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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Vibro-acoustic modulation and data fusion for localizing alkali–silica reaction–induced damage in concrete

This article investigates the application of vibro-acoustic modulation testing for diagnosing damage in concrete structures. The vibro-acoustic modulation technique employs two excitation frequencies on a structure. The interaction of these excitations in the measured response indicates damage through the presence of sidebands in the frequency spectra. Past studies using this technique have mostly focused on metals and composites (thin plates or laminates). Our research focuses on concrete, which is a highly heterogeneous material susceptible to a variety of chemical, physical, and mechanical damage processes. In particular, this article investigates diagnosing cracking in concrete from an expansive gel produced by an alkali–silica reaction in the presence of moisture. Past studies have been limited to damage detection using vibro-acoustic modulation testing, whereas this article extends the technique to damage localization. A cement slab with pockets of reactive aggregate is used to investigate the diagnosis technique. The effects of different testing parameters, such as locations, magnitudes, and frequencies of the two excitations, are analyzed and incorporated in the damage localization methodology. A Bayesian probabilistic methodology is developed to fuse the information from multiple test configurations in order to construct damage probability maps for the test specimen. The results of vibro-acoustic modulation–based damage localization are validated by petrographic study of cores taken from the slab.

Karve, Pranav↗
DOE OSTI2012

Case for Open-Source PEV Charge Management Data Framework

The future growth of electrified transportation could be enhanced through interaction with smart grid system architectures. This paper summarizes current literature regarding plug-in electric vehicle - renewables integration and highlights areas of need to implement such integration at a multi-utility scale. Future smart grid implementations hold the key to transferring information and control parameters between distributed and centralized decision agents. The discussion highlights the opportunity to leverage federal investments in grid renovation and electric vehicle introduction to create system-wide value from improved reliability and reduced fossil fuel consumption. An approach to scaling a previously defined 'green signal' methodology for electric vehicles will be detailed across a utility grid balancing region. The research will include a synopsis of the communications opportunities and challenges of coordinating the responses of many resources. The results are expected to show that, with some variation in the charge profiles of individual vehicles, the aggregate set can interface with grid management methods to significantly influence the ability to integrate distributed and centralized renewables to improve environmental quality.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Estimating future global per capita water availability based on changes in climate and population

Human populations are profoundly affected by water stress, or the lack of sufficient per capita available freshwater. Water stress can result from overuse of available freshwater resources or from a reduction in the amount of available water due to decreases in rainfall and stored water supplies. Analyzing the interrelationship between human populations and water availability is complicated by the uncertainties associated with climate change projections and population projections. We present a simple methodology developed to integrate disparate climate and population data sources and develop first-order per capita water availability projections at the global scale. Simulations from the coupled land-ocean-atmosphere Community Climate System Model version 3 (CCSM3) forced with a range of hypothetical greenhouse gas emissions scenarios are used to project grid-based changes in precipitation minus evapotranspiration as proxies for changes in runoff, or fresh water supply. Population growth changes according to several Intergovernmental Panel on Climate Change (IPCC) storylines are used as proxies for changes in fresh water demand by 2025, 2050 and 2100. These freshwater supply and demand projections are then combined to yield estimates of per capita water availability aggregated by watershed and political unit. Results suggest that important insights might be extracted from the use of the process developed here, notably including the identification of the globe s most vulnerable regions in need of more detailed analysis and the relative importance of population growth versus climate change in in altering future freshwater supplies. However, these are only exemplary insights and, as such, could be considered hypotheses that should be rigorously tested with multiple climate models, multiple observational climate datasets, and more comprehensive population change storylines.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Enhanced Ion Conductivity through Hydrated, Polyelectrolyte-Grafted Cellulose Nanocrystal Films

