发明授权
- 专利标题: Multiphase physical transport modeling method and modeling system
- 专利标题(中): 多相物理传输建模方法和建模系统
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申请号: US12555771申请日: 2009-09-08
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公开(公告)号: US08396693B2公开(公告)日: 2013-03-12
- 发明人: George Danko
- 申请人: George Danko
- 申请人地址: US NV Reno
- 专利权人: Board of Regents of the Nevada System of Higher Education, on behalf of the University of Nevada, Reno
- 当前专利权人: Board of Regents of the Nevada System of Higher Education, on behalf of the University of Nevada, Reno
- 当前专利权人地址: US NV Reno
- 代理机构: UNR-DRI Technology Transfer Office
- 代理商 Ryan A. Heck
- 主分类号: G06F17/10
- IPC分类号: G06F17/10
摘要:
A general, computational-mathematical modeling method for the solution of large, boundary-coupled transport problems involving the flow of mass, momentum, energy or subatomic particles is disclosed. The method employs a modeling processor that extracts a matrix operator equation (or set of equations) from a numerical transport code (NTC). The outputs of software codes, available for modeling physical problems governed by conservation laws in the form of differential equations, can be processed into closed-form operator equations with the method. Included is a numerical transport code functionalization (NTCF) model which can be determined numerically, based on a system of solutions of an NTC, evaluating outputs for a given set of inputs. The NTCF model is a linear or nonlinear, multi-variable operator equation or set of such equations. The NTCF model defines relationships between general, time-variable inputs and outputs, some known and some unknown, considered as boundary values. The user of an NTCF model can directly work with the processed model output, instead of running the original numerical code in general applications of a boundary-value problem. The numerical transport code functionalization model can be employed as a surrogate for representing the numerical transport code to provide a solution to the transport problem. The invention enables modeling efficiency and availability to be increased, while computational complexity and cost decreased. Computational times for complex modeling problems can, in some cases, be dramatically reduced, for example by several orders of magnitude.
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