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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

GenomePeek—an online tool for prokaryotic genome and metagenome analysis

As increases in prokaryotic sequencing take place, a method to quickly and accurately analyze this data is needed. Previous tools are mainly designed for metagenomic analysis and have limitations; such as long runtimes and significant false positive error rates. The online tool GenomePeek (edwards.sdsu.edu/GenomePeek) was developed to analyze both single genome and metagenome sequencing files, quickly and with low error rates. GenomePeek uses a sequence assembly approach where reads to a set of conserved genes are extracted, assembled and then aligned against the highly specific reference database. GenomePeek was found to be faster than traditional approaches while still keeping error rates low, as well as offering unique data visualization options.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Remixing the ‘Appropriate Mix’: Reassessing NATO’s Deterrence and Defense Posture in the Face of New Threats

The North Atlantic Treaty Organization (NATO) and the countries of Europe face a renewed challenge from the east vis-à-vis the Putin regime in Moscow. In the face of these new challenges, NATO must reconsider its deterrence and defense posture in order to deter conflict in Europe. Unfortunately, Russian attempts to rewrite the rules of the post-Cold War international order by force have been coupled with nuclear saber rattling and overt nuclear threats. Russia’s nuclear threats, in addition to provocative changes to Russia’s nuclear posture in its Military Doctrine, are methods to make up for Russia’s conventional military inferiority relative to NATO and the United States. Some have described Moscow’s actions as laying the groundwork for a nuclear coercion strategy. While the decrease in the nuclear arsenals of Russia and the United States has reduced the likelihood of nuclear annihilation to an all-time low since the height of the Cold War, Russia’s nuclear coercion strategy is increasing the probability of nuclear employment in Europe. The probability of nuclear use is compounded by Russia’s tremendous local military advantage around its periphery in spite of U.S. global military primacy. This military advantage increases the incentive to use military force if Russian decision-makers conclude that a quick military victory is possible, or if Russian leaders miscalculate based on an incorrect assessment of military force balance or resolve of their adversary. The integration of Lithuania, Latvia, and Estonia (referred to as the Baltics in this paper) into the NATO alliance in 2004 makes Russia’s military advantage in its periphery increasingly relevant. Each NATO state is required to assist any NATO state that comes under attack per Article V of the North Atlantic Treaty. The Baltic states’ proximity to Russia, their weak indigenous militaries, their former status as Soviet Republics, large population of ethnic Russians, and Russian President Vladimir V. Putin’s claim that he will protect Russians wherever they are makes the Baltics the most likely flashpoint for conflict between NATO and Russia. This analysis will tackle the problem of reshaping NATO’s deterrence and defense posture in light of the new Russian threat and its obligation to defend its most vulnerable members. Specifically, it will assess the suitability of NATO’s “appropriate mix” of nuclear, conventional, and missile defense capabilities to deterring conventional conflict with Russia and, if conventional deterrence fails, preventing Russian nuclear escalation. It will use a scenario-based approach informed by a deterrence model to explore how changes to NATO’s posture and policy could impact the deterrence of Russian aggression.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

'Constraint consistency' at all orders in cosmological perturbation theory

We study the equivalence of two—order-by-order Einstein's equation and Reduced action—approaches to cosmological perturbation theory at all orders for different models of inflation. We point out a crucial consistency check which we refer to as 'Constraint consistency' condition that needs to be satisfied in order for the two approaches to lead to identical single variable equation of motion. The method we propose here is quick and efficient to check the consistency for any model including modified gravity models. Our analysis points out an important feature which is crucial for inflationary model building i.e., all 'constraint' inconsistent models have higher order Ostrogradsky's instabilities but the reverse is not true. In other words, one can have models with constraint Lapse function and Shift vector, though it may have Ostrogradsky's instabilities. We also obtain single variable equation for non-canonical scalar field in the limit of power-law inflation for the second-order perturbed variables.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Design Guidelines for Deployable Wind Turbines for Defense and Disaster Response Missions

Access to on-site electrical energy is critical to ensuring a successful military or humanitarian response to conflicts and disasters. These missions typically rely on access to liquid fuel that could be vulnerable to disruption or attack during transport. Generating power on location with wind technology—whether at a contingency base or disaster response coordination point—can reduce this risk and enhance mission reach by diversifying energy sources. Common characteristics of these missions are short planning and execution time horizons and a global scope of potential locations. Compared to conventional wind turbine applications, defense and disaster response applications place a premium on rapid shipping and installation, short-duration operation (days to months), and quick teardown upon mission completion. These design drivers depart from features found in conventional distributed wind turbines, thus necessitating unique design guidance. The supporting information for this guidance comes from available relevant references, technical analyses, and input from industry and military stakeholders. This paper serves as a summary of the full report, Design Guidelines for Deployable Wind Turbines for Military Operational Energy Applications (Sandia report SAND2021-14581 R [1]), which presents the best currently available design guidance for deployable wind turbines to facilitate the effective development and acquisition of technology solutions to support mission success.

