The Daniel Guggenheim School of Aerospace Engineering at Georgia Tech

Core Courses

Advanced Design Methods I – AE 6373

Instructor: Prof. Dimitri Mavris
Lecture Hours: 3
Laboratory Hours: 3
Credit Hours: 4

The main objective of this course is to expose students to complex systems design methodologies from both a theoretical and practical perspective. These methodologies have been matured over the last few decades by industry, government and academic sources (such as the ASDL) starting from traditional design paradigms and transforming them into the current state-of-the-art design trends by utilizing revolutionary mathematical approaches and innovative views from various fields and sectors. The course focuses its theoretical content in these revolutionary approaches and their transformation into formalized design methods for complex systems such as aircraft. The theoretical aspect of the course is complimented by a practical class project that allows students to put in practice the advanced design methods learned through a realistic commercial aircraft design study.

The course covers a variety of topics with which the traditional design paradigm, characteristically deterministic and heavily reliant on historical data, is replaced by a new one characterized by a physics-based, probabilistic perspective. A strong emphasis is placed on techniques and topics used to analyze and understand the behavior of a system, such as statistical methods of variance, design of experiments, and surrogate models. This basis leverages the formulation and implementation of probabilistic approaches with which techniques related to technology infusion modeling, robust systems design, and uncertainty analysis can be addressed. Visualization of these analytical exercises is also emphasized and used to develop critical thinking with respect to expected and unexpected system behavior features. Another major segment of the course deals with decision-making techniques where the synthesis of a multitude of perspectives, preferences, and objectives, are synthesized into a ranked array of solution alternatives. The sensitivity of top-ranked solution variations to perturbations in decision-making parameters such as weighting vectors is explored and shown to be as important, if not more, than system parameters.

This course also features a team project where students are asked to implement the vast majority of concepts and techniques covered through the course, roughly following the Technology Identification, Evaluation, and Selection (TIES) methodology. The project includes a design space exploration exercise based on which an optimization routine is performed based on a baseline aircraft definition. The project also includes modeling the infusion of technologies and the analysis of their impact based on probabilistic approaches that identify key areas of improvement to meet aggressive performance and economic goals. Finally a series of decision-making techniques is used to select a technology portfolio of interest.

Aircraft Design I – AE 6343

Instructor: Prof. Dimitri Mavris
Lecture Hours: 3
Laboratory Hours: 1
Credit Hours: 4

The objective of this course is twofold: First, to expose students to aerospace engineering material over all main areas and with enough detail and complexity so as to award a level of proficiency with which breadth and depth of concepts are adequately balanced. Secondly, for students to become skilled on the graduate level fixed wing design methods, approaches, concepts and tools presented using the aforementioned academic material background as a knowledge basis.

The course begins with a review of requirements analysis and concept down-selection, extending beyond undergraduate level material and into more formalized systems engineering paradigms. Next, constraint and mission analysis is presented starting with the fundamental formulation from a energy-based perspective and then covering the actual implementation of the technique where all assumptions must be cross-consistent and supported by adequate analyses. This section of the course culminates with a project where students are required to build their own constraint analysis and mission sizing tool. The remainder of the course is dedicated to the primary aerospace engineering disciplines with an emphasis on their impact and implications on design as a multi-disciplinary practice. This includes aerodynamics, propulsion, structures, stability and control, and performance. Other design topics and considerations are also addressed, including economics of manufacturers and operators, environmental compatibility, and special topics such as air carrier operations. A second project involves the use of established aircraft performance analysis tools to conduct a design or re-design exercise.

Aerospace Systems Engineering – AE 6372

Instructor: Prof. Daniel Schrage
Lecture Hours: 3
Credit Hours: 3

This course covers a variety of systems engineering topics, techniques, and practices within the context of aerospace engineering and design. The course is heavily reliant on the design projects of the applied design laboratory to implement the systems engineering techniques in a team-based setting through the academic term. Key topics include Introduction to aerospace systems engineering, systems engineering and quality engineering methods and tools, requirements analysis, functional decomposition and allocation, analysis of alternatives, management and planning tools, top-down design decision support processes, computer integrated environments, Integrated Product/Process Development (IPPD), and other established techniques such as Pugh matrices for design concept comparison, and Quality Function Deployment.

