most citedMulti-scale modeling in thermal conductivity of Polyurethane incorporated with Phase Change Materials using Physics-Informed Neural Networks

175 citations · 180 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CE2023

Multiscale modeling of thermal properties in Polyurethane incorporated with phase change materials composites: A case study

Bokai Liu, Weizhuo Lu, Xiaoyue Hu +4

Polyurethane (PU) is an ideal thermal insulation material due to its excellent thermal properties. The incorporation of Phase Change Materials (PCMs) capsules into Polyurethane (PU…

physics.comp-ph2023★ 175 cited

Multi-scale modeling in thermal conductivity of Polyurethane incorporated with Phase Change Materials using Physics-Informed Neural Networks

Bokai Liu, Yizheng Wang, Timon Rabczuk +2

Polyurethane (PU) possesses excellent thermal properties, making it an ideal material for thermal insulation. Incorporating Phase Change Materials (PCMs) capsules into Polyurethane…

cs.HC2018★ 2 cited

Macro pose based non-invasive thermal comfort perception for energy efficiency

Bin Yang, Xiaogang Cheng, Dengxin Dai +3

Individual thermal comfort perception gives important feedback signals for energy efficient control of smart buildings. However, there is no effective method to measure real-time t…

cs.CV2018

Non-invasive measuring method of skin temperature based on skin sensitivity index and deep learning

Xiaogang Cheng, Bin Yang, Kaige Tan +5

In human-centered intelligent building, real-time measurements of human thermal comfort play critical roles and supply feedback control signals for building heating, ventilation, a…

cs.HC2018★ 3 cited

Non-invasive thermal comfort perception based on subtleness magnification and deep learning for energy efficiency

Xiaogang Cheng, Bin Yang, Anders Hedman +3

Human thermal comfort measurement plays a critical role in giving feedback signals for building energy efficiency. A non-invasive measuring method based on subtleness magnification…