17 WIND ENERGY↗
DOE OSTI2022

Design Guidelines for Deployable Wind Turbines for Defense and Disaster Response Missions

Access to on-site electrical energy is critical to ensuring a successful military or humanitarian response to conflicts and disasters. These missions typically rely on access to liquid fuel that could be vulnerable to disruption or attack during transport. Generating power on location with wind technology can reduce this risk and enhance mission reach by diversifying energy sources. Common characteristics of these missions are short planning and execution time horizons and a global scope of potential locations. Compared to conventional wind turbine applications, defense and disaster response applications place a premium on rapid shipping and installation, short-duration operation (days to months), and quick teardown upon mission completion. These design drivers depart from features found in conventional distributed wind turbines, thus necessitating unique design guidance. The supporting information for this guidance comes from available relevant references, technical analyses, and input from industry and military stakeholders. This poster serves as a summary of project publications which presents the best currently available design guidance for deployable wind turbines to facilitate the effective development and acquisition of technology solutions to support mission success. This Defense and Disaster Deployable Turbine Project (D3T) is a multi-laboratory effort led by Sandia National Laboratories and funded by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Wind Energy Technologies Office.

deployable wind↗
DOE OSTI2018

Electron Environment at Geostationary Orbit: AE9 Summary Results

This report captures the outputs from the AE9 for the electron environment at geostationary orbit. There is no new work, simply a collection of model outputs to make them easier to use and tailored to quick data gathering for geostationary orbit studies. Other models do exist, such as POLE, but a comprehensive look at each is beyond the scope of this work. Other resources are contained in the references.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Learning new physics from data: A symmetrized approach

Thousands of person years have been invested in searches for new physics (NP), the majority of them motivated by theoretical considerations. Yet, no evidence of beyond the Standard Model physics has been found. This suggests that model-agnostic searches might be an important key to explore NP, and help discover unexpected phenomena which can inspire future theoretical developments. A possible strategy for such searches is identifying asymmetries between data samples that are expected to be symmetric within the Standard Model. We propose exploiting neural networks (NNs) to quickly fit and statistically test the differences between two samples. Our method is based on an earlier work, originally designed for inferring the deviations of an observed dataset from that of a much larger reference dataset. We present a symmetric formalism, generalizing the original one, avoiding fine-tuning of the NN parameters and any constraints on the relative sizes of the samples. Our formalism could be used to detect small symmetry violations, extending the discovery potential of current and future particle physics experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Downhole Sensing and Event-Driven Sensor Fusion for Depth-of-Cut Based Autonomous Fault Response and Drilling Optimization

Achieving robust and efficient drilling is a critical part of reducing the cost of geothermal energy exploration and extraction. Drilling performance is often evaluated using one or more of three key metrics: depth of cut (DOC), rate of penetration (ROP), and mechanical specific energy (MSE). All three of these quantities are related to each other. DOC refers to the depth a bit penetrates into rock during drilling. This is an important quantity for estimating bit behavior. ROP is the simply the DOC multiplied by the rotational rate, and represents how quickly the drill bit is advancing through the ground. ROP is often the parameter used for drilling control and optimization. Finally, MSE provides insight into drilling efficiency and rock type. MSE calculations rely on ROP, drilling force, and drilling torque. Surface-based sensors at the top of the drill are often used to measure all these quantities. However, top-hole measurements can deviate substantially from the behavior at the bit due to lag, vibrations, and friction. Therefore, relying only on top-hole information can lead to suboptimal drilling control. In this work, we describe recent progress towards estimating ROP, DOC, and MSE using down-hole sensing. We assume down-hole measurements of torque, weight-on-bit (WOB). Our hypothesis is that these measurements can provide more rapid and accurate measures of drilling performance. We show how a multi-layer perceptron (MLP) machine learning algorithm can provide rapid and accurate performance when evaluated on experimental data taken from Sandia’s Hard Rock Drilling Facility. In addition, we implement our algorithms on an embedded system intended to emulate a bottom-hole-assembly for sensing and estimation. Our experimental results show that DOC can be estimated accurately and in real-time. These estimates when combined with measurements for rotary speed, torque, and force can provide improved estimates for ROP and MSE. These results have the potential to enable better drilling assessment, improved control, and extended component lifetimes.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Experimentally Validated Computational Modeling of Creep and Creep-Cracking for Nuclear Concrete Structures

