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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 811 records · Page 45

Search for a critical point of strongly-interacting matter in central \(^{40}\)Ar + \(^{45}\)Sc collisions at 13 A–75 A GeV/c beam momentum

The critical point of strongly interacting matter is searched for at the CERN SPS by the NA61/SHINE experiment in central \(^{40}\)Ar + \(^{45}\)Sc collisions at 13 A, 19 A, 30 A, 40 A, and 75 A GeV/c. The dependence of the second-order scaled factorial moments of proton multiplicity distributions on the number of subdivisions in transverse momentum space is measured. The intermittency analysis uses statistically independent data sets for every subdivision in transverse and cumulative-transverse momentum variables. The results obtained do not indicate the searched intermittent pattern. An upper limit on the fraction of correlated protons and the intermittency index is obtained based on a comparison with the Power-law Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurements of differential two-particle number and transverse momentum correlation functions in pp collisions at $\sqrt{\textit{s}}$ = 13 TeV

Differential two-particle normalized cumulants (R 2 ) and transverse momentum correlations (P 2 ) are measured as a function of the relative pseudorapidity and azimuthal angle difference (Δη, Δφ) of charged particle pairs in minimum bias pp collisions at $\sqrt{s}$ = 13 TeV. The measurements use charged hadrons in the pseudorapidity region of |η| < 0.8 and the transverse momentum range 0.2 < p T < 2.0 in order to focus on soft multiparticle interactions and to complement prior measurements of these correlation functions in p–Pb and Pb–Pb collisions. The correlation functions are reported for both unlike-sign and like-sign pairs and their charge-independent and charge-dependent combinations. Both the R 2 and P 2 measured in pp collisions exhibit features qualitatively similar to those observed in p–Pb and Pb–Pb collisions. The Δη and Δφ root mean square widths of the near-side peak of the correlation functions are evaluated and compared with those observed in p–Pb and Pb–Pb collisions and show smooth evolution with the multiplicity of charged particles produced in the collision. The comparison of the measured correlation functions with predictions from PYTHIA8 shows that this model qualitatively captures their basic structure and characteristics but feature important differences. In addition, the R$^{CD}_{2}$ is used to determine the charge balance function of hadrons produced within the detector acceptance of the measurements. The integral of the balance function is found to be compatible with those reported by a previous measurement in Pb–Pb collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Characterizing the Spread of COVID-19 from Human Mobility Patterns and SocioDemographic Indicators

Mobility is an indicator of human movement through space and time. With the increasing availability of geolocated data (from GPS, accelerometers, etc.), it is now possible to examine individual as well as group human mobility patterns. Human mobility is influenced by both intrinsic (i.e. personal motivations) and extrinsic (i.e., events like natural hazards or a pandemic like the COVID-19) factors. However, the intricate relationships between human mobility patterns and sociodemographic characteristics in the context of a pandemic are yet to be fully explored. Our goal is to overcome this gap by using human mobility data at the census block group level from mobile phones and combining those with social vulnerability indicators to examine the overall spread of COVID-19 at local spatial scales. We used 585,878 weekly visits to 37,871 points of interests (POIs) from Safegraph to quantify mobility indices and social distancing metrics in 2,820 census block groups in the city of Los Angeles (LA) - before and during lockdown as well as during the phase1 and phase 2 reopening. Finally, using supervised machine learning algorithms, we classified the census block groups in LA into High, Medium and Low categories that represented the vulnerability of these block groups based on the cumulative number of occurrences of COVID-19 cases till July 24, 2020. Our results indicate that the tree-based classifiers performed well in comparison to the Support Vector Machines and Multinomial Logit models. Gradient Boosting had the highest classification accuracy of 97.4% COVID-19 with an AUC score of 0.987. The block groups with high COVID-19 cases also had a high concentration of socially vulnerable populations, high human mobility index and a low social distancing index.

