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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Scalable Quantum Cryptography Network for Protected Automation Communication (Final Report)

This is the final report for a CEDS-funded project aimed at developing a new quantum technology for securing utility communication networks used to control and monitor electrical grid equipment. Securing these control networks represents a unique challenge as the performance of the security solution has a direct impact on the stability and reliability of the electrical grid. Traditional, software-based solutions - developed for information networks - are not suitable for utility control networks because they introduce latency, require burdensome maintenance and upgrades, are often incompatible with legacy equipment, and introduce operational complexity that reduces grid reliability. Consequently, many U.S. utilities do not use existing solutions and, instead, protect their critical control networks through the careful isolation and obscuration of their networked equipment. With more utilities embracing grid automation, the attack surface that utilities must defend from hackers has grown to an unmanageable size. To address this situation, Qubitekk and its partners proposed and developed a hardware-based solution that can secure critical control networks without negatively impacting grid performance. This new solution is based on quantum key distribution (QKD) techniques that guarantee secure key generation and distribution across a utility control network. Through deployment and field testing of a prototype QKD system, we have shown that this solution delivers long-term network security, is technically feasible to implement and maintain on a utility’s distribution substation network and does not negatively impact grid operations. In addition, the project has identified and solved key challenges associated with generating, transmitting, and measuring coherent photonic quantum states on a real-world fiber optic network. These additional findings are playing a critical role in advancing quantum networks for quantum computing applications. An overview of the QKD prototype development effort, field testing activities and results, and additional findings relevant to emerging quantum networks are presented in this report.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Multi-Physics Simulations of Molten Chloride Fast Reactor using Nek5000 and PROTEUS-NODAL

This report documents the FY20 work to demonstrate a specific multi-physics capability within NEAMS tools to model molten chloride fast reactors (MCFR). Specifically, the CFD code Nek5000 and the neutronics code PROTEUS-NODAL were coupled off-line to calculate the delayed neutron precursor distribution within the flowing fuel salts in an MCFR core. An MCFR benchmark problem and a 3D test problem based on a conceptual MSR design were successfully solved through the coupled simulation of Nek5000 and PROTEUS-NODAL. In the coupled simulations for these test problems, Nek5000 provided high-quality flow field information, and PROTEUS-NODAL performed the neutron diffusion calculation along with the precursor drift model. The impact of precursor drift on the core status was also investigated. Additionally, the precursor drift model implemented in PROTEUS-NODAL was verified by making use of the reference precursor distribution generated from Nek5000. Results of these test problems suggest that the multi-physics capability of Nek5000 and PROTEUS-NODAL was properly developed for tracking delayed neutron precursor drift.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Evaluating the impact of wildfire smoke on solar photovoltaic production

There are growing needs to understand how extreme weather events impact the electrical grid. Renewable energy sources such as solar photovoltaics are expanding in use to help sustainably meet electricity demands. Wildfires and, notably, the widespread smoke resulting from them, are one such extreme event that can impair the performance of solar photovoltaics. However, isolating the impact that smoke has on photovoltaic energy production, separate from ambient conditions, can be difficult. In this work, we seek to understand and quantify the impacts of wildfire smoke on solar photovoltaic production within the Western United States. Our analysis focuses on the construction of a random forest regression model to predict overall solar photovoltaic production. The model is used to separate and quantify the impacts of wildfire smoke in particular. To do so, we fuse historical weather, solar photovoltaic energy production, and PM2.5 particulate matter (primary smoke pollutant) data to train and test our model. The additional weather data allows us to capture interactions between wildfire smoke and other ambient conditions, as well as to create a more powerful predictive model capable of better quantifying the impacts of wildfire smoke on its own. We find that solar PV energy production decreases 8.3% on average during high smoke days at PV sites as compared to similar conditions without smoke present. Finally, this work allows us to improve our understanding of the potential impact on photovoltaic-based energy production estimates due to wildfire events and can help inform grid and operational planning as solar photovoltaic penetration levels continue to grow.

