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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.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Countering the future chemical weapons threat

After decades of difficult negotiations, the Chemical Weapons Convention (CWC) was adopted in 1993 and entered into force on 29 April 1997, banning the development, production, stockpiling, transfer, and use of chemical weapons (CW). As the CWC celebrates the 25th anniversary of its entry into force, it can document considerable success, much of it attributed to the CWC implementing body—the Organisation for the Prohibition of Chemical Weapons (OPCW). However, facing a volatile international security environment and an everchanging chemical industry, the OPCW must transform to meet its mission and remain an exemplar for multilateralism. As the next CWC review conference approaches in 2023, a next-generation OPCW 2.0 can be effective and credible only if it reinforces international norms against CW, anticipates future challenges posed by advancements in science and technology (S&T), incorporates more qualitative elements into the verification and compliance system, and keeps pace with technological change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Nanoscience -- Potential and Threats

As the world’s population continues to expand, scientists are working to address the energy needs and challenges that accompany growth with environmentally responsible approaches. Nanoscience is helping to provide solutions to energy and environmental concerns in a number of ways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

Rapid Threat Organism Recognition Pipeline

The RAPTOR computational pipeline identifies microbial nucleic acid sequences present in sequence data from clinical samples. It takes as input raw short-read genomic sequence data (in particular, the type generated by the Illumina sequencing platforms) and outputs taxonomic evaluation of detected microbes in various human-readable formats. This software was designed to assist in the diagnosis or characterization of infectious disease, by detecting pathogen sequences in nucleic acid sequence data from clinical samples. It has also been applied in the detection of algal pathogens, when algal biofuel ponds became unproductive. RAPTOR first trims and filters genomic sequence reads based on quality and related considerations, then performs a quick alignment to the human (or other host) genome to filter out host sequences, then performs a deeper search against microbial genomes. Alignment to a protein sequence database is optional. Alignment results are summarized and placed in a taxonomic framework using the Lowest Common Ancestor algorithm.

Solberg, OwenD.↗
DOE OSTI2022

Master State Threat Identifier (masti)

The MSE cyber sensor offers a novel approach for scalable network monitoring using heterogeneous computing. Packet data is collected, analyzed, and stored by a stand alone cyber sensor. Machine learning algorithms are run to discover patterns in the communication without the need for deep packet inspection. Tuning of the detection algorithms happens automatically, without need for an engineer to manually create detection rules.

Russell, PierceL↗
DOE OSTI2014

Safeguards at Gas Centrifuge Enrichment Plants: Why is Iran a Threat? [Slides]

GCEPS safeguards (Desire to close gaps on undeclared feed) - Timely detection of the misuse of the facility to produce HEU - Timely detection of the diversion of declared UF6 - Timely detection of the misuse of the facility to produce undeclared LEU – Operator “no one would ever divert undeclared LEU product” – Breakout vs. Clandestine Ops (CSA and AP safeguards options) • Tightened coverage of GCEPs – declared operations (SNRI,C/S) • Unattended monitoring system – in development for GCEPs – Load Cells – Monitoring cylinders / weight – On-Line Enrichment Monitoring – Cylinder Verification Station – NDA, Weight,… – UF6 Cylinder Tracking - UID • Sensitive technology! Khan network and undeclared facilities

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Assessment of Threats to Wetland Integrity at New Boston Air Force Station, New Hampshire, with Recommendations for Mitigation

