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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Testing and Simulation of an Updated Cartridge Loop Vehicle

The Versatile Test Reactor (VTR) is a sodium-cooled, fast-spectrum test reactor that is being developed in the United States and will support a variety of irradiation test vehicle configurations, including cartridge loops. This work includes out-of-pile experimental results from a single-phase, natural circulation cartridge loop vehicle with geometry relevant to VTR irradiation sites, as well as comparisons between the experimental results and results predicted using the TRAC/RELAP Advanced Computational Engine (TRACE) modeling tool. The experiments were conducted in the thermosyphon test loop (TSTL) facility at Oak Ridge National Laboratory. Comparisons are also made between the current experimental data and results from natural circulation experiments previously conducted in the TSTL in a cartridge vehicle that is similar in design but has smaller flow areas. This cartridge vehicle and the experimental program were developed to add to the single-phase, natural circulation data collected in the previous iteration of the cartridge loop design, which supports future irradiation experiments and adds to a database that is useful for validating computer models. Comparisons of experimental results to TRACE model predictions is a pertinent step in validating the computational tool for supporting future irradiation experiment design and safety calculations, and comparisons to previous cartridge loop results highlight the impact of the design changes made to the test vehicle. The experiments conducted include several steady state tests and transients, including power ramp, loss of offsite power, and loss of external flow scenarios. This work shows that TRACE can accurately predict temperatures and flow conditions in the cartridge loop and the updated vehicle design achieves higher mass flow rates at the same steady state power levels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Phyllosilicate mineral dissolution upon alkaline treatment under aerobic and anaerobic conditions

The dissolution of phyllosilicate minerals exposed to high-pH environments has been studied to determine the influence of alkaline treatments and variable redox conditions on clay dissolution and the potential formation of new phases via incongruent dissolution phenomena. The present study focused on the dissolution of phyllosilicate minerals (illite, muscovite, and montmorillonite) under anaerobic and aerobic conditions using comparative solutions (sodium hydroxide and ammonium hydroxide) at similar ionic strength in the presence and absence of oxygen. Our batch data show that there is a rapid decrease in aluminum dissolution (< 240 hrs) and slow increase in silica over time (up to 1440 hrs). This trend was particularly evident for montmorillonite which shows the greatest dissolution for ammonium hydroxide, likely due to intercalation of the polyatomic cation ammonium into the mineral’s expandable layers. When comparing alkaline treatments, the strong base, sodium hydroxide, dissolved more of the mica minerals, illite and muscovite, likely due to ion-pairing between the silicate tetrahedra [SiO4]n- and Na+ cations in solution. In addition, redox conditions affect the systems similarly with treatment, although the sodium hydroxide treatment results in greater variability in solution redox conditions. For all investigated phyllosilicates, the calculated aqueous aluminum and silicon ratios over time are significantly different from the minerals’ stoichiometric ratios. As a result, we conclude that incongruent dissolution occurred and suggest formation of secondary precipitates. Understanding the potential for clay mineral alterations from interaction with alkaline solutions has implications for in situ remediation, mining operations, and waste interactions with the subsurface. This research shows that incongruent dissolution is likely and will lead to secondary precipitation which may have long term physical and chemical impacts in the subsurface.

mineral dissolution, phyllosilicate, alkaline, amm↗
DOE OSTI2023

Longitudinal Effects on Plant Species Involved in Agriculture and Pandemic Emergence Undergoing Changes in Abiotic Stress

