SBIR Phase I: Theory and Simulation of Strongly Anisotropic Turbulence: Applications to Separation and Purification Technology

SBIR 第一阶段：强各向异性湍流理论与模拟：在分离纯化技术中的应用

• 批准号: 9560876
• 负责人: Ilya Staroselsky
• 金额: $ 7.5万
• 依托单位: Cambridge Hydrodynamics Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-02-01 至 1996-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9560876&HistoricalAwards=false
• 关键词: SBIR; Phase; Theory; Simulation; Strongly

9560876 Staroselsky This Small Business Innovation Research Phase I project will capitalize upon the success of the renormalization group (RNG)-based turbulence models recently developed by Cambridge Hydrodynamics in order to develop an effective approach to predict the behavior of difficult, highly anisotropic turbulent flows often encountered in chemical engineering devices. Although existing RNG models have already demonstrated superior performance in physical situations where the anisotropy of turbulence scales is moderate, they require an extension to handle significant body forces due to high swirl, buoyancy, etc. The primary technical objectives include the extension of RNG two-equation models to a tensorial framework to handle significant small-scale anisotropy induced by high swirl. These models will then be tested and refined on a variety of prototype cases. Finally, proof-of-concept studies of separation and/or purification devices will be performed followed by detailed comparisons with experimental data and alternative prediction techniques. If Phase II is approved, the models will be extended to handle other sources of anisotropy such as strong stratification effects. The final product of the Phase I-III effort will be a commercially viable design and analysis tool for chemical engineering applications which should yield a major improvement in the confidence level for flow prediction in complex real-world devices. The prediction of the behavior of advanced separation and purification devices remains a difficult problem. The work proposed here will replace empirical estimation by predictive capability and should find wide applications throughout chemical engineering. The implementation of Cambridge HydrodynamicsO new models in the commercially viable computer code FLUENT, marketed by our Phase III partner Fluent, Inc., will ensure wide application of project results.

9560876 Staroselsky 这个小型企业创新研究第一阶段项目将利用剑桥流体动力学最近开发的基于重正化群 (RNG) 的湍流模型的成功，以开发一种有效的方法来预测困难的、高度各向异性的湍流的行为。在化学工程装置中遇到。尽管现有的 RNG 模型已经在湍流尺度各向异性适中的物理情况下表现出优越的性能，但它们需要扩展以处理由于高涡流、浮力等而产生的巨大体积力。主要技术目标包括扩展 RNG 的二方程模型到张量框架，以处理由高涡流引起的显着的小尺度各向异性。然后，这些模型将在各种原型案例上进行测试和改进。最后，将进行分离和/或纯化装置的概念验证研究，然后与实验数据和替代预测技术进行详细比较。如果第二阶段获得批准，这些模型将扩展到处理其他各向异性来源，例如强分层效应。 I-III 阶段工作的最终产品将是一种用于化学工程应用的商业上可行的设计和分析工具，这将大大提高复杂现实设备中流量预测的置信度。 先进分离和纯化装置的行为预测仍然是一个难题。这里提出的工作将通过预测能力取代经验估计，并且应该在整个化学工程中得到广泛的应用。 Cambridge HydrodynamicsO 新模型在商业上可行的计算机代码 FLUENT 中的实施（由我们的第三阶段合作伙伴 Fluent, Inc. 销售）将确保项目结果的广泛应用。