Award Abstract # 1752054
CAREER: Automated Synthesis of Compound Machines Using Computational Design Optimization

NSF Org: CMMI
Division of Civil, Mechanical, and Manufacturing Innovation
Recipient: UNIVERSITY OF ILLINOIS
Initial Amendment Date: March 12, 2018
Latest Amendment Date: March 12, 2018
Award Number: 1752054
Award Instrument: Standard Grant
Program Manager: Kathryn Jablokow
CMMI
 Division of Civil, Mechanical, and Manufacturing Innovation
ENG
 Directorate for Engineering
Start Date: August 15, 2018
End Date: January 31, 2023 (Estimated)
Total Intended Award Amount: $500,000.00
Total Awarded Amount to Date: $500,000.00
Funds Obligated to Date: FY 2018 = $342,580.00
History of Investigator:
  • Kai James (Principal Investigator)
    kai.james@gatech.edu
Recipient Sponsored Research Office: University of Illinois at Urbana-Champaign
506 S WRIGHT ST
URBANA
IL  US  61801-3620
(217)333-2187
Sponsor Congressional District: 13
Primary Place of Performance: University of Illinois at Urbana-Champaign
104 S Wright St, 319G Talbot Lab
Urbana
IL  US  61801-2935
Primary Place of Performance
Congressional District:
13
Unique Entity Identifier (UEI): Y8CWNJRCNN91
Parent UEI: V2PHZ2CSCH63
NSF Program(s): EDSE-Engineering Design and Sy,
CAREER: FACULTY EARLY CAR DEV
Primary Program Source: 01001819DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 067E, 073E, 1045, 9102
Program Element Code(s): 072Y00, 104500
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041

ABSTRACT

Computer algorithms have been used to automatically generate and optimize designs for everything from aircraft wing structures to cardiovascular stents. However, these algorithms are typically limited to the design of single-body structures, with all motion occurring by means of structural deformation. This limits the complexity of the designs that can be synthesized, preventing the design of multi-body systems containing several moving parts. This Faculty Early Career Development Program (CAREER) project will advance the science of automated computational design by creating new algorithms capable of generating and optimizing multi-body systems. Starting with only a mathematical description of design materials and physical environment, the algorithms will automatically generate assemblies for compound machines that combine multiple basic components such as levers, hinges, wheels, and axles, which together form the foundation of all mechanical design. This work will enable a new level of automated computational design not previously possible under existing design frameworks. The knowledge obtained from this research will benefit a wide range of applications including nanoscale mechanisms for delivery of medications and self-reproducing robotic systems. The project also involves an integrated education program featuring a STEM Pipeline program for undergraduate students from underrepresented minority groups. The program includes bi-weekly labs and seminars, team design projects, and K-12 outreach activities.

The algorithms created in this project will rely upon several novel design formulations devised specifically for the design task. Chief among these will be an original topology optimization-type framework in which the internal topologies of multiple planar design domains are optimized simultaneously, while also optimizing the connectivity between adjacent domains to form compound mechanisms whose components can slide and rotate freely with respect to one another. The mechanical behavior of the designs will be modeled using a combination of finite element analysis and flexible multibody dynamics to capture the rigid body motion and the elastic deflection of the system components. Additionally, adjoint sensitivity analysis will be used to derive and compute the design sensitivities that will power the gradient-based optimization algorithms. The new design framework will be validated via high-fidelity computational simulations, as well as through fabrication and experimental testing. This testing will be used to quantify the efficiency of the generated designs, as determined by their mechanical and geometric advantage.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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