Project Grant DESC0015071

This Project Grant award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) provides $415,754 to the Texas A&M Engineering Experiment Station (Tees) to advance computational methods for accurately characterizing the mechanical behavior of critical materials. The key products and services to be delivered include: Developing a global programming "epsilon-optimal" spatial branching technique using a novel class of efficient convex underestimators. An...

This $211,135 federal Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to expand and improve the use of stochastic simulation models for optimal decision-making under uncertainty. The award, with a performance period from July 2024 to June 2027, will enhance the SIMOPT testbed of simulation optimization problems and solvers, making it more powerful, widely applicable, and aligned...

This Project Grant from the National Science Foundation's Engineering program (CFDA 47.041) provides $181,366 to Virginia Polytechnic Institute and State University for research developing efficient surrogate modeling methods to predict design performance in the presence of discontinuities. The research aims to facilitate complex engineering design problems by modeling system performance as a piecewise continuous function and developing local Gaussian process approaches that accommodate regime...

This $275,000 Project Grant from the National Science Foundation's (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences (CFDA 47.049) program supports research on optimization algorithms and digital twins constrained by partial differential equations (PDEs) that incorporate data to make decisions resilient to uncertainty. The research will develop: (1) inexact adaptive semismooth Newton and trust-region methods to solve these optimization problems; (2) primal dual...

This $841,716 National Science Foundation project grant supports the development of a new Multi-Fidelity Accelerated Global Search framework by the University of Washington from June 2022 through May 2025. The framework will intelligently combine high- and low-fidelity models to guide computational effort in optimizing complex bio-manufacturing processes through statistical analysis. This addresses the need for large-scale stochastic optimization that reduces high-fidelity simulations by...

The National Science Foundation (NSF) Directorate for Engineering (CFDA 47.041) awarded a $372,500 project grant to the Regents of the University of Minnesota to develop AI-enabled automated algorithms for solving complex mathematical optimization problems in chemical engineering. The 3-year research program will leverage state-of-the-art artificial intelligence and machine learning methods to automate the selection and configuration of optimization algorithms for problems arising in chemical...

This $255,934 National Science Foundation Technology, Innovation, and Partnerships grant will support Exlattice, Inc.'s development of machine learning-powered additive manufacturing simulation software. Under the SBIR Phase I Project Grant, Exlattice will create a proof-of-concept for 3-5 orders of magnitude faster process simulation software to predict manufacturing failures from high temperature, residual distortion, and residual stresses. The proposed hybrid data-driven and physics-based...

This Project Grant award from the National Science Foundation (NSF) Division of Civil, Mechanical, and Manufacturing Innovation aims to develop data-driven methodologies for efficient monitoring and operation of multistage manufacturing systems. The $300,442 award to the University of Wisconsin System will establish an integrated mathematical framework to model the spatial interactions between machines and the temporal degradation of each machine in a multistage manufacturing process. The...

Federal Grant Award Summary The National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation awarded a Faculty Early Career Development (CAREER) grant of $551,703 to Texas A&M Engineering Experiment Station (beginning July 1, 2026, through June 30, 2031) under the Engineering program (CFDA 47.041). The award funds research to advance simulation optimization methodologies by coupling exploratory simulation analysis with optimization techniques to enable more...

The National Science Foundation awarded a $200,000 Project Grant to Florida Institute of Technology Inc. under the Engineering program (CFDA 47.041) to investigate new approaches for concurrently considering manufacturing processes in the early stages of materials and product design. Specifically, the two-year award will support the development of a novel systems-based framework for the inverse co-design of materials, products, and manufacturing processes in terms of robust decisions made...