当前位置: X-MOL 学术Numer. Heat Transf. Part A Appl. › 论文详情
Simultaneous identification of thermophysical properties of semitransparent media using an artificial neural network trained by a 2-D axisymmetric direct model
Numerical Heat Transfer, Part A: Applications ( IF 2.960 ) Pub Date : 2020-04-06 , DOI: 10.1080/10407782.2020.1746167
Yang Liu; Yann Billaud; Didier Saury; Denis Lemonnier

In this article, a multilayer artificial neural network (ANN) identification model is developed to simultaneously identify the thermal conductivity and the effective absorption coefficient of semitransparent materials from flash-type experimental measurements. Firstly, the ANN is trained by means of data generated by a 2-D axisymmetric heat transfer model whose radiative part is treated via the P1 approximation. A sensitivity study is then used to prove the theoretical feasibility of the identification strategy. Several training data distributions (uniform or Gaussian types) are tested on synthetic data, and on noisy ones for checking the robustness. Finally, the efficiency of this estimation approach is investigated using experimental data obtained by flash method on a PMMA sample. The estimated thermal conductivity and the effective absorption coefficient are compared with values obtained from the literature and other measurements.
更新日期:2020-04-06

 

全部期刊列表>>
材料学研究精选
Springer Nature Live 产业与创新线上学术论坛
胸腔和胸部成像专题
自然科研论文编辑服务
ACS ES&T Engineering
ACS ES&T Water
屿渡论文,编辑服务
杨超勇
周一歌
华东师范大学
段炼
清华大学
中科大
唐勇
跟Nature、Science文章学绘图
隐藏1h前已浏览文章
中洪博元
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
x-mol收录
福州大学
南京大学
王杰
左智伟
电子显微学
何凤
洛杉矶分校
吴杰
赵延川
试剂库存
天合科研
down
wechat
bug