also, the tube length required (spatial direction y in figure 1) is minimum because only is necessary the length for the flow does not vary in this spatial direction because periodic conditions assume no influence of walls or position in any direction. Then, the computational domain is reduced 99%, as shown in table 2, because only is necessary the single isolated finned tube module (figure 1) with a tube length of 0.05194 m. However, the numerical simulation requires a correct inclusion of boundary conditions in order to adequately represent the physical phenomenon. So, the boundary conditions are applied to a turbulent air flow in a stationary and fully-developed flow regime. The methodology developed by Patankar et al. [25] and Kelkar and Patankar [26] is implemented in this work. This methodology was generated for laminar flows and as a consequence, only velocity, pressure and temperature are considered as a periodic behaviour. However, additional considerations for turbulent flows need to be implemented. These considerations should depend on the turbulence model selected.
The periodic velocity is based on the non slip condition on the boundary walls of the computational domain and negligible value of the velocity variation in every spatial direction. So, the analysis is presented for the flow direction (z), which can be generalized for the remaining spatial directions. Thereby, the periodic condition for the component velocity in the flow direction (w˜) is defined as follows:
∂w˜∂z=0u˜=0v˜=0E11
\n\t\t\t\t
where u˜,v˜,w˜ are the mean velocity components in the respective spatial directions x, y, z.
In the case of fully developed flows, the velocity is the same at a characteristic length (L), and this is shown in the next equation:
w˜(x,y,z)=w˜(x,y,z+L)E12
\n\t\t\t\t
The periodic boundary velocities need an initial value wb (bulk velocity), which is calculated with the following equation:
wb=1Ayz∫0x∫0ywmeddxdyE13
\n\t\t\t\t
where wmed is an initial velocity profile.
The pressure field is obtained from a periodic behavior taking into consideration a pressure drop in the flow direction. This implies that the pressure is defined by the sum of a periodic pressure term in the flow direction and an average pressure drop. This is represented in the following equation:
P(x,y,z)=P˜(x,y,z)−βzE14
\n\t\t\t\t
where P˜ and β are periodic pressure and average pressure-gradient in the flow direction.
Dimensions:
Layout
x (m)
y (m)
z (m)
cells
Finned tube bank
0.4572
1.0
0.59878
34200000
Single isolated finned tube module
0.1143
0.05194
0.20312
178512
Computational domain reduction:
Finned tube bank
reference
Single isolated finned tube module
99.6
Table 2.
Finned tube layout dimensions.
These two terms are defined in the pair of equations (15) and (16):
P˜(x,y,z)=P˜(x,y,z+L)E15
\n\t\t\t\t
β=P˜(x,y,z)−P˜(x,y,z+L)L=ΔP˜LE16
\n\t\t\t\t
where ΔP˜ is the pressure drop over a finned tubes module, which can be calculated through the empirical equation (6).
The temperature field is obtained with constant wall heat flux boundary condition, which considers a constant variation of temperature in the flow direction; that is, the heat transfer magnitude is the same from one finned tube module to another finned tube module. This boundary condition can be appropriate for the present study because it can be applied to turbulent flows. However, it is appropriate if a uniform heat transfer is found in the small finned tube bank simulation. The numerical results in small finned tube bank show a quasi-constant mean temperature (plane xy) in the flow direction as shown in results section.
The temperature field is obtained from a periodic behavior and an adjustment term of the temperature in the flow direction. Thus, the temperature is defined by a periodic temperature term in the flow direction and an average temperature adjustment term expressed in the next expression:
T(x,y,z)=T˜(x,y,z+L)+γzE17
\n\t\t\t\t
where T˜(x,y,z) and γ are the mean temperature field and the temperature-gradient term, respectively. The temperature-gradient term can be calculated with the following equation:
γ=T˜(x,y,z)−T˜(x,y,z+L)L=Q˙m˙gcpLE18
\n\t\t\t\t
whereQ˙, m˙, and cp are heat addition, mass flow, and specific heat at constant pressure, respectively.
The heat addition in the flow direction for the single isolated module is determined with the next equation:
Q˙=UoATΔTMLE19
\n\t\t\t\t
where Uo is the overall heat transfer coefficient, AT the overall finned surface and ΔTML the logarithmic mean temperature difference.
The value of Uo is obtained from equation (1) and AT is obtained with geometry of finned tube. For more details about calculations of these parameters see reference [21].
The numerical simulation of turbulent flow on a single isolated module needs the implementation of periodic conditions for additional variables, according to the turbulence model. In the case of k-ε RNG turbulence model, the turbulent kinetic energy (k) and its dissipation rate (ε) show a periodic behavior, according to Martínez [27]. So, the periodic condition for the turbulent kinetic energy and its dissipation rate are defined as follows:
k˜(x,y,z)=k˜(x,y,z+L)E20
\n\t\t\t\t
ε˜(x,y,z)=ε˜(x,y,z+L)E21
\n\t\t\t\t
The inclusion of periodic boundary conditions in the simulation of single isolated module requires light changes in the governing equations. The mass conservation equation does not change and is evaluated by means of equation (1). In the case of pressure field, the momentum conservation equation needs to include the adjust term of average pressure-gradient in the flow direction. So, the equation (2) can be written as:
The term β is included in the CFD code PHOENICS 3.5.1 [28] by means of an additional source term in the momentum equation. On the other hand, the evaluation of temperature field requires that energy conservation equation must be adjusted in order to include the cooling of gas phase in the flow direction. So, the equation (3) can be written as:
The term ∇⋅(V→˜γ) is included in the CFD code PHOENICS 3.5.1 [28] by means of an additional source term in the energy equation.
The turbulent kinetic energy and the dissipation turbulent rate are calculated directly from equations (20) and (21) because these equations do not change.
3.3. Numerical details
The numerical simulation is developed for a single isolated finned tube module in the fully developed flow, which is shown in Figure 5. In this figure, the single isolated finned tube module is presented with boundary conditions calculated with methodology proposed. The dimensions of computational domain and the mesh used for simulation are shown in table 2. This table exhibits a reduction in computational domain with single isolated finned tube module of 99% that represents finite calculation times. The used mesh in numerical simulation considers that numerical predictions are independent from it. The thermodynamic employed conditions in the simulation work are presented in table 1 for finned tube length of 0.05194 m and figure 5. On the other hand, the complex geometry is represented by cut-cell method [29], which allows the use of Cartesian grids. The numerical simulations consider a staggered grid under a hybrid discretization scheme of the convective term. It was also considered that the system is in a stationary state and is only exposed to one gravitational field (in heat recoveries, the fluid generally flows in vertical direction), and that the gas discharge (finned tube bank outlet) occurs in a sea level atmosphere. Finally, the geometric characteristics of the finned tube used in this study are shown concurrently in Figure 3.
The numerical results are used for evaluating average Nusselt Number (Nu) and average friction factor in small finned tube bank and single isolated module. The results are compared with values obtained from Correlations of Kawaguchi, et al [18] and Weierman [15] models, respectively.
The average Nusselt number is calculated with the next equation:
Nu¯=h¯dvkgE24
\n\t\t\t\t
where h¯ is the average convective coefficient, which is defined as:
h¯=Q˙AoΔTLMnumE25
\n\t\t\t\t
where ΔTLMnum is the numerical-logarithmic mean temperature difference, which is calculated as:
where Ti and Tb are the mean temperature inside finned tubes and mean boundary temperature, respectively. The conditions at z and z+L correspond to the inlet and exit of the single isolated finned tube module.
The numerical-average friction factor is obtained directly from equation (6) in which numerical pressure drop is calculated from the next expression:
ΔP˜=Pb(z)−Pb(z+L)E27
\n\t\t\t\t
where Pb is the numerical-mean pressure.