Roy, Avipsa↗

Stochastic Approximation for Multi-period Simulation Optimization with Streaming Input Data

We consider a continuous-valued simulation optimization (SO) problem, where a simulator is built to optimize an expected performance measure of a real-world system while parameters of the simulator are estimated from streaming data collected periodically from the system. At each period, a new batch of data is combined with the cumulative data and the parameters are re-estimated with higher precision. The system requires the decision variable to be selected in all periods. Therefore, it is sensible for the decision-maker to update the decision variable at each period by solving a more precise SO problem with the updated parameter estimate to reduce the performance loss with respect to the target system. We define this decision-making process as the multi-period SO problem and introduce a multi-period stochastic approximation (SA) framework that generates a sequence of solutions. Two algorithms are proposed: Re-start SA (ReSA) reinitializes the stepsize sequence in each period, whereas Warm-start SA (WaSA) carefully tunes the stepsizes, taking both fewer and shorter gradient-descent steps in later periods as parameter estimates become increasingly more precise. We show that under suitable strong convexity and regularity conditions, ReSA and WaSA achieve the best possible convergence rate in expected sub-optimality either when an unbiased or a simultaneous perturbation gradient estimator is employed, while WaSA accrues significantly lower computational cost as the number of periods increases. In addition, we present the regularized ReSA, which obviates the need to know the strong convexity constant and achieves the same convergence rate at the expense of additional computation.

Computer Science↗

Vibronic and Environmental Effects in Simulations of Optical Spectroscopy

Including both environmental and vibronic effects is important for accurate simulation of optical spectra, but combining these effects remains computationally challenging. We outline two approaches that consider both the explicit atomistic environment and the vibronic transitions. Both phenomena are responsible for spectral shapes in linear spectroscopy and the electronic evolution measured in nonlinear spectroscopy. The first approach utilizes snapshots of chromophore-environment configurations for which chromophore normal modes are determined. We outline various approximations for this static approach that assumes harmonic potentials and ignores dynamic system-environment coupling. The second approach obtains excitation energies for a series of time-correlated snapshots. This dynamic approach relies on the accurate truncation of the cumulant expansion but treats the dynamics of the chromophore and the environment on equal footing. Both approaches show significant potential for making strides toward more accurate optical spectroscopy simulations of complex condensed phase systems.

Chemistry↗

Effect of Catalyst and Catalyst Layer Composition on Catalyst Support Durability

Polymer electrolyte membrane fuel cells (PEMFCs) are efficient, zero-emission engines for the automotive sector. However, cost and durability are major barriers for the commercialization of PEMFCs. Degradation of the carbon support in the cathode catalyst layer due to high potential excursions caused by unmitigated events like H 2 starvation, or start-up/shutdown are still a major durability issue in PEMFCs. Catalyst support durability was studied by accelerated stress tests (ASTs) that included repeated potential cycling from 1.0 to 1.5 V. The effect of catalyst layer composition on carbon corrosion was studied using membrane electrode assemblies with different catalysts (Pt, PtCo), catalyst composition (catalyst wt.%, supports), ionomer composition (loading, and equivalent weights). The corrosion of the carbon support is similar between Pt and PtCo catalysts. However, the performance degradation rate is higher for the alloy catalysts due to differences in catalyst particle size and the transition metal’s leaching accelerating the performance degradation. The carbon loss is lower for catalysts with lower initial carbon loading (or higher catalyst wt.%), which is better for durability. However, the cumulative loss of carbon is identical for electrodes with the same catalyst support irrespective of catalyst and ionomer composition in the catalyst layer.

25 ENERGY STORAGE↗

In-Operando XRD Study of the Effects of Water Vapor on Phase Formation in LSM/YSZ SOFC Cathodes

Here, in-operando XRD was conducted on anode supported SOFC button cells with LSM-YSZ cathodes operated at varying cathode air compositions under constant current conditions for over 1000 h. 1-hour XRD scans were continuously collected throughout the entire operation duration. By taking the sum of measured intensities from all of the collected patterns, the resulting cumulative XRD count times allowed the identification of minor phases present at concentrations as low as <0.1 wt%. In dry air with no contaminants, the cathode exhibited improving power output during the first couple of hundred hours, followed by stable operation. The effect of 3% H 2 O + 12% CO 2 on the LSM-YSZ cathode was very similar to the effect of 3% H 2 O alone, exhibiting performance degradation. Increasing contaminants in the cathode air were found to decrease the performance of the cells. In-operando XRD discovered an increase in MnO concentration and decrease in La 2 O 3 . A gradual expansion of the LSM lattice resulting from loss of Sr or O was discovered in the LSM/YSZ cathodes tested in humid cathode air. The inverse relationship between the unit cell volume and operating voltage suggests a possible correlation between Sr segregation and performance degradation in the LSM/YSZ cathodes.

25 ENERGY STORAGE↗

Addressing Limitations of the Endpoint Slippage Analysis

Some rate of oxidation and reduction side-reactions will inevitably coexist in most rechargeable batteries. While parasitic reduction traps electrons, parasitic oxidation donates electrons to the cell’s inventory and may cause temporary capacity gain. Consequently, capacity measurements can provide unreliable information about the total extent of side-reactions occurring in the cell. The most widely used method to determine the rate of both these parasitic processes involves analyzing the slippage of endpoints, which consists in tracking the termination of cell charge and discharge when data is represented along a cumulative capacity axis. Here, we argue that this approach could lead to inaccuracies when applied to certain systems, which includes Si electrodes in Li-ion batteries and hard carbon in Na-ion batteries. This inaccuracy originates from the smooth nature of the voltage profiles of these materials at low and high alkali-ion content, causing the termination of charge and discharge to be dictated by voltage changes at both the positive and negative electrodes. We analyze this issue in quantitative terms and propose equations that can provide true rates of parasitic processes from experimental endpoint slippage data. This work shows that, in battery science, well-established analytical approaches may not be directly transferrable to new electrode systems.

25 ENERGY STORAGE↗

Correlations between Texture Profile Analysis and Sensory Evaluation of Cured Largemouth Bass Meat (Micropterus salmoides)

Texture is an important factor in evaluating the quality of aquatic products. To evaluate the texture properties of cured large mouth bass, edible sodium chloride (0, 1.0, 2.0, and 3.0%) was smeared to the bass meat. Texture profile analysis (TPA) and sensory evaluation were performed to evaluate the quality of the cured samples, and the correlations of the indexes in the two methods were analyzed. Two principal components were obtained from the TPA indexes and sensory evaluation indexes, and the cumulative variance contribution rates were 73.87% and 72.99%, respectively. Results from the principal component analysis showed that the main indicators that affected the TPA were gumminess and springiness, while those that affected sensory evaluation were chewiness and adhesiveness. The TPA index and sensory evaluation could be effectively improved when the sodium chloride added to the bass meat was 1%. In the correlation analysis, sensory springiness was negatively correlated with TPA hardness ( P < 0.05 , r = −0.553) but positively correlated with TPA chewiness ( P < 0.05 , r = 0.596). After stepwise regression analysis, the prediction equation between the sensory springiness and TPA hardness was obtained as SSp=5.770−0.002Ha. These results provide a basis for predicting the quality of large mouth bass cured products.

Li, Meijin↗

A New Model for Simulating the Imbibition of a Wetting-Phase Fluid in a Matrix-Fracture Dual Connectivity System

The imbibition experiment is an effective approach for measuring petrophysical properties of porous media, with many such experiments performed over the past decade. Quite some empirical, analytical, and numerical models have been developed to simulate spontaneous imbibition of the wetting phase fluid into porous media, but limitations still exist. In previous studies, the imbibition process has been considered to give a piston-like displacement or the porous medium modeled as multiply-sized pores linked with bonds; both approaches fail to yield comprehensive results due to their neglect of the presence of irregular fractures or nonuniform flow paths through the matrix. By building a numerical model for simulating laboratory-scale experimental data, we performed imbibition tests on several fractured Barnett Shale samples having fractures either parallel ( P ) or transverse ( T ) to the bedding plane and used MATLAB to build a new numerical model by combining the imbibition process in fractures and the matrix using concepts from percolation theory. The experimental data show that the rocks with P -direction fractures have a more steady increase of imbibition rates than the case of T -direction one. As the shale matrix with low pore connectivity hampers the upward water movement, the imbibition rate of shales with T -direction fractures will decrease suddenly after the bottom layer in contact with water is saturated during the initial period. This wetting phase movement (WPM) model can simulate 3D porous media with 2D fractures. The rate of imbibition by fractured porous media is associated with physical parameters such as porosity and fracture distribution (e.g., the number and angle of fractures). Using Monte Carlo methods, we examined fracture parameters and predicted elapsed time and cumulative water imbibition, for the Barnett Shale samples. The results show that the rate of imbibed water mass is sensitive to the number of fractures directly connected to water source, and the connectivity between two neighboring grid cells is a key parameter for the wetting-front progression. The findings of this study can help to better understand the imbibition process with multiple influencing processes and factors in fractured-matrix rocks. Although the experiments, data simulation, and prediction results are based only on Barnett Shale samples, the model is readily applicable to imbibition tests of other fractured rocks to show the spatial and temporal behavior during a dynamic imbibition process that are not easily captured experimentally.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Rise of US Photovoltaics: An Exploration of Land Use Density Trends in Large‐Scale Solar Facility Attributes, 2012–2021

An energy transition is underway in the United States; renewable energy generation is now on par with coal and nuclear generation. The number of large-scale solar photovoltaic facilities increased approximately tenfold between 2012 and 2021, with an associated 25-fold increase in cumulative installed capacity. With ambitious decarbonization and renewable energy deployment goals at both the federal and state levels, deployments of large-scale solar photovoltaic facilities will continue apace. This growth is likely to be complex with ripples of impacts felt throughout different aspects of society, and thus accurate solar land use metrics allowing more accurate predictions are of value to policymakers, planners, and other stakeholders in the future photovoltaic build-out. In this paper, we leverage data from the newly released US Large-Scale Solar Photovoltaic Database to examine recent trends in large-scale solar photovoltaic land use. We analyze the relationships between solar array capacity density (W/acre) and a range of facility attributes to better understand the future land requirements of solar capacity expansion over the coming years. Installed capacity was the single strongest determinant of solar array area. However, we found substantial variation in capacity density across facility attributes, including mount type, latitude, urbanicity, time, and prior land use.

14 SOLAR ENERGY↗

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗

Quantitative Universal Option Prioritizer (QUOP) v1.0.0

Quantitative Universal Option Prioritizer (QUOP) is a three-layer analytical hierarchy process (AHP) based multi-criteria decision-making option evaluation and prioritization tool. Decision-making often entails evaluation of options. Such competing options can either be mutual substitutes or cumulative means to achieve an objective. The options themselves can be methods, tools, technologies, processes, etc. Stakeholders involved in achieving the objective may view each option characteristic differently, depending on their needs and preferences. The QUOP tool enables a streamlined quantitative collaborative process of weighing the opinion of each stakeholder in evaluating the options. The evaluation may also be performed under different scenarios, for instance, various option potential estimates, prices, or end-user demand projections. The QUOP tool can find application in both public and private sectors, as well as on an individual level. The major advantage of using the QUOP decision-making tool is in documenting the quantified stakeholder opinion, therefore the background to each decision made, while simultaneously maintaining high transparency and stakeholder involvement. The tool is particularly suitable for decisions involving a high number of options and option characteristics, that is, aspects of each option that matter to the stakeholders

Grahovac, Milica↗

LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields

LTAU (Loss Trajectory Analysis for Uncertainty) is a technique for estimating the uncertainty in a model's predictions for any regression task by approximating the cumulative distribution function (CDF) of the model's errors over the course of training. The approximated CDF, combined with a similarity search algorithm in the model's descriptor space, can then be used to estimate the likelihood that the model's predictions on any given test point will fall below a chosen threshold. LTAU-FF (LTAU in atomistic Force Fields) is the application of LTAU specifically for use with atomistic force fields.

Vita, JoshuaA↗

via-wind (A Visual Impact Assessment Tool for Wind Turbines) [SWR-24-87]

Via-wind is an open-source tool for conducting visual impact assessments for wind turbines. It combines geographic information system (GIS) and 3D simulation methods to account for the key factors driving the visual impact of installed wind turbines, including distance, viewing angle, turbine orientation, visual exposure, and the cumulative effects of multiple turbines. This software is optimized for use in high-performance computing environments to enable large scale (e.g., country-wide) analysis, but can also be run on a single server or personal computer. For more information, please see the related journal article: https://www.sciencedirect.com/science/article/pii/S0306261924021846

Lopez, Anthony↗

Oxaliplatin–DNA Adducts as Predictive Biomarkers of FOLFOX Response in Colorectal Cancer: A Potential Treatment Optimization Strategy

