Award Data

We aim to develop data-driven heterogeneous data fusion approaches for unanticipated event/target detection, which will be more robust and immune to model mismatch problems encountered by model-based approaches. Considering the low intrinsic dimensionality of the sensor data, we propose several data-level fusion approaches based on some state-of-the-art dimensionality reduction techniques. For lin ...

Improving feature extraction, event detection, and target classification in multi-sensor systems requires new mathematical methods and processing techniques. In addition, previous research and experience suggests that leveraging sensor data that has not experienced significant dimensionality reduction can preserve subtle features when processed jointly with other relevant data. However, traditiona ...

The ability of Large-eddy simulation (LES) techniques to accurately predict combustion instabilities and the onset of lean blow-out is not yet firmly established, especially in realistic operating conditions. A number of modeling choices play an importan...

In this Air Force Phase I STTR program, MATECH proposes to demonstrate novel pre-ceramic polymer systems complimenting the development of Ultra High Temperature (UHT), high ceramic yield, refractory ceramic matrix composites (CMCs). A leader in developme...

In this Phase 1 proposal, Vuronyx Technologies in collaboration with Georgia Institute of Technology, Atlanta (GT) intends to fabricate composite panels using high strength and high modulus carbon fibers synthesized from polyacrylonitrile (PAN) precursor...

Tensile-strained germanium tin structures will be developed for infrared emitters and detectors that are compatible with silicon fabrication processes.Optical detectors in the wavelength range of 2-5 microns will be developed by using GeSn on silicon ...

Current methods for inspecting the external surfaces of low-observable (LO) aircraft are time consuming and error prone. Technology that can reduce inspection times and minimize human error will benefit the Air Force by increasing assessment reliability and aircraft availability while reducing maintenance costs. To address this need, Intelligent Automation (IAI) and Carnegie Mellon University (CMU ...

Liquid Crystal Arrayed Microcavities (LCAM) are a new hyperspectral technology initiated by collaboration among Spectral Molecular Imaging, Advanced Microcavity Sensors and Montana State University Spectrum Laboratory.At the core of this revolutionary technology lie picoliter volume optical cavities that exploit liquid crystal birefringence for tuning an effective cavity length.During a Phase I on ...

Our Phase I work focused on improving modeling and simulations so that the impact of autonomous systems in the battlespace could be better understood. As we have trained our attention on Phase II, it has become increasingly clear that the work we are doing to improve the modeling and simulation of autonomous systems also provides significant leverage for the development of the intelligent behavior ...

Enig Associates, Inc., a small business providing advanced modeling and simulation capabilities to the DoD and DoE, is proposing an innovative and novel electrical approach, using explosive-driven flux compression generators to Joule heat light metal load in sub millisecond time scale from a solid metal state to a first ionization plasma state going through multi-phase transitions to generate an a ...