Here,iIonically conductive, hydrated polyelectrolyte nanocomposites are prepared from iodomethane-treated poly(2-vinylpyridine) (mPV)-grafted cellulose nanocrystals (MxG-CNC-g-mPV). These polyelectrolyte-grafted nanoparticle (PEGN) films exhibit an order-of-magnitude higher iodide ion conductivity relative to mPV films and a high in-plane/through-plane anisotropy. The PEGN architecture prevents CNC aggregation, maximizing the CNC/polyelectrolyte interface. PEGN films were prepared with varying polymer graft density (0.03-0.12 chains/nm 2 ) and molecular weight (7k-30k g/mol). The greatest ion conductivity enhancement is observed with lower molecular weight, higher density grafts: ca. 89 ± 6 mS/cm (140 ±10 mS/cm accounting for the volume of the CNC) versus 3.3 ± 0.4 mS/cm for ungrafted mPV. Poly(styrene-block-2-vinylpyridine)-grafted CNCs were prepared in which the insulating polystyrene block or the conducting mPV block was directly attached to the CNCs; only the films with the mPV block closest to the CNCs exhibited an enhancement in conductivity relative to mPV. Together, these data point to beneficial CNC/polyelectrolyte interfacial effects, resulting in significant ionic conductivity enhancement along the length of the CNCs in these films.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2014

Surface Condensation of CO2 onto Kaolinite

The fundamental adsorption behavior of gaseous and supercritical carbon dioxide (CO2) onto poorly crystalline kaolinite (KGa-2) at conditions relevant to geologic sequestration has been investigated using a quartz crystal microbalance (QCM) and density functional theory (DFT) methods. The QCM data indicated linear adsorption of CO2 (0-0.3 mmol CO2/g KGa-2) onto the kaolinite surface up through the gaseous state (0.186 g/cm3). However in the supercritical region, CO2 adsorption increases dramatically, reaching a peak (0.9-1.0 mmol CO2/g KGa-2) near 0.43 g/cm3, before declining rapidly to surface adsorption values equivalent or below gaseous CO2. This adsorption profile was not observed with He or N2. Comparative density functional studies of CO2 interactions with kaolinite surface models rule out CO2 intercalation and confirm that surface adsorption is favored up to approximately 0.35 g/cm3 of CO2, showing distorted T-shaped CO2-CO2 clustering, typical of supercritical CO2 aggregation over the surface as the density increases. Beyond this point, the adsorption energy gain for any additional CO2 becomes less than the CO2 interaction energy (~0.2 eV) in the supercritical medium resulting in overall desorption of CO2 from the kaolinite surface.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2015

Pridopidine, a dopamine stabilizer, improves motor performance and shows neuroprotective effects in Huntington disease R6/2 mouse model

Abstract Huntington disease ( HD ) is a neurodegenerative disorder for which new treatments are urgently needed. Pridopidine is a new dopaminergic stabilizer, recently developed for the treatment of motor symptoms associated with HD . The therapeutic effect of pridopidine in patients with HD has been determined in two double‐blind randomized clinical trials, however, whether pridopidine exerts neuroprotection remains to be addressed. The main goal of this study was to define the potential neuroprotective effect of pridopidine, in HD in vivo and in vitro models, thus providing evidence that might support a potential disease‐modifying action of the drug and possibly clarifying other aspects of pridopidine mode‐of‐action. Our data corroborated the hypothesis of neuroprotective action of pridopidine in HD experimental models. Administration of pridopidine protected cells from apoptosis, and resulted in highly improved motor performance in R6/2 mice. The anti‐apoptotic effect observed in the in vitro system highlighted neuroprotective properties of the drug, and advanced the idea of sigma‐1‐receptor as an additional molecular target implicated in the mechanism of action of pridopidine. Coherent with protective effects, pridopidine‐mediated beneficial effects in R6/2 mice were associated with an increased expression of pro‐survival and neurostimulatory molecules, such as brain derived neurotrophic factor and DARPP 32, and with a reduction in the size of mHtt aggregates in striatal tissues. Taken together, these findings support the theory of pridopidine as molecule with disease‐modifying properties in HD and advance the idea of a valuable therapeutic strategy for effectively treating the disease.

