pSeven
pSeven is a desktop application that provides advanced tools for Design Exploration and Predictive Modeling, packaged in an easy-to-use graphical user interface.
pSeven allows even non-math experts to solve challenging engineering problems and discover optimal designs just in a few clicks!
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Integrate, Explore & Predict
- Automate complex product design processes and integrate all external software and data into a single workflow
- Solve engineering problems with a complete toolset for Design Exploration and Predictive Modeling
- Compose a model of the product from different data sets, analytical and simulation models
- Explore this model with tools for Design Exploration
- Predict responses for new designs or operational regimes of the product with tools for Predictive Modeling
Latest use cases
Tire dynamics model identification
pSeven based project for Formula Student, a student engineering competition held annually all over the world. The results allowed increasing the accuracy of the mathematical model of the longitudinal movement of the racing car, which even closer brought it to the real model of the car's behavior on the track.
Design Exploration
pSeven allows efficiently exploring model behavior with a wide range of techniques for Design of Experiments (DoE) and solving single- and multi-objective Design Optimization problems with both fast to evaluate analytical models and computationally expensive simulations. With pSeven you can also assess the influence of uncertain parameters of a product on its' characteristics with Uncertainty Quantification (UQ) capabilities.
Predictive Modeling
By creating a predictive model from existing test, experimental and/or simulation data pSeven allows to predict response values for new designs, accelerate complex simulations by many orders of magnitude and capture essential knowledge from vast amounts of data. Such models are also often called approximation models, response surface models (RSM), surrogate models, metamodels etc.
Process Integration
pSeven is a platform that allows to capture even the most complex design processes by integrating tools for Design Exploration and CAD/CAE software you are using into a single workflow, define its logic and collect, analyze and reuse engineering data.
SmartSelection
SmartSelection is an approach in pSeven that automatically chooses the most efficient Design Exploration or Predictive Modeling technique for a given type of problem and data, hides techniques' internal complexity and opens expert level mathematics even for non-math experts.
What's new in pSeven?
Before pSeven v2025.02 we recommended our users to integrate Simcenter Amesim using exposed parameters in the simulation model and batch-mode execution. Despite being a valid and generic approach, it still may not be convenient enough for daily usage.
Addressing the growing number of requests, we introduce a new Amesim block, which streamlines the integration to literally several clicks.
Just specify your Amesim project in the block and it will extract the whole tree of input and output parameters automatically – simply choose what you want to use in your workflow and your model is ready for automated execution, for example, in optimization studies.
The new block enables direct integration of Forge by Transvalor into pSeven workflows. You only should specify Forge project, and the block will automatically extract available input parameters and results and present them in the UI.
Choose which of them to be used and your Forge simulation is ready to be linked with for example DSE block for parametric studies and optimization or other simulation and post-processing tools.
Direct integration blocks were updated to support most recent versions:
- StarCCM block was updated to support newer versions, explicitly tested with version 2302 and should work with all versions above.
- FloEFD block was updated for compatibility with up-to-date versions of Siemens FloEFD.
Why choose pSeven?
From a technical point of view:
- Unique, fast and efficient optimization algorithms.
- Innovative techniques for predictive modeling.
- Automatic selection of the most efficient technique for a given problem and data.
- Powerful workflow engine for process integration and automation.
From a business point of view:
- Reduction of cost expensive physical and computational experiments.
- Reuse of already available in-house engineering data.
- Improved collaboration between different engineering departments.