Dynamic impact mechanical damage analysis and tomato robotic post-picking crating optimization based on multiscale finite element model by Guohang Lu, Zinuo Wang, Nianzu Dai, Jin Yuan, Xuemei Liu, Georgios Papadakis

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Numerical Simulation of Microwave-Induced Cracking of Coal Containing Pyrite Powder Based on a Multi-Field Coupling Model by Yidu Hong, Shengyi Long, Xiaowan Sun

“…The coal matrix damage efficiency was also related to the position of the sample under the static heating mode. …”
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Correlation coefficients of vibration signals and machine learning algorithm for structural damage assessment in beams under moving load by Toan Pham-Bao, Vien Le-Ngoc

“…In order to create a reliable and potential framework for predicting damage efficiently, these features are used as input variables to the machine learning model. …”
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Study on the destructive effect of a certain type of precision-guided mortar shell on light armored vehicles by XU Xin, YANG Leilei, WANG Xiaokun, LIU Xu, WANG Xiaoqing

“…In this paper, based on the practical problem of insufficient damage efficiency of conventional mortars on light armored vehicles, the damage effects of mortar fragments and shock waves on light armored vehicles and combatants under static and dynamic blasting modes are calculated by classical damage theory, and verified by BMP-3 armored vehicles. …”
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Evaluation of detonation performance of explosives ICM-101, ONC, and TNAZ based on improved VHL equation of state by Yong Han, Qin Liu, Yingliang Duan, Yaqi Zhao, Xinping Long

“…Detonation performance is crucial for evaluating the power of high explosives (HEs), and the equation of state (EOS) that accurately describes the high-temperature, high-pressure, and high-temperature, medium-pressure states of detonation products is key to assessing the damage efficiency of these energetic materials. This article examines the limitations of the VLW EOS in representing the thermodynamic states of explosive detonation gas products under high-temperature and medium-to high-pressure conditions. …”
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