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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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323 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Silver diamine fluoride differentially affects dentin and hypomineralized enamel permeabilities

OBJECTIVES: To investigate the physicochemical effect of silver diamine fluoride (SDF) by correlating permeability with mineral density and elemental composition of hypomineralized enamel and carious dentin. METHODS: Enamel and dentin from human carious primary teeth with and without SDF treatment in-vivo, and hypomineralized enamel from permanent molars with and without SDF treatment in-vitro were scanned using micro X-ray computed tomography. Spatial maps of biometals (calcium, zinc), phosphorus, and silver were generated using X-ray fluorescence microprobe. Permeabilities were computed using Porous Microstructure Analysis software. RESULTS: The intrinsic permeability of SDF-treated carious dentin was 14.3 % lower than untreated sound dentin (6.39e-15 ± 3.01e-15 m² vs 7.46e-15 ± 1.82e-15 m²; P < 0.0001), while untreated carious dentin was 98.4 % higher (1.48e-14 ± 7.11e-15 m²; P < 0.0001). SDF-treated and untreated transparent dentin showed similar reduced permeabilities (75.6 % and 78.4 % lower than untreated sound dentin, respectively; P = 0.93). Severely hypomineralized enamel showed permeability reaching 108.1 % of adjacent sound dentin (5.71e-15 ± 2.04e-15 m² vs 5.28e-15 ± 1.30e-15 m²; P = 0.1409) and was significantly higher than mildly hypomineralized enamel (1.39e-15 ± 1.04e-15 m²; P < 0.0001). SDF treatment did not significantly impact the permeability of severely hypomineralized enamel (12.4 % reduction; P = 0.07). Principal component regression identified Zn level as a significant effector of tissue permeabilities in carious primary teeth (P < 0.0001). SIGNIFICANCE: This study introduces a computational method to measure dental tissue permeability, and demonstrates that SDF significantly reduces permeability in carious dentin but not intact hypomineralized enamel. The study reveals biometal Zn localization can alter dentin and enamel permeabilities, providing new insights into pathobiological mechanisms underlying caries and hypomineralization.

Chou, Conrad↗
DOE OSTI2021

Portable quantitative confocal Raman spectroscopy: Non-destructive approach of the carbonation chemistry and kinetics

Highlights: • Raman spectroscopy was used to monitor carbonation of portlandite • The approach was non-destructive, continuous, and performed within the material • Carbonation was identified coupling Raman spectroscopy and chemometrics • Kinetics was calculated for one portlandite thickness at different CO{sub 2}-percentages Carbonation is one major alteration process of cementitious materials. It can be monitored through several methods, all destructive. In this study, some preliminary investigations were conducted to monitor the carbonation process of pure portlandite with an in situ and non-destructive spectroscopic method. This complementary approach was motivated by a literature review indicating the benefits of Raman spectroscopy, but requiring innovative approaches for data acquisition and analysis. The material was selected to validate this spectroscopic monitoring, coupled with chemometrics tools to allowing an early detection of the carbonation reaction through a structure identified in the spectra data population. The carbonation occurred abruptly, and spectra analysis indicated the occurrence of phases synonymous of microstructural evolutions. Varying the atmospheric percentage of CO{sub 2} (0.04% - 4%) conducted to an appreciation of the kinetics of the carbonation front through the same thickness of portlandite.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synchrotron X-ray diffraction analysis of constituent phases in transition joint between nickel alloy 738LC and a MnFeCoNiCu alloy

Synchrotron x-ray diffraction (XRD) analysis was performed on transition joints between a single-phase MnFeCoNiCu alloy and Ni-base Alloy 738LC to efficiently identify the constituent phases across the interface, with different levels of material intermixing generated by laser-welding with variable power. Here, the intermixing extent was quantified by postmortem energy dispersive x-ray spectroscopy mapping. Diffraction-based analyses on complex composition spaces with limited prior data present significant challenges because elemental substitution in both disordered and ordered phases is more extensive than in conventional alloy spaces, which may effectuate relatively large shifts in the observed lattice parameters that convolute the analysis. Therefore, thermodynamic simulations and crystallographic literature data were employed to construct a system-specific diffraction library of twelve prospective phases for the composition space investigated. Subsequently, for predicted disordered cubic phases, statistical hard-sphere models were established to estimate the lattice parameters and predict diffraction peak positions for inclusion in the library. The library was then employed to analyze diffraction profiles measured from the variably intermixed transition joints, with focus on accounting for both high and low-intensity peaks. 99.0 % of diffraction peaks with relative intensity greater than 0.001 were assigned to phases from the system-specific library, exemplifying rigorous peak accounting and indicating that no unexpected phases were present. Up to six of the twelve library phases were experimentally found in the transition joints. The lattice parameters predicted by the statistical hard-sphere model based upon thermodynamic simulations agree reasonably well with the measured values for the disordered FCC matrix phase.

36 MATERIALS SCIENCE↗
DOE OSTI2023

In-situ thermodynamics measurements at metal oxides-solution interfaces using Flow Adsorption Microcalorimetry.

Mineral-fluid interfaces are the principal sites of geochemical processes near Earth’s surface, hosting chemical reactions that play a fundamental role in (bio)geochemical cycles and in the fate and transport of anthropogenic contaminants, and that effectively control the compositions of soil and water environments. These complex interfaces are critical for our energy and environmental future. The mineral-fluid interface has been studied in an unprecedented level of detail with both experimental and computational approaches, separately and in combination. However, conspicuously missing from studies of the mineral-fluid interface are direct measurements of the energies of ion sorption and exchange. The literature on energetics and enthalpies of exchange, adsorption, dissolution, precipitation, and surface protonation reactions, especially those directly supported by experimental data, remains scarce despite their fundamental nature. The overarching goal of this project is to complete a systematic study of the thermodynamics properties of interfacial reactions at four MO surfaces (Rutile (α-TiO2), Quartz (SiO2), boehmite (γ-AlOOH) and goethite (α-FeOOH)) through the application and construction of novel flow adsorption microcalorimetry techniques and instrumentations. These unique and specialized microcalorimeters will operate at various temperatures and solution chemical compositions allowing for in-situ measurements across metal oxides and ligands of various characteristics. The overall research goal will be accomplished by completing the following three specific objectives (O): O1) Determine the energetics of surface protonation and deprotonation, ion exchange and ligand sorption reactions; O2) Investigate the surface charge thermodynamic properties under a range of temperature and solution chemical compositions; and O3) Develop predictive trends of the interplay between MO structure, surface coverage and surface reactivity. In addition to key thermodynamics parameters, calorimetric measurements provide a wealth of mechanistic information about reactions energetics and kinetics, surface charge characteristics, and structure-reactivity or selectivity relationships, all obtained in-situ and in real-time. This report includes science highlights from various projects completed over the performance period of the project. Also listed are dissemination opportunities, people supported on the grant and the impact on available physical resources and the discipline as a whole.

58 GEOSCIENCES↗
DOE OSTI2025

Discovery, Design, Synthesis and Testing of High Performance Structural Alloys (Final Technical Report)

The overarching goal of this project is to understand the phase stability and mechanical behavior of non-stoichiometric multi-principal element alloy (MPEA) materials. In order to identify suitable alloys, we plan to use a combinatorial thin film screening approach, in collaboration with scientists at Lawrence Berkeley National Laboratory who are performing computational work as well as complementary experimental work. Specific tasks within the scope of this project include the fabrication, using thin film deposition from six sputtering targets, of combinatorial samples with multi-dimensional gradients in composition and microstructure. These samples are studied to screen MPEA systems for promising candidate alloys with specific composition(s), based on characterization of composition, structure and mechanical behavior across the thin film. We want to produce single-phase MPEAs with chemical homogeneity in a given thin film region, simple grain structures, and no intermetallic phases present. Gradient films facilitate first-pass screening for desirable characteristics and inform the next stage of work that involves fabrication of bulk MPEA specimens for (tensile) mechanical testing and characterization. To make the bulk alloys, metal (elemental) pieces are melted to form MPEAs, followed by heat treatment to homogenize the composition and microstructure. A subset of alloys is also cast, using vacuum arc melting, to yield larger samples (diameter ~1 cm and length ~5-10 cm) and these allow us to assess viability of scale-up for the alloys in structural applications. Further processing plans include rolling and heat treatment to recrystallize selected bulk MPEAs and grow grains to different extents, in order to investigate size effects in the mechanical behavior of MPEAs. Microspecimen testing will be performed (primarily in tension) to assess the mechanical behavior over a range of temperatures. The deformation microstructure of mechanically tested alloys will be characterized using transmission electron microscopy (TEM) to provide a scientific basis for understanding the structure-property relationships in MPEA mechanical behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Many-body Nuclear Dynamics

