A prediction model using response surface methodology based on cell size and foam density to predict thermal conductivity of polystyrene foams

Biobased foams for thermal insulation: material selection, processing, modelling, and performance

“…Micro-CT scanning of experimental foams to create structural information inputs for a model is a potential means ll this gap. 116 Additionally, all models assessed here have neglected to account for the possibility of polymer blends or solid Table 1 Assumptions regarding structure and heat transfer mechanisms and predictions made by a variety of thermal conductivity models 42,43,47,48,106,113,116,122 2 Assumptions made in a variety of models corresponding to comparable observations in experimental biobased foams [13][14][15][16][17][18][19][20][21][22][23][24]26,27,[41][42][43]47,48,54,62,64,73,106,113,116,122,123 additives. Granted, it is not reasonable to consider every possible additive, but certainly it would be desirable to have a better understanding of how different polymer domains in a blend impact thermal conductivity depending on how those domains are arranged.…”

Finite Element Simulation and Experimental Test of Ovine Corneal Tissue Cutting Process in Cataract Surgery Operation

“…Also, the dwell time selection above 20 seconds caused the aluminum side to fracture due to overheating. Nowadays, design of experiment (DOE) methods have a broad range in engineering applications [10][11][12][13][14]. Taguchi method is one of the most popular DOE methods [15][16][17][18].…”

Combined systems based on OSOFC/HSOFC: Comparative analysis and multi‐objective optimization of power and emission

“…The details of this approach are available in the literature. [42][43][44] F I G U R E 3 Thermal resistances of a single heat pipe [Colour figure can be viewed at wileyonlinelibrary.com]…”