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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Neutron diffraction measurements and micromechanical modelling of temperature-dependent variations in TATB lattice parameters

Triaminotrinitrobenzene (TATB) is a highly anisotropic molecular crystal used in several plastic-bonded explosive (PBX) formulations. TATB-based explosives exhibit irreversible volume expansion (“ratchet growth”) when thermally cycled. A theoretical understanding of the relationship between anisotropy of the crystal, crystal orientation distribution (texture) of polycrystalline aggregates, and the intergranular interactions leading to this irreversible growth is necessary to accurately develop physics-based predictive models for TATB-based PBXs under various thermal environments. In this work, TATB lattice parameters were measured using neutron diffraction during thermal cycling of loose powder and a pressed pellet. The measured lattice parameters help clarify conflicting reports in the literature as these new results are more consistent with one set of previous results than another. The lattice parameters of pressed TATB were also measured as a function of temperature, showing some differences from the powder. This data is used along with anisotropic single-crystal stiffness moduli reported in the literature to model the nominal stresses associated with intergranular constraints during thermal expansion. The texture of both specimens were characterized and the pressed pellet exhibits preferential orientation of (001) poles along the pressing direction, whereas no preferred orientation was found for the loose powder. Lastly, thermal strains for single-crystal TATB computed from lattice parameter data for the powder is input to a self-consistent micromechanical model, which predicts the lattice parameters of the constrained TATB crystals within the pellet. The agreement of these model results with the diffraction data obtained from the pellet is discussed along with future directions of research.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Experimental evidence for chemo-mechanical coupling during carbon mineralization in ultramafic rocks

It is known that storing carbon dioxide in the subsurface as carbonate minerals has the benefit of long-term stability and immobility. Ultramafic rock formations have been suggested as a potential reservoir for this type of storage due to the availability of cations to react with dissolved carbon dioxide and the fast reaction rates associated with minerals common in ultramafic formations; however, the rapid reactions have the potential to couple with the mechanical and hydraulic behavior of the rocks and little is known about the extent and mechanisms of this coupling. In this study, we argue that the dissolution of primary minerals and the precipitation of secondary minerals along pre-existing fractures in samples lead to reductions in both the apparent Young's modulus and shear strength of aggregates, accompanied by reduction in permeability. Hydrostatic and triaxial deformation experiments were run on dunite samples saturated with de-ionized water and carbon dioxide-rich solutions while stress, strain, permeability and pore fluid chemistry were monitored. Sample microstructures were examined after reaction and deformation using scanning electron microscopy (SEM). The results show that channelized dissolution and carbonate mineral precipitation in the samples saturated with carbon dioxide-rich solutions modify the structure of grain boundaries, leading to the observed reductions in stiffness, strength and permeability. A geochemical model was run to help interpret fluid chemical data, and we find that the apparent reaction rates in our experiments are faster than rates calculated from powder reactors, suggesting mechanically enhanced reaction rates. In conclusion, we find that chemo-mechanical coupling during carbon mineralization in dunites leads to substantial modification of mechanical and hydraulic behavior that needs to be accounted for in future modeling efforts of in situ carbon mineralization projects.

58 GEOSCIENCES↗
DOE OSTI2023

3-O-Methyltolcapone and Its Lipophilic Analogues Are Potent Inhibitors of Transthyretin Amyloidogenesis with High Permeability and Low Toxicity

Transthyretin (TTR) is an amyloidogenic homotetramer involved in the transport of thyroxine in blood and cerebrospinal fluid. To date, more than 130 TTR point mutations are known to destabilise the TTR tetramer, leading to its extracellular pathological aggregation accumulating in several organs, such as heart, peripheral and autonomic nerves, and leptomeninges. Tolcapone is an FDA-approved drug for Parkinson’s disease that has been repurposed as a TTR stabiliser. We characterised 3-O-methyltolcapone and two newly synthesized lipophilic analogues, which are expected to be protected from the metabolic glucuronidation that is responsible for the lability of tolcapone in the organism. Immunoblotting assays indicated the high degree of TTR stabilisation, coupled with binding selectivity towards TTR in diluted plasma of 3-O-methyltolcapone and its lipophilic analogues. Furthermore, in vitro toxicity data showed their several-fold improved neuronal and hepatic safety compared to tolcapone. Calorimetric and structural data showed that both T4 binding sites of TTR are occupied by 3-O-methyltolcapone and its lipophilic analogs, consistent with an effective TTR tetramer stabilisation. Moreover, in vitro permeability studies showed that the three compounds can effectively cross the blood-brain barrier, which is a prerequisite for the inhibition of TTR amyloidogenesis in the cerebrospinal fluid. Our data demonstrate the relevance of 3-O-methyltolcapone and its lipophilic analogs as potent inhibitors of TTR amyloidogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