Aircraft Design II – AE 6344

Instructor: Prof. Dimitri Mavris
Lecture Hours: 3 (Spring)
Laboratory Hours: 1 (Spring)
Credit Hours: 4 (Spring)

The applied design laboratory constitutes the design practicum for the graduate design curriculum where, during two academic semesters, student teams work on Grand Challenge projects. These are real, relevant, open-ended problems that have been formulated by industry and government partners. Alternatively, Grand Challenge projects include nationally ranked graduate design competitions such as the AIAA graduate design competition or the NASA international design competition. During the first term teams organize themselves and conduct the majority of the background research so that team members can get acquainted with the subject matter. Teams also take care of programmatic considerations and acquire necessary resources such as modeling tools. Regular lectures focus on specific design techniques and skills such as presentation in front of a live audience, electronic reviews, dynamic multi-attribute decision making, and analysis of alternatives. The first term concludes with a critical review with invited subject matter experts.

During the second term there are no lectures, and all attention is turned to the execution of the ‘’Grand Challenge’’ project which is monitored through regular reviews with the course instructor. Beyond the specific deliverables defined by industry/government partners or competition regulations for each project, all teams are required to present a 45 minute presentation during the annual External Advisory Board Review where members of the community representing a multitude of industry and government entities engage the students with questions and comments about their work. In addition, each team conducts a final critical review with project sponsors and subject matter experts around the end of the term.

Advanced Design Methods II – AE 6374

Instructor: TBD
Lecture Hours: 3
Credit Hours: 3

Introduction to modern multidisciplinary design optimization methods and techniques. Numerical optimization with applications, stochastic methods, Genetic Algorithms, multidisciplinary decomposition methods, multi-level optimization strategies.

Advanced Design Methods III – AE 6375

Instructor: Prof. Dimitri Mavris, Invited Lecturers
Lecture Hours: 3
Credit Hours: 3

Advanced Design Methods III is a project-based course covering a variety of methods, techniques, and tools that enable the study, development and analysis of complex systems and systems of systems (SoS). Methods and techniques covered include SoS architecting, qualitative methods, agent-based modeling, system dynamics modeling, discrete event simulation, stochastic process models, graph theory, advanced surrogate modeling, decision making techniques, game theory, and real options. For each technique, if applicable, a software tool for implementation is provided to students and introduced in a lab-style classroom tutorial. Each of these components is covered individually, including the theoretical formulation, criteria for applicability, and application to example problems. These techniques are then woven together via a semester-long project that teaches students how to combine these complementary techniques to solve a real world problem, using the SoS-level Grand Challenge problems as the foundation for the project.

The primary objective of the course is for students to leave with an appreciation of the challenges and opportunities in SoS research, and have a toolbox of methods and tools that can be applied when faced with these problems in a real-world setting. For each method and technique in the toolbox, students should walk away with a basic philosophical understanding as well as the skills to practically implement these techniques. Additionally, students will have gained actual experience with commonly used tools for implementation through the execution of the project. Students should gain an appreciation for how techniques can complement one another, and at what point in the design, development, and decision making process each is most appropriate, and how they can be used in tandem to gain a more complete set of information about the problem. The course concludes with a critical review of the project conducted by the course instructor(s), and any specialized guests the instructors choose to invite from the various problem topic areas.

Air Breathing Propulsion Systems Design – AE 6361

Instructor: Prof. Brian German
Lecture Hours: 3
Credit Hours: 3

Introduction to propulsion system cycle analysis and design at the conceptual and preliminary levels, with emphasis on gas turbine engines. Develop a working understanding of engine cycle analysis, basic component performance, engine installation effects, and operability for aircraft gas turbine propulsion systems. Learn the basics of the conceptual and preliminary design process for both the commercial and military engine markets. Explore emerging and proposed propulsion system concepts intended to address the ever-increasing needs for improved fuel efficiency, reduced noise, and increased aircraft performance.

Safety by Design – AE 6362

Instructor: Prof. Daniel Schrage
Lecture Hours: 3
Credit Hours: 3

Autonomous situational flight model allows students to examine complex behaviors in the "pilot-vehicle-operational conditions" system. Flight certification and airworthiness requirements are mapped into formal scenarios.