Award Data

Aret Associates and Oak Ridge National Laboratory (ORNL) propose an interdisciplinary effort to further develop and validate a robust, operational biomonitoring application that can process soil microbiome data to reliably detect episodic and low-level chronic contamination while maintaining low false alarm rate.The Phase II SBIR work will build upon the successful Phase I proof-of-concept demonst ...

Deep Learning for standoff detection of Special Nuclear Material (DLeN) applies the same deep learning techniques that allow computers to beat human performance in image recognition and the game of Go to detecting Special Nuclear Material. Spectral analysis and signal processing can in some cases be augmented by the use of much larger neural nets that conduct much deeper analysis of features of th ...

In this work we propose to further develop and demonstrate a mesh generation approach based on clipped Voronoi diagrams. This approach to mesh generation has the potential to significantly improve performance and robustness, while retaining important elements of high quality meshes including boundary alignment, stretching, and element regularity. Clipped Voronoi diagrams also automatically de-feat ...

New classes of aircraft, providing personal, on-demand mobility, are under development and are poised to revolutionize short-duration air travel. The impetus for this work comes from advances in electronics and controls, and increases in electric motor power densities. As these aircraft are integrated into the transportation system, they will encounter icing conditions that may challenge the des ...

Complex and often violent urban wind environments pose a significant challenge to the safety and ride quality for vehicles intended for the Urban Air Mobility (UAM) market. UAM aircraft concepts must have control authority, turbulence rejection, and ride comfort as figures of merit at the forefront of the configuration selection process. However, the evaluation of handling qualities has traditiona ...

The use of small unmanned aerial vehicles (SUAVs) for civilian as well has military tasks, has been expanding steadily over the years. In this regard, cooperation and interoperability amongst multiple SUAVs has been seen as a key direction of future research by National Aeronautics and Space Administration (NASA). A central challenge in the cooperative navigation using multiple SUAVs is that they ...

The proposed SBIR develops a near real-time aircraft noise monitoring tool called UAM Noise Integration Tool (UNIT) for e-VTOL aircraft that is capable of being integrated within the real-time NASA ATM-X Testbed environment. It is highly relevant to the NASA 2018 SBIR Focus Area 20, Subtopic A3.01 Advanced Air Traffic Management Systems Concepts, since it addresses the area of “achieving high ef ...

Artificial Intelligence (AI) algorithms, which are the heart of emerging aviation autonomous systems and autonomy technologies, are generally perceived as black boxes whose decisions are a result of complex rules learned on-the-fly. Unless the decisions are explained in a human understandable form, the human end-users are less likely to accept them, and in the case of aviation applications, certif ...

Our long-term vision is to seamlessly integrate resolvent operator-based spectral analysis into Cascade’s high-fidelity large eddy simulation (LES) environment, for accurate prediction and efficient modeling of supersonic jet noise from complex nozzles. Resolvent analysis is a frequency-domain technique that can identify resonance phenomena such as jet screech and other tonal acoustic effects, p ...

CFD-based reduced order modeling (ROM) has been an active research area, as they can be used directly with common linear flutter analysis tools. Among them, linearized reduced-order modeling approaches rely on linearization of the nonlinear unsteady aerodynamic flow equations, assuming that the amplitude of the unsteady motion is limited to small perturbations about the nonlinear steady-state flow ...