A Life Cycle Analysis of Refinery Fuel Products Air Emissions Using Refinery Emissions Inventory Data

With the transportation sector being a major source of air pollutant emissions, this study seeks to evaluate criteria pollutant emissions associated with the use of petroleum fuels in vehicles using the GREET® (Greenhouse gases, Regulated Emissions, and Energy use in Transportation) well-to-wheel model. The life cycle of petroleum fuels includes the major stages of crude recovery, crude transportation, crude refining, fuel distribution and fuel combustion (vehicle operation). This study focuses on quantifying refinery emissions, in terms of both refinery throughput and various refinery fuel products, by matching a refinery emissions inventory dataset with refinery operation information, at various levels (national, regional, facility, and process unit). The refinery emissions in terms refinery throughput (per refinery crude input, in g/mmbtu crude) are developed at a regional level for various Petroleum Administration for Defense Districts (PADD), and also aggregated at the national level. To allocate refinery emissions to refinery products, a methodology is developed using a refinery operation optimization Linear Programming (LP) model for individual refineries. The results from individual refinery facilities are then aggregated to obtain statistical national average (capacity weighted) emissions for each product. Because refineries vary by complexity of operation, configuration, crude quality, and product slate, the derived emissions demonstrate large variation for each product and per unit of crude input. Relative to previous estimates used in the GREET model, the present research shows reductions in refinery (and life cycle) emissions for most criteria pollutants. The reduction is especially significant for sulfur dioxide (SOx) emissions.

Allocation↗
DOE OSTI2023

Aggregate residential demand flexibility behavior: A novel assessment framework

Residential demand flexibility (DF) could save the U.S. electric grid up to 10 GW of peak demand while supporting increased amounts of renewable generation. However, less than 40% of the estimated DF peak reduction capacity is currently realized, and less than 8% of American households are enrolled. These low participation rates are combined with high rates of "overriding" a DF event and eventual opt-outs among enrolled customers. There is still not a comprehensive understanding of the drivers of DF participation and occupant interaction with DF program signals. We, therefore, present a novel survey processing framework to assess occupant DF-relevant behavior from the American Time Use Survey (ATUS). Using the framework, we summarize both the extensive and intensive behavior of more than 200,000 ATUS respondents (2003-2018 data) and provide insights on the DF-relevant behavior of residential occupants, which is generally overlooked in the literature. Here we use the framework to identify the activity priorities of residential occupants in the United States during different DF-relevant periods (critical peak, peak, and off-peak). These preferred activities capture overlooked routine behaviors that could be barriers to DF participation, if ignored, and might explain the high levels of overrides often exhibited by participants of demand response.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)↗
DOE OSTI2015

SPECTROSCOPIC INFRARED EXTINCTION MAPPING AS A PROBE OF GRAIN GROWTH IN IRDCs

We present spectroscopic tests of MIR to FIR extinction laws in IRDC G028.36+00.07, a potential site of massive star and star cluster formation. Lim and Tan developed methods of FIR extinction mapping of this source using Spitzer-MIPS 24 μm and Herschel-PACS 70 μm images, and by comparing to MIR Spitzer-IRAC 3–8 μm extinction maps, found tentative evidence for grain growth in the highest mass surface density regions. Here we present results of spectroscopic infrared extinction mapping using Spitzer-IRS (14–38 μm) data of the same Infrared dark cloud (IRDC). These methods allow us to first measure the SED of the diffuse Galactic interstellar medium that is in the foreground of the IRDC. We then carry out our primary investigation of measuring the MIR to FIR opacity law and searching for potential variations as a function of mass surface density within the IRDC. We find relatively flat, featureless MIR–FIR opacity laws that lack the ∼12 and ∼35 μm features associated with the thick water ice mantle models of Ossenkopf and Henning. Their thin ice mantle models and the coagulating aggregate dust models of Ormel et al. are a generally better match to the observed opacity laws. We also find evidence for generally flatter MIR to FIR extinction laws as mass surface density increases, strengthening the evidence for grain and ice mantle growth in higher density regions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Plutonium Retention by Crystalline Silicotitanate under Hyperalkaline Conditions Relevant to Tank-Side Cesium-Removal at the Hanford Site

