SBIR Phase I: Rapid and Accurate Multi-Variable Optimization Software for Arrays of Heat Sinks

SBIR 第一阶段：快速、准确的散热器阵列多变量优化软件

• 批准号: 1819580
• 负责人: Georgios Karamanis
• 金额: $ 22.5万
• 依托单位: TRANSPORT PHENOMENA TECHNOLOGIES
• 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: 2018-06-15 至 2020-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1819580&HistoricalAwards=false
• 关键词: SBIR; Phase; Rapid; Accurate; Multi

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to reduce the power required to cool the data and telecommunications centers that drive the internet age. Currently nearly 2.0% of the energy consumed in the United States is used to run such data centers and, often, half of this is used for cooling. The corresponding greenhouse gas emissions will also be reduced. Longer term this technology can be adapted to increasing the efficiency of air-conditioning/refrigeration and power generation. Commercially, the computational fluid dynamics software market the product will compete in is projected to grow from $1.3 billion at present to over $2 billion by 2022. It will also stimulate the growth of the manufacture of specialty heat sinks with optimal geometries for efficient thermal management.This intellectual merit of this SBIR Phase I project is based on proposing to hybridize three common numerical methods, i.e., computational fluid dynamics (CFD), flow network modeling (FNM) and multi-variable optimization (MVO), a non-trivial objective. The result will be a software platform that can accurately and simultaneously optimize the geometry of an array of heat sinks found in various types of circuit packs, e.g., blade servers in data centers. This is not possible with CFD alone as it is too slow and it is not possible with FNM alone as it is not sufficiently accurate. The method of the hybrid approach to preserve the accuracy of CFD is to embed pre-computed, non-dimensional look-up tables of flow and thermal resistances from CFD simulations in an FNM. The software will accommodate both single-phase flows of air and water and evaporating/boiling flows of water and refrigerant, which requires modeling complex heat, mass and momentum transport phenomena. Experiments will validate its accuracy on thermal mock-ups of circuit packs.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.

这个小型企业创新研究（SBIR）项目的更广泛的影响/商业潜力是减少驱动互联网时代的数据和电信中心冷却所需的电力。目前，美国近2.0%的能源消耗用于运行此类数据中心，其中一半用于冷却。相应的温室气体排放也将减少。从长远来看，这项技术可以用于提高空调/制冷和发电的效率。在商业上，该产品将竞争的计算流体动力学软件市场预计将从目前的13亿美元增长到2022年的20亿美元以上。它还将刺激具有最佳几何形状的专用散热器的生产增长，以实现有效的热管理。SBIR第一阶段项目的这一智力优势是基于提出混合三种常见的数值方法，即，计算流体动力学（CFD）、流网络建模（FNM）和多变量优化（MVO），一个非平凡的目标。其结果将是一个软件平台，可以准确地和同时优化在各种类型的电路包中发现的散热器阵列的几何形状，例如，数据中心的刀片服务器。这是不可能的CFD单独，因为它是太慢，这是不可能的FNM单独，因为它是不够准确。保持CFD准确性的混合方法的方法是在FNM中嵌入来自CFD模拟的流阻和热阻的预先计算的无量纲查找表。该软件将适应空气和水的单相流动以及水和制冷剂的蒸发/沸腾流动，这需要对复杂的热量，质量和动量传输现象进行建模。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。