In this paper, based on the Rayleigh quotient and its generalized Rayleigh quotient, two treatments are developed to solve the complex eigenvalue problems, which arise from the analysis of the optical wave propagation in Slab waveguides with some perfectly matched layers. Numerical examples illustrate that these treatments are efficient and feasible, and the generalized Rayleigh quotient method is better than the Rayleigh quotient method for some eigenvalues with smaller norm.
In this paper, an efficient numerical method is developed to solve the one-dimensional inverse nonlinear heat conductivity problem (INHCP). The method is proven absolute stability. It is more efficiently applied to determine the inner heat conductivity distribution by the measured surface temperature signals of some materials, such as semiconductor, steel, etc.
In this paper, a local marching numerical method is developed to solve the one-dimensional inverse nonlinear heat conductivity problem (INHCP). Numerical analysis shows that the method has absolute stability. It can be more efficiently applied to efficiently determine the heat conductivity distribution by some measured surface temperature signal of some materials, such as semiconductor, steel, and so on.
In this paper, based on the Rayleigh Quotient Iteration method, a new treatment is developed to solve the complex eigenvalue problems, which arise from the analysis of the optical wave propagation in Slab waveguides with some perfectly matched layers. Numerical examples illustrate that this treatment is more efficient and feasible. It can be widely applied to the numerical calculation of optical wave propagation in open waveguides.
Photoacoustic measurement techniques can be used to determine thermal properties on and below the sample's surface, thus subsurface thermal inhomogeneities, such as continuous distributions of thermal parameters, become measurable by photoacoustic methods. In this paper, a numerical reconstruction treatment of thermal conductivity depth distribution is provided. Some simulation examples show that the method can be used in inverse computation of thermal conductivity by surface modulated photoreflectance signals.
In this paper, for an inhomogeneous material in which the thermal conductivity is varied as a function of depth, we propose an efficient method to inversely compute the depth distribution of optical-absorption coefficient by the surface temperature of the material. The results of inverse computation by a group of surface temperature data show that some more accurate optical- absorption coefficients can be obtained.
In this paper, for the solid sample composed of three layers in which the thermal property is inhomogeneous and tho optical-absorption coefficient is varied, a new and effective numerical method is proposed, and it is used to nondestructively reconstruct the depth distribution of optical-absorption coefficient in multilayer inhomogeneous material through by the photothermal signal which are measured on the surface of a sample with the photothermal method. By means of the relation between absorption coefficient and nitrogen concentration, we may obtain the spatial distribution of the nitrogen concentration in a GaP:N sample. Inverse results by experimental data show that the performance of the approach at p/n junction is better.
In our paper, a theoretical treatment which includes a new and effective numerical method is proposed. It is used to nondestructively reconstruct the depth distribution of optical absorption coefficient in multilayer inhomogeneous material, through by the photothermal signal which is related to the surface temperature of a sample and measured with the photothermal method. Numerical simulations demonstrate the performance of the approach is better.
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