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Xu Yongjia,Lu Xinzheng,Fei Yifan,Huang Yuli 한국CDE학회 2022 Journal of computational design and engineering Vol.9 No.5
There are numerous advantages of deep neural network surrogate modeling for response time-history prediction. However, due to the high cost of refined numerical simulations and actual experiments, the lack of data has become an unavoidable bottleneck in practical applications. An iterative self-transfer learning method for training neural networks based on small datasets is proposed in this study. A new mapping-based transfer learning network, named as deep adaptation network with three branches for regression (DAN-TR), is proposed. A general iterative network training strategy is developed by coupling DAN-TR and the pseudo-label strategy, and the establishment of corresponding datasets is also discussed. Finally, a complex component is selected as a case study. The results show that the proposed method can improve the model performance by near an order of magnitude on small datasets without the need of external labeled samples, well behaved pre-trained models, additional artificial labeling, and complex physical/mathematical analysis.
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Guangming Lu,Xuezhen Wang,Na Teng,Jingyuan Hu,Liyue Zhang,Jinyue Dai,Yongjia Xu,Sakil Mahmud,Xiaoqing Liu 한국고분자학회 2021 폴리머 Vol.45 No.4
Bio-based epoxy resins with an ultrahigh glass transition temperature (Tg) and excellent flame retardancy are critical for developing sustainable polymers. Herein, a novel trifunctional epoxy monomer triglycidyl ether of resveratrol (TGER) was synthesized from renewable resveratrol. The chemical structure of TGER was confirmed by Fourier transform infrared (FTIR), ¹H, and <SUP>13</SUP>C nuclear magnetic resonance (NMR) spectroscopy which was then reacted with 4,4’-diaminodiphenylmethane (DDM) to form resin. The obtained resin was evaluated in terms of flame retardance and thermal properties. The resultant TGER-DDM 240 resin shows excellent flame-retardant properties, presenting a residual char of 42.5% at 800 ℃, limiting oxygen index (LOI) of 31.2%, and flammability rating of V-0 in UL94 test. Moreover, the resin possesses an ultrahigh Tg at 294 ℃. This work provides a facile method for preparing high-performance flame-retardant epoxy resin from a renewable resource.
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