The principal goal of this work was to better understand the fusion of neutron-rich nuclei a topic relevant to the fields of both nuclear physics and nuclear astrophysics. The work provides insight into the structure and reactions of neutron-rich nuclei namely the extent of their neutron density distribution and its polarizability. By comparing the fusion excitation functions for a chain of isotopes with a common target nucleus changes in the attractive nuclear potential are assessed. This change in the attractive potential is related to changes in the neutron density distribution with increasing number of neutrons or changes in fusion dynamics with increasing neutron number. The impact of the pairing of valence neutrons and protons on the fusion cross-section is also examined. Measurement of an isotopic chain is a powerful tool to address this topic. The experimental program made use of several different accelerator facilities. The core of the experimental work involved experiments at the ReA3 accelerator and the Facility for Rare Isotope Beams (FRIB) situated at Michigan State University, at GANIL, the French national nuclear physics laboratory, and the University of Notre Dame. At ReA3 the degree to which α-clusters associated with fusion of 28,30,32 Si + 28 Si result from the collision dynamics or reflect an initial α-cluster structure was explored. Alpha clusters observed in fusion reactions exceed the predictions of the standard statistical model. This experiment provides a measure of how clusterization is impacted by the increasing neutron-richess of the system. In the experiment at GANIL we investigated fusion in 19 O + 12 C and 20 O + 12 C. This experiment utilized the recently developed active-target detector MuSIC@Indiana. Using this proven, highly efficient, active-target detector we measured the fusion excitation function for these neutron-rich systems. Grounded by these experimental measurements, theoretical models were used to examine the role of unpaired valence neutrons on the fusion cross-section at energies just above the fusion barrier.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Macroscopic and microscopic behaviors of Mn(II) (ad)sorption to goethite with the effects of dissolved carbonates under anoxic conditions

Manganese and its compounds have been extensively researched because of their far-reaching roles in a wide range of biogeochemical processes in natural systems. The (ad)sorption behavior of Mn(II), however, is poorly understood despite its important role as the primary reaction step for surface-catalyzed Mn(II) oxidation that is the principal abiotic process forming various Mn (oxyhydr)oxides in nature. Here, we systematically examined Mn(II) (ad)sorption to one of the most common natural sorbents, goethite, in oxygen- and carbonate-free systems. Traditional sorption edge and isotherm experiments were conducted by varying sorbate-to-sorbent ratio (0.027–15 μmol∙m -2 ) and solution pH (pH 5.0–9.0). The effects of dissolved carbonates on Mn(II) sorption were also assessed in a range of naturally prevalent concentrations (0.5–10 mM NaHCO 3 ). The Mn(II) uptake on goethite followed a typical Langmuir isotherm in the absence of dissolved carbonates, with increasing maximum adsorption capacities (Γ max ) from 0.19 at pH 6.5 to 3.4 μmol∙m -2 at pH 9.0. The presence of dissolved carbonates raised the extent of Mn(II) adsorption, which appeared to be directly correspondent to that of the adsorption of dissolved carbonates. Extended X-ray absorption fine structure (EXAFS) analysis indicated that Mn(II) predominantly formed inner-sphere binuclear bidentate surface complexes. Mn(II) uptake became deviated from the Langmuir model and showed a clear indication of surface precipitation when the Mn(II) sorption density (Γ) exceeded a threshold value in a given solution composition. This secondary Mn(II) phase was identified as rhodochrosite using X-ray diffraction (XRD) and transmission electron microscope (TEM). Furthermore, it would be plausible that a minor fraction of adsorbed Mn(II) coexisted with the secondary rhodochrosite according to a linear combination fitting (LCF) of the X-ray absorption near edge structure (XANES) spectra of Mn reference and samples. These systematic investigations of the macroscopic and microscopic behaviors of Mn(II) (ad)sorption to goethite provide a critical avenue for disentangling surface-catalytic Mn(II) oxidation processes, which ultimately lead to the formation of diverse Mn (oxyhydr)oxides in the environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Descriptors of water aggregation

