Altair HyperStudy

Product information

Multi-disciplinary Design Exploration & Optimization

Altair HyperStudy is a multi-disciplinary design exploration, study, and optimization software for engineers and designers. Using design-of-experiments, metamodeling, and optimization methods, HyperStudy creates intelligent design variants, manages runs, and collects data. Users are guided to understand data trends, perform trade-off studies, and optimize design performance and reliability. HyperStudy’s intuitive user interface combined with its seamless integration to Altair HyperWorks™ makes design exploration technology accessible to non-experts.

1. Benefits

HyperStudy provides engineers and designers a user-friendly environment with state-of- the-art design exploration methods and data mining tools to:

Efficiently understand the relationships between design parameters and design requirements
Easily sort, analyze, and explore large design data sets
Perform quick trade-offs between conflicting designs requirements
Quickly calibrate simulation models to correlate with test data
Increase product life and robustness
Reduce design development cycles
Increase the return on their CAE solver investments

2. Capabilities

2.1. Design of Experiments (DOE)

DOE helps engineers to clearly understand the relationships between design variables and overall system performance. DOE methods in HyperStudy include:

Box-Behnken
Hammersley
Central composite design
Modified Extensible Lattice Sequences (MELS)
D-Optimal
Latin HyperCube
Direct input of external run-matrix
Plackett-Burman
Fractional factorial
Taguchi
Full factorial
User defined

2.2. Fit Approach

Fit approach is used to create meta-models to replace computationally intensive simulations. They are also used to smooth noisy functions to enable optimization algorithms to work more effectively.

Fit models can be used in DOE, optimization, and stochastic studies. HyperStudy’s fit module allows use of different methods for different responses. Available fit methods are:

Least squares regression
Moving least squares
Radial basis function
HyperKriging

2.3.Optimization

HyperStudy offers multidisciplinary optimization as well as reliability and robustness optimization. Through multidisciplinary design optimization, engineers can improve the overall design performance. If variations in design and operating environments are critical to design quality, reliability and robustness optimization can be used reduce the sensitivity of designs to these variations.

HyperStudy contains a comprehensive suite of optimization algorithms that include:

Altair’s proprietary optimization algorithm, adaptive response surface method and global response surface method (ARSM and GRSM)
Sequential quadratic programming (SQP)
Method of feasible directions (MFD)
Genetic algorithm (GA)
Multi-objective GA (MOGA)
Sequential optimization and reliability analyses (SORA).
Single loop approach (SLA)
User-defined optimization algorithms (through included API)

2.4. Stochastic

The stochastic approach in HyperStudy allows engineers to assess reliability and robustness of designs and provide qualitative guidance to improve and optimize the design based on these assessments.

Stochastic studies can be performed using either the exact simulation or fit model. HyperStudy sampling methods include:

Simple Random
Latin Hypercube
Hammersley
Statistical distribution functions (Normal, Uniform, Triangular, Weibull and Exponential)
Modified Extensible Lattice Sequences (MELS)

2.5. Post-Processing and Data Mining

HyperStudy helps engineers to gain a deeper understanding of a design through extensive post-processing and data-mining capabilities. This significantly simplifies the task of sorting, analyzing and exploring large design data sets. Some of the available tools are:

Correlation matrices
Scatter plots
Effects and Interactions tables and plots
Histograms
Parallel coordinate plots
Pareto plots
Ordination plots
Box plots

2.6. Parameterization of Analysis Models

HyperStudy has a number of models among which are Altair HyperMesh™, Altair MotionView™, Spreadsheet, Workbench, Altair SimLab™, Altair Feko™ and Altair Flux™. HyperMesh, Altair MotionView and Altair SimLab™ models are HyperStudy's direct integration with Altair pre-processors HyperMesh, MotionView and SimLab. They provide the capability to directly parameterize finite-element, multi-body, and fluid-dynamicssolver input data for CAE solvers, thus making the study parameterization process easy and efficient. Feko, Altair Flux,™ Spreadsheet, and Workbench models simplify the use of these tools with HyperStudy by direct parameter and response import. For other solvers, HyperStudy is a powerful parameterization tool with a built-in text and numeric processor.

2.7. Shape Parameter Definition Using Morphing Technology

Shape changes can be easily created on complex finite-element models using the powerful morphing technology in HyperMesh. These morphed shapes can be saved as HyperStudy shape parameters.

2.8. Direct Interfaces to Popular Solvers

To facilitate streamlining the study process without additional data filtering and translation steps, HyperStudy directly reads the plot and animation data of many solvers, including: