北航数学论坛

题目: Quantitative Forecasting for Energy Applications 

报告人：Daniel Tartakovsky教授（斯坦福大学）

报告时间：2019.9.4 下午3:00-4:00

报告地点：数学学院E404（沙河校区）

摘要: Design and operations of energy systems rely, to a large degree, on mathematical models whose veracity is often questionable. Selection of a proper model is driven by a quantity of interest ( i.e., by specific questions one is asked) and by tolerance to risk ( i.e., by the level of predictive uncertainty one is willing to tolerate). We elucidate this problem by considering several energy-related applications that range from batteries to pipelines, and span the scales from nanometers to kilometers. The first application deals with design of hierarchical nanoporous carbon-based materials that exhibit high specific electric double layer capacitances and high rate capability in an organic electrolyte, which makes them attractive for energy storage. The second application is related to optimal siting of ground heat exchangers, which exploit differences between air and soil temperatures to heat and/or cool buildings. The third application stems from the need of insurance companies to estimate the risks of a pipeline rapture and associated environmental remediation costs. Put together, these problems illustrate an application-centered modeling philosophy that is the opposite of a proverbial hammer in search of a nail.

个人简介:

Daniel Tartakovsky教授本科毕业于苏联喀山州立大学应用数学与力学系，在1993-1996年师从于美国工程院院士Sholom Neuman博士，并于1996年获得了亚利桑那大学的博士学位。他随后加入了美国能源部洛斯阿拉莫斯国家实验室数学建模与分析小组，并先后担任了博士后研究员、小组负责人等职位。Tartakovsky教授2004年加入加州大学圣地亚哥分校，并于2008年获得了终身正教授。2016年，他接受了斯坦福大学能源与环境学院的终身教授职位，一直工作至今。Tartakovsky教授的主要研究兴趣是应用数学、计算数学的理论及其在环境流体和生物医学建模中的应用。他先后在PNAS、SIAM、Journal of Fluid Mechanics, Physical Review Letters 等著名期刊上发表了175篇文章，总引用为5083.

邀请人：王鹏