FOLFOX is one of the most effective treatments for advanced colorectal cancer (CRC). However, cumulative oxaliplatin neurotoxicity often results in halting the therapy. Oxaliplatin functions predominantly via the formation of toxic covalent drug-DNA adducts. We hypothesize that oxaliplatin-DNA adduct levels formed in vivo in peripheral blood mononuclear cells (PBMC) are proportional to tumor shrinkage caused by FOLFOX therapy. We further hypothesize that adducts induced by sub-therapeutic "diagnostic microdoses" are proportional to those induced by therapeutic doses and are also predictive of response to FOLFOX therapy. These hypotheses were tested in CRC cell lines and a pilot clinical study. Four CRC cell lines were cultured with therapeutically relevant (100 µM) or diagnostic microdose (1 µM) concentrations of [ 14 C]oxaliplatin. The C-14 label enabled quantification of oxaliplatin-DNA adduct level with accelerator mass spectrometry (AMS). Oxaliplatin-DNA adduct formation was correlated with oxaliplatin cytotoxicity for each cell line as measured by the MTT viability assay. Six CRC patients received by IV a diagnostic microdose containing [ 14 C]oxaliplatin prior to treatment, as well as a second [ 14 C]oxaliplatin dose during FOLFOX chemotherapy, termed a "therapeutic dose." Oxaliplatin-DNA adduct levels from PBMC correlated significantly to mean tumor volume change of evaluable target lesions (5 of the 6 patients had measurable disease). Finally, oxaliplatin-DNA adduct levels were linearly proportional between microdose and therapeutically relevant concentrations in cell culture experiments and patient samples, as was plasma pharmacokinetics, indicating potential utility of diagnostic microdosing.

60 APPLIED LIFE SCIENCES↗

Evaluation of WRF simulation of deep convection in the US Southern Great Plains

The Southern Great Plains (SGP) exhibits a relatively high frequency of periods with extremely high rainfall rates (RR) and hail. Here, seven months of 2017 are simulated using the Weather Research and Forecasting (WRF) model applied at convection permitting resolution with the Mibrandt-Yau microphysics scheme. Simulation fidelity is evaluated, particularly during intense convective events, using data from ASOS stations, dual-polarization RADAR, gridded data sets and observations at the DoE Atmospheric Radiation Measurement site. The spatial gradients and temporal variability of precipitation and the cumulative density functions for both RR and wind speeds exhibit fidelity. Odds ratios >1 indicate WRF is also skillful in simulating high composite reflectivity (cREF, used as a measure of widespread convection) and RR > 5 mmhr –1 over the domain. Detailed analyses of the ten days with highest spatial coverage of cREF >30 dBZ show spatially similar reflectivity fields and high RR in both RADAR data and WRF simulations. However, during periods of high reflectivity, WRF exhibits a positive bias in terms of very high RR (> 25 mmhr –1 ) and hail occurrence, and during the summer and transition months, maximum hail size is underestimated. For some renewable energy applications fidelity is required with respect to the joint probabilities of wind speed and RR and/or hail. While partial fidelity is achieved for the marginal probabilities, performance during events of critical importance to these energy applications is currently not sufficient. Further research into optimal WRF configurations in support of potential damage quantification for these applications is warranted.

54 ENVIRONMENTAL SCIENCES↗

The Essential Role of Westerly Wind Bursts in ENSO Dynamics and Extreme Events Quantified in Model “Wind Stress Shaving” Experiments

Abstract Westerly wind bursts (WWBs)—brief but strong westerly wind anomalies in the equatorial Pacific—are believed to play an important role in El Niño–Southern Oscillation (ENSO) dynamics, but quantifying their effects is challenging. Here, we investigate the cumulative effects of WWBs on ENSO characteristics, including the occurrence of extreme El Niño events, via modified coupled model experiments within Community Earth System Model (CESM1) in which we progressively reduce the impacts of wind stress anomalies associated with model-generated WWBs. In these “wind stress shaving” experiments we limit momentum transfer from the atmosphere to the ocean above a preset threshold, thus “shaving off” wind bursts. To reduce the tropical Pacific mean state drift, both westerly and easterly wind bursts are removed, although the changes are dominated by WWB reduction. As we impose progressively stronger thresholds, both ENSO amplitude and the frequency of extreme El Niño decrease, and ENSO becomes less asymmetric. The warming center of El Niño shifts westward, indicating less frequent and weaker eastern Pacific (EP) El Niño events. Removing most wind burst–related wind stress anomalies reduces ENSO mean amplitude by 22%. The essential role of WWBs in the development of extreme El Niño events is highlighted by the suppressed eastward migration of the western Pacific warm pool and hence a weaker Bjerknes feedback under wind shaving. Overall, our results reaffirm the importance of WWBs in shaping the characteristics of ENSO and its extreme events and imply that WWB changes with global warming could influence future ENSO.

Meteorology & Atmospheric Sciences↗