4. Results
The methodology proposed is applied for evaluating boundary conditions in a single isolated finned tube module (figure 1). The predicted values are utilized in a numerical simulation in order to verify a correct representation of physical phenomena with these boundary conditions. These values require independence of results in heat transfer (Nusselt number) and pressure drop (friction factor) for different finned tube configurations, number of finned tubes, and finned tube lengths. So, a sensitive analysis is necessary in order to support previous considerations. The results of sensitive analysis shows that assumptions of methodology are correct, which are discussed in section 4.1. On the other hand, numerical predictions (focused in the outside flow) show a correct representation of interaction of heat transfer and flow hydrodynamics, which is presented in section 4.2. The comparative analysis of results between numerical predictions and results obtained from Kawaguchi et al [18] and Weierman [15] models for Nusselt number and friction factor, respectively, show close values as discussed in section 4.2.
4.1. Sensitive analysis
The LMTD method is applied to different finned tube layouts and finned tube lengths, which are described in section 2.3. The main goal of the analysis is to verify that friction factor and Nusselt number are independent of finned tube rows, number of finned tube per row, and finned tube length for the finned tube bank showed in figure 1. The comparative analysis at different finned tube configurations and finned tube lengths with thermodynamic conditions presented in table 1 are shown in table 4. In this table, Nusselt number and friction factor are presented at different finned tube configurations from 2 finned tubes per row and 2 finned tubes rows (red polygon in figure 4) until reach 4 finned tubes per row and 6 finned tubes rows (gray dashed box, figure 4). Evaluations are done for tube lengths of 1 m, 0.5 m y 0.05194m as shown in table 3. Predictions show constant values of Nusselt number and friction factor for the same finned tube rows. So, the Nusselt number varies from 100.3 to 99.3 and the friction factor changes from 0.31 to 0.321 for different finned tube rows (2 to 6) of the small heat recovery. These results exhibit independence of predictions in dimensionless parameters with finned tube length and finned tubes per row in a heat recovery. The only variation of results is for configurations at different finned tube rows as shown in table 3. The main reason of dimensionless parameters variation is temperature reached by the gas phase (outside flow). These temperature variations slightly affect results because the gas phase is cooled in 3 ºC temperature difference for configurations analyzed at different finned tube rows. The results exhibit variations lower than 1% for Nusselt number and 3.6% for friction factor. These deviations are calculated for different finned tube rows, which is not representative of the same physical phenomenon because different finned tube layouts represent different gas cooling. In spite of this situation, the results show close values in Nusselt number and friction factor. Therefore, assumptions considered in the methodology are correct because finned tube bank performance is independent of finned tube rows, number of finned tubes per row, and finned tube length in a finned tube bank. This methodology allows numerical studies in heat recoveries at industrial scale because the computational domain can be reduced in 99% as shown in table 2. So, the calculation times are finites due to the analysis is focused in a single isolated finned tube module in the fully developed flow.
Finned tube length: 1 m
Finned tubes per row
2
3
4
Finned tube rows
Nu
f
Nu
f
Nu
f
2
99.3
0.321
99.3
0.321
99.3
0.321
3
99.6
0.319
99.6
0.319
99.6
0.319
4
99.8
0.313
99.8
0.313
99.8
0.313
5
100.01
0.311
100.01
0.311
100.01
0.311
6
100.3
0.31
100.3
0.31
100.3
0.31
Finned tube length: 0.5 m
Finned tubes per row
2
3
4
Finned tube rows
Nu
f
Nu
f
Nu
f
2
99.3
0.321
99.3
0.321
99.3
0.321
3
99.6
0.319
99.6
0.319
99.6
0.319
4
99.8
0.313
99.8
0.313
99.8
0.313
5
100.01
0.311
100.01
0.311
100.01
0.311
6
100.3
0.31
100.3
0.31
100.3
0.31
Finned tube length: 0.05194 m
Finned tubes per row
2
3
4
Finned tube rows
Nu
f
Nu
f
Nu
f
2
99.3
0.321
99.3
0.321
99.3
0.321
3
99.6
0.319
99.6
0.319
99.6
0.319
4
99.8
0.313
99.8
0.313
99.8
0.313
5
100.01
0.311
100.01
0.311
100.01
0.311
6
100.3
0.31
100.3
0.31
100.3
0.31
Table 3.
Sensitivity analysis results.
4.2. Numerical results
The predictions for velocity field, pressure field, and temperature field are shown in Figure 6. In all figures, profiles of the variables are presented on the x-z plane, because this is the plane that exhibits most changes in properties. The velocity contours (figure 6a) reflect an apparently symmetric behaviour but the field is slight asymmetry due to the fin helical layout. The recirculation zones are observed at the rear portion of the tubes, with reference to air flow direction. These recirculation zones are narrow because the flow tends to stick to the contour of finned tubes by turbulence generated. The recirculation region has amplitude and length of approximately 49.85 mm and 52.61 mm, respectively. The flow tends to accelerate in the free zones where the cross-section area is smaller (central region of computational domain and at the side portions of the central finned tube) with a maximum velocity of 5.017 m/s. Finally, the backwater area where the flow is stopped abruptly at the central portion of the finned tube exhibit has a width and a length of about 9.75 mm and 6.57 mm, respectively.
The pressure contours (figure 6b) indicate an apparently symmetric pressure profile, similar to the velocity profile, which is not symmetric due to the helical fin. The results show a high-pressure zone at the front portion of the tube, taking the flow direction as the point of reference. This high-pressure zone is created due to flow stopping abruptly at the central portion of the finned tube, producing a backwater zone. At the rear of the finned tube, there is a low-pressure area that is stratified at the outlet of single isolated module. The mean pressure at the inlet and outlet of the module is 23.184 Pa and 9.019 Pa, respectively, as shown in table 4. The pressure drop is 14.165 Pa, which represents a friction factor of 0.311 (table 4). The deviation of numerical results is 3.13% and 0.32% for pressure drop and friction factor, respectively. So, numerical predictions with boundary conditions calculated from methodology correspond to results obtained with Weierman´s [15] model.
Numerical predictions of temperature contours (figure 6c) show an apparently symmetric profile, which are not symmetric due to the helical fin. The results exhibit that the high-temperature region is located at the central region of the computational domain, whereas the low-temperature areas are located at the rear of the finned tubes, viewed with respect to the flow direction. So, the most important heat transfer effects occur at the front of the extended surfaces and at the sides of the finned tube between the backwater zone and the recirculation zone. This pattern is attributed to the air flow coming into abrupt contact with the finned tubes, and to turbulence being created at the sides of the finned tubes. On the other hand, the temperature contours exhibit that flow temperature is dominated for inside fluid temperature in the recirculation zone. The mean temperature at inlet and outlet of module is 43.76°C and 34.73°C (table 4). The temperature difference is 9.03°C, which represents a numerical-mean Nusselt number of 95.1, as shown in table 4. Numerical results show deviations of 4.25% and 5.18% for temperature difference and Nusselt number, respectively. These results show that numerical predictions are close to results obtained with Kawaguchi´s et al. [18] model. So, the numerical simulation represents adequately heat transfer in a single isolated finned tube module with boundary conditions calculated from methodology.
Numerical Simulation
model
Weierman
Pinlet (Pa)
24.44
na
Poutlet (Pa)
10.27
na
ΔP (Pa)
14.17
13.74
deviation
3.13%
reference
f
0.311
0.31
deviation
0.32%
reference
Kawaguchi
Tinlet (ºC)
40.78
na
Toutlet (ºC)
31.78
na
ΔT (ºC)
9.0
9.4
deviation
4.25%
reference
Nu
95.1
100.3
deviation
5.18%
reference
Table 4.
