作者：
Ying YangBenzhuo LuDepartment of Computational Science and Mathematics
Guilin University of Electronic TechnologyGuilin 541004GuangxiChina LSEC
Institute of Computational Mathematics and Scientific/Engineering Computingthe National Center for Mathematics and Interdisciplinary SciencesAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China
Poisson-Nernst-Planck equations are a coupled system of nonlinear partial differential equations consisting of the Nernst-Planck equation and the electrostatic Poisson equation with delta distribution sources,which de...
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Poisson-Nernst-Planck equations are a coupled system of nonlinear partial differential equations consisting of the Nernst-Planck equation and the electrostatic Poisson equation with delta distribution sources,which describe the electrodiffusion of ions in a solvated biomolecular *** this paper,some error bounds for a piecewise finite element approximation to this problem are *** numerical examples including biomolecular problems are shown to support our analysis.
Sensitivity analysis (SA) is a fundamental tool of uncertainty quantification(UQ). Adjoint-based SA is the optimal approach in many large-scale applications, such as the direct numerical simulation (DNS) of combustion...
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Sensitivity analysis (SA) is a fundamental tool of uncertainty quantification(UQ). Adjoint-based SA is the optimal approach in many large-scale applications, such as the direct numerical simulation (DNS) of combustion. However, one of the challenges of the adjoint workflow for time-dependent applications is the storage and I/O requirements for the application state. During the time-reversal portion of the workflow, forward state is required in last-in-first-out order. The resulting requirements for storage at exascale are enormous. To mitigate this requirement, application state is regenerated from checkpoints over short windows of application time. This approach drastically reduces the total volume of stored data, allows the caching of state in the regeneration window in memory and on local SSDs, may accelerate the application execution by reducing output frequency, and reduces the power overhead from I/O. We explore variations to this workflow, applied to a proxy for the SA of turbulent combustion, by varying checkpoint number, state storage, and other regeneration options to find efficient implementations for minimizing compute time or power consumption.
This paper aims to study feasible Barzilai-Borwein (BB)-like methods for extreme symmetric eigenvalue problems. For the two-dimensional case, we establish the local superlinear convergence result of FLBB, FSBB, FABB, ...
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We propose a new nonoverlapping domain decomposition preconditioner for the discrete system arising from the edge element discretization of the three-dimensional Maxwell's equations. This preconditioner uses the s...
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In this paper, we propose a new trust region affine scaling method for nonlinear programming with simple bounds. Our new method is an interior-point trust region method with a new scaling technique. The scaling matrix...
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A new system is generated from a multi-linear form of a （2＋1）- dimensional Volterra system. Though the system is only partially integrable and needs additional conditions to possess two-soliton solutions, its （1＋...
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A new system is generated from a multi-linear form of a （2＋1）- dimensional Volterra system. Though the system is only partially integrable and needs additional conditions to possess two-soliton solutions, its （1＋1）- dimensional reduction gives an integrable equation which has been studied via reduction skills. Here, we give this （1＋1）-dimensional reduction a simple bilinear form, from which a Backlund transformation is derived and the corresponding nonlinear superposition formula is built.
In this paper,we consider the positive semi-definite space tensor cone constrained convex program,its structure and *** study defining functions,defining sequences and polyhedral outer approximations for this positive...
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In this paper,we consider the positive semi-definite space tensor cone constrained convex program,its structure and *** study defining functions,defining sequences and polyhedral outer approximations for this positive semidefinite space tensor cone,give an error bound for the polyhedral outer approximation approach,and thus establish convergence of three polyhedral outer approximation algorithms for solving this *** then study some other approaches for solving this structured convex *** include the conic linear programming approach,the nonsmooth convex program approach and the bi-level program *** numerical examples are presented.
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