Award Data

Although metal AM technologies have continued to progress, there are still many different challenging factors to a build that impact part quality and the amount of time it takes to successfully process a first-run component without defects. Triton Systems proposes to develop a machine learning algorithm that adjusts print parameters during the build in reaction to in-situ sensor data in order to ...

Seatrec will collaborate with a team from the Woods Hole Oceanographic Institution to demonstrate the technical feasibility and commercial applicability of a novel energy harvesting system that converts thermal energy from high-latitude air-sea temperature differences into electricity.  This capability will extend the endurance and capability of observing system elements, reduce battery waste, a ...

We propose a suite of video processing algorithms utilizing the machine learning (ML) techniques of artificial intelligence (AI) reinforcement learning, deep learning, and transfer learning to process submarine imagery obtained by means of periscope cameras. Machine learning (ML) can help in addressing the challenge of human failure of assessing the data of periscope imagery. Though pre-tuned blac ...

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 ...

The introduction of substandard or counterfeit materials into the DoD supply chain can have extremely expensive, and potentially life threatening, consequences. Current techniques used to detect nonconforming materiel can be destructive (e.g., manual sectioning and inspection of a part), time consuming and expensive (e.g., micro-computed tomography, ultrasound), or provide only limited informatio ...

"Micro-calorimetry is a Nondestructive Test (NDT) capable of detecting heat characteristics that could identify improperly processed, counterfeit, substandard, nonconforming or fake raw material prior to materials introduction into end-product production cycles. Current calorimetric technology is an extremely sensitive, expensive and time consuming process, utilizing an adiabatic or semi-adiabat ...

In hypersonic flight, airborne particles such as water or ice can penetrate and alter the bow shock and flow field, enhance erosion mechanisms and alter aerodynamics. Particles break up as they pass through the shock wave, impact the surface, erode and increase surface roughness, increase turbulence and heat transfer, and augment heating that can destroy heat shields prematurely. Many tests and th ...

The significance of the problem is to deploy combined quantum communication-and-processing near to Navy applications.   Our approach, when successful, would enable small, ambient operating QPUs to be connected at a distance by quantum-secure communication.  Unlike bulky optical components and in-contrast to cryogenic qubits, our system, using in situ generated photons, offers a practical s ...

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 ...

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 ...