首页|Study Results from Beihang University in the Area of Machine Learning Reported (Estimation of Stress Intensity Factor for Surface Cracks In the Firtree Groove Structure of a Turbine Disk Using Pool-based Active Learning With Gaussian Process …)
Study Results from Beihang University in the Area of Machine Learning Reported (Estimation of Stress Intensity Factor for Surface Cracks In the Firtree Groove Structure of a Turbine Disk Using Pool-based Active Learning With Gaussian Process …)
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Researchers detail new data in Machine Learning. According to news reporting out of Beijing, People's Republic of China, by NewsRx editors, research stated, "Calculation of the stress intensity factor K is a crucial and difficult task in linear elastic fracture mechanics. With the capacity to solve complex input-output problems of an underlying system, machine learning is especially useful in the calculation of K. However, when faced with complex systems, such as the firtree groove structure of a turbine disk, the data-consuming issue has always been a thorny problem in K -solutions combined with machine learning studies for a long time." Funders for this research include National Major Science and Technology Project, Fundamental Research Funds for the Central Universities. Our news journalists obtained a quote from the research from Beihang University, "In this paper, a novel K -solution method called PA-GPR (Pool -based Active learning with Gaussian Process Regression) for the calculation of the stress intensity factor for surface cracks in the firtree groove structure of a turbine disk is proposed. Using the pool -based active learning strategy, the proposed K -solution method could make the GPR model have a great regression performance with a few samples required. In the pool -based active learning strategy analysis, the learning function based on greedy sampling is proposed to select samples with a high contribution to the training of the GPR model. The calculation of K for a semi -elliptical surface crack in the firtree groove structure is evaluated to verify the accuracy and effectiveness of the proposed method."
BeijingPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesGaussian ProcessesMachine LearningBeihang University
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