14 SOLAR ENERGY↗
DOE OSTI2022

Niowave Flow Testing of the High Power Converter - FY 21

Design work for a 100 kW converter to produce a neutron flux via electron impact on a flowing stream of liquid metal lead-bismuth (LBE) was conducted in FY20. In FY21, the focus shifted to a 20 kW converter which was designed in collaboration with Niowave engineers. A flow visualization model is needed to validate model results for the 20 kW converter and ensure adequate coolant flow over containment structures. This work highlights the mockup that was made with quartz side plates by LANL.

42 ENGINEERING↗
DOE OSTI2026

Impact of Molten Gallium on the Microstructure and Corrosion Behavior of Aluminum and Uranium-Aluminum Alloys for Used Nuclear Fuel Reprocessing

Test reactors around the world utilize highly enriched uranium fuel to achieve high neutron fluxes for materials testing. Once spent, the remaining uranium is a valuable resource for subsequent fuel fabrication. However, some of these test reactor cores consist of curved plate-type fuel elements, fabricated using aluminum alloy 6061 (AA6061) cladding to encapsulate a uranium-aluminum alloy (UAlx) fuel matrix. These assemblies require non-standard reprocessing approaches for uranium recovery, as aluminum dissolves readily in acidic solutions, generating large volumes of waste and complicating downstream chemical separations. In this work, we investigate a novel chemical decladding strategy based on the interaction between AA6061/UAlx and molten gallium (Ga). Ga is known to induce severe degradation of aluminum metal through liquid metal embrittlement (LME), even at relatively low Ga concentrations. By penetrating the aluminum crystal lattice, Ga disrupts grain cohesion and facilitates fracture or dissolution of the aluminum matrix. Thermodynamic analysis of the Al–Ga binary phase diagram suggests that Ga may offer a viable pathway to selectively weaken or dissolve the AA6061 cladding, and potentially the aluminum component of the UAlx fuel matrix within. To this end, parametric experiments were performed at 50 °C and 100 °C across a range of Al–Ga atomic fractions. At lower Al fractions, the AA6061 was completely molten after 2 hours of exposure to the Ga metal. In contrast, samples with higher Al fractions (0.9 Al, 0.1 Ga) contained residual solids after 2 hours, which were characterized by microstructural examination using electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM). These Al-Ga compositions were also evaluated using FactSage thermodynamic modeling to further elucidate the relationship between phase diagram behavior and LME.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Challenges of Interpreting and Applying New IPC-J-STD-001 Cleanliness Standards in High-Reliability Applications

The electronics industry has rapidly and widely embraced the replacement of ROSE testing with an SIR-focused approach to testing for certification of a qualified manufacturing plan. These new cleanliness documentation standards, housed in IPC J-STD-001 Rev. H, have just begun to impact electronics manufacturers as design and production teams work through how to meet them. This research focuses on the particular challenges of applying these new standards in high-reliability product applications, through the lens of interpreting SIR test results and what they mean for process capability, repeatability and diagnosing a need for process changes. The experiments examined a variety of factors that influence SIR results and suggest areas where SIR test plans can be greatly improved.

Capen, William↗
DOE OSTI2023

Electrochemical Characterization of Molten Salt Chemistry During Atmospheric Ingressions

This report describes the salt chemistry and sedimentation studies that were completed in FY23 as part of the Pyrochemical Fuel Cycles – ANL project. The primary objective of these activities was to employ electrochemical methods in order to quantify and gain insights into the reaction mechanisms associated with the interaction of O2 and moisture impurities with the molten chloride salts used for the pyrochemical processing of nuclear materials. If not monitored and controlled, the ingression of these atmospheric impurities can lead to changes in the salt redox conditions and initiate the formation of oxide particles, potentially resulting in operational and safeguards challenges. By elucidating the mechanisms underlying the formation of oxide particles, we can effectively monitor the conditions of the salt and design systems to mitigate the influence of atmospheric O2 and H2O. To achieve these goals, we designed a test system that allowed for precisely controlled gas ingressions into the molten salt vessel. This system included on-line monitoring provided by electrochemical probes that enable near real-time measurements of the salt conditions throughout the course of the experiment. Using this system, we systematically varied experimental conditions, including O2/Ar flow rates and O2 concentrations, to comprehensively understand their impact on solid particle formation. We also used a particle size and shape analyzer to characterize the particles that were generated. Tests in FY23 concentrated on the formation of CeO2 particles, but we also prepared a separate apparatus targeting UO2 particles for use in FY24. We additionally conducted extensive modeling activities in support of this work. This included multiphysics simulations of the gas ingressions along with the development of a machine learning workflow to enable accelerated molecular dynamics modeling of the molten salt chemistry of LiCl-KCl-UCl3. The combination of experimental and modeling tools has allowed us to begin to get a more complete understanding of the reactions that occur when atmospheric ingressions occur in pyroprocessing systems.

