SBIR Phase II: Hybrid Lattice Boltzmann Technique for Heat Transfer Prediction

SBIR 第二阶段：用于传热预测的混合格子玻尔兹曼技术

• 批准号: 0239176
• 负责人: Ilya Staroselsky
• 金额: $ 50万
• 依托单位: Exa Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-02-15 至 2007-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0239176&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Hybrid; Lattice; SBIR; Phase; II; Hybrid; Lattice

This Small Business Innovation Research (SBIR) Phase II project will produce a unique computational tool for heat transport prediction in industrial devices by hybridizing our Digital Physics technology based on Lattice Boltzmann Methods (LBM) for hydrodynamics with efficient partial differential equation (PDE) solution for heat transfer. The project will start with the development and implementation of a wide range of physical features including variable thermodynamic and kinetic molecular properties as well as flow dependent turbulent/transitional Prandtl number, followed by introducing algorithms that ensure stable, accurate, and noiseless performance of the full-physics LBM/PDE algorithm. Upon algorithm optimization and benchmarking, we will focus on full thermal studies of industrial devices provided by our commercial customers. These beta tests will be followed by Phase III commercialization. The hybrid thermal transport prediction tool for development in this Phase II SBIR project will open major new commercial markets for our current PowerFLOW product, especially at the engineering design level, as well as open important new markets for novel technologies in various industrial problems ranging from classical macroscopic flows to microscopic flows like those in MEMS devices. This new technology should also establish new markets for computer aided engineering (CAE), especially in manufacturing industries.

这项小型企业创新研究（SBIR）第二阶段项目将通过基于晶格Boltzmann方法（LBM）与有效的部分微分方程（PDE）解决方案融合我们的数字物理技术来生产一种独特的计算工具，用于工业设备中的热传输预测。该项目将从各种物理特征的开发和实施开始，包括可变的热力学和动力学分子特性以及依赖流动性的湍流/过渡性prandtl数字，然后引入算法，以确保稳定，准确，准确且无噪声且无噪声且无噪声性能LBM/PDE Algorithm。通过算法优化和基准测试，我们将专注于商业客户提供的工业设备的全面热研究。这些Beta测试将进行III期商业化。在此II阶段SBIR项目中，用于开发的混合热运输预测工具将为我们当前的PowerFlow产品开放主要的新商业市场，尤其是在工程设计水平上，以及开放的重要新市场，用于各种工业问题的新型新市场，范围从经典的宏观流到Mems Decestices中的微观流程，包括经典的宏观流程。这项新技术还应为计算机辅助工程（CAE）建立新的市场，尤其是在制造业中。