Award Data

The goal of the proposed DTRA Phase I program is to develop a set a diagnostic tool to capture the evolution of aerosols and particulates ejected from liquid-filled containers impacted by fragments and shock waves in a detonation environment. Since these involve CWMD scenarios, the need is for optical diagnostics that are capable of providing accurate measurements at large standoff distances. Furt ...

The current state-of-the-art radiation detection materials have different drawbacks limiting their applications in the next-generation mobile radiation detection system. NP Photonics proposes to develop a novel scintillating glass that can be used to make large form-factor scintillators for nuclear battlefield operations. The proposed scintillating glass has the advantages of low cost, short decay ...

Machine learning algorithms have demonstrated performance on par with or superior to human analysts on large datasets when sufficient training data is available.  For military applications obtaining sufficient, truthed data is always a challenge.  Three approaches have been used for measured data collections to support sensor exploitation programs: coordinated collections, turntable measurements ...

Characterization of liquid aerosol droplets in agent defeat scenarios presents enormous challenges, in part due to high optical density conditions in sprays generated from shock or fragment interactions with liquid-filled containers.  We propose a new diagnostic that can probe optically dense regions, based on optical scattering of laser light from particles/droplets.  Our diagnostic instrument ...

This work is focused on the development of fabrication technology for large form-factor scintillation crystals for multi-modal detection of radioactive sources, and development of mobile imaging and mapping instruments based on these large format scintillators.

The detection of radionuclide aerosols is a critical indicator of a nuclear detonation. Current detection systems used in the Comprehensive Nuclear Test Ban Treaty’s  (CTBT) global monitoring network stations spend 24 hours collecting and concentrating particulates from the air to gather enough sample material for adequate detection sensitivity. This approach is inherently a batch process that ...

The Defense Threat Reduction Agency (DTRA) uses High-Fidelity (HF) computer codes, many of which are legacy codes that have evolved over many years, to investigate weapon effects phenomenology and techniques for countering Weapons of Mass Destruction (WMD). As DTRA’s reliance on HF codes for tasks critical to national security continues to increase, transitioning such codes from legacy coding pr ...

An artificial intelligence solution (AI) is proposed that utilizes very recent advances in machine learning and deep learning to improve Atom Trap Trace Analysis (ATTA) image analysis. The proposed solution shortens turnaround times and extends the capabilities of ATTA systems allowing a full accounting, across densities, of the nature and number of radionuclides in the images to be analyzed. The ...

The ATTA technique makes it possible for DTRA to accurately monitor nuclear activities in a real-time fashion. However, such a capability should be provided in varying contexts of low/high S/N images, spurious events, vibrations, and cosmic radiations, operated in the ocean floater/UAV/orbital vehicles. For this purpose, InfoBeyond advocates A2TTA (Real-time Isotope Identification and Quantificati ...

Atom Trap Trace Analysis (ATTA) has proven to be a valuable technique for detecting rare gas radioisotopes. By tuning the frequency of a laser to the resonance of a desired isotope, only atoms of that isotope are captured by a magneto-optical trap (MOT) and detected by observing its fluorescence with a CCD camera. Existing approaches rely on manually selecting a region-of-interest (ROI) of image p ...