| NSF Org: |
CMMI Division of Civil, Mechanical, and Manufacturing Innovation |
| Recipient: |
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| Initial Amendment Date: | September 5, 2017 |
| Latest Amendment Date: | September 5, 2017 |
| Award Number: | 1748259 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Joanne Culbertson
CMMI Division of Civil, Mechanical, and Manufacturing Innovation ENG Directorate for Engineering |
| Start Date: | September 1, 2017 |
| End Date: | September 30, 2018 (Estimated) |
| Total Intended Award Amount: | $83,125.00 |
| Total Awarded Amount to Date: | $83,125.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
5700 CORPORATE DR PITTSBURGH PA US 15237-5851 (724)814-3178 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
100 North 3rd Street Phoenix AZ US 85004-2231 |
| 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): | CDS&E |
| Primary Program Source: |
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| 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
Advanced computation and data science tools have the potential to transform fundamental research, enhancing researchers' productivity and catalyzing new discoveries that enable greater economic prosperity and national security and a higher quality of life. This award supports a one day workshop to define core knowledge and competencies essential to the use of advanced computation and emerging data-enabled methods in fundamental materials and manufacturing research. The workshop will convene leading researchers in materials science and engineering, manufacturing, mechanical engineering, computer science, mathematics and statistics to collaborate and develop a roadmap that will be widely disseminated to the community.
The meeting will produce a framework for enabling the broader engineering community to more fully realize the benefits of emerging information technology in their fundamental research. The roadmap provides a foundation for enhanced education and training activities, empowering both current researchers and the future science and engineering workforce. By highlighting and catalyzing opportunities for enhanced research productivity, the workshop will benefit researchers, educators, designers, manufacturers and others interested in advanced materials and manufacturing research and will spur the development of new curricula.
PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
Advanced computational approaches enabled by increasingly sophisticated material models, computing algorithms, and hardware have become transformative agents in the progress of science and engineering. Fueled by many of the same drivers, data-driven and data-enabled discoveries are also becoming possible. However, the application of these approaches is not yet well established and, thus, there is significant unrealized potential in the use of advanced computational tools and data-driven methods in materials and manufacturing.
To better leverage the opportunities of advanced computation and data in materials and manufacturing, this project aimed to accomplish the following objectives: (1) identify the core knowledge and gaps in applying advanced computation and data in these arenas and (2) develop action plans for closing these gaps.
A planning team of five materials and manufacturing experts was convened to help accomplish the project’s objectives. The planning team organized a workshop that included nearly 35 participants from the materials and manufacturing communities, who gathered for a daylong meeting in Phoenix, Arizona on March 11, 2018 to discuss prevailing knowledge gaps and opportunities for closing them. Through presentations and facilitated discussions, a total of 38 technical gaps were identified, along with several cultural gaps. Six high priority technical gap areas were identified: (i) data-driven approaches; (ii) digital data infrastructure; (iii) coupling of simulations and experiments; (iv) digital representation and visualization; (v) predictive multiscale modeling; (vi) uncertainty quantification and propagation.
In addition to core knowledge gaps and action plans, several broader recommendations were made by the group to address other overarching community issues including a lack of cross-disciplinary collaboration, the disconnect among the various stakeholder groups (e.g., academia, government laboratories, and industry), and inadequate training opportunities.
Detailed outputs from the project were captured during the workshop and a report was published that is freely available on the web (www.tms.org/coreknowledge) for the benefit of an international, diverse community that extends beyond the more than 14,000 members of The Minerals, Metals & Materials Society. The report provides a foundation for enhanced education and training activities, empowering both current researchers and the future science and engineering workforce. It is expected that readers of the report will begin addressing the action plans and recommendations outlined in the document, whether by providing support for such activities or by initiating and contributing to specific research, development, and implementation efforts within their organizations.
Last Modified: 02/04/2019
Modified by: Justin Scott
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