Teaching

AerE 3620: Aerospace Systems Integration

Emphasis on impact of component interfaces in aerospace systems. Understand how changes in variables associated with individual components impact the performance of the aerospace system. Specific integration challenges include: capturing implicit disciplinary interactions (e.g. structures/aerodynamics, propulsion/aerodynamics), propagating tolerances through the system (i.e. uncertainty modeling), balancing component attributes in the system objective.

Learning objectives:

  • Formulate engineering design optimization problems
  • Explain the pros and cons of various optimization algorithms
  • Solve single-disciplinary optimization problems analytically
  • Extend design optimization for multiple disciplines or components
  • Understand how different components in aerospace systems interact and how they impact the system’s performance
  • Use computers to solve optimization problems numerically

AerE 4630/5630: Introduction to Multidisciplinary Design Optimization

Introduction to the theory and methods of Multidisciplinary Design Optimization (MDO), including system coupling, system sensitivity methods, decomposition methods, MDO formulations (such as multi-discipline feasible (MDF), individual discipline feasible (IDF) and all-at-once (AAO) approaches, and MDO search methods.

Learning objectives:

  • Compute a system’s performance using numerical simulations
  • Write codes to optimize a system’s performance, subject to constraints
  • Identify the best optimization algorithm and analysis tools for MDO problems.
  • Write a project proposal for an MDO problem of their interest.
  • Solve the MDO problem, analyze the optimization results, and write a project report.

Supervising Undergraduate Students from ISU and NSF REU Programs

We have supervised 12 undergraduate researchers at Iowa State University over the past four years. Each student meets with iDesign lab team members to identify a research topic of interest, conduct a brief literature review of existing methods and tools, learn to run numerical analyses and/or optimization on high-performance computing (HPC) systems, and carry out detailed evaluations of simulation results. Students regularly attend group meetings to share progress and discuss challenges.

These research projects are closely integrated with ongoing iDesign initiatives. For example, undergraduate student Kiet Tuong investigated the impact of unsteady propeller wakes on airfoil aerodynamic performance and performed aerodynamic shape optimization for wing–propeller interaction. He presented and published his work at the 2021 AIAA Aviation Conference. Another student, Andrew Thomas, developed a graphical user interface (GUI) to streamline the use of our design optimization tool, DAFoam; this GUI has since been integrated into the AerE 3620 course project.

In addition, we have supervised four undergraduate researchers through the NSF REU program LAUNCH-UAS from 2021 to 2023. These students conducted MDO research during the summer and presented their work at ISU’s summer research seminars.

Outreach

We collaborated with Iowa State University’s Go Further program to conduct outreach activities for middle school students in Fall 2024. A graduate student and Dr. He gave presentations during a conference session focused on the use of machine learning in paper airplane design.

The session began with personal stories about their career paths, current research in multidisciplinary design optimization, and future career goals. Dr. He then introduced how machine learning and artificial intelligence can enhance our daily lives. This was followed by an interactive, hands-on activity where students folded various paper airplane designs and conducted test flights to evaluate and compare their performance.