CAREER: Bridging the Gap between Deterministic and Stochastic Structures for Mixed Stochasticity System Design
- Funded by National Science Foundation (NSF)
- Total publications:0 publications
Grant number: 2142290
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Key facts
Disease
COVID-19Start & end year
20222026Known Financial Commitments (USD)
$250,000Funder
National Science Foundation (NSF)Principal Investigator
Hongyi XuResearch Location
United States of AmericaLead Research Institution
University of ConnecticutResearch Priority Alignment
N/A
Research Category
Secondary impacts of disease, response & control measures
Research Subcategory
Economic impacts
Special Interest Tags
N/A
Study Type
Non-Clinical
Clinical Trial Details
N/A
Broad Policy Alignment
Pending
Age Group
Not Applicable
Vulnerable Population
Not applicable
Occupations of Interest
Not applicable
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.
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.