高性能流体的智能设计用于热管理:整合响应表面方法,加权的切比切夫方法和强度帕雷托进化算法II
Mohamed Bechir Ben Hamida1, Ali Basem2, Neeraj Varshney3
1Deanship of Scientific Research, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia.
Scientific reports
|July 2, 2025
概括
本研究引入了一个新的纳米流体热物理性质 (TPP) 的多目标优化框架,使更好的传热应用成为可能. 开发的模型准确地预测了TPP,指导了针对特定工程需求的最佳纳米流体选择.
科学领域:
- 材料科学 材料科学 材料科学
- 热力学是一种热力学.
- 化学工程是化学工程的重要组成部分.
背景情况:
- 优化纳米流体热物理性质 (TPPs) 对于增强传热应用至关重要.
- 现有的研究往往将优化限制在两个目标上,阻碍实际实施.
- 需要一个全面的框架来同时优化多个TPP.
研究的目的:
- 开发和验证纳米流体TPP的新型多目标优化框架.
- 将响应表面方法 (RSM) 与增强登 (EHC) 和强度帕雷托进化算法II (SPEA-II) 整合起来.
- 根据优先目标选择最佳纳米流体时使用权重切比切夫方法 (WTM) 进行决策.
主要方法:
- 使用响应表面方法 (RSM) 来建模关键的热物理性质.
- 增强登 (EHC) 和强度帕雷托进化算法II (SPEA-II) 已集成用于多目标优化.
- 权重的切比切夫方法 (WTM) 便于选择最佳的纳米流体配置.
主要成果:
- RSM模型在密度比,粘度比,特定热容量比和导热率比方面表现出高的预测精度 (R2>0.99).
- 多目标优化框架成功地确定了各种优先级场景的最佳纳米流体组成和操作条件.
- 确定了ZnO和CeO2纳米流体的特定最佳条件,平衡密度,粘度,特定热容量和导热性等特性.
结论:
- 开发的框架为纳米流体TPP多目标优化提供了可靠和准确的方法.
- 该研究表明,能够根据特定的工程要求和优先事项选择最优的纳米流体.
- 这些发现强调了ZnO的多功能性,Al2O3的热储优势,以及CeO2纳米流体的高温性能.
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