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AI and machine learning for engineering design

Aeronautical and astronautical engineering, Artificial Intelligence, Civil and environmental engineering, Classes and programs, Computer modeling, Design, Faculty, Invention, Machine Learning, Mechanical engineering, MIT Sloan School of Management, Nuclear science and engineering, School of Engineering, Students

Artificial intelligence optimization offers a host of benefits for mechanical engineers, including faster and more accurate designs and simulations, improved efficiency, reduced development costs through process automation, and enhanced predictive maintenance and quality control.“When people think about mechanical engineering, they’re thinking about basic mechanical tools like hammers and … hardware like cars, robots, cranes, but mechanical engineering […]

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DOE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions

Aeronautical and astronautical engineering, Artificial Intelligence, Computer modeling, Computer science and technology, Department of Energy (DoE), DMSE, Electrical engineering and computer science (EECS), Machine Learning, Mathematics, Mechanical engineering, MIT Schwarzman College of Computing, Research, School of Engineering, School of Science, Security studies and military, Space, Supercomputing

The U.S. Department of Energy’s National Nuclear Security Administration (DOE/NNSA) recently announced that it has selected MIT to establish a new research center dedicated to advancing the predictive simulation of extreme environments, such as those encountered in hypersonic flight and atmospheric re-entry. The center will be part of the fourth phase of NNSA’s Predictive Science Academic Alliance

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Simpler models can outperform deep learning at climate prediction

Algorithms, Artificial Intelligence, Climate change, Computer modeling, data, EAPS, Earth and atmospheric sciences, Emissions, IDSS, Machine Learning, MIT Schwarzman College of Computing, Pollution, Public health, Research, School of Science, Sustainability

Environmental scientists are increasingly using enormous artificial intelligence models to make predictions about changes in weather and climate, but a new study by MIT researchers shows that bigger models are not always better.The team demonstrates that, in certain climate scenarios, much simpler, physics-based models can generate more accurate predictions than state-of-the-art deep-learning models.Their analysis also

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