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，从食物，毒品，化妆品，纺织品和木材防腐剂到轮胎，电子和发动机。不管纳米颗粒类型如何，其形成，生长和最终破坏都涉及物理过程，从而导致许多不同形状和大小的颗粒分布。在大多数情况下，行业希望更好地控制粒子分布。在其他情况下，目的是防止颗粒的形成。无论哪种方式，人们都需要了解粒子如何随着时间的流逝而发展和进化，以实现这些目标。该项目旨在提高软件的预测能力，以模拟复杂流场中纳米颗粒种群的运输和演变（例如，燃烧引擎中的纳米颗粒）。该项目中开发的改进工具将通过更好地预测烟灰颗粒的形成，生长和破坏，从而使燃烧场受益。这将支持更清洁的内燃机，燃气轮机发动机和熔炉的设计。除了燃烧之外，通过该项目获得的工具可以通过确定可以利用哪些环境特性来增强/触发某些颗粒，增加某些类型的粒子的形成或完全抑制它们，从而推动制造生产。最后，要开发的软件不限于固体氧化纳米颗粒和烟灰。实际上，可以通过此处开发的工具来描述纳米至微型材料的任何分散相，包括气溶胶的分散，灰尘，等离子体中的带电颗粒，甚至代表天体物理学中大物体的“颗粒”。除了该项目的科学目标外，PIS还将从事公众的宣传和教育工作，包括制作视频为公众解释计算流体动力学，向研究人员开展研讨会教授软件技能，并参与来自多元化和代表性不足背景的本科生。该项目将提高数值框架的预测能力，以模拟复杂流场中纳米颗粒种群的运输和演变。研究目标包括：（1）解决纳米颗粒数密度功能函数的种群平衡方程（PBE），而身体准确性没有妥协。该方法不仅提供了粒子的完整分布，还提供了所有相关特性。（2）评估耦合流求解器和PBE求解器的计算有效的数值实现；（3）通过共享开发的软件并与其他研究小组合作，对纳米颗粒分布进行了新的物理和化学见解。这些目标将通过利用基础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求解器执行图形处理单元（GPU）上粒子种群的时间演化。 PIS计划通过确保感兴趣的研究人员能够为代码库做出贡献，以将NGA软件作为开源并建立NGA周围的用户社区。这将允许该项目的更大增长。这一方面是高级网络基础设施办公室的软件集群特别感兴趣的，该奖项为该奖项提供了共同的资金。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识分子优点和更广泛的影响评估标准来通过评估来获得支持的。