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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Transmission of the atypical/Nor98 scrapie agent to Suffolk sheep with VRQ/ARQ, ARQ/ARQ, and ARQ/ARR genotypes

Scrapie is a transmissible spongiform encephalopathy that occurs in sheep. Atypical/Nor98 scrapie occurs in sheep that tend to be resistant to classical scrapie and it is thought to occur spontaneously. The purpose of this study was to test the transmission of the Atypical/Nor98 scrapie agent in three genotypes of Suffolk sheep and characterize the distribution of misfolded prion protein (PrP Sc ). Ten sheep were intracranially inoculated with brain homogenate from a sheep with Atypical/Nor98 scrapie. All sheep with the ARQ/ARQ and ARQ/ARR genotypes developed Atypical/Nor98 scrapie confirmed by immunohistochemistry, and one sheep with the VRQ/ARQ genotype had detectable PrP Sc consistent with Atypical/Nor98 scrapie at the experimental endpoint of 8 years. Sheep with mild early accumulations of PrP Sc in the cerebellum had concomitant retinal PrP Sc . Accordingly, large amounts of retinal PrP Sc were identified in clinically affected sheep and sheep with dense accumulations of PrP Sc in the cerebellum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Environmental associations of Ophidiomyces ophidiicola , the causative agent of ophidiomycosis in snakes

Emerging pathogenic fungi have become a topic of conservation concern due to declines observed in several host taxa. One emerging fungal pathogen, Ophidiomyces ophidiicola, is well documented as the causative agent of ophidiomycosis, otherwise known as snake fungal disease (SFD). O. ophidiicola has been found to cause disease in a variety of snake species across the United States, including the eastern massasauga (Sistrurus catenatus), a federally threatened rattlesnake species. Most work to date has involved detecting O. ophidiicola for diagnosis of infection through direct sampling of snakes, and attempts to detect O. ophidiicola in the abiotic environment to better understand its distribution, seasonality, and habitat associations are lacking. We collected topsoil and groundwater samples from four macrohabitat types across multiple seasons in northern Michigan at a site where Ophidiomyces infection has been confirmed in eastern massasauga. Using a quantitative PCR (qPCR) assay developed for O. ophidiicola, we detected Ophidiomyces DNA in topsoil but observed minimal to no detection in groundwater samples. Detection frequency did not differ between habitats, but samples grouped seasonally showed higher detection during mid-summer. We found no relationships of detection with hypothesized environmental correlates such as soil pH, temperature, or moisture content. Furthermore, the distribution of Ophidiomyces positive samples across the site was not linked to estimated space use of massasaugas. Our data suggests that season has some effect on the presence of Ophidiomyces. Differences in presence between habitats may exist but are likely more dependent on the time of sampling and currently uninvestigated soil or biotic parameters. These findings build on our understanding of Ophidiomyces ecology and epidemiology to help inform where and when snakes may be exposed to the fungus in the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Calibration verification for stochastic agent-based disease spread models

Accurate disease spread modeling is crucial for identifying the severity of outbreaks and planning effective mitigation efforts. To be reliable when applied to new outbreaks, model calibration techniques must be robust. However, current methods frequently forgo calibration verification (a stand-alone process evaluating the calibration procedure) and instead use overall model validation (a process comparing calibrated model results to data) to check calibration processes, which may conceal errors in calibration. In this work, we develop a stochastic agent-based disease spread model to act as a testing environment as we test two calibration methods using simulation-based calibration, which is a synthetic data calibration verification method. The first calibration method is a Bayesian inference approach using an empirically-constructed likelihood and Markov chain Monte Carlo (MCMC) sampling, while the second method is a likelihood-free approach using approximate Bayesian computation (ABC). Simulation-based calibration suggests that there are challenges with the empirical likelihood calculation used in the first calibration method in this context. These issues are alleviated in the ABC approach. Despite these challenges, we note that the first calibration method performs well in a synthetic data model validation test similar to those common in disease spread modeling literature. We conclude that stand-alone calibration verification using synthetic data may benefit epidemiological researchers in identifying model calibration challenges that may be difficult to identify with other commonly used model validation techniques.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

An Implementation for Transforming a Home Energy Management System to a Multi-agent System

In the United States, 41% of produced energy is consumed by the building sector, i.e. residential and commercial buildings (Building Energy Data Book, Buildings Sector, US Department of Energy, Office of Energy Efficiency and Renewable Energy, Building Technologies Office, 2012. n.d.). The anticipation is that Home Energy Management Systems (HEMS) will support energy efficiency gains through control of the devices in an optimal fashion. New opportunities are offering the ability to integrate grid type controls and the most suitable way to perform these controls is through a multi-agent system (MAS). In this paper, approaches on supporting a HEMS and MAS integration are discussed.

Zandi, Helia↗
DOE OSTI2019

Thermodynamic Studies on a Hydrogen Bonded Acidic (HBA) 3,5-bis(trifluoromethyl)phenol-Functionalized Polymer as a Gas Chromatography Stationary Phase for Selectively Speciating Chemical Warfare Agents

We used for the first time hydrogen bonded acidic (HBA) polymer, poly{methyl[3-(2-hydroxyl, 4,6-bistrifluoromethyl)phenyl]propylsiloxane } , (DKAP), as stationary phase for gas chromatography (GC) of chemical warfare agent (CWA) organophosphate (OP), surrogates, dimethylmethylphosphonate (DMMP), diisopropylmethylphosphonate (DIMP), diethylmethylphosphonate (DEMP), and trimethylphosphate (TMP), with high sensitivity and selectivity. Adsorption of OPs to DKAP was one-to-several orders of magnitude higher relative to commercial polar, mid-polar, and nonpolar stationary phases. We also performed for the first-time thermodynamic studies on the adsorption of OP vapors and obtained quantitative binding energy data for interactions with various stationary phases. These data help to identify the correct pair of hetero-polar columns for a two-dimensional system, employing nonpolar stationary phase as GC1, rejecting interfering molecules, and DKAP as GC2 stationary phase, for selective, sensitive, and rapid field detection of CWAs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Superhydrophobic Powder Additives to Enhance Chemical Agent Resistant Coating Systems for Military Equipment for the US Marine Corps (USMC) Corrosion Prevention and Control (CPAC) Program

The primary goal of the CPAC program at ORNL was to explore the feasibility of introducing various silica-based superhydrophobic (SH) powder additives as a way to improve the corrosion resistance of US Department of Defense (DOD) military-grade chemical agent resistant coating (CARC) systems. ORNL had previously developed and patented several SH technologies of interest to the USMC, and one of the objectives of this program was to identify methods to incorporate these technologies into the USMC’s corrosion-resistance strategy. This report discusses findings of the CPAC and their application.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2015

Investigating the Hydrolysis Reactions of a Chemical Warfare Agent Surrogate: A Systematic Study using 1 H, 13 C, 17 O, 19 F, 31 P, and 35 Cl NMR Spectroscopy

During the summer of 2015, I participated in the DHS HS-STEM fellowship at Sandia National Laboratories (SNL, NM) under the supervision of Dr. Todd M. Alam in his Nuclear Magnetic Resonance (NMR) Spectroscopy research group. While with the group, my main project involved pursing various hydrolysis reactions with Diethyl Chlorophosphate (DECP), a surrogate for the agent Sarin (GB). Specifically, I performed different hydrolysis reactions, monitored and tracked the different phosphorous containing species using phosphorous ( 31 P) NMR spectroscopy. With the data collected, I performed kinetics studies mapping the rates of DECP hydrolysis. I also used the NMR of different nuclei such as 1 H, 13 C, 17 O, and 35 Cl to help understand the complexity of the reactions that take place. Finally, my last task at SNL was to work with Insensitive Nuclei Enhanced by Polarization Transfer (INEPT) NMR Spectroscopy optimizing conditions for 19 F- 31 P filtering NMR experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Highly Multiplexed Assays for Detection of Biothreat and Food Safety Agents, CRADA No. TC02156.0

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and BioSearch Technologies Inc. (BTI) of Novato, California, to develop Multiplexed Molecular Assays for the Rapid and Sensitive Detection of Microbial Agents of Concern for Bioterrorism and Food Safety for the Food and Drug Administration (FDA) Center for Food Safety and Applied Nutrition (CFSAN). There are no outstanding leans for this project.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Highly Multiplexed Assays for Detection of Biothreat and Food Safety Agents Final Report CRADA No. TC02156.0

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and BioSearch Technologies Inc. (BTI) of Novato, California, to develop Multiplexed Molecular Assays for the Rapid and Sensitive Detection of Microbial Agents of Concern for Bioterrorism and Food Safety for the Food and Drug Administration (FDA) Center for Food Safety and Applied Nutrition (CFSAN). There are no outstanding leans for this project.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Novel Chemistry to Support the Detection of Advanced Chemical Agents

Recent news reports coming from Asia and the UK have highlighted the emerging threats of Non-Traditional Agents (NTAs) to national security. The UK incident underscores how NTAs may linger in the environment and at trace. Building on Sandia's extensive analytical chemistry work in this field, a polysilphenylene analog of Sandia's proprietary DKAP polymer coatings was synthesized and evaluated for high temperature operation. Initial test results are inconclusive as to the improved thermal stability of the new polymer with TGA/DSC results indicating a lower glass transition go temperature for the new "Hot DKAP" material and a similar to slightly lower start to mass loss for "Hot DKAP", but slower degradation rate in clean dry air. Additional testing with a TGA-MS system to identify what the fragments lost as a function of temperature is still needed to fully characterize the materials thermal properties. In addition, the material still needs to be evaluated for thermodynamic properties for analytes of interest using either GC or SPC coated devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Agent-Based Transportation Energy Analysis Model: Methodology and Initial Results (CRADA 16155)

