MFIX-DEM PHI: Performance and Capability Improvements Towards Industrial Grade Open-Source DEM Framework with Integrated Uncertainty Quantification Email Page
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Performer: Arizona State University
Top: Temperature profile of a 398K rotating drum filled with alumina particles.<br/>Bottom: Evolution of average bed temperature.
Top: Temperature profile of a 398K rotating drum filled with alumina particles.
Bottom: Evolution of average bed temperature.
Website: Arizona State University
Award Number: FE0026393
Project Duration: 09/09/2015 – 02/28/2018
Total Award Value: $703,385
DOE Share: $515,625
Performer Share: $187,760
Technology Area: Coal Utilization Science
Key Technology: Simulation-Based Engineering
Location: Tempe, AZ

Project Description

Arizona State University, along with Lawrence Livermore National Laboratory and Sandia National Laboratories, will address the enhancement of computational fluid dynamics (CFD) coupled with a discrete element method (DEM) in the open-source-code Multiphase Flow with Interphase eXchanges (MFiX-DEM), which is developed and maintained by the National Energy Technology Laboratory (NETL). The objectives of the project are to improve the performance and physical modeling capabilities of MFiX-DEM while tightly integrating these improvements with an intuitive graphical user interface (GUI) driven by an uncertainty quantification (UQ) framework, and to effectively pave the way to wider and more rapid industrial adoption of MFiX-DEM.

Project Benefits

This project directly addresses industry’s need for tools that can be used to solve problems of realistic size, with modest high-performance computing (HPC) resources within an acceptable timeframe. This work has the potential to transform the way multiphase flow-based engineering systems are designed and evaluated by providing a user-friendly tool that offers integrated UQ; enhanced physical modeling capabilities such as particle size distributions, heat transfer, and chemical reactions; and improved performance through code modernization. These contributions will enable the ability to run industrial-scale problems by taking advantage of the advanced HPC systems that will be ubiquitously available in the near future due to an HPC landscape that is rapidly evolving towards heterogeneous many-core architectures.

Contact Information

Federal Project Manager Jason Hissam: jason.hissam@netl.doe.gov
Technology Manager Briggs White: briggs.white@netl.doe.gov
Principal Investigator Aytekin Gel: Aytekin.Gel@asu.edu

 

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