For this work, we rely on a total of 23 (cluster size, 8 structural, and 14 connectivity) descriptors to investigate structural patterns and connectivity motifs associated with water cluster aggregation. In addition to the cluster size n (number of molecules), the 8 structural descriptors can be further categorized into (i) one-body (intramolecular): covalent OH bond length (r OH ) and HOH bond angle (θ HOH ), (ii) two-body: OO distance (r OO ), OHO angle (θ OHO ), and HOOX dihedral angle ($\phi$ HOOX ), where X lies on the bisector of the HOH angle, (iii) three-body: OOO angle (θ OOO ), and (iv) many-body: modified tetrahedral order parameter (q) to account for two-, three-, four-, five-coordinated molecules (q m , m = 2, 3, 4, 5) and radius of gyration (R g ). The 14 connectivity descriptors are all many-body in nature and consist of the AD, AAD, ADD, AADD, AAAD, AAADD adjacencies [number of hydrogen bonds accepted (A) and donated (D) by each water molecule], Wiener index, Average Shortest Path Length, hydrogen bond saturation (% HB), and number of non-short-circuited three-membered cycles, four-membered cycles, five-membered cycles, six-membered cycles, and seven-membered cycles. We mined a previously reported database of 4 948 959 water cluster minima for (H 2 O) n , n = 3–25 to analyze the evolution and correlation of these descriptors for the clusters within 5 kcal/mol of the putative minima. It was found that r OH and % HB correlated strongly with cluster size n, which was identified as the strongest predictor of energetic stability. Marked changes in the adjacencies and cycle count were observed, lending insight into changes in the hydrogen bond network upon aggregation. A Principal Component Analysis (PCA) was employed to identify descriptor dependencies and group clusters into specific structural patterns across different cluster sizes. The results of this study inform our understanding of how water clusters evolve in size and what appropriate descriptors of their structural and connectivity patterns are with respect to system size, stability, and similarity. The approach described in this study is general and can be easily extended to other hydrogen-bonded systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Thermally Induced Structural Transitions in Epoxy Thermoset Polymer Networks and Their Spectroscopic Responses

The polymer network structure of epoxy thermosets plays a significant role in its final material properties. However, the effects of mild thermal exposure on these network structures are poorly studied. In this work, wide-angle X-ray scattering was used to investigate the polymer network structure of two epoxy thermosets: homopolymerized bisphenol A (BPA) epoxy resin and BPA epoxy resin cured with a polyether amine hardener (BPA/T-403). Using density functional theory and wide-angle X-ray scattering, insights into the polymer network structure were obtained. Diffraction features were determined to originate from hardener-to-hardener molecular distance, perpendicular π–π stacking of aromatic p-phenylene rings, and the average carbon–carbon distance in the polymer. Thermal exposure was found to permanently alter these structural features for both thermosets, with an increase in the π–π stacking distance. Homopolymerized BPA had an additional decrease in the hardener-to-hardener distance. These structural alterations were found to be detectable using Fourier transform infrared spectroscopy and Raman spectroscopy, with changes in the hardener-to-hardener distance having the largest variations in the resulting spectra specifically at the aromatic and ether frequencies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Broadband multiwavelength properties of the archetypal blazar 3C 279 during the 2017 Event Horizon Telescope campaign

The archetypal blazar 3C 279 hosts a prominent relativistic jet and exhibits strong broadband variability across the electromagnetic spectrum. In April 2017, the Event Horizon Telescope (EHT) observed 3C 279, alongside one of the most extensive quasi-simultaneous multiwavelength (MWL) campaigns ever conducted. With the aim of investigating the physical processes governing 3C 279, we analyzed individual observations and multiband light curves, and constructed a new quasi-simultaneous MWL spectrum. We also performed phenomenological modeling using the turbulent extreme multi-zone (TEMZ) model to constrain the fundamental physical properties of the source. The EHT observations reveal a clear flux increase in the innermost core between April 5 and 11, 2017. Over a broader timescale, radio measurements at longer wavelengths show concurrent enhancements in core flux and polarization around mid-April, coinciding with the ejection of a superluminal knot. Record UV-optical flares with strong polarization variability occurred in late March, followed by gamma-ray activity that declined before the end of the EHT observing period. During this interval, the source remained in a low X-ray state and showed no detectable VHE emission. The TEMZ modeling suggests that the broadband spectrum and variability of 3C 279 can be explained within a jet scenario in which turbulent plasma cells are compressed by a stationary conical shock. However, alternative interpretations, such as magnetic reconnection or a moving shock-in-jet event, remain plausible. This coordinated MWL campaign advances our understanding of the origin of jet and gamma-ray emission in 3C 279, while also providing a comprehensive publicly available dataset that will serve as a valuable reference for future studies.

