computer science

OpenMDAO

OpenMDAO is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand OpenMDAO rather than just read about it. In short: OpenMDAO is an open-source high-performance computing platform for systems analysis and multidisciplinary optimization written in the Python programming language. The OpenMDAO project is primarily focused on supporting gradient based optimization with analytic derivatives to allow you to explore large design spaces with hundreds or thousands of design variables, but the framework also has a number of parallel comput…

Key takeaways

OpenMDAO belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect OpenMDAO to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of OpenMDAO from memory before moving on to harder problems.

Reference excerpt

OpenMDAO is an open-source high-performance computing platform for systems analysis and multidisciplinary optimization written in the Python programming language. The OpenMDAO project is primarily focused on supporting gradient based optimization with analytic derivatives to allow you to explore large design spaces with hundreds or thousands of design variables, but the framework also has a number of parallel computing features that can work with gradient-free optimization, mixed-integer nonlinear programming, and traditional design space exploration. 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. The development of OpenMDAO is led out of the NASA Glenn 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.

Worked examples

Example 1 — a first encounter with OpenMDAO

Start with the simplest possible case. Write down what OpenMDAO claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to OpenMDAO before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about OpenMDAO ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of OpenMDAO

In research: OpenMDAO appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses OpenMDAO in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: OpenMDAO is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cross-platform software, Free software programmed in Python, Mathematical optimization software, so understanding it makes those chapters shorter.
In everyday life: Look for OpenMDAO outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study OpenMDAO in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what OpenMDAO means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain OpenMDAO out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is OpenMDAO in simple terms?

Why does OpenMDAO matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study OpenMDAO?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on OpenMDAO.