In a Nuclear Power Plant, one of the most important components is the concrete nuclear reactor cavity, which serves both a structural and protective function as the biological radiation shield. Given that creep has been identified as a major knowledge gap in the assessment of nuclear structures (NUREG/CR-7153), this work helps to further the understanding of creep behavior of massive concrete containment structures for decades to enable safe and long-term operation of these facilities. This project has developed a robust, experimentally validated model to predict creep in nuclear concrete structures for up 60 years using short-term creep data thereby enabling a longer service life of critical facilities and early detection of structural failure. The work presented in this report is a pairing of computational and experimental methods. For the first time, the time temperature superposition (TTS) principle was successfully used to generate a uniaxial creep compliance master curve to predict mortar creep response for up to 22,500 days (nearly 60 years) at a reference temperature of 20°C. These data were used as input into finite element analysis (FEA) codes that use highly realistic random, 3D concrete microstructures from reconstructed coarse limestone aggregates. Finite element analysis performed provides the ability to quickly upscale mortar viscoelastic behavior to long-term concrete creep/relaxation data. A master creep compliance curve, constructed from the TTS principle, spanning 27 years, was used to validate two and a half decades of simulated concrete creep. Concurrently, three different simulated wall specimens were designed to mimic the behavior of post-tensioned concrete nuclear containment facility vessel walls over time as a result of concrete creep. The specimens were designed with different thicknesses, transverse and longitudinal reinforcement ratios, and level of post-tensioning stress. Each specimen contained various instrumentation to measure internal concrete temperature, concrete strain, and post-tensioning strain hourly for over 3 years. The concrete creep model developed in this project, based on the FEA concrete simulations, was applied to simulate the structural-scale experiments of prestressed concrete walls conducted in this project using the Grizzly code. These models can represent the effects of reinforcing and prestressing. Although there are some discrepancies with the experimental data, the model can predict the overall trends of the creep response in these experiments. One of these experimental models was also applied to an extended time to demonstrate how the findings from this study can be used to predict the behavior of actual structures of interest that have been in service for extended periods of time.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Development of a Convolutional Neural Network Classifier for Data Starved Spectra - 20199

The Institute for Clean Energy Technology (ICET) at Mississippi State University is exploring the utility of machine learning in augmenting its mobile radiation surveying platforms, which are currently being developed as means to survey depleted uranium contaminated areas in support of remediation and decommissioning efforts. Mobile survey platforms provide a means to efficiently scan large areas of interest while reducing human exposure to radiation and other hazards. The survey platforms can also be used for scanning for any gamma emitting isotope in addition to depleted uranium. The spectral data that the platforms collect may be data starved with relatively low counts and poorly defined spectral features depending on the speed of the platforms and scintillation detector selection. Such data-starved spectra are difficult to use for isotope identification, requiring advanced knowledge of the possible radionuclides that could be present and environmental factors that could attenuate signals or introduce background noise. These factors in combination with the volume of survey data increases the time it takes to perform analysis of survey data when the source type is unknown. There are a number of algorithms in the field of machine learning that can be used to classify data that would be challenging and time-consuming for a human to identify. Supervised machine learning algorithms train models based on extensive amounts of human-labeled training data. Once sufficiently trained, these models can be used to quickly make high-fidelity predictions on new data. Convolutional neural networks are machine learning algorithms that excel in learning representations of 'shapes'. They do this by taking numerical input data and convolving them with spatial feature detectors referred to as filters. These filters are incrementally adjusted to reduce the prediction error on the data during the backpropagation step of training. Discussed in this paper is the development of a convolutional neural network classifier (CNNC) that can utilize spectral survey data for source discrimination and isotope identification. Bench-top laboratory experiments data using LaBr{sub 3}(Ce) scintillation detectors were used to train and evaluate the performance of the developed CNNC. The CNNC is capable of discriminating a variety of gamma emitting source types, differentiating different forms of uranium (depleted vs. natural), and estimating the amount of uranium for a known geometry. The discussed CNNC may be useful in scenarios where survey systems are deployed in situations where hazardous radioactive material maybe present, but the type is unknown. When used in remediation applications the CNNC can be used to screen-out false positives, helping reduce remediation costs. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