Squitieri, Ferdinando↗
DOE OSTI2015

Transcriptional Responses to Sucrose Mimic the Plant-Associated Life Style of the Plant Growth Promoting Endophyte Enterobacter sp. 638

Growth in sucrose medium was previously found to trigger the expression of functions involved in the plant associated life style of the endophytic bacterium Enterobacter sp. 638. Therefore, comparative transcriptome analysis between cultures grown in sucrose or lactate medium was used to gain insights in the expression levels of bacterial functions involved in the endophytic life style of strain 638. Growth on sucrose as a carbon source resulted in major changes in cell physiology, including a shift from a planktonic life style to the formation of bacterial aggregates. This shift was accompanied by a decrease in transcription of genes involved in motility (e.g. flagella biosynthesis) and an increase in the transcription of genes involved in colonization, adhesion and biofilm formation. The transcription levels of functions previously suggested as being involved in endophytic behavior and functions responsible for plant growth promoting properties, including the synthesis of indole-acetic acid, acetoin and 2,3-butanediol, also increased significantly for cultures grown in sucrose medium. Interestingly, despite an abundance of essential nutrients transcription levels of functions related to uptake and processing of nitrogen and iron became increased for cultures grown on sucrose as sole carbon source. Transcriptome data were also used to analyze putative regulatory relationships. In addition to the small RNA csrABCD regulon, which seems to play a role in the physiological adaptation and possibly the shift between free-living and plant-associated endophytic life style of Enterobacter sp. 638, our results also pointed to the involvement of rcsAB in controlling responses by Enterobacter sp. 638 to a plant-associated life style. Lastly, targeted mutagenesis was used to confirm this role and showed that compared to wild-type Enterobacter sp. 638 a ΔrcsB mutant was affected in its plant growth promoting ability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Concrete Structure Health Monitoring Using Vibro-acoustic Testing and Machine Learning

Assessment and management of aging concrete structures in nuclear power plants require a more systematic approach than simple reliance on margins of safety in existing codes. Research is required to deploy online monitoring capability to assess the health of concrete structures in nuclear power plants and perform predictive analytics based on heterogeneous measurements, in order to reduce the operation and maintenance costs. The research effort described in this report focuses on the health monitoring of concrete slabs containing reactive aggregates using the vibro-acoustic modulation (VAM) technique and predictive modeling. The research is developing an approach to enable detection, localization, and estimation of the extent of degradation in concrete slabs due to alkali-silica reaction (ASR). The project outcomes are generic and extendable to other degradation modes in concrete. A concrete slab without reinforcements was cast at Vanderbilt University and cured in aggressive conditions to accelerate ASR degradation. In this report, we develop a methodology for the automation of VAM testing, and the construction of machine learning models to facilitate damage localization in concrete structures. We investigate how machine learning models based on physics simulation data can be effectively utilized for damage localization (damage location and depth) and estimation in a concrete slab specimen. Our study indicates that these models could potentially support damage localization and estimation for NPP structures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Mathematical Modelling of Arctic Polygonal Tundra with Ecosys: 2. Microtopography Determines How CO 2 and CH 4 Exchange Responds to Changes in Temperature and Precipitation

Differences of surface elevation in arctic polygonal landforms cause spatial variation in soil water contents (θ), active layer depths (ALD), and thereby in CO 2 and CH 4 exchange. In this paper, we test hypotheses in ecosys for topographic controls on CO 2 and CH 4 exchange in trough, rim, and center features of low- and flat-centered polygons (LCP and FCP) against chamber and eddy covariance (EC) measurements during 2013 at Barrow, Alaska. Larger CO 2 influxes and CH 4 effluxes were measured with chambers and modeled with ecosys in LCPs than in FCPs and in lower features (troughs) than in higher (rims) within LCPs and FCPs. Spatially aggregated CO 2 and CH 4 fluxes from ecosys were significantly correlated with EC flux measurements. Lower features were modeled as C sinks (52–56 g C m -2 yr -1 ) and CH 4 sources (4–6 g C m -2 yr -1 ), and higher features as near C neutral (-2–15 g C m -2 yr -1 ) and CH 4 neutral (0.0–0.1 g C m -2 yr -1 ). Much of the spatial and temporal variations in CO 2 and CH 4 fluxes were modeled from topographic effects on water and snow movement and thereby on θ, ALD, and soil O 2 concentrations. Model results forced with meteorological data from 1981 to 2015 indicated increasing net primary productivity in higher features and CH 4 emissions in some lower and higher features since 2008, attributed mostly to recent rises in precipitation. Finally, small-scale variation in surface elevation causes large spatial variation of greenhouse gas (GHG) exchanges and therefore should be considered in estimates of GHG exchange in polygonal landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Advantage of multi-band solar-induced chlorophyll fluorescence to derive canopy photosynthesis in a temperate forest

