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 ...

The proposed approach provides innovative sensor data association algorithms capable of performing correct data association in multi-target tracking environments with one or more sensors. Current air and missile threats have the ability to fly non-ballistic, highly maneuvering hypersonic trajectories, and the ability to maintain closely spaced trajectories. Improved detection/track association is ...

The objective of this project is to develop a capability to model fracture of materials used in hypersonic vehicles that results from hypervelocity impact while exposed to extreme temperatures. Symplectic Engineering’s approach addresses this challenge at two levels. At the computational level, a Relaxed Extended Finite Element approach is pursued to represent (possibly intersecting) fractures l ...

This STTR research study aims to enhance and apply thermo-mechanically coupled computational models for high-temperature fracture. This topic is particularly challenging in that hypersonic flight in the atmosphere generates extreme conditions over a vehicle that can affect the strength and performance the vehicle materials, both in-flight conditions as well as for cases where the vehicle encounter ...

This topic seeks an innovative NL solution for answering questions that data analysts ask when analyzing data sets to increase efficiency and consistency. The government is working on an all-digital missile defense simulation architecture that will deliver massive amounts of simulation data. Data analysts will soon be inundated with more data than they can possibly analyze manually. A critical par ...

Seed Innovations (Seed) and the University of Colorado in Denver (UCD) apply our experience in natural language processing (NLP), artificial intelligence, big data, data analytics, automatic code generation, framework development, and software architecture to accomplish the research required. Through the research on this project, Seed and UCD design and develop a proof-of-concept system, Intellige ...

The most direct way to meet the technical objectives for the Secure Virtual Environment (SVE) for Cyber Resiliency Validation would be to replicate the missile defense system’s tactical hardware, software, and network. However, this is cost prohibitive due to the amount of hardware procurement required for the Cyber test environment. Luckily, with the exception of supply chain threats, firmware, ...

Current methods of validating the cyber resiliency of missile defense systems require testing of actual systems, which removes them from operation and subjects them to potentially damaging effects. Cyber ranges can be used as an alternative, but they are limited in scale, costly, time-consuming to configure and have limited capability to model wireless tactical networks and their inherent vulnerab ...

The Ballistic Missile Defense System (BMDS) is aptly described as a system of systems. Each subsystem within the BMDS is comprised of many custom-designed firmware and software elements. The designs can only be integrated together upon receipt of physical hardware (Circuit Card Assemblies). This delay introduces significant risk to the developer and procurer since system-level design issues may no ...

The proposed work will develop a massively parallelized architecture for Monte Carlo simulation of real-time fire control schedulers. The parallelized architecture will utilize the recent developments in multiprocessing/multithreading technology based on graphical processing units. The system will be designed to perform in real-time assuming non-collocated sensors observing the threats and then co ...