Comparative results.
Figure 6.
Numerical predictions.
5. Conclusion
The methodology, based on the LMTD method, for calculating boundary conditions in a single isolated finned tube module is adequate because the Nusselt number and friction factor show a quasi-constant behaviour for different finned tube length and finned tubes per row. The maximum deviations for Nusselt number and friction factor are lower than 1% and 3.6%, respectively. Therefore, the methodology can be used in numerical analysis of heat recoveries at industrial scale because the computational domain can be reduced in 99% which allows finite computational times. Numerical predictions in the single isolated finned tube module show that pressure contours are adequate because mean pressure drop and mean friction factor exhibit a deviation of 3.13% and 0.32% with respect to model developed by Weierman [15]. On the other hand, the pressure contours exhibit that the high pressure values are located in backwater zone and the main dissipative effect of flow energy is located at this region. Therefore, the pressure drop is dominated for backwater zone. The temperature field show a deviation of 4.25% and 5.18% for temperature difference and Nusselt number with respect to Kawaguchi´s, et al [18] model. The temperature contours exhibit that bare tube temperature is dominated by inside fluid temperature. Therefore, the inside fluid temperature must be considered as a lower limit temperature for cooling of flue gases in order to avoid dew point of acid gases.
Nomenclature
Symbols
Subscripts
A
surface area
b
bulk, boundary
A2
tube row coefficient
f
fin
B
contraction factor
g
gases
cp
specific heat at constant pressure
gp
gas-phase
d
diameter
i
inside
e
thickness
l
longitudinal
f
friction factor
med
Initial profile
G
gas mass flux
num
numeric
g→¯
gravitational acceleration
o
outside (tube diameter), overall
h¯
average convective coefficient
r
Radiation, rows
h˜
mean enthalpy
t
bare tube, transverse
h
mean convective coefficient
v
volume-equivalent diameter
k
thermal conductivity
w
wall, tube material
k˜
turbulent kinetic energy
L
characteristic length
Greek letters
l
height
β
average-pressure gradient
m˙
mass flow
ρ¯
mean density
N
Number of tubes
ρ
density
n
number
ε˜
dissipation turbulent rate
Nu
Nusselt Number
η
efficiency
Nu¯
average Nusselt number
µ
viscosity
P˜
periodic pressure
γ
temperature-gradient term
Pb
mean pressure
Pr
Prandtl number
Q˙
heat addition
Re
Reynolds number
Rf
fouling factor
S
pitch
s
gap
T˜
periodic temperature
T
temperature
t
thickness
U
overall heat transfer coefficient
u˜,v˜,w˜
mean velocity components
V→˜
instantaneous velocity
V→″
fluctuating velocity
w
velocity
ΔP˜
pressure drop
ΔTML
logarithmic mean temperature difference.
Acknowledgement
We appreciate the support given to the research presented here by Universidad Nacional Autonoma de Mexico (Direccion General de Asuntos del Personal Academico, PAPIIT- IN106112-3), and Universidad Autonoma Metropolitana Azcapotzalco.
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Salinas",authors:[{id:"146232",title:"PhD.",name:"William",middleName:null,surname:"Vicente Rodriguez",fullName:"William Vicente Rodriguez",slug:"william-vicente-rodriguez",email:"wvicenter@ii.unam.mx",position:null,institution:null},{id:"146501",title:"Dr.",name:"Eliseo",middleName:null,surname:"Martinez",fullName:"Eliseo Martinez",slug:"eliseo-martinez",email:"emartineze@ii.unam.mx",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Methodology",level:"1"},{id:"sec_2_2",title:"2.1. Finned tube bank analysis",level:"2"},{id:"sec_3_2",title:"2.2. Logarithmic Mean Temperature Difference (LMTD) method",level:"2"},{id:"sec_4_2",title:"2.3. Sensitive analysis of finned tube bank",level:"2"},{id:"sec_6",title:"3. Numerical simulation",level:"1"},{id:"sec_6_2",title:"3.1. Governing equations",level:"2"},{id:"sec_7_2",title:"3.2. Boundary conditions",level:"2"},{id:"sec_8_2",title:"3.3. Numerical details",level:"2"},{id:"sec_10",title:"4. Results",level:"1"},{id:"sec_10_2",title:"4.1. Sensitive analysis",level:"2"},{id:"sec_11_2",title:"4.2. Numerical results",level:"2"},{id:"sec_13",title:"5. Conclusion",level:"1"},{id:"sec_14",title:"Nomenclature",level:"1"},{id:"sec_15",title:"Acknowledgement",level:"1"}],chapterReferences:[{id:"B1",body:'BealeS. B.SpaldingD. B.1999A Numerical Study of Unsteady Fluid Flow in In-line and Staggered Tube Banks. Journal of Fluids and Structures, 1367237540889-9746'},{id:"B2",body:'CominiG.CroceG.2003Numerical Simulation of Convective Heat and Mass Transfer in Banks of Tubes. International Journal for Numerical Methods in Engineering, 5712175517731755-1773'},{id:"B3",body:'BealeS. B.2007Use of Streamwise Periodic Boundary Condition for Problems in Heat and Mass Transfer. ASME Journal of Heat Transfer, 12946016050022-1481'},{id:"B4",body:'BealeS. B.2008Benchmark Studies for the Generalized Streamwise Periodic Heat Transfer Problem. ASME Journal of Heat Transfer, 130111145020022-1481'},{id:"B5",body:'BenhamadoucheS.LaurenceD.2003LES, Coarse LES, and Transient RANS Comparisons on the Flow Across a Tube Bundle. International Journal of Heat and Fluid Flow, 2444704790014-2727X.'},{id:"B6",body:'Salinas-VázquezM.de la LamaM. A.VicenteW.MartínezE.2011Large Eddy Simulation of a Flow through Circular Tube Bundle. Applied Mathematical Modelling, 359439344060030-7904X.'},{id:"B7",body:'HofmannR.PonweiserK.2008Experimental and Numerical Investigations of Serrated-Finned Tubes in Cross-Flow. Available from: www.zid.tuwien.ac.at/fileadmin/files_zid/projekte/2008/08-302-2.pdf.'},{id:"B8",body:'McilwainS. R.2010A Comparison of Heat Transfer Around a Single Serrated Finned Tube and a Plain Finned Tube. IJRAAS, 228894ISSN\n\t\t\t'},{id:"B9",body:'McilwainS. R.2010A CFD Comparison of Heat Transfer and Pressure Drop Across Inline Arragement Serrated Finned Tube Heat Exchangers with an Increasing Number of Rows. IJRAAS, 42162169ISSN\n\t\t\t'},{id:"B10",body:'LemoueddaA.SchmidA.FranzE.BreuerM.DelgadoA.2011Numerical Investigations for the Optimization of Serrated Finned-Tube Heat Exchangers. Applied Thermal Engineering, 318-9139314011359-4311'},{id:"B11",body:'GanapathyV.2002Industrial Boilers, Heat Recovery and Steam Generators: Design, Applications and Calculations. In Marcel Dekker, (Ed), 3335070-82470-814-8York.\n\t\t\t'},{id:"B12",body:'GnielinskiV.1976New equations for heat and mass transfer in turbulent pipe and channel flow. Int. Chem. Eng. 1613593660020-6318'},{id:"B13",body:'RaneM. V.TandaleS.2005Water-to-water heat transfer in tube-tube heat exchanger: Experimental and analytical study. Applied Thermal Engineering, 2517271527291359-4311'},{id:"B14",body:'BejanA.1995Convection Heat Transfer. In Wiley, (Ed), 3913950-47127-150-0'},{id:"B15",body:'WeiermanC.1976Correlations Ease The Selection of Finned Tubes. Oil and Gas Journal, 7436941000030-1388'},{id:"B16",body:'ESCOA Turb-X HF Rating Instructions.1979Extended Surface Corporation of America (ESCOA), Pryor, OK.'