Hierarchical Multi-scale Modelling of Thermal/Fluid Transport Processes in Energy-intensive Applications

能源密集型应用中热/流体传输过程的分层多尺度建模

• 批准号: RGPIN-2014-06128
• 负责人: Amon, Cristina
• 金额: $ 4.23万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=588828
• 关键词: Hierarchical; Multi; scale; Modelling; Thermal

Advances in nanoscale science and technology have enormous potential to improve the performance of engineered systems, by allowing us to design materials and structures at the smallest length and time scales while enhancing functionality. Increasing computational power has enabled simulation of the physical behavior of nanoscale systems, with increasing detail and accuracy. However, detailed component-level and system-level simulations of multi-scale systems whose performance is dictated by nanoscale phenomena cannot be carried out, even with current supercomputers. This is a major roadblock for simulation-based design and optimization of multi-scale complex engineered systems. Our previous research has focused on hierarchical modelling of semiconductor thermal transport across multiple scales. Building on this expertise, the proposed research will expand the hierarchical multi-scale methodology to multi-physics thermal/fluid transport in energy-intensive applications. The main goals are (a) to increase our understanding of fundamental phenomena occurring at the smallest relevant length and time scales, and (b) to develop a methodology for representing and transferring this knowledge to larger scales. This will enable formulation of novel strategies and design innovations at the smallest scales to improve or revolutionize component- and system-level performance. We envision applications in electronic devices and sustainable energy systems, as described below. Reducing transistor size while increasing transistor density has been the key approach for increasing electronics performance, with substantial gains achieved by reducing the transistor’s channel from 3200 to 22 nm over the last decades. As transistor density increases, thermal energy is generated at a higher rate than can be removed, creating localized hotspots and high temperature gradients, with detrimental effects on performance and reliability. In addition, the growth in the number of material interfaces has made energy transport across interfaces a significant contributor to thermal performance. Hence, understanding thermal transport across nanoscale interfaces is essential for designing next-generation electronics. We will build on our previous work in hierarchical modeling to enable multi-scale multi-physics engineering of next-generation electronic devices. Sustainable energy is another domain in which the proposed hierarchical modelling methodology can have tremendous impact, and we will focus on wind energy and fuel cell technologies. In wind farms, wake losses can be as large as 10%-20% of the total energy production. Previous work has identified the design of the wind turbine layout as the most significant factor affecting wake generation and propagation. The proposed hierarchical approach bridging models at multiple length scales will allow optimal design based on accurate first-principle modelling of wind wakes in complex terrains. Improving mass and thermal transport in gas diffusion layers (GDL) is essential to advance PEM fuel cell technology. Leveraging my group’s experience in both traditional and mesoscopic methods for simulation of porous media, we propose a hierarchical approach to model GDL transport from pore-level to system-level. Elucidating the main factors affecting GDL transport at the smallest length scales and their effect on system-level performance will generate novel designs for next-generation PEM fuel cells. Overall, the multi-scale hierarchical modelling methodology aims to develop physics-based, first-principle models of system behavior at the smallest relevant scales. These models will increase understanding of the underlying phenomena and their effect on macroscale performance by bridging nanoscale to macroscale predictions.

纳米科学和技术的进步具有巨大的潜力来改善工程系统的性能，使我们能够在增强功能的同时，以最小的长度和时间尺度设计材料和结构。随着计算能力的增强，纳米级系统的物理行为的模拟变得更加详细和准确。然而，即使使用当前的超级计算机，也无法对性能由纳米级现象决定的多尺度系统进行详细的组件级和系统级模拟。这是基于仿真的多尺度复杂工程系统设计和优化的主要障碍。 我们以前的研究主要集中在半导体热输运的多尺度分层模型上。在这一专门知识的基础上，拟议的研究将把分层多尺度方法扩展到能源密集型应用中的多物理热/流体传输。主要目标是(A)增加我们对在最小的相关长度和时间尺度上发生的基本现象的了解，以及(B)发展一种方法来表示和转移这种知识到更大的尺度。这将能够在最小的范围内制定新的战略和设计创新，以改进组件和系统级的性能或使其发生革命性变化。我们设想在电子设备和可持续能源系统中的应用，如下所述。 在减小晶体管尺寸的同时增加晶体管密度一直是提高电子性能的关键方法，在过去几十年中，通过将晶体管的沟道从3200 nm减少到22 nm，实现了显著的收益。随着晶体管密度的增加，热能的产生速度比可以去除的速度更快，从而产生局部热点和高温度梯度，对性能和可靠性造成不利影响。此外，材料界面数量的增加使得界面之间的能量传输成为热性能的重要贡献因素。因此，了解纳米尺度界面上的热传输对于设计下一代电子产品是至关重要的。我们将在我们以前的分层建模工作的基础上，实现下一代电子设备的多尺度多物理工程。 可持续能源是另一个拟议的分层建模方法可以产生巨大影响的领域，我们将重点关注风能和燃料电池技术。在风力发电场，尾流损失可能高达总发电量的10%-20%。以前的工作已经确定了风力机布局的设计是影响尾迹产生和传播的最重要的因素。建议的层次化方法在多个长度尺度的模型之间架起桥梁，将允许基于复杂地形中的风尾迹的准确第一原理模型的最佳设计。 改善气体扩散层(GDL)中的传质和热传输是推进PEM燃料电池技术的关键。利用我的团队在模拟多孔介质的传统和介观方法方面的经验，我们提出了一种分层方法来模拟从孔隙水平到系统水平的GDL传输。阐明在最小长度尺度下影响GDL传输的主要因素及其对系统级性能的影响，将为下一代PEM燃料电池提供新的设计方案。 总体而言，多尺度分层建模方法的目的是在最小的相关尺度上开发基于物理的、第一原理的系统行为模型。这些模型将通过将纳米尺度的预测与宏观尺度的预测联系起来，增加对潜在现象及其对宏观尺度表现的影响的理解。