Guo, Jicheng↗
DOE OSTI2025

Virocell Necromass Provides Limited Plant Nitrogen and Elicits Rhizosphere Metabolites That Affect Phage Dynamics

Bacteriophages impact soil bacteria through lysis, altering the availability of organic carbon and plant nutrients. However, the magnitude of nutrient uptake by plants from lysed bacteria remains unknown, partly because this process is challenging to investigate in the field. In this study, we extend ecosystem fabrication (EcoFAB 2.0) approaches to study plant-bacteria-phage interactions by comparing the impact of virocell (phage-lysed) and uninfected 15 N-labelled bacterial necromass on plant nitrogen acquisition and rhizosphere exometabolites composition. We show that grass Brachypodium distachyon derives some nitrogen from amino acids in uninfected Pseudomonas putida necromass lysed by sonication but not from virocell necromass. Additionally, the bacterial necromass elicits the formation of rhizosphere exometabolites, some of which (guanosine), alongside tested aromatic acids ( p -coumaric and benzoic acid), show bacterium-specific effects on bacteriophage-induced lysis when tested in vitro. The study highlights the dynamic feedback between virocell necromass and plants and suggests that root exudate metabolites can impact bacteriophage infection dynamics.

Brachypodium↗
DOE OSTI2024

Joint inference of multiplicative and additive systematics in galaxy density fluctuations and clustering measurements

Galaxy clustering measurements are a key probe of the matter density field in the Universe. With the era of precision cosmology upon us, surveys rely on precise measurements of the clustering signal for meaningful cosmological analysis. However, the presence of systematic contaminants can bias the observed galaxy number density, and thereby bias the galaxy two-point statistics. As the statistical uncertainties get smaller, correcting for these systematic contaminants becomes increasingly important for unbiased cosmological analysis. We present and validate a new method for understanding and mitigating both additive and multiplicative systematics in galaxy clustering measurements (two-point function) by joint inference of contaminants in the galaxy overdensity field (one-point function) using a maximum-likelihood estimator (MLE). We test this methodology with Kilo-Degree Survey-like mock galaxy catalogues and synthetic systematic template maps. We estimate the cosmological impact of such mitigation by quantifying uncertainties and possible biases in the inferred relationship between the observed and the true galaxy clustering signal. Our method robustly corrects the clustering signal to the sub-percent level and reduces numerous additive and multiplicative systematics from 1.5σ to less than 0.1σ for the scenarios we tested. In addition, we provide an empirical approach to identifying the functional form (additive, multiplicative, or other) by which specific systematics contaminate the galaxy number density. Even though this approach is tested and geared towards systematics contaminating the galaxy number density, the methods can be extended to systematics mitigation for other two-point correlation measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evaluations of the Fates of Alkali Metals, Actinides, Mercury, and Iodine During DWPF Recycle Diversion

