Thermal concentrating efficiency enhanced for multilayer circular thermal concentrators with gradient structures

IF 5 2区 工程技术 Q1 ENGINEERING, MECHANICAL International Journal of Heat and Mass Transfer Pub Date : 2024-09-16 DOI:10.1016/j.ijheatmasstransfer.2024.126166
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Abstract

The thermal concentrating efficiency of a thermal concentrator is determined by the ratio of its interior to exterior temperature gradients, serving as a crucial indicator influenced by the interaction of geometrical and thermal conductivity parameters. Finding simpler and more effective ways to improve thermal concentrating efficiency has been a key concern in this field. In our study, we present a method to enhance the concentrating efficiency of an isotropic multilayer circular thermal concentrator by introducing gradient-distributed thermal conductivities or layer thicknesses within the multilayer circular structure. Our goal is to identify the optimal structural setup parameters for achieving enhanced thermal concentrating efficiency using an optimization approach that combines stepwise refinement search with machine-learning predictions. Initial investigations explore the impacts of different gradient schemes on thermal concentration performance. The gradient distribution function with high thermal concentrating efficiency is established through the stepwise refinement search strategy and the machine-learning model. Subsequently, a detailed search process is carried out in small increments, followed by finite element simulations to validate the thermal concentrating efficiency and ascertain the optimal design parameters of the thermal concentrator. Our findings reveal that the optimally designed gradient thermal concentrator showcases an 8.56 % increase in thermal concentrating efficiency compared to a single-layer structure without gradients. Moreover, applying the gradient function to the outer and inner rings elucidates the inherent influence of the inner and outer layered ring structures on thermal concentrating efficiency. The optimization methodology, combining stepwise refinement search and machine-learning predictions, succeeds in improving the efficiency with easy, fast and efficient operation. This approach can be extended to advance the development of various other thermal metastructured devices.

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提高具有梯度结构的多层圆形热聚光器的热聚光效率
热聚光器的热聚光效率由其内部和外部温度梯度的比值决定,是受几何参数和热传导参数相互作用影响的重要指标。寻找更简单、更有效的方法来提高热聚光效率一直是这一领域的关键问题。在我们的研究中,我们提出了一种方法,通过在多层圆形结构中引入梯度分布的导热系数或层厚,来提高各向同性多层圆形集热管的集热效率。我们的目标是利用一种将逐步细化搜索与机器学习预测相结合的优化方法,确定最佳结构设置参数,以实现更高的热集中效率。初步研究探索了不同梯度方案对热浓缩性能的影响。通过逐步细化搜索策略和机器学习模型,确定了热浓缩效率高的梯度分布函数。随后,我们以小增量的方式进行了详细的搜索过程,并通过有限元模拟验证了热浓缩效率,确定了热浓缩器的最佳设计参数。我们的研究结果表明,与没有梯度的单层结构相比,经过优化设计的梯度热集中器的热集中效率提高了 8.56%。此外,将梯度函数应用于外环和内环还阐明了内外分层环结构对热聚光效率的内在影响。该优化方法结合了逐步细化搜索和机器学习预测,操作简便、快速、高效,成功地提高了效率。这种方法可以推广到其他各种热结构装置的开发中。
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来源期刊
CiteScore
10.30
自引率
13.50%
发文量
1319
审稿时长
41 days
期刊介绍: International Journal of Heat and Mass Transfer is the vehicle for the exchange of basic ideas in heat and mass transfer between research workers and engineers throughout the world. It focuses on both analytical and experimental research, with an emphasis on contributions which increase the basic understanding of transfer processes and their application to engineering problems. Topics include: -New methods of measuring and/or correlating transport-property data -Energy engineering -Environmental applications of heat and/or mass transfer
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