Crystalline silicotitanate (CST) is used in Hanford’s Tank-Side Cesium-Removal (TSCR) process to selectively remove Cs-137 from highly caustic, nitrate-rich tank supernatants. Recent testing with actual waste samples suggests that CST can also retain measurable plutonium (Pu), which could affect radiological classification and disposal pathways for spent CST. To quantify this behavior, Pu partitioning to CST was studied under Hanford-relevant conditions using batch-contact experiments in a representative simulant (2 M NaNO3, 0.7 M NaOH). Isotherm data were measured and distribution ratios calculated, with Cs+ uptake used as benchmark. Under low-carbonate conditions, Pu was retained strongly by CST in systems initially contacted with either PuO2 nanoparticles (Pu(IV)) or aqueous Pu(VI), with distribution ratios of ~2,200–3,700 mL/g, generally exceeding those for Cs+ (~400–1,000 mL/g). Increasing carbonate concentration strongly reduced PuO2 nanoparticle retention; at [Na2CO3] = 1 M, distribution ratios decreased by up to one order of magnitude to roughly 100–300 mL/g. Electron microscopy suggests that Pu retention involves a combination of mechanisms such as PuO2 NP aggregation induced by CST leachate components, and association with CST bead surfaces.

Neumann, J.↗
DOE OSTI2015

Probabilistic Swinging Door Algorithm as Applied to Photovoltaic Power Ramping Event Detection

Photovoltaic (PV) power generation experiences power ramping events due to cloud interference. Depending on the extent of PV aggregation and local grid features, such power variability can be constructive or destructive to measures of uncertainty regarding renewable power generation; however, it directly influences contingency planning, production costs, and the overall reliable operation of power systems. For enhanced power system flexibility, and to help mitigate the negative impacts of power ramping, it is desirable to analyze events in a probabilistic fashion so degrees of beliefs concerning system states and forecastability are better captured and uncertainty is explicitly quantified. A probabilistic swinging door algorithm is developed and presented in this paper. It is then applied to a solar data set of PV power generation. The probabilistic swinging door algorithm builds on results from the original swinging door algorithm, first used for data compression in trend logging, and it is described by two uncertain parameters: (i) e, the threshold sensitivity to a given ramp, and (ii) s, the residual of the piecewise linear ramps. These two parameters determine the distribution of ramps and capture the uncertainty in PV power generation.

14 SOLAR ENERGY↗
DOE OSTI2017

Concrete Structural Health Monitoring in Nuclear Power Plants

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Health monitoring of concrete structures is performed in order to understand the current condition of a structure based on heterogeneous measurements and then produce high confidence actionable information regarding structural integrity; this information can then be used to support operational and maintenance decisions. The paper describes a framework of research activities for the health monitoring of nuclear power plant concrete structures. The proposed framework consists of four elements: health monitoring, data analytics, uncertainty quantification, and prognosis. The goal of this framework is to enable plant operators to make risk-informed decisions on structural integrity, remaining useful life, and performance of concrete structures across the nuclear fleet. Among several concrete degradations, the research focuses on the degradation caused by the Alkali-Silica Reaction (ASR). ASR is a chemical reaction that in presence of sufficient moisture forms a gel that increases in volume and exerts an expansive pressure inside the material causing micro- to macro-cracks. The paper also presents development of controlled concrete samples with reactive aggregates to cause ASR degradation and application of different non-destructive evaluation techniques to detect the damage caused by ASR. Initial results are presented in the paper along with potential path forward.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Parallel storage system with burst buffer appliance for storage of partitioned key-value store across a plurality of storage tiers

Parallel storage systems are provided with a burst buffer appliance for storage of a partitioned key-value store across a plurality of storage tiers. The burst buffer appliance is configured to store key-value data on first and second storage tiers comprising respective disjoint subsets of storage. One or more servers in the partitioned key-value store provide (i) an interface between one or more local key-value stores and one or more additional storage architectures, and/or (ii) a key value interface that provides access to at least one hardware key-value store. The local key-values are optionally sorted both locally by the local store and globally by the overall MDHIM framework. The local and global sorting can be leveraged to provide batch input/output (IO) operations that aggregate multiple requests into batch operations on one or more sorted ranges.

