With OpenMDAO version 3.37.1 and later, JAX (a machine learning library from Google) has been included as an optional dependency. Brings with it the ability to automatically differentiate (AD) components, assuming that they are written in a JAX-traceable way. Think of this as python code with a few modifications. We have doc pages (updated) on how to get up and running with JAX, as well as a video example.

While the OpenMDAO code base is constantly improving, the inclusion of AD is perhaps one of the largest step changes in OpenMDAO that we have seen in several years. AD is one of the most requested features from our users as it can decrease the amount of effort required to make models, as well as decrease maintenance of those models over the long term. To give you an idea of the type of impact that JAX AD can have, we had an explicit component that was 225 lines of code, and using JAX AD we shortened that to just 80 lines. The majority of the effort of designing the component was in calculating those analytic derivatives. The derivative computation time of JAX AD vs. analytical derivatives vs. Finite Difference is something that we need to explore in the future.

We hope that this new capability that the OpenMDAO development team created will be very useful to you. Please keep us informed of your successes and challenges with this update. As always, you can get answers to your OpenMDAO questions on Stack Overflow.

The MDAO team at NASA is please to announce that we will be hosting another set of four interns over the summer 2025 term. They will be working on Aviary, which is OpenMDAO with physics for aircraft modelling and optimization. Last year’s interns created numerous aircraft models, identified bugs, and submitted fixes. Applications are open now and please tell your students to apply by October 25th to be considered in the first round.

Aviary Internship Applications

NASA is sponsoring internships focused around Uncertainty Quantification (UQ) during summer of 2024. To better understand the potential impact of new aircraft and technologies, these uncertainties must be modeled. UQ is a process in by which these unknown factors can be mathematically modeled to allow a more robust estimate of the vehicle level performance. This internship will contribute to the development and application UQ methods and techniques in multidisciplinary design analysis and optimization frameworks such as OpenMDAO.

The most competitive candidates will have a background in Python and OpenMDAO programming.

Apply Now.

Summer 2024

Internship applications to work with the OpenMDAO / Aviary team modelling traditional and novel aircraft in Aviary are open through August 31, 2023. Aviary will be an open-source, aircraft preliminary design tool, which will be launched in December 2023. We are looking for a number of interns to stress-test the tool in summer of 2024 by building novel and traditional aircraft using the tool. We’ll be collecting feedback on ease-of-use, bugs, and modelling challenges for custom subsystems.

Applicants most have at least completed their Junior year of college by the start of the internship. Familiarity with the python programming language is going to be essential as well as a some understanding of aircraft design.

Application window will closed by August 31st, 2023 with the hope that offer letters will be sent out in the December time frame.

Apply Now

We are continuing to tackle the requests for capabilities and features which came up at the OpenMDAO workshop in October 2022. Given the new year, we will be updating our roadmap soon to plan a general path for development in 2023.

Justin Gray has departed the OpenMDAO team after over a decade of leading the project. The OpenMDAO project is a direct result of Justin’s effort to expand adjoint-based optimization and increase the complexity of NASA’s system-modeling capabilities for aviation. Under Justin’s leadership, OpenMDAO was developed from the idea that adjoint-based optimization would be more efficient, to successful system-level studies of novel hybrid and all-electric aircraft. Justin’s future effort will be focused on a start-up that he co-founded and we have no doubt he will be successful to anything he applies his talents to. If you wish to reach out to him personally, please contact him via Justin’s personal email.

We often said that Justin did the work of two people and so it’s no surprise that we have two people stepping up to fulfill different aspects that Justin previously managed. Rob Falck will continue as the development team lead for OpenMDAO and Dymos, managing aspects of the codes’ technical development. Eliot Aretskin-Hariton will be the external partnerships lead. Eliot organized the 2022 OpenMDAO workshop and has also been serving as the integration-lead for the large system-level optimizations that the team has been publishing over the last few years including the Tilt-wing and Quad-Rotor concept vehicles. (You can read more about those in Publications if you have not read them already.) If you’re looking for new ways to collaborate with the OpenMDAO team, please send Eliot an email.