When solar-induced chlorophyll fluorescence (SIF) is developed as a novel approach to quantify gross primary production (GPP), narrow SIF emission spectrum around the atmospheric oxygen absorption windows (˜ 761 nm and ˜687 nm) has been widely used to represent SIF and to derive GPP. As SIF is a continuous spectrum, deriving the full broadband SIF emission spectrum over 640–850 nm provides an opportunity to fully explore the potential of SIF in estimating GPP. Using high-frequency measurements of canopy carbon flux and SIF emissions at the atmospheric absorption bands, here we reconstruct the full SIF spectrum from SIF signals at the absorption bands, and then analyze correlations between the GPP and the selected single SIF bands and their combinations using both linear regression (LR) and Gaussian processes regression (GPR). Our results indicate that (1) the red SIF bands (640–700 nm) shows low correlation with GPP due to the strong (re)absorption of red SIF emissions by leaf chlorophyll; (2) the individual bands in near-infrared area (at 720 nm, 740 nm, and 761 nm) can determine about 60% and 62% of the variance in GPP with hourly scale by LR and GPR, respectively, and the combination of those SIF bands provide increased predictive power, explaining 66% and 76% variance in GPP with hourly scale by LR and GPR, respectively; (3) the solar radiation saturation, fraction of direct solar radiation, air temperature and leaf area index may have negative impacts on the SIF-GPP correlations when they are beyond optimal thresholds; and (4) the temporal aggregation of SIF-GPP (daily scale) enhances the correlations as compared with the hourly scale: the daily combination of SIF bands (at 687 nm, 720 nm, and 761 nm) can account for 80% and 93% of variance in daily daytime GPP by LR and GPR, respectively, suggesting that the combination of these three bands of SIF on the daily scale is the best proxy for GPP. Our results provide a new approach to analyze the SIF-GPP correlations using the ground-based full broadband SIF emission, suggesting that multi-bands SIF has a stronger capacity in predicting plant GPP than traditionally used signal band SIF data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models

While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. Our study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict the reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. Moreover, these reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Finally, limitations of applying MLBMA to the synthetic study and future real-world modeling are discussed.

58 GEOSCIENCES↗
DOE OSTI2019

Streamflow Reconstruction in the Upper Missouri River Basin Using a Novel Bayesian Network Model

A Bayesian model that uses the spatial dependence induced by the river network topology, and the leading principal components of regional tree ring chronologies for paleo-streamflow reconstruction is presented. In any river basin, a convergent, dendritic network of tributaries come together to form the main stem of a river. Consequently, it is natural to think of a spatial Markov process that recognizes this topological structure to develop a spatially consistent basin-scale streamflow reconstruction model that uses the information in streamflow and tree ring chronology data to inform the reconstructed flows, while maintaining the space-time correlation structure of flows that is critical for water resource assessments and management. Given historical data from multiple streamflow gauges along a river, their tributaries in a watershed, and regional tree ring chronologies, the model is fit and used to simultaneously reconstruct the full network of paleo-streamflow at all gauges in the basin progressing upstream to downstream along the river. Our application to 18 streamflow gauges in the Upper Missouri River Basin shows that the mean adjusted R 2 for the basin is approximately 0.5 with good overall cross-validated skill as measured by five different skill metrics. The spatial network structure produced a substantial reduction in the uncertainty associated with paleo-streamflow as one proceeds downstream in the network aggregating information from upstream gauges and tree ring chronologies. Uncertainty was reduced by more than 50% at six gauges, between 6% and 50% at one gauge, and by less than 5% at the remaining 11 gauges when compared with the traditional principal component regression reconstruction model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Potential improvements in brain dose estimates for internal emitters

