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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Small arms suppression project (LLNL final report)

US Special Operations Command (USSOCOM) was seeking a technological leap in small firearms weapon suppressor technology, because anticipated enemy capabilities are requiring the operators to have smaller detection cross sections to ensure the safe execution of missions. Suppressors have been developed almost exclusively through trial-and-error methods since the time of the original design by Hiram Maxim over one hundred years ago. Consequently USSOCOM deemed it prudent to perform a physicsbased study of weapon suppression to understand performance limits and possibly identify breakthrough technologies. Lawrence Livermore National Laboratory’s (LLNL’s) high performance production level computational tool called ALE3D (Arbitrary Lagrangian-Eulerian 3D and 2D) has unique physics models and numerical algorithms for modeling suppressor dynamics. The flexible and extendable code framework supports fully integrated hydrodynamics, heat transfer, solid and fluid dynamics, and chemistry that can be applied to simulating propellant-driven motion of a bullet down a gun barrel, the transfer of heat from the burning propellant to the barrel and suppressor, the chemistry of muzzle flash, and the shock/acoustic/optical signatures in the near-field. LLNL’s originally anticipated role was to augment ALE3D for this task, by developing the software and analysis methodologies specific to the simulation of blast and muzzle flash phenomena. It was believed that insights provided by our ALE3D simulations in tandem with a coordinated experimental component by our other team members from Oak Ridge National Laboratory (ORNL) and the U. S. Army Armament, Research, Development and Engineering Center (ARDEC), would have excellent prospects of yielding useful suppressor design improvements that could be transitioned to industry and utilized by US Special Operations Command. The three year effort has come to fruition with the development of revolutionary suppressor designs that far outperform any previous or current design by anyone outside this multi-lab team.

42 ENGINEERING↗
DOE OSTI2020

Transfer Factors for the FRMAC Assessment Manual and Turbo FRMAC to Improve Radiological Dose Assessment

The Turbo FRMAC analysis tool is used to perform complex calculations to quickly evaluate radiological consequences and aid in decision making during an emergency response by assessing impacts to the public, workers, and the food supply. Turbo FRMAC calculations are based on methods established by the Federal Radiological Monitoring and Assessment Center (FRMAC). To be able to assess impacts, input data called transfer factors that describe radionuclide uptake by local plants and animals are required. During the code application exercises in late 2016, identifying, finding, and validating nonstandard transfer factors proved to be time consuming and diverted the teams’ activity away from other critical tasks. As a result, a task was undertaken to dramatically expand the list of available transfer factors (food and non-food) and incorporate these factors into Turbo FRMAC. This will ultimately result in improved efficiency of the assessment team to perform calculations during times when the FRMAC is activated and provide more defensible, vetted data from which to calculate results. As a result of these and subsequent exercises, transfer factors were needed for the following items: bell peppers, Christmas tree, deer, flowers, fresh cucumbers, tomatoes, grapefruit, lichens, mushrooms, oranges, snap beans, squash, strawberries, sugarcane for sugar and seed, sweet corn, tea, tobacco, tree bark, and watermelon. To expand the applicability of the information tables, generic transfer data were also provided for common categories and recommendations were made for expanding the list of chemicals based on chemical similarity. The data presented in this report were compiled from recent literature with most of the data encompassing the period from 2000 to 2018. The following radionuclides were targeted during the literature search: elements associated with reactor accidents or nuclear detonations (Sr 89/90, Cs 134/137, Ce 141/144, Ru 103/106, I 129/131/133, Pu 238/239, Am 241, Zr 95, and Nb 95) and elements associated with industrial accidents or dirty bombs (Ir 192 and Co 60). Data from other elements were evaluated if they were identified during the literature search. In addition, reports were evaluated that were recommended by the research consultants. For each plant or animal transfer factor, the goal was to determine the geometric mean, the geometric standard deviation, the minimum, the maximum, and the number of measurements used. If only one measurement was available that was presented as the mean. Concentration ratios with large geometric standard deviations (GSDs) were generally the result of a paucity of measurements or a few disparate measurements. Measurement disparity was observed for data from different soil types. The geometric mean (GM) is a good reference value for planning and responses purposes, but the location-specific concentrations are unlikely to be similar to the model results. Recommendations for further work include: segregating the data to reflect the influence of soil type, developing approaches to incorporate animal data based on aggregated transfer measurements, and including data for foliar deposition on plants.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Advanced Reactor Cyber Analysis and Development Environment (ARCADE) for System-Level Design Analysis

Cybersecurity is a persistent concern to the safety and security of Nuclear Power Plants (NPPs), but has lacked data-driven, evidence-based research. Rigorous cybersecurity analysis is critical for the licensing of advanced reactors using a performance-based approach. One tool that enables cybersecurity analysis is modeling and simulation. The nuclear industry makes extensive use of modeling and simulation throughout the decision process but lacks a method to incorporate cybersecurity analysis with existing models. To meet this need, the Advanced Reactor Cyber Analysis and Development Environment (ARCADE) was developed. ARCADE is a suite of publicly available tools that can be used to develop emulations of industrial control system devices and networks and integrate those emulations with physics simulators. This integration of cyber emulations and physics models enables rigorous cyber-physical analysis of cyber-attacks on NPP systems. This report provides an overview of key considerations for using ARCADE with existing physics models and demonstrates ARCADE’s capabilities for cybersecurity analysis. Using a model of the Small Modular Advanced High Temperature Reactor (SmAHTR), ARCADE was able to determine the sensitivity of the primary heat exchangers (PHX) to coordinated cyber-attacks. The analysis determined that while the PHX’s failures cause disruption to the reactor, they did not cause any safety limits to be exceeded because of the plant design, including passive safety features. Further development of ARCADE will enable rigorous, repeatable, and automated cyber-physical analysis of advanced reactor control systems. These efforts will also help reduce regulatory uncertainty by presenting similar types of cybersecurity analyses in a common format, driving standard approaches and reporting.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Searching for Short-Lived Particles Using the FASER Neutrino Detector

Short-lived particles such as $\tau$ leptons and charm hadrons produced from high-energy neutrino interactions can provide key insights into the Standard Model and beyond. In this study, initial results of the performance of dedicated search tools developed for FASERν are presented. For charged charm searches, all daughter tracks are identified for ~3/4 of the events. Advanced yet reliable machine learning tools are used for D0 detection. For $\tau$ searches, a signal / background ratio of 3.8 is achieved. These results are a major step towards discovering the first charm hadrons and $\tau$ leptons produced from collider neutrinos.

Thor, Simon [CERN] (ORCID:000000029183526X)↗
DOE OSTI2026

Yet Another NLA Library: T-LAPACK

In recent years, Randomized numerical linear algebra (RandNLA) proved to be more than a theoretical novelty: projects like RandLAPACK demonstrate its practical value across architectures, and projects like RandBLAS build trust in randomization as a tool for high-performance NLA. This BoF considers two main questions. First, what are the pressing issues in software standards and implementation that need to be resolved for RandNLA to become a core component of HPC? Second, how can we mobilize a community effort to make progress on these issues? The BoF will engage the audience to discuss the idea of growing the role of RandNLA in high-performance computing and what it would take to scale from niche prototypes to robust, production-quality software libraries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Checking Questionable Entry of Personally Identifiable Information Encrypted by One-Way Hash Transformation

Background: As one of the several effective solutions for personal privacy protection, a global unique identifier (GUID) is linked with hash codes that are generated from combinations of personally identifiable information (PII) by a one-way hash algorithm. On the GUID server, no PII is permitted to be stored, and only GUID and hash codes are allowed. The quality of PII entry is critical to the GUID system. Objective: The goal of our study was to explore a method of checking questionable entry of PII in this context without using or sending any portion of PII while registering a subject. Methods: According to the principle of GUID system, all possible combination patterns of PII fields were analyzed and used to generate hash codes, which were stored on the GUID server. Based on the matching rules of the GUID system, an error-checking algorithm was developed using set theory to check PII entry errors. We selected 200,000 simulated individuals with randomly-planted errors to evaluate the proposed algorithm. These errors were placed in the required PII fields or optional PII fields. The performance of the proposed algorithm was also tested in the registering system of study subjects. Results: There are 127,700 error-planted subjects, of which 114,464 (89.64%) can still be identified as the previous one and remaining 13,236 (10.36%, 13,236/127,700) are discriminated as new subjects. As expected, 100% of nonidentified subjects had errors within the required PII fields. The possibility that a subject is identified is related to the count and the type of incorrect PII field. For all identified subjects, their errors can be found by the proposed algorithm. The scope of questionable PII fields is also associated with the count and the type of the incorrect PII field. The best situation is to precisely find the exact incorrect PII fields, and the worst situation is to shrink the questionable scope only to a set of 13 PII fields. In the application, the proposed algorithm can give a hint of questionable PII entry and perform as an effective tool. Conclusions: The GUID system has high error tolerance and may correctly identify and associate a subject even with few PII field errors. Correct data entry, especially required PII fields, is critical to avoiding false splits. In the context of one-way hash transformation, the questionable input of PII may be identified by applying set theory operators based on the hash codes. The count and the type of incorrect PII fields play an important role in identifying a subject and locating questionable PII fields.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Global trends in Akkermansia muciniphila research: A bibliometric visualization