-Eliot and Rob

PDFs of the presentations are available below. Videos of the presentations have been uploaded to youtube and linked here after they are edited in the coming month. Check this post for updates.

Government and Industry Presentations

• OpenMDAO Development Update (pdf | video)- Rob Falck, NASA
• Improvements to Interpolators & Lessons Learned (pdf | video) – John Jasa, NASA
• Dymos Development Update (pdf | video) – Rob Falck, NASA
• Model-Based Systems Analysis & Engineering (MBSA&E) for the Sustainable Flight National Partnership (SFNP) (pdf | video) – Eric Hendricks, NASA
• Training resources being developed (pdf | video) – John Jasa, NASA
• Improvement Proposals – Poems ( video ) – Rob Falck, NASA
• Co-design of Transmission & Distribution for improved power system planning and Operation (pdf | video) – Aadil Latif, NREL
• Project Gemini: Towards Gradient-Based Optimization Using Measures of Effectiveness (pdf | video) – Christopher Lupp, AFRL
• Gradient-Based Optimization of Power and Thermal Management Systems (pdf | video) – Christopher Lupp, AFRL
• Leveraging on OpenMDAO to enhance MDO capability at ONERA (pdf | video) – Sébastien Defoort, ONERA
• Mphys: Standardizing High-Fidelity Optimization with OpenMDAO (pdf | video) – Kevin Jacobson, NASA
• Community Needs Discussion (video unavailable)

Academia Presentations

• MDO with Coupled Adjoints: From the Unified Derivatives Equation to OpenMDAO (pdf | video) – Joaquim Martins, University of Michigan
• Conceptual Aircraft Design in OpenMDAO (pdf | video) – Eytan Adler, University of Michigan
• Towards Efficient Aero-Structural-Acoustic Optimization for Urban Air Mobility Vehicle Design (pdf | video) – Bernardo Pacini, University of Michigan
• Aeropropulsive Design Optimization and Nonlinear Solver Development in OpenMDAO (pdf | video) – Anil Yildirim, University of Michigan
• Coupled Spacecraft System and Trajectory Optimization Framework using GMAT and OpenMDAO (pdf | video) – Gage Harris, Iow a State University
• Design of Floating Offshore Wind Turbines Using OpenMDAO and Dymos (pdf | video) – Yong Hoon Lee, University of Memphis
• Topology Optimization, Second Derivatives and OpenMDAO (pdf | video) – Graeme Kennedy, Georgia Institute of Technology
• Multidisciplinary Design Optimization for Novel Offshore Systems (pdf | video) – Kapil Khanal, Cornell University

If you’re interested in a job at NASA, we have a current opening posted on the USA Jobs website for a position within the branch that both develops OpenMDAO and builds applications for it like pyCycle, Dymos, and Mphys to do systems analysis and conceptual aircraft design. In this position you’d be working on propulsion modeling, electric aircraft propuslsion system design, as well as a decent amount of code development.

If you’re looking for a broad new challenge, and like working with OpenMDAO, please apply!

With the OpenMDAO community converging (pun intended!) on NASA Glenn Research Center for the
OpenMDAO Workshop, the Mphys community will be using the opportunity to hold a one day workshop on Oct. 26th. That is ​immediately following the OpenMDAO Workshop on October 24th and 25th.
Mphys is a collaboratively developed OpenMDAO library which is tackling
one of the major barriers to wider adoption of high-fidelity MDAO:
modularity through standardized interfaces for the coupling of multiphysics problems.
​
The Mphys Workshop will be an opportunity to learn more about multiphysics optimization and see the types of problems people are applying it to.
It will also be a chance to participate in the planning for the next steps of Mphys development.
​
Whether you’ve been collaborating with us on Mphys for years or will be new to Mphys,
we’re looking forward to seeing you there! Register here.
If you are not able to join us in person, we are planning to have a virtual attendance option.
Stay tuned for more information on that

