Stochastic Computational Electromagnetics: Fundamental Aspects and Advanced Applications

随机计算电磁学：基本方面和高级应用

• 批准号: 261775-2013
• 负责人: Sarris, Costas
• 金额: $ 2.99万
• 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=637168
• 关键词: Stochastic; Computational; Electromagnetics; Fundamental; Aspects

Research on computational electromagnetics has been dedicated to the simulation of arbitrarily complex yet well-defined structures. However, several cutting-edge research areas, notably plasmonics and nanotechnology, employ devices that are increasingly subject to fabrication process variability. Moreover, while electromagnetic simulators are now able to model large-scale wireless propagation problems, they are still limited by the inherent statistical variability of indoor and urban environments. In general, the development of powerful electromagnetic simulation tools that effectively incorporate statistical uncertainty is bound to have a far-reaching impact on the pace of technology advancement with respect to grand research challenges such as the design of low-cost yet efficient solar cells, the development of biomedical instrumentation for cancer detection and treatment, and wireless service planning.Current state of the art in scientific computing under stochastic uncertainty is based on post-processing data from repetitive simulations. Not surprisingly, this approach has existed for years and it is too time consuming to incorporate in a typical engineering design cycle. In other words, while the level of complexity and significance of modeling uncertainty is constantly rising, the relevant modelling tools have remained fundamentally the same. The present proposal is aimed at closing this gap, in order to meet the challenge of modeling statistically variable electromagnetic structures and fields with applications in plasmonics, biomedical hyperthermia and wireless communications. Our approach is focused on the fundamental reformulation of field solvers to embed statistical uncertainty in a computationally efficient manner. The Finite-Difference Time-Domain method will be used as a platform to demonstrate these ideas.

计算电磁学的研究一直致力于模拟任意复杂但定义明确的结构。然而，几个前沿研究领域，特别是等离子体和纳米技术，采用越来越多地受到制造工艺可变性的影响的设备。此外，虽然电磁模拟器现在能够模拟大规模的无线传播问题，但它们仍然受到室内和城市环境固有的统计变化的限制。总的来说，有效地纳入统计不确定性的强大电磁仿真工具的开发必然会对技术进步的步伐产生深远的影响，这些技术进步涉及重大的研究挑战，例如低成本但高效的太阳能电池的设计，用于癌症检测和治疗的生物医学仪器的开发，在随机不确定性下的科学计算的当前技术状态是基于来自重复模拟的后处理数据。毫不奇怪，这种方法已经存在多年，并且在典型的工程设计周期中使用太耗时。换句话说，虽然建模不确定性的复杂性和重要性不断提高，但相关的建模工具基本上保持不变。本提案旨在缩小这一差距，以满足模拟统计变量的电磁结构和领域的等离子体，生物医学热疗和无线通信中的应用的挑战。我们的方法是集中在基本上重新制定的领域解决方案，以嵌入统计不确定性的计算效率的方式。时域差分法将被用作一个平台来展示这些想法。