首页|Reports from Department of Civil Engineering Advance Knowledge in Machine Learni ng (Assessment of Arresting Performance of Integral Buckle Arrestors for Sandwic h Pipes Using Machine Learning Techniques)
Reports from Department of Civil Engineering Advance Knowledge in Machine Learni ng (Assessment of Arresting Performance of Integral Buckle Arrestors for Sandwic h Pipes Using Machine Learning Techniques)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news reporting out of Hangzhou, People’s R epublic of China, by NewsRx editors, research stated, “Integral buckle arrestors are regarded as the most effective arresting devices and can be perfectly adapt ed to innovative sandwich pipes. In the present study, hyperbaric chamber tests were performed on reduced-scale sandwich pipe specimens equipped with integral a rrestors, and the effect of interface bonding behaviour on the crossover pressur e was examined.”
HangzhouPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningDepartment of Civil Engineering
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