Agenda

8:00am – Refreshments
8:30am – Welcome
8:45am – State of OpenMDAO development – Visualization Tools / N2, Reporting System (
9:45am – State of OpenMDAO development – Improvements to Interpolators & Why not to use Piecewise Linear
10:00am – Break
10:15am – State of Dymos development – New Dymos Features
10:45am – Model-Based Systems Analysis & Engineering (MBSA&E) Effort and vision / overview
11:30am – Training resources being developed
12:00pm to 12:15pm – Lunch Starts
1:15pm – Poems, critical ones being worked on (#69 + others)
1:30pm – NREL uses of OpenMDAO – Aadil Latif
2:00pm – AFRL/QUAD Aero-Propulsion system optimization
2:30pm – AFRL Effectiveness-Based Design: Current Work and Future Challenges
3:00pm – AFRL – creating a PTMS tool in OpenMDAO
3:30pm – Break
3:45pm – ONERA – FAST-OAD and WhatsOpt
4:15pm – Community Needs Discussion
5:00pm – End of Day 1

Day 1 Evening:
6:00pm – Dinner and Board Games at TableTop Cafe Event

Day 2 Morning:
8:00am – Refreshments
8:30am – Welcome
8:45am – UMich Presentations – broad view of theory, applications, and future MDO Lab work
9:15am – UMich Presentations – OpenConcept
9:45am – UMich Presentations – OpenMDAO Solver Development / aeropropulsive work for Thesis
10:15am – Break + Exchange Store for Swag
10:45am – UMich Presentations – aeroacoustic optimization of eVTOL vehicles
11:15am – MPhys Overview that will include MDO Lab contributions
11:45am – Open Discussion
12:00pm to 12:15pm – Lunch Starts
1:15pm – Iowa State University – OpenMDAO & GMAT Integration
1:45pm – University of Memphis – Design of Floating Offshore Wind Turbines
2:15pm – Structural and Topology Optimization Applications from Georgia Tech
2:45pm – Cornell – Design Optimization of Offshore Systems
3:15pm – Break
3:30pm – Open Discussion
5:00pm – End of Day 2

The OpenMDAO workshop is returning to the NASA Glenn Research Center in Cleveland Ohio on October 24-25th. Signup for a seat now! We have a few open slots for external presentations, and you can propose a topic when you sign up.

This is an opportunity for users and developers to meet and have conversations about the next steps for OpenMDAO development, the capabilities you’d like to see added to the toolbox, and the challenges you’re facing with your current implementations. In our first workshop we presented some of the new tools we were building and the POEM process for how the community could interact with the Dev team and propose upgrades. The world got in the way of holding follow up in-person annual workshops, but we did host a 2020 reverse hackathon to maintain links to the community and get a better sense of the kinds or problems that you were facing. These were great opportunities for you, our valued users, to give the Dev team feedback on areas we could work on improving.

For this next in-person workshop we’d like to present you with some of the new tools we’ve built in the last four years and new training resources we are creating for you. Additionally, we want to hear from you about what stumbling blocks exist in your organizations that are preventing OpenMDAO usage. We also want to hear from our users about the cool new things you’re building in OpenMDAO and what are your biggest challenges to adopting OpenMDAO internal to your organization.

We look forward to seeing you in Cleveland to be a part of the OM community!

Professors Martins and Ning have published a new text book on multidisciplinary design optimization, and they’ve generously decided to give the digital version away for free!

There are good lessons on Problem formulation (Section 1.2), comparisons of gradient-based and gradient-free algorithms (Sections 1.4.1-1.4.3), and overview of numerical solver algorithms (Section 3.6), and a great introduction to various MDO concepts (Section 13) — including an introduction to the MAUD equations that underpin OpenMDAO (Section 13.2.6). If you want to learn more about some of the various techniques for taking derivatives of your numerical models, I highly recommend Chapter 6.

They’ve provide code and examples from the textbook in a companion github repo. You can learn more about how AD works, test out surrogate modeling methods, or try out a 10 bar truss example.

They also have a set of lectures based on the content of the book free on youtube

It takes a lot of work to put a text book like this together, and its a true service to the community to offer the digital version for free. If you find it useful in your work, you can thank the authors by citing their book:

@book{mdobook,
author = {Martins, Joaquim R. R. A. and Ning, Andrew},
title = {Engineering Design Optimization},
isbn = {9781108833417},
publisher = {Cambridge University Press},
month = {Jan},
year = {2022}
}