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Updated: Jul 5, 2025

A Coupled Experiment-finite Element Modeling Methodology for Assessing High Strain Rate Mechanical Response of Soft Biomaterials
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评估送向前反向传播人工神经网络,用于应变率敏感机械建模

Víctor Tuninetti1, Diego Forcael1, Marian Valenzuela2

  • 1Department of Mechanical Engineering, Universidad de La Frontera, Temuco 4811230, Chile.

Materials (Basel, Switzerland)
|January 23, 2024
PubMed
概括

本研究使用人工神经网络 (ANN) 准确识别金属制造的材料模型参数,即使具有有限的高冲击测试数据. 基于感知子的ANN架构被证明是最有效的,用于预测各种应变速率下的材料行为.

关键词:
人工神经网络的人工神经网络机械行为 机械行为建模建模是什么意思塑料的流动 塑料的流动变种速率的变种率是什么

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Engineering stress is calculated as the load divided by the original, undeformed cross-sectional area. It approximates a material under load. This approximation is especially relevant post-yield in ductile materials. Though engineering stress-strain diagrams are often used for their convenience and accessibility, they can sometimes fall short in accuracy, particularly when dealing with large strain values.
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The utilization of strain gauges as transducers for converting mechanical strain into electrical signals is a common practice in various engineering applications. These strain gauges are frequently integrated into Wheatstone bridge circuits to accurately measure parameters such as force or pressure. Within this context, each element within the circuit exhibits a resistance that undergoes subtle variations when subjected to mechanical strain. The primary objective is to convert minuscule...
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