A computational inverse technique for material characterization of a functionally graded cylinder using a progressive neural network
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In order to exploit an inverse problem solver in the magnetostatic fields, a new formulation of the inverse problems is proposed in this paper. As a result, it is shown that all of the inverse problems in magnetostatic fields can be reduced to find the position and magnitude of field source. By combining this new formulation, the finite-element method, and the artificial intelligence technique, we work out a general purpose inverse problem solver in the magnetostatic fields. Intensive tests of this solver suggest that the ability of this solver is depending greatly on the available data base. This solver is now applied to find a source position of the human eye fields. As a result, a plausible source position of the human eye fields can be estimated.
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A new theorem of inverse formula is introduced for a kind of infinite series. Thus some new results for important inverse problems in physics are presented in this paper. These are the inverse problems for obtaining the phonon density of states, the inverse blackbody radiation problem for remote sensing, and the solution for inverse Ewald summation. Of more importance, it shows the possibility of the application of number theory to physical problems.
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Electromagnetic forward and inverse solvers are considered for the analysis and design of electromagnetic metasur-faces. This paper reviews (i) a forward solver that takes the surface susceptibilities of metasurfaces and calculates their scattered fields and (ii) an inverse solver that takes user-defined desired power patterns and outputs the required metasurface properties. An omega-bianisotropic transmitting metasurface is then fabricated and measured to evaluate the performance of these forward and inverse solvers.
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<p>Electromagnetic forward and inverse solvers are considered for the analysis and design of electromagnetic metasurfaces. This paper reviews (i) a forward solver that takes the surface susceptibilities of metasurfaces and calculates their scattered fields and (ii) an inverse solver that takes user-defined desired power patterns and outputs the required metasurface properties. An omega-bianisotropic transmitting metasurface is then fabricated and measured to evaluate the performance of these forward and inverse solvers.</p>
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<p>Electromagnetic forward and inverse solvers are considered for the analysis and design of electromagnetic metasurfaces. This paper reviews (i) a forward solver that takes the surface susceptibilities of metasurfaces and calculates their scattered fields and (ii) an inverse solver that takes user-defined desired power patterns and outputs the required metasurface properties. An omega-bianisotropic transmitting metasurface is then fabricated and measured to evaluate the performance of these forward and inverse solvers.</p>
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A procedure for the experimental convergence evaluation of a hydraulic-network solver is proposed, based on using genetic algorithms to search for network parameter values that maximize the number of iterations of the hydraulic-network solver under test. The efficiency of the method is demonstrated by the example of convergence evaluation for the EPANET hydraulic simulator. Examples of a pipe network and of combinations of parameter values for which the static solver of the simulator fails to converge in a reasonable number of iterations are given. The features of the EPANET 2.00.12 solver responsible for loss of convergence are discussed. New criteria for the automatic start of solution damping aimed at improving the convergence of the solver are proposed. The better convergence of the EPANET solver modified in accordance with these criteria is confirmed by the random and the proposed search-based testing method.
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Some examples of inverse problem approach of the phenomena related to materials are introduced. What is the inverse problem?, what could be obtained, identified or estimated by an inverse approach? are discussed based on the inverse processing of elastic waves. Some problems and uncectainities involved in inverse processing are also discussed.
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