Search NASA⌕ Search

SEARCH · Search NASA

Results for “Factors”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

$$\omega \rightarrow 3\pi $$ and $$\omega \pi ^{0}$$ transition form factor revisited

Abstract In light of recent experimental results, we revisit the dispersive analysis of the $$\omega \rightarrow 3\pi $$ ω → 3 π decay amplitude and of the $$\omega \pi ^0$$ ω π 0 transition form factor. Within the framework of the Khuri–Treiman equations, we show that the $$\omega \rightarrow 3\pi $$ ω → 3 π Dalitz-plot parameters obtained with a once-subtracted amplitude are in agreement with the latest experimental determination by BESIII. Furthermore, we show that at low energies the $$\omega \pi ^0$$ ω π 0 transition form factor obtained from our determination of the $$\omega \rightarrow 3\pi $$ ω → 3 π amplitude is consistent with the data from MAMI and NA60 experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Semileptonic form factors for $$B\rightarrow D^*\ell \nu $$ at nonzero recoil from $$2+1$$-flavor lattice QCD: Fermilab Lattice and MILC Collaborations

Abstract We present the first unquenched lattice-QCD calculation of the form factors for the decay $$B\rightarrow D^*\ell \nu $$ B → D ∗ ℓ ν at nonzero recoil. Our analysis includes 15 MILC ensembles with $$N_f=2+1$$ N f = 2 + 1 flavors of asqtad sea quarks, with a strange quark mass close to its physical mass. The lattice spacings range from $$a\approx 0.15$$ a ≈ 0.15 fm down to 0.045 fm, while the ratio between the light- and the strange-quark masses ranges from 0.05 to 0.4. The valence b and c quarks are treated using the Wilson-clover action with the Fermilab interpretation, whereas the light sector employs asqtad staggered fermions. We extrapolate our results to the physical point in the continuum limit using rooted staggered heavy-light meson chiral perturbation theory. Then we apply a model-independent parametrization to extend the form factors to the full kinematic range. With this parametrization we perform a joint lattice-QCD/experiment fit using several experimental datasets to determine the CKM matrix element $$|V_{cb}|$$ | V cb | . We obtain $$\left| V_{cb}\right| = (38.40 \pm 0.68_{\text {th}} \pm 0.34_{\text {exp}} \pm 0.18_{\text {EM}})\times 10^{-3}$$ V cb = ( 38.40 ± 0 . 68 th ± 0 . 34 exp ± 0 . 18 EM ) × 10 - 3 . The first error is theoretical, the second comes from experiment and the last one includes electromagnetic and electroweak uncertainties, with an overall $$\chi ^2\text {/dof} = 126/84$$ χ 2 /dof = 126 / 84 , which illustrates the tensions between the experimental data sets, and between theory and experiment. This result is in agreement with previous exclusive determinations, but the tension with the inclusive determination remains. Finally, we integrate the differential decay rate obtained solely from lattice data to predict $$R(D^*) = 0.265 \pm 0.013$$ R ( D ∗ ) = 0.265 ± 0.013 , which confirms the current tension between theory and experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measurement of the nuclear modification factor of $b$-jets in 5.02 TeV Pb+Pb collisions with the ATLAS detector

This paper presents a measurement of b-jet production in Pb+Pb and pp collisions at $\sqrt{sNN}$ = 5.02 TeV with the ATLAS detector at the LHC. The measurement uses 260 pb –1 of pp collisions collected in 2017 and 1.4 nb –1 of Pb+Pb collisions collected in 2018. In both collision systems, jets are reconstructed via the anti-$k_t$ algorithm. The b-jets are identified from a sample of jets containing muons from the semileptonic decay of b-quarks using template fits of the muon momentum relative to the jet axis. In pp collisions, b-jets are reconstructed for radius parameters R = 0.2 and R = 0.4, and only R = 0.2 jets are used in Pb+Pb collisions. For comparison, inclusive R = 0.2 jets are also measured using 1.7 nb –1 of Pb+Pb collisions collected in 2018 and the same pp collision data as the b-jet measurement. The nuclear modification factor, $R_{AA}$, is calculated for both b-jets and inclusive jets with R = 0.2 over the transverse momentum range of 80–290 GeV. The nuclear modification factor for b-jets decreases from peripheral to central collisions. The ratio of the b-jet $R_{AA}$ to inclusive jet $R_{AA}$ is also presented and suggests that the $R_{AA}$ for b-jets is larger than that for inclusive jets in central Pb+Pb collisions. The measurements are compared with theoretical calculations and suggest a role for mass and colour-charge effects in partonic energy loss in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Accelerated Constrained Sparse Tensor Factorization on Massively Parallel Architectures

This study presents the first constrained sparse tensor factorization (cSTF) framework that optimizes and fully offloads computation to massively parallel GPU architectures, and the first performance characterization of cSTF on GPU architectures. In contrast to prior work on tensor factorization, where the matricized tensor times Khatri-Rao product (MTTKRP) is the primary performance bottleneck, our systematic analysis of the cSTF algorithm on GPUs reveals that adding constraints creates an additional bottleneck in the update operation for many real-world sparse tensors. While executing the update operation on the GPU brings significant speedup over its CPU counterpart, it remains a significant bottleneck. To further accelerate the update operation, we propose cuADMM, a new update algorithm that leverages algorithmic and code optimization strategies to minimize both computation and data movement on GPUs. As a result, our framework delivers significantly improved performance compared to prior state-of-the-art. On 10 real-world sparse tensors, our framework achieves geometric mean speedup of 5.1 × (max 41.59 ×) and 7.01 × (max 58.05 ×) on the NIVIDA A100 and H100 GPUs, respectively, over the state-of-the-art SPLATT library running on a 26-core Intel Ice Lake Xeon CPU.

Soh, Yongseok↗
DOE OSTI2025

Insights from Optimizing HPL Performance on Exascale Systems: A Comparative Analysis of Panel Factorization

High performance LINPACK (HPL) remains the primary benchmark for evaluating supercomputing performance. It includes many parts with substantial internal complexity, and its performance is affected by a large number of parameters that interact in ways that are difficult to predict on large-scale heterogeneous supercomputer systems. We present a comprehensive performance analysis of HPL on Frontier, the world’s first exascale supercomputer, which achieved HPL performance of 1.35 exaflops. Through empirical parameter tuning, detailed modeling, and comparative evaluation, we uncover critical performance insights, share lessons learned, and outline best practices for effective parameter tuning on exascale systems. We introduce and evaluate two novel PDFACT strategies: a dedicated-thread (DT) variant and a GPU-based variant (GPUPDFACT) implementation using HIP cooperative groups, demonstrating that GPU-based factorization outperforms conventional CPU-based PDFACT on Frontier’s architecture. Our findings establish key performance factors for HPL on exascale systems and offer valuable guidance for future high-performance computing and benchmarking efforts.

Lu, Hao [ORNL] (ORCID:000000018941870X)↗
DOE OSTI2025

Factors Controlling Electrochemistry-Induced Deposition