Robotics & Machine Learning Daily News2024,Issue(Nov.22) :22-23.

New Findings from University of Shanghai for Science and Technology Describe Adv ances in Machine Learning (Buckling Behaviors Prediction of Biological Staggered Composites With Finite Element Analysis and Machine Learning Coupled Method)

上海科技大学的新发现描述了机器学习的发展趋势(基于有限元分析和机器学习耦合方法的生物交错复合材料屈曲行为预测)

Robotics & Machine Learning Daily News2024,Issue(Nov.22) :22-23.

New Findings from University of Shanghai for Science and Technology Describe Adv ances in Machine Learning (Buckling Behaviors Prediction of Biological Staggered Composites With Finite Element Analysis and Machine Learning Coupled Method)

上海科技大学的新发现描述了机器学习的发展趋势(基于有限元分析和机器学习耦合方法的生物交错复合材料屈曲行为预测)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的新数据在一份新的报告中提供。据新闻报道来自中国人民日报上海,由NewsRx记者报道,研究称,“交错”在蛋白质基质中矿物晶体交错排列的结构中,i是最生物复合材料中的代表性微观结构。因为它是细长的几何形状和大的外形矿物晶体的比例及其在压缩载荷下的破坏机制主要受控通过屈曲。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Fresh data on Machine Learning are pre sented in a new report. According to newsoriginating from Shanghai, People’s Re public of China, by NewsRx correspondents, research stated, “Staggeredstructure , where mineral crystals are arranged in a staggered manner in protein matrix, i s the mostrepresentative microstructure in biological composites. Because of th e elongated geometry and large aspectratio of mineral crystals, their failure m echanism under compressive loading is predominantly controlledby buckling.”

Key words

Shanghai/People’s Republic of China/As ia/Cyborgs/Emerging Technologies/Machine Learning/University of Shanghai for Science and Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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