AE 598

Spring 2025 All Classes

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Credit: 1 TO 4 hours.

Subject offerings of new and developing areas of knowledge in aerospace engineering intended to augment existing formal courses. Topics and prerequisites vary for each section. See Class Schedule or departmental course information for both.

May be repeated in the same or separate terms if topics vary to a maximum of 12 hours.

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AE 598 class schedule data for spring 2025
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
57732	Lecture-Discussion	PE	1:00PM -2:20PM	TR	410C1 Engineering Hall	Eggl, S	Part of Term: 1 Date Range: 01/21/25-05/07/25 Section Title: Planetary Entry Section Info: Graduate-level overview of planetary entry systems. Topics include: flight mechanics; guidance, navigation, and control systems; thermal protection systems; aerothermodynamics; descent and landing systems; aerocapture; aerobraking; mission and vehicle design; and modeling and simulation. Case studies are used throughout to illustrate technical content. Pre-reqs: AE 312, AE 352, AE 402 (or equivalents) or permission from instructor
39832	Online	PO	ARRANGED	n.a.	n.a.	Eggl, S	Part of Term: 1 Date Range: 01/21/25-05/07/25 Credit: 4 hours Section Title: Planetary Entry Section Info: Graduate-level overview of planetary entry systems. Topics include: flight mechanics; guidance, navigation, and control systems; thermal protection systems; aerothermodynamics; descent and landing systems; aerocapture; aerobraking; mission and vehicle design; and modeling and simulation. Case studies are used throughout to illustrate technical content. Pre-reqs: AE 312, AE 352, AE 402 (or equivalents) or permission from instructor. For more details on this course section, please see http://engineering.illinois.edu/online/courses/. Non-Degree students may enroll on a space-available basis with consent of Program Coordinator, Jenna Russell (jennar@illinois.edu). Restriction(s): Restricted to Graduate - Urbana-Champaign. Restricted to MS:Mechanical Engineerng -UIUC, MS:Env Engr CivilEngr ONL-UIUC, NDEG:Engineering GR ONL - UIUC, MS: Aerospace Engr-Online-UIUC, MENG:Engr:Energy Sys Onl-UIUC, MENG:Mech Engineering Onl-UIUC, MENG:Elec & Comp Eng ONL -UIUC, MENG:Engr:AeroSys Online- UIUC, MENG:ENGR:Digital Ag ONL- UIUC, MS: Civil Engr - Online - UIUC, or MS:Industrial Engr Online-UIUC.
49926	Lecture-Discussion	SR	1:00PM -2:20PM	MW	410B1 Engineering Hall	Tsukamoto, H	Part of Term: 1 Date Range: 01/21/25-05/07/25 Credit: 4 hours Section Title: Formal Methods in AE Robotics Section Info: 4 hours Topic: Formal Methods in Aerospace Robotics This course presents advanced formal methods for providing performance guarantees in motion planning and control (guidance and control) of nonlinear dynamical systems under uncertainty, with a special focus on aerospace and robotic systems. Topics include a review of robotics and optimal control, robust and adaptive control, safe planning and control, risk-aware planning and control, uncertainty quantification, safe reinforcement learning, learning-based/data-driven planning and control, applications in aerospace and robotic systems, and a final project. The themes of the final project will be given, but students are welcome to work on their own ideas. Prerequisites: Statistics (STAT 361, STAT 400, or MATH 461), robotics (AE 482, ECE 470, or ME 445), and feedback control (AE 454 or ECE 486), or permission of instructor. It is desirable also to have some basics of optimal control (AE 504 or ECE 515).
62621	Lecture	UQ1	12:30PM -1:50PM	TR	403B2 Engineering Hall	Panesi, M	Part of Term: 1 Date Range: 01/21/25-05/07/25 Credit: 4 hours Section Title: Uncertainty Quantification Section Info: This course will introduce technique for quantifying the uncertainty of simulation predictions. After the predictive science challenge is introduced and motivated with examples, we will: review basic statistical tools and distributions; discuss probability as measures of belief; examine the strengths, limitations, and design of experiments for calibration and validation; introduce quantitative model selection and hypothesis testing for the design and evaluation of physical models; and present methods to propagate known uncertainties through a predictive simulation to the quantity of interest. Inverse adjoint-based sensitivity methods will be discussed for use in validation and uncertainty quantification. Mechanics based examples will be used throughout for motivation.