In this work we identify changes in high-resolution zones across the globe linked by environmental similarity that have implications for agriculture, bioenergy, and zoonosis. We refine exhaustive vector comparison methods with improved similarity metrics as well as provide multiple methods of amalgamation across 744 months of climatic data. The results of the vector comparison are captured as networks which are analyzed using static and longitudinal comparison methods to reveal locations around the globe experiencing dramatic changes in abiotic stress. Specifically we (i) incorporate updated similarity scores and provide a comparison between similarity metrics, (ii) implement a new feature for resource optimization, (iii) compare an agglomerative view to a longitudinal view, (iv) compare across 2-way and 3-way vector comparisons, (v) implement a new form of analysis, and (vi) demonstrate biological applications and discuss implications across a diverse set of species distributions by detecting changes that affect their habitats. Species of interest are related to agriculture (e.g., coffee, wine, chocolate), bioenergy (e.g., poplar, switchgrass, pennycress), as well as those living in zones of concern for zoonotic spillover that may lead to pandemics (e.g., eucalyptus, flying foxes).

Cashman, Mikaela↗
DOE OSTI2025

Electron microscopy data on irradiation effects in glassy carbon, nuclear graphite, pyrolytic carbon, and carbon fibers

Glassy carbon, a monoatomic allotrope of carbon, is a candidate material for components in fission nuclear power systems due to its radiation tolerance. This article presents comprehensive electron microscopy data revealing the effects of neutron and electron irradiation on glassy carbon. For comparison, additional data are provided for pyrolytic graphite and carbon fibers, materials that exhibit similar structural behavior under irradiation. In situ electron irradiation experiments further illustrate the real-time microstructural evolution of glassy carbon during exposure. The dataset is organized into five parts: (1) transmission electron microscopy (TEM) micrographs of as-received and neutron-irradiated glassy carbon; (2) TEM micrographs of neutron-irradiated graphite; (3) TEM micrographs of unirradiated and irradiated carbon–carbon composites; (4) TEM micrographs of pyrolytic carbon specimens in both conditions; (5) scanning transmission electron microscopy (STEM) micrographs of as-received and neutron-irradiated glassy carbon and (6) in situ electron irradiation data of a glassy carbon particle. These datasets provide valuable insights into radiation-induced structural changes in carbon-based materials relevant to nuclear applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Predicting U 3 O 8 powder processing conditions: An AI/ML approach analyzing deep learning embeddings of SEM micrographs

High-resolution SEM images of uranium-oxide powders encode micro- and nanoscale clues to their synthesis route and calcination temperature. We trained a ResNet-50 model on 11 commercial-scale U₃O₈ classes, ammonium diuranate (ADU) or uranyl peroxide (H₂O₂) precursors calcined at temperatures ranging from 400 to 750 °C and added a 256-D projection head before the classifier to analyze the learned representation. The best of eight seeds reached 92.4 % accuracy on reserved testing data, but our focus is the structure of the embedding space rather than the accuracy and labels. We quantify class relatedness in the original 256-D space using centroid similarity and distributional distances, and we use Uniform Manifold Approximation Projection (UMAP) for visualization. ‘Unknown’ images from different preparation methods, SEM operators, and from the literature localized near the expected classes under a nearest-centroid analysis without retraining, as well as clustered in similar UMAP space. In conclusion, this embedding-centered workflow complements black-box classification by providing quantitative, similarity-based comparisons of U₃O₈ morphologies and reduces storage space by up to 98 % for image data used in millisecond vector search comparisons.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Within and Among Fish Species Differences in Simulated Turbine Blade Strike Mortality: Limits on the Use of Surrogacy for Untested Species

Use of surrogacy remains a useful method for prioritizing research on representatives of at-risk groups of fishes, yet quantifiable evidence in support of its use is generally not available. Blade strike impact represents one of the most traumatic stressors experienced by fish during non-volitional movements through hydropower turbines. Here, we use data generated from laboratory trials on blade strike impact experiments to directly test use of surrogacy for salmonid and clupeid fishes. Results of logistic regression indicated that a -taxonomic (genus) variable was not a significant predictor of mortality among large rainbow trout and brook trout. Similar results were found for young-of-the-year shad species, but genus-level taxonomy was a significant predictor of mortality while species was not. Multivariate analysis of morphometric data showed that shad clustered together based on similarities in fish shape which was also closely associated with genus. Logistic regression including size as a major covariate suggested total fish length was not a significant predictor of mortality, yet dose–response data suggest differential susceptibility to lower strike velocities. We suggest that use of surrogacy among species is justifiable but should be avoided within a species since the effects of size remain unclear.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Geothermal Fault Zone and Fluid Imaging through Joint Airborne ZTEM and Ground MT Data Inversion Analysis

