【摘 要】
：
We propose a general-purpose algorithm and computational code for the solution of Partial Differential Equations(PDEs)on random geometry and with random par
【机 构】
：
KAUSTKINGABDULLAHUniv.OFSci.&Tech.
论文部分内容阅读
We propose a general-purpose algorithm and computational code for the solution of Partial Differential Equations(PDEs)on random geometry and with random parameters.
其他文献
The discretization error for conforming simplicial finite elements is estimated by computing a function in an auxiliary subspace.The corresponding error est
The focus of the collaborative research center TRR154,supported by the German science foundation,is to study the optimization of gas transport networks and
The European gas supply is characterized by a variety of sources of supply,high import dependency,numerous market actors along the value chain and different
The MODAL GasLab(Mathematical Optimization and Data Analysis Laboratories)brings state-of-the-art mathematical optimization methods into practice in the gas
In 2008 OGE,Germanys largest gas transport system operator,initiated the Research Cooperation Network Optimization due to the challenges imposed by new regu
About 25 Talk 1: Evaluating gas network capacities Prof.Dr.Thorsten Koch,TU-Berlin,koch@zib.de In 2008 Open Grid Europe,Germanys largest gas transport syste
Tensor-train(TT)decompositions can enable dramatic compression of arrays arising from discretizations of high dimensional functions.In many applications,how
This talk is concerned with low-rank approximations of solution manifolds of parametric diffusion equations,with a particular focus on the case of piecewise
We apply Tensor Train approximation to solve stochastic elliptic PDE with stochastic Galerkin discretization.We compare two strategies of the polynomial cha
This talk concerns a low-rank approximation method for the model reduction of non-linear parametric dynamical systems.The proposed approach combines the con