A Concept to Eliminate the Meshing Bottleneck During the Design and Analysis of Fluid Systems
A Concept to Eliminate the Meshing Bottleneck During the Design and Analysis of Fluid Systems
批准号:
1825991
负责人:
Jason Hicken
金额:
$31.2万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-09-01 至 2022-08-31
中文摘要
许多对美国经济、国防和国民健康至关重要的系统的正常运行取决于流体的流动(即液体或气体的流动)。这类系统的例子包括商用和军用飞机、汽车发动机、风力涡轮机和心脏泵。流体系统的特点是不直观的物理特性,这使得它们的设计变得格外困难。在缺乏实验数据和工程经验的非常规流体系统的概念设计过程中,这一困难尤为尖锐。原则上,工程师可以使用数值模拟来分析创新的流体系统,但高保真模拟在概念设计中的应用有限。为什么?流动模拟通常依赖于网格,网格将流体占据的区域划分为许多较小的体积,为复杂的几何形状生成高质量的网格仍然是一个耗时的人在回路中的过程。这项研究将探索一种全新的方法来缓解啮合瓶颈,从而改进流体系统的设计过程。项目成果将包括新的算法和算法的原型实现,这些算法将在在线储存库中提供。该研究项目将研究一种新的浸没边界方法及其在设计优化中的应用。关键的洞察力是将浸没边界方法框架化为反问题。其思想是在几何体内部引入体力或表面通量,其作用类似于施加边界条件的控制变量。这种控制的最优值是通过求解一个偏微分方程约束反问题来确定的。这种方法对于概念设计过程中的流体系统分析很有吸引力,因为计算网格不需要与几何形状一致。此外,与大多数浸没边界方法不同,该项目的方法仍然是精确的,并且与高阶离散化兼容。为了评估这个概念的潜力,该项目将调查几个关键问题:在可选的反问题公式中,哪一个是最好的?这个问题应该如何正规化?我们如何有效地解决反问题?当这个概念应用于不完美的CAD几何图形时,它的健壮性和精确度如何?那么,如何使用该方法来推进形状优化算法?该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The proper function of many systems vital to the United States' economy, defense, and national health depend on fluid flow (i.e., the flow of a liquid or gas). Examples of such systems include commercial and military aircraft, automobile engines, wind turbines, and heart pumps. Fluid systems are characterized by unintuitive physics, which makes them exceptionally difficult to design. This difficulty is particularly acute during the conceptual design of unconventional fluid systems, for which experimental data and engineering experience is lacking. In principle, engineers could use numerical simulations to analyze innovative fluid systems, but high-fidelity simulations have found limited use during conceptual design. Why? Flow simulations typically rely on meshes, which divide the region occupied by the fluid into many smaller volumes, and generating high-quality meshes for complex geometries remains a time-consuming, human-in-the-loop process. This research will investigate a fundamentally new approach to mitigate the meshing bottleneck and thereby improve the fluid system design process. Project outcomes will include novel algorithms and prototype implementations of the algorithms that will be made available in an online repository. The research project will study a novel immersed-boundary method and its application to design optimization. The key insight is to frame the immersed-boundary method as an inverse problem. The idea is to introduce a body force, or surface flux, interior to the geometry that acts like a control variable to impose the boundary conditions. The optimal value for this control is determined by solving a partial-differential-equation constrained inverse problem. This approach is attractive for the analysis of fluid systems during conceptual design, because the computational mesh does not need to conform to the geometry. Furthermore, unlike most immersed-boundary methods, this project's approach remains accurate and is compatible with high-order discretizations. To assess the potential of the concept, the project will investigate several critical questions: among alternative inverse-problem formulations, which one is the best? How should the problem be regularized? How do we solve the inverse problem efficiently? How robust and accurate is the concept when applied to imperfect CAD geometries? And, how can the method be used to advance shape optimization algorithms?This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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DOI:
10.2514/6.2022-1862
发表时间:
2022
期刊:
AIAA SciTech Forum
影响因子:
--
作者:
[Hicken, Jason E., Kaur, Sharanjeet]
通讯作者:
Kaur, Sharanjeet
DOI:
10.1002/fld.4816
发表时间:
2020
期刊:
International Journal for Numerical Methods in Fluids
影响因子:
1.8
作者:
[Yan, Jianfeng, Hicken, Jason E.]
通讯作者:
Hicken, Jason E.
Immersed Boundary Method as an Inverse Problem
作为反问题的浸入边界法
DOI:
10.2514/6.2018-4162
发表时间:
2018
期刊:
2018 AIAA Fluid Dynamics Conference
影响因子:
--
作者:
[Yan, Jianfeng, Hicken, Jason E.]
通讯作者:
Hicken, Jason E.
DOI:
10.2514/6.2021-1939
发表时间:
2020-01
期刊:
AIAA Scitech 2021 Forum
影响因子:
--
作者:
[Sharanjeet Kaur;Jason E. Hicken]
通讯作者:
Sharanjeet Kaur;Jason E. Hicken
CAREER: Simulation-Enhanced Virtual Design Environments for Fluid Systems
-
批准号:1554253
-
项目类别:Standard Grant
-
资助金额:$50.0万
-
财政年份:2016
-
负责人:Jason Hicken
-
依托单位:
Enabling Multidisciplinary Design Optimization: Inexact-Newton-Krylov and the Individual-Discipline-Feasible Formulation
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批准号:1332819
-
项目类别:Standard Grant
-
资助金额:$30.3万
-
财政年份:2013
-
负责人:Jason Hicken
-
依托单位:
海外基金