This report documents the efforts of Argonne and Exelon researchers to implement an agent-based model of charging demand and infrastructure expansion for the seven-county Chicago metropolitan area. Conducted as a project task under a broad Cooperative Research and Development Agreement (CRADA) between Argonne National Laboratory and Exelon, the project spanned a roughly 15-month time period during which Argonne and Exelon researchers developed a close working relationship. In addition to face-to-face meetings - both at the Laboratory and at Exelon’s offices in Washington, DC - bi-weekly web-enabled meetings and a file-sharing folder facilitated interaction and document sharing among the project team. Team members represented a broad cross-section of skill sets and internal organizations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

SEDONA SpEctroscopic Detection Of Nerve Agents

Although the threat of a liquid explosive attack on a passenger aircraft has been mitigated by limiting the size of carry-on bottles, highly potent chemicals (e.g., nerve agents) are a very serious threat. A single travel bottle full of such chemicals would cause great harm to many people and create a national security incident disrupting civilian air travel. Current screening methods to detect highly potent chemicals require opening a closed bottle. Experts at Los Alamos National Laboratory have developed SEDONA, a low magnetic field nuclear magnetic resonance (NMR) to detect chemical threats through unopened bottles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Autonomous reinforcement learning agents for improving predictions and observations of extreme climate events

Primary Focus Area: This proposal addresses focus area 2, “Predictive modeling through the use of AI techniques.” Science Challenge: Extreme climate events associated with severe weather, coastal and inland flooding, droughts, heat waves and wildfires are expected to increase in frequency and severity in the future. Due to the complexity and chaotic behavior of the climate system, accurately predicting and observing extreme climate events requires a tremendous amount of human intervention to run predictive climate simulations and deploy measurement systems. Extreme events often unfold very quickly, leaving little time to iterate on simulations or re-position instruments. Through reinforcement learning, autonomous AI agents can be designed to make real-time decisions to characterize extreme climate events more efficiently through adaptive models and targeted observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Next Generation Chemical Agent Detection Architecture [Poster]

Sandia National Labs (SNL)-designed, portable chemical warfare agent (CWA) detection systems consist of three-stages: collection, separation, and detection. We use microfabrication technologies to miniaturize these stages and to reduce the overall size, weight, power, and (potentially) cost of the final system. Our newest system consists of a multi-dimensional separation stage and an miniature ion mobility spectrometer (IMS) detector for unprecedented system sensitivity, selectivity, and depth of target list.

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

Statistical Learning for Nonlinear Model Reduction from Local Simulations of Stochastic and Particle- and Agent-Based Systems

Stochastic physical systems across the sciences that have very high-dimensional state spaces, with a large number of fast degrees of freedom that force direct simulators to proceed by integration steps that are orders of magnitude smaller than events of interests (e.g., particle collisions). Examples range from molecular motion to dynamics of large populations of cells. A grand challenge in the simulation and understanding of such systems is the systematic construction of accurate, interpretable, reduced models, enabling faster simulations, revealing fundamental properties of the dynamics, and predicting phenomena of interest that the original simulator could not reached with sufficient accuracy or within a given computational budget. In this projected we developed novel statistical estimation/machine learning techniques for analyzing and building empirical reduced models for important families of high-dimensional stochastic systems, in particular: - we developed techniques for estimating interaction kernels in interacting particle- and agent-based systems, which are ubiquitous in Physics, Biology and many other sciences, given observed trajectories of the system; - we developed techniques for nonlinear model reduction for high-dimensional stochastic systems that have a small number of unknown, nonlinear slow variables, and a large number of fast modes, that are possibly of large magnitude, given observed short trajectories of the system in the form of bursts of trajectories from different initial conditions; - we developed novel techniques for estimating linear dynamical systems on graphs when both the dynamics and the underlying graph are unknown, and we have a sparse set of space-time observations; - we considered the problem of estimating an unknown nonlinear observation function of a standard process (e.g. Brownian motion), so that we can recognized if an observed dynamics is "just" a nonlinear version of a known dynamics; we also developed benchmarks for learning algorithms aimed at learning and classifying diffusion processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Agent-Based Models for COVID-19 [Slides]

Goals: 1) Evaluate "what if” scenarios and mitigation strategies to combat COVID-19 spread within LANL and 2) perform retrospective analysis to assess accuracy of LANL COVID-19 agent-based model (ABM).

60 APPLIED LIFE SCIENCES↗