Uncertainty Quantification Methodologies for Enabling Extreme-Scale Science
Sector: Commercial • Location: United States of America
Source: Grants.gov
The Advanced Scientific Computing Research (ASCR) program of the Office of Science (SC), U.S. Department of Energy (DOE), hereby invites proposals for basic mathematical, statistical and computational research that significantly advances uncertainty quantification methodologies for enabling extreme-scale science.
The purpose of this FOA is to invite proposals in ASCR Applied Mathematics basic res
Project Information FAQ
Project Information
Want to explore the full details? View the full report
Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | archived |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | The Advanced Scientific Computing Research (ASCR) program of the Office of Science (SC), U.S. Department of Energy (DOE), hereby invites proposals for basic mathematical, statistical and computational research that significantly advances uncertainty quantification methodologies for enabling extreme-scale science. The purpose of this FOA is to invite proposals in ASCR Applied Mathematics basic research that significantly advance uncertainty quantification (UQ) methodologies as an enabling technology in extreme-scale scientific computing. UQ broadly refers to the end-to-end study of the accuracy, reliability, development and effective use of computational models in making scientific inferences. Mathematically rigorous UQ methodologies are essential to a wide range of DOE science and engineering applications in carrying out predictions, design optimization, decision making, or other high-level tasks. UQ relies on a broad range of applied mathematics and statistics research, along with algorithmic and computational developments, and subject matter expertise, to enable an appropriate level of confidence in the use of computational models for scientific investigations. A companion Program Announcement to DOE Laboratories (LAB 13-895) will be posted on the SC Grants and Contracts web site at: http://www.science.doe.gov/grants The full text of the Funding Opportunity Announcement (FOA) is located on FedConnect. Instructions for completing the Grant Application Package are contained in the full text of the FOA which can be obtained at: https://www.fedconnect.net/FedConnect/?doc=DE-FOA-0000895&agency=DOE. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