The fates of alkali metals, actinides, mercury, and iodine in the Defense Waste Processing Facility Recycle Diversion process (as currently conceptualized) have been evaluated through paper studies based on available knowledge of the chemistry, physical properties, solubility, and volatility of the various species involved. The effect of pH in the range from 9 to 13 has been discussed. Recommendations for additional studies to close technology gaps have been provided, many of which are contingent upon the results of pending testing and sample characterization efforts. There is uncertainty in the amounts of soluble actinides passing through the process filter, though the bulk of the actinides should be captured on the filter with the Recycle Collection Tank solids and the total amounts of actinides should be relatively low. The Recycle Collection Tank pH could impact the fraction of actinides reaching the evaporator, but the primary factors determining the actinide fate are expected to be the amount of CO 2 sorption from air sparging or, for certain actinides (such as plutonium), oxidation and/or sorption to MnO 2 solids from permanganate additions to destroy the glycolate anion. Process optimization could minimize the amounts of actinides passing the filter. Depending upon the levels of mercury observed in recycle stream samples and because of the volatility of mercury, the evaporator should be designed with the capability to remove dense mercury phases from the condensate to avoid exceeding ETP WAC limits. The facility design must be adequate to transfer dense mercury phases and testing to confirm mercury transfer is needed. Simulant containing mercury is recommended for both filtration and evaporation testing. OLI Modeling of the various recycle streams is recommended to provide insight on the fate of iodine. Iodine-spiked simulants are recommended for upcoming evaporation tests. The pro) ect should consider the likelihood and impact of NAS scale formation in the evaporators. Process optimization may be needed to minimize the accumulation of NAS scale and possibly the sorption of actinides in the evaporator. Actual waste testing of the Recycle Diversion filtration and evaporation should include the analysis of actinides, mercury, and iodine to determine their partitioning.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Dark energy survey internal consistency tests of the joint cosmological probes analysis with posterior predictive distributions

Beyond ΛCDM, physics or systematic errors may cause subsets of a cosmological data set to appear inconsistent when analysed assuming ΛCDM. Here, we present an application of internal consistency tests to measurements from the Dark Energy Survey Year 1 (DES Y1) joint probes analysis. Our analysis relies on computing the posterior predictive distribution (PPD) for these data under the assumption of ΛCDM. We find that the DES Y1 data have an acceptable goodness of fit to ΛCDM, with a probability of finding a worse fit by random chance of p = 0.046. Using numerical PPD tests, supplemented by graphical checks, we show that most of the data vector appears completely consistent with expectations, although we observe a small tension between large- and small-scale measurements. A small part (roughly 1.5 per cent) of the data vector shows an unusually large departure from expectations; excluding this part of the data has negligible impact on cosmological constraints, but does significantly improve the p-value to 0.10. The methodology developed here will be applied to test the consistency of DES Year 3 joint probes data sets.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Long-term impact of light- and elevated temperature-induced degradation on photovoltaic arrays

Low levelized cost of electricity (LCOE) has been identified as critical for widespread adoption of photovoltaics (PV) without subsidies. Maintaining decades-long high-energy production is often an under-recognized opportunity in meeting cost goals because component lifetimes are not fully quantified at the time of manufacture. Whereas certain standardized tests minimize risk of early failure, there is little guidance to quantitatively predict degradation (or lack thereof) over decades, based on accelerated tests. In this article, we move toward bridging the understanding between indoor accelerated tests and outdoor performance data, with the goal of predicting energy yield with enough accuracy to inform financial decisions. Light- and elevated temperature-induced degradation (LETID) in p-type Si modules is analyzed in terms of impact on long-term module performance and thus LCOE. A method to predict the progression of LETID, using fixed kinetic constants and a numerical solution to the basic reaction rate equations, is detailed. Predictions are compared against both published data and that new to this study. These data include both indoor accelerated tests and fielded modules. We use the results in financial models to derive LCOE of modules in different climates with varying amounts of LETID, including uncertainty. Cost models based on the predictions indicate that LETID has a significant and climate-dependent impact on LCOE. Finally, we show that - even given the uncertainties identified in the study - these financial calculations can provide useful guidance to quantify risk based on accelerated test results. The analysis serves as an example of developing a predictive approach to PV reliability using physics of failure.

