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Week in Tech: An Architectural Styrofoam Biodigester

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New AI tool calculates materials' stress and strain based on photos

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IMAGE: This visualization shows the deep-learning approach in predicting physical fields given different input geometries. The left figure shows a varying geometry of the composite in which the soft material is.
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Credit: Courtesy of Zhenze Yang, Markus Buehler, et al
Isaac Newton may have met his match.
For centuries, engineers have relied on physical laws developed by Newton and others to understand the stresses and strains on the materials they work with. But solving those equations can be a computational slog, especially for complex materials.
MIT researchers have developed a technique to quickly determine certain properties of a material, like stress and strain, based on an image of the material showing its internal structure. The approach could one day eliminate the need for arduous physics-based calculations, instead relying on computer vision and machine learning to generate estimates in real time. ....

Chi Hua Yu , Markus Buehler , Isaac Newton , Zhenze Yang , Generative Adversarial Neural Network , Laboratory For Atomistic , Office Of Naval Research , Army Research Office , Rensselaer Polytechnic Institute , Department Of Materials Science , Materials Science , Mcafee Professor , Sir Isaac , Generative Adversarial Neural , சி ஹுவா யூ , மார்கஸ் பூஎளீர் , ஐஸ்யாக் நியூட்டன் , அலுவலகம் ஆஃப் கடற்படை ஆராய்ச்சி , இராணுவம் ஆராய்ச்சி அலுவலகம் , ரென்சீலர் பாலிடெக்நிக் நிறுவனம் , துறை ஆஃப் பொருட்கள் அறிவியல் , பொருட்கள் அறிவியல் , அம்கஃபீ ப்ரொஃபெஸர் , ஐயா ஐஸ்யாக் ,

New AI tool calculates materials' stress and strain based on photos | MIT News | Massachusetts Institute of Technology

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Isaac Newton may have met his match.
For centuries, engineers have relied on physical laws developed by Newton and others to understand the stresses and strains on the materials they work with. But solving those equations can be a computational slog, especially for complex materials.
MIT researchers have developed a technique to quickly determine certain properties of a material, like stress and strain, based on an image of the material showing its internal structure. The approach could one day eliminate the need for arduous physics-based calculations, instead relying on computer vision and machine learning to generate estimates in real time. ....

Chi Hua Yu , Markus Buehler , Isaac Newton , Zhenze Yang , Generative Adversarial Neural Network , Laboratory For Atomistic , Office Of Naval Research , Army Research Office , Rensselaer Polytechnic Institute , Department Of Materials Science , Materials Science , Mcafee Professor , Sir Isaac , Generative Adversarial Neural , சி ஹுவா யூ , மார்கஸ் பூஎளீர் , ஐஸ்யாக் நியூட்டன் , அலுவலகம் ஆஃப் கடற்படை ஆராய்ச்சி , இராணுவம் ஆராய்ச்சி அலுவலகம் , ரென்சீலர் பாலிடெக்நிக் நிறுவனம் , துறை ஆஃப் பொருட்கள் அறிவியல் , பொருட்கள் அறிவியல் , அம்கஃபீ ப்ரொஃபெஸர் , ஐயா ஐஸ்யாக் ,

Scientists Turn Spider Webs Into Spider Harps To Hear Spider 'Voices'

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