Chroma Shift and Gamut Shape: Going Beyond Average Color Fidelity and Gamut Area

Though sometimes referred to as a two-measure system for evaluating color rendition, IES TM-30-15 includes other key components that go beyond the high-level average values IES Rf and IES Rg. This article focuses on the Color Vector Graphic and Local Chroma Shift (IES Rcs,hj), discussing the calculation methods for these evaluation tools and providing context for the interpretation of the values. It also presents alternatives for quantifying the same characteristics, which can inform the development of future measures. The Color Vector Graphic (CVG) is a visual representation of hue and chroma shifts across different hues. It quickly communicates complex information about how object colors will be rendered by a light source, although it is difficult or impossible to use for writing a specification. CVGs demonstrate that increases in chroma for certain hues sometimes means a decrease in chroma for other hues, and illustrates hue shifts for intermediate colors. The combination of shifts over different hues can be referred to as gamut shape. Complementing this information are the IES Rcs,hj values, which quantify the average relative chroma shift for samples in each of the 16 hue-angle bins (j) specified in IES TM-30-15. Unlike measures of average color fidelity and gamut area, gamut shape and hue-specific chroma shift are new concepts with no directly-comparable historical references. It will be critical to incorporate the Color Vector Graphic and Local Chroma Shift values into practice because they capture information about color rendition that is impossible to describe with average measures (such as CIE Ra, IES Rf, or IES Rg), but that is critical to understanding human evaluations of color quality in architectural environments.

Chroma Shift↗
DOE OSTI2014

SU-E-T-27: A Tool for Routine Quality Assurance of Radiotherapy Dose Calculation Software

Purpose: Dose calculation software is thoroughly evaluated when it is commissioned; however, evaluation of periodic software updates is typically limited in scope due to staffing constraints and the need to quickly return the treatment planning system to clinical service. We developed a tool for quickly and comprehensively testing and documenting dose calculation software against measured data. Methods: A tool was developed using MatLab (The MathWorks, Natick, MA) for evaluation of dose calculation algorithms against measured data. Inputs to the tool are measured data, reference DICOM RT PLAN files describing the measurements, and dose calculations in DICOM format. The tool consists of a collection of extensible modules that can perform analysis of point dose, depth dose curves, and profiles using dose difference, distance-to-agreement, and the gamma-index. Each module generates a report subsection that is incorporated into a master template, which is converted to final form in portable document format (PDF). Results: After each change to the treatment planning system, a report can be generated in approximately 90 minutes. The tool has been in use for more than 5 years, spanning 5 versions of the eMC and 4 versions of the AAA. We have detected changes to the algorithms that affected clinical practice once during this period. Conclusion: Our tool provides an efficient method for quality assurance of dose calculation software, providing a complete set of tests for an update. Future work includes the addition of plan level tests, allowing incorporation of, for example, the TG-119 test suite for IMRT, and integration with the treatment planning system via an application programming interface. Integration with the planning system will permit fully-automated testing and reporting at scheduled intervals.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2017

Sandia Dynamic Materials Program Strategic Plan.

Materials in nuclear and conventional weapons can reach multi-megabar pressures and 1000s of degree temperatures on timescales ranging from microseconds to nanoseconds. Understanding the response of complex materials under these conditions is important for designing and assessing changes to nuclear weapons. In the next few decades, a major concern will be evaluating the behavior of aging materials and remanufactured components. The science to enable the program to underwrite decisions quickly and confidently on use, remanufacturing, and replacement of these materials will be critical to NNSA’s new Stockpile Responsiveness Program. Material response is also important for assessing the risks posed by adversaries or proliferants. Dynamic materials research, which refers to the use of high-speed experiments to produce extreme conditions in matter, is an important part of NNSA’s Stockpile Stewardship Program.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Failure Mechanism of Fast-Charged Lithium Metal Batteries in Liquid Electrolyte

In recent years, lithium anode has re-attracted broad interest because of the necessity of employing lithium metal in the next-generation battery technologies such as lithium sulfur (Li-S) and lithium oxygen (Li-O2) batteries. Fast capacity degradation and safety issue associated with rechargeable lithium metal batteries have been reported, although the fundamental understanding on the failure mechanism of lithium metal at high charge rate is still under debate due to the complicated interfacial chemistry between lithium metal and electrolyte. Herein, we demonstrate that, at high current density, the quick growth of porous solid electrolyte interphase towards bulk lithium, instead of towards the separator, dramatically builds up the cell impedance that directly leads to the cell failure. Understanding the lithium metal failure mechanism is very critical to gauge the various approaches used to address the stability and safety issues associated with lithium metal anode. Otherwise, all cells will fail quickly at high rates before the observation of any positive effects that might be brought from adopting the new strategies to protect lithium.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2026

