
NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
Recipient: |
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Initial Amendment Date: | December 12, 2021 |
Latest Amendment Date: | June 3, 2022 |
Award Number: | 2142290 |
Award Instrument: | Continuing Grant |
Program Manager: |
Harrison Kim
harkim@nsf.gov (703)292-7328 CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
Start Date: | January 1, 2022 |
End Date: | December 31, 2026 (Estimated) |
Total Intended Award Amount: | $536,740.00 |
Total Awarded Amount to Date: | $536,740.00 |
Funds Obligated to Date: |
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History of Investigator: |
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Recipient Sponsored Research Office: |
438 WHITNEY RD EXTENSION UNIT 1133 STORRS CT US 06269-9018 (860)486-3622 |
Sponsor Congressional District: |
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Primary Place of Performance: |
191 Auditorium Rd. Storrs CT US 06269-3139 |
Primary Place of
Performance Congressional District: |
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Unique Entity Identifier (UEI): |
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Parent UEI: |
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NSF Program(s): |
EDSE-Engineering Design and Sy, CAREER: FACULTY EARLY CAR DEV |
Primary Program Source: |
01002324DB NSF RESEARCH & RELATED ACTIVIT 010V2122DB R&RA ARP Act DEFC V |
Program Reference Code(s): |
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Program Element Code(s): |
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Award Agency Code: | 4900 |
Fund Agency Code: | 4900 |
Assistance Listing Number(s): | 47.041 |
ABSTRACT
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).
Systems or products composed of parts that have random (or stochastic) characteristics pose a significant challenge to the design of complex engineering systems. There is a lack of systematic methods for designing artifacts utilizing this type of mixed stochasticity structure. This Faculty Early Career Development Program (CAREER) project will establish a novel computational framework that bridges the gap between random and regular structural patterns to enable: 1) generative design of structures with tailorable stochasticity and desired properties and 2) design of mixed stochasticity structural systems that consist of mixed stochastic structural units to achieve optimal performance. Two sets of engineering applications will be used to evaluate the methodology and demonstrate its benefit to society: design of microstructural materials in energy storage systems and design of a mixed stochasticity structural system for vehicle impact safety. The broader application of the research developments will benefit a wide range of industries, such as high-capacity energy storage materials, structural safety and reliability, and automotive lightweighting, which rely on materials and structures with mixed stochasticity. Furthermore, the results of this research will contribute theories and methodologies that benefit the reliability design of mixed stochasticity systems, such as power grid systems, water distribution systems, and transportation systems. The education and outreach objective of this project is to create a prototype of education-research-industry integration and apply it to K-12 education outreach, outreach to local businesses, and university education. The K-12 education outreach will motivate students to pursue education and careers in science and engineering fields. The outreach to local businesses will assist small businesses and small manufacturers to compete in the post?COVID-19 world. The integration among research, industry practice, and education will strengthen the undergraduate and graduate students? learning experiences.
The overarching research goal of this project is to create a novel computational framework that bridges the gap between deterministic and stochastic structures by establishing a unified design space that covers structural patterns whose stochasticity ranges from random to regular. This framework enables generative design of microstructures/structures with tailorable properties and stochasticity, as well as design of a mixed stochasticity structural system that consists of deterministic and stochastic structural units to achieve optimal performance. This research will transform the discovery and design of structural/microstructural systems in three ways. First, a first-of-its-kind design representation method will be developed for mixed stochasticity structures that will enable the design of structures with tailorable stochasticity. Second, the research will provide a theoretical foundation for transferring knowledge between deterministic and stochastic systems to inspire new designs that achieve target properties. Third, a new design framework will be established for the robustness and reliability-based design of mixed stochasticity structural system. The education and outreach plan includes a Science, Technology, Engineering, Arts, and Math (STEAM) project for K-12 teachers and students in underrepresented minority schools, research dissemination to local small businesses and small manufacturers, and integration among university education, research, and industrial collaboration.
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.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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