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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

HELIOSEISMOLOGY OF PRE-EMERGING ACTIVE REGIONS. I. OVERVIEW, DATA, AND TARGET SELECTION CRITERIA

This first paper in a series describes the design of a study testing whether pre-appearance signatures of solar magnetic active regions were detectable using various tools of local helioseismology. The ultimate goal is to understand flux-emergence mechanisms by setting observational constraints on pre-appearance subsurface changes, for comparison with results from simulation efforts. This first paper provides details of the data selection and preparation of the samples, each containing over 100 members, of two populations: regions on the Sun that produced a numbered NOAA active region, and a 'control' sample of areas that did not. The seismology is performed on data from the GONG network; accompanying magnetic data from SOHO/MDI are used for co-temporal analysis of the surface magnetic field. Samples are drawn from 2001-2007, and each target is analyzed for 27.7 hr prior to an objectively determined time of emergence. The results of two analysis approaches are published separately: one based on averages of the seismology- and magnetic-derived signals over the samples, another based on Discriminant Analysis of these signals, for a statistical test of detectable differences between the two populations. We include here descriptions of a new potential-field calculation approach and the algorithm for matching sample distributions over multiple variables. We describe known sources of bias and the approaches used to mitigate them. We also describe unexpected bias sources uncovered during the course of the study and include a discussion of refinements that should be included in future work on this topic.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2010

STATISTICAL ANALYSIS OF TANK 19F FLOOR SAMPLE RESULTS

Representative sampling has been completed for characterization of the residual material on the floor of Tank 19F as per the statistical sampling plan developed by Harris and Shine. Samples from eight locations have been obtained from the tank floor and two of the samples were archived as a contingency. Six samples, referred to in this report as the current scrape samples, have been submitted to and analyzed by SRNL. This report contains the statistical analysis of the floor sample analytical results to determine if further data are needed to reduce uncertainty. Included are comparisons with the prior Mantis samples results to determine if they can be pooled with the current scrape samples to estimate the upper 95% confidence limits (UCL95%) for concentration. Statistical analysis revealed that the Mantis and current scrape sample results are not compatible. Therefore, the Mantis sample results were not used to support the quantification of analytes in the residual material. Significant spatial variability among the current scrape sample results was not found. Constituent concentrations were similar between the North and South hemispheres as well as between the inner and outer regions of the tank floor. The current scrape sample results from all six samples fall within their 3-sigma limits. In view of the results from numerous statistical tests, the data were pooled from all six current scrape samples. As such, an adequate sample size was provided for quantification of the residual material on the floor of Tank 19F. The uncertainty is quantified in this report by an UCL95% on each analyte concentration. The uncertainty in analyte concentration was calculated as a function of the number of samples, the average, and the standard deviation of the analytical results. The UCL95% was based entirely on the six current scrape sample results (each averaged across three analytical determinations).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

Ion chamber absorbed dose calibration coefficients, N{sub D,w}, measured at ADCLs: Distribution analysis and stability

Purpose: To analyze absorbed dose calibration coefficients, N{sub D,w}, measured at accredited dosimetry calibration laboratories (ADCLs) for client ionization chambers to study (i) variability among N{sub D,w} coefficients for chambers of the same type calibrated at each ADCL to investigate ion chamber volume fluctuations and chamber manufacturing tolerances; (ii) equivalency of ion chamber calibration coefficients measured at different ADCLs by intercomparing N{sub D,w} coefficients for chambers of the same type; and (iii) the long-term stability of N{sub D,w} coefficients for different chamber types by investigating repeated chamber calibrations. Methods: Large samples of N{sub D,w} coefficients for several chamber types measured over the time period between 1998 and 2014 were obtained from the three ADCLs operating in the United States. These are analyzed using various graphical and numerical statistical tests for the four chamber types with the largest samples of calibration coefficients to investigate (i) and (ii) above. Ratios of calibration coefficients for the same chamber, typically obtained two years apart, are calculated to investigate (iii) above and chambers with standard deviations of old/new ratios less than 0.3% meet stability requirements for accurate reference dosimetry recommended in dosimetry protocols. Results: It is found that N{sub D,w} coefficients for a given chamber type compared among different ADCLs may arise from differing probability distributions potentially due to slight differences in calibration procedures and/or the transfer of the primary standard. However, average N{sub D,w} coefficients from different ADCLs for given chamber types are very close with percent differences generally less than 0.2% for Farmer-type chambers and are well within reported uncertainties. Conclusions: The close agreement among calibrations performed at different ADCLs reaffirms the Calibration Laboratory Accreditation Subcommittee process of ensuring ADCL conformance with National Institute of Standards and Technology standards. This study shows that N{sub D,w} coefficients measured at different ADCLs are statistically equivalent, especially considering reasonable uncertainties. This analysis of N{sub D,w} coefficients also allows identification of chamber types that can be considered stable enough for accurate reference dosimetry.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

Identification of Leakage Spectra from Neutron Activation in Glass/Cherenkov Detectors - Paper 96

Oak Ridge National Laboratory has developed a new detector system concept that can be deployed in major US cities to identify the leakage spectrum of a nuclear weapon detonation. The detector is based on a small piece of glass that has been doped with an element that has a high activation cross section and creates a radioactive activation product with a reasonable length half-life. The decay of the activation product(s) after exposure creates Cherenkov light which can propagate to a photomultiplier and can be turned into a count-rate signal. The signal from each glass in each detector in a city can be individually analyzed to determine the amount of activation products produced in the initial exposure. Several activation products can be determined in a single glass if the half-lives are not the same. With a known source location and a detailed 3D model of a city, neutron transport simulations can be made by using a library of known sources to predict the activation amounts each source would have made in the glass detectors. A simple comparison of the measured activation amounts and the predicted activation amounts can identify the source spectrum contained in the library that is the best match. Choosing dopants with a large range in the threshold energy for the activation reactions can help to differentiate the spectra in the library. The method of matching the measured activation amounts to the predicted activation amounts to identify the source spectrum is similar to the analysis used for the passive Activation Foil Integrated Detector System (AFIDS), also developed at Oak Ridge National Laboratory. In AFIDS, wires or foils of known mass and isotopic composition are deployed before and then collected after exposure. Counting gammas in a nearby laboratory determines the activation amounts. The glass/Cherenkov system is active - it uses a battery-powered detector to count flashes of Cherenkov light and to communicate its count rates to a remote location for further analysis. Work has been performed in several areas, including glass making, automated detection and communication systems and software tools for analysis of the signal and source spectrum identification. Bell and Boatner have developed phosphate glasses that incorporate elements with high capture cross sections, and Hayward has simulated the response with Geant4 and measured the response with isotopic gamma sources. This paper will focus on the software tools for determining the activation amounts from the Cherenkov count-rate signal and finding the best matching source spectrum. A test problem in an urban environment is used to demonstrate the potential of a spectrum identification system using neutron activation. The analysis methods developed to identify the neutron leakage spectra from Cherenkov light given off by neutron activation in doped glasses work well. The calculation used to unfold the count-rate information into the number of actual activation products uses robust algorithms that can also compute associated uncertainties. These uncertainties and the known uncertainties of the glass tube material compositions are incorporated into the matching analysis to determine which of the source spectra in the library best matches the measured activation data. Any measurement method used to identify a neutron source spectrum relies at some point on a comparison against known sources; no identification method is definitive. Detection systems measure some physical aspect of the source, not its serial number. Many systems measure the physical aspect to determine that the source has some property, and then leave it to experts to determine which potential sources share that property. The analysis system presented here incorporates the comparison into the analysis itself. The statistical tests show which of the known library sources match the measured data the best and whether that match is a good match. If the best match still does not fit the measured data well (a very high χ{sup 2} value), that indicates the true source is not one of the sources in the library. This is still valuable information for decision makers. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2010

STATISTICAL ANALYSIS OF TANK 18F FLOOR SAMPLE RESULTS

Representative sampling has been completed for characterization of the residual material on the floor of Tank 18F as per the statistical sampling plan developed by Shine [1]. Samples from eight locations have been obtained from the tank floor and two of the samples were archived as a contingency. Six samples, referred to in this report as the current scrape samples, have been submitted to and analyzed by SRNL [2]. This report contains the statistical analysis of the floor sample analytical results to determine if further data are needed to reduce uncertainty. Included are comparisons with the prior Mantis samples results [3] to determine if they can be pooled with the current scrape samples to estimate the upper 95% confidence limits (UCL{sub 95%}) for concentration. Statistical analysis revealed that the Mantis and current scrape sample results are not compatible. Therefore, the Mantis sample results were not used to support the quantification of analytes in the residual material. Significant spatial variability among the current sample results was not found. Constituent concentrations were similar between the North and South hemispheres as well as between the inner and outer regions of the tank floor. The current scrape sample results from all six samples fall within their 3-sigma limits. In view of the results from numerous statistical tests, the data were pooled from all six current scrape samples. As such, an adequate sample size was provided for quantification of the residual material on the floor of Tank 18F. The uncertainty is quantified in this report by an upper 95% confidence limit (UCL{sub 95%}) on each analyte concentration. The uncertainty in analyte concentration was calculated as a function of the number of samples, the average, and the standard deviation of the analytical results. The UCL{sub 95%} was based entirely on the six current scrape sample results (each averaged across three analytical determinations).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Microstructure, microstructural stability and mechanical properties of sand-cast Mg–4Al–4RE alloy

This paper presents a methodology for assessing the phase composition and the results of structural stability tests of the sand-cast Mg–4Al–4RE alloy after annealing it at 175 and 250 °C for 3000 h. The microstructure was analyzed with optical, scanning electron, and transmission electron microscopy. The phase composition was determined with X-ray diffraction. The structure of the Mg–4Al–4RE (AE44) alloy is composed of large grains of α-Mg solid solution, needle-shaped precipitates of the Al{sub 11}RE{sub 3}phase, polyhedral precipitates of the Al{sub 2}RE phase and Al{sub 10}RE{sub 2}Mn{sub 7} phase. After annealing at 175 °C for 3000 h, no changes in the alloy structure are observed, whereas after annealing at 250 °C the precipitates of the Al{sub 11}RE{sub 3} phase are found to be in the initial stages of spheroidization. The coarse-grained structure and unfavorable morphology of the intermetallic phases in the sand-cast AE44 alloy, which are caused by low solidification rates, result in low creep resistance up to 200 °C and low mechanical properties at ambient temperature and at 175 °C. - Highlights: • Complement the knowledge about the microstructure of Mg-Al-RE alloys. • Clarify the mechanism of formation of Mg17Al12 phase above 180 °C. • Applying a chemical dissolution of the α-Mg in order to phase identification. • Applying a statistical test to assess the spheroidization of precipitates. • Quantitative description of microstructure of Mg-Al-RE alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Object-Based Evaluation of Dynamical and Statistical Downscaled Precipitation Products over CONUS

High-resolution precipitation data, generated through dynamical downscaling (DD) or statistical downscaling (SD) of global climate model output, provide critical information for regional climate assessment and adaptation planning. Most downscaling development and validation have focused on accurate gridscale precipitation construction and ignored the spatial structure of precipitation across model grids and at the event scale. However, many applications, e.g., hydrologic modeling and the analysis using the downscaled precipitation, require a reasonable representation of the spatial structure of precipitation within watersheds. Therefore, a set of standard metrics to evaluate the representation of the spatial structure of individual storms across diverse downscaled precipitation products is desired. To address this need, we conducted an object-based evaluation of precipitation in decades-long DD and SD products over the contiguous United States (CONUS). Specifically, we evaluate their ability to reproduce various features of precipitation objects in the observations: total volume, precipitation area, peak intensity, and spatial structure. Multiple metrics (bias, Perkins score, and nonparametric statistical tests) are used to quantify model performance. Our evaluation reveals notable variations in performance among individual products across different climate zones and seasons, as well as between extreme and nonextreme events. In general, most DD products exhibit balanced performance across the four precipitation object features, while SD products vary more significantly in their performance across products. Based on this comprehensive evaluation, we provide guidance on choosing downscaled products for specific regions, seasons, and precipitation object features. These findings and recommendations can inform precipitation-relevant modeling and analysis over CONUS, guide future downscaling technique developments, and provide actionable information for climate impact assessment and adaptation.

Downscaling↗
DOE OSTI2025

A comparative analysis of YOLOv8 and U-Net image segmentation approaches for transmission electron micrographs of polycrystalline thin films

Metallic thin films offer a platform to experimentally study the dynamics of microstructural evolution, but the required transmission electron microscopy (TEM)-based imaging generates complex images that are challenging to segment and quantify. This work provides a comparative analysis of a new YOLOv8 model and an established U-Net model for bright-field TEM images of polycrystals, employing a framework leveraging physical observables to evaluate performance against two hand-traced benchmark datasets. This methodology obviates the comparison of large, diversely structured, and manually labeled datasets that are required to assess performance on a per-image/per-pixel basis. It is found that the YOLOv8 model, adapted for real-time instance segmentation, has up to 43× faster inferencing (NVIDIA GeForce RTX 4090) compared to U-Net and reconstructs hand-traced grain size distributions (GSDs) with excellent fidelity, finding mean diameter within 3% for grains near an optimal magnification; for grains that deviate from the optimal pixel-diameter, the size of small- (large)-diameter grains is systematically over- (under)-estimated. This is partially mitigated by including scale-aware augmentations during training. Moreover, when the bias is corrected post-inference by a rigid shift in distribution, the YOLOv8 model reproduces ground truth GSDs with exceptional fidelity, with statistical tests indicating <5% probability that the distributions are distinct. Based on ground truth data, calibration curves pertaining to this shift can be constructed for a given model. This issue is not present in the U-Net model’s results, indicating that for quantitative measurements where the true size of objects is of interest, special procedures must be implemented for YOLO-based models.

36 MATERIALS SCIENCE↗
DOE OSTI2016

AGR-1, AGR-2 and AGR-3/4 Dimensional Change Data Analysis

A series of Advanced Gas Reactor (AGR) experiments have been completed in the Advanced Test Reactor at Idaho National Laboratory in support of qualification and development of tristructural isotropic fuel. Each AGR test consists of multiple independently controlled and monitored capsules containing fuel compacts placed in a graphite cylinder. These capsules are instrumented with thermocouples embedded in the graphite, enabling temperature control. The fuel compacts are composed of fuel particles surrounded by a graphitic A3 matrix material. Dimensional change in AGR fuel compacts is vital because the swelling or shrinkage affects the size of the gas gaps that are used to control temperatures. Analysis of dimensional change in the AGR fuel compacts is needed to establish the variables directly relating to compact shrinkage. The variables initially identified for consideration were matrix density, compact density, fuel packing fraction, uranium loading, fuel particle diameter, cumulative fast neutron fluence, and volume average time average fuel temperature. In addition to the data available from the AGR experiments, the analysis included specimens formed from the same A3 matrix material used in Advanced Graphite Creep (AGC) experiments, which provide graphite creep data during irradiation for design and licensing purposes. The primary purpose of including the AGC specimens was to encompass dimensional behavior at zero packing fraction, zero uranium loading, and zero particle diameter. All possible combinations of first-order variable regressions were considered in the analysis. The study focused on identifying the best regression models for percent change in diameter, length, and volume. Bootstrap analysis was used to ensure the resulting regression models were robust and well-performing. The variables identified as very significant in predicting change in one or more dimensions (diameter, length, and volume) are volume average time average temperature, fast fluence, compact density, packing fraction and fuel particle diameter. Due to the presence of confounding effects between several variables, interpretation of these results is equivocal; the use of multiple statistical tests provides additional confidence in the conclusion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Assessing the Macroeconomic Importance of Gasoline and Vehicle Spending

Vector error correction (VEC) was used to test the importance of a theoretical causal chain from transportation fuel cost to vehicle sales to macroeconomic activity. Real transportation fuel cost was broken into two cost components: real gasoline price (rpgas) and real personal consumption of gasoline and other goods (gas). Real personal consumption expenditure on vehicles (RMVE) represented vehicle sales. Real gross domestic product (rGDP) was used as the measure of macroeconomic activity. The VEC estimates used quarterly data from the third quarter of 1952 to the first quarter of 2014. Controlling for the financial causes of the recent Great Recession, real homeowners’ equity (equity) and real credit market instruments liability (real consumer debt, rcmdebt) were included. Results supported the primary hypothesis of the research, but also introduced evidence that another financial path through equity is important, and that use of the existing fleet of vehicles (not just sales of vehicles) is an important transport-related contributor to macroeconomic activity. Consumer debt reduction is estimated to be a powerful short-run force reducing vehicle sales. Findings are interpreted in the context of the recent Greene, Lee, and Hopson (2012) (hereafter GLH) estimation of the magnitude of three distinct macroeconomic damage effects that result from dependence on imported oil, the price of which is manipulated by the Organization of Petroleum Exporting Countries (OPEC). The three negative macroeconomic impacts are due to (1) dislocation (positive oil price shock), (2) high oil price levels, and (3) a high value of the quantity of oil imports times an oil price delta (cartel price less competitive price). The third of these is the wealth effect. The VEC model addresses the first two, but the software output from the model (impulse response plots) does not isolate them. Nearly all prior statistical tests in the literature have used vector autoregression (VAR) and autoregressive distributed lag models that considered effects of oil price changes, but did not account for effects of oil price levels. Gasoline prices were rarely examined. The tests conducted in this report evaluate gasoline instead of oil.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

The persistent shadow of the supermassive black hole of M87. II. Model comparisons and theoretical interpretations

The Event Horizon Telescope (EHT) observation of M87∗ in 2018 has revealed a ring with a diameter that is consistent with the 2017 observation. The brightest part of the ring is shifted to the southwest from the southeast. In this paper, we provide theoretical interpretations for the multi-epoch EHT observations for M87∗ by comparing a new general relativistic magnetohydrodynamics model image library with the EHT observations for M87∗ in both 2017 and 2018. The model images include aligned and tilted accretion with parameterized thermal and nonthermal synchrotron emission properties. The 2018 observation again shows that the spin vector of the M87∗ supermassive black hole is pointed away from Earth. A shift of the brightest part of the ring during the multi-epoch observations can naturally be explained by the turbulent nature of black hole accretion, which is supported by the fact that the more turbulent retrograde models can explain the multi-epoch observations better than the prograde models. The EHT data are inconsistent with the tilted models in our model image library. Assuming that the black hole spin axis and its large-scale jet direction are roughly aligned, we expect the brightest part of the ring to be most commonly observed 90 deg clockwise from the forward jet. This prediction can be statistically tested through future observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Maternal exposures in the National Birth Defects Prevention Study: Time trends of selected exposures

Background Our objective was to describe time trends in selected pregnancy exposures in the National Birth Defects Prevention Study (NBDPS). Methods We analyzed data from the NBDPS, a multi‐site case–control study of major birth defects, for mothers of live‐born infants without birth defects (controls), with an expected date of delivery (EDD) from 1998 to 2011. Mothers from the 10 participating centers across the United States were interviewed by phone between 6 weeks and 2 years after the EDD. We focused on maternal race/ethnicity and five maternal risk factors: obesity, use of folic acid‐containing multivitamins, opioid analgesics, selective serotonin reuptake inhibitors, and loratadine because of their prevalence of use and some reports of associations with major birth defects. Prevalence time trends were examined using the Kendall's τ β test statistic. Results The exposure trend analysis included 11,724 control mothers with EDDs from 1998 to 2011. We observed a significant increase in obesity prevalence among control mothers, as well as use of selective serotonin reuptake inhibitors and loratadine. We also observed an increase in periconceptional use of folic acid‐containing multivitamins. Some of the time trends varied by race/ethnicity. No remarkable trend in the overall use of opioid analgesics was observed. The racial/ethnic distribution of mothers changed slightly during the study period. Conclusion Long‐term, population‐based case–control studies continue to be an effective way to assess exposure‐birth defects associations and provide guidance to health care providers. However, investigators examining rare outcomes covering many years of data collection need to be cognizant of time trends in exposures. Birth Defects Research (Part A) 103:703–712, 2015. © 2015 Wiley Periodicals, Inc.

Dawson, April L.↗
DOE OSTI2017

Low Cerebral Blood Volume Identifies Poor Outcome in Stent Retriever Thrombectomy

BackgroundMechanical thrombectomy (MT) is an efficient treatment of acute stroke caused by large-vessel occlusion. We evaluated the factors predicting poor clinical outcome (3-month modified Rankin Scale, mRS >2) although MT performed with modern stent retrievers.MethodsWe prospectively collected the clinical and imaging data of 105 consecutive anterior circulation stroke patients who underwent MT after multimodal CT imaging. Patients with occlusion of the internal carotid artery and/or middle cerebral artery up to the M2 segment were included. We recorded baseline clinical, procedural and imaging variables, technical outcome, 24-h imaging outcome and the clinical outcome. Differences between the groups were studied with appropriate statistical tests and binary logistic regression analysis.ResultsLow cerebral blood volume Alberta stroke program early CT score (CBV-ASPECTS) was associated with poor clinical outcome (median 7 vs. 9, p = 0.01). Lower collateral score (CS) significantly predicted poor outcome in regression modelling with CS = 0 increasing the odds of poor outcome 4.4-fold compared to CS = 3 (95% CI 1.27–15.5, p = 0.02). Lower CBV-ASPECTS significantly predicted poor clinical outcome among those with moderate or severe stroke (OR 0.82, 95% CI 0.68–1, p = 0.05) or poor collateral circulation (CS 0–1, OR 0.66, 95% CI 0.48–0.90, p = 0.009) but not among those with mild strokes or good collaterals.ConclusionsCBV-ASPECTS estimating infarct core is a significant predictor of poor clinical outcome among anterior circulation stroke patients treated with MT, especially in the setting of poor collateral circulation and/or moderate or severe stroke.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Emergence of robust anthropogenic increase of heat stress-related variables projected from CORDEX-CORE climate simulations

The information of when and where region-specific patterns in both mean and extreme temperatures leading to heat stress will emerge from the present-day climate variability is important to plan adaptation options, but to date studies on this issue still remain limited and fragmented. Here, we estimate the time of emergence (TOE) of temperature and wet-bulb temperature (Tw), a better indication of heat stress, using fine-scale, long-term regional climate model projections under the RCP2.6 and RCP8.5 scenarios across six different domains. Differently from previous studies, the TOE is determined using three methods applied on impact-relevant variables: two different signal-to-noise frameworks based on summer mean temperature and Tw and a statistical test to identify significant differences in daily extreme distributions. The TOE response to RCP2.6 and RCP8.5 with respect to the end of 20th century variability differs significantly regardless of which TOE metric is applied. For summer mean temperature, the land fraction reaching TOE is expected to exceed 90% by the 2050s under the RCP8.5, whereas the increase rate of land exposure to TOE tends to stagnate over time under the RCP2.6 so that more than 40% of land will not experience TOE by the end of the 21st century. Compared to temperature, the TOE of Tw is reached earlier in most of the wet tropics but is delayed in hot and dry regions because of the nonlinear response of Tw to humidity. For both temperature and Tw, the TOE appears earlier in regions with low baseline variability, such as in the tropics. Despite the uncertainties arising from the choice of TOE metrics, the vast majority of regions in Africa and southeast Asia experience TOE in the early 21st century under both the RCP2.6 and RCP8.5 scenarios, which stresses the urgent need for developing adequate adaptation strategies in these regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Analyzing the impact of design factors on solar module thermomechanical durability using interpretable machine learning techniques

Solar modules in utility-scale systems are expected to maintain decades of lifetime to rival conventional energy sources. However, cyclic thermomechanical loading often degrades their long-term performance, highlighting the importance of effective design to mitigate thermal expansion mismatches between module materials. Given the complex composition of solar modules, isolating the impact of individual components on overall durability remains a challenging task. In this work, we analyze a comprehensive data set that comprises bill-of-materials (BOM) and thermal cycling power loss from 251 distinct module designs to identify the predominant design factors and their impacts on the thermomechanical durability of modules. The methodology of our analysis combines machine learning modeling (random forest) and Shapley additive explanation (SHAP) to correlate design factors with power loss and interpret the model’s decision-making. The interpretation reveals that silicon type (monocrystalline or polycrystalline), encapsulant thickness, busbar numbers, and wafer thickness predominantly influence the degradation. With lower power loss of around 0.6% on average in the SHAP analysis, monocrystalline cells present better durability than polycrystalline cells. This finding is further substantiated by statistical testing on our raw data set. The SHAP analysis also demonstrates that while thicker encapsulants lead to reduced power loss, further increasing their thickness over around 0.6 to 0.7 mm does not yield additional benefits, particularly for the front side one. In addition, other important BOM features such as the number of busbars are analyzed. This study provides a blueprint for utilizing explainable machine learning techniques in a complex material system and can potentially guide future research on optimizing the design of solar modules.

14 SOLAR ENERGY↗
DOE OSTI2020

Quantifying the effect of tow architecture variability on the performance of biaxially braided composite tubes

Targeted experiments are performed with stereoscopic digital image correlation to quantify the effect of irregular braid structure on the local surface mechanical response of carbon-fiber reinforced epoxy composite tubes. Virtual models comparing both nonuniform and uniform tow structure of the outer braid of each specimen are integrated into numerical simulations similar to experiments. Experimental and numerical results agree well. Statistical tests are used to support correlations between as-manufactured braid variation ranges to local increases in stress up to 18% compared to an ideal, uniform structure in the elastic regime. Results support improved manufacturing and modeling efforts of defect sensitive braided composites.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Systematics in the XENON1T data: The 15-keV anti-axion

The XENON1T collaboration Aprile et al. [2020] has found an excess of electron recoil events in their Science Run 1 data below ~7 keV with a spectral shape consistent with that expected from a solar-axion-induced signal. The claimed statistical significance of the solar-axion model over the null hypothesis is 3.5σ. In this work we provide suggestive evidence for mismodeling in the electron recoil data that may decrease the local significance of the axion model. To reach this conclusion, we search for a signal with the spectral template of the solar axion model, but shifted to higher (unphysical) energies above ~7 keV. We find that the distribution of significances found from this side-band analysis does not follow the expected chi-square distribution. For example, we find a high-significance feature in the data, with a global $p$-value $p≈0.026$, when the solar axion model is shifted upwards in energy by ~15 keV and allowed to have a negative normalization. We argue that such statistical tests, if performed a priori, provide a data-driven way to test and potentially account for systematic uncertainties on the background model in low-threshold dark matter experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Machine learning-enhanced hybrid modeling approach for better identification of a building thermal network model and improved prediction

The gray-box modeling approach, which uses a semi-physical thermal network model, has been widely used in building prediction applications, such as model predictive control (MPC). However, unmeasured disturbances, such as occupants, lighting, and in/exfiltration loads, make it challenging to apply this approach to practical buildings. In this word, we propose a hybrid modeling approach that integrates the gray-box model with a model for unmeasured disturbance. After reviewing several system identification approaches, we systematically designed the unmeasured disturbance model with a model selection process based on statistical tests to make it robust. We generated data based on the building model calibrated by real operational data and then trained the hybrid model for two different weather conditions. The hybrid model approach demonstrates an RMSE reduction of approximately 0.2–0.9 °C and 0.3–2 °C on 1-day ahead temperature prediction compared to the Conventional approach for mild (Berkeley, CA) and cold (Chicago, IL) climates, respectively. In addition, this approach was applied to experimental data obtained from the laboratory building to be used for the MPC application, showing superior prediction performances.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