OpenMDAO
 | |
| Developer(s) | NASA Glenn Research Center |
|---|---|
| Stable release |
1.6.3
|
| Development status | Active |
| Operating system | Cross-platform |
| Type | Technical computing |
| License | Apache License 2.0 |
| Website |
openmdao |
OpenMDAO is an open-source Multidisciplinary Design, Analysis, and Optimization (MDAO) framework, written in the Python programming language.
The OpenMDAO framework is designed to aid in linking together separate pieces of software for the purpose of combined analyses. It allows users to combine analysis tools (or design codes) from multiple disciplines, at multiple levels of fidelity, and to manage the interaction between them. OpenMDAO is specifically designed to manage the dataflow (the actual data) and the workflow (what code is run when) in conjunction with optimization algorithms and other advanced solution techniques.[1]
The development of OpenMDAO is led out of the NASA Glenn Research Center, with support from the NASA Langley Research Center.
Features
- Library of built-in solvers and optimizers
- Tools for metamodeling
- Data recording capabilities
- Support for analytic derivatives
- Support for high-performance computer clusters and distributed computing
- Extensible plugin library
Applications
NASA’s motivation in supporting the OpenMDAO project stems from the demands of unconventional aircraft concepts like Turbo-Electric distributed propulsion. Although NASA’s focus is on analyzing aerospace applications, the framework itself is general and is not specific to any discipline.
Framework structure
OpenMDAO is designed to separate the flow of information (dataflow) from the process in which analyses are executed (workflow). It does that by using four specific constructs: Component, Assembly, Driver, and Workflow.
The construction of system models begins with wrapping (or writing from scratch) various analysis codes as Components. A group of components is linked together inside an Assembly, specifying the dataflow between them. Once the dataflow is in place, one can select specific Drivers (optimizers, solvers, design of experiments, etc.) and set up a Workflow to determine exactly how the problem should be solved.
OpenMDAO also includes a web-browser-based graphical user interface (GUI) for visual construction, execution, and optimization of models.
See also
External links
Notes
- ↑ J. S. Gray, K. T. Moore, and B. A. Naylor, “OPENMDAO: An Open Source Framework for Multidisciplinary Analysis and Optimization,” in 13th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Fort Worth, TX, AIAA, AIAA-2010-9101, Fort Worth, Texas, 2010.