14 SOLAR ENERGY↗
DOE OSTI2022

Memory forensic analysis of a programmable logic controller in industrial control systems

In industrial control systems (ICS), programmable logic controllers (PLCs) are used to automate physical processes such as nuclear plants and power grid stations, and are often subject to cyber attacks. As in conventional IT domain, the memory analysis of the PLCs can help answer important forensic questions about the attack, such as the presence of malicious firmware, injection of modified control logic (the program running on the PLC), and manipulation of I/O devices (e.g., sensors and actuators). Unlike conventional IT domain, PLCs have heterogeneous hardware architecture, proprietary firmware and control software, making it challenging to employ a unified framework for their memory forensics. For merely extracting artifacts of forensic importance, reverse-engineering the firmware is a tedious task, and the effort needs to be repeated for every PLC model. As a community, a step-wise approach to tackle this challenge is to analyze the memory of specific PLCs, and subsequently find a generic framework applicable to all PLCs. Our work is a step forward in this direction. By following a methodology that focuses on the functional layer of PLCs instead of reverse engineering the firmware, we analyze the digital forensic artifacts available in a common PLC, Allen-Bradley ControlLogix 1756-L61. Before diving into the memory dump, we analyze the PLC control software to create a list of important artifacts that are sure to exist in the PLC memory dump. The approach employs a setup where PLC control software RSLogix-5000 is connected to the PLC, and the memory dump can be obtained as and when needed. We create test cases that sequentially highlight each category of artifacts, followed by an examination of the resultant impact on memory. After attaining the listed artifacts, we employ conventional string and known data searches to extract interesting information present in this PLC's memory. The memory analysis profile, presented as a Python library and shared with the community, can help a forensic investigator to readily extract forensic artifacts from the same model's controller. The adopted approach may help researchers in creating memory profile of other PLCs, and ultimately formulating a generic PLC memory analysis framework.

Rais, Muhammad Haris↗
DOE OSTI2023

In situ high-temperature 3D imaging of the damage evolution in a SiC nuclear fuel cladding material

Silicon carbide (SiC)-based nuclear fission fuel rod cladding has been considered as one of the possible designs for accident tolerant fuels. It is in the form of a SiC fibre reinforced SiC matrix composite tube (SiC f -SiC m ) with monolithic SiC outer and/or inner coating layers. This study focuses on the deformation and fracture processes in this material using in situ X-ray micro-computed tomography (XCT) at room temperature (RT) and 1200 °C in an inert gas environment in a C-ring compression loading configuration. Prior to testing, local properties and residual stresses were characterised using nanoindentation and Raman spectroscopy since they can impact the mechanical behaviour of the material. The 3D strain distribution, crack formation and propagation processes including the toughening mechanisms (e.g., crack deflection, micro-cracking, crack bridging and bifurcation) are investigated in the coating and underlying composites at RT and 1200 °C. There is no particular sequence which toughening mechanism occurs first – this is very different from the conventional toughening theory in ceramic-matrix composites under uniaxial tension loading. Indeed, no evidence of fibre pull-out or fibre fracture was observed in this SiC f -SiC m nuclear cladding material in the current C-ring compression configuration. The correlation between local measurements and bulk mechanical behaviour are discussed.

3D imaging↗
DOE OSTI2020

Aqueous solvation of the chloride ion revisited with density functional theory: impact of correlation and exchange approximations

The specificity of aqueous halide solvation is fundamental to a wide range of bulk and interfacial phenomena spanning from biology to materials science. Halide polarizability is thought to drive the ion specificity, and if so, it is essential to have an accurate description of the electronic properties of halide ions in water. To this end, the solvation of the chloride anion, Cl - has been reinvestigated with state-of-the-art density functional theory. Specifically, the PBE-D3, PBE0-D3, and SCAN functionals have been employed to probe the impact of correlation and exchange approximations. Anticipating the findings, adding exact exchange improves the electronic structure, but simultaneously significantly reduces the Cl - polarizability, resulting in an over-structured Cl–O radial distribution function (RDF) and longer water H-bond lifetimes to Cl - . SCAN does not yield as much improvement in the energetics of Cl - relative to bulk water, but does result in a smaller reduction of the polarizability and thus a less structured Cl–O RDF, which agrees better with experiment. Special consideration is therefore warranted in assessing the impact of exchange on the energy, charge density, and the charge density response when designing and testing hybrid functionals for aqueous halide solvation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Using strong lensing to detect subhaloes with steep inner density profiles