Bent, John M.↗
DOE OSTI2017

Concrete structural health monitoring in nuclear power plants - 212

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on existing code margins of safety. Health monitoring of concrete structures is performed in order to understand the current condition of a structure based on heterogeneous measurements and produce high-confidence actionable information regarding structural integrity. This information can be used to support operational and maintenance decisions. This paper describes a framework of research activities for health monitoring of nuclear power plant concrete structures. The proposed framework consists of four elements: (1) health monitoring, (2) data analytics, (3) uncertainty quantification, and (4) prognosis. The goal of this framework is to enable plant operators to make risk-informed decisions about structural integrity, remaining useful life, and performance of concrete structures across the nuclear fleet. Among several concrete degradations, research focuses on degradation caused by the alkali-silica reaction (ASR). ASR is a chemical reaction that, in the presence of sufficient moisture, forms a gel that increases in volume and exerts an expansive pressure inside the material, thus causing micro to macro-cracks. This paper also presents development of controlled concrete samples with reactive aggregates to cause ASR degradation and application of different non-destructive evaluation techniques to detect the damage caused by ASR. Initial results are presented in the paper along with a potential path forward. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

National population mapping from sparse survey data: A hierarchical Bayesian modeling framework to account for uncertainty

Population estimates are critical for government services, development projects, and public health campaigns. Such data are typically obtained through a national population and housing census. However, population estimates can quickly become inaccurate in localized areas, particularly where migration or displacement has occurred. Some conflict-affected and resource-poor countries have not conducted a census in over 10 y. We developed a hierarchical Bayesian model to estimate population numbers in small areas based on enumeration data from sample areas and nationwide information about administrative boundaries, building locations, settlement types, and other factors related to population density. We demonstrated this model by estimating population sizes in every 10- m grid cell in Nigeria with national coverage. These gridded population estimates and areal population totals derived from them are accompanied by estimates of uncertainty based on Bayesian posterior probabilities. The model had an overall error rate of 67 people per hectare (mean of absolute residuals) or 43% (using scaled residuals) for predictions in out-of-sample survey areas (approximately 3 ha each), with increased precision expected for aggregated population totals in larger areas. This statistical approach represents a significant step toward estimating populations at high resolution with national coverage in the absence of a complete and recent census, while also providing reliable estimates of uncertainty to support informed decision making.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2014

Investigation of iodine dopant amount effects on dye-sensitized hierarchically structured ZnO solar cells

Highlights: • The effect of I amount on the photovoltaic performance was investigated. • The enhancement in η of ZnO:I DSSCs was from 38% to 77% compared with ZnO DSSCs. • Appropriate I doping enhanced light harness and inhibited charge recombination. - Abstract: We prepare a series of iodine doped zinc oxide monodisperse aggregates (ZnO:I) with various iodine concentrations as the photoanodes of dye-sensitized solar cells (DSSCs) to study iodine dopant amount-dependent photovoltaic performance. The iodine-doped DSSCs achieve overall conversion efficiency (η) of 3.6–4.6%. The enhancement in η of ZnO:I DSSCs is from 38% to 77% as compared to undoped ZnO DSSCs. The significantly enhanced η of DSSCs is found to be correlated with iodine dopant amount. The optimum iodine dopant amount is determined to be 2.3 wt% by X-ray photoelectron spectroscopy. Furthermore, the incident photon to current conversion efficiency and electrochemical impedance spectroscopy data reveal a systematic correlation between photovoltaic properties and the iodine dopant amount. The enhancement of open-circuit potential of ZnO:I cells is arising from negative shift of their flat-band potential, as demonstrated by Mott–Schottky measurement.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Synthesizing Stellar Populations in South Pole Telescope Galaxy Clusters. I. Ages of Quiescent Member Galaxies at 0.3 < $\textit{z}$ < 1.4

