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Simulation of neutron radiation damage in silicon semiconductor devices

Hoekstra, Robert J.; Castro, Joseph P.; Shadid, John N.; Fixel, Deborah A.

A code, Charon, is described which simulates the effects that neutron damage has on silicon semiconductor devices. The code uses a stabilized, finite-element discretization of the semiconductor drift-diffusion equations. The mathematical model used to simulate semiconductor devices in both normal and radiation environments will be described. Modeling of defect complexes is accomplished by adding an additional drift-diffusion equation for each of the defect species. Additionally, details are given describing how Charon can efficiently solve very large problems using modern parallel computers. Comparison between Charon and experiment will be given, as well as comparison with results from commercially-available TCAD codes.

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Developing a computationally efficient dynamic multilevel hybrid optimization scheme using multifidelity model interactions

Castro, Joseph P.; Gray, Genetha A.; Giunta, Anthony A.; Hough, Patricia D.

Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and groundwater remediation.

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On the Development of a Java-Based Tool for Multifidelity Modeling of Coupled Systems: LDRD Final Report

Gardner, David R.; Castro, Joseph P.; Hennigan, Gary L.; Young, Michael F.

This report describes research and development of methods to couple vastly different subsystems and physical models and to encapsulate these methods in a Java{trademark}-based framework. The work described here focused on developing a capability to enable design engineers and safety analysts to perform multifidelity, multiphysics analyses more simply. In particular this report describes a multifidelity algorithm for thermal radiative heat transfer and illustrates its performance. Additionally, it describes a module-based computer software architecture that facilitates multifidelity, multiphysics simulations. The architecture is currently being used to develop an environment for modeling the effects of radiation on electronic circuits in support of the FY 2003 Hostile Environments Milestone for the Accelerated Strategic Computing Initiative.

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16 Results
16 Results