Principe, G. [Trieste U.; INFN, Trieste; Bologna, ↗
DOE OSTI2024

Carbonate Management to Enable Energy- and Carbon-Efficient CO 2 Electrolysis (Final Technical Report)

The rapid growth and plummeting cost of solar energy have spurred growing interest in using CO 2 electrolysis to produce chemicals and fuels as an alternative to conventional petrochemical processes. High-temperature (>800 °C) solid oxide electrolyzers that convert CO 2 into CO and O 2 have recently become commercially available. Low-temperature electrolysis cells offer the prospect of more convenient and flexible operation, which is critical for utilizing intermittent solar energy, and provide access to more valuable C 2+ products such as ethylene, ethanol, and propanol. Over the past 10 years, research in this area has yielded substantial progress in both fundamental understanding of the requisite electrocatalytic reactions and design of prototype devices. Leveraging insights from fuel cells and membrane water electrolyzers, researchers have developed electrolysis cells with gas diffusion electrodes (GDE) that have demonstrated high CO 2 electrolysis current densities (>100 mA cm –2 ) as well as promising selectivity and stability. Despite these advances, the energy efficiency (electrical energy-to-product) and carbon efficiency (CO 2 -to-product) of low-temperature CO 2 electrolysis remain far too low for large-scale deployment. A preponderance of evidence indicates that the principal source of efficiency losses is the rapid and thermodynamically favorable reaction of CO 2 with hydroxide (OH – ) to form carbonate (CO 3 2– ). Carbonate formation imposes steady-state electrolysis conditions that result in large voltage and CO 2 losses for all known (photo)electrochemical CO 2 cells. While much current research remains focused on CO 2 reduction catalyst design, this largely overlooked CO 3 2– problem presents a fundamental scientific barrier to creating a viable electrochemical option for converting solar energy into chemicals and fuels. The project pursues an integrated, multi-PI research effort that establishes a fundamental science of CO 3 2– management. PI Kanan and Co-PI Mani’s contribution to the project is to evaluate strategies to mitigate the CO 3 2– problem by changing the properties of the electrolyte and the environment in which CO 2 reduction catalysis takes place. Experimental studies showed that electrolytes composed of a high concentration of both CO 3 2– and HCO 3 – , which serve as moderately alkaline buffers, improved the cell voltage by compared to all-HCO 3 – electrolytes, but these buffered systems still show substantial CO 2 uptake that reduces pH over time. Computational studies developed a homogenized model of a CO 2 reduction catalyst layer that permits a low-cost exploration of the high-dimensional parameter space associated with catalyst layers on gas diffusion electrodes. The model was validated by accurately reproducing experimental data for the related but simpler reaction of CO reduction and then used to probe the effects of catalyst layer architecture on CO 2 reduction. Minimizing the size of catalyst and hydrophobic domains in the catalyst layer is predicted to mitigate CO 3 2– formation and thereby enable prolonged operation at elevated pH. In support of the CO 2 electrolysis studies, a new method for rapidly prototyping electrochemical cells was developed and validated. The method uses a combination of 3D printing and electroless plating to generate conductive cell components for evaluating new cell designs. The carbonate problem encompasses mass transport processes and acid-base reactions that are relevant to many other electrochemical systems. Investigation of strategies to address the carbonate problem led to an additional line of inquiry into the physicochemical phenomena that determine the efficiency of electrochemical acid-base production, which has numerous applications in the broader field of carbon management. New strategies for using the supporting electrolyte to inhibit H + /OH – recombination in electrochemical acid-base production were evaluated, leading to the development of a novel acid-base producing system that eliminates the need for ion exchange membranes and exhibits promising efficiency and current densities for scalable applications.

25 ENERGY STORAGE↗
DOE OSTI2024

Speciation and Aqueous Dissolution of Macronutrients in Fire Ash: Variation across Ecosystems and the Effects on Nutrient Cycling