Using stellar population synthesis models to infer star formation histories (SFHs), we analyze photometry and spectroscopy of a large sample of quiescent galaxies that are members of Sunyaev–Zel'dovich (SZ)-selected galaxy clusters across a wide range of redshifts. We calculate stellar masses and mass-weighted ages for 837 quiescent cluster members at 0.3 < $\textit{z}$ < 1.4 using rest-frame optical spectra and the Python-based Prospector framework, from 61 clusters in the SPT-GMOS Spectroscopic Survey (0.3 < $\textit{z}$ < 0.9) and three clusters in the SPT Hi-z cluster sample (1.25 < $\textit{z}$ < 1.4). We analyze spectra of subpopulations divided into bins of redshift, stellar mass, cluster mass, and velocity-radius phase-space location, as well as by creating composite spectra of quiescent member galaxies. We find that quiescent galaxies in our data set sample a diversity of SFHs, with a median formation redshift (corresponding to the lookback time from the redshift of observation to when a galaxy forms 50% of its mass, $t_{50}$) of $\textit{z}$ = 2.8 ± 0.5, which is similar to or marginally higher than that of massive quiescent field and cluster galaxy studies. We also report median age–stellar mass relations for the full sample (age of the universe at $t_{50}$ (Gyr) = 2.52 (±0.04)–1.66 (±0.12) log$_{10}(M/10^{11}M_⊙$)) and recover downsizing trends across stellar mass; we find that massive galaxies in our cluster sample form on aggregate ~0.75 Gyr earlier than lower-mass galaxies. We also find marginally steeper age–mass relations at high redshifts, and report a bigger difference in formation redshifts across stellar mass for fixed environment, relative to formation redshifts across environment for fixed stellar mass.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Light-regulated synthesis of cyclic-di-GMP by a bidomain construct of the cyanobacteriochrome Tlr0924 (SesA) without stable dimerization

Here, phytochromes and cyanobacteriochromes (CBCRs) use double bond photoisomerization of their linear tetrapyrrole (bilin) chromophores within cGMP-specific phosphodiesterases/Adenylyl cyclases/FhlA (GAF) domain-containing photosensory modules to regulate activity of C-terminal output domains. CBCRs exhibit much more diverse photocycles than phytochromes, and are often found in large modular proteins such as Tlr0924 (SesA), one of three blue light regulators of cell aggregation in the cyanobacterium Thermosynechococcus elongatus . Tlr0924 contains a single bilin-binding GAF domain adjacent to a C-terminal diguanylate cyclase (GGDEF) domain whose catalytic activity requires formation of a dimeric transition state presumably supported by a multi-domain extension at its N-terminus. To probe the structural basis of light-mediated signal propagation from the photosensory input domain to a signaling output domain for a representative CBCR, these studies explore the properties of a bidomain GAF-GGDEF construct of Tlr0924 (Tlr0924Δ) that retains light-regulated diguanylate cyclase activity. Surprisingly, CD spectroscopy and size exclusion chromatography data do not support formation of stable dimers in the either the blue-absorbing 15Z P b dark state or the green-absorbing 15E P g photoproduct state of Tlr0924Δ. Analysis of variants containing site-specific mutations reveals that proper signal transmission requires both chromophorylation of the GAF domain and individual residues within the amphipathic linker region between GAF and GGDEF domains. Based on these data, we propose a model in which bilin binding and light signals are propagated from the GAF domain via the linker region to alter the equilibrium and interconversion dynamics between active and inactive conformations of the GGDEF domain to favor or disfavor formation of catalytic competent dimers.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

AbacusSummit Cleaned Halo Catalogs

This is a data release from the AbacusSummit suite of cosmological N-body simulations. It contains dark matter halo catalogs and particle samples from those halos. The halo catalogs have been augmented (cleaned) using halo merger tree information. Descriptions of AbacusSummit, the cleaned halo catalogs, and instructions for manipulating these catalogs can be found at the following URL: abacussummit.readthedocs.io/ The halo catalog cleaning is structured as a set of auxiliary files that are ingested by the reader code at runtime. But this release contains both the original catalogs and the auxiliary files, thus forming a self-contained dataset. The files in this release are aggregated by redshift. We define sets of simulations (like all c000 sims or all hugebase sims), and then store one redshift from all simulations per tarball. This is designed to support the use-case where a user wants to analyze multiple simulations at a certain redshift.

79 ASTRONOMY AND ASTROPHYSICS↗