GridPIQ Reference Data

GridPIQ uses dozens of publicly available datasets to provide context for a user's grid project, as well as defaults for users to choose from. Users can choose to import their own data to better customize their analysis or use GridPIQ-supplied defaults. This allows users to get up and running with an analysis very quickly without having to spend significant time pulling together input data. To run an electric vehicle (EV) smart charging project, a user will need to provide or select from prepopulated values for the regional load profile shape and peak load, region of interest and closest weather station, EV charging profile, number of EVs to add for the analysis, maximum EV charging power, location of chargers relative to grid infrastructure, and allowable charging times (for coordinated charging mode). The outputs of the analysis are changes in air quality, EV energy consumption, EV peak demand, and EV hourly consumption profile—before and after project implementation." For a detailed description of the tool methodology, including all the publicly available datasets used by the tool, see the [GridPIQ documentation](https://gridpiq.pnnl.gov/v2-beta/doc/).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

SU-E-T-172: Evaluation of the Exradin A26 Ion Chamber in Megavoltage Photon Beams as a Reference Class Instrument

Purpose: The Exradin A26 is a new design of micro-ionization ion chamber that externally resembles the Exradin A16 model but has significant internal changes to address measurement issues reported in the literature for the A16. This project involved the characterization of two versions of the A26 chamber in high energy x-rays with particular reference to the performance specification laid out in the imminent Addendum to TG-51. Methods: The Exradin A26 was investigated in a range of megavoltage photon beams (6–25 MV). Investigations looked at chamber settling, ion recombination and polarity. Since it has been previously shown that non-ideal performance is most easily identified through ion recombination measurements, the focus was on the determination of Pion. Results: i) Chamber settling - the chamber response stabilizes very quickly (within 3 minutes), even after a large change in the polarizing voltage.ii) The polarity correction was found to be small (within 0.2% of unity)iii) The chamber showed linear behavior for a Jaffe plot (1/reading vs 1/polarizing voltage) for applied voltages ≤ 200 V.iv) The recombination correction showed a linear variation with the doseper- pulse, was not significantly dependent on the polarity of the collecting voltage and was consistent with the chamber dimensions (i.e. agreed with Boag theory). Conclusion: An initial investigation of the Exradin A26 micro chamber suggests that although its performance exceeds the AAPM specification for a reference-class ion chamber for use in megavoltage photon beams it is a significant improvement over the previous A16 design. Further work is required to evaluate long-term stability and determine kQ factors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

A database of synthetic inelastic neutron scattering spectra from molecules and crystals

Abstract Inelastic neutron scattering (INS) is a powerful tool to study the vibrational dynamics in a material. The analysis and interpretation of the INS spectra, however, are often nontrivial. Unlike diffraction, for which one can quickly calculate the scattering pattern from the structure, the calculation of INS spectra from the structure involves multiple steps requiring significant experience and computational resources. To overcome this barrier, a database of INS spectra consisting of commonly seen materials will be a valuable reference, and it will also lay the foundation of advanced data-driven analysis and interpretation of INS spectra. Here we report such a database compiled for over 20,000 organic molecules and over 10,000 inorganic crystals. The INS spectra are obtained from a streamlined workflow, and the synthetic INS spectra are also verified by available experimental data. The database is expected to greatly facilitate INS data analysis, and it can also enable the utilization of advanced analytics such as data mining and machine learning. Notice: This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a non-exclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan ( http://energy.gov/downloads/doe-public-access-plan ).

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Technical Note: Range verification system using edge detection method for a scintillator and a CCD camera system

Purpose: Three-dimensional irradiation with a scanned carbon-ion beam has been performed from 2011 at the authors’ facility. The authors have developed the rotating-gantry equipped with the scanning irradiation system. The number of combinations of beam properties to measure for the commissioning is more than 7200, i.e., 201 energy steps, 3 intensities, and 12 gantry angles. To compress the commissioning time, quick and simple range verification system is required. In this work, the authors develop a quick range verification system using scintillator and charge-coupled device (CCD) camera and estimate the accuracy of the range verification. Methods: A cylindrical plastic scintillator block and a CCD camera were installed on the black box. The optical spatial resolution of the system is 0.2 mm/pixel. The camera control system was connected and communicates with the measurement system that is part of the scanning system. The range was determined by image processing. Reference range for each energy beam was determined by a difference of Gaussian (DOG) method and the 80% of distal dose of the depth-dose distribution that were measured by a large parallel-plate ionization chamber. The authors compared a threshold method and a DOG method. Results: The authors found that the edge detection method (i.e., the DOG method) is best for the range detection. The accuracy of range detection using this system is within 0.2 mm, and the reproducibility of the same energy measurement is within 0.1 mm without setup error. Conclusions: The results of this study demonstrate that the authors’ range check system is capable of quick and easy range verification with sufficient accuracy.

60 APPLIED LIFE SCIENCES↗