Search NASA⌕ Search

SEARCH · Search NASA

Results for “EXPLOSIVE”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

MACHINE LEARNING BASED CHEMICAL EXPLOSIVE MODE ANALYSIS (ML-CEMA)

The software consists of a Machine Learning based Chemical Explosive Mode Analysis (ML-CEMA) tool for advanced computational flame diagnostics. CEMA, originally based on eigen-analysis of the local thermochemical system, is capable of identifying reaction fronts and limit phenomena such as auto-ignition and extinction in practical combustion systems, such as internal combustion engines and gas turbine combustors. However, the original CEMA is computationally expensive for large reaction mechanisms that are typically needed to describe fuel chemistry of practical large-hydrocarbon fuels. This novel ML-CEMA tool employs a ML technique to accelerate the eigen-analysis of the basic CEMA approach by orders of magnitude, thus making it suitable for practical fuels. In ML-CEMA,zero-dimensional (0D) reactors and one-dimensional (1D) premixed flames are first used to generate a large number of data points for neural network based ML training. The trained ML model is then used to perform CEMA prediction. This ML-CEMA tool has been demonstrated in canonical 0D and 1D configurations as well as highly-transient three-dimensional spray flames exhibiting multi-mode turbulent combustion, showing promising results. ML-CEMA, as a standalone tool, can be used for computationally-efficient diagnostics of massive datasets generated from both experiments and simulations. For example, based on spatially resolved measurements of a small set of reactive scalars(such as temperature, hydroxyl radical and formaldehyde), ML-CEMA can effectively identify flame fronts and rare events. ML-CEMA also provides a robust online or offline flame feature detection tool. When used for on-the-fly simulations, ML-CEMA further enables zone-adaptive combustion modeling, in which the predicted eigenvalue is used as a robust mode indicator for judicious assignment of locally-valid combustion models. This ML-CEMA based zone-adaptive model can lead to substantial computational cost savings when used for large-scale simulations of multi-mode combustion systems. Third Party Code Web Page to Download Code Web Page Location of Third Party License

Xu, Chao↗
DOE OSTI2021

Defeat system for vehicle attached improvised explosive devices

An explosive device detection and expulsion system broadly comprising a detection subsystem for sensing an IED attached to a vehicle and an expulsion subsystem for expelling the IED from the vehicle. The detection subsystem includes a sensor for detecting an IED via an electromagnetic field change or capacitance change, vibrations, and/or heat, and a controller for activating the expulsion subsystem upon receiving a detection signal from the sensor. The expulsion subsystem includes a deployable panel configured to be attached to the vehicle and a deployable mechanism for shifting the deployable panel from an undeployed state to a deployed state so as to expel the IED from the vehicle.

Hower, Brent↗
DOE OSTI2021

Methods and devices for preventing computationally explosive calculations in a computer for model parameters distributed on a hierarchy of geometric simplices

A computer-implemented method of preventing computationally explosive calculations. The method includes obtaining, by a processor of the computer, measured data of one of a physical process or a physical object; performing hierarchical numerical modeling of a physical process inclusive of an Earth model containing at least one of (a) infrastructure in the ground and (b) a formation feature in the ground, wherein predicted data is generated; comparing the measured data to the predicted data to calculate an estimated error; analyzing the estimated error via an inversion process to update the at least one of the Earth model and infrastructure model so as to reduce the estimated error and to determine a final composite Earth model of at least one of the infrastructure and the feature; and using the final composite Earth model to characterize at least one of the process and the physical object.

Source record↗
DOE OSTI2023

The 2022 Hunga eruption exercises the nuclear explosion monitoring community

The 2022 Hunga eruption was a global event recorded by all three Comprehensive Test Ban Treaty Organization (CTBTO) International Monitoring System (IMS) geophysical waveform sensor technologies: seismic, infrasound, and hydroacoustic. Large volcanic eruptions are rare and additionally present an opportunity to test seismoacoustic detection, location, and identification methods for nuclear explosion monitoring.

