Combining engineering data science with design exploration is the new powerful approach helping designers and engineers from all industries to improve their designs effectively. By using an automatic process for data creation, collection and for import of data sets, HyperStudy enables the design space to be smartly and efficiently explored leading to dramatic time savings. Automatic data analysis, through a broad portfolio of data-mining tools, is essential to gain insight, understand trends and make better decisions, while developing innovating new concepts.

Increasing pressure on improving equipment performance are pushing the limits of simulation predictions. In most cases, model input parameters are hard, if not impossible to determine, and material data tends to be average values produced by suppliers. Calibration by optimization offered by HyperStudy allows tuning of material characteristics with respect to experiments. From composites to magnetic materials, HyperStudy provides an easy way to attain accurate models by minimizing the difference between simulation vs measurement.

Modern architectural design firms face the challenge of offering innovative designs exploiting new materials, while balancing form and function with sustainability initiatives all within delivery schedules. For large scale of architectural, engineering, and construction (AEC) projects, frequent change orders while retaining on-time delivery pressure is common. HyperStudy capabilities for design exploration and optimization bring novel technologies to traditional simulation methods. It enables a broader community of designers and civil engineers to confidently and rapidly apply simulation both earlier and throughout AEC projects, from design guidance to validation, to deliver safe constructions, on time.

Both the time-to-market of a product and its performance are particularly important in the medical domain where a solution delivered on time really changes peoples’ lives. Simulation technology combined with design exploration and machine learning enables engineers to meet those challenges effectively.