Background Akkermansia muciniphila is a member of the gut microbiome, using mucin as sources of carbon, nitrogen, and energy. Since the first discovery of this unique bacterium in 2004, A. muciniphila has been extensively studied. It is considered a promising “next-generation beneficial microbe.” The purpose of this paper is to sort out the research status and summarize the hotspots through bibliometric analysis of the publications of A. muciniphila. Methods The publications about A. muciniphila from January 2004 to February 2022 were obtained from the Web of Science Core Collection. Visualization analyses were performed using three bibliometric tools and GraphPad Prism. Results A total of 1,478 published documents were analyzed. Annual publication number grew from 1 in 2004 to 336 in 2021, with China being the leading producer (33.36%). De Vos, Willem M was the most productive author with the highest H-index (documents = 56, H-index = 37), followed by Cani, Patrice D (documents = 35, H-index = 25). And Scientific Reports published the most papers. PNAS was the keystone taxa in this field, with high betweenness centrality (0.11) and high frequency. The keywords with high frequency in recent years include: oxidative stress, diet, metformin, fecal microbiota transplantation, short-chain fatty acids, polyphenols, microbiota metabolites and so on. The keyword “oxidative stress” was observed to be increasing in frequency recently. Conclusion Over time, the scope of the research on the clinical uses of A. muciniphila has gradually increased, and was gradually deepened and developed toward a more precise level. A. muciniphila is likely to remain a research hotspot in the foreseeable future and may contribute to human health.

Li, Zitong↗
DOE OSTI2019

Using Real-Time Electricity Prices to Leverage Electrical Energy Storage and Flexible Loads in a Smart Grid Environment Utilizing Machine Learning Techniques

With exposure to real-time market pricing structures, consumers would be incentivized to invest in electrical energy storage systems and smart predictive automation of their home energy systems. Smart home automation through optimizing HVAC (heating, ventilation, and air conditioning) temperature set points, along with distributed energy storage, could be utilized in the process of optimizing the operation of the electric grid. Using electricity prices as decision variables to leverage electrical energy storage and flexible loads can be a valuable tool to optimize the performance of the power grid and reduce electricity costs both on the supply and demand sides. Energy demand prediction is important for proper allocation and utilization of the available resources. Manipulating energy prices to leverage storage and flexible loads through these demand prediction models is a novel idea that needs to be studied. In this paper, different models for proactive prediction of the energy demand for an entire city using different machine learning techniques are presented and compared. The results of the machine learning techniques show that the proposed nonlinear autoregressive with exogenous inputs neural network model resulted in the most accurate predictions. These prediction models pave the way for the demand side to become an important asset for grid regulation by responding to variable price signals through battery energy storage and passive thermal energy storage using HVAC temperature set points.

25 ENERGY STORAGE↗
DOE OSTI2016

Ubiquitous giant Lyα nebulae around the brightest quasars at z ∼ 3.5 revealed with MUSE

Direct Lyα imaging of intergalactic gas at z∼2 has recently revealed giant cosmological structures around quasars, e.g., the Slug Nebula. Despite their high luminosity, the detection rate of such systems in narrow-band and spectroscopic surveys is less than 10%, possibly encoding crucial information on the distribution of gas around quasars and the quasar emission properties. In this study, we use the MUSE integral-field instrument to perform a blind survey for giant Lyα nebulae around 17 bright radio-quiet quasars at 3<z<4 that does not suffer from most of the limitations of previous surveys. After data reduction and analysis performed with specifically developed tools, we found that each quasar is surrounded by giant Lyα nebulae with projected sizes larger than 100 physical kiloparsecs and, in some cases, extending up to 320 kpc. The circularly averaged surface brightness profiles of the nebulae appear to be very similar to each other despite their different morphologies and are consistent with power laws with slopes ≈−1.8. The similarity between the properties of all these nebulae and the Slug Nebula suggests a similar origin for all systems and that a large fraction of gas around bright quasars could be in a relatively “cold” (T ∼ 10{sup 4 }K) and dense phase. In addition, our results imply that such gas is ubiquitous within at least 50 kpc from bright quasars at 3<z<4 independently of the quasar emission opening angle, or extending up to 200 kpc for quasar isotropic emission.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

EmpiriciSN: Re-sampling Observed Supernova/Host Galaxy Populations Using an XD Gaussian Mixture Model

We describe two new open-source tools written in Python for performing extreme deconvolution Gaussian mixture modeling (XDGMM) and using a conditioned model to re-sample observed supernova and host galaxy populations. XDGMM is new program that uses Gaussian mixtures to perform density estimation of noisy data using extreme deconvolution (XD) algorithms. Additionally, it has functionality not available in other XD tools. It allows the user to select between the AstroML and Bovy et al. fitting methods and is compatible with scikit-learn machine learning algorithms. Most crucially, it allows the user to condition a model based on the known values of a subset of parameters. This gives the user the ability to produce a tool that can predict unknown parameters based on a model that is conditioned on known values of other parameters. EmpiriciSN is an exemplary application of this functionality, which can be used to fit an XDGMM model to observed supernova/host data sets and predict likely supernova parameters using a model conditioned on observed host properties. It is primarily intended to simulate realistic supernovae for LSST data simulations based on empirical galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Magnetic Flux Rope Identification and Characterization from Observationally Driven Solar Coronal Models