58 GEOSCIENCES↗
DOE OSTI2020

Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing XXI

This volume contains 12 sessions, 28 papers and 26 presentations on the following topics: Photonic Integrated Circuits and Plasmonic Sensing; Advancs in CBE Signature Modeling and Sensor Algorithms I; Standoff Sensing of CBRNE Hazards I; Standoff Sensing of CBRNE Hazards II; Advances in CBE Signature Modeling and Sensor Algorithms II; Biological Hazard Sensing; Chemical Hazard Sensing; Joint Session with Conferences 11390 and 11416: Spectroscopy for CBRNE Detection and Warning; Radiological and Nuclear Sensing; Explosive Material Sensing; Poster Session.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Improved Smartphone Network Deployment Methods for Explosion Collection

Improved Smartphone Network Deployment Methods for Explosion Collection Samuel Kei Takazawa1, Sarah Popenhagen1, Milton A. Garcés1, Luis Ocampo Giraldo2, Jay Hix2 1University of Hawai?i, 2Idaho National Laboratory Milton A. Garcés, milton@isla.hawaii.edu ETI – Consortium for Enabling Technologies and Innovation: Director, Anna Erickson, Ph.D.

98 - NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL↗
DOE OSTI2025

The Henkin-McGill critical temperature test for explosives revisited: An overview of historical and modern method development

Many overarching standards, regulations, or other requirements necessitate that the critical temperature (T crit ) of an energetic material be known or estimate prior to operations such as heating. However, they rarely, if ever, provide a specific method for doing so. While other methods exist to calculate T crit , such as the Frank-Kamenetskii equation, computer simulation, etc., these cannot be readily utilized for energetics that are physical mixtures (i.e. most pyrotechnics) or materials where detailed material properties required for such calculations are lacking. Here, in this study, a COTS (commercial off-the-shelf) SBAT (Simulated Bulk Auto-ignition Test) apparatus is modified to perform Henkin cookoff tests. This creates a simple, efficient, and cost-effective solution to estimate required T crit values for energetic materials. After a historical overview of the evolution of the Henkin test, several common energetic materials (PETN, RDX, etc.) for which T crit has been readily calculated, and historical data is available, were analyzed for comparison and verification purposes. This was followed by a variety of pyrotechnic mixtures and other materials to where calculation methods cannot be readily used. The modified apparatus, as well as an updated sample shell sealing method, produced results that aligned well with historical data. It also produced reasonable T crit estimates for those materials where the Frank-Kamenetskii equation cannot be applied.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Comparative Study of Two BAM Designs for Friction Sensitivity Testing of Explosives

A new commercial design of BAM friction tester that utilizes a programmable servo motor was tested in comparison to the traditional cam-driven model. Displacement and velocity profiles were analyzed for both designs; significant differences were found between the two designs, most notable of which is that the traditional cam-driven unit has plate velocities that can be 50–75 % greater than those seen on the servo-driven model. Five energetic materials were also tested on each machine, including PETN, RDX, HMX, CL-20, and HNAB. Finally, results from the servo-driven model generally showed slightly less sensitivity when compared to the cam driven model, though the magnitude of the difference is not significant enough to require modification of safe handling procedures for the materials tested.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Retention of radionuclides in sol–gel surrogate nuclear explosive debris

Sol–gel vitrification can be used to rapidly produce solid, vitreous materials to support nuclear forensics research. Here, this work investigates three sol–gel synthetic approaches’ ability to retain fission products within the glass as a function of drying temperature. Eight of the ten fission products studied were quantitatively retained (less than 5% losses) at temperatures up to 600 °C for glasses prepared using an acidic catalyst and at temperatures up to 300 °C for glasses prepared using a basic catalyst. Both systems show partial loss of ruthenium and complete loss of iodine at temperatures above 300 and 100 °C, respectively.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