From creating learning models to consulting! Achieving real-time simulations.
Are you involved in CAE and facing these concerns? - Parameter studies take too much time - I want to speed up routine CAE work - The calculation speed is insufficient for real-time CAE use The CAE Proxy Solution can solve these problems! The CAE Proxy Solution is a consulting service that uses deep learning to substitute simulations.
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basic information
■ Strengths of CAE Proxy Solutions - Ultra-fast computation: Proxy calculations using deep learning predict phenomena at a speed 1000 times faster than simulations. - Generation of distributions: Field quantities such as stress and flow velocity can be obtained as distributions, allowing for evaluation of results at arbitrary locations. - Learning from measured data: If sufficient measured data is available, a proxy model can be constructed without simulations. ■ Service Content We provide the know-how of deep learning necessary for constructing proxy models and answer fundamental questions that serve as hurdles to data utilization, such as: - How to use data for predictions - What features to extract for predictions - What models to use for learning data features ■ Reasons to Choose ASTOM Among the plethora of AI services available, ASTOM is the only technology that specializes in CAE and can directly generate simulation results. It is also unique to ASTOM's CAE proxy solutions to predict not only changes in numerical parameters such as material properties and boundary conditions but also predictions based on shape changes.
Price information
You can approach the operation of the CAE agent solution in stages. Starting with the question, "Will the CAE agent solution be helpful for this issue?", we will respond to your individual requests regarding budget, duration, and more. - Issue Analysis: Free - Data Consulting: From 500,000 yen - Agent Model Construction: From 1,500,000 yen - System Development: From 2,000,000 yen - Support: From 500,000 yen
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Applications/Examples of results
■ Surrogate model for predicting steady-state stress in structural analysis Replaces the calculation of steady-state stress under tensile loading of a perforated aluminum plate, predicting the distribution and maximum value of von Mises stress. ■ Surrogate model for predicting unsteady vortices in fluid analysis Predicts the time-varying distribution of Kármán vortices within piping. ■ Surrogate model for predicting rainfall from measured data Trains on satellite global precipitation maps (GSMaP) to predict rainfall across Japan one hour later.
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Company information
1. Diversification and Advancement As a cutting-edge comprehensive testing machine manufacturer that meets the diverse needs of all customers, we are committed to connecting to the 21st century. 2. Responsibility and Duty We are dedicated to maintaining our position as the mother tool of the industry and coexisting with our customers. 3. Harmony and Coexistence We strive for harmony with our employees, the community, and society, aiming to be a "good corporate citizen."
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