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Tag: tribe_events
35 events found.
Digital Twin
Events
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Robots are increasingly essential in various industries. This webinar will cover using a Model-Based Systems Engineering approach for creating requirements and architecture in robotics. What Attendees Will Learn: Bridge system architecture to system-level simulation Perform system-level simulation with integrated reduced-order models, 0D/1D components, and control systems Define, design, and test embedded software while conducting safety […] |
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Getting the most out of COMSOL simulations requires efficient use of the available simulation budget as well as validating that the simulation produces results that agree with reality. This webinar will discuss the role design of experiments, predictive machine learning models (aka surrogate models), and machine learning tools such as statistical calibration play in calibrating […] |
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This two-day workshop taking place in London and online, will bring together the aerodynamics modelling and measurement communities to share knowledge, challenges, and approaches, fostering open discussion on how both disciplines can work together more effectively in the context of CFD validation. The event aims to bridge the gap between aerodynamic computational and wind-tunnel testing […] |
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Manufacturing industries are transforming, inspired by greater automation, digital twin adoption, AI augmentation, new materials, and battery technologies. These changes create opportunities and challenges for engineers, designers, and manufacturers. Join the India Open Meeting to discover how cutting-edge simulation technologies and tools are driving innovation, enabling smarter designs, greener products, faster development, and superior performance. […] |
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This webinar explores how SmartUQ enhances ANSYS simulation and digital twin workflows by integrating advanced design of experiments, surrogate modeling, and uncertainty quantification techniques. It outlines approaches for accelerating high-fidelity analysis, managing variability, and strengthening predictive performance through data-driven methods within complex engineering simulation processes. For registration click here.. |
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