pSeven
 | This article contains content that is written like an advertisement. (January 2021) |
 | |
| Developer(s) | pSeven SAS |
|---|---|
| Stable release | 6.51
/ December 27, 2023 |
| Operating system | Cross-platform (Windows, Linux) |
| Available in | English |
| License | Proprietary |
| Website | www |
pSeven is a design space exploration (DSE) software platform that was developed by pSeven SAS that features design, simulation, and analysis capabilities and assists in design decisions. It provides integration with third-party CAD and CAE software tools; multi-objective and robust optimization algorithms; data analysis, and uncertainty quantification tools.
pSeven comes under the notion of PIDO (Process Integration and Design Optimization) software. Design space exploration functionality is based on the mathematical algorithms of pSeven Core Python library.
pSeven algorithms from pSeven Core laid the foundation for the development of pSeven Enterprise, a cloud-native low-code platform used for engineering automation.
History[edit]
In 2003, researchers from the Institute for Information Transmission Problems started collaborating with Airbus to perform R&D in the domains of simulation and data analysis using the pSeven Core library as pSeven's background. The first version of the pSeven Core library was created in association with EADS Innovation Works in 2009. Since 2012,[1] pSeven software platform for simulation automation, data analysis, and optimization has been developed and marketed by pSeven SAS, incorporating pSeven Core.
Functionality[edit]
Data and model analysis[edit]
pSeven provides a variety of tools for data and model analysis:
- The design of experiments allows controlling the process of surrogate modeling via an adaptive sampling plan.
- Sensitivity and Dependence analysis are used to filter non-informative design parameters in the study, ranking the informative ones with respect to their influence on the given response function and selecting parameters that provide the best approximation.
- Uncertainty quantification capabilities in pSeven are based on OpenTURNS library.
- Dimension reduction is the process of reducing the number of random variables under consideration by obtaining a set of principal variables.
- Predictive modeling capabilities in pSeven incorporate several proprietary approximation techniques, including methods for ordered and structured data, replacing expensive computations with approximation models.[2]
Optimization[edit]
Optimization algorithms implemented in pSeven allow solving single and multi-objective constrained optimization problems as well as robust and reliability-based design optimization problems. Users can solve both engineering optimization problems with cheap semi-analytical models and problems with expensive (in terms of CPU time) objective functions and constraints.[3][4] The SmartSelection adaptively selects the optimization algorithm for a given optimization problem.
Process integration[edit]
pSeven provides tools to build and automatically run the workflow, to configure and share library of workflows and to distribute computation, including HPC. The main process integration tools of pSeven:
- CAD/CAE integration adapters (SolidWorks, CATIA, NX, PTC Creo, KOMPAS-3D, ANSYS Workbench), CAE solvers and other engineering tools (ANSYS Mechanical, ANSYS CFD, FloEFD, CST Microwave Studio, ADAMS, Simulink, MATLAB, Scilab, Abaqus, Unified FEA, Nastran, LS-DYNA, Simcenter STAR-CCM+, OpenFOAM, etc.)
- High Performance Computing (HPC) capabilities (supported batch systems: SLURM, TORQUE, LSF)
- Functional Mock-up Interface (FMI) for model exchange and co-simulation
Applications[edit]
pSeven's application areas are different industries such as aerospace,[5] automotive, energy, electronics, biomedical and others.
pSeven has been used for the optimization of layered composite armor in order to reduce its weight[6] and for multidisciplinary and multi-objective optimization of an aircraft family.[7]
References[edit]
- ^ OraResearch, Design Space Exploration Industry Timeline
- ^ Burnaev E., Prikhodko P., Struzik A., "Surrogate models for helicopter loads problems", Proceedings of 5th European Conference for Aerospace Science"
- ^ F. Gubarev, V. Kunin, A. Pospelov, "Lay-up Optimization of Laminated Composites: Mixed Approach with Exact Feasibility Bounds on Lamination Parameters"
- ^ Dmitry Khominich, Fedor Gubarev, Alexis Pospelov, "Shape Optimization of Rotating Disks", 20th Conference of the International Federation of Operational Research Societies, 2014
- ^ Airbus achieves multi-objective optimization of its aircraft families with pSeven Core (ex Macros) software
- ^ A. Bragov, F. Antonov, S. Morozov, D. Khominich, "Numerical optimization of the multi-layered composite armor", Light-Weight Armour Group (LWAG) conference-2014
- ^ Alestra S., Brand C., Druot T., Morozov S., "Multi-objective Optimization of Aircrafts [sic] Family at Conceptual Design Stage", IPDO 2013 : 4th Inverse problems, design and optimization symposium, 2013 June 26–28, Albi, ed. by O. Fudym, J.-L. Battaglia, G.S. Dulikravich et al., Albi; Ecole des Mines d'Albi-Carmaux, 2013 (ISBN 979-10-91526-01-2)