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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Reinforced Ammo Can Validation Test Report for Lawrence Livermore National Laboratory

A research effort was conducted to investigate the effects of an unintentional internal detonation of energetic materials on a small transportation container called the “Reinforced Ammo Can” (RAC), which is currently approved for the transport of energetic materials up to 2 grams net explosive weight (NEW) onsite at Lawrence Livermore National Laboratory (LLNL). The project used experimental testing of the containers based on simulated results conducted by a Missouri S & T explosives engineering graduate student while on an internship working in explosives safety at LLNL. The proposed experimental testing consisted of 20 central detonation tests in separate Reinforced Ammo Can containers to verify their high explosive (HE) containment capability. RAC containers are required for transporting secondary explosives on site at LLNL Site 200 in quantities between 300 mg and 2 grams of Trinitrotoluene (TNT) equivalent NEW. Currently, the LLNL Environmental Safety and Health (ES&H) Manual states that the RAC containers are permissible for on-site transportation of secondary explosives up to 2 grams NEW by approved HE handlers with the approval of an Explosives Safety Expert (ESE). Simulated results indicated that tensile failure of the closure mechanism on the container is the most likely failure mode, and showed potential occurrence at the 2 gram NEW threshold. Experimental validation tests were conducted indicating failure/rupture of the containers lid with venting of the detonation products at the 2 gram NEW test threshold with an explosive mass safety factor of 1.3. Failure consisted of impact opening the container latch mechanism resulting in potential ejection of the lid depending on the orientation of the charge within the confinement. This analysis solely is an evaluation of the response of the containment if a detonation were to occur, it does NOT consider the probability of such an event.

42 ENGINEERING↗
DOE OSTI2022

Development of efficient solar cells using combination of QSPR and DFT approaches

The awarded research project aimed to design and determine the effective organic dye-sensitizers from the ensemble of chromophores for the dye-sensitized solar cell (DSSC) and fullerene-derivatives (FDs) as acceptor for polymer solar cell (PSC) followed by explore the electron transfer mechanism using the combined quantitative structure-property relationship (QSPR) analysis in conjunction with density functional theory (DFT) and time-dependent DFT (TDDFT)-based calculations. Based on our proposal we have employed different in silico approaches to design photo-efficient organic dye-sensitizers for DSSCs and FDs as acceptor for PSCs with exhaustive screening methodology.

14 SOLAR ENERGY↗
DOE OSTI2022

Uncertainty Quantification and Sensitivity Analysis for Simulation of Hostile Blast Events [Slides]

A mesh convergence study shows that shock arrival times converge for basic flow shots. Sensitivity study reveals a surprisingly high sensitivity to the placement of the HE package. Bayesian inference tools used on the experimental datasets suggest this is a real effect. Sensitivity analysis of ambient conditions such as temperature and pressure reveal minimal effect. Porting of pressure data from QUINOA simulations to perform structural analysis on the aeroshell geometry was successful, and shows a strong dependence of payload response to the angle of attack.

42 ENGINEERING↗
DOE OSTI2020

Standoff Detection of Chemical Plumes Using Swept-ECQCL Remote Detection Technology: Results from EMRTC Complex Terrain Dual Tracer Experiment

