PFI-RP: Design and additive manufacturing of heat exchangers

PFI-RP：热交换器的设计和增材制造

• 批准号: 1941206
• 负责人: Xiaoping Qian
• 金额: $ 54.99万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1941206&HistoricalAwards=false
• 关键词: PFI; RP; Design; additive; manufacturing

The broader impact/commercial potential of this Partnerships for Innovation – Research Partnerships (PFI-RP) project is to improve energy efficiency for convection-related applications, ranging from automotive to aerospace, power conversion, refrigeration, and others. The project will develop advanced computational techniques to improve the performance of heat exchangers, advancing design and manufacturing techniques in the energy industry. This project will also foster the training of technology commercialization for graduate students, and research training for under-represented students in STEM disciplines.The proposed project integrates topology optimization and additive manufacturing for heat exchangers. Density-based topology optimization of conjugate heat transfer systems will be conducted in a high-performance computing environment. An adjoint approach will be used to obtain the sensitivity. We will use density gradient-based formulations to address overhang angle and support structure control. The resulting heat exchangers will be manufactured via a metallic additive process. Thermal-hydraulic and durability tests will be conducted to validate performance.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.

该创新合作伙伴关系 - 研究合作伙伴关系 (PFI-RP) 项目的更广泛影响/商业潜力是提高对流相关应用的能源效率，包括汽车、航空航天、电力转换、制冷等。该项目将开发先进的计算技术来提高热交换器的性能，推进能源行业的设计和制造技术。该项目还将促进研究生的技术商业化培训，以及 STEM 学科中代表性不足的学生的研究培训。拟议项目集成了热交换器的拓扑优化和增材制造。 共轭传热系统基于密度的拓扑优化将在高性能计算环境中进行。将使用伴随方法来获得灵敏度。我们将使用基于密度梯度的公式来解决悬垂角度和支撑结构控制。由此产生的热交换器将通过金属增材工艺制造。将进行热水力和耐久性测试来验证性能。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。

项目成果

Quantum Topology Optimization via Quantum Annealing

• DOI: 10.1109/tqe.2023.3266410
• 发表时间: 2023-01
• 期刊: IEEE Transactions on Quantum Engineering
• 作者: Zisheng Ye;Xiaoping Qian;W. Pan

A Framework for Physics-Informed Deep Learning Over Freeform Domains

自由形式域上基于物理的深度学习框架

• DOI: 10.1016/j.cad.2023.103520
• 发表时间: 2023
• 期刊: Computer-Aided Design
• 影响因子: 4.3
• 作者: Mezzadri, Francesco;Gasick, Joshua;Qian, Xiaoping
• 通讯作者: Qian, Xiaoping

Density gradient‐based adaptive refinement of analysis mesh for efficient multiresolution topology optimization

• DOI: 10.1002/nme.6863
• 发表时间: 2021-10
• 期刊: International Journal for Numerical Methods in Engineering
• 影响因子: 2.9
• 作者: F. Mezzadri;Xiaoping Qian

Simultaneous topology and machine orientation optimization for multiaxis machining

• DOI: 10.1002/nme.6839
• 发表时间: 2021-10
• 期刊: International Journal for Numerical Methods in Engineering
• 影响因子: 2.9
• 作者: Joshua Gasick;Xiaoping Qian