Background: Element-specific biokinetic models are used to reconstruct doses to systemic tissues from internal emitters. Typically, a systemic model for a radionuclide explicitly depicts only its dominant repositories. Remaining tissues and fluids are aggregated into a pool called Other tissue in which the radionuclide is assumed to be uniformly distributed. In the systemic biokinetic models used in radiation protection, the brain usually is addressed as an implicit mass fraction of Other tissue rather than an explicitly depicted repository. Additionally, due to increasing interest in radiation effects on the brain, efforts are underway to improve brain dosimetry for internal radiation sources. Methods: We assessed potential improvements in brain dosimetry for internal emitters by explicitly modelling brain kinetics rather than treating the brain as a mass fraction of Other tissue. We selected ten elements for which brain kinetics can be modeled using published biokinetic data. Injection dose coefficients were calculated for a relatively long-lived radioisotope of each element using each of two versions of the ICRP’s latest systemic biokinetic model for each element, the original version and a modified version differing only in the treatment of brain. If the ICRP model contained an explicit brain pool, the modified version depicted brain instead as a mass fraction of Other tissue. If the ICRP model included brain in Other tissue, the modified version included an explicit brain pool with kinetics based on best available brain-specific data.Results: The result for a given radionuclide is expressed as a ratio A:B, where A and B are the dose coefficients based on the versions of the model with and without an explicit brain pool, respectively. The following ratios A:B were obtained for the 10 radionuclides addressed here: 241 Am, 0.13; 207 Bi, 0.57; 234 U, 0.81; 239 Pu, 0.96; 203 Hg (vapor), 1.4; 134 Cs, 1.5; 54 Mn, 1.7; 210 Po, 1.7; 226 Ra, 1.9; 210 Pb, 3.3. These ratios indicate that a dose estimate for brain based on a biokinetic model with brain implicitly contained in Other tissue may substantially underestimate or substantially overestimate a dose estimate that reflects best available brain-specific biokinetic data. Of course, the reliability of the latter estimate depends on the quality of the underlying biokinetic data.Conclusions: Finally, where feasible, the brain should be depicted explicitly in biokinetic models used in epidemiological studies addressing adverse effects of ionizing radiation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

A creep-damage model for mesoscale simulations of concrete expansion-degradation phenomena

Long-term performance of aging concrete in nuclear power plants (NPPs) requires a careful examination of the physical phenomena taking place in the material. Concrete under high neutron irradiation is subjected to large irreversible deformations as well as mechanical damage, caused by a swelling of the aggregates. However, these results, generally obtained in accelerated conditions in test reactors, cannot be directly applied to NPP irradiated structures, i.e., the biological shield, operating conditions due to difference in time scale and environmental conditions (temperature, humidity). Mesoscale numerical simulations are performed to separate the underlying mechanisms and their interactions. The cement paste creep-damage model accounts for the effect of the loading rate on the apparent damage properties of the material and uses an event-based approach to capture the competition between creep and damage. The model is applied to the simulation of irradiation experiments from the literature and shows a good agreement with the experimental data.

Concrete↗
DOE OSTI2021

Energy Efficiency: What Has Research Delivered in the Last 40 Years?