As part of the Complex Terrain Dual Tracer Experiments performed in support of the LYNM program, a swept-wavelength external cavity quantum cascade laser (swept-ECQCL) remote detection system was deployed to measure chemical plume propagation with high temporal resolution. The swept-ECQCL remote detection technology was initially developed at PNNL, and is now under further development at Opticslah, LLC under SBIR funding from DOE (DOE SBIR Phase I Project DE-SC0019855, Remote Detection Technologies, Program Manager Chris Ramos). The swept-ECQCL technology provides a single-frequency infrared laser source which is rapidly scanned over a large wavelength range to measure the infrared absorption of gases, liquids, or solids. Analysis of the measured infrared absorption spectrum is used to detect, identify, and quantify the chemical species which are present. While most previous laser-based techniques used small wavelength tuning ranges to measure only a few isolated spectral lines of a few species, the swept-ECQCL provides the large tuning range needed to measure multiple species simultaneously, and to detect broad absorption features from large molecules or condensed phase materials. In addition, the swept-ECQCL systems have high enough spectral resolution and sensitivity to measure narrow lines of small molecules and determine isotope ratios. The remote detection system for gas plumes is based on the swept-ECQCL technology, and consists of a swept-ECQCL source, infrared detector, control electronics, and beam transmitting and alignment optics. The remote detection system directs the infrared output of the swept-ECQCL to a target retro reflector typically located at ~10-10,000 m distance. The swept-ECQCL wavelength is varied continuously over a large wavelength range (>1000 nm) at rates up to 1000 Hz. The swept ECQCL light reflected from the remote target is collected and focused onto an infrared photodetector. By measuring the detector signal continuously as the swept-ECQCL wavelength is varied, a time-series of absorption spectra are measured for the gases along the beam line of-sight. Based on analysis and fitting of the measured absorption spectra, the time-dependent chemical concentrations of species are determined. Multiple species and mixtures can be detected simultaneously, for all species with absorption features above the sensor noise floor. The sensor output is thus a continuous, high-speed record of identified chemicals along with their concentrations and isotope ratios of interest. The high-speed operation enables low-noise operation in conditions of atmospheric turbulence and allows tracking of fluctuating concentrations in transient chemical plumes as needed for reliable remote detection applications. All components operate with minimal cooling requirements and no cryogens are needed. In addition, the output infrared light is invisible with an intensity below the maximum permissible exposure (MPE) threshold of 100 mW/cm2 for these infrared wavelengths and thus eye safe. The measurement concept for plume detection using the swept-ECQCL remote detection system is as follows. The ECQCL beam is directed toward a remote retro-reflector, which reflects the beam back to the ECQCL system where it is focused onto an infrared photodetector. The line-of-sight from the ECQCL system to the retro-reflector defines the measurement path. The detected infrared signal is recorded continuously and detects the absorption of molecular species along the measurement path. Before a plume release, the system measures absorption from atmospheric constituents, which in this LWIR band consist primarily of lines from H 2 O and CO 2 , with additional weaker absorption from N 2 O, NH 3 , and O 3 possibly contributing. The system then measures any changes in absorption due to the tracer compounds when they enter the measurement path. The shape of absorption features is used to distinguish and identify the different tracer compounds, and the strength of the absorption is used to determine the path-integrated concentration – also called the column density.

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

Resilience Lessons From the Southeast United States Woody Pellet Supply Chain Response to the COVID-19 Pandemic†

The Coronavirus Disease 2019 (COVID-19) instigated a pandemic that impacted economies, employment, and shipping worldwide. This paper reviews how one international supply chain performed and identifies lessons that may be helpful to improve future resilience. Economic and employment data through November 2020 are used to review the effects of COVID-19 on operations of the bioenergy supply chain in the southeastern United States (SE United States) that utilizes wood fiber to fabricate pellets. Conditions associated with the production of pellets in the SE United States changed with the outbreak of COVID-19. Federal and state government programs and classification of workers in this sector as “essential” during the pandemic helped maintain the woody pellet supply chain and other industries during a period of general shut down in 2020. The availability of personal protective equipment, long-term supply contracts, and established safety cultures are among the factors that enhance supply chain resilience while limited availability of skilled workers, inadequate stakeholder engagement, and dependence on external policies are among factors that reduce resilience. The analysis concludes with recommendations for the SE pellet supply chain, and other biomass supply chains, to improve their resilience to future disturbances. When best practices are implemented, SE United States biomass offers opportunities to contribute to post-pandemic economic recovery while incentivizing better forest resource management.

09 BIOMASS FUELS↗
DOE OSTI2021

Comparative Analysis of Machine Learning Models for Day-Ahead Photovoltaic Power Production Forecasting

A main challenge for integrating the intermittent photovoltaic (PV) power generation remains the accuracy of day-ahead forecasts and the establishment of robust performing methods. The purpose of this work is to address these technological challenges by evaluating the day-ahead PV production forecasting performance of different machine learning models under different supervised learning regimes and minimal input features. Specifically, the day-ahead forecasting capability of Bayesian neural network (BNN), support vector regression (SVR), and regression tree (RT) models was investigated by employing the same dataset for training and performance verification, thus enabling a valid comparison. The training regime analysis demonstrated that the performance of the investigated models was strongly dependent on the timeframe of the train set, training data sequence, and application of irradiance condition filters. Furthermore, accurate results were obtained utilizing only the measured power output and other calculated parameters for training. Consequently, useful information is provided for establishing a robust day-ahead forecasting methodology that utilizes calculated input parameters and an optimal supervised learning approach. Finally, the obtained results demonstrated that the optimally constructed BNN outperformed all other machine learning models achieving forecasting accuracies lower than 5%.

