| NSF Org: |
OAC Office of Advanced Cyberinfrastructure (OAC) |
| Recipient: |
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| Initial Amendment Date: | May 10, 2011 |
| Latest Amendment Date: | August 31, 2015 |
| Award Number: | 1036170 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Edward Walker
edwalker@nsf.gov (703)292-4863 OAC Office of Advanced Cyberinfrastructure (OAC) CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | September 1, 2011 |
| End Date: | August 31, 2016 (Estimated) |
| Total Intended Award Amount: | $26,448.00 |
| Total Awarded Amount to Date: | $26,448.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
926 DALNEY ST NW ATLANTA GA US 30318-6395 (404)894-4819 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
225 NORTH AVE NW ATLANTA GA US 30332-0002 |
| 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): | Leadership-Class Computing |
| 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): | 47.070 |
ABSTRACT
This award facilitates scientific research using the large new computational resource named Blue Waters being developed by IBM and scheduled to be deployed at the University of Illinois. It provides travel funds to support technical coordination between the principal investigators at Georgia Institute of Technology, University of Washington, San Diego Supercomputer Center, University of Texas at Austin, the Blue Waters project team and vendor technical team.
The proposed research employs direct numerical simulations (DNS) to address research questions associated with three high Reynolds number turbulent flows: a turbulent non-premixed methane flame; scalar mixing and particle dispersion in isotropic turbulence; and turbulent wall-bounded flow in a channel. In each case, the central emphasis is on reaching sufficiently high Reynolds number to explore the resulting complex physics. Due to the compute time requirements, these simulations, which are on grids up to 8192-cubed resolution or equivalent, are not feasible on existing facilities and exceed what is experimentally possible. The advanced algorithms developed by the researchers will allow the simulations to address fundamental research issues at the heart of energy production (turbulent combustion) and consumption (transportation) technologies.
Turbulent combustion is at the center of a large fraction of US energy production, and wall-bounded turbulence is central to the energy losses inherent in transportation. An understanding of the detailed dynamics of the turbulence in these applications will likely increase predictive capabilities of the effects of turbulence leading to enhanced performance through improved design. Thus, the primary impact of the proposed DNS and the subsequent research that it will enable will be on the engineering of combustion and transportation systems. This in turn affects energy consumption and pollution.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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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.
The intellectual merits of this work include addressing both computational and scientific challenges in the conduct of state-of-the-art numerical simulations of turbulent fluid flow, on a scale that was achieved for the first time in our domain science specialty. Over the lifetime of this project we have successfully conducted massive computations requiring over a quarter million cores on Blue Waters that could not be performed readily elsewhere, and have led to a number of significant new insights. In particular as reported in a 2015 PNAS publication the the properties of flow features indicative of severe local deformation of the fluid in turbulent motion are demonstrated convincingly to be different from the picture commonly assumed in the literature. A vital advance in the parallel algorithm needed to track the motion of up to nearly 300 million marked fluid elements in the flow was developed and successfully applied, using remote-memory addressing programming tools that are expected to be more widely available in the future. A new parallel algorithm utilizing both distributed and shared memory programming and a hybrid numerical method has also been developed and applied to obtain new insights of turbulent mixing at high Schmidt number, where low molecular diffusivity introduces very demanding resolution requirements. Current results suggest a asympotic trend for the small-scale statistics of the mixed substance in a regime never fully reached before.
The value of the new simulation datasets (nearly 1 Petabyte in total) is recognized through an effort to make some of the data publicly available through a web-hosting mechanism developed by a leading group in our specialty. The new insights obtained are expected to have basic consequences for a broad range of societally important fields of inquiry, including the study of turbulent combustion in energy science and of cloud physics in meteorology. The challenges inherent to the size of our computations have also contributed to new developments in advanced cyberinfrastructure, including efficient job scheduling taking account of the network topology on a massively parallel computer, and the future possibility of including data compression features in large-scale portable datasets. This work has supported the thesis research of at least two recent PhD recipients and two more within the next two years.
Last Modified: 03/15/2017
Modified by: Pui-Kuen Yeung
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