Award Data

Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

Through this STTR contract, we propose to evaluate the efficacy of our vaccine, FlowVax Marburg, in nonhuman primates (NHPs). This will be achieved through four Tasks. In Task 1, we will manufacture the vaccine in a quantity sufficient for the animal studies. In Task 2, we will perform MHC genotyping on a representative population of NHPs and, based on results, select a set of MHC-matched NHPs for ...

There are currently no vaccines or therapeutics available for Marburg Virus Disease (MVD). Given the specter of weaponization and the terrible morbidity and high mortality rate of MVD, this represents a critical threat to the operational readiness of the Warfighter. While traditional vaccines have contributed greatly to public health, they have some limitations especially in the context of operati ...

A significant barrier to the insertion of ceramic matrix composite (CMC) materials into advanced aircraft engines is their inherent lack of toughness under erosion and post erosion. Our team will develop and demonstrate a physics-based model for erosion/post erosion of CMC’s at room and elevated temperatures (RT/ET). The ICME (Integrated Computational Material Engineering) Physics based Multi Sc ...

Advances in both software and computer hardware have made the finite element method the preeminent choice for analyzing highly complex systems that are of great value to the Department of Defense.   The US Defense industry, however, continues to spend enormous time and resources in mesh generation, a key step in finite element analysis, despite progress that has been made in automated mesh gener ...

In the proposed STTR study, Catto Propellers, Inc. (Catto) and the University of North Dakota (UND) will create an efficient new propeller design utilizing advanced composite materials for use on small unmanned x systems.  During Phase I, a comprehensive study will be conducted to develop a new propeller design in order to increase propeller efficiency, reduce aerodynamic noise and utilize innova ...

Areté and the Machine Learning for Artificial Intelligence (MLAI) Lab at the University of Arizona (UofA) will develop and demonstrate new approaches that improve the performance of in situ machine learning (ML) algorithms as they evolve over time, adapt to new environments, and are capable of transferring their learned experiences across platforms.  Technological advances that will be brought t ...

The overall goal of this STTR Phase I project is to develop a concept to mitigate the effects of motion/vibration for a shipboard material extrusion additive manufacturing (AM) system.  NAVSEA has been installing advanced manufacturing equipment, including 3D printers, onboard ships in support of shipboard operations and to evaluate performance of the equipment in shipboard environments and in re ...

Modern US Navy ships and submarines are configured with an ever-increasing level of automation, including state-of-the-art embedded wireless sensors that monitor vital system functions. However, sensor nodes have the potential to serve as targets for cybersecurity attacks or be susceptible to corruption through accidental or malicious events. To address these shortfalls and minimize vulnerabilitie ...

Condition-based maintenance plus (CBM+), and cyber-physical systems (CPS) in general, depend on correct sensor data for analysis, decision making and control loops. If the sensor data that arrives at the point of processing is not correct, or more accurate, is outside its accepted error range, then any further processing will be incorrect as well. This could result in, in the case of CBM+, not det ...