Parameters of genetic algorithm.
The main objective of this paper is to introduce a new fractional-order theory called nonlinear fractional generalized photo-thermoelasticity involving three temperatures. Due to strong nonlinearity, it is very difficult to solve the wave problems related to this theory analytically. Therefore, we propose a new boundary element algorithm and technique for simulation and optimization of the considered problems related to this theory. The genetic algorithm (GA) as an optimization method has been applied based on free form deformation (FFD) technique to improve the performance of our proposed technique. In the formulation of the considered problem, the profiles of the considered objects are determined by FFD technique, where the FFD control point positions are treated as genes, and then the chromosome profiles are defined with the gene sequence. The population is established by a number of individuals (chromosomes), where the objective functions of individuals are achieved by the boundary element method (BEM). A nonuniform rational B-spline curve (NURBS) was used to model optimized boundary where it reduces the number of control points and provides the flexibility to design several different shapes for solving the considered photo-thermoelastic wave problems. The numerical results verify the validity and accuracy of our proposed boundary element technique.
- boundary element method
- nonlinear generalized photo-thermoelasticity
- three temperatures
- modeling and optimization
- anisotropic semiconductor structures
In semiconductors, an electronic deformation leads to local strain which produces plasma waves that are similar to thermal waves generated by local periodic elastic deformation. In general, the electric resistance of semiconductor decreases with increasing temperature, due to semiconductor electrons released from atoms by heat. Recently, the fractional differential equations that can be used for describing many real-world systems have gotten more and more researchers’ attention due to their many applications in sciences and engineering fields.
Recently, increasing attention has been directed toward generalized micropolar thermoelastic problems in anisotropic media due to its many applications in aeronautics, astronautics, geophysics, plasma physics, nuclear plants, nuclear reactors, automobile industries, military technologies, robotics, earthquake engineering, soil dynamics, mining engineering, high-energy particle accelerators, and other engineering industries.
The classical thermoelasticity (CTE) theory has been proposed by Duhamel  and Neuman  and has two physical paradoxes. First, the heat conduction equation of this theory does not include any elastic terms. Second, the heat conduction equation is of a parabolic type, predicting infinite propagation speed of thermal energy. This prediction is a physically unacceptable situation. Biot  developed the classical coupled thermoelasticity (CCTE) theory to resolve the first
The main aim of this paper is to introduce a new fractional-order theory called nonlinear generalized photo-thermoelasticity involving three temperatures. The governing equations of transient thermal stress wave propagation problems associated with this theory are very difficult to solve analytically because of strong nonlinearity. So, we need to develop new numerical techniques for solving such equations. Therefore, we propose a new boundary element technique for solving the governing equations of the proposed theory. The numerical results are depicted graphically to confirm the validity and accuracy of our proposed technique.
A brief summary of this chapter is as follows. Section 1 outlines the background and provides the readers with the necessary information from books and articles for a better understanding of the generalized thermoelastic theories associated with the distributions of three temperature and thermal stress fields. Section 2 describes the formulation of the new theory and its related problems. Section 3 discusses the implementation of the new BEM to obtain the carrier density field. Section 4 studies the implementation of the new BEM for solving the nonlinear radiative heat conduction equation, to obtain the three temperature fields. Section 5 studies the development of the new BEM and its implementation for solving the move equation based on the known three temperature fields, to obtain the displacement field. Section 6 discusses the shape optimization scheme for semiconductor structures. Section 7 presents the new numerical results that describe the BEM results which are in excellent agreement with the FDM and FEM results.
2. Formulation of the problem
We considered the Cartesian coordinates for a semiconductor structure which occupies the region and bounded by a closed surface .
The coupled plasma and thermoelastic wave equations during photothermal process can be written as follows:
The wave equation:
The plasma wave equation:
where , and are the diffusion coefficient, carrier density, equilibrium carrier concentration at temperature , electron relaxation time, and thermal expansion coefficient, respectively. Also, we assumed that .
The two-dimensional three-temperature (2D-3T) radiative heat conduction equations can be expressed as follows:
The total energy of unit mass can be described by
where is mechanical stress tensor; is the density; is the mass force vector; is the displacement vector; is the constant elastic moduli; are the stress-temperature coefficients; are specific heat capacities of electron, ion, and phonon, respectively; are conductive coefficients of electron, ion, and phonon, respectively; is the electron-ion coefficient; is the electron-phonon coefficient; the total temperature , is the recombination term; and is the semiconductor gap energy.
3. BEM solution of carrier density field
In order to construct the integral equation, we use the following Green’s function:
We assume that the solution of Eq. (2) can be written as
which can be written in the following form .
where the minority carrier diffusion length is . Thus after imposing initial conditions and boundary conditions , we have
4. BEM solution of temperature field
By applying the Caputo scheme, we have .
Based on , we can write
To solve Eq. (17), the functions and can be interpolated as
Differentiating Eq. (18) with time, we obtain
Thus, the temperature can be determined from the following system:
where is an unknown matrix and and are known matrices.
5. BEM solution of displacement field
On the basis of the weighted residual method, the differential equations (1) can be transformed to the following integral equations:
which can be written as
This matrix system can be written as follows:
where represents the displacements and represents the tractions.
By using the boundary conditions in Eq. (27), we get
where is an unknown matrix and and are known matrices. We refer the interested readers to Reference  for further details.