},{id:"B17",body:'NirA.1991Heat Transfer and Friction Factor Correlations for Crossflow over Staggered Finned Tube Banks. Heat Transfer Engineering, 12143580145-7632'},{id:"B18",body:'Kiyoshi Kawaguchi, Kenichi Okui, Takaharu Kashi.2005Heat transfer and pressure drop characteristics of finned tube banks in forced convection. Journal of Enhanced Heat Transfer, 1211201065-5131'},{id:"B19",body:'MartinezE.SotoG.VicenteW.SalinasM.2005Comparative Analysis of Heat Transfer and Pressure Drop in Helically Segmented Finned Tube Heat Exchangers. Applied Thermal Engineering, 3011-12147014761359-4311'},{id:"B20",body:'JonhWeale. P. E.PeterH.RumseyP. E.DaleSartor. P. E.LeeEng.Lock2002Laboratory Low-Pressure Drop Design. ASHRAE Journal, Vol. August 38420001-2491'},{id:"B21",body:'MartinezE.VicenteW.SalinasM.SotoG.2010Thermal Design Methodology of Industrial Compact Heat Recovery with Helically Segmented Finned Tubes. Heat Exchangers; design, types and applications. In Nova Publishers, (Ed), Series: Energy Science, Engineering and Technology, 215228978-1-61761-308-1'},{id:"B22",body:'MartínezE.VicenteW.SalinasM.SotoG.2009Single-phase experimental analysis of heat transfer in helically finned heat exchangers, Applied Thermal Engineering, 2911-12220522101359-4311'},{id:"B23",body:'FavreA.(969Problems of Hydrodynamics and Continuum Mechanics, SIAM.'},{id:"B24",body:'YakhotV.OrszagS.1986Renormalization Group Analysis of Turbulence. Basic Theory. Journal of Scientific Computing, 113510885-7474'},{id:"B25",body:'PatankarS. V.LiuC. H.SparrowE. M.1977Fully Developed Flow and Heat Transfer in Ducts Having Streamwise-Periodic Variations of Cross-Sectional Area, ASME Journal of Heat Transfer, 99, 180186'},{id:"B26",body:'KelkarK. M.PatankarS. V.1987Numerical Prediction of Flow and Heat Transfer in a Parallel Plate Channel with Staggered Fins, ASME Journal of Heat Transfer, 109, 2530'},{id:"B27",body:'MartínezE. E.2011Simulación Numérica de un Flujo de Gases Turbulentos en un Banco de Tubos aletdos en Geometría Compleja. Ph.D Thesis. Universidad Autónoma Metropolitana, México City, México.'},{id:"B28",body:'LudwingJ. C.QinH. Q.SpaldingD. B.1989The PHOENICS Reference Manual. Technical Report CHAM TR/200, CHAM Ltd, London.'},{id:"B29",body:'ChoiY.HongJ.HwangH.ChoiJ.2008Cartesian Grid Method with Cut Cell in the Mold Filling Simulation. Journal Materials Science British Technology, 2433793821005-0302'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"E. Martínez",address:null,affiliation:'
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1. Introduction
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Most of the fetal and maternal complications become apparent with advancing gestation. However, since very important complications that occur later in pregnancy can be predicted in the first trimester, the focus has been set on the evaluations in early pregnancy, thus inverting the pyramid of prenatal care. Although vast majority of early screening tests have been developed and employed, the outcome of pregnancies with the major obstetric syndromes still fails to be significantly improved. The changes etiologically and pathophysiologically associated with disturbed placentation and responsible for the perinatal mortality and morbidity should be sought even earlier, in the preimplantation period, in relation between the embryo and the endometrium.
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2. Early pregnancy screening tests and algorithms
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The idea of inverted pyramid of prenatal care has emerged for the purpose of prediction and prevention and then early detection and treatment of health disorders of the fetus. By applying this principle, a number of disorders could be prevented or treated with better outcome: fetal aneuploidy and anomalies, miscarriage, stillbirth, preterm delivery, preterm premature rupture of membranes, preeclampsia, and intrauterine growth restriction [1].
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In recent years, screening for aneuploidies during the first trimester has reached effectiveness of over 90% in identifying the most common aneuploidies by a combination of maternal age, fetal nuchal translucency, as well as analysis of free beta-hCG and pregnancy-associated plasma protein A (PAPP-A) [2]. Effectiveness of screening for potential aneuploidies was further augmented with the introduction of the noninvasive prenatal testing using maternal plasma cell-free (cf) DNA, as a secondary test in those patients already regarded as being at high risk. The detection rate of major aneuploidies with this test is up to 99. 3%, with false positive rate of 0. 11% [3].
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The development of sonography and MRI diagnostics has led to a growing number of early detected anomalies. A large number of these anomalies can be detected already at 11–14 weeks, while a number can only be found at a later gestation [4]. The prenatal detection rate for the major anomalies is around 68% (varying from 33 to 96%) [5, 6].
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First trimester screening often focuses on fetal aneuploidy and major structural anomalies. However, certain maternal characteristics, such as the age and body mass index (BMI), have shown to be very informative, with regard to the predicting miscarriage and stillbirth. The risk of preterm delivery is determined by algorithms that combine these results of the first trimester screening for aneuploidy, increased nuchal translucency, the abnormal ductus venosus flow, and low level of PAPP-A, with the characteristics of the mother [7, 8, 9]. Such example is the information on the length of the cervical canal from 11- to 13-week gestation [9, 10]. The risk of spontaneous preterm delivery is associated with cervical shortening in the second trimester, as well as in the first trimester. Combining this parameter with fetal aneuploidy analyses and major structural anomaly results is likely to be used in the future to select a high-risk group that may benefit from close follow-up.
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Another example is the screening for the development of early preeclampsia (PE), based on the combination of maternal risk factors, mean arterial pressure, maternal serum PAPP-A, uterine artery Doppler, and placental growth factor. This algorithm has a 95% detection rate for a false-positive rate of 10% [11, 12]. Also, different angiogenesis-related biomarkers; antiangiogenic proteins, like soluble fms-like tyrosine kinase-1 (sFlt-1) and soluble endoglin; or proangiogenic proteins, placenta growth factor (PlGF) and vascular endothelial growth factor (VEGF) have been pointed out by a number of authors [10]. The placental protein-13 and other markers, disintegrin and metalloprotease-12 (ADAM12), activin A, or inhibin A, and other microelements or antioxidants, in isolation or in combination, were evaluated in order to predict complications of pregnancy [13, 14, 15]. It was also shown that early administration of low-dose aspirin (60–80 mg), starting from the first trimester, reduces the incidence of intrauterine growth restriction as well as its related pregnancy and neonatal complications for 17%, with number needed to treat (NNT) 72, and 14% reduction in fetal or neonatal deaths with NNT 24 [16].
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The detection of the small for gestational age (SGA) fetuses could be predicted by algorithms with the combination of maternal characteristics, mean arterial pressure, uterine artery Doppler, and the measurement of various placental products in maternal blood at 11–13 weeks, at a false-positive rate of 10%, about 75% of pregnancies without preeclampsia delivering SGA neonates before 37 weeks and 45% of those delivering at term [17]. Screening for macrosomia by a combination of maternal characteristics and obstetric history with fetal NT and maternal serum- free ß-hCG and PAPP-A at 11–13 weeks could potentially identify, at a false-positive rate of 10%, about 35% of women who deliver macrosomic neonates [18].
