首页|Research Conducted at University of Nottingham Has Provided New Information abou t Machine Learning (A Machine Learning-driven Approach To Predicting Thermo-elas to-hydrodynamic Lubrication In Journal Bearings)
Research Conducted at University of Nottingham Has Provided New Information abou t Machine Learning (A Machine Learning-driven Approach To Predicting Thermo-elas to-hydrodynamic Lubrication In Journal Bearings)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Researchers detail new data in Machine Learning. According to news originatingfrom Nottingham, United Kingdom, by New sRx correspondents, research stated, “Traditional methodsof evaluating the perf ormance of journal bearings, for example thermal-elastichydrodynamic- lubrication theory, are limited to simplified conditions that often fail to accurately mod el realworld components.Numerical models that include additional phenomena such as cavitation and fully coupled effects likedeformation, temperature, pressure and viscosity can be more accurate but require a large amount ofcomputational overhead, making analysis slower and more costly.”
NottinghamUnited KingdomEuropeCybo rgsEmerging TechnologiesMachine LearningUniversity of Nottingham
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