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Implicit solution of large-scale radiation - material energy transfer problems

Peter N. Brown, Bao Rong Chang, Frank R. Graziani, Carol S. Woodward

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Abstract

Modeling of radiation-diffusion processes has traditionally been accomplished through simulations based on decoupling and linearizing the basic physics equations. By applying these techniques, physicists have simplified their model enough that problems of moderate sizes could be solved. However, new applications demand the simulation of larger problems for which the inaccuracies and nonscalability of current algorithms prevent solution. Recent work in iterative methods has provided computational scientists with new tools for solving these problems. In this paper, we present an algorithm for the implicit solution of the multi- group diffusion approximation coupled to an electron temperature equation. This algorithm uses a stiff ODE solver coupled with Newton's method for solving the implicit equations arising at each time step. The Jacobian systems are solved by applying GMRES preconditioned with a semicoarsening multigrid algorithm. By combining the nonlinear Newton iteration with a multigrid preconditioner, we take advantage of the fast, robust nonlinear convergence of Newton's method and the scalability of the linear multigrid method. Numerical results show that the method is accurate and scalable.

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Modeling of radiation-diffusion processes has traditionally been accomplished through simulations based on decoupling and linearizing the basic physics equations. By applying these techniques, physicists have simplified their model enough that problems of moderate sizes could be solved. However, new applications demand the simulation of larger problems for which the inaccuracies and nonscalability of current algorithms prevent solution. Recent work in iterative methods has provided computational scientists with new tools for solving these problems. In this paper, we present an algorithm for the implicit solution of the multi- group diffusion approximation coupled to an electron temperature equation. This algorithm uses a stiff ODE solver coupled with Newton's method for solving the implicit equations arising at each time step. The Jacobian systems are solved by applying GMRES preconditioned with a semicoarsening multigrid algorithm. By combining the nonlinear Newton iteration with a multigrid preconditioner, we take advantage of the fast, robust nonlinear convergence of Newton's method and the scalability of the linear multigrid method. Numerical results show that the method is accurate and scalable.

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Available abstract

Modeling of radiation-diffusion processes has traditionally been accomplished through simulations based on decoupling and linearizing the basic physics equations. By applying these techniques, physicists have simplified their model enough that problems of moderate sizes could be solved. However, new applications demand the simulation of larger problems for which the inaccuracies and nonscalability of current algorithms prevent solution. Recent work in iterative methods has provided computational scientists with new tools for solving these problems. In this paper, we present an algorithm for the implicit solution of the multi- group diffusion approximation coupled to an electron temperature equation. This algorithm uses a stiff ODE solver coupled with Newton's method for solving the implicit equations arising at each time step. The Jacobian systems are solved by applying GMRES preconditioned with a semicoarsening multigrid algorithm. By combining the nonlinear Newton iteration with a multigrid preconditioner, we take advantage of the fast, robust nonlinear convergence of Newton's method and the scalability of the linear multigrid method. Numerical results show that the method is accurate and scalable.

Key concepts: Multigrid method, Generalized minimal residual method, Solver, Preconditioner, Newton's method, Jacobian matrix and determinant, Nonlinear system, Iterative method

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