This study investigated the speciation and aqueous dissolution of macronutrients in fire ash from diverse ecosystems and speciation of ash and smoke from laboratory burning, exploring the variations and their causes. The speciation of phosphorus (P), calcium (Ca), and potassium (K) in fire ash from five globally distributed ecosystems was characterized by using X-ray absorption spectroscopy and sequential fractionation. Aqueous dissolution of the macronutrients was measured by batch experiments at acidic and alkaline pHs. The results showed that P existed mainly as Ca phosphates, Ca as double carbonates, calcite, and sulfates, and most K was associated with Ca carbonates. Mineralogy and the relative abundance of the species were primarily controlled by elemental stoichiometry and fire temperature. Differences in Ca and P speciation existed between ash and smoke from laboratory burning, possibly caused by the temperature difference and/or mass fractionation during burning. The rates, extents, and pH dependencies of macronutrient dissolution differed among macronutrients and depended on their speciation, with K being highly soluble and the P and Ca regulated by solution pH. The variability in ash macronutrient chemistry and ecosystemspecific fire ash loads resulted in varying loads and availability of individual macronutrient from fire among ecosystems. This study provides a mechanistic understanding of how fires transform the chemistry of macronutrients and affect macronutrient returns to soils across different ecosystems, which is essential for evaluating the disturbance to ecosystem nutrient cycling by fires.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Application of an Embedded Fracture and Borehole Modeling Approach to the Understanding of EGS Collab Experiment 1

EGS Collab is a series of meso-scale experiments and associated numerical simulation activities being funded by the United States Department of Energy, Geothermal Technologies Office (GTO) to investigate enhanced geothermal system processes under in-situ stress and slightly elevated temperature conditions. This project is designed to provide scientists and engineers with immediate access to impermeable rock at scales larger than possible in the laboratory, but generally smaller than those for commercial production. Immediate access to rock is provided via the existing drifts of the former Homestake Gold Mine, now operated as the Sanford Underground Research Facility in Lead, South Dakota. The objectives of the EGS Collab project are to develop well controlled fracture networks between injector and producer boreholes using normal and shear stimulation for permeability enhancement. The first experimental site was located off the West Access drift on the 4850 Level (4850 feet below ground surface) in phyllite of the Precambrian Poorman formation, and involved the creation of a fracture network comprising a combination of hydraulic and natural fractures. A second experimental site is now being considered near the battery alcove on the 4100 Level in amphibolite and rhyolite of the Yates Unit. Data generated during these experiments will be compared against predictions of a suite of computer codes specifically designed to solve problems involving coupled thermal, hydrological, geomechanical, and geochemical processes. Comparisons between experimental and numerical simulation results will provide code developers with direction for improvements and verification of process models, build confidence in the suite of available numerical tools, and ultimately identify critical future development needs for the geothermal modeling community. Moreover, conducting thorough comparisons of models, modelling approaches, measurement approaches and measured data, via the EGS Collab project, will serve to identify techniques that are most likely to succeed at the Frontier Observatory for Research in Geothermal Energy (FORGE), the GTO’s flagship EGS research effort. Experiment 1 has comprised a series of successful tests, including a long-term chilled-water circulation test, but the testbed has two atypical EGS elements. Active ventilation in the adjacent drift over a 50-year period cooled the testbed rock mass and hydraulic fracturing intersected monitoring boreholes making them conduits for fluid flow. Numerical simulations executed in support of the design of the EGS Collab Experiment 1, computed a radial temperature distribution and stress gradient orthogonal to the drift axis, resulting in the forecast of an oblong hydraulic fracture geometry, extended in the direction of the drift from the stimulation borehole. This paper describes the numerical simulation of long-term chilled-water circulation test with an embedded fracture and borehole modeling approach. The principal objective of the simulation work is show agreement between experimental observations in terms of production fluid temperatures, monitoring borehole temperatures, injection and production pressures, and tracer recoveries using a single conceptual model for the fracture network, using characterization and monitoring data generally available for EGS. A secondary objective is to improve the numerical simulation result comparisons with additional data available from the broader monitoring equipment within the testbed versus deeper, hotter, and more remote EGS. One complicating factor for comparisons between the numerical simulation results and experimental observations, is the Joule-Thomson heating associated with large pressure drops across the fracture network.

numerical simulation, embedded fractures and boreh↗
DOE OSTI2025

Subspace-Driven Learning for Anomaly Detection in Process Transients

Nuclear power plant (NPP) monitoring and diagnostic centers are actively investigating and implementing automated anomaly detection algorithms to help plants catch anomalies sooner, thereby preventing or reducing the duration of unexpected shutdowns. Current machine learning-based anomaly detection methods are expected to be highly effective during stable, full-power operations because NPPs typically operate as baseload power generators, meaning there are extensive operating data available from plant equipment. However, it is expected that anomaly detection methods will face significant challenges during transient conditions (i.e., when power output falls below full power) because plants only occasionally operate at these lower power levels, generating sparse transient operational data, and resulting in false alarms or missed detections. Here, to address this issue, transfer learning is used, which for this problem leverages knowledge (in the form of learned features) from stable, full-power operations to improve detection accuracy during transient conditions, even with limited data. In this effort, a novel subspace approach is developed to transfer a subset of the data features from full power operation to transients. This approach is validated through experiments using synthetic data and was found to outperform two baseline transfer learning approaches in anomaly detection performance across a range of amounts of transient data used in the training process.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2023

Evaluation of Equiatomic CrMnFeCoNiCu System and Subsequent Derivation of a Non-Equiatomic MnFeCoNiCu Alloy

Investigation into non-equiatomic high-entropy alloys has grown in recent years due to questions about the role of entropy stabilization in forming single-phase solid solutions. Non-equiatomic alloys have been shown to retain the outstanding mechanical properties exhibited by their equiatomic counterparts and even improve electrical, thermal, and magnetic properties, albeit with relaxed composition bounds. However, much remains to understand the processing–structure–property relationships in all classes of so-called high-entropy alloys (HEAs). Here, we are motivated by the natural phenomena of crystal growth and equilibrium conditions to introduce a method of HEA development where controlled processing conditions determine the most probable and stable composition. This is demonstrated by cooling an equiatomic CrMnFeCoNiCu alloy from the melt steadily over 3 days (cooling rate ~4 °C/h). The result is an alloy containing large Cr-rich precipitates and an almost Cr-free matrix exhibiting compositions within the MnFeCoNiCu system (with trace amounts of Cr). From this juncture, it is argued that the most stable composition is within the CrMnFeCoNiCu system rather than the CrMnFeCoNi system. With further optimization and evaluation, a unique non-equiatomic alloy, Mn 17 Fe 21 Co 24 Ni 24 Cu 14 , is derived. The alloy solidifies and recrystallizes into a single-phase face-centered cubic (FCC) polycrystal. In addition to possible applications where Invar is currently utilized, this alloy can be used in fundamental studies that contrast its behavior with its equiatomic counterpart and shed light on the development of HEAs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Novel usage of deep learning and high-performance computing in long-baseline neutrino oscillation experiments

Mención Internacional en el título de doctorDeep-learning methods are playing a crucial role in numerous scientific and industrialapplications. Over the past two decades, these techniques have helped in the collection,reconstruction, and analysis of large data samples in particle physics experiments. Themain topic of this PhD research is the study of deep-learning techniques in long-baselineneutrino oscillation experiments. Neutrinos are mysterious light elementary particles,and their investigation is essential to shed light on some of the remaining open questionsin physics. The work presented here describes an algorithm based on a convolutionalneural network developed to provide highly accurate and efficient selections of electronneutrino and muon neutrino interactions in the Deep Underground Neutrino Experiment(DUNE). With this algorithm, the electron neutrino (antineutrino) selection efficiencypeaks at 90% (94%) and exceeds 85% (90%) for reconstructed neutrino energies between2-5 GeV. The selection efficiency for muon neutrino (antineutrino) interactions is foundto have a maximum of 96% (97%) and exceeds 90% (95%) efficiency for reconstructedneutrino energies above 2 GeV. When considering all electron neutrino and antineutrinointeractions as signal (both those appearing from oscillations and those intrinsic tothe beam), a selection purity of 90% is achieved. These event selections are criticalto maximise the sensitivity of the experiment to CP-violating effects, key to furtherunderstand the matter-antimatter asymmetry of the Universe.In high-energy physics experiments, deep learning has also been explored for producingfast simulations and physically-motivated manipulations of simulated images. Some ofthose simulations, such as the light production and detection, are very computationallyexpensive and require novel methods to produce the necessary samples while controllingthe varied underlying physics model parameters. To do so, we invented the model-assistedgenerative adversarial network (MAGAN), first validated on simple generic case studiesand then successfully applied to the DUNE photon-detector simulation.Moreover, we also developed graph neural networks for 3D-voxel classification ofambiguities and optical crosstalk for a different particle physics experiment, most preciselyfor the proposed SuperFGD. This novel 3D-granular plastic-scintillator neutrino detectorwill be used to upgrade the near detector of the T2K neutrino oscillation experiment, and our method reports efficiencies and purities of 94-96% per event in the classificationof particle track voxels.Due to the growth and complexity of deep neural networks, researchers have beeninvestigating techniques to train those networks in a more computationally-efficient way.Many efforts have been made by the community to optimise deep-learning models byparallelising or distributing their training computation across multiple devices. In thisthesis, we study an approach based on data locality for those neural networks that cannotbenefit from scaling their computation due to a significant bottleneck in the data I/O.The research also includes a detailed study on the performance of deep neural networkson hardware accelerator boards.Los métodos de aprendizaje profundo son cada vez más utilizados en numerosas aplicacionescientíficas e industriales hoy en día. Durante las dos últimas décadas, estastécnicas se han empleado en la recolección, reconstrucción y análisis de la gran cantidadde datos generados por experimentos de física de partículas. El tema principal de estatesis doctoral es el uso de estos modelos de aprendizaje profundo en experimentos defísica de neutrinos, en concreto en los experimentos de larga distancia DUNE y T2K. Losneutrinos, partículas fundamentales neutras, de las más ligeras del Universo, pueden serclave para explicar algunas de las cuestiones todavía sin resolver en física fundamental.Entre las diferentes contribuciones que esta tesis ha hecho a su estudio, cabe destacar eldesarrollo de un algoritmo basado en una red de neuronas convolucional para seleccionarcon gran eficiencia y precisión las interacciones de neutrinos electrónicos y muónicos enel Deep Underground Neutrino Experiment (DUNE). La eficiencia de selección obtenidapara neutrinos (antineutrinos) electrónicos alcanza un máximo del 90% (94%) y supera el85% (90%) para neutrinos con energías reconstruidas en el rango 2-5 GeV. La selección deneutrinos (antineutrinos) muónicos tiene una eficiencia máxima del 96% (97%) y excedeel 90% (95%) para neutrinos con energías reconstruidas de más de 2 GeV. Considerandocomo señal todas las interacciones de neutrinos y antineutrinos electrónicos (procedentestanto de oscilaciones como intrínsecos en el haz inicial), se logra una pureza en la seleccióndel 90%. Dichas selecciones de eventos son fundamentales para maximizar la sensibilidaddel experimento a los efectos de violació...

