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DTSTAMP:20230124T171523Z
LOCATION:C147-154
DTSTART;TZID=America/Chicago:20221114T133000
DTEND;TZID=America/Chicago:20221114T141800
UID:submissions.supercomputing.org_SC22_sess452_misc147@linklings.com
SUMMARY:PAW-ATM – Distinguished Speaker: The Convergence of Exascale Compu
 ting, Data Science, and Visualization toward Zero-Carbon Fuels for Power a
 nd Transportation
DESCRIPTION:Workshop\n\nPAW-ATM – Distinguished Speaker: The Convergence o
 f Exascale Computing, Data Science, and Visualization toward Zero-Carbon F
 uels for Power and Transportation\n\nChen\n\nMitigating climate change whi
 le providing the nation’s transportation and power generation are importan
 t to energy and environmental security.  The shift to hydrogen as a clean 
 energy carrier is one of the most promising strategies to reduce CO2 emiss
 ions in the face of increasing energy demand.  While hydrogen has a few dr
 awbacks as an energy carrier due to its low energy density, ammonia is sim
 pler to transport and store for extended periods of time, making it an att
 ractive carbon-free energy carrier for off-grid localized power generation
  and marine shipping.  However ammonia has poor reactivity and forms NOx a
 nd N2O emissions.  The poor ammonia reactivity can be circumvented by part
 ial cracking of ammonia to form ammonia/hydrogen/nitrogen blends tailored 
 to match conventional hydrocarbon fuel properties. However, combustion of 
 ammonia/hydrogen/nitrogen blends at high pressure, and in particular, the 
 coupling between turbulence and fast hydrogen diffusion remains poorly und
 erstood. Pre-exascale computing provides a unique opportunity for direct n
 umerical simulation (DNS) of turbulent combustion with ammonia/hydrogen bl
 ends to investigate the pressure effects on combustion rate, blow-off limi
 ts and chemical pathways for NOx and N2O formation.\n\nExascale computing 
 introduces challenges for data management and the need for reduced order s
 urrogate models (ROMS) for chemical species dimension reduction and for no
 vel in situ analysis and visualization methods.  A novel model driven on-t
 he-fly ROM recently formulated and implemented in reactive flow DNS to red
 uce the computational cost of chemistry will be described.  Recent advance
 s in topological segmentation, feature extraction, and statistical summari
 zation for extreme-scale data will be discussed in the context of in situ 
 analysis workflows that capture salient time-varying features.\n\nSession 
 Format: Recorded\n\nTag: Applications, Architectures, Heterogeneous System
 s, Hierarchical Parallelism, Parallel Programming Languages and Models, Pe
 rformance, Performance Portability, Scientific Computing\n\nRegistration C
 ategory: Workshop Reg Pass
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