ABSTRACT The inner region of a subhalo’s density distribution is particularly sensitive to dark matter microphysics, with alternative dark matter models leading to both cored and steeply-rising inner density profiles. This work investigates how the lensing signature and detectability of dark matter subhaloes in mock HST-, Euclid-, and JWST-like strong lensing observations depend on the subhalo’s radial density profile, especially with regards to the inner power-law slope, $\beta$. We demonstrate that the minimum subhalo mass detectable along the Einstein ring of a system is strongly dependent on $\beta$. In particular, we show that subhaloes with $\beta = 2.2$ can be detected down to masses over an order-of-magnitude lower than their Navarro–Frenk–White (NFW) counterparts with $\beta = 1$. Importantly, we find that the detectability of subhaloes with steep inner profiles is minimally affected by increasing the complexity of the main lens galaxy’s mass model. This is a notable characteristic of these subhaloes, as those with NFW or shallower profiles become essentially undetectable when multipole perturbations are added to the lens model. The results of this work highlight how the underlying dark matter physics can significantly impact the expected number of subhalo detections from strong gravitational lensing observations. This is important for testing Cold Dark Matter against alternative models, such as Self-Interacting Dark Matter, that predict a diverse range of subhalo inner density profiles.

dark matter↗
DOE OSTI2025

Network-Aware and Welfare-Maximizing Dynamic Pricing for Energy Sharing

The proliferation of behind-the-meter (BTM) distributed energy resources (DER) within the electrical distribution network presents significant supply and demand flexibilities, but also introduces operational challenges such as voltage spikes and reverse power flows. In response, this paper proposes a network-aware dynamic pricing framework tailored for energy-sharing coalitions that aggregate small, but ubiquitous, BTM DER downstream of a distribution system operator's (DSO) revenue meter that adopts a generic net energy metering (NEM) tariff. By formulating a Stackelberg game between the energy-sharing market leader and its prosumers, we show that the dynamic pricing policy induces the prosumers toward a network-safe operation and decentrally maximizes the energysharing social welfare. The dynamic pricing mechanism involves a combination of a locational ex-ante dynamic price and an ex-post allocation, both of which are functions of the energy sharing's BTM DER. The ex-post allocation is proportionate to the price differential between the DSO NEM price and the energy-sharing locational price. Simulation results using real DER data and the IEEE 13-bus test systems illustrate the dynamic nature of network-aware pricing at each bus, and its impact on voltage.

aggregates↗
DOE OSTI2024

Simulation of Helium Flow Visualization Apparatus for Studies of Blanket Cooling in Fusion Reactors

Flow visualization is essential to understanding helium cooling performance. This article investigates helium flow visualization in an apparatus to support the design of the blanket first wall for a fusion reactor. Helium’s safety advantages make it an attractive coolant, but effective cooling and flow visualization remain challenging. Sophisticated simulations are conducted in different test sections to address three key areas in the design of a test apparatus and cooling channel enhancements: the influence of viewing glass windows on flow patterns, the impact of increased heating, and the effectiveness of cooling structures like baffles. Viewing glass windows introduce flow recirculation region bifurcation and flow asymmetry, affecting flow patterns and necessitating careful analysis in future experiments. Increased heating results in helium flow detachment from the heated surface, leading to hot spots. Cooling structures, particularly baffles, prove effective in maintaining consistent attachment to the heated surface, improving the heat transfer performance. Further, this study also examines a tunable parameter in the turbulence model, highlighting the importance of accurate model tuning for future fusion reactor cooling designs. With an imminent helium flow visualization facility, these simulations will be used to optimize cooling structures on the heated wall to improve flow attachment and heat transfer efficiency. This work serves as a first investigation of the helium flow visualization apparatus for blanket cooling enhancement in fusion reactor design.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