Our study addressed two projects identified in the Integrated Natural Resources Management Plan (INRMP) for New Boston Air Force Station (NBAFS), New Hampshire that are related to sustaining high-quality wetland habitats on the station. These studies were intended to: (1) evaluate erosion and its impacts on NBAFS wetlands, (2) evaluate degraded wetlands for restoration potential and (3) develop designs for wetland restoration. This report includes brief descriptions of each wetland evaluated, existing and potential erosion problems at each wetland, and recommendations for restoration actions to mitigate impacting factors at high risk wetlands. In October 2011, we surveyed 15 wetlands on NBAFS for evidence of impacts from erosion. These wetlands were chosen because they were adjacent to roads, developed areas, or disturbed areas, and therefore had a higher potential for impact from erosion. Parameters evaluated at these wetlands and adjacent areas included (1) evidence of existing sedimentation and erosion into wetland areas; (2) source of sediment; (3) slope; (4) soil type; (5) surrounding land cover; (6) presence and extent of intervening non-erosive land (e.g., vegetated surface, pavement); (7) water inputs (surface runoff, groundwater); and (8) frequency and nature of erosion events. The evaluation was watershed-based and utilized existing topographic information to determine the watershed of each wetland. Erosion problems at specific locations were ranked according to risk, including probability of occurrence, magnitude of effect, and severity of effects. Our evaluations were used to determine opportunities for wetland restoration. Restoration activities were developed on a case-by-case basis with an emphasis on wetlands at highest risk of degradation. Our recommendations for restoration focused on eliminating or reducing risk using minimally intrusive procedures and engineering solutions that could be achieved at relatively low cost. We emphasize concepts such as permeable paving, stabilization of road surfaces, nonnative plant removals, and native plant buffers that eliminate the source of the disturbance or reduce the energy of runoff while increasing groundwater infiltration rates. Recommended restoration actions and solutions are intended to be sufficiently explicit to develop work plans for restoration activities.

Van Lonkhuyzen, Robert A.↗
DOE OSTI2013

Decision Analysis Methods For the Analysis of Nuclear Terrorism Threats with Imperfect Information

Protection of commercial nuclear fuel cycles against adversary groups who may attempt to steal weapons-usable material is an issue of interest to the U.S. Department of Energy, Office of Nuclear Energy. The wide array of potential nuclear fuel cycle configurations and the security measures that could be deployed to protect them pose a daunting system design problem. In general, there are billions of potential design configurations. Moreover, the design choices are not independent – the effectiveness of one design feature or security measure can affect the desirability of other design choices. To explore this issue, we develop a mixed-integer optimization problem that solves a complex decision tree to allocate security resources across a commercial nuclear fuel cycle configuration. A nominal UREX+ reprocessing facility is used to demonstrate how the model allocates resources across a particular fuel cycle facility and shows how the problem can be scaled up to include other facilities and design features in the fuel cycle. In our model, the defender first chooses a set of safeguards to implement in order to mitigate the risk of a terrorist theft from various unit operations in the reprocessing facility. The attacker observes the defender’s strategy choice and executes an attack to acquire material, including the possibility of declining to attack at all. The model considers the terrorist as an intelligent adversary with a set of attack strategies known to the defender. The strategic choices made by both the defender and attacker affect the probability of a successful attack by the terrorist and in turn affect the distribution of consequences to the defender. We use a decision tree to illustrate the interactions among costs, decisions, correlated uncertainties, and outcomes, and then show how to formulate the problem as a mixed-integer program with an equivalent solution. The novel features of our formulation include the following. First, as discussed above, we use a sequential game-theoretic formulation (a Stackelberg game). This formulation assumes the attacker can observe the defender’s actions before the attack is executed. Many previous game-theoretic studies have assumed attacker and defender act simultaneously without knowledge of the other’s strategy choice. We believe the sequential game formulation is more applicable for knowledgeable insider adversaries, the focus of this study. Second, we build on our previous work that has developed a methodology to reflect the correlation among probability distributions represented as discrete chance nodes in a decision tree. We illustrate how this methodology can be applied to two chance nodes in a decision tree that relate the quality of the materials that might be stolen or diverted by an adversary with the yield of a weapon that might be constructed from that material. In a decision tree, the dependence of the yield on the quality of the material could be modeled with conditional probabilities of the weapon yield given the quality of the materials obtained. For three outcome discretizations, this would require the assessment of nine conditional probabilities from domain experts as part of the model building effort. In contrast, our methodology will allow this same representation of the tree based on the assessment of the correlation between these two chance nodes by the experts, which we believe is a much easier and more reliable assessment task. The advantage of this approach increases as the number of dependent chance nodes grows in a decision tree representation of this problem. Third, we extend this approach to the approximation of the dependence between discrete binary events such as success or failure represented by binary chance nodes in a decision tree or in the special case of a probabilistic risk analysis (PRA) based on an event tree. This extension is a novel application in this domain, and uses Monte Carlo simulation to determine the appropriate conditional probabilities on the binary chance nodes when the number of correlated uncertainties is more than two. Fourth, we show how these decision trees or probability trees can be formulated and solved as equivalent integer programming (IP) problems. The advantages of the IP representation include the opportunity to use the computing power associated with powerful optimization solver algorithms available on high speed computers to solve very large versions of these trees, and the ability to include several such models of different facilities into a much larger IP with connecting constraints that represent budget restrictions, number of available inspection opportunities in a given time window, or other dependencies among these facilities. Policy makers can use the resulting model to inform their decisions about how to assess terrorism risk and to safeguard the commercial nuclear fuel cycle.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Insider Threat Case Studies at Radiological and Nuclear Facilities

