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Scott A Lathrop

Shodor Education Foundation, Inc.

Astronomical Sciences

National Geospatial Intelligence Research

(baxq)
Mar 2019 - Dec 2019

2020

Robert L. Cieri and C. G. Farmer (2020): Computational Fluid Dynamics Reveals a Unique Net Unidirectional Pattern of Pulmonary Airflow in the Savannah Monitor Lizard (Varanus exanthematicus), Anatomical Record-Advances in Integrative Anatomy and Evolutionary Biology, American Association for Anatomy, Vol 303, Num 7, pp1768-1791
Elaad Applebaum, Alyson M. Brooks, Thomas R. Quinn, and Charlotte R. Christensen (2020): A Stochastically Sampled IMF Alters the Stellar Content of Simulated Dwarf Galaxies, Monthly Notices of the Royal Astronomical Society, The Royal Astronomical Society, Vol 492, Num 1, pp8-21
Joshua L. Lansford and Dionisios G. Vlachos (2020): Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials, Nature Communications, Springer Nature Limited, Vol 11, Num 1, pp1513

2019

K. Marsac and A. K. Navarre–Sitchler (2019): Extending the Longevity of Produced Water Disposal Wells: Evaluation Using Reactive Transport Modeling, (in preparation)
Ferah Munshi, Alyson M. Brooks, Charlotte Christensen, Elaad Applebaum, Kelly Holley-Bockelmann, Thomas R. Quinn, and James Wadsley (2019): Dancing in the Dark: Uncertainty in ultra-faint dwarf galaxy predictions from cosmological simulations, The Astrophysical Journal, The American Astronomical Society, Vol 874, Num 1, pp40

2017

Katharine J. Cahill, Scott Lathrop, and Steven Gordon (2017): Building a Community of Practice to Prepare the HPC Workforce, Elsevier BV, Procedia Computer Science (17th annual International Conference on Computational Science, ICCS 2017), Vol 108, pp2131-2140, Zürich, Switzerland

2016

Scott Lathrop (2016): A Call to Action to Prepare the High-Performance Computing Workforce, Computing in Science & Engineering, Institute of Electrical and Electronics Engineers, Vol 18, Num 6, pp80-83

Research Using Supercomputers Aims to Understand Aviation Turbulence


Mar 31, 2020

While turbulence like this is common, there is still relatively little known about how to accurately predict and monitor it. Using high performance computing, however, Katelyn Barber, a former Blue Waters Graduate Fellow from the University of North Dakota, is working to make turbulence prediction more accurate, which could have implications for improved air travel in the future.


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Following the lizard lung labyrinth


Dec 13, 2019

In their latest study, biologists have discovered that Savannah monitor lizards have lung structures that are a kind of a hybrid system of bird and mammal lungs. The researchers took CT scans of the entire lung labyrinth and used two different supercomputers to simulate airflow patterns at the highest resolution. The software used computational fluid dynamics similar to those used to forecast weather, calculating millions of equations every tenth of a second. The findings show that vertebrate lung evolution is complicated and we have yet to understand the full picture.


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