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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1°×0.1°), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of -3.96 and -0.71 W m -2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m -2 , respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Floor and ceiling effects in the EORTC QLQ-C30 Physical Functioning subscale among patients with advanced or metastatic breast cancer

The European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 30 Physical Functioning subscale is a widely used patient-reported outcome measure that quantifies cancer patients' physical functioning. Strong floor/ceiling effects can affect a scale's sensitivity to change. The aim of this study was to characterize floor/ceiling effects of the physical functioning domain in patients with advanced/metastatic breast cancer enrolled in commercial clinical trials and a community-based trial. The clinical trial cohort comprised patients from 5 registrational trials submitted to the Food and Drug Administration for review (2010-2017). The community cohort comprised a subgroup of patients from the Alliance Patient Reported Outcomes to Enhance Cancer Treatment (PRO-TECT) trial. The distribution of patient responses to Physical Functioning items and the summed score were assessed at the baseline and 3-month follow-up for both cohorts. Descriptive statistics were used to determine floor/ceiling effects at the item and scale levels. The clinical trial cohort and the community cohort consisted of 2407 and 178 patients, respectively. Twenty-four percent or more of the respondents reported “not at all” for having trouble/needing help with each Physical Functioning item across both cohorts and measurement time points. Fourteen to twenty percent of the patients scored perfectly (100 of 100) on the Physical Functioning subscale summary measure (where higher scores indicated better physical functioning) across both cohorts and time points. Minor floor effects and notable ceiling effects were found at the item and scale levels of the Physical Functioning subscale, regardless of cohort, and this creates some uncertainty about its ability to detect changes in physical functioning among high-functioning patients. In conclusion, investigators may consider adding additional high-functioning items from the EORTC's item library to more accurately describe the impact of anticancer treatment on patients' physical functioning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Field Evaluation of the High Efficiency Dehumidification System (HEDS) at the Timken Museum of Art - Measurement and Verification (M&V) Results from Summer, Winter and Spring Evaluation Periods

The High Efficiency Dehumidification System (HEDS) technology from Conservant Systems Inc., installed at the Timken Museum of Art in San Diego, California, was evaluated to determine its performance relative to appropriate baseline operation. Data was collected for measurement and verification for several weeks during three evaluation periods: Summer (Aug-Sep 2023), Winter (Dec 2023-Feb 2024) and Spring (May-Jun 2024). The evaluation included operating the heating, ventilation and air conditioning (HVAC) system in both constant air volume (CAV) and variable air volume (VAV) modes, with and without the HEDS energy recovery and HVAC system optimization technology enabled. The electricity consumption of the chiller and the gas-supplied reheat energy were measured to characterize savings achieved by the HEDS operation. Based on these measurements, the HEDS was responsible for chiller electrical load savings during the summer evaluation period of 39% and 42% for the CAV and VAV operating modes, respectively; 97% and 100% chiller electrical load reductions were observed during the winter evaluation for the CAV and VAV operating modes, respectively; and the corresponding reductions during the spring evaluation were 42% and 52% for CAV and VAV operation, respectively. The measured reheat energy reductions, which are typically provided by natural gas, due to the HEDS during summer were 64% and 97% in CAV and VAV operating modes, respectively, while the corresponding values were 99% and 78% during the winter evaluation, and 59% and 56% during the spring evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment

Distributed wind projects, which are connected at the distribution level of an electricity system or in off-grid applications to serve specific or local energy needs, often rely solely on wind resource models to establish wind speed and energy generation expectations. Historically, anemometer loan programs have provided an affordable avenue for more accurate onsite wind resource assessment, and the lowering cost of lidar systems has shown similar advantages for more recent assessments. While a full 12 months of onsite wind measurement is the standard for correcting model-based long-term wind speed estimates for utility-scale wind farms, the time and capital investment involved in gathering onsite measurements must be reconciled with the energy needs and funding opportunities that drive expedient deployment of distributed wind projects. Much literature exists to quantify the performance of correcting long-term wind speed estimates with 1 or more years of observational data, but few studies explore the impacts of correcting with months-long observational periods. This study aims to answer the question of how short you can go in terms of the observational time period needed to make impactful improvements to model-based long-term wind speed estimates. Three algorithms, multivariable linear regression, adaptive regression splines, and regression trees, are evaluated for their skill at correcting long-term wind resource estimates from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) using months-long periods of observational data from 66 locations across the US. On average, correction with even 1 month of observations provides significant improvement over the baseline ERA5 wind speed estimates and produces median bias magnitudes and relative errors within 0.22 m s −1 and 4 percentage points of the median bias magnitudes and relative errors achieved using the standard 12 months of data for correction. However, in cases when the shortest observational periods (1 to 2 months) used for correction are not well correlated with the overlapping ERA5 reference, the resultant long-term wind speed errors are worse than those produced using ERA5 without correction. Summer months, which are characterized by weaker relative wind speeds and standard deviations for most of the evaluation sites, tend to produce the worst results for long-term correction using months-long observations. The three tested algorithms perform similarly for long-term wind speed bias; however, regression trees perform notably worse than multivariable linear regression and adaptive regression splines in terms of correlation when using 6 months or less of observational data for correction. Translating the analysis to wind energy, median relative errors in the capacity factor are on average within 10 % using 1 month of training. If the observation period used for correction is not well correlated with the reference data, however, misrepresentation of the observed capacity factor can be substantial. The risk associated with poor correlation between the observed and reference datasets decreases with increasing training period length. In the worst-correlation scenarios, the median capacity factor relative errors from using 1, 3, and 6 months are within 47 %, 26 %, and 16 %, respectively.

17 WIND ENERGY↗
DOE OSTI2026

SBND Shower Reconstruction with SPINE

The Short-Baseline Near Detector (SBND) is a liquid argon time projection chamber (LArTPC) neutrino detector in the Short-Baseline Neutrino (SBN) program at Fermilab. SBND is designed to investigate the Low-Energy Excess (LEE), an unexplained excess of electron-like events observed by previous short-baseline neutrino experiments that may point to physics beyond the Standard Model. In LArTPC detectors, precise shower reconstruction is essential for distinguishing electrons from photons, a key requirement for testing possible explanations of the LEE and improving $\nu_e$ event selection. In this poster, the reconstruction studies using the Scalable Particle Imaging with Neural Embeddings (SPINE), a machine learning based reconstruction framework for particle imaging detectors will be presented. SPINE combines sparse convolutional neural networks (CNN) and graph neural networks (GNN) to enable detailed reconstruction and characterization of neutrino interactions in LArTPC detectors. Shower calorimetry and kinematic reconstruction are performed in dedicated post-processing stages. Strong agreement between data and Monte Carlo simulation will be demonstrated, indicating high-precision detector calibration and reconstruction performance. The agreement between reconstructed and true electron shower energy will also be discussed, emphasizing the robustness of the shower reconstruction performance. These results demonstrate the unprecedented precision achievable with SPINE in SBND, highlighting their potential for future high-resolution neutrino measurements.

Fan, Castaly [Florida U.; Fermilab] (ORCID:0000000↗
DOE OSTI2020

In situ monitoring of the stopped muon flux at Mu2e

The specific object of Mu2e search is the neutrino-less coherent $\mu^-\rightarrow e^-$ conversion in the field of an aluminum nucleus and the signal is a monoenergetic electron of energy $ \approx 104.97$ MeV. This process is forbidden in the Standard Model but allowed in many of its extensions: with minimal changes to include neutrino masses and oscillation, the Branching Ratio of this process, or the similarly interesting $\mu\rightarrow e \gamma$ decay, is expected to be of the order of $\mathcal{O}(10^{-54})$. Values like these are below any currently achievable experimental sensitivity, and the observation of a signal would be unambiguous evidence of New Physics. The upper limit on the muon conversion was set by SINDRUM II at $7\times10^{-13}$ (90\% C.L.) and the goal of the Mu2e collaboration is an improvement of 4 order of magnitudes.\\ The Mu2e experiment can be conceptually divided into three stages: interaction of the primary proton pulse with the tungsten target a nd production of $\pi$ and $\mu$; collection and transport of the produced particles down to the aluminum stopping target; interaction with the stopping target and measurement of the output particles. The measurement of the stopped muon flux is of cardinal importance for the normalization of the Mu2e results. The baseline design includes two detectors developed to measure this flux, counting $\gamma$ emitted by the muonic atoms: HPGe and LaBr$_3$(Ce). The studies performed by the Mu2e Collaboration show that these two systems can be reliably used to determine the overall normalization.\\ The number of stopped muons is proportional to the number of protons on target, which itself depends on the extraction system for the proton beam. The Mu2e beam delivery system will use a resonant extraction to create the proton pulses and this method is characterized by intensity fluctuations on the time scale of milliseconds. These fluctuations, aside from the proportional fluctuation of t he number of muons, have a non-trivial impact on the overall! performance of the apparatus. For example, higher intensity proton bunches translate into higher veto rates by the Cosmic Rays Veto system, which is triggered by secondary particles generated by the proton interaction. Another example is the effect of the instantaneous luminosity on the reconstruction efficiency: higher intensity translates into higher detector occupancy, which in turn reduces the reconstruction efficiency.\\ The two cited detectors encounter limitations when trying to monitor the flux at the millisecond timescales: HPGe is by construction a slow detector while the rate of emission of the $\gamma (1809\textrm{ keV})$ the LaBr$_3$(Ce) will measure is too low. As of today, no system allows to monitor these fluctuations and the goal of this Thesis is to try filling this gap. The method we developed to monitor the fluctuations of the stopped muon flux, and by extension, the fluctuation in the proton pulses intensity is based on counting the number of muons capt ured in the stopping target by counting the number of protons produced in the process of the nuclear muon capture. This is one of the possible processes a stopped muon can undergo and it can lead to the ejection of charged particles.\\ The reconstruction algorithms were developed by the Mu2e collaboration with the explicit (and sometimes implicit) aim to reconstruct tracks of electrons in an energy range of a conversion electron. The protons we are interested in behave quite differently from these electrons and the cardinal task of this study has been to tailor the reconstruction routines to these particles. This has been done by analyzing simulated events consisting of a single proton to optimize the procedure and understand the features of these tracks. A major difference with respect to the electrons is the non-relativistic nature of $100\div300$ MeV$/c$ protons: accounting for the low velocity is both a challenge and a unique signature of the tracks.\\ The use of a pulse d beam and the need to allow produced $\pi$ to decay and $\m! u$ to int! eract in the stopping target forces the definition of a Mu2e \textit{event}: an event is comprised by everything which happens in a $1.7\ \mu$s window between the incidence two consecutive proton pulses. This means that the reconstruction will be performed in an environment crowded by many different particles. The next step of this study has been to estimate the performance of the method in a fully-fledged Mu2e simulated event and to study what kind of selections would improve it.\\ Our results are satisfactory since the number of reconstructed protons is significant (few per event), and show that a monitor on the timescale of milliseconds is indeed possible.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

High-Fluence Active Irradiation and Combined Effects Testing of Sapphire Optical Fiber Distributed Temperature Sensors

The goal of this work was to investigate the in-core performance of sapphire optical fiber temperature sensors and to develop clad sapphire optical fibers for in-core instrumentation. We fabricated clad sapphire optical fibers and evaluated the distributed sensing performance of these sensors via optical backscatter reflectometry under high fluence and combined radiation and temperature effects. A series of irradiations was completed to evaluate the effect of irradiation on sapphire optical fiber temperature sensors and to determine the operational limits of these sensors. (1) Objective 1: Fabricate sapphire optical fiber sensors. (2) Objective 2: Evaluate the clad sapphire fiber to verify single-mode behavior and determine and characterize the light modes supported by optical fibers. (3) Objective 3: Characterize the in-core temperature sensing of sapphire optical fiber, as well as the combined temperature and irradiation effects. (4) Objective 4: Evaluate the lifetime and performance of the sensor under irradiation to high neutron fluence. Objectives 1, 2, and 3 were completed during the first 2 years of the project. Due to the Covid pandemic, Objective 4, a high-fluence irradiation performed at the Massachusetts Institute of Technology Research Reactor (MITR), was delayed, as partner facilities were subject to mandatory shutdowns and required a 1 year, no-cost extension. This irradiation was eventually completed on December 12, 2022. This work indicates that sapphire optical fiber sensors may be a solution for ultra-high-temperature applications in which traditional silica optical fibers are prone to fail. Sapphire sensors are potentially suitable for experiments featuring temperatures above 700°C for long periods of time, or for any length of time above 1000°C. Experiments featuring a low total fluence, such as irradiations conducted in the Transient Reactor Test (TREAT) facility, also represent good applications for sapphire optical sensors. Additional work is required to characterize the sapphire fiber cladding performance, which falls outside the scope of this project, as well as the effects of high temperatures on the response of the fiber. A comprehensive material study is recommended as future work to evaluate the attenuation in sapphire under irradiation, and how that attenuation changes with irradiation temperature. The drift and attenuation in the fiber at temperatures of up to 1600°C and a total fluence of up to 2.9 x 10 17 n/cm 2 was minimal, and the fibers returned to baseline after being heated to 1600°C under irradiation. This is promising for the future use of sapphire optical fibers in advanced reactors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Characterization of UV optical components for photon detector calibration in liquid argon TPCs

Large liquid argon time projection chambers (LArTPCs)require stable and well-characterized delivery of ultraviolet (UV)light for in situ calibration of photosensors at cryogenictemperatures. This article reports bench-top and cryogenicmeasurements of the optical components used in a UV lightcalibration system, including multi-mode fused-silica fibers,SMA-to-SMA connectors, optical fiber feedthroughs, andlight-diffuser assemblies. Light loss in several fiber types and SMAconnectors was measured across wavelengths from275–970 mm. In addition,light-loss measurements of the tested fibers after severalliquid-nitrogen thermal cycles showed no statistically significantdegradation relative to baseline measurements, and high-rate pulsedexposure (30–90 million pulses from a275 nm LED) likewise showed nomeasurable aging in jacketed fibers. A compact, palm-sized,3D-printed PEEK diffuser housing with stacked UV-grade fused-silicadiffusers yields Lambertian emission and the most uniform angulardistribution. Optical components exhibiting improved UV transmissionwere deployed successfully in multiple DUNE small- and large-scaleprototypes, demonstrating reliable operation of UV light calibrationsystem. These findings inform component selection and calibrationprocedures for achieving reliable, uniform UV light delivery inlarge-scale cryogenic detectors such as DUNE.

Behera, B. [South Dakota Sch. Mines Tech.] (ORCID:↗
DOE OSTI2023

Integration of Computational Docking into Anti-Cancer Drug Response Prediction Models

Cancer is a heterogeneous disease in that tumors of the same histology type can respond differently to a treatment. Anti-cancer drug response prediction is of paramount importance for both drug development and patient treatment design. Although various computational methods and data have been used to develop drug response prediction models, it remains a challenging problem due to the complexities of cancer mechanisms and cancer-drug interactions. To better characterize the interaction between cancer and drugs, we investigate the feasibility of integrating computationally derived features of molecular mechanisms of action into prediction models. Specifically, we add docking scores of drug molecules and target proteins in combination with cancer gene expressions and molecular drug descriptors for building response models. The results demonstrate a marginal improvement in drug response prediction performance when adding docking scores as additional features, through tests on large drug screening data. We discuss the limitations of the current approach and provide the research community with a baseline dataset of the large-scale computational docking for anti-cancer drugs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Evidence for ionization damage in mid-wave infrared nBn detectors

The effects of 63 MeV proton and 60Co gamma irradiation on the operation of 4.3 μm cutoff nBn photodetectors are demonstrated separately, and both are shown to yield a total ionizing dose (TID) effect. The effect is shown here in an InAsSbBi nBn detector and has been observed in other bulk alloy nBn detectors, and is unusual as it is notably absent in superlattice nBn detectors. The non-antireflection coated detectors exhibit a pre-radiation quantum efficiency of 17% at 3.3 μm wavelength and a dark current density of 50 μA/cm2, or roughly 300× the Rule 07 expectation, at their ideal operating voltage of −0.4 V bias at 150 K. Step-wise proton irradiation and in situ measurement indicate that the dark current increases to about 400× Rule 07 at the highest proton dose level of 150 krad(Si) (9.10 × 1011 p+/cm2), while the quantum efficiency is degraded at a relatively faster rate than the majority of analogous detectors characterized by our lab. Both the photocurrent and dark current are also shown to exhibit a turn-on voltage magnitude reduction of 100 mV following either gamma or proton irradiation, a trend which is attributable to negative trapped charge at the barrier interface (TID effect). This theory is further supported by an observed capacitance density magnitude reduction with dose and affirmed with Silvaco TCAD simulations. Following both proton exposure and subsequent anneal and gamma exposure and subsequent anneal; dark current, photocurrent, and CV all approach their pre-radiation baseline values.

Physics↗
DOE OSTI2024

Characterization of Flex-Fuel Prechamber Enabled Mixing-Controlled Combustion With Gasoline/Ethanol Blends at High Load

This numerical study focuses on the characterization of prechamber-enabled mixing-controlled combustion (PC-MCC) at ~18 bar brake mean effective pressure (BMEP) and 2200 rpm with 10% by volume ethanol-gasoline blend (E10) and pure ethanol (E100). Computational fluid dynamic (CFD) simulations of a stock and prechamber retrofitted single-cylinder Caterpillar C9.3B are carried out using CONVERGE. Prechamber equivalence ratio at spark timing, prechamber spark timing advance, and main chamber injection strategy are assessed with respect to their impact on ignition assistance performance and emissions characteristics relative to a diesel baseline at the same boundary conditions. Simulation results indicate that PC-MCC is flex-fuel capable and operates well for both E10 and E100 at the operating conditions considered. The results demonstrate that the use of a pilot-main injection strategy enables spark timing in the prechamber to be advanced and thus reduces spark plug firing pressure while maintaining robust ignition assistance. Results also indicate that the rich prechamber operation is favored for improved ignition assistance capabilities. Furthermore, the findings of this work suggest that a heavy-duty vehicle using a PC-MCC engine can utilize any blend of gasoline and ethanol, up to including pure ethanol, with no major sacrifices in performance relative to the diesel engine.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Range Hood Use and Effectiveness in Reducing Indoor Air Pollution During Gas and Induction Cooking

The Cooking Energy and Ventilation Impacts on Children's Asthma (CEVICA) study measured cooking frequency, range hood use, indoor air quality and respiratory health indicators of children with asthma living in homes with gas stoves in California's San Joaquin Valley. The study installed electric induction stoves and repeated measurements over three 2-week intensive periods, at baseline and at the end of two consecutive 3-month study phases. Stove replacements occurred at the start of Phase 1 or Phase 2 by random assignment. There were 4184 cooking events identified by automated analysis of time-series data from temperature sensors mounted above the cooktops and 1038 related range hood usage events detected from data recorded by anemometers, smart plugs, or motor loggers. Analysis of 1-minute resolved PM2.5 and NO 2 data identified and quantified 2685 PM 2.5 events and 2606 NO 2 events. Range hood use was characterized as a binary variable (>3 min vs. <3 min use). Range hood use was more common during cooking events associated with particle emissions and longer cooking durations. PM 2.5 concentrations during events with range hood use were comparable to those without use, which could result from limited effectiveness or if range hoods were preferentially used during higher-emission cooking scenarios. In homes with gas cooking, integrated NO 2 concentrations were about 45 percent higher during cooking events with no range hood use compared to those range hood use. The lowest pollutant levels were observed when the range hood operated for more than half of the cooking duration. These findings show that operation of venting range hood during cooking can substantially reduce short-term indoor exposure NO 2 in homes with gas cooking.

Fang, Yi↗
DOE OSTI2022

Speaker-targeted Synthetic Speech Detection

Text-to-speech technologies are evolving quickly towards realistic-sounding human-like voices. As this technology improves, so does the opportunity for malpractice in speaker identification (SID) via spoofing, the process of impersonating a voice biometric via synthesis. More data typically equates to a more realistic voice model, which poses an issue for well-known subjects, such as politicians and celebrities, who have vast amounts of multimedia available online. Detection of synthetic speech has relied on signal processing techniques that focus on the generation of new acoustic features and train deep learning models to detect when an audio file has been manipulated through the characterization of unnatural changes or artifacts. However, these techniques do not use any information from the speaker they are evaluating. This paper proposes to incorporate information from the speaker-of-interest (SoI) into the models to avoid specific spoofing attacks for certain vulnerable people. The wealth of data for well-known people can also be used to train a speaker-specific spoofing detector with a higher level of accuracy than a speaker-independent model. The paper proposes a new xResNet-PLDA system and compares it to three different baseline systems: a state-of-the-art speaker identification system, an xResNet system trained to discriminate between bona fide and fake speech, and a speaker identification system in which the PLDA and calibration models were trained with bona fide and fake speech. We evaluated the systems in two different scenarios — a cross-validation scenario and a hold-out scenario — with three different databases. We show how the proposed system outperforms dramatically the baseline systems in each scenario and for each database. Finally, we show how using a small amount of the SoI’s speech to adapt global calibration parameters improves the performance of the system, especially in unseen conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

The NuMI Flux Prediction at ICARUS

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment seeking to probe fundamental symmetries within the structure of the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) mixing matrix, and perform precision measurements its parameters including the neutrino mass ordering via the sign of $\Delta m^2_{31}$, and the charge-parity violating phase, $\delta_{CP}$. To make these measurements with high precision, DUNE will require external $\nu$-Ar scattering cross section data as a crucial input to the oscillation fit. Imaging Cosmic And Rare Underground Signals (ICARUS) is a 476 t liquid argon neutrino detector located at Fermi National Accelerator Laboratory (FNAL) where it is serving as the far detector for the Short-Baseline Neutrino (SBN) program along the Booster Neutrino Beam (BNB) axis. ICARUS additionally lies 795 m downstream and 100.1 mrad off-axis of the Neutrinos at the Main Injector (NuMI) neutrino beam. From this position, ICARUS is exposed to a large flux of NuMI (anti-)electron and (anti-)muon neutrinos, and poses a unique opportunity to provide high-statistics measurements of quasi-elastic and single pion-production cross sections for four neutrino flavors ($\nu_{\mu}$, $\nu_{e}$, $\bar{\nu}_{\mu}$, $\bar{\nu}_{e}$). This dissertation is centered around accurately characterizing the models and estimating their precision for use in making these measurements. This includes identifying major sources of uncertainty in the models such that they can be properly propagated to the cross section measurements. Specifically, this work focused on the model of the NuMI beamline and its impact on the neutrino fluxes, but also delved into the detector response model and its impact on reconstructed observables in the detector. Significant efforts were made to improve the characterization to enhance precision and thus reduce the level of propagated uncertainty. In particular, the NuMI flux was determined to be composed of 57% $\nu_{\mu}$, 38% $\bar{\nu}_{\mu}$, 3% $\nu_{e}$, and 2% $\bar{\nu}_{e}$ while the horns are operating in the positive-particle focusing configuration. The total uncertainty on the $\nu_{\mu} + \bar{\nu}_{\mu}$ ($\nu_{e} + \bar{\nu}_{e}$) flux while operating in the forward horn operating mode was determined to be 10.84% (9.04%). Compared to the on-axis flux, mesons that eventually decay to neutrinos more frequently reinteract within the NuMI structure, resulting in elevated uncertainty as these processes are not well-constrained by existing hadron interaction cross section measurements. Covariance matrices were calculated to propagate the flux uncertainty characterization to NuMI analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Pre-Transient Characterization of MLOF-1 Test Pin

This study focuses on the pre-transient characterization of U-10Zr test and sibling fuel pins for the THOR-M-LOF test series. Using neutron radiography, element contact profilometry (ECP), precise gamma scan (PGS), and gas assay, sampling, and recharge (GASR) analysis, it was confirmed that the fuel pins were intact and suitable for testing. Key fuel behaviors quantified include axial elongation, diametral strain, fluff structure geometry, axial isotope distribution, and fission gas release. Any deviations from historically expected behaviors were investigated and attributed to factors other than the irradiation behavior of the fuel pin. These pre-transient measurements establish a baseline for future post-transient analysis, which will be used to inform fuel performance models and safety criteria for sodium-cooled fast reactors (SFRs). The results will enhance understanding of transient fuel behavior and expand limited data on LOF scenarios.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Advanced Reactors Spent Fuel & Waste Science and Technology Program

Based on the higher interest in Advanced Reactor (AR) deployment (e.g., ARDP ) for potential new fuel cycles, the Spent Fuel & Waste Science and Technology (SFWST) Program has begun to evaluate the possible implications of long-term management and final disposition of potential Advance Reactor spent nuclear fuels (SNF) that would be generated in potential advanced reactors. Safely managing and dispositioning the potential future AR SNF, and any other associated radioactive wastes, is the primary focus of this initial preliminary assessment of those. This paper summarizes three primary tasks the Spent Fuel & Waste Science and Technology (SFWST) Program is executing (or collaborating on) related to the back end of the nuclear fuel cycle (BENFC) for potential future advanced reactors: 1. Advanced Reactors Spent Fuel and Waste Streams: Strategies for the BENFC This set of activities define a high-level strategy for how to systematically approach, identify, and close research and development (R&D) gaps/potential issues associated with long-term management and final disposition of AR SNF and other possible AR waste streams. This task involves summarizing advanced reactor concepts, their likely SNF and other waste forms, and identifying previous experience with similar materials, for example from DOE-managed SNF, with closely related characteristics to the potential future AR SNF. Technical R&D gaps between the breadth of detailed understanding for safe storage, transportation and disposal of the existing light water reactor SNF fuel cycle (e.g., see NASEM, 2022) and potential future fuel cycles based on advanced reactors would then be identified. 2. Characterization and Packaging Options of Advanced Reactor SNF These activities evaluate characteristics and packaging options for advanced reactor spent fuel forms. The fuel forms are categorized into three types: (1) tri-structural isotropic (TRISO), (2) metallic, and (3) fuel salt. Emphasis is given to TRISO and metallic SNF and additional waste streams from such AR as driven by the near-term anticipated operation of the Xe-100 and the Natrium reactors as advanced-reactor demonstrations1. Preliminary information for the spent-fuel salt discharged from molten-salt reactors (MSRs) is examined to provide a baseline for future efforts. All calculations and assumptions in this work are based on publicly available information. The following characteristics are calculated or estimated for use in the preliminary assessments: SNF volume and mass, radiation/activity levels through time, thermal conditions through time, potential radionuclide source terms, chemical interactions and evolutions, disposal inventories, and waste-form lifetime. Using those characteristics, calculations to determine the applicability of existing canister designs were performed. These evaluations included geometric (e.g., dimension, volume) and mass/weight considerations, known operational approaches and loading procedures, physical and chemical considerations/conditions for storage environments, as-loaded radiation, thermal, and criticality analyses to identify constraints for storage, transportation, and disposal. 3. Back-End Management of Advanced Reactors (BEMAR) The DOE NE-8 organization has defined an Integrated Project Team to evaluate the Back End Management of Advanced Reactors (BEMAR) (includes DOE staff from a range of organizations (e.g., NE-81, NE-82, OCED) and national laboratory technical staff within the DOE NE-81 and NE-82 programs). This BEMAR group works directly with advance reactors developers to assess for the DOE the technical feasibility of storage, transportation, and disposal of AR SNF based on the characteristics provided by the developers to DOE (much of which is proprietary). The BEMAR is also tasked to develop rough-order-of-magnitude cost estimates to compare the waste management system for individual advanced reactors to existing light-water reactor management practices. To accomplish this, the BEMAR group is implementing a Systems Engineering approach.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

A crystal plasticity model with an atomistically informed description of grain boundary sliding for improved predictions of deformation fields

Crystal plasticity (CP) is a powerful meso-scale technique for deformation modeling in polycrystalline materials. Crystal plasticity models typically do not include an explicit description of grain boundary (GB) sliding, which could lead to inaccurate predictions of strain distributions, especially in the vicinity of GBs. In the present study, a CP model is developed that includes GB sliding as an additional deformation mechanism and models the interaction between slip and GB sliding. Atomistic simulations are used to formulate the constitutive model for GB sliding and its interaction with incident slip. The deformation fields and structure of the GBs are obtained directly from experimental characterization and are faithfully reproduced as bicrystal systems for molecular dynamics simulations. The GBs are modeled as random-type (non-coincidence, asymmetrical) boundaries as observed from experimental data. The underlying atomistic-scale mechanism for pure sliding of random GBs was found to be analogous to fluid-flow. The interaction between incident slip and a sliding GB caused local increases in stress concentration, which further led to a momentary increase in the local sliding rate. The displacement profiles at the sliding GBs computed from the CP model with sliding accommodation are 38% more accurate than the baseline CP model as quantified by the mean squared error between the simulations and experiment. Here these results help improve the sophistication and accuracy of deformation modeling by including physics-based descriptions for GB sliding and its interaction with slip, eventually leading to more reliable predictions of micromechanical quantities.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