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: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=638762
• 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，可以提高工程系统的性能，使我们能够在最小的长度和时间尺度上设计材料和结构，同时增强功能。不断增长的计算能力使得能够模拟纳米级系统的物理行为，并具有越来越多的细节和准确性。然而，即使使用当前的超级计算机，也无法对其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。这是多尺度复杂工程系统基于仿真的设计和优化的主要障碍。我们以前的研究主要集中在多尺度半导体热输运的分层建模。在此专业知识的基础上，拟议的研究将扩展分层多尺度方法，以多物理热/流体传输在能源密集型应用。主要目标是：（a）增加我们对发生在最小相关长度和时间尺度上的基本现象的理解，以及（B）开发一种方法来表示和转移这些知识到更大的尺度。这将有助于在最小规模上制定新的战略和设计创新，以改善或彻底改变组件和系统级性能。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。在增加晶体管密度的同时减小晶体管尺寸一直是提高电子性能的关键方法，在过去的几十年中，通过将晶体管的沟道从3200 nm减小到22 nm，实现了实质性的收益。随着晶体管密度的增加，热能的产生速率高于可以去除的速率，从而产生局部热点和高温度梯度，对性能和可靠性产生不利影响。此外，材料界面数量的增长使得跨界面的能量传输成为热性能的重要贡献者。因此，了解纳米界面的热传输对于设计下一代电子产品至关重要。我们将在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场工程。可持续能源是另一个领域，其中提出的分层建模方法可能会产生巨大的影响，我们将重点关注风能和燃料电池技术。在风力发电场中，尾流损失可以高达总能量生产的10%-20%。先前的工作已经确定风力涡轮机布局的设计是影响尾流产生和传播的最重要因素。所提出的分层方法桥接模型在多个长度尺度将允许优化设计的基础上准确的第一原理建模的风在复杂的地形。改善气体扩散层（GDL）中的质量和热传递对于推进PEM燃料电池技术至关重要。利用我的团队在传统和介观方法模拟多孔介质的经验，我们提出了一个层次的方法来模拟GDL传输从孔隙级到系统级。阐明在最小长度尺度上影响GDL传输的主要因素及其对系统级性能的影响将产生下一代PEM燃料电池的新设计。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系统行为的第一原理模型。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性能的影响的理解。