Altair HyperStudy™

Powerful Design Exploration and Optimization

HyperStudy® is a multidisciplinary design study software that enables engineers to explore and optimize their product performance and robustness.

By using automatic processes combining state-of-the-art mathematical methods, predictive modeling and data mining, HyperStudy explores the design space of any system model smartly and efficiently. Users are guided to understand data trends, perform trade-off studies, and optimize design performance and reliability, while considering multiphysics constraints.

The intuitive user interface combined with seamless integration to Altair HyperWorks™ makes design exploration technology accessible to non-experts.

HyperStudy Overview Video

Why Altair HyperStudy?

Improve Product Performance

Proven by engineers and designers from various industries, HyperStudy inspires them to deliver lighter, safer, and more cost effective products, while reducing the development time.

Increase Productivity and Return on Investment

Guide multidisciplinary engineering teams to gain insight from simulations and testing data to find the shortcut to winning designs.

Empower Your Competitiveness

Smart and efficient design space exploration helps engineers reduce trial-and-error iterations and saves time throughout the complete design process.

Key Features

Multidisciplinary Optimization

Perform not only CAD-based but also coupled structural, electromagnetics, CFD, thermal, and multi-body dynamics optimization. Fit models exchanged between experts facilitates multidisciplinary exploration.

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Solver-neutral Open Environment

HyperStudy seamlessly connects to Altair simulation solutions and easily interfaces with third-party tools. Various models and solvers can be linked into a workflow to perform multiphysics design studies.

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Data Mining Tools

Extensive post-processing and data-mining capabilities help engineers gain a faster understanding of their complex design problems, while simplifying the exploration of large design data sets.

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Guided Process

A step-by-step process guides the user through the study definition and results analysis. Features such as reports and archives dramatically improve usability.

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Automatic Data Generation

Create intelligent design variants, manage runs, and extract results automatically. Solution supports multi-execution solver runs and leverages Altair HPC solutions.

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Proven Mathematical Methods

Design of experiments, response surface modeling, and optimization are well suited for large FEA model treatments. Machine learning can be set up from imported or collected data.

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  1. General Process
  2. Study Definition
  3. Predictive Modeling
  4. Multiphysics Optimization
  5. Data Mining