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Robust and Efficient High Order Methods for Time Dependent Problems

Robust and Efficient High Order Methods for Time Dependent Problems
针对瞬态问题的稳健且高效的高阶方法
批准号:
1522593
负责人:
Xiangxiong Zhang
金额:
$19.69万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2019-08-31

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中文摘要
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英文摘要
Robust and efficient high order accurate methods for computation have gained more and more popularity in the numerical modeling of real world problems for their ability to produce high fidelity simulations. However, such methods are not available or not well understood for hydrodynamics equations modeling high speed flows in spacecraft design, combustion, detonation, astrophysical jets, hurricanes, tsunamis, plasma dynamics, and inertial confinement fusion. This research project aims to develop improved numerical methods for simulation of these systems. Progress in designing robust and more efficient high order methods will significantly impact on simulation technology for such applications. The state of high order accurate numerical methods is still far from being practically satisfactory for time-dependent nonlinear problems. Compared to their low order counterparts, high order methods are much harder to stabilize and might be less efficient in practice due to much larger computer memory cost. Thus it remains challenging to utilize a high order accurate method to solve nonlinear hydrodynamics equations in real world problems. The objective of this proposal is to address these real-world problem challenges from specific perspectives. First of all, one would like to ensure the robustness of Eulerian schemes by preserving certain invariances of physical quantities such as positivity. Second, one would like to design more efficient implementations of very high order schemes on curved elements for complex geometries.
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Efficient Neural Network Based Numerical Schemes for Hyperbolic Conservation Laws
  • 批准号:
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 项目类别:
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  • 资助金额:
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  • 财政年份:
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  • 负责人:
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  • 依托单位:
海外基金