News & Honors

• Department Head Daniel Hastings was named president-elect of the AIAA. Hastings is the AIAA's 17th president with ties to MIT and the organization's first Black president. He will assume the presidency in May 2024, succeeding current president Laura McGill.

• Wesley Harris has been appointed the AIAA Vice Chair of Fellows Selection Committee by current AIAA President, Laura McGill. Harris will serve as the Vice Chair of this year's Fellows Selection Committee (2024) and then will serve as Chair for the class of 2025, leading selection of the AIAA Class of 2025 Fellows.

• Danielle Wood spoke on "Sustainable Use of Orbital Space for Science and Society" at the 2023 American Association for the Advancement of Science (AAAS) Annual Meeting in D.C.

• A number of AeroAstro faculty, researchers and students participated in MIT Space Week and SpaceTech as speakers or panelists, including: Mia Bruno, Kerri Cahoy, Zachary Cordero, Olivier de Weck, Daniel Erkel, Chloé Gentgen, Jeffrey Hoffman, Daniel Jang, Claire Johnson, Alex Meredith, Adriana Mitchell, Joey Murphy, Ufuoma Ovienmhada, Julia Pasiecznik, Justin Schiavo, Cruz Soto, Will Parker, Hannah Tomio and Danielle Wood.

• Andrew Kopeikin, Nancy Leveson and Natasha Neogi have had a paper accepted for the INCOSE (International Council on System Engineering) conference this summer. The paper describes Andrew's PhD dissertation research on modeling and analyzing complex human-machine collaboration using systems theory.

• Hannah Tomio, a PhD student in STAR Lab was awarded the Corning Women in Optical Communications Scholarship by Corning/Optica. Tomio was honored at the Optical Fiber Communications (OFC) Conference held March 8-12.

Conferences

Space Traffic Management Conference

Students from ARCLab, DINaMo Group and Space Enabled went to the 9th Annual Space Traffic Management Conference at The University of Texas at Austin March 1-2. The conference is mainly organized by Moriba Jah, MIT MLK Visiting Associate Professor 2022-2023.

MOCAT-SSEM: A Source-Sink Evolutionary Model for Space Debris Environment Evolutionary Modeling

Miles Lifson, Daniel Jang, Celina Pasiecznik, and Richard Linares

Geosynchronous Satellite Behavior Classification via Unsupervised Machine Learning

Thomas G. Roberts, Haley E. Solera, Richard Linares

Geosynchronous Satellite Pattern of Life Node Detection and Classification

Haley E. Solera, Thomas G. Roberts, Richard Linares

Feasibility Analysis of On-Orbit Debris Detection Using Commercial Star Trackers

Allan Shtofenmakher, Hamsa Balakrishnan

Mass Reuse for Orbit Changes under a Global STM Regime

Phillip M. Cunio

Research

The "ARTEMIS Steelworks" team (Advancing Reactor Technologies for Electrolytic Manufacturing of In-situ Steel), was selected as one of seven finalists in NASA's 2023 BIG Idea Challenge. They will receive $170,000 to develop their technology, which will support a future metal production pipeline on the Moon. The interdisciplinary team, led by Palak Patel, Jose Soto ‘25, Scarlett Koller and mentored by George Lordos, is currently recruiting additional members to help develop a Molten Regolith Electrolysis proof of concept system to produce steel from lunar regolith simulant.

If you are interested, please email palak@mit.edu or josesoto@mit.edu.

Last summer, members from the Computational Turbulence Group (Yuenong Ling, Gonzalo Arranz, Emily Williams and Adrián Lozano-Durán) participated in the 2022 Center for Turbulence Research Summer Program at Stanford University. Their work, a machine-learning-based closure model for turbulent flows, has been selected for the cover page of the program's proceedings. It is the first application of ML-based high-fidelity CFD to a realistic aircraft configuration.

"Economical sizing and multi-azimuth layout optimization of grid-connected rooftop photovoltaic systems using Mixed-Integer Programming."

Alharbi, Abdulaziz, Zeyad Awwad, Abdulelah Habib, and Olivier de Weck

Applied Energy 335 (2023): 120654.

Solar energy is expected to be a significant contributor to meet the increasing global energy demand. Rooftop photovoltaic (PV) systems account for a substantial portion of the global solar energy potential. However, optimizing the size and layout of these systems remains challenging. Existing approaches either focus on maximizing energy generation, heavily restrict the space of potential layouts, ignore inverter-type implications, or neglect practical aspects, such as minimizing self-shading. This paper presents a mixed-integer programming (MIP) model to address these limitations for PV systems installed on flat rooftops. The proposed model optimizes the net present value (NPV) and can produce multi-azimuth layouts while accounting for practical considerations, including mitigating self-shading, and ensuring rooftop walkability.