Stress Field Prediction in Particulate Polymer Composite Materials Using Paired Image-To-Image Translation Approach
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-0418-7_26
Reference20 articles.
1. Nagaraja KC, Rajanna S, Prakash GS, Rajeshkumar G (2021) Mechanical properties of polymer matrix composites: effect of hybridization. Mater Today Proc 34:536–538. https://doi.org/10.1016/j.matpr.2020.03.108
2. Gupta S, Sharma A, Varma RK, Kushvaha V (2022) A review on performance of near-surface mounted-carbon fiber-reinforced polymer laminates bonded into slits. Polymer Compos 1. https://doi.org/10.1002/pc.26795
3. Hsissou R, Seghiri R, Benzekri Z et al (2021) Polymer composite materials: a comprehensive review. Compos Struct 262:113640. https://doi.org/10.1016/j.compstruct.2021.113640
4. Sharma A, Kushvaha V (2020) Predictive modelling of fracture behaviour in silica-filled polymer composite subjected to impact with varying loading rates using artificial neural network. Eng Fract Mech 239:107328. https://doi.org/10.1016/j.engfracmech.2020.107328
5. Sharma A, Madhushri P, Kushvaha V, Kumar A (2020) Prediction of the fracture toughness of silicafilled epoxy composites using K-nearest neighbor (KNN) method. In: 2020 international conference on computational performance evaluation (ComPE). IEEE, pp 194–198
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