14 SOLAR ENERGY↗
DOE OSTI2025

Solid Wastes from Geothermal Energy Production and Implications for Direct Lithium Extraction

Direct lithium extraction (DLE) of brines after geothermal power production offers opportunities to produce environmentally benign “green” lithium; however, some environmental impact is inevitable. We examined solid waste production at geothermal power plants in southern California that are also locations for planned DLE facilities. Currently, the geothermal plants in this region produce approximately 79,800 metric tons (wet weight) per year of solid waste, which represents about 28 metric tons per GWh of net electricity production or approximately 500 mg solids per kg geothermal brine. Approximately 15% of this waste requires management as hazardous waste. Solids produced during power production represent about 0.2% of the total dissolved solids in the brine. Lithium production will require the removal of silica, iron, and other metals as part of the DLE process. Using a mass balance approach, we calculate that precipitation of silica and metals could produce up to an additional 6800 mg solids per kg brine. Calcium occurs at very high concentrations, and the amount of solids disposed in landfills will be dependent on the amount of calcium removed during lithium recovery. Our analysis shows that evaluation of brine chemistry in the context of the DLE process is useful for evaluating the potential solid waste impacts of producing lithium from brines.

42 ENGINEERING↗
DOE OSTI2026

The Extended Embedded Self-Shielding Method in SCALE 6.3/Polaris

The SCALE transport lattice code, Polaris, has been previously developed to generate few-group homogenized cross sections for whole-core nodal diffusion simulators in which the embedded self-shielding method (ESSM) is used for resonance self-shielding calculations to process cross sections. Although the ESSM capability has been very successful in light-water reactor analysis, it may require enhancements in computational efficiency; treatment of spatially dependent resonance self-shielding effects; and handling of interrelated resonance effects among fuel, cladding, and control rod materials. Therefore, this study focuses on improving computational efficiency by using a Dancoff-based Wigner–Seitz approximation combined with a material-based resonance categorization, through which a spatially dependent ESSM capability is developed to accurately estimate self-shielded cross sections inside the fuel. Benchmark results show that the new capability significantly enhances computational efficiency and accuracy for spatially dependent local zones within the fuel and through depletion.

ESSM↗
DOE OSTI2020

Stimulation of Insect Herbivory by Elevated Temperature Outweighs Protection by the Jasmonate Pathway

Rising global temperatures are associated with increases in the geographic range, population size, and feeding voracity of insect herbivores. Although it is well established that the plant hormone jasmonate (JA) promotes durable resistance to many ectothermic herbivores, little is known about how JA-mediated defense is influenced by rising temperatures. Here, we used the Arabidopsis-Trichoplusia ni (cabbage looper) interaction to investigate the relative contribution of JA and elevated temperature to host resistance. Video monitoring of T. ni larval behavior showed that elevated temperature greatly enhanced defoliation by increasing the bite rate and total time spent feeding, whereas loss of resistance in a JA-deficient mutant did not strongly affect these behaviors. The acceleration of insect feeding at elevated temperature was not attributed to decreases in wound-induced JA biosynthesis, expression of JA-responsive genes, or the accumulation of defensive glucosinolates prior to insect challenge. Quantitative proteomic analysis of insect frass, however, provided evidence for a temperature-dependent increase in the production of T. ni digestive enzymes. Our results demonstrate that temperature-driven stimulation of T. ni feeding outweighs the protective effects of JA-mediated resistance in Arabidopsis, thus highlighting a potential threat to plant resilience in a warming world.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Effect of Collimation on Diffraction Signal-to-Background Ratios at a Neutron Diffractometer

High diffraction signal-to-background ratios (SBRs), the ratios of diffraction peak integrated intensity over its background intensity, are desired for a neutron diffractometer to acquire good statistics for diffraction pattern measurements and subsequent data analysis. For a given detector, while the diffraction peak signals primarily depend on the characteristics of neutron beam and sample coherent scattering, the background largely originates from the sample incoherent scattering and the scattering from the instrument space. In this work, we investigated the effect of collimation on neutron diffraction SBRs of Si powder measurements using one high-angle area detector bank coupled with six different collimation configurations in a large and complex instrument space at the engineering materials diffractometer VULCAN, SNS, ORNL. The results revealed that the diffraction SBRs can be significantly improved by a proper coarse collimator that leaves no gap between the detector and the collimator, and the improvement of SBRs by a fine radial collimator was remarkable with a proper coarse collimator in place but not distinguishable without one. It was also found that the diffraction SBRs were not effectively improved by adding neutron absorbing element boron to the fine radial collimator body, which indicates that either the absorption of secondary scattered neutrons by the added boron is insignificant or the collimator base material (resin and ABS) alone attenuates background scattering sufficiently. These findings could serve as a useful reference for diffractometer developers and/or operators to optimize their collimation to achieve higher diffraction SBRs.

