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Next-Gen Gas Network Simulation
arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2021-08-05 , DOI: arxiv-2108.02651 Christian Himpe, Sara Grundel, Peter Benner
arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2021-08-05 , DOI: arxiv-2108.02651 Christian Himpe, Sara Grundel, Peter Benner
To overcome many-query optimization, control, or uncertainty quantification
work loads in reliable gas and energy network operations, model order reduction
is the mathematical technology of choice. To this end, we enhance the model,
solver and reductor components of the "morgen" platform, introduced in Himpe et
al [J.~Math.~Ind. 11:13, 2021], and conclude with a mathematically, numerically
and computationally favorable model-solver-reductor ensemble.
中文翻译:
下一代天然气网络模拟
为了克服可靠的天然气和能源网络运营中的多查询优化、控制或不确定性量化工作负载,模型降阶是首选的数学技术。为此,我们增强了“morgen”平台的模型、求解器和还原器组件,在 Himpe 等人 [J.~Math.~Ind. 11:13, 2021],并以数学上、数值上和计算上有利的模型-求解器-还原器集合作为结论。
更新日期:2021-08-07
中文翻译:
下一代天然气网络模拟
为了克服可靠的天然气和能源网络运营中的多查询优化、控制或不确定性量化工作负载,模型降阶是首选的数学技术。为此,我们增强了“morgen”平台的模型、求解器和还原器组件,在 Himpe 等人 [J.~Math.~Ind. 11:13, 2021],并以数学上、数值上和计算上有利的模型-求解器-还原器集合作为结论。