This project has aimed to achieve detailed electrical resistivity resolution at geothermal reservoir scales by combining airborne natural electromagnetic (EM) field surveying (ZTEM) with ground magnetotelluric (MT) measurements to approximate an airborne MT geophysical method. MT alone is relatively expensive and may have permitting challenges in sensitive areas. Airborne ZTEM field data contains only the magnetic field, requires a background assumption, and has been limited to relatively high frequencies, thus suffering uniqueness problems. Based on proto-type 2D simulations, ZTEM ambiguities may be reduced through formal incorporation with possibly sparse ground MT soundings, which we pursued in full 3D for this project. The methodology was tested at the high-temperature Roosevelt Hot Springs geothermal system, Utah, which was considered advantageous given the near total exposure of crystalline reservoir rocks across the project area. ZTEM and ground MT survey data were acquired in 2017, subcontracted to outside parties with which we have worked in the past. These included 80 remote-referenced tensor MT soundings over the Mineral Mountains and adjacent Roosevelt Hot Spring producing geothermal system. These MT stations abut later coverage of a similar number of MT stations taken for the Utah FORGE project providing excellent total data aperture to re-solve structure beneath both project areas better than either set alone. The airborne ZTEM survey covered 704 line kilometers in E-W flight lines with a 250 m line spacing. Although this survey was timed during a maintenance-related shutdown of power production at the Roosevelt Hot Springs, other noise sources difficult to identify but including two high-voltage state-scale transmission lines compromised the ZTEM survey badly leading to unusable responses. Thus, with DOE management concurrence, the project proceeded to emphasize inversion and interpretation of the joint SubTER-FORGE MT data sets with regard to the Roosevelt Hot Springs reservoir recharge and to deep heat sources for both it and the Utah FORGE EGS project area. We also investigated the joint ZTEM-MT sampling concept with data sets from the Eleven Mile Canyon prospect area donated by the U.S. Navy (A. Sabin, PoC). Inversion of the SubTER-FORGE MT data using the HexMT 3D finite element algorithm reveals a large, low-resistivity anomaly extending sub-vertically through the depth range of the crust beneath the western Mineral Mountains. The steep conductive zone connects in the lower crust to a more tabular conductor characteristic of much of the Great Basin that generally is ascribed to current mafic magmatic underplating, hybridization and fluid release. The location of the resolved anomaly relative to the recent (0.5-0.8 Ma) eruptive centers of the Mineral Mountains implicates it as remnants of the magma body which fed these centers. This structure appears to be currently feeding heat and fluids upward into the Roosevelt Hot Springs hydrothermal system, as well as heat laterally to the FORGE project area. Separate and joint inversion models were carried out for the donated Eleven Mile Canyon MT-ZTEM data set to demonstrate concept. ZTEM only inversion showed two main alteration zones in the western portion of the project area known from geological mapping. Joint inversion including an E-W profile of MT soundings sharpened these features considerably. It also resolved in much greater detail the graben related normal faulting structure of the central project area which lies at depths exceeding the sensitivity of ZTEM alone. The sparse number of MT da-ta relative to the ZTEM required upweighting the former by a factor of several, but an exact procedure awaits future research. Our final impression is that sparse MT data can improve resolution of the subsurface over that of ZTEM alone. However, well sampled MT data are to be preferred and offer the simplicity of interpreting just one data type, and possess the superior resolution capability coming with the electric field everywhere, and from their high bandwidth.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Quantitative Performance Assessment of Proxy Apps and Parents (Report for ECP Proxy App Project Milestone ADCD-504-28)