Yu, Dunji↗
DOE OSTI2025

Ultra-sensitive radon assay using an electrostatic chamber in a recirculating system

Rare event searches such as neutrinoless double beta decay and Weakly Interacting Massive Particle detection require ultra-low background detectors. Radon contamination is a significant challenge for these experiments, which employ highly sensitive radon assay techniques to identify and select low-emission materials. This work presents the development of ultra-sensitive electrostatic chamber (ESC) instruments designed to measure radon emanation in a recirculating gas loop, for future lower background experiments. Unlike traditional methods that separate emanation and detection steps, this system allows continuous radon transport and detection. This is made possible with a custom-built recirculation pump. A Python-based analysis framework, PyDAn, was developed to process and fit time-dependent radon decay data. Radon emanation rates are given for various materials measured with this instrument. A radon source of known activity provides an absolute calibration, enabling statistically-limited minimal detectable activities of 20 uBq. These devices are powerful tools for screening materials in the development of low-background particle physics experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Combining Reclaimed PET with Bio-Based Monomers Enables Plastics Upcycling

Less than 30% of PET plastic is recycled in the United States. The low reclamation rate may be due to mechanical recycling accounting for the majority of commercial PET recycling. Mechanical recycling yields a lower-quality recycled plastic than the process of chemically recycling back to the monomer phase, which can be energetically and economically expensive. In this work, recently published in Joule, reclaimed PET bottles are chemically recycled and converted into higher-value fiberglass-reinforced plastics (FRPs).This presentation will focus on the supply-chain level energy and greenhouse gas emissions intensities associated with this novel upcycling route. The Materials Flows through Industry supply chain analysis tool, developed at NREL, is used to estimate these impacts. Depending on the extent and speed of adoption, this strategy for plastic upcycling could lead to significant energy usage and emissions reductions over the traditional FRP supply chain. Overall, this approach may provide an economic incentive for plastics recycling and renewable feedstock use through the creation of higher-value FRPs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

A Unified Tracer Analysis of DESI DR2 Baryon Acoustic Oscillations

We improve upon previous efforts to optimally combine overlapping galaxy samples in the DESI baryon acoustic oscillation analysis. By weighting each galaxy by its linear bias, overlapping galaxies are combined into a single, unified catalog, naturally avoiding double counting of cosmic volume and including all auto- and cross- information at the catalog level. Improvements over the previous effort include the addition of QSO out to $z=1.6$ to account for all overlapping DR2 tracers and redshift-dependent bias treatment to improve reconstruction. We report distance measurements using this unified tracer, and find them to be highly consistent with the baseline DR2 BAO analysis. We also test for tracer-dependent systematics within the DESI data, and find no evidence of tracer-dependent systematics within $0.8

Sanders, N. [Ohio U., Athens] (ORCID:0009000800202↗
DOE OSTI2026

Assessing plasma face component thermal response to rotating 3D magnetic fields for SPARC tokamak

Thermal response simulations of plasma-facing components (PFCs) in the SPARC tokamak, performed with the HEAT code, show that three-dimensional (3D) heat loads resulting from stationary n=1 perturbations require highly radiative scenarios, with up to 95% of the power crossing the separatrix (P SOL ) being radiated, to maintain PFC temperatures within acceptable operational limits, whereas the application of slowly rotating 3D fields substantially reduces the thermal loads. The HEAT module, developed to predict heat loads from non-axisymmetric plasmas, is extended to model time-dependent heat flux patterns generated by rotating 3D fields, and a comprehensive thermal analysis is performed on PFCs subjected to both the maximum and minimum power loads, as well as to rotating heat flux distributions, to evaluate the temperature evolution for varying perturbation amplitudes and rotation frequencies. The extension of this analysis to 3D fields with toroidal mode number n=2 shows that this configuration leads to weaker localized heat flux peaks relative to the n=1 case, enabling safe operation with less than 80% of the power radiated when static 3D fields of low amplitude are applied, while using slowly rotating fields at higher amplitudes. These results indicate that n=2 perturbations are generally less detrimental to divertor power exhaust, emphasizing the strong dependence of divertor power exhaust on the characteristics of the applied 3D fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Velocity Dependence of Rate‐And‐State Friction in Granular Fault Gouge and Implications for Slow‐Slip Events