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

RELAP5-3D Modeling of High Temperature Test Facility (HTTF) Test PG-26

The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a scaled integral effects experiment designed to investigate transient behavior in high-temperature gas-cooled nuclear reactors with prismatic fuel and reflector blocks. Several tests have been completed, and more are still planned to at the HTTF, including depressurized conduction cooldown (DCC) and pressurized conduction cooldown (PCC) transients. This report analyses test PG-26, a progression of the Double Ended Inlet-Outlet Crossover Duct Break transient that is referred to as a DCC. PG-26 has been performed at the HTTF between May 30 and June 30, 2019. Core initial conditions (i.e., before the DCC started) have been met using low power (<100 kW) and two of ten available electric heaters. The DCC transient was initiated during the 50 th hour of the test. The break valves were opened, and hot helium from the core and cold helium from the reactor cavity simulation tank (RCST) started mixing. The gases flowed in a countercurrent fashion, where the top half of the hot duct contained hot helium that flowed in one direction and cold helium that flowed in the other direction in the bottom half of the duct. After the pressure and density reached equilibrium, the event entered a diffusion mode. The onset of a reverse natural circulation was not observed during the DCC period of the test. Version 4.4.2ie of the RELAP5-3D computer code has been used to model the HTTF PG-26 test, and results have been compared to available high-quality measured data. The model used in this study is the quality-controlled HTTF RELAP5-3D model (HTTF base 2018-04-19 QA), originally developed by P. Bayless. The report includes RELAP5-3D results of the “base calculations” as well as some sensitivities to important uncertain model inputs, such as primary helium mass flow rate, core ceramic thermal properties, as well as heat evacuation and loop friction models. Using the base RELAP5-3D model predicts a countercurrent helium flow in the hot duct observed at the beginning of the DCC, but instead of going into a molecular diffusion mode, the model predicts the onset of natural convection. Increasing friction in the core and hot duct prevents the natural convection from happening in some of the simulations. Although some temperatures are well predicted (and even overpredicted), the general tendency is to underpredict the ceramic and helium temperatures and heat removal rates during the DCC, resulting in many of the assessment findings being in minimal or insufficient agreement with the data. It is worth noting that the described discrepancies between measured data and RELAP5-3D predictions are not RELAP5-3D code limitations. More so, they reflect limitations in boundary condition and thermal property knowledge. While the RELAP5-3D calculations of the test provide some insights into what happens during the transient, and point to missing or potentially uncertain data to which the experimenters can direct their attention, the principal conclusion is that the PG-26 test data are insufficient for a system code assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