In this deck from the 2017 HPC Advisory Council Stanford Conference, Mahdi Esmaily from Stanford presents: Best Practices: Multi-Physics Methods, Modeling, Simulation & Analysis. "The cycle of modeling high impact applications to finding new solutions is completed by the use of high-performance computing. I this talk, I will discuss two particular applications which have highly benefitted from HPC. The surgical operation performed on single ventricle heart patients has not been modified in last few decades despite a high rate of mortality. Through multiscale simulation of the circulatory system, it is now possible to model this surgery and optimize it using the state of the art optimization techniques. In-silico analysis has allowed us to test new surgical design without posing any risk to patient's life. I will show the outcome of this study, which is a novel surgical option that may revolutionize current clinical practice. The second application that I will discuss in this talk is related to renewable energy. The particle-based solar receivers operate by collecting radiative energy volumetrically through dispersed particles rather than the conventional approach of absorption via a surface. I will discuss our recent work on the investigation of the operating modes of these devices, where we are exploring the interaction of particles with turbulence, solid boundaries and radiation." Watch the video: http://wp.me/p3RLHQ-gp0 Learn more: http://www.hpcadvisorycouncil.com/events/2017/stanford-workshop/agenda.php Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter

1. Mahdi Esmaily
Stanford University
Center for Turbulence Research
HPC meeting, Feb 7-­8, 2017
Multi-­Physics Methods, Modeling,
Simulation & Analysis

2. From application to new solutions
Application
Physical
modeling
Governing
equations
HPC
Optimization
analysis
New
solutions

3. Application: Cardiovascular modeling

4. Congenital heart disease

5. Patient-­specific modeling

6. Multiscale modeling

7. Fluid-­solid interaction simulations

8. Systemic oxygen delivery:
𝐽"(𝑑) =
𝑂𝐷(𝑑)
𝑉+,
=
𝐶.
𝑉+,
−
1
𝑄. 𝑑
𝑄"(𝑑)
Coronary oxygen delivery:
𝐽2(𝑑) =
𝑂𝐷2(𝑑)
𝑉+,
=
𝐶.
𝑉+,
−
1
𝑄. 𝑑
𝑄2(𝑑)

9. Optimization results
1%
Improvement in oxygen delivery
0.5%
Improvement in coronary OD
Standard
3.5 mm BT-­shunt

10. Going back to the basics

11. Ejector pump

12. New solutions: a novel surgery

13. Application: renewable energy

14. Particle-­based solar receiver

15. Physical modeling

16. Soleil-­MPI
• Variable density incompressible formulation
• Discrete-­ordinate method for radiation transport
• Lagrangian point-­particles with collison modeling
• Non-­uniform structured rectilinear mesh
• Internal geometric multigrid solver
• Object oriented Fortran 2003
• Parallel (distributed memory)
• Tested with over a billion grid cells and particles
• Scales to Titan full capacity
Fluid flow
Radiation
transport
Lagrangian
particles

18. Analysis
Temperature
Velocity

19. Predicted near-­wall temperature
8 m/s
4 m/s
2 m/s

20. Learned lessons
With collision modeling Without collision modeling