Abstract The standard rate‐and‐state friction (RSF) has extensively captured frictional behaviors, but it fails to explain the velocity dependence of frictional stability transition and widespread slow‐slip events (SSEs) in experiments and nature adequately. An alternative microphysical Chen‐Niemeijer‐Spiers (CNS) model can well describe the velocity dependence of frictional behaviors of granular gouges. Using the original CNS model, standard RSF parameters can be quantified microphysically. However, some micro‐parameters are not easy to estimate quantitatively, making it difficult to extrapolate to natural and experimental conditions. Here, we simplify the microphysically‐derived RSF parameters including direct effect a , evolution effect b , and critical slip distance D c , as well as equivalent values ( a eq , b eq , and D eq ). The simplified friction parameters directly illustrate their velocity dependence, namely the essentially constant a , a eq , and D c , negatively velocity‐dependent b and b eq , as well as varying D eq for different laws. They are roughly consistent with experimental results in various fault gouges. A modified CNS model is further derived from the original CNS model, establishing a direct link between the standard RSF and CNS models. The modified CNS model exhibits virtually identical frictional behaviors to the original CNS, but differs from the standard RSF at large velocity perturbations. Moreover, the linearized stability analysis indicates that the critical stiffness for the modified CNS model is velocity‐dependent. Compared with the standard RSF, the modified CNS model not only explains the velocity dependence of frictional stability transition, but also exhibits a more gradual transition for SSEs with a broader range of stiffness ratios.

Geochemistry & Geophysics↗
DOE OSTI2020

Localized Strain Analysis of Ce- and Mg-Treated Cast Iron under Uniaxial Compression

Cast iron exhibits a wide range of mechanical properties, depending on its microstructural features. The microstructure of cast iron consists of several microconstituents with different elastic-plastic behavior, making the strain non-uniform across the bulk material. To understand the individual effects of these microconstituents on the overall mechanical behavior, local strain analysis using digital image correlation analysis was carried out. Samples with two different compositions (varying cerium, magnesium and silicon) were processed at different solidification velocities in a Bridgman furnace. Sections of the directionally solidified samples were loaded under uniaxial compression to measure global and local strain behavior. Despite the variability of the microstructure, the stress–strain curves obtained by digital image correlation (DIC) were found to react in a well-controlled way to changes in solidification velocity. It was observed that high-strain failure (greater than 15%) was accompanied by local straining of the softer ferritic phase, but during low-strain failure, local straining was not prominent. Higher nodularities, due to higher solidification velocities, raised the compressive strength without affecting the toughness significantly. Higher percentages of carbides led to higher compressive strengths with corresponding losses in ductility. The continuity of the matrix was also found to play an important role in the behavior during compression.

ductile failure↗
DOE OSTI2021

Cyber-Power Co-Simulation for End-to-End Synchrophasor Network Analysis and Applications

The resiliency, reliability and security of the next generation cyber-power smart grid depend upon efficiently leveraging advanced communication and computing technologies. Also, developing real-time data-driven applications is critical to enable wide-area monitoring and control of the cyber-power grid given high-resolution data from Phasor Measurement Units (PMUs). North American Synchrophasor Initiative Network (NASPlnet) provides guidance for PMU data exchanges. With the advancement in networking and grid operation, it is necessary to evaluate the performance of different data flow architectures suggested by NASPInet and analyze the impact on applications. Therefore, we need a cyber-power co-simulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents an end-to-end automated and user-driven cyber-power co-simulation using NS3 to model communication networks, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application utilizing PMU data in an IEEE 39 bus test system is presented using this cosimulation testbed.

Mustafa, Hussain M.↗
DOE OSTI2022

Comparative analysis of the sensitivity of nanometallic thin film thermometers

Thin film platinum resistive thermometers are conventionally applied for resistance thermometry techniques due to their stability and proven measurement accuracy. Depending upon the required thermometer thickness and temperature measurement, however, performance benefits can be realized through the application of alternative nanometallic thin films. Herein, a comparative experimental analysis is provided on the performance of nanometallic thin film thermometers most relevant to microelectronics and thermal sensing applications: Al, Au, Cu, and Pt. Sensitivity is assessed through the temperature coefficient of resistance, measured over a range of 10–300 K for thicknesses nominally spanning 25–200 nm. In this work, the interplay of electron scattering sources, which give rise to the temperature-dependent TCR properties for each metal, are analyzed in the framework of a Mayadas–Shatzkes based model. Despite the prevalence of evaporated Pt thin film thermometers, Au and Cu films fabricated in a similar manner may provide enhanced sensitivity depending upon thickness. These results may serve as a guide as the movement toward smaller measurement platforms necessitates the use of smaller, thinner metallic resistance thermometers.

36 MATERIALS SCIENCE↗