Formed through magnetic field shearing and reconnection in the solar corona, magnetic flux ropes are structures of twisted magnetic field, threaded along an axis. Their evolution and potential eruption are of great importance for space weather. Here we describe a new methodology for the automated detection of flux ropes in simulated magnetic fields, utilizing field-line helicity. Our Flux Rope Detection and Organization (FRoDO) code, which measures the magnetic flux and helicity content of pre-erupting flux ropes over time, as well as detecting eruptions, is publicly available. As a first demonstration, the code is applied to the output from a time-dependent magnetofrictional model, spanning 1996 June 15–2014 February 10. Over this period, 1561 erupting and 2099 non-erupting magnetic flux ropes are detected, tracked, and characterized. For this particular model data, erupting flux ropes have a mean net helicity magnitude of 2.66×10{sup 43} Mx{sup 2}, while non-erupting flux ropes have a significantly lower mean of 4.04×10{sup 42} Mx{sup 2}, although there is overlap between the two distributions. Similarly, the mean unsigned magnetic flux for erupting flux ropes is 4.04×10{sup 21} Mx, significantly higher than the mean value of 7.05×10{sup 20} Mx for non-erupting ropes. These values for erupting flux ropes are within the broad range expected from observational and theoretical estimates, although the eruption rate in this particular model is lower than that of observed coronal mass ejections. In the future, the FRoDO code will prove to be a valuable tool for assessing the performance of different non-potential coronal simulations and comparing them with observations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1971

Radioactive nondestructive test method

Various radioisotope techniques were used as diagnostic tools for determining the performance of spacecraft propulsion feed system elements. Applications were studied in four tasks. The first two required experimental testing involving the propellant liquid oxygen difluoride (OF2): the neutron activation analysis of dissolved or suspended metals, and the use of radioactive tracers to evaluate the probability of constrictions in passive components (orifices and filters) becoming clogged by matter dissolved or suspended in the OF2. The other tasks were an appraisal of the applicability of radioisotope techniques to problems arising from the exposure of components to liquid/gas combinations, and an assessment of the applicability of the techniques to other propellants.

Obrien, J. R.↗
NASA NTRS1978

Loran-C time difference calculations

Some of the simpler mathematical equations which may be used in Loran-C navigation calculations were examined. A technique is presented to allow Loran-C time differences to be predicted at a location. This is useful for receiver performance work, and a tool for more complex calculations, such as position fixing.

Fischer, J. P.↗
NASA NTRS1981

Onboard utilization of ground control points for image correction. Volume 3: Ground control point simulation software design

The software developed to simulate the ground control point navigation system is described. The Ground Control Point Simulation Program (GCPSIM) is designed as an analysis tool to predict the performance of the navigation system. The system consists of two star trackers, a global positioning system receiver, a gyro package, and a landmark tracker.

Source record↗
NASA NTRS1980

Manufacturing cost/design system: A CAD/CAM dialogue

The development of the Manufacturing Cost/Design System (MC/DS) will provide the aerospace design engineer a tool with which to perform heretofore impractical design manufacturing cost tradeoffs. The Air Force Integrated Computer Aided Manufacturing (ICAM) Office has initiated the development and demonstration of an MC/DS which, when fully implemented, will integrate both design and manufacturing data bases to provide real time visibility into the manufacturing costs associated with various design options. The first release of a computerized system will be made before the end of 1981.

Loshigian, H. H.↗
NASA NTRS1984

The future scientific CCD

Since the first introduction of charge-coupled devices (CCDs) in 1970, CCDs have been considered for applications related to memories, logic circuits, and the detection of visible radiation. It is pointed out, however, that the mass market orientation of CCD development has left largely untapped the enormous potential of these devices for advanced scientific instrumentation. The present paper has, therefore, the objective to introduce the CCD characteristics to the scientific community, taking into account prospects for further improvement. Attention is given to evaluation criteria, a summary of current CCDs, CCD performance characteristics, absolute calibration tools, quantum efficiency, aspects of charge collection, charge transfer efficiency, read noise, and predictions regarding the characteristics of the next generation of silicon scientific CCD imagers.

Janesick, J. R.↗
NASA NTRS1987

CCD Luminescence Camera

New diagnostic tool used to understand performance and failures of microelectronic devices. Microscope integrated to low-noise charge-coupled-device (CCD) camera to produce new instrument for analyzing performance and failures of microelectronics devices that emit infrared light during operation. CCD camera also used to indentify very clearly parts that have failed where luminescence typically found.

Janesick, James R.↗