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Despite the introduction of the vast early pregnancy screening tests, there is still a very slight decrease or even increase in the rate of preterm birth and almost a constant rate of miscarriage, stillbirth, preeclampsia, and SGA [19, 20, 21, 22, 23]. Except for hereditary and structural disorders of the fetus, other disorders are etiologically and pathophysiologically associated with disturbed placentation and responsible for the perinatal mortality and morbidity [24].
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The reasons why the modern medicine still fails to significantly improve the outcome of pregnancy with the major obstetric syndromes should be sought in the earlier period of pregnancy, even before the conception, and on another subcellular level (Personal communication Dudenhausen, Tirana 2015). Because the consequence of these disturbances is seen in dysfunctional placentation, their sources must be searched before the time of implantation. This means that the changes that lead to the insufficient implantation should be sought in the preimplantation period, in relation between the embryo and the endometrium.
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The onset and progression of pregnancy require the coordinated implantation of the embryo and trophoblast invasion into the receptive maternal decidua, followed by proper remodeling of the spiral arteries. Proliferation, migration, and invasion of trophoblastic cells into the maternal endometrium are the essential steps. If any of these steps fails to complete properly because of the endometrial dysfunction, the consequences would be the basis for development of obstetric complications.
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3. Maternal health at preconception period
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The implanting embryo physically establishes connections with the mother through the endometrium, by a fine-tuned and synchronized crosstalk necessary to support the feto-placental development and health throughout gestation [25]. Early alterations of endometrial physiology can affect the development of the conceptus and the success of pregnancy. The overall status of maternal health is reflecting on the endometrium. If we agree that the optimally prepared mucous membranes (either endogenously, by its own sex hormone or by exogenous regimes) are one of the preconditions for the successful implantation, then the modification of its preparation could influence the occurrence of disorders in later pregnancy and after the birth of the child.
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Several studies have shown that preimplantation embryos are sensitive to environmental conditions in which it develops, either in vitro or in vivo, for example, in response to culture conditions or maternal diet [26]. Those conditions can affect future growth and developmental potential, both pre- and postnatally. Recent findings have demonstrated that perturbations of the maternal physiology during the peri-conceptional period (e.g., maternal diet) have impact both on preimplantation phenotype and long-term development and could lead to impaired health during adulthood [26]. Emerging evidence suggests the metabolic status of the mother may “program” the offspring’s long-term risk of metabolic disease [27].
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Modifications of preimplantation embryo conditions, using assisted reproductive technologies (ARTs) or somatic cell nuclear transfer (SCNT), have been associated with developmental abnormalities and postnatal consequences such as the large offspring syndrome (LOS) in animals [28, 29, 30]. Early alterations of the maternal or embryo environment may affect the quality of the embryo-endometrium crosstalk that further leads to pregnancy failure or postnatal detrimental consequences.
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4. Endometrium
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Before the embryo can implant in the endometrium, the endometrium must be in a receptive state. As a result of a series of timed hormonal events, the so-called window of implantation is opened, which is the time most suitable for the endometrium to support trophoblast-endometrial interaction [31].
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The term windows of vulnerability (WOV), i.e., period of time when the endometrium is subject to the influence of factors that may disrupt implantation conditions, has recently been introduced within the framework of reproductive medicine, besides the window of implantation (WOI), i.e., the optimal period of time of activation of endometrial receptivity (De Ziegler, personal communication, MSD symposium, Barcelona 2016).
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Prepregnancy approaches such as weight management, blood pressure and blood sugar control, smoking cessation, and optimization of the pregnancy interval may improve implantation and placentation and lead to better pregnancy outcomes [32].
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There are a number of different treatment protocols for the “inadequate” endometrium. The medical treatment with estrogens, vasodilators, and sildenafil citrate has neither led to significant improvements of morphological parameters nor to the results in terms of increasing implantation and reduction of the number of miscarriages [33, 34]. There have been reports of trials with immunoglobulins and anticoagulants in pregnancy complication prevention [35, 36, 37, 38, 39].
\n
The local endometrium therapy is ongoing for several years. One of the promising therapeutic targets is the corticotropin-releasing hormone (CRH). During implantation, corticotropin-releasing hormone plays a key role in facilitating endometrial decidualization and early maternal tolerance. The embryo implantation provokes the maternal endometrial response similar to the invading semi-allograft that produces acute inflammatory response. After the implantation, the embryo suppresses this response and prevents the rejection [40]. The deregulation of expression pattern of CRH was associated with unfavorable reproductive outcomes as well as chronic endometrium-derived inflammatory disorders, such as endometriosis and adenomyosis [41]. Positive outcome was found after the intrauterine administration of autologous peripheral blood mononuclear cells (PBMCs) [41] especially when pretreated with corticotropin-releasing hormone that acts by regulating apoptosis of activated T- lymphocytes at the implantation site [42]. The results of eight studies showed that intrauterine administration of activated autologous peripheral blood mononuclear cells prior to embryo transfer improves the reproductive outcomes in women with repeated implantation failure [43].
\n
Besides endometrial receptivity, another very important parameter is the endometrial thickness. Defined minimal thickness at approximately 7 mm and clinical pregnancy rates after embryo transfer increase with increasing endometrial thickness. One of the new therapeutic approaches to improve endometrial thickness is the intrauterine perfusion with granulocyte colony-stimulating factor (G-CSF). In clinical reproduction, G-CSF has been proposed as a treatment for implantation failure and repeated miscarriages, two indications for which a US patent has been issued. These authors have applied the drug subcutaneously [44]. Gleicher’s papers on flushing uterus cavity with growth factors before the embryo transfer have proposed granulocyte colony-stimulating factor as the treatment of implantation failure and repeated miscarriages [44]. Chang reported successful endometrial expansion in a small group of women with thin endometrium resistant to standard treatments, who were able to proceed to embryo transfer and conceive after uterine perfusion with G-CSF [45].
\n
The use of platelet-rich plasma (PRP) to improve endometrial receptivity is gaining increasing attention in assisted reproduction technologies. Platelets contain a significant amount of growth factors that have positive effects on local tissue repair and endometrial receptivity. Several authors have reported autologous PRP intrauterine injection improves pregnancy and birth rates, especially in patients presenting poor endometrial growth [46].
\n
Chang and associates have recently published the attempt to improve the quality of endometrial thickness, implantation rate, and pregnancy success and to reduce the complications and miscarriage rate, by flushing the uterus cavity with autologous platelet-rich plasma in preparation for the implantation during IVF process [47]. Farimani reported the first successful pregnancy after administration of PRP in a woman with recurrent implantation failure [48]. Kim et al. suggested that the use of autologous PRP improved not only endometrial thickness but restored the endometrial receptivity of damaged endometrium and increased the implantation, pregnancy, and live birth rates (LBR) of the 24 patients with refractory thin endometrium [49]. This therapy delivers biological growth factors, PDGF, TGF-b, and VEGF, insulin-like growth factor 1, epidermal growth factor (EGF), and epithelial cell growth factor to the endometrium. Our group has, so far, treated 25 patients with PRP technology and has achieved a significant improvement of the implantation rates and in reducing the number of abortions. We reported the first case of human embryo obtained after autologous platelet leukocyte-rich plasma (PLRP) in vitro activation of ovaries by interrupting Hippo signaling and PLRP stimulating AKT pathway with ultrasound-guided orthotropic re-transplantation [50]. The patient was a case of an early menopausal woman for whom the ovarian cortex was frozen, thawed, and treated with autologous PLRP which was then transplanted into her menopausal ovaries. Two months after the procedure, follicle formation was noted, and an egg was retrieved resulting in a single embryo [50].