6. Shape optimization scheme for semiconductor structures
Two criteria can be implemented during shape optimization of semiconductor structures:
I. The minimum global compliance based on the tractions and boundary displacements
II. The minimum boundary based on the equivalent stresses and the reference stress
where is a natural number.
Based on the boundary displacement and the reference displacement , we can write
which can be used to obtain
The efficiency of the proposed technique has been improved using FFD, GA, and the following nonuniform rational B-spline curve (NURBS):
where are the B-spline basis functions of order o and are the weights of control points .
7. Numerical results and discussion
The efficiency of our numerical modeling technique has been improved using a nonuniform rational B-spline curve (NURBS) to decrease the computation time and the model’s optimized boundary where it reduces the number of control points and provides the flexibility to design a large variety of shapes.
Figure 1 shows the main steps of the genetic algorithm of photo-thermoelastic semiconductor structures.
The design vector is represented by a chromosome which consists of genes :
Thus, genes can be considered as design variables.
The following constraints are also imposed on each gene:
where and are the left and right admissible values of .
The uniform mutation and boundary mutation are implemented, where the uniform mutation operator replaces a gene of the chromosome with the new random value which corresponds to the design parameter as shown in Figure 2 .
The uniform mutation probability determines the gene number which will be modified in each population. The boundary mutation operator is a special case of the uniform mutation. The gene after mutation receives one of the boundary values or as shown in Figure 3 .
The boundary mutation is very useful for boundary element problems in which the solution is on the boundary. The boundary mutation probability determines the gene number which will be modified in each population.
The simple crossover and arithmetical crossover are implemented, where the operator of the simple crossover creates two new chromosomes and from two existing chromosomes selected randomly, and , where both chromosomes are coupled together as shown in Figure 4 .
The simple crossover probability determines the chromosomes number which will be crossing in each population.
The arithmetic crossover operator creates two identical new chromosomes from two existing chromosomes selected randomly, and , where the gene values in the new chromosomes are the arithmetic average of genes of the parents as shown in Figure 5 .
The operator of the cloning increases the probability of survival of the best chromosome by duplicating this one to the next generation. The probability of the cloning decides how many copies of the best chromosome will be in the new generation.
The ranking selection allows chromosomes to survive with a great value of an objective function. The first step of the ranking selection is sorting all the chromosomes according to the value of the objective function. Then on the basis of the position in the population, the probability of survival is attributed to every chromosome by the following formula:
where rank is the chromosome position after sorting, is the probability of survival, and is a selection coefficient.
A shape optimization of the photo-thermoelastic semiconductor structure presented in Figure 6 is considered. Only the parts of the boundary, where the temperature field and the heat flux are prescribed, undergo the shape modification.
The optimal shape of the photo-thermoelastic semiconductor structure for isotropic, transversely isotropic, orthotropic, and anisotropic is presented in Figure 7 . Table 1 contains the genetic algorithm parameters which were applied.
|Design parameter number||5|
|Uniform mutation probability||0.015|
|Boundary mutation probability||0.0075|
|Simple crossover probability||0.075|
|Arithmetic crossover probability||0.075|
The efficiency of our numerical modeling technique has been improved using GA, FFD, and NURBS to decrease the computation time of solving three-temperature photo-thermoelastic problems in semiconductor structures. Due to strong nonlinearity, it is very difficult to solve the problems related to this theory analytically. Therefore, we propose a new boundary element model for our current complex problem. So, the validity and accuracy of the proposed technique were confirmed by comparing graphically the one-dimensional results obtained from BEM with those obtained using the finite difference method (FDM) of Pazera and Jędrysiak  and finite element method (FEM) of Xiong and Tian  which have been reduced as a special case from the current problem. For comparison reasons, the 2D-3T radiative heat conduction is replaced by heat conduction. Figure 8 shows the variations of the temperature and with the time . The differences between time distributions of electron temperature , ion temperature , phonon temperature , and total temperature can be seen from this figure. Figures 9 – 11 show the variations of the thermal stresses , , and with the time . It can be seen from these figures that the BEM results are in excellent agreement with the FDM and FEM results.
The aim of this study is to propose a new theory called nonlinear fractional generalized photo-thermoelasticity involving three temperatures and implement a new boundary element technique for modeling and optimization of the three-temperature nonlinear fractional generalized photo-thermoelastic interaction problems in anisotropic semiconductor structures associated with the proposed theory. This technique is implemented based on genetic algorithm (GA), free-form deformation (FFD) method, and nonuniform rational B-spline curve (NURBS) as the global optimization techniques for solving complex problems associated with the proposed theory. FFD is an efficient and accurate technique for treating optimization problems with complex shapes. In the formulation of the considered problem, solutions are obtained for specific arbitrary parameters which are the control point positions in the considered problem; the profiles of the considered objects are determined by FFD method, where the FFD control points positions are treated as genes; and then the chromosomes profiles are defined with the gene sequence. The population is founded by a number of individuals (chromosomes), where the objective functions of individuals are determined by the BEM. The optimal shape of the photo-thermoelastic semiconductor structure for isotropic, transversely isotropic, orthotropic, and anisotropic is obtained. The proposed technique can be applied to a wide range of modeling and optimization problems related with our proposed theory. The numerical results verify the validity and accuracy of our proposed boundary element technique. Also, the BEM is more powerful and simple to use than the FDM or FEM, because it reduces the computational cost. The present numerical results for our general and complex problem may provide interesting information for mechanical engineers, material science researchers, computer scientists, and designers of semiconductor devices.
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