Seven case studies are presented. The cases include thefts of various materials and sabotage. For each case there is an overview of the incident, a timeline, a profile of the perpetrator, and a discussion of the security system failures which allowed the incident to take place.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2014

COE Task Order 4. Final Report: Automated Threat Recognition

Lawrence Livermore National Laboratory (LLNL) was tasked by the Department of Homeland Security (DHS) Science and Technology Directorate (S&T) with developing an automated target recognition algorithm for finding objects of interest in checked baggage at airports. The project used x-ray computed tomography (CT) data collected on a medical scanner of various simulated checked bags. Target objects of interest include clay, rubber, and saline in various concentrations. The final results are 93.9% probability of detection (P D ) with 11.9% probability of false alarm (PFA) on all targets and 100% detection for pseudo target sheets. This result is achieved by using a three-stage algorithm made up of segmentation, post-processing, and feature extraction and object classification. The segmentation proved to be the most important stage and it involves merging two distinct segmentation results followed by a set of algorithms for cleaning up the merged segmentations. The first segmentation algorithm operates on planar 10x10 voxel slabs (two- dimensional segments) in the three spatial planes. The segmenter calculates a probability that each slab in the image is a part of a target, determines if the probability was above a threshold, and then merges all connected slabs together. The second segmentation algorithm is an ensemble segmenter, which generates a set of possible segmentations through random permutations and computes an average behavior. The distinct properties of these segmenters results in a merged segmentation with superior results than either segmenter alone. The merged segmentation is “cleaned up” using post processing techniques to achieve the final labeled images. The final classification stage made use of a random forest classifier algorithm to discriminate targets from non-targets based on a set of features of the segmented objects partially from the voxel slabs and partially from the individual voxels. Features include standard statistics such as mean, median, and standard deviations of the density, features capturing some aspects of texture, and some features about the surrounding bag structure. In addition to the detection and false alarm results above, we show how the algorithms can be trained to “overfit” to the limited data set provided and achieve near perfect results (P D =100% and P FA =0%). This over-training is not recommended for long-term operation, but instead is meant to demonstrate how test design is an important factor in aviation security. Possible improvements to the algorithm and the testing methodology (including blind testing) are also presented.

42 ENGINEERING↗
DOE OSTI2015

A new method of passive counting of nuclear missile warheads -a white paper for the Defense Threat Reduction Agency

Cosmic ray muon imaging has been studied for the past several years as a possible technique for nuclear warhead inspection and verification as part of the New Strategic Arms Reduction Treaty between the United States and the Russian Federation. The Los Alamos team has studied two different muon imaging methods for this application, using detectors on two sides and one side of the object of interest. In this report we present results obtained on single sided imaging of configurations aimed at demonstrating the potential of this technique for counting nuclear warheads in place with detectors above the closed hatch of a ballistic missile submarine.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