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Data Modeling in Functional Clothing Design:Forward and Inverse Problems Approaches
作者:    时间:2018-11-27 浏览次数:

  

报告人:徐定华

工作单位:浙江理工大学

报告时间: 12月1日9:00

报告地点:数学与统计学院一楼报告厅

报告摘要:

Textile material design is of paramount important in the study of functional clothing design. The experimental data shows that there are great challenges in Intelligent Manufacturing in Clothing Industry, such as Thermal Comfort Clothing (TCC) and Thermal Protective Clothing (TPC). The experimental Data varies from the data on clothing parameters, environmental situation, human body comfort Index and skin Injury. Therefore the data modelling of functional clothing design will based on physical model of heat and moisture transfer. The advantages of the data modelling may reduce the design cost and experimental risk.

We focus on revealing heat and moisture transfer characteristics in the system of human body-clothing-environment, which directly determine thermal comfort/safety level of human body. Based on the parabolic model of dynamic heat and moisture transfer, we present inverse problems of textile parameters determination (IPTPD), including thickness, thermal conductivity and porosity determination. Moreover we mathematically formulate a new space-fractional parabolic model of heat transfer within thermal protective clothing under high environmental temperature- humidity, and the corresponding inverse problems of textile material design are put forward. Some numerical algorithms are presented by the regularization approaches. Theoretical study and numerical simulation results validate the formulation of the IPTPD and demonstrate effectiveness of the proposed numerical algorithms.

报告人简介:

徐定华,浙江理工大学理学院教授,上海财经大学数学学院教授、博士生导师、教授委员会主任、副院长。现任教育部高校数学类专业教学指导委员会委员、中国数学学会高等教育工作委员会委员。研究方向:应用与计算数学,主要开展偏微分方程反问题理论、计算及其应用研究。曾任高校教务处长、研究生部主任、学院院长。曾评为全国优秀教师、省教学名师。国家级教学成果奖获得者,全国大学生数学建模竞赛2018年A题命题人。