CAREER: Scalable Approaches for Multiphysics Fluid Simulation
CAREER: Scalable Approaches for Multiphysics Fluid Simulation
批准号:
1943036
负责人:
Amanda Randles
金额:
$49.99万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-04-15 至 2025-03-31
中文摘要
在过去的十年中,我们已经看到了在医疗实践和生物医学研究中使用个性化血流模拟的出现。 这些模型用于帮助设计新的药物,设备和治疗各种疾病。大规模模拟捕捉流体运动以及所包含的颗粒和细胞的相互作用。 这项跨学科的研究将为研究人员创建一个工具,以交互方式修改设备或血管的几何形状或描述细胞的属性,以研究变化如何影响可以改善治疗设计的指标。该项目还将提供一个框架,以促进计算和生物医学工程交叉领域的新教育计划,旨在促进对STEM学位和职业的更广泛兴趣。为了让下一代科学家参与计算建模,该项目旨在(i)为K-12学生开发基于虚拟现实的互动模块,(ii)开发符合标准的中小学课堂课程附加组件,以及(iii)举办实施研讨会,以广泛传播材料和研究结果。拟议的研究计划将开发和建立新的多尺度,多物理场建模技术,使用户能够使用并行流体结构相互作用(FSI)模型,以直观和互动的方式设计新的治疗方法。该计划耦合互补资源,包括虚拟现实和增强现实界面,大规模并行流体模拟和高保真细胞粘附模型。将结合以下关键组成部分:(i)开发一种强大、有效的捕获一系列细胞类型的能力,(ii)在复杂几何形状中初始化高细胞密度的并行方法,以及(iii)用于设计反馈和修改的交互式技术。 由此产生的网络基础设施代表了一种新的和潜在的变革性FSI工程范式,将导致基础知识的进步,更有效的研究技术,增强的临床能力,以及超越生物工程和生物医学领域的跨领域影响。通过开发最先进的、模拟驱动的、几何交互方法所获得的知识将产生广泛的影响,超出项目中所研究的用例。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值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
Over the past decade, we have seen an emergence of the use of personalized blood flow simulations in medical practice and biomedical research. These models are used to help design new drugs, devices, and treatments for a wide range of diseases. Large-scale simulations capture both the fluid movement and the interaction of included particles and cells. This interdisciplinary research will create a tool for researchers to interactively modify the geometry of the device or vessels or properties describing the cells to study how changes influence metrics that can improve treatment design. This project will also provide a framework to facilitate new educational programs at the intersection of computing and biomedical engineering with the goal to promote wider interest in STEM degrees and careers. To engage next generation scientists with computational modeling, the project aims to (i) develop virtual reality-based interactive modules for K-12 students, (ii) develop standards-aligned primary and secondary school classroom curriculum add-ons, and (iii) host implementation workshops to broadly disseminate the material and findings. The proposed research program will develop and establish new multiscale, multiphysics modeling techniques that enable users to use parallel fluid-structure-interaction (FSI) models to design new therapeutics in an intuitive and interactive manner. The program couples complementary resources including virtual reality and augmented reality interfaces, massively parallel fluid simulation, and high-fidelity cellular adhesion models. The following key components will be combined: (i) the development of a robust, efficient capability to capture a range of cell types, (ii) a parallel method to initialize high cell densities in complex geometries, and (iii) interactive techniques for design feedback and modification. The resulting cyberinfrastructure represents a new and potentially transformative FSI engineering paradigm that will lead to advances in fundamental knowledge, more effective research techniques, enhanced clinical capabilities, and cross-cutting impacts that transcend the bioengineering and biomedical fields. The knowledge gained by development of a state-of-the-art, simulation-driven, geometry-interaction methodology will have wide impacts beyond the use cases investigated in the project.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.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1007/978-3-031-08751-6_7
发表时间:
2022
期刊:
Scientific Reports
影响因子:
4.6
作者:
[S. Roychowdhury;E. Draeger;A. Randles]
通讯作者:
S. Roychowdhury;E. Draeger;A. Randles
DOI:
10.1016/j.jocs.2023.102060
发表时间:
2023-05
期刊:
J. Comput. Sci.
影响因子:
--
作者:
[S. Roychowdhury;E. Draeger;A. Randles]
通讯作者:
S. Roychowdhury;E. Draeger;A. Randles
Student Support: IEEE Cluster 2018 Conference
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批准号:1814225
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项目类别:Standard Grant
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资助金额:$2.0万
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财政年份:2018
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负责人:Amanda Randles
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依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位: