Optimization from a Working Baseline: A Design Education Approach

Nathan Delson; Mark Anderson

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Conference: 2012 ASEE Annual Conference & Exposition
Location: San Antonio, Texas
Publication Date: June 10, 2012
Start Date: June 10, 2012
End Date: June 13, 2012
ISSN: 2153-5965
Conference Session: Design Tools and Methodology II
Tagged Division: Design in Engineering Education
Page Count: 13
Page Numbers: 25.1013.1 - 25.1013.13
DOI: 10.18260/1-2--21770
Permanent URL: https://peer.asee.org/21770
Download Count: 381

Paper Authors

biography

Nathan Delson University of California, San Diego

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Nathan Delson’s interests include mechatronics, biomedical devices, human-machine interfaces, and engineering education. He is Co-founder and Past President of Coactive Drive Corp., which develops novel actuators and control methods for use in force feedback human interfaces. Medical device projects include an instrumented mannequin and laryngoscope for expert skill acquisition and airway intubation training. He received his undergraduate degree in mechanical engineering from University of California, San Diego, and then went on to get a doctorate in mechanical engineering from the Massachusetts Institute of Technology in 1994. He was a lecturer and Director of the Design Studio at Yale University for four years, and then returned to his alma matter, UC, San Diego, in 1999. He is now a tenured lecturer and Director of the Design Center in the Department of Mechanical and Aerospace Engineering. He teaches hands-on design courses including an introductory design class, a mechatronics class, and a capstone design class. His interests in design education include increasing student motivation, teamwork, and integration of theory into design projects.

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Mark Anderson University of California, San Diego

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Abstract

Optimization from a Working Baseline: A Design Education ApproachBy necessity many student design projects are compressed into a short time period and use lowcost components. It is often tempting to tackle ambitious open-ended design challenges withinthis short time period. However, as a consequence many students rush to complete designswithout optimization, or use trial-and-error rather than analytical optimization (which isespecially tempting with low cost components). Our approach has been to use two separate typesof design projects, with one focused on use of analysis for optimization, and a second that istruly open-ended.The analytical optimization project uses the approach of “optimization from a working baseline.”With this approach, all student teams start with the same working baseline design, and then aretasked with improving system performance. This approach skips the concept generation phase ofdesign, but ensures that all teams have a working design that is well suited for a multi-factorialoptimization effort.This approach has been applied to two courses. The first is a senior mechanical engineeringcourse where students work on a Mechatronics project. Each pair of students start with a non-optimized turntable, and are tasked with increasing its open-loop and closed-loop performance.Areas of optimization include gear ratio selection, friction reduction, and control system gainselection. The turntable dynamics can be accurately modeled, which leads to analysis-guidedoptimization. The restriction to a single degree-of-freedom turntable limits how open-ended thedesign challenge is. However, this limitation is addressed by a second, real-world designproblem where concept generation is a critical component of the project.The second example of optimization from a working baseline comes from a senior aerospacedesign course. The optimization project involves a small, electric-powered airplane that istethered to a stationary pylon. Teams start from a working baseline that is constructed from aslightly modified commercial airplane kit. Optimization is then performed to improve both high-and low-speed performance. Design changes typically include wing shape modifications, addingaerodynamic control surfaces, and changes to the airplane weight distribution. The motion-constraining tether reduces the degrees-of-freedom such that analytical models can be readilyobtained to support the optimization process. This hardware optimization project occurs inparallel with a second, more open-ended, project where student teams develop conceptualsolutions to a full-scale aerospace design problem.The value and utility of the working baseline approach will be described using examples ofstudent work, as well as comments from the peer review process that takes place in both courses.Most notably, ready success of the baseline design instills confidence that appears to motivateeven lower-performing students to expend additional effort on system optimization. Strongstudents have identified optimization methods beyond what was originally envisioned by thecourse instructors.The approach of starting from a working baseline focuses the project on analysis-drivenoptimization, and prepares students for truly open-ended design projects that are addressed inseparate projects.

Citation
Format

Delson, N., & Anderson, M. (2012, June), Optimization from a Working Baseline: A Design Education Approach Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--21770

TY  - CPAPER
AB  -      Optimization from a Working Baseline: A Design Education ApproachBy necessity many student design projects are compressed into a short time period and use lowcost components. It is often tempting to tackle ambitious open-ended design challenges withinthis short time period. However, as a consequence many students rush to complete designswithout optimization, or use trial-and-error rather than analytical optimization (which isespecially tempting with low cost components). Our approach has been to use two separate typesof design projects, with one focused on use of analysis for optimization, and a second that istruly open-ended.The analytical optimization project uses the approach of “optimization from a working baseline.”With this approach, all student teams start with the same working baseline design, and then aretasked with improving system performance. This approach skips the concept generation phase ofdesign, but ensures that all teams have a working design that is well suited for a multi-factorialoptimization effort.This approach has been applied to two courses. The first is a senior mechanical engineeringcourse where students work on a Mechatronics project. Each pair of students start with a non-optimized turntable, and are tasked with increasing its open-loop and closed-loop performance.Areas of optimization include gear ratio selection, friction reduction, and control system gainselection. The turntable dynamics can be accurately modeled, which leads to analysis-guidedoptimization. The restriction to a single degree-of-freedom turntable limits how open-ended thedesign challenge is. However, this limitation is addressed by a second, real-world designproblem where concept generation is a critical component of the project.The second example of optimization from a working baseline comes from a senior aerospacedesign course. The optimization project involves a small, electric-powered airplane that istethered to a stationary pylon. Teams start from a working baseline that is constructed from aslightly modified commercial airplane kit. Optimization is then performed to improve both high-and low-speed performance. Design changes typically include wing shape modifications, addingaerodynamic control surfaces, and changes to the airplane weight distribution. The motion-constraining tether reduces the degrees-of-freedom such that analytical models can be readilyobtained to support the optimization process. This hardware optimization project occurs inparallel with a second, more open-ended, project where student teams develop conceptualsolutions to a full-scale aerospace design problem.The value and utility of the working baseline approach will be described using examples ofstudent work, as well as comments from the peer review process that takes place in both courses.Most notably, ready success of the baseline design instills confidence that appears to motivateeven lower-performing students to expend additional effort on system optimization. Strongstudents have identified optimization methods beyond what was originally envisioned by thecourse instructors.The approach of starting from a working baseline focuses the project on analysis-drivenoptimization, and prepares students for truly open-ended design projects that are addressed inseparate projects.
AU  - Nathan Delson
AU  - Mark Anderson
CY  - San Antonio, Texas
DA  - 2012/06/10
PB  - ASEE Conferences
TI  - Optimization from a Working Baseline: A Design Education Approach
UR  - https://peer.asee.org/21770
DO  - 10.18260/1-2--21770
ER  -