This article presents a critical assessment of 40 years of research that may be brought under the umbrella of energy efficiency, spanning different aggregations and domains—from individual producing and consuming agents to economy-wide effects to the role of innovation to the influence of policy. After 40 years of research, energy efficiency initiatives are generally perceived as highly effective. Innovation has contributed to lowering energy technology costs and increasing energy productivity. Energy efficiency programs in many cases have reduced energy use per unit of economic output and have been associated with net improvements in welfare, emission reductions, or both. Rebound effects at the macro level still warrant careful policy attention, as they may be nontrivial. Complexity of energy efficiency dynamics calls for further methodological and empirical advances, multidisciplinary approaches, and granular data at the service level for research in this field to be of greatest societal benefit.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Projecting Continental U.S. Water Stress Based on Global Datasets

Human populations may be adversely impacted by water stress, a situation which is commonly defined as a per capita water availability of less than 1700 cubic meters of freshwater per person per year. Water stress may result from either overuse of available freshwater resources or a reduction in the amount of available water due to decreases in rainfall and stored water supplies. Analyzing the interrelationship between human populations and water availability is complicated by the uncertainties associated with climate change projections and population projections. We have developed a simple methodology to integrate disparate climate and population data sources and develop first-order per capita water availability projections at the global scale. Simulations from the coupled land-ocean-atmosphere Community Climate System Model version 3 (CCSM3) forced with a range of hypothetical greenhouse gas emissions scenarios have been used to project grid-based changes in precipitation minus evapotranspiration as proxies for changes in runoff, or fresh water supply. Population growth changes, according to Intergovernmental Panel on Climate Change (IPCC) storylines, have been used as proxies for changes in fresh water demand by 2025, 2050 and 2100. These freshwater supply and demand projections have then been combined to yield estimates of per capita water availability aggregated by U.S. watershed. Results suggest that important insights might be extracted from the use of the process developed here, including the identification of potentially vulnerable areas in need of more detailed analysis. This high-level analysis also illustrates the relative importance of population growth versus climate change in in altering future freshwater supplies. However, these are only exemplary insights and, as such, could be considered hypotheses that should be rigorously tested with multiple climate models, multiple observational climate datasets, and more comprehensive population growth projections.

climate change impacts↗
DOE OSTI2019

Single-Polymer–Particle Growth Kinetics with Molecular Catalyst Speciation and Single-Turnover Imaging

The dynamics of the local environments surrounding molecular polymerization catalysts plausibly impact turnover kinetics, but the impact of and nature of such dynamics have previously been obscured by ensemble averaging. With Grubbs’ second generation ruthenium metathesis catalyst and a precipitation polymerization system, studies at the single-particle and -turnover level establish that (1) an inverse correlation exists between rate and duration of single-polymer–particle growth of aggregates, consistent with a local environment density model for the time-variable kinetics; (2) cross-linking additives produced a small, but detectible, reduction in overall monomer incorporation; (3) total ruthenium quantity within the polymer particles (as characterized by energy dispersive X-ray spectroscopy) is differentiable from the quantity that is catalytically active (as characterized by in situ fluorescence microscopy), providing catalyst speciation information; and (4) time-resolved enyne metathesis reactions can be imaged, corresponding to single turnovers at individual molecular catalysts during polymer growth under synthetically relevant conditions. Here, these findings identify and characterize reactivity distributions likely arising from the dynamics of local environments. As such, these data provide reactivity information that is unavailable through traditional ensemble analytical methods that obscure this type of information through averaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Dissecting Reactor Antineutrino Flux Calculations

Current predictions for the antineutrino yield and spectra from a nuclear reactor rely on the experimental electron spectra from 235 U , 239 Pu , 241 Pu and a numerical method to convert these aggregate electron spectra into their corresponding antineutrino ones. In our present work we investigate quantitatively some of the basic assumptions and approximations used in the conversion method, studying first the compatibility between two recent approaches for calculating electron and antineutrino spectra. We then explore different possibilities for the disagreement between the measured Daya Bay and the Huber-Mueller antineutrino spectra, including the 238 U contribution as well as the effective charge and the allowed shape assumption used in the conversion method. Here, we observe that including a shape correction of about + 6 % MeV - 1 in conversion calculations can better describe the Daya Bay spectrum. Because of a lack of experimental data, this correction cannot be ruled out, concluding that in order to confirm the existence of the reactor neutrino anomaly, or even quantify it, precisely measured electron spectra for about 50 relevant fission products are needed. With the advent of new rare ion facilities, the measurement of shape factors for these nuclides, for many of which precise beta intensity data from TAGS experiments already exist, would be highly desirable.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