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Titlebook: Nonlinear Approaches in Engineering Application; Automotive Engineeri Reza N. Jazar,Liming Dai Book 2024 The Editor(s) (if applicable) and

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樓主: 女孩
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發(fā)表于 2025-3-25 07:01:38 | 只看該作者
22#
發(fā)表于 2025-3-25 08:57:01 | 只看該作者
Quy Dang Nguyen,Tra Van Nguyen,Dai Quoc Vo,Tuan Ngoc Vu,Sina Milani,Hormoz Marzbani,Reza N. Jazar
23#
發(fā)表于 2025-3-25 14:39:27 | 只看該作者
Mingjia Wang,Tegwyn G. Murden,Hettiadura E. T. Fernando, Reza N. Jazar,M. Mahinfalah
24#
發(fā)表于 2025-3-25 17:04:11 | 只看該作者
Javad Khazaii,Ali Khazaei,Hamid Khayyam,Reza N. Jazar
25#
發(fā)表于 2025-3-25 22:30:17 | 只看該作者
rary heavy-IT o- ented enterprises. This is accompanied by chapters on information systems c- sidered both from engineering and social perspectives. Particular topics on so- ware engineering have been placed in a separate book part. We addressed also advancements in information retrieval and formal
26#
發(fā)表于 2025-3-26 02:18:48 | 只看該作者
Three-Dimensional Nonlinear Vibration Model and Response Characteristics of Deep-Water Riser-Test Pivariational principle. The infinitesimal segment of the RTS is too short, such that it can be regarded as a straight segment. Because the vibration data of deep-water RTS cannot be accurately measured onsite, a simulation experiment was performed to validate the nonlinear vibration model in this stu
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發(fā)表于 2025-3-26 06:29:44 | 只看該作者
28#
發(fā)表于 2025-3-26 08:37:37 | 只看該作者
Nonlinear Analysis of Flexible Parallel Mechanisms Through Bézier-Based Integrationte joints and one prismatic joint while possessing only one degree of freedom. This chapter comprehensively analyzes this mechanism, considering its components’ rigid and flexible behaviors and introducing a newly developed Bézier-based integration approach to solve the governing equation. In this c
29#
發(fā)表于 2025-3-26 14:37:10 | 只看該作者
30#
發(fā)表于 2025-3-26 18:14:10 | 只看該作者
Physics-Informed Neural Network for Solution of Nonlinear Differential Equationsto agriculture, medicine, civil infrastructure, and even natural language processing. Of note, neural networks have been utilized in various engineering domains such as material science, fluid dynamics, and condition monitoring. Quite recently, a new category of neural networks, i.e. physics-informe
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