\n
The human endometrium is a dynamic tissue that undergoes monthly cyclic changes, including proliferation, differentiation, and degeneration. Apoptosis is the common pathway of cell death for eliminating senescent endometrial cells from the functional layer of the human endometrium during the late secretory phases of the cycle. It has recently been implied that autophagy is involved in the endometrial cell cycle affecting apoptosis and is the most prominent during the late secretory phase [51]. It is known that the impact on autophagy processes in the endometrium may lead to a reduced incidence of pregnancy complications related to the implantation. Our group has proved that autophagy, a process of controlled self-digestion involved in cellular homeostasis, is dysregulated in endometrial tissue of polycystic ovary syndrome (PCOS) patients and that treatment with metformin might influence endometrial autophagy in PCOS [52]. Other studies reported that metformin can improve endometrial receptivity, enhance endometrial vascularity and blood flow, and revert endometrial hyperplasia and carcinoma into normal endometria in addition to improving hyperandrogenism and insulin resistance in some women with PCOS [53, 54].
\n
\n
5. Embryo environment
\n
The essential requirements for normal implantation and subsequent placentation leading to a healthy gestation are receptive endometrium and healthy embryo. However, there is still a growing number of unexplained failed implantation outcomes that could not be assigned to known factors and require further investigation.
\n
In recent years it was indicated that different etiologies of infertility arose as a result of the underlying genetic and epigenetic changes that contribute to the endometrial dysfunction and lead to implantation failure, miscarriage, and adverse outcomes. These epigenetic and genetic changes lead to placentation defects and contribute to the short- and long-term outcomes associated with infertility. One of the main causes for altered genetic and epigenetic regulation of embryo development and placentation was assigned to hormonal and nutrition-related changes in maternal environment. Embryos respond to the in vivo maternal environment during gestation or during cultivation in vitro in multiple ways that can influence their future growth and health. Developmental plasticity could be altered by the changes in imprinted gene expression, nutrient, and stress-related signaling pathways or cell cycling and apoptotic rates. Embryo phenotype changes through a complex network of interactions with a central role for maternal-fetal neuroendocrine signaling [55]. Maternal undernutrition during gestation alters maternal steroid hormone levels, including elevation of glucocorticoids (GC; corticosterone, cortisol), the stress hormones, which can alter the physiological condition of the conceptus and affect the intrauterine fetal and postnatal growth and cardiovascular and metabolic physiology and enhance the risk of adult-onset disease. This exposure of the embryo to glucocorticoids can alter the fetal hypothalamus pituitary adrenal (HPA) axis, leading to increased fetal GC activity which can, in turn, modify the expression of many downstream-regulated genes that control growth and metabolism, including cardiovascular and renal physiology [55].
\n
The influence of placental function and placental/fetal exchange on fetal programming has been in focus of the recent research. Now it has become widely accepted that maternal nutrition can have the long-term consequences on the offspring without necessarily affecting the size at birth. Altered embryo phenotypes induced by prenatal nutrition are associated with epigenetic modifications. Many imprinted genes contribute to placental function and nutrient exchange [56]. Early epigenetic effects in embryos caused by environmental conditions can lead to physiological impairment to growth due to reduced nutrient supply. There is now evidence from human studies and animal experiments that show the overnutrition and undernutrition during the prenatal period which have lifelong health effects for the offspring and induce the development of noncommunicable diseases during postnatal life [57].
\n
Besides nutrition, the hormonal milieu at conception is known to affect a number of imprinted genes that are expressed during the preimplantation period. Hormonal status will be especially affected during fertility treatment, mostly during IVF. Because superovulation could lead to altered expression of endometrial genes critical to tissue remodeling and placentation, hyperstimulated hormonal status has been implicated in an increased risk for pregnancy complications related to abnormal placentation [58]. Although global methylation pattern was found to be similar among the IVF and spontaneous conceptions early during placentation in the first trimester, differential methylation has been identified in multiple loci between IVF and non-IVF fertility treatments pregnancies but not when compared with spontaneous conceptions. This suggests that there are differences in the infertile population that might be linked to specific treatments, including the hormonal hyperstimulation, that could affect gene imprinting [59]. Several studies have found that the use of ARTs is linked with irregular DNA methylation in human gamete, embryo, placenta, and umbilical cord samples [60, 61]. There were also studies that showed association between specific procedures with methylation differences in placenta, suggesting that specific fertility treatments affect the placental epigenome and function [62].
\n
\n
6. Embryo monitoring
\n
The embryo has, in addition to the endometrium, the crucial importance for the success and regularity of the implantation and then placentation. The morphological assessment of the embryos’ quality is insufficient for the cognition of its biological resources. The new invasive and noninvasive techniques of embryo quality assessment have been developed. Nowadays, the invasive technology means preimplantation genetic testing (PGT), the aneuploidy screening, or diagnosis of specific genetic disorders of the embryo before the transfer by using next-generation sequencing (NGS). These tests include biopsy trophectoderm cells with blastocyst vitrification [63, 64, 65]. With trophectoderm biopsy, both maternal and paternal abnormalities can be studied. Possible disadvantages are the presence of mosaicism and the fact that the trophectoderm might not be a representative of the inner cell mass.
\n
Noninvasive time-lapse embryo monitoring allows continuous embryo observation without the need to remove the embryo from optimal culturing conditions. The information on the cleavage pattern, morphologic changes, and embryo development dynamics could help us identify embryos with a higher implantation potential. It has also been shown that imaging phenotypes reflect the molecular program of the embryo, where individual blastomeres develop autonomously toward embryo genomic activation [66].
\n
This type of monitoring allows for the collection of much more information on the timing of the cleavages and the dynamics of the morphologic changes, with analysis of the kinetics of the events up until the blastocyst stage [67].
\n
Various kinetic and morphologic markers have already been found that are associated with the minimal likelihood of implantation and others that are predictive of blastocyst development, implantation potential, genetic health, and pregnancy [68, 69].
\n
\n
7. Gametes
\n
After the formation of the embryo, its fate is already determined. The gamete quality has the crucial part in the creation of the high-quality embryos. The conditions, in which oogenesis and spermatogenesis take place, have a crucial impact on the quality of embryos that is formed from these gametes.
\n
7.1 Oogenesis
\n
The evaluation of the oocyte quality based on morphological evaluation is not sufficient for an insight into the biological potential. It can identify those cells that have nuclear immaturity, significant degeneration, or major abnormalities. Recently, the developed strategies including the genomic, transcriptomic, and proteomic approaches have been applied in assisted reproduction. Their goal is to identify a “molecular profile” of embryo development by detecting the chemical components in the oocyte, granulosa cells, follicular fluid, and embryo culture medium [70].
\n
Better predictors, the birefringence properties of the meiotic spindle, and the zona pellucida are indicative of good health of the oocyte [71]. A very useful data can be obtained from the application of studying gene expression from cumulus cells, using microarrays, as biomarkers for oocyte viability. The metabolomic profiling of oocyte spent culture media by mass spectroscopy has shown differences related to oocyte maturation, embryo development, and implantation success [72]. Oocyte quality can be assessed by the measurement of oocyte oxygen consumption [73].