The ECP Proxy Application Project has an annual milestone to assess the state of ECP proxy applications and their role in the overall ECP ecosystem. Our FY22 March/April milestone (ADCD- 504-28) proposed to: Assess the fidelity of proxy applications compared to their respective parents in terms of kernel and I/O behavior, and predictability. Similarity techniques will be applied for quantitative comparison of proxy/parent kernel behavior. MACSio evaluation will continue and support for OpenPMD backends will be explored. The execution time predictability of proxy apps with respect to their parents will be explored through a carefully designed scaling study and code comparisons. Note that in this FY, we also have quantitative assessment milestones that are due in September and are, therefore, not included in the description above or in this report. Another report on these deliverables will be generated and submitted upon completion of these milestones. To satisfy this milestone, the following specific tasks were completed: Study the ability of MACSio to represent I/O workloads of adaptive mesh codes. Re-define the performance counter groups for contemporary Intel and IBM platforms to better match specific hardware components and to better align across platforms (make cross-platform comparison more accurate). Perform cosine similarity study based on the new performance counter groups on the Intel and IBM P9 platforms. Perform detailed analysis of performance counter data to accurately average and align the data to maintain phases across all executions and develop methods to reduce the set of collected performance counters used in cosine similarity analysis. Apply a quantitative similarity comparison between proxy and parent CPU kernels. Perform scaling studies to understand the accuracy of predictability of the parent performance using its respective proxy application. This report presents highlights of these efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Probing FeSi, a d -electron topological Kondo insulator candidate, with magnetic field, pressure, and microwaves

Recently, evidence for a conducting surface state (CSS) below 19 K was reported for the correlated d -electron small gap semiconductor FeSi. In the work reported herein, the CSS and the bulk phase of FeSi were probed via electrical resistivity ρ measurements as a function of temperature T , magnetic field B to 60 T, and pressure P to 7.6 GPa, and by means of a magnetic field-modulated microwave spectroscopy (MFMMS) technique. The properties of FeSi were also compared with those of the Kondo insulator SmB 6 to address the question of whether FeSi is a d -electron analogue of an f -electron Kondo insulator and, in addition, a “topological Kondo insulator” (TKI). The overall behavior of the magnetoresistance of FeSi at temperatures above and below the onset temperature T S = 19 K of the CSS is similar to that of SmB 6 . The two energy gaps, inferred from the ρ( T ) data in the semiconducting regime, increase with pressure up to about 7 GPa, followed by a drop which coincides with a sharp suppression of T S . Several studies of ρ( T ) under pressure on SmB 6 reveal behavior similar to that of FeSi in which the two energy gaps vanish at a critical pressure near the pressure at which T S vanishes, although the energy gaps in SmB 6 initially decrease with pressure, whereas in FeSi they increase with pressure. The MFMMS measurements showed a sharp feature at T S ≈ 19 K for FeSi, which could be due to ferromagnetic ordering of the CSS. However, no such feature was observed at T S ≈ 4.5 K for SmB 6 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Topological data analysis of task-based fMRI data from experiments on schizophrenia

We use methods from computational algebraic topology to study functional brain networks, in which nodes represent brain regions and weighted edges represent similarity of fMRI time series from each region. With these tools, which allow one to characterize topological invariants such as loops in high-dimensional data, we are able to gain understanding into low-dimensional structures in networks in a way that complements traditional approaches based on pairwise interactions. In the present paper, we analyze networks constructed from task-based fMRI data from schizophrenia patients, healthy controls, and healthy siblings of schizophrenia patients using persistent homology, which allows us to explore the persistence of topological structures such as loops at different scales in the networks. We use persistence landscapes, persistence images, and Betti curves to create output summaries from our persistent-homology calculations, and we study the persistence landscapes and images using k-means clustering and community detection. Based on our analysis of persistence landscapes, we find that the members of the sibling cohort have topological features (specifically, their 1-dimensional loops) that are distinct from the other two cohorts. From the persistence images, we are able to distinguish all three subject groups and to determine the brain regions in the loops (with four or more edges) that allow us to make these distinctions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Availability of Critical Benchmark Experiments for the Pebble Tanker Transportation Model for Nuclear Criticality Safety Validation of TRISO Pebbles

