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Engineering (Richard D. Braatz and Umberto Ravaioli)

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1 Engineering (Richard D. Braatz and Umberto Ravaioli)
Create algorithms, software, & analysis tools for multiscale simulation #1 challenge in simulation-based engineering science (NSF Blue Ribbon Panel Report) Need tools for coupling scales

2 Example: CO2 Sequestration (LANL, MMI)
Energy Engineering  policy decisions depend on accurate simulation of all of these time and length scales Energy engineering  policy decisions depend on accurate simulation of all of these time and length scales NCSA Strategic Planning Presentation (April 20,2010)

3 Example: Biological Membrane Simulation Needed for Biomedical Engineering Apps
Length scales range from ions to lipids to proteins and ion channels to membranes (to cells to tissues to organs) Length scales range from ions to lipids to proteins and ion channels to membranes (to cells to tissues to organs) figure courtesy of Dr. Mark Hill, Faculty of Medicine, University of New South Wales, Australia NCSA Strategic Planning Presentation (April 20,2010)

4 Bottlenecks/Issues to Achieving Objectives
Need new numerical algorithms for the simulation of systems that span widely varying time and length scales Need algorithms to analyze the effects of uncertainties in parameters and at interfaces between physical domains on simulation outputs Need parallel/scalable multiscale simulation algorithms Need algorithms for applying such models to perform engineering Lack of long-term funding (e.g., training grants, centers) large enough to support a cohesive multiscale simulation effort across campus Large multiscale simulation proposals to NSF handicapped by lack of faculty in multiscale mathematics and applied quantum chemistry No courses in multiscale simulation on campus to train people No books provide a balanced coverage of multiscale simulation No educational materials on “best practices” tools for multiscale simulation for training people with varied disciplinary backgrounds Need software that simplifies the implementation of the algorithms NCSA Strategic Planning Presentation (April 20,2010)

5 Cyberinfrastructure Challenges in Reaching the Objectives
Lack of software that enables a non-expert in multiscale simulation to implement a numerically accurate multiscale simulation algorithm Lack of software to facilitate the validation of such a simulation Lack of scalable software to analyze the effects of uncertainties in parameters and at interfaces between physical domains on outputs computed from a multiscale simulation code Lack of workflow tools to facilitate running multiscale simulations on computers with large numbers of processors Lack of support staff with deep expertise in multiscale simulation Lack of support staff with deep expertise in many key simulation methods, e.g., computational fluid dynamics, KMC simulation These challenges addressable only by computational researchers from many science and engineering disciplines & new NCSA staff NCSA Strategic Planning Presentation (April 20,2010)

6 Challenges, Barriers, and Opportunities in Engineering Science (NSF Blue Ribbon Panel)
The Tyranny of Scales: The Challenge of Multiscale Modeling and Simulation Verification, Validation, and Uncertainty Quantification Dynamic Simulation Systems, Sensors, Measurements, and Heterogeneous Simulations New Vistas in Simulation Software The Emergence of Big Data in Simulation and the Role of Visualization in SBES Next-Generation Algorithms and Computational Performance Need for carrying out engineering tasks Need for computational efficiency NCSA Strategic Planning Presentation (April 20,2010)

7 Multiscale Mathematics Needs (DOE MMI)
Multiresolution Methods Hybrid Methods Closure Methods Adaptive Methods Error Estimation Methods Uncertainty Quantification Methods Inverse and Optimization Methods Dimensional Reduction Methods Unifying Mathematical Framework  facilitate methods development Mathematical Software  make available to engineers Need for computational efficiency Need for carrying out engineering tasks NCSA Strategic Planning Presentation (April 20,2010)

8 Strategy: Multiscale Simulation Education
Create materials for training in multiscale simulation Consider a similar approach for other education efforts Summer School in Multiscale Simulation (2011) Summer School in Multiscale Simulation (2012) Virtual School of Computational Science and Engineering Lots of experience in textbook writing, Heath, Aluru, Braatz University course delivered via access grid (2012) Textbook Heath, Aluru, Braatz, … NCSA Strategic Planning Presentation (April 20,2010)

9 Strategy: Meeting Staff & Software Needs
Numerical Simulation NCSA CFD expert Work w/existing IACAT faculty & NCSA staff algorithms, software, & analysis tools for multiscale simulation NCSA KMC expert Blue Waters Hires Faculty in multiscale math These challenges addressable only by computational researchers from many science and engineering disciplines & new NCSA staff Faculty in applied quantum chemistry IGERT & other proposals NCSA Strategic Planning Presentation (April 20,2010)

10 Reference slide Multiscale Mathematics Initiative: A Roadmap, U.S. Department of Energy, December 2004, Simulation-based Engineering Science: Revolutionizing Engineering Science through Simulation, NSF Blue Ribbon Panel Report, May 2006, Community Input on the Future of High Performance Computing, NSF HPC Task Force, December 2009, NCSA Strategic Planning Presentation (April 20,2010)


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