\n
Spermatogenesis: the quality of spermatogenesis is the condition for the formation of a good embryo. The advanced sperm selection techniques are based not only on the morphological assessment (defragmentation, MACS) but also on the evaluation of specific cellular characteristics (membrane integrity, density, surface charge) that provide a choice of better quality sperm. The methods of improving conditions of gametogenesis, which are applied so far, do not provide a sufficient effect. They are mainly related to the balance correction of microelements and vitamins, as well as the oxydo-reductive processes in the body. The sperm chromatin and DNA integrity are necessary to ensure normal embryo development. It is now clear that DNA damage in spermatozoa has a negative influence on blastocyst development and the pregnancy outcome [74] . Similarly, centrosome integrity is critical for successful fertilization and embryo development. There are studies that have described the association between sperm with DNA damage and a history of recurrent miscarriage [75].
\n
\n
7.2 Advanced therapy
\n
Magnetic-activated cell sorting (MACS) technology for sperm could improve obstetric and perinatal outcomes compared with those achieved after swim up. Treatment of sperm with MACS procedure prior to IVF results in a marked improvement in pregnancy rate and cessation of the abortion rate in couples whose ejaculates initially had high levels of SDF [76].
\n
A number of prerequisites are needed to create high-quality oocytes, those conditions are likely to be grouped into several parts: the existence of high quality responsive oogonia, its potential of the adequate number increase and quality of mitochondria, the presence of sufficient amounts and types of growth factors, orchestrated by the balance of blocking (Hippo) and activating (ACT) gene pathways [77].
\n
For decades it was believed that the woman’s reproductive potential is entirely dependent on the size of the stock (pool) of primordial follicles in the ovary. The paradigm that has prevailed for decades in the scientific world about the existence of a consistent number of primordial follicles, established during embryonic and fetal period, was in many ways changed by Tilly’s group work. They practically demonstrated the existence of germline or oogonial stem cells [78].
\n
Their dormant status is characterized by communication with surrounding granulosa cells and numerous mechanical and chemical factors controlling the progression of their cell cycle. These factors control signaling activation of the pathways included in the primordial follicle dormant status regulation, like Hippo and AKT signaling [77]. During the recent years, various programs have been developed to try to improve the quality of oocytes. It has been shown that it can be influenced on the activation of primordial cells and maturation to the mature oocyte. The stem cells can be influenced by the stem cell therapy in order to obtain the intracellular communication with the existing ovarian primordial oogonia. The therapy with mesenchymal stem cells has led to the recovery features of oocytes after the chemotherapy-induced insufficiency [79]. The animal experiments by the in vitro therapy with developed stem cells have led to the birth of live offspring without abnormalities [80]. Other groups of authors have tried to improve the ovarian function with the growth factors obtained from the plasma and enriched with platelets and leukocytes. The cases of childbirth after re-transplantation of ovaries with support of PRP have been published [81]. Our group has achieved a normal pregnancy outcome after the sonographically guided therapy with growth factors in a female patient aged 40 years, after 18 attempts of in vitro fertilization.
\n
The role of the number and function of mitochondria in the development of quality oocytes is surely very important. The problems of mitochondrial heteroplasmy go with the complicated, technologically very complex methods of polar body transfer, spindle transfer, and pronuclear or oocyte transfer [82, 83, 84]. The augmentation of autologous mitochondria carries a potential treatment. Our team has inaugurated the attempt of the mitochondrial energy boosting with ovarian high-intensity interval training (HIIT).
\n
The autologous growth factors that are intraovarian instilled are leading to the changes in the production and efficiency of the local growth factors. The influence on the genetic control of oogenesis, by the modification of the Hippo and AKT signaling pathways, is possible in different ways. The correction of the gene signaling or autologous tissue genetic bioengineering is certainly a step forward in obtaining the quality gametes [50, 84].
\n
\n
\n
8. Conclusion
\n
Implantation is one of the crucial periods in human reproduction. Increasing body of evidence suggests that the improper (dysfunctional) implantation and the formation of the placenta can endanger life and health of both the fetus and the mother, during prenatal life and decades after delivery. The changes that lead to the insufficient implantation should be sought in the preimplantation period, in relation between the embryo and the endometrium. It is possible that the time is approaching when the disorders of the pregnancy caused by dysfunctional implantation would be the indication for the application of a natural IVF (without ovarian stimulation) with the use of new biotechnological achievements. For better results of the perinatal medicine, it is necessary to apply earlier (in the preconception and preimplantation periods) the therapy based on the subcellular and genetic level by applying the latest biotechnological procedures.
\n
\n',keywords:"implantation, fetal health, pregnancy complications",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/67850.pdf",chapterXML:"https://mts.intechopen.com/source/xml/67850.xml",downloadPdfUrl:"/chapter/pdf-download/67850",previewPdfUrl:"/chapter/pdf-preview/67850",totalDownloads:254,totalViews:0,totalCrossrefCites:0,dateSubmitted:"April 30th 2019",dateReviewed:"May 23rd 2019",datePrePublished:"June 25th 2019",datePublished:null,dateFinished:null,readingETA:"0",abstract:"Implantation is one of the crucial periods in human reproduction. Increasing body of evidence suggests that the improper (dysfunctional) implantation and the formation of the placenta can endanger life and health of both the fetus and the mother, during prenatal life and decades after delivery. The idea of the inverted pyramid of prenatal care has emerged in the recent years, as the early detection and prevention of health disorders of the fetus are specially focusing on the first trimester. By applying this principle, disorders in the perinatal period could be prevented or treated with better outcome. The changes that lead to the deficient implantation should be sought in the preimplantation period, in relation between the embryo and the endometrium. It is possible that the time is approaching when the disorders of the pregnancy caused by dysfunctional implantation would be the indication for the application of a natural IVF (without ovarian stimulation) with the use of new biotechnological achievements. For better results of the perinatal medicine, it is necessary to apply earlier (in the preconception and preimplantation periods) the therapy based on the subcellular and genetic level by applying the latest biotechnological procedures.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/67850",risUrl:"/chapter/ris/67850",signatures:"Aleksandar Ljubic, Dzihan Abazovic, Dusica Ljubic, Andrea Pirkovic and Andjela Perovic",book:{id:"7961",title:"Induced Abortion and Spontaneous Early Pregnancy Loss",subtitle:"Focus on Management",fullTitle:"Induced Abortion and Spontaneous Early Pregnancy Loss - Focus on Management",slug:"induced-abortion-and-spontaneous-early-pregnancy-loss-focus-on-management",publishedDate:"April 22nd 2020",bookSignature:"Igor Lakhno",coverURL:"https://cdn.intechopen.com/books/images_new/7961.