首页|Researchers from Harbin Institute of Technology Detail Findings in Machine Learning (A Phase Field and Machining-learning Approach for Rapid and Accurate Prediction of Composites Failure)
Researchers from Harbin Institute of Technology Detail Findings in Machine Learning (A Phase Field and Machining-learning Approach for Rapid and Accurate Prediction of Composites Failure)
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Investigators discuss new findings in Machine Learning. According to news reporting originating in Harbin, People’s Republic of China, by NewsRx journalists, research stated, “A new approach is proposed for rapid and accurate prediction for composite failure in combination of the phase field and machine-learning methods. First, using experimentally-fitted tangent modulus instead of elastic modulus as constitutive relationship, a modified phase field method (MPFM) is established for the crack propagation and mechanical response, which can be effectively applied for composites with a nonlinear constitutive relationship.” Funders for this research include National Natural Science Foundation of China (NSFC), Science foundation of National Key Laboratory of Science and Technology on Advanced Composites in Special Environments.
HarbinPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningHarbin Institute of Technology
NETL
NSTL
Sage
