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Reduced Order Modeling for Under Body Blasts

Parametric model order reduction has become an indispensable tool for computational-based design and optimization, statistical analysis, embedded computing, and real-time optimal control. In essence, it enables solutions to complex modeling problems in a fraction of the compute time.  It is also essential for “what-if” scenarios where real-time simulation responses are desired.

Charbel Farhat, Stanford University
Philip Avery, Stanford University
Pat Collins, Army Research Laboratory
Jari Knap, Army Research Laboratory
Large-scale Data Assimilation Using Parallel and Cloud Computing

Understanding the evolving state of the nearshore zone, e.g., ocean surface waves and seabed elevation, is crucial to many tactical decisions for naval operations, coastal infrastructure design and management, protection of the hinterland against flooding, shoreline management, and recreational safety. 

Eric Darve, Stanford University
Robert Wallace, Engineer Research and Development Center
Stacy Howington, Engineer Research and Development Center
Matthew Farthing, Engineer Research and Development Center
Tyler Hesser, Engineer Research and Development Center
Scalable, Shared and Distributed Memory Algorithms for Computational Solids, Fluids and Geometry

The design of numerical algorithms at the most basic and fundamental levels, leverages mathematics, applied mathematics, and computer science disciplines.  Real-world problems such as studying the effects of underbody blasts on motivate these methods for studying phenomena, such as solid material deformation, plasticity, and fracture, as well as interactions with fluids like air and water.  These algorithms are as applicable to underbody blasts as they are to the design and analysis of ship wakes or to ordnance storage and detonation, wh

Ron Fedkiw, Stanford University
CFD for Blood Transfusions on the Battlefield and Inhalation of Toxic Agents in the Lung

This project has two components.  One component is to study the adhesion of blood platelets to an injured vessel site. This is a critical initial stage for the formation of a platelet plug to stop bleeding.  The second component is to study the deposition of aerosol particles in the lungs to help study the effects of airborne pollutants, and infective and toxic agents.

Eric E. G. Shaqfeh, Stanford University
Gianlucca Iaccarino, Stanford University
Armando Rodriguez, Army Institute of Surgical Research
Andrew Cap, Army Institute of Surgical Research
Lorne Blackbourne, Army Institute of Surgical Research
Jana Kesavan, Edgewood Chemical Biological Center
Steven Hill, Army Research Laboratory
Paul Dabisch, National Biodefense and Countermeasures Center
Dynamic Target Surveillance under Ballistic Threat

Many of the challenges faced in the battlefield by the Army can be attributed to planning and strategic decision making. Optimal decision making in the battlefield is a complex problem that requires considering other actors, reasoning about uncertainty in how events may play out, and addressing the fact that strategies must be executed using noisy observations of the world.

Mykel Kochenderfer, Stanford University
Dale Shires, Army Research Laboratory
Barry Seacrest, Army Research Laboratory
Manuel Vindiola, Army Research Laboratory
Abdel-Hameed Badawy, New Mexico State University
Patrick Jungwirth, Army Research Laboratory
Jaime Acosta, White Sands Missile Range
High-Performance Computing Enabled Ballistic Armor and Underbody Blast Protection

Traumatic Brain Injury (TBI) is one of the primary causes of long term disability for the modern soldier. Improving the foam liners in the helmets used on the battlefield can reduce the risk of TBI to U.S. Soldiers.  The objective of this research is the development of computational models for enhanced blast protection of soldiers using ballistic fabric.  Computer simulation of textiles is difficult due to multiple size scales present in such materials.

Tarek Zohdi, University of California, Berkeley
Raju Namburu, Army Research Laboratory
Sikhanda Satapathy, Army Research Laboratory
Stephen Bilyk, Army Research Laboratory
Ramakrishna Valisetty, Army Research Laboratory
Reduced Order Parameter Estimation for Underbody Blasts

The ability to conduct fast and reliable simulations of dynamical systems is of special interest to Army operations. Because such simulations can be very complex and involve millions of variables, it can be prohibitive in CPU time to run repeatedly on many different configurations. Reduced-Order Modeling (ROM) provides a concrete way to handle such complex simulations using a realistic amount of resources. However, uncertainty is hardly taken into account.

Martine Ceberio, University of Texas, El Paso
Miguel Argaez, University of Texas, El Paso
High-Order Arbitrary Lagrangian-Eulerian Methods and Model Order Reduction for Plasticity to Simulate Melting and Solidification of Metals During Extreme Events

Problems in which solids, particularly metals, start to flow, or deform plastically, are ubiquitous in army applications, including traditional ballistic penetration problems of armor, structural integrity under fire, welding, and additive manufacturing processes.

Adrian Lew, Stanford University
Brian Henz, Army Research Laboratory