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Collaborative Research: CDS&E: Leveraging hardware acceleration for accurate particle dynamics in turbulent flows

合作研究：CDS

基本信息

批准号：
1761683
负责人：
Kyle Niemeyer
金额：
$ 26.14万
依托单位：
Oregon State University
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
起止时间：
2018-08-15 至 2023-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1761683&HistoricalAwards=false
关键词：
Collaborative Research CDS&amp Leveraging hardware

项目摘要

Nanoparticles are present in many aspects of everyday life, from food, drugs, cosmetics, textiles, and wood preservatives to tires, electronics, and engines. Regardless of a nanoparticle's type, its formation, growth, and eventual destruction involves physical processes that lead to distributions of particles of many different shapes and sizes. In most cases, industry wants better means to control the particle distributions; in other cases, the objective is to prevent the formation of particles. Either way, one needs to understand how particles behave and evolve over time to accomplish those goals. This project aims to improve the predictive capabilities of software for simulating the transport and evolution of populations of nanoparticles in complex flow fields (e.g., nanoparticles in a combustion engine). The improved tools developed in this project will benefit the combustion field by enabling better predictions of the formation, growth, and destruction of soot particles. This will support the design of cleaner internal combustion engines, gas turbine engines, and furnaces. Beyond combustion, the tools developed and understanding gained through this project could advance manufacturing by identifying which environmental properties can be leveraged to enhance/trigger certain particles, increase the formation of certain types of particles, or suppress them altogether. Finally, the software to be developed is not limited to solid-oxide nanoparticles and soot. In fact, any dispersed phase of nano- to micro-size materials can be described by the tools developed here, including dispersion of aerosols, dust, charged particles in plasmas, and even "particles" representing large objects in astrophysics. In addition to the scientific objectives of the project, the PIs will engage in public outreach and education efforts, including producing videos explaining computational fluid dynamics for the public, running workshops teaching software skills to researchers, and involving undergraduate students from diverse and underrepresented backgrounds in research. This project will improve the predictive capabilities of numerical frameworks for simulating the transport and evolution of populations of nanoparticles in complex flow fields. The research objectives include: (1) Solving the population balance equation (PBE) for nanoparticle number density functions with no compromise in physical accuracy. The approach provides not only the full distribution of particles but also all their relevant properties; (2) Evaluate a computationally efficient numerical implementation of a coupled flow solver and PBE solver; and (3) Enable new physical and chemical insights into nanoparticle distributions across a wide range of fields by sharing the software developed and working with other research groups. These objectives will be achieved by leveraging the strengths of the underlying computer architectures: using traditional central processing units (CPUs) to solve the flow fields and particle transport, while performing the temporal evolution of the population of particles on graphics processing units (GPUs) using a Monte Carlo solver. The PIs plan to release the NGA software as open source and build a user community around NGA by ensuring that interested researchers are able to contribute to the codebase. This will allow a wider growth of the project. This aspect is of special interest to the software cluster in the Office of Advanced Cyberinfrastructure, which has provided co-funding for this award.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.

纳米颗粒存在于日常生活的许多方面，从食品，药品，化妆品，纺织品和木材防腐剂到轮胎，电子产品和发动机。无论纳米颗粒的类型如何，其形成，生长和最终破坏都涉及导致许多不同形状和尺寸的颗粒分布的物理过程。在大多数情况下，工业需要更好的方法来控制颗粒分布;在其他情况下，目标是防止颗粒的形成。无论哪种方式，都需要了解粒子如何随着时间的推移而行为和进化，以实现这些目标。该项目旨在提高软件的预测能力，用于模拟复杂流场中纳米粒子群体的运输和演变（例如，内燃机中的纳米颗粒）。在这个项目中开发的改进的工具将有利于燃烧领域，使更好地预测的形成，增长和破坏的烟尘颗粒。这将有助于设计更清洁的内燃机、燃气涡轮机和熔炉。除了燃烧之外，通过该项目开发的工具和获得的理解可以通过确定哪些环境特性可以用来增强/触发某些颗粒，增加某些类型颗粒的形成或完全抑制它们来促进制造。最后，要开发的软件不仅限于固体氧化物纳米颗粒和烟灰。事实上，任何纳米到微米尺寸材料的分散相都可以通过这里开发的工具来描述，包括气溶胶，尘埃，等离子体中的带电粒子，甚至是天体物理学中代表大型物体的“粒子”的分散。除了该项目的科学目标外，PI还将参与公共宣传和教育工作，包括为公众制作解释计算流体动力学的视频，举办研讨会，向研究人员教授软件技能，并让来自不同和代表性不足背景的本科生参与研究。该项目将提高数值框架的预测能力，用于模拟复杂流场中纳米粒子群体的运输和演变。研究目标包括：（1）在不损害物理精度的情况下，求解用于纳米颗粒数密度函数的粒子数平衡方程（PBE）。该方法不仅提供了颗粒的完整分布，而且还提供了所有相关属性;（2）评估耦合流求解器和PBE求解器的计算效率数值实现;（3）通过共享开发的软件并与其他研究小组合作，实现对纳米颗粒分布的新的物理和化学见解。这些目标将通过利用底层计算机架构的优势来实现：使用传统的中央处理单元（CPU）来解决流场和粒子传输，同时使用Monte Carlo求解器在图形处理单元（GPU）上执行粒子群的时间演化。 PI计划将NGA软件作为开源发布，并通过确保感兴趣的研究人员能够为代码库做出贡献，围绕NGA建立一个用户社区。这将使该项目得到更广泛的发展。高级网络基础设施办公室（Office of Advanced Cyberinfrastructure）的软件集群对此特别感兴趣，该办公室为该奖项提供了共同资助。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。