Cooperative Agreement 70NANB25H104
- This Cooperative Agreement award, funded by the National Institute of Standards and Technology (NIST) under the Measurement and Engineering Research and Standards (CFDA 11.609) program, aims to develop a biomanufacturing modeling and ontology platform to accelerate digital twin model development and deployment. The $244,235 project will create an integrated biomanufacturing process ontology, develop a multi-scale digital twin model, and construct a machine learning ontology to facilitate...
- This $256,000 National Science Foundation Engineering Directorate Project Grant supports the development of a digital twin composition method by Diamond Age Technology LLC. The awardee will develop techniques to efficiently combine disparate data sources describing industrial process facilities into a single digital representation with sub-centimeter accuracy. This digital twin can then be projected into spatial computing environments like virtual and augmented reality. The goal is to encode...
- This Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $269,979 to the Santa Fe Institute of Science to conduct collaborative research on developing robust digital twin models that can accurately predict the behavior of complex systems under unexpected conditions. The key objectives are to: Investigate the generalization abilities of digital twins by combining mathematical tools from nonlinear dynamics and machine...
- This $199,066 Project Grant was awarded by the National Science Foundation's Engineering program (CFDA 47.041) to Miami University to automate the creation of digital twins for manufacturing systems using computer vision and deep learning. The research aims to significantly reduce the manual effort required to construct digital twins while improving their accuracy, contributing to advancements in smart manufacturing and autonomous systems. Key innovations include developing a dataset of...
- This $493,637 federal Project Grant award, funded by the National Science Foundation (NSF) Engineering program (CFDA 47.041), aims to advance simulation-based manufacturing process digital twin (DT) technologies. The key research goals are to: 1) develop a self-organizing DT framework that continuously validates and calibrates the simulator, 2) create optimal control algorithms for contingency scenarios, and 3) leverage parallel computing for rapid optimization. The research will establish...
- This $350,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will support the development of a Bayesian data assimilation framework for digital twins. The project aims to create a statistical framework for understanding and managing uncertainty in digital twin systems, which integrate modeling, data collection, prediction, and decision-making for physical, biological, or engineering systems. Specifically, the grant will...
- This National Science Foundation Project Grant of $283,099 will support the development of new stochastic optimization methods to calibrate digital twins using large datasets. Awarded under the Engineering program (CFDA 47.041), the grant will fund research at the University of Michigan from January 2023 through December 2025. Specifically, the university researchers will develop computational approaches using statistical theories to guide simulation experiments and identify optimal subsets of...
- This $444,562 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research at Michigan State University to address the digital transformation of the facility management industry. The key objectives are to: Construct a digital twin ecosystem to enhance the role of facility managers through physical and cognitive assistance. Develop a multi-modal user interface to promote effective interaction within the digital ecosystem. Gauge facility...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) federal grant award provides $174,980 to the Rochester Institute of Technology (RIT) to develop techniques and a framework for enabling "live 3D digital twins" - real-time digital representations of 3D physical objects. The project aims to create adaptive digital twin pipelines that can maintain low latency and high accuracy across varying network and compute resources, with applications...
- This Project Grant award from the National Science Foundation (NSF) Integrative Activities program (CFDA 47.083) provides $224,642 to the University of Louisiana at Lafayette to create high-fidelity digital models, or "digital twins," of space-specific power generation sources, loads, communication, and control systems. This research aims to support NASA's Artemis program, which seeks to return humans to the Moon and establish a sustainable presence there. The project involves...
PURPOSE: THE PURPOSE OF THIS GRANT IS TO IS TO DEVELOP A SEMANTIC EVALUATION TECHNOLOGY AND TOOLS DESIGNED TO ASSESS AND VALIDATE COMPLIANCE OF DIGITAL TWIN SYSTEMS WITH EXISTING INTEGRATION STANDARDS AND MEASUREMENT PROTOCOLS. THE PROJECT WILL ADVANCE MEASUREMENT SCIENCE FOR MANUFACTURING SYSTEMS INTEGRATION AND WILL FOCUS SPECIFICALLY ON THE APPLICATION OF SEMANTIC TECHNOLOGIES TO THE INTEROPERABILITY, TESTING, AND VALIDATION OF DIGITAL TWINS.ACTIVITIES TO BE PERFORMED: THE PROJECT WILL CREATE A SCALABLE, EXTENSIBLE, AND MODULAR ONTOLOGY SYSTEM AND TOOLS FOR COMPLIANCE VALIDATION. TO ACCOMPLISH THIS, THE PROJECT WILL IDENTIFY KEY TERMS AND COMPETENCY QUESTIONS FOR DIGITAL TWINS COMPLIANCE, CODIFY STAKEHOLDER CONSENSUS ON KEY CONTENT FOR DIGITAL TWIN COMPLIANCE ONTOLOGIES, GENERATE KNOWLEDGE GRAPHS BY COMBINING ONTOLOGIES WITH NIST COMPLIANCE DATA, AND EVALUATE RESULTING KNOWLEDGE GRAPHS AGAINST COMPETENCY QUESTIONS.EXPECTED OUTCOMES: RESULTS FROM THE PROJECT WILL SUPPORT THE BROADER IMPLEMENTATION OF DATA INTEROPERABILITY TECHNOLOGY BY ADVANCING SEMANTIC INFRASTRUCTURE, ENABLING REPRODUCIBLE VALIDATION, AND FOSTERING COLLABORATIVE ALIGNMENT BETWEEN PRACTITIONERS AND STANDARDS BODIES. INTENDED BENEFICIARIES: US MANUFACTURERS AND MANUFACTURING INTEGRATION APPLICATION PROVIDERS. THIS PROJECT WILL LEVERAGE ONTOLOGY ENGINEERING BEST PRACTICES TO PROVIDE A SCALABLE FOUNDATION FOR EVALUATING DIGITAL TWIN SYSTEMS IN MANUFACTURING. THIS WORK WILL SUPPORT MORE RELIABLE AND INTEROPERABLE DIGITAL MODELS, ULTIMATELY REDUCING WASTE, IMPROVING DATA QUALITY, AND STRENGTHENING US MANUFACTURING COMPETITIVENESS.SUBRECIPIENT ACTIVITIES: THE RECIPIENT DOES NOT PLAN TO SUBAWARD FUNDS.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $99.9k | 8/22/25 |