SBIR Phase I: Rapid and Accurate Multi-Variable Optimization Software for Arrays of Heat Sinks
SBIR Phase I: Rapid and Accurate Multi-Variable Optimization Software for Arrays of Heat Sinks
批准号:
1819580
负责人:
Georgios Karamanis
金额:
$22.5万
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
项目状态:
已结题
起止时间:
2018-06-15 至 2020-05-31
中文摘要
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英文摘要
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.
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SBIR Phase II: Rapid and Accurate Multi-Variable Optimization Software for Arrays of Heat Sinks
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批准号:2025882
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项目类别:Cooperative Agreement
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资助金额:$98.63万
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财政年份:2020
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负责人:Georgios Karamanis
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依托单位:
国内基金
海外基金
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