This study addresses the need for comprehensive investigations into TRi-structural ISOtropic (TRISO) fuel pebble transportation validation. In this work, an exploratory model, the pebble tanker(PT), was developed with the aim of facilitating the validation of nuclear criticality safety calculations in the context of industrial-scale transportation of TRISO fuel. The PT model was designed to investigate the availability and applicability of critical benchmark experiments crucial for assessing the transportation of these pebbles. This work incorporated sensitivity/uncertainty (S/U) similarity studies to quantify the applicability of critical benchmark experiments and to address nuclear data uncertainties in the context of TRISO transportation. Two container models were investigated: one for the Hermes-type pebble and one for the Pebble Bed Modular Reactor (PBMR)–type pebble. The models were simplified, considering fuel, containment, and either water or air, to enable a focus on the underlying physics of applications involving TRISO fuel pebbles using the PT model. A crucial aspect under consideration was the capacity of the transport package to hold pebbles while ensuring subcriticality in the flooded state. An approach in the criticality validation process involves assessing the similarity between systems through an integral index parameter evaluation. This involves calculating a correlation coefficient (referred to as c k ) based on shared nuclear data–induced uncertainty between a benchmark experiment and the application of the PT model. To facilitate this analysis, the SCALE tools, particularly the CSAS6-Shift, TSUNAMI-3D-Shift, and TSUNAMI-IP sequences, were employed for comprehensive studies in neutronics and S/U analysis. Our findings showed that there are sufficient critical experimental benchmarks to perform this validation of the PT model in the most reactive state, i.e. when the tanker is flooded. This paper provides valuable insights into validating a transport package for Generation IV TRISO fuel pebbles.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Revealing Local Structures through Machine-Learning-Fused Multimodal Spectroscopy

Atomistic structures of materials offer valuable insights into their functionality. Determining these structures remains a fundamental challenge in materials science, especially for systems with defects. While both experimental and computational methods exist, each has limitations in resolving nanoscale structures. Core-level spectroscopies, such as X-ray absorption (XAS) or electron energy-loss spectroscopies (EELS), have been used to determine the local bonding environment and structure of materials. Recently, machine learning (ML) methods have been applied to extract structural and bonding information from XAS/EELS data. However, frameworks relying solely on a single data stream, defined as characterization data derived from a single element using one technique, are often insufficient because multiple local environments can yield similar spectral features, making it challenging to differentiate between competing structural hypotheses. Here, in this work, we address this challenge by integrating multimodal ab initio simulations, experimental data acquisition, and ML techniques for structure characterization. Our goal is to determine local structures and properties using EELS and XAS data from multiple elements and edges. To showcase our approach, we use various lithium nickel manganese cobalt (NMC) oxide compounds which are used for lithium ion batteries, including those with oxygen vacancies and antisite defects, as the sample material system. We successfully inferred local element content, ranging from lithium to transition metals, with quantitative agreement with experimental data. Beyond local element inference, we find that ML model based on multimodal spectroscopic data is able to determine whether local defects such as oxygen vacancy and antisites are present, a task which is impossible for single mode spectra or other experimental techniques. Furthermore, our framework is able to provide physical interpretability, bridging spectroscopy with the local atomic and electronic structures.

battery↗
DOE OSTI2020

Performing k eff Validation of As-Loaded Criticality Safety Calculations Using UNF-ST&DARDS: Applicable Experiment Selection

