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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Hardness Prediction by Incorporating Heat Transfer and Molten Pool Fluid Flow in a Multi-pass, Multi-layer Weld for Onsite Repair of Grade 91 steel

Introduction: In the current fleet of fossil-fired power plants, creep strength enhanced ferritic steels (CSEF) are used to sustain the harsh service conditions. Enhanced properties of Grade 91 steel result from tempered martensite with a fine distribution of MX and M23C6 carbides. Grade 91 steel is subjected to onsite welding repair to remedy their degradation due to extreme service condition. Knowledge of weld repairability of these steels, such as as-welded hardness distribution, is essential to establishing sound repair procedures. Experimental trial and error tests can consume a lot of time as many welding variables need to be studied. For numerical modelling, most of the multi-pass multi-layer models are based on finite element method, which are limited to solve the heat conduction equation and ignore convective heat transfer due to melt flow. Moreover, the mesh has to be pre-built based on a known or assumed weld cross-section geometry. These finite element based models thus have limited predictive capability as defects are not considered and nugget size are pre-assumed. This research aims at developing a thermal and microstructure evolution model incorporating molten pool dynamics in a multi-pass multi-layer material deposition to predict the as-welded hardness distribution. Technical Approach: All the thermal, physical, and metallurgical properties of Grade 91 as a function of temperature are collected from the literature and inputted into the thermo-fluid model based on Flow-3D, a computational fluid dynamics software. A multi-pass, multi-layer material deposition is simulated where the melting of filler wire into the molten pool is directly considered based on the volume of fluid (VOF) method. The flow behaviour of the molten pool is used to understand the formation of deposition geometry and defects. The temperature profiles during the multi-pass, multi-layer welding are calculated. The results computed using the new model are compared against the experimental data of fusion zone geometry and thermal cycles. Hardness prediction in the heat-affected zone (HAZ) are made using Johnson-Mehl-Avrami (JMA) equation for solid-state phase transformation kinetics. The JMA parameters are extracted from the experimental data available in the literature. For comparison, a standard finite element heat conduction model is also developed to predict the thermal cycles and hardness distribution in the multi-pass, multi-layer weld. Expected Result: Results obtained using the molten pool dynamic simulation versus the finite element heat conduction model are compared. Specifically, the effects of convective heat transfer on the accuracy of the calculated thermal history, bead shape and size, and HAZ hardness distribution are examined.

Modeling, Grade 91 steel, Multi-pass multi-layer d↗
DOE OSTI2024

Viscoelastic relaxation and topological fluctuations in glass-forming liquids

In this study, a method for characterizing the topological fluctuations in liquids is proposed. This approach exploits the concept of the weighted gyration tensor of a collection of particles and permits the definition of a local configurational unit (LCU). The first principal axis of the gyration tensor serves as the director of the LCU, which can be tracked and analyzed by molecular dynamics simulations. Analysis of moderately supercooled Kob–Andersen mixtures suggests that orientational relaxation of the LCU closely follows viscoelastic relaxation and exhibits a two-stage behavior. The slow relaxing component of the LCU corresponds to the structural, Maxwellian mechanical relaxation. Additionally, it is found that the mean curvature of the LCUs is approximately zero at the Maxwell relaxation time with the Gaussian curvature being negative. This observation implies that structural relaxation occurs when the configurationally stable and destabilized regions interpenetrate each other in a bicontinuous manner. Finally, the mean and Gaussian curvatures of the LCUs can serve as reduced variables for the shear stress correlation, providing a compelling proof of the close connection between viscoelastic relaxation and topological fluctuations in glass-forming liquids.

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

First observation of a high-𝐾 band structure in 162 Er and implications in the context of the identical bands phenomenon

The first ever identification of a high-𝐾 band structure in 162 Er is reported. Based on a 𝐾 𝜋 = 7 (−) isomer, it is found to be identical in nature to the corresponding 𝐾 𝜋 = 7 − sequence in 164 Er up to its highest observed spin. Furthermore, the phenomenon of identical high-K bands built on a two-quasiparticle configuration in an isotopic chain is reported here for the first time. While this is a notable addition to the systematics of known identical bands in nuclei at normal deformation, a satisfactory global understanding of the phenomenon remains elusive.

150 ≤ A ≤ 189↗
DOE OSTI2024

A Simulated Evaluation of Powder Flowability Through a Partially Obstructed Consumable in Blown Powder Directed Energy Deposition Systems

Abstract In the interest of continued industrialization of metal additive manufacturing in modern production environments, cost is often referenced as a primary deterrent to new adopters. Conventional economic models for additive systems, processes, and supply chains often focus on specific process applications with little generalizability, or they neglect significant costs associated with production such as machine maintenance and consumable part replacement. Compounding the latter issue are substantial knowledge gaps in consumable part wear characterization for additive and other convergent manufacturing systems. In coaxial blown powder directed energy deposition systems, gas atomized metal powder is wasted during material deposition at a rate that is partly dependent on present wear phenomena in a consumable nozzle housed in the cladding head assembly. The price and lead time required to replace the nozzle incentivizes its reuse even when visibly worn. Often this initiates a process quality decline in the form of underbuilt geometry and internal defects due to losses in powder catchment efficiency. While depositing H13 steel using a hybrid manufacturing machine tool equipped with such a deposition system, a unique partial clog with a bridge-like structure formed at the consumable nozzle exit when supporting argon gas flows failed mid-process. To further understand coaxial multi-phase powder flow in the event of support gas failure, a computational fluid dynamics simulation is tailored to relevant process parameters, H13 powder material profile, and machine operator observations collected after the incident. The resulting differences in powder flow compared to control gas flow parameters is presented and discussed. The powder flowability and performance of the clogged nozzle is then assessed by using an optical profilometer to extract the profile of the clog and recreate the clog geometry within the simulation environment. In past work this simulation has been experimentally validated for a 316L steel powder material profile and used specifically for analyzing powder stream geometry and catchment efficiency. After the initial powder flow characterization, the clog is removed, and the nozzle is reprofiled. After removing the obstructing clog, the newly unobstructed nozzle geometry, the original off the shelf nozzle geometry, and additional nozzle profiles exploring different consumable refurbishment strategies are reevaluated in the simulation. Powder catchment efficiency for all variant nozzle geometries and relevant flow variables are compared and discussed, along with potential mitigation strategies for optimizing powder flowability with worn consumables. This work expands on the known morphology of blown powder obstructions and wear defects present in consumable coaxial nozzles while discussing pragmatic simulation driven responses to unanticipated subsystem failure in hybrid manufacturing machining platforms.

DeWitte, Lisa↗
DOE OSTI2024

A graphics processing unit accelerated sparse direct solver and preconditioner with block low rank compression

We present the GPU implementation efforts and challenges of the sparse solver package STRUMPACK. The code is made publicly available on github with a permissive BSD license. STRUMPACK implements an approximate multifrontal solver, a sparse LU factorization which makes use of compression methods to accelerate time to solution and reduce memory usage. Multiple compression schemes based on rank-structured and hierarchical matrix approximations are supported, including hierarchically semi-separable, hierarchically off-diagonal butterfly, and block low rank. Here, in this paper, we present the GPU implementation of the block low rank (BLR) compression method within a multifrontal solver. Our GPU implementation relies on highly optimized vendor libraries such as cuBLAS and cuSOLVER for NVIDIA GPUs, rocBLAS and rocSOLVER for AMD GPUs and the Intel oneAPI Math Kernel Library (oneMKL) for Intel GPUs. Additionally, we rely on external open source libraries such as SLATE (Software for Linear Algebra Targeting Exascale), MAGMA (Matrix Algebra on GPU and Multi-core Architectures), and KBLAS (KAUST BLAS). SLATE is used as a GPU-capable ScaLAPACK replacement. From MAGMA we use variable sized batched dense linear algebra operations such as GEMM, TRSM and LU with partial pivoting. KBLAS provides efficient (batched) low rank matrix compression for NVIDIA GPUs using an adaptive randomized sampling scheme. The resulting sparse solver and preconditioner runs on NVIDIA, AMD and Intel GPUs. Interfaces are available from PETSc, Trilinos and MFEM, or the solver can be used directly in user code. We report results for a range of benchmark applications, using the Perlmutter system from NERSC, Frontier from ORNL, and Aurora from ALCF. For a high frequency wave equation on a regular mesh, using 32 Perlmutter compute nodes, the factorization phase of the exact GPU solver is about 6.5× faster compared to the CPU-only solver. The BLR-enabled GPU solver is about 13.8× faster than the CPU exact solver. For a collection of SuiteSparse matrices, the STRUMPACK exact factorization on a single GPU is on average 1.9× faster than NVIDIA’s cuDSS solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Analysis of Air-Purifying Respirator (APR) and Powered Air-Purifying Respirator (PAPR) Cartridge Performance Testing on a Hanford AX Tank Farm Exhauster Slipstream Volume 1

Washington River Protection Solutions (WRPS) conducted tests of four types of chemical cartridges for air-purifying respirators (APR) and powered air-purifying respirators (PAPR) to determine the period of time the cartridges would provide adequate performance1 for APRs and PAPRs used to protect workers when exposed to a mixture of Chemicals of Potential Concern (COPCs) from vapors exiting the Hanford AX tank farm exhauster slipstream. The Occupational Safety and Health Administration (OSHA) considers cartridge testing to be a valid approach for establishing a cartridge service life. Testing is applied in situations where mixtures of COPCs exist, and where other approaches, such as manufacturer recommendations and modeling, are less reliable. The tests were designed and conducted to assure measurement and/or control of the key variables OSHA identified as important to estimate the cartridge service life, including temperature, humidity, COPC concentration, breathing rate, and cartridge adsorption capacity. Cartridge testing using vapors from a Hanford AX tank farm exhauster slipstream was conducted from August 25–27, 2017. Vapors from the exhauster slipstream were fed to two respirator cartridge test stands developed by WRPS in collaboration with HiLine Engineering (Richland, Washington). Four different cartridges were assessed. Multipurpose APR cartridges—SCOTT 7422-SD1 and SCOTT 7422-SC1 (SCOTT Safety, Monroe, North Carolina)—were assessed on separate days using an APR cartridge test stand. Multipurpose PAPR cartridges—MSA-TL (TL1) (MSA Safety Inc., Pittsburgh, Pennsylvania) and 3M FR57 (TL2) (3M Company, Maplewood, Minnesota)—also were tested over the same two days using a separate PAPR cartridge test stand. Sample media (i.e., sorbent tubes) were used to collect samples of the vapor stream entering and exiting the respirator cartridges and were subsequently analyzed for COPC concentrations. Pacific Northwest National Laboratory was tasked with conducting an independent analysis of the analytical results and making recommendations based on the results for respiratory cartridge performance and service life. The key conclusions from the analysis are described below.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Leak detection in a subcritical boiler

Thermal power plants experience cycling duty leading to the fatigue of the boiler and heat exchanger tubes. As a result, tube failures occur frequently in coal fired fleets leading to forced outages. Furthermore, because the tube leaks have been the major source of unwanted shutdowns and the number of outages is increasing, present work focuses on the detection and isolation of the leak in a subcritical boiler based upon the process data from a commercial coalfired power plant. The mass balance equation around the steam drum was analyzed using timeseries data collected from a 300 MW power plant. The ratio of the feed water mass flow rate to the steam mass flow rate was defined as a key parameter for detecting leaks. The difference in slope between the feedwater and steam mass flow rate during the normal and faulty operations was established as the upper control limit for real time monitoring. To reduce false alarm rates that arise when raw signal is directly compared against the threshold due to common process fluctuations, an optimal filter was derived for smoothing. It was found that the optimal filter reacted much more quickly to process changes than an exponential moving average filter, around 8 h earlier on average. Occurrence of relatively high false alarm rates even in the filtered responses was related to the cycling of the boiler from the base load condition. Variable threshold was established to keep false alarm rates to the minimum while maintaining the leak detection rate. Finally, the leak was located at the economizer and this could readily be isolated by investigating the magnitude of the mass flow rates ratio and the temperature at the economizer outlet.

42 ENGINEERING↗
DOE OSTI2020

Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral system

Complex social-ecological systems can be difficult to study and manage. Simulation models can facilitate exploration of system behavior under novel conditions, and participatory modeling can involve stakeholders in developing appropriate management processes. Participatory modeling already typically involves qualitative structural validation of models with stakeholders, but with increased data and more sophisticated models, quantitative behavioral validation may be possible as well. In this study, we created a novel agent-basedmodel applied to a specific context: Zimbabwean non-governmental organization the Muonde Trust has been collecting data on their agro-pastoral system for the last 35 years and had concerns about land-use planning and the effectiveness of management interventions in the face of climate change. We collaboratively created an agent-based model of their system using their data archive, qualitatively calibrating it to the observed behavior of the real system without tuning any parameters to match specific quantitative outputs. We then behaviorally validated the model using quantitative community-based data and conducted a sensitivity analysis to determine the relative impact of underlying parameter assumptions, Indigenous management interventions, and different rainfall variation scenarios. We found that our process resulted in a model which was successfully structurally validated and sufficiently realistic to be useful for Muonde researchers as a discussion tool. The model was inconsistently behaviorally validated, however, with some model variables matching field data better than others. We observed increased model system instability due to increasing variability in underlying drivers (rainfall), and also due to management interventions that broke feedbacks between the components of the system. Interventions that smoothed year-to-year variation rather than exaggerating it tended to improve sustainability. The Muonde trust has used the model to successfully advocate to local leaders for changes in land-use planning policy that will increase the sustainability of their system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

VotE-Dams: a compilation of global dams' locations and attributes (v1)

This dataset represents a compilation of two global and three USA-specific datasets of dam locations and their attributes. The major hurdle toward developing this compilation was the identification of duplicates within the source datasets, especially given the variable precision of dam location coordinates. The most immediately-useful product in this dataset is a spreadsheet (VotE-Dams_v1.csv) that documents the unique dams found across the datasets, their coordinates, and their ids within the respective source datasets. We do not reproduce the source datasets (GRaND, GOODD, GeoDAR, NID, and EHA) here, but their download locations are provided in the README files ('Overview' tab). Some of the source datasets are provided as shapefiles, which require geospatial data software to open (e.g. QGIS/ArcGIS for graphical display, geopandas for Python, rgdal for R, many others freely available). The provided README documents metadata of the source datasets and provides attribute-linking information (i.e. matches attributes among various source datasets that contain the same, or similar, information but have different names). Note that the README is provided as both .xslx and a collection of .csvs (one per tab in the .xslx file). We suggest using the .xlsx version that preserves images, formatting, and sheets. .xlsx files can be viewed using (free) Google Docs or Microsoft Excel.Finally, we provide Technical Documentation.pdf that describes the procedures used to identify unique and duplicate dams.The title of this dataset refers to our 'Veins of the Earth' (VotE) project, which seeks to provide a flexible, scale-free representation of the Earth's river networks. Dams are a critical component of VotE as they heavily influence flows throughout river networks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Field Validation of Air-Source Heat Pumps for Cold Climates

Heating energy is the largest end-use for U.S. residential buildings accounting for approximately one-third of residential building energy consumption (EIA 2021). Historically, air-source heat pumps have been limited to temperate climates because of subpar performance at extremely cold outdoor air temperatures. However, recent advances to cold-climate air-source heat pump technology, which typically rely on inverter-driven, variable-speed compressors and variable-speed fans, have significantly improved low-temperature heat pump performance enabling the technology to save energy for many homes in cold climates. The primary objective of this project was to measure in-field performance of centrally ducted, variable-capacity air-source heat pumps in cold climates to validate performance and develop field-based performance maps. The project focused on quantifying heat pump performance at cold temperatures. The sites identified for the study were primarily located in the Northwest United States since homes in the region tend to have all-electric space heating systems and high-efficiency heat pumps have been incentivized in the region for several years. NREL partnered with Ecotope, Inc., a small energy consulting firm located in Seattle, WA, for site recruitment, monitoring equipment installation, data quality management. All the sites included in the study had previously installed a high-efficiency, central heat pump system. One site was in a Denver, CO suburb, which was the only dual fuel heat pump in the study. We used airside and power measurements, collected at 5-second intervals, to quantify heat pump capacity, coefficient of performance (COP), and auxiliary heater energy consumption. We developed algorithms to automatically determine the heat pump operating mode including defrost and auxiliary heating operation. A whole-house thermal and duct audit was completed during the initial site visit to estimate winter heating loads and assess heat pump sizing. Whole-home heating design loads were calculated at ASHRAE 99% design temperatures and compared to manufacturer-reported maximum capacities to assess the heat pump sizing at each site.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Local-Scale Framework for Techno-Economic Analysis of Subsurface Hydrogen Storage

The energy sector is evolving toward increased reliance on renewable energy technologies to meet state, national, and organization decarbonization goals. This trend is creating challenges and opportunities with meeting current and future energy demand under the variable supply conditions that most renewables provide. Hydrogen (H 2 ) is a promising energy carrier that may meet the need for both on-demand and long-duration storage to maintain energy security and resilience. Underground hydrogen storage (UHS) is a method of storing H 2 in subsurface geological systems, such as depleted hydrocarbon reservoirs, salt caverns, saline aquifers, hard rock, and other engineered systems. UHS has the potential to store large quantities of H 2 over time, providing a reliable source of energy while minimizing surface footprints at a lower investment cost compared to surface storage. Earlier work estimated that, if converted and retrofitted, existing underground natural gas storage (UGS) facilities in the U.S. can store approximately 327 TWh, or 9.8 million metric tons, of pure H 2 . However, a shift to pure H 2 would decrease the collective working-gas energy of the UGS facilities by approximately 75% due to physical and chemical differences between natural gas and hydrogen. The same work also suggests that almost 75% of the existing UGS facilities in the U.S. could maintain current energy demand buffering using a blend of only 20% H 2 to 80% natural gas, by volume at surface conditions. If we can take advantage of the suite of mature technologies of existing UGS facilities and natural gas utility systems to accelerate the transition to a hydrogen economy in the U.S., a 20% H 2 blend could lead to a 6-7% reduction of greenhouse gas emissions for energy delivered through natural gas utility systems.

03 NATURAL GAS↗
DOE OSTI2024

Rhenium Isotope Reconnaissance of Uranium Ore Concentrates

Exploration of natural isotopic variations of the element rhenium (Re) is in its infancy, with initial studies revealing isotopic fractionation in a variety of geological materials. Here, in this work, we investigate Re isotope variation as a new geochemical tool, given its redox-sensitive properties and affinity for organic matter and sulfides. In this work, Re abundance and isotope ratio data were collected from uranium ore concentrates (UOCs) across a variety of depositional ages, locations, geologic settings, and deposit types. Ore types from which the UOC were derived include sandstone, unconformity, and quartz-pebble (QP) conglomerate. To isolate Re from the U-rich matrix of UOCs, a new purification method utilizing DGA ion exchange resin was developed. We found that UOCs exhibit a wide range of Re isotope ratios, with sandstone ore-derived UOCs having the isotopically lightest values, QP conglomerate ore-derived UOCs having the heaviest, and unconformity ore-derived UOCs in between (with some overlap with sandstone UOCs). The Re isotope ratio range observed in UOCs extends previously reported values by more than a factor of two. Industrial processing (e.g., incomplete recovery of Re from ore, contamination, fractionation during processing) may play a role in the isotopic variability in the UOCs. However, systematic differences between ore types suggest that the depositional setting is a significant factor. For nuclear forensic investigations, Re isotopic compositions combined with data from other isotopic systems provide geochemical signatures that can aid in provenance assessment of UOCs. Regardless of the specific causes for the wide range of Re isotope ratios in UOCs, these initial data indicate Re is a promising tool for nuclear forensic investigations on samples from early in the nuclear fuel cycle.

58 GEOSCIENCES↗
DOE OSTI2020

Imprecise global sensitivity analysis using bayesian multimodel inference and importance sampling

Global Sensitivity Analysis (GSA) aims to understand the relative importance of uncertain input variables to model response. Conventional GSA involves calculating sensitivity (Sobol’) indices for a model with known model parameter distributions. However, model parameters are affected by aleatory and epistemic uncertainty, with the latter often caused by lack of data. In this paper, we propose a new framework to quantify uncertainty in probability model-form and model parameters resulting from small datasets and integrate these uncertainties into Sobol’ index estimates. First, the process establishes, through Bayesian multimodel inference, a set of candidate probability models and their associated probabilities. Imprecise Sobol’ indices are calculated from these probability models using an importance sampling reweighting approach. This results in probabilistic Sobol’ indices, whose distribution characterizes uncertainty in the sensitivity resulting from small dataset size. The imprecise Sobol’ indices thus provide a measure of confidence in the sensitivity estimate and, moreover, can be used to inform data collection efforts targeted to minimize the impact of uncertainties. Through an example studying the parameters of a Timoshenko beam, we show that these probabilistic Sobol’ indices converge to the true/deterministic Sobol’ indices as the dataset size increases and hence, distribution-form uncertainty reduces. The approach is then applied to assess the sensitivity of the out-of-plane properties of an E-glass fiber composite material to its constituent properties. This second example illustrates the approach for an important class of materials with wide-ranging applications when data may be lacking for some input parameters.

42 ENGINEERING↗
DOE OSTI2023

The inclusion of uncertainty in circularity transition modeling: A case study on wind turbine blade end-of-life management

The transition to a more circular economy (CE) is complex and hard to predict, including in sustainable energy technologies. Many sources of uncertainty make it challenging to model CE scenarios and their potential benefits. As an example, the high variability in costs and revenues of different recycling options makes future wind turbine blade recycling highly uncertain. To better understand this challenge, the circular economy, life cycle assessment and visualization (CELAVI) framework - a discrete event simulation and life cycle assessment framework - is modified to incorporate uncertainty analysis capabilities. Moreover, a 3-step procedure that covers different aspects of uncertainty in CE studies and includes a Monte-Carlo analysis is proposed. The procedure is tested in a case study on wind turbine blade recycling using CELAVI. Results highlight that grinding and landfilling costs are the most influential parameters for wind power circularity. The model's output coefficients of variation (when input parameter uncertainties are propagated) are between 92% and 384% depending on the indicator. The approach developed in this study may help researchers and decision-makers who study circularity prioritize their data collection effort. Finally, our method contributes to a mounting yet critical body of research: the measurement of uncertainty in circularity transitions.

17 WIND ENERGY↗
DOE OSTI2020

Rapid Determination of Uranium Isotopic Abundance from Cotton Swipes: Direct Extraction via a Planar Surface Reader and Coupling to a Microplasma Ionization Source

The collection of solid particulates and liquids from surfaces by the use of cloth swipes is fairly ubiquitous. In such methods, there is a continuous concern regarding the ability to locate and quantitatively sample the analyte species from the material. In this effort, we demonstrate the initial coupling of an Advion Plate Express plate reader to a liquid sampling–atmospheric pressure glow discharge (LS-APGD) microplasma ionization source with an Orbitrap mass spectrometer to perform uranium isotopic analyses of solution residues on cotton swipes. The Plate Express employs a sampling probe head to engage and seal against the swipe surface. Subsequentially, the analyte residues are desorbed and transported within a 2% HNO 3 electrolyte flow to the ionization source. Quantitative recoveries were observed following a single 30 s extraction step, with the absolute mass sampled per extraction being ~100 ng. While the intrasample variability in the analytical responses for triplicate sampling of the same swipe yield ~30% RSD, this lack of precision is offset by the ability to determine isotope ratios for enriched uranium specimens with a precision of better than 10% RSD. Pooled, intersample precision ( n = 9) was found to be <5%RSD across the various sample compositions. Finally, 235 U/ 238 U determinations (ranging from 0.053 to 1.806) were accurate with errors of <10%, absolute. The 234 U- and 236 U-inclusive ratios were determined with similar accuracy in enriched samples. While the driving force for the effort is in the realm of nuclear nonproliferation efforts, the ubiquitous use of cloth swipes across many application areas could benefit from this convenient approach, including the use of versatile, reduced-format mass spectrometer systems.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Dynamic regulation of water potential in Juniperus osteosperma mediates ecosystem carbon fluxes

Summary Some plants exhibit dynamic hydraulic regulation, in which the strictness of hydraulic regulation (i.e. iso/anisohydry) changes in response to environmental conditions. However, the environmental controls over iso/anisohydry and the implications of flexible hydraulic regulation for plant productivity remain unknown. InJuniperus osteosperma, a drought‐resistant dryland conifer, we collected a 5‐month growing season time series ofin situ, high temporal‐resolution plant water potential () and stand gross primary productivity (GPP). We quantified the stringency of hydraulic regulation associated with environmental covariates and evaluated how predawn water potential contributes to empirically predicting carbon uptake. Juniperus osteospermashowed less stringent hydraulic regulation (more anisohydric) after monsoon precipitation pulses, when soil moisture and atmospheric demand were high, and corresponded with GPP pulses. Predawn water potential matched the timing of GPP fluxes and improved estimates of GPP more strongly than soil and/or atmospheric moisture, notably resolving GPP underestimation before vegetation green‐up. Flexible hydraulic regulation appears to allowJ. osteospermato prolong soil water extraction and, therefore, the period of high carbon uptake following monsoon precipitation pulses. Water potential and its dynamic regulation may account for why process‐based and empirical models commonly underestimate the magnitude and temporal variability of dryland GPP.

Plant Sciences↗
DOE OSTI2024

Generating An Advanced Cross-section Library For HTGR Pebble Bed Depletion Calculations Using Reduced-Order Model Generation Techniques

For code development, Advanced Reactor Technologies - Gas Cooled Reactors Program (ART-GCR) rely on a collaboration with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, but the cross sections generation and the methodology definition is part of this program area goals. Based on previous studies in FY23, the size of microscopic cross section libraries increases rapidly with the number of tabulations, requiring significant amount of memory and drastically slowing down the Griffin calculations when evaluating cross sections via the multivariate linear interpolation approach. Rising to these challenges, this work investigates constructing Reduced-order Models (ROMs) for the multi-group microscopic cross sections to accelerate the cross section evaluation in Griffin. A database of multigroup cross sections is first collected considering all possible parameters that a designer could change for optimization. Down-selection of the ROM techniques afterward shows Deep Neural Network (DNN) as the best candidate when jointly consider memory efficiency, predictive accuracy, computational cost, scalability, flexibility and ease of implementation of the algorithms in comparison to the multidimensional interpolation. This work develops a specific interface that enables the cross section predictions using pre-trained DNN models into Griffin leveraging the existing ROM capabilities. DNNs have been trained for all isotopes for use in Griffin. Preliminary Griffin testing shows that DNNs exhibit exceptional predictive accuracy and the use of DNNs provides orders of magnitude improvement in memory efficiency compared to conventional interpolation techniques. With such ROM techniques, it holds great promise to further increase the fidelity of the Pebble Bed Reactor (PBR) simulation by increasing the number of tabulations/state variables during cross section evaluation, while maintaining the computational cost affordable in Griffin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Measurements and interpretations of W ± Z production cross-sections in pp collisions at $\sqrt{s}=13$ TeV with the ATLAS detector

Measurements of integrated and differential cross-sections for W ± Z production in proton-proton collisions are presented. The data collected by the ATLAS detector at the Large Hadron Collider from 2015 to 2018 at a centre-of-mass energy of $\sqrt{s}=13$ TeV are used, corresponding to an integrated luminosity of 140 fb −1 . The W ± Z candidate events are reconstructed using leptonic decay modes of the gauge bosons into electrons or muons. The integrated cross-section per lepton flavour for the production of W ± Z is measured in the detector fiducial region with a relative precision of 4%. The measured value is compared with the Standard Model prediction at a precision of up to next-to-next-to-leading-order in QCD and next-to-leading-order in electroweak. Cross-sections for W + Z and W − Z production and their ratio are presented. The W ± Z production is also measured differentially as functions of various kinematic variables, including new observables sensitive to CP-violation effects. All measurements are compared with state-of-the-art Standard Model predictions from fixed-order calculations or Monte Carlo generators based on next-to-leading-order matrix elements interfaced with parton showers. An effective field theory interpretation of the measurements is performed, considering both CP-conserving and CP-violating dimension-6 operators modifying the W ± Z production. In the absence of observed deviations from the Standard Model, limits on CP-conserving Wilson coefficients are extracted using the transverse mass of the W ± Z system. For CP-violating coefficients a machine learning approach is used to construct an observable with enhanced sensitivity to CP-violation effects.

hadron-hadron scattering↗