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"255757",title:"Dr.",name:"Igor",middleName:"Victorovich",surname:"Lakhno",slug:"igor-lakhno",fullName:"Igor Lakhno"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Early pregnancy screening tests and algorithms",level:"1"},{id:"sec_3",title:"3. Maternal health at preconception period",level:"1"},{id:"sec_4",title:"4. Endometrium",level:"1"},{id:"sec_5",title:"5. Embryo environment",level:"1"},{id:"sec_6",title:"6. Embryo monitoring",level:"1"},{id:"sec_7",title:"7. Gametes",level:"1"},{id:"sec_7_2",title:"7.1 Oogenesis",level:"2"},{id:"sec_8_2",title:"7.2 Advanced therapy",level:"2"},{id:"sec_10",title:"8. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'Nicolaides K. A model for a new pyramid of prenatal care based on the 11 to 13 weeks’ assessment. Prenatal Diagnosis. 2011;31:3-6'},{id:"B2",body:'Wright D, Syngelaki A, Bradbury I, Akolekar R, Nicolaides KH. First-trimester screening for trisomies 21, 18 and 13 by ultrasound and biochemical testing. Fetal Diagnosis and Therapy. 2014;35(2):118-126. DOI: 10.1159/000357430. Epub 2013 Dec 18'},{id:"B3",body:'Sonek JD, Cuckle HS. 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Treatment with granulocyte colony-stimulating factor in patients with repetitive implantation failures and/or recurrent spontaneous abortions. Journal of Reproductive Immunology. 2015;108:123-135'},{id:"B43",body:'Maleki-Hajiagha A, Razavi M, Rezaeinejad M, Rouholamin S, Almasi-Hashiani A, Pirjani R, et al. Intrauterine administration of autologous peripheral blood mononuclear cells in patients with recurrent implantation failure: A systematic review and meta-analysis. Journal of Reproductive Immunology. 2019;131:50-56'},{id:"B44",body:'Gleicher N, Vidali A, Barad DH. Successful treatment of unresponsive thin endometrium. Fertility and Sterility. 2011;95(6):2123'},{id:"B45",body:'Chang Y, Li J, Chen Y, et al. Autologous platelet-rich plasma promotes endometrial growth and improves pregnancy outcome during in vitro fertilization. International Journal of Clinical and Experimental Medicine. 2015;8(1):1286-1290'},{id:"B46",body:'Bos-Mikich A, Ferreira MO, de Oliveira R, Frantz N. Platelet-rich plasma or blood-derived products to improve endometrial receptivity? Journal of Assisted Reproduction and Genetics. 2019;36(4):613-620. DOI: 10.1007/s10815-018-1386-z'},{id:"B47",body:'Sumarac-Dumanovic M, Apostolovic M, Janjetovic K, et al. Downregulation of autophagy gene expression in endometria from women with polycystic ovary syndrome. Molecular and Cellular Endocrinology. 2016;440:116-124'},{id:"B48",body:'Farimani M, Poorolajal J, Rabiee S, Bahmanzadeh M. Successful pregnancy and live birth after intrauterine administration of autologous platelet-rich plasma in a woman with recurrent implantation failure: A case report. International Journal of Reproductive BioMedicine (Yazd). 2017;15(12):803-806'},{id:"B49",body:'Kim H, Shin JE, Koo HS, Kwon H, Choi DH, Kim JH. Effect of autologous platelet-rich plasma treatment on refractory thin endometrium during the frozen embryo transfer cycle: A pilot study. Frontiers in Endocrinology (Lausanne). 2019;10:61. Published 2019 Feb 14. DOI: 10.3389/fendo.2019.00061'},{id:"B50",body:'Ljubić A, Abazović D, Vučetić D, et al. Autologous ovarian in vitro activation with ultrasound-guided orthotopic re-transplantation (in press). American Journal of Clinical and Experimental Obstetrics and Gynecology. 2017;4(5):51-57'},{id:"B51",body:'Choi JY, Jo MW, Lee EY, Oh YK, Choi DS. The role of autophagy in human endometrium. Biology of Reproduction. 2012;86(3):70. DOI: 10.1095/biolreprod.111.096206'},{id:"B52",body:'Schoolcraft WB, Fragouli E, Stevens J, Munne S, Katz-Jaffe MG, Wells D. Clinical application of comprehensive chromosomal screening at the blastocyst stage. Fertility and Sterility. 2010;94:1700-1706'},{id:"B53",body:'Jakubowicz DJ, Seppala M, Jakubowicz S, Rodriguez-Armas O, Rivas-Santiago A, Koistinen H, et al. 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Cochrane Database of Systematic Reviews. 2015;2:CD011320'},{id:"B69",body:'Seli E, Robert C, Sirard MA. OMICS in assisted reproduction: Possibilities and pitfalls. Molecular Human Reproduction. 2010;16:513-530'},{id:"B70",body:'Menezo Y, Elder K, Benkhalifa S, Dale B. DNA methylation and gene expression in IVF. Reproductive Biomedicine Online. 2010;20:709-710'},{id:"B71",body:'Nagy ZP, Jones-Colon S, Roos P, Botros L, Greco E, Dasig J, et al. Metabolomic assessment of oocyte viability. Reproductive Biomedicine Online. 2009;18:219-225'},{id:"B72",body:'Tejera A, Herero J, de Los Santos MJ, Garrido N, Ramsing N, Meseguer M. Oxygen consumption is a quality marker for human oocyte competence conditioned by ovarian stimulation regimens. Fertility and Sterility. 2011;96:618-623'},{id:"B73",body:'Evgeni E, Byron A. Human sperm DNA fragmentation and its correlation with conventional semen parameters. Journal of Reproduction & Infertility. 2014;15(1):2-14'},{id:"B74",body:'Leach M, Aitken R, Sacks G. Sperm DNA fragmentation abnormalities in men from couples with a history of recurrent miscarriage. Australian and New Zealand Journal of Obstetrics and Gynaecology. 2015;55:379-373'},{id:"B75",body:'Gil M, Shalom V, Carreras S. Sperm selection using magnetic activated cell sorting (MACS) in assisted reproduction: A systematic review and meta-analysis. Journal of Assisted Reproduction and Genetics. 2013;30(4):479-485'},{id:"B76",body:'Cheng Y, Feng Y, Jansson L, Sato Y, Deguchi M, Kawamura K, et al. Actin polymerization-enhancing drugs promote ovarian follicle growth mediated by the hippo signaling effector YAP. The FASEB Journal. 2015;29(6):2423-2430'},{id:"B77",body:'Johnson J, Canning J, Kaneko T, Pru JK, Tilly JL. Germline stem cells and follicular renewal in the postnatal mammalian ovary. Nature. 2004;428(6979):145-150'},{id:"B78",body:'Afifi N, Reyad O. Role of mesenchymal stem cell therapy in restoring ovarian function in a rat model of chemotherapy-induced ovarian failure: A histological and immunohistochemical study. The Egyptian Journal of Histology. 2013;36:114-126'},{id:"B79",body:'Hayashi K, Ogushi S, Kurimoto K, et al. Offspring from oocytes derived from in vitro primordial germ cell–like cells in mice. Science. 2012;338:971-975'},{id:"B80",body:'Callejo J, Salvador S, González-Nuñez S, et al. Live birth in a woman without ovaries after autograft of frozen-thawed ovarian tissue combined with growth factors. Journal of Ovarian Research. 2013;6:33-36'},{id:"B81",body:'Smeets HJM. Preventing the transmission of mitochondrial DNA disorders: Selecting the good guys or kicking out the bad guys. Reproductive BioMedicine Online. 2013;27:599-610'},{id:"B82",body:'Amato P, Tachibana M, Sparman M, Mitalipov S. Three-parent in vitro fertilization: Gene replacement for the prevention of inherited mitochondrial diseases. Fertility and Sterility. 2014;101(1):31-35'},{id:"B83",body:'Mitalipov S, Wolf DP. Clinical and ethical implications of mitochondrial gene transfer. Trends in Endocrinology & Metabolism. 2014;25(1):5-7'},{id:"B84",body:'Kawamura K, Cheng Y, Suzuki N, et al. Hippo signaling disruption and Akt stimulation of ovarian follicles for infertility treatment. PNAS. 2013;110(43):17474-17479'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Aleksandar Ljubic",address:null,affiliation:'
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In order to help Authors identify appropriate funding agencies and institutions, we have created a list, based on extensive research on various OA resources (including ROARMAP and SHERPA/JULIET) of organizations that have funds available. Before consulting our list we encourage you to petition your own institution or organization for Open Access funds or check the specifications of your grant with your funder to ascertain if publication costs are included. Where you are in receipt of a grant you should clarify:
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If you are associated with any of the institutions in our list below, you can apply to receive OA publication funds by following the instructions provided in the links. Please consult the Open Access policies or grant Terms and Conditions of any institution with which you are linked to explore ways to cover your publication costs (also accessible by clicking on the link in their title).
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