The general method for performing validation of as loaded criticality safety calculations using UNF ST&DARDS is presented in a paper by Clarity, which includes a description of the UNF-ST&DARDS system. Proof-of-principle analyses were performed in the summer of 2019 for MPC-32 dual purpose canisters (DPCs) containing pressurized water reactor (PWR) fuel assemblies. Summaries of these results are presented in this and a companion paper for this conference. The current paper describes the TSUNAMI-IP calculations performed to select applicable experiments for validation of 11 MPC-32 DPCs. The companion paper discusses the TSUNAMI-3D calculations used to generate sensitivity data to support the experiment selections discussed here. Experiment selection is based on the sensitivity/uncertainty (S/U) methods used to validate criticality safety calculations of as-loaded DPCs containing pressurized water reactor (PWR) spent nuclear fuel (SNF). This process has been demonstrated and is summarized in this paper. The approach is similar to that used in NUREG/CR-7109, which provides an approach for validation of PWR burnup credit (BUC), including major and minor actinides and major fission products. The premise of S/U-based validation is that applicable experiments—those having a similar bias to a given application system—will have similar sensitivities for each isotope and reaction in the two systems. It is assumed that cross sections with larger uncertainties are more likely to contain data errors which contribute to the bias. The integral index c k thus propagates the system sensitivities with the nuclear covariance data to calculate a correlation coefficient representing the similarity of the two systems. In this work, a c k value of 0.8 or higher is interpreted as identifying an experiment with sufficient similarity for use in validation. This paper presents a brief summary of the characteristics of the 11 MPC-32 DPCs used in the proof of-principle analysis for as-loaded criticality safety calculation validation and an overview of the critical experiment suite with which each of these DPC models was compared. A summary and discussion of c k results is also presented, followed by conclusions and a discussion of future work to be performed for validation of UNF ST&DARDS as-loaded criticality safety calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Forensic species identification of elasmobranchs landed in Costa Rican artisanal fisheries

Elasmobranchs represent one of the most imperiled taxa, yet few nations have developed catch limits and no international or bilateral catch limits exist. One barrier to establishing catch limits is a lack of accurate species-specific extraction rates due to many species looking similar, distinguishing characteristics (fins and head) being removed, or grouping of all elasmobranchs together in fisheries data. To better understand the species-specific impacts fisheries are having on elasmobranchs we used forensic genetic techniques to identify the types and quantities of shark species landed in Costa Rican artisanal small-scale and mid-scale fisheries. We collected elasmobranch tissue samples from fishermen in three locations along Costa Rica’s Pacific Coast: Coyote, Bejuco, and Ojochal, from April 2013 to September 2014. We used DNA barcoding techniques, utilizing a 1044 base pair region of the NADH dehydrogenase subunit 2 gene, to identify to species 275 of the 416 samples collected. Within these fisheries, seven species of shark and one ray were identified, with the scalloped hammerhead shark (Sphyrna lewini) accounting for ~750-80% of all sharks landed. Observed total lengths (TL) for the scalloped hammerhead shark (10.9–99 cm) in these fisheries suggests the sharks sampled were all either juveniles or neonates. Based on these data it is likely that the areas from which these samples were collected represent nursery grounds for the scalloped hammerhead shark. The quantity of young scalloped hammerhead sharks removed from these areas, and ones similar to them, by these artisanal fisheries could be of great importance when determining future conservation measures for this species. We conclude our findings also indicate that sharks caught in these artisanal fisheries do not appear to represent those sold in markets around San Jose.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Availability and Performance Loss Factors for U.S. PV Fleet Systems

In the PV Fleet Performance Data Initiative, we partner with photovoltaic (PV) fleet owners to collect time-series PV production data and publish aggregated, anonymized results. This report is an update of our previous publications, specifically a FY 2021 performance index publication and a FY 2022 fleet degradation analysis. In this analysis, we have increased our data participants and system totals by around 10% to 8.5 GW and 24,000 separate inverter data channels. Four major analysis topics are considered in this report: Performance Index (PI) trends, PV system availability, soiling losses, and PV system degradation. Performance Index and inverter availability are assessed on a larger set of data from our FY 2021 report: 1,128 systems compared with 200 systems from before. The increased number of systems is due to an improved data quality methodology, as well as introducing new systems to the analysis. Overall results are similar to previously published values - overall inverter availability is low in the first six months of system performance before reaching steady-state by the end of the first year. Excluding this six-month startup period, system-level aggregated data shows a median (P50) system availability of 0.99 and a lower 10th percentile (P90) value of 0.95 (Figure ES-1). A dependence on system size is also demonstrated, with worse inverter availability results for larger PV systems. Causes of this effect are under investigation, but may be impacted by inverter size, which also show lower availability for larger inverter sizes. This report also investigates PI, correcting for degradation, soiling, snow, and availability. Following these corrections, the median system PI over its entire lifetime is 0.95. PI values reported here are approximately 3% lower than what we presented in our previous FY 2021 report. Soiling loss is assessed in a comprehensive way for the first time in this report. Results are presented using the COmbined Degradation and Soiling (CODS) method, as implemented in RdTools (v3.0.0a4). Soiling values are presented for 255 systems, which indicated irradiance-weighted soiling loss greater than 1%. The values have been published in an updated NREL soiling map at nrel.gov/pv/soiling.html. Finally, we investigated system degradation using three different data analysis techniques: conventional RdTools (year-on-year (YOY)), CODS, and Performance Loss Rate (PLR) analysis. Overall degradation results are consistent with our previous publications. Rerunning conventional RdTools on our updated fleet shows that some data partners have systematically fallen below the median system degradation rate (change over time) of -0.75 %/year. A comparison with PLR analysis, which looks at change in annual PI over time, shows that median system degradation is consistent with -0.5% to -0.75% per year change. However, at the P90 value, system degradation is substantially faster. These two results are consistent and indicate that resulting degradation statistics depend to a great degree on the population of PV systems making up the analysis cohort and whether soiling impacts the systems. The use of CODS for degradation analysis provides a different method for degradation assessment, which explicitly excludes the impact of recoverable soiling on degradation analysis. Excluding soiling effects yields an annual system degradation around -0.5% per year on average. This indicates that a portion of system performance loss may be attributed to periodic soiling that is not fully recovered. This report provides PV system owners/operators with background and methods to analyze PV system performance, give guidance for expected cohort performance, and performance loss values for use in pro-forma financial models, which guide new-build system design and bankability reports.

14 SOLAR ENERGY↗
DOE OSTI2023

Cooking methods and kitchen ventilation availability, usage, perceived performance and potential in Canadian homes

Cooking is a substantial contributor to air pollutant exposures in many residences. Effective use of kitchen ventilation can mitigate exposure; however, information on its availability, usage, and potential to increase its use across the population has been limited. This study aimed to obtain nationally representative information on cooking methods, kitchen ventilation availability and usage, and the potential for education to increase effective usage. An online survey was sent to a representative sample of Canadian homes to collect data on cooking methods, the presence and use of mechanical kitchen ventilation devices, perceived device performance, and willingness to implement mitigation strategies. Responses were weighted to match key demographic factors and analyzed using non-parametric statistics. Among the 4500 respondents, 90% had mechanical ventilation devices over the cooktop (66% of which were vented to the outside), and 30% reported regularly using their devices. Devices were used most often for deep-frying, followed by stir-frying, sautéing or pan-frying, indoor grilling, boiling or steaming. Almost half reported rarely or never using their ventilation devices during baking or oven self-cleaning. Only 10% were fully satisfied with their devices. More frequent use was associated with the device being vented to the outdoors, having more than two speed settings, quiet operation if only one speed, covering over half of the cooktop, and higher perceived effectiveness. After being informed of the benefits of kitchen ventilation, 64% indicated they would consider using their devices more often, preferentially using back burners with ventilation, and/or using higher ventilation device settings when needed. This study provides population-representative data on the most used cooking methods, kitchen ventilation availability and usage, and influencing factors in Canadian homes. Such data are needed for exposure assessments and evaluating the potential to mitigate cooking-related pollutant exposures via more effective use of kitchen ventilation. The data can be reasonably extrapolated to the United States, given the similarities in residential construction practices and cultural norms between the two countries.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Intercropping kura clover with prairie cordgrass mitigates soil greenhouse gas fluxes

Prairie cordgrass (PCG) ( Spartina pectinata Link) has a high tolerance to soil salinity and waterlogging, therefore, it can thrive on marginal lands. Optimizing the nitrogen (N) input is crucial to achieving desirable biomass production of PCG without negatively impacting the environment. Thus, this study was based on the hypothesis that the use of legumes such as kura clover ( Trifolium ambiguum M. Bieb.) (KC) as an intercrop with PCG can provide extra N to the crop reducing the additional N fertilizer and mitigating soil surface greenhouse gas (GHG) emissions. Specific objective of the study was to assess the impact of PCG managed with different N rates [0 kg N ha -1 (PCG-0N), 75 kg N ha -1 (PCG-75N), 150 kg N ha -1 (PCG-150N), and 225 kg N ha -1 (PCG-255N)], and PCG intercropped with KC (PCG-KC) on GHG fluxes and biomass yield. The experimental site was established in 2010 in South Dakota under a marginally yielding cropland. The GHG fluxes were measured from 2014 through 2018 growing seasons using the static chamber. Net global warming potential (GWP) was calculated. Data showed that cumulative CH 4 and CO 2 fluxes were similar for all the treatments over the study period. However, the PCG-KC, PCG-0N, and PCG-75N recorded lower cumulative N 2 O fluxes (384, 402, and 499 g N ha -1 , respectively) than the PCG-150N (644 g N ha -1 ) and PCG-255N (697 g N ha -1 ). The PCG-KC produced 85% and 39% higher yield than the PCG-0N in 2016 and 2017, respectively, and similar yield to the other treatments (PCG-75N, PCG-150N, and PCG-255N) in these years. Net GWP was 52% lower for the PCG-KC (112.38 kg CO 2 -eq ha -1 ) compared to the PCG-225N (227.78 kg CO 2 -eq ha -1 ), but similar to other treatments. Soil total N was 15%% and 13% higher under PCG-KC (3.7 g kg -1 ) than that under PCG-0N (3.2 g kg -1 ) and PCG-75N (3.3 g kg -1 ), respectively. This study concludes that intercropping prairie cordgrass with kura clover can enhance biomass yield and reduce fertilizer-derived N 2 O emissions and net global warming potential.

09 BIOMASS FUELS↗
DOE OSTI2024

Quantitative radiography for determining density fluctuations in HED experiments

We have developed a method to extract density fluctuation measurements from x-ray radiographs of high-energy density (HED) instability growth and turbulence experiments. We use this information to calculate density fluctuation statistics for constraining the performance of turbulent mix models in HED systems. The density calculation combines image filtering, removal of systemic effects such as backlighter variation, calculation of transmission across multiple materials, and use of tracer materials to generate an approximate single-material density field. From the density map, we calculate both average density and a variance-like moment b (density-specific-volume covariance), which we compare to our models. We infer both quantities from a single image, which is significantly more information than the historic single scalar mix width measurements. We also develop a method of analyzing simulation outputs that incorporate both the density fluctuation metric from a turbulence model and the bulk material maps from the hydrodynamic code. This analysis helps address the question of how to initialize the simulations for best comparison to data from systems with large separations of scale in the mixing perturbation initial condition. We find that our data analysis method yields 1D average density and b curves with similar morphology and amplitudes as those from preliminary simulation comparisons.

47 OTHER INSTRUMENTATION↗