ModelCenter® Explore is a software solution that provides engineers with an environment to easily:

  • Run powerful algorithms and trade study tools
  • Search, investigate and understand the design space
  • Incorporate multiple variables (cost, performance, risk)
  • Visualize results and the impact of design changes
  • Find optimum solutions

ModelCenter® Explore drives innovation and improves product quality by enabling users to thoroughly explore and understand the design space, make
better decisions, and find optimal solutions.


ModelCenter® Explore is a graphical environment for design investigation and optimization that supports your entire product development team. Once a repeatable simulation workflow has been created with ModelCenter® Integrate, engineers can iteratively execute the workflow (using parallel computing resources if available), with each run corresponding to a different set of inputs. This allows engineers to explore and quantify the performance, cost, reliability, and risk of a large number of different design alternatives in a relatively short period of time.

ModelCenter® is also capable of exercising the engineering workflows using a rich set of trade study tools, such as parametric studies, Design of Experiments (DOE), optimization algorithms, and robustness and reliability analyses. Decision support tools such as sensitivity analyses, multi-dimensional scatter-plots, and trade-off charts allow engineers to identify key design parameters, understand important trade-offs, and ultimately to identify better designs. It is adaptable, and works well with groups whose designs change frequently.


A suite of built-in design optimization algorithms can be used to automatically search for improved designs. Users specify their goals and requirements as well as a list of the workflow input variables that can be modified. The optimization algorithm then repeatedly runs the workflow and attempts to find the values for the input variables that best achieve the user’s goals while satisfying their requirements. A number of different types of algorithms are included in the framework (gradient algorithms, genetic algorithms, algorithms based on response surface models, etc.), along with a wizard to help users choose the algorithm(s) that are most appropriate for solving their problem. Users can add their own custom algorithms to the framework using the Algorithm Development Toolkit.

Probabilistic Analysis

Probabilistic analysis tools can be used to help users assess and understand the impact of uncertainties on their engineering analysis results. For example, a designer may wish to better understand the effect of manufacturing tolerances on the performance and/or failure probability of a product. The Reliability Pak includes a number of algorithms (including Monte Carlo analysis) that will help engineers to make these assessments. When used in conjunction with an optimization algorithm, these reliability tools allow users to perform robust and reliability based design.

Decision Support

Results from multi-run studies can be used to discover important trends and tradeoffs, evaluate uncertainty and risk, and to optimize the system design. ModelCenter® Explore provides a suite of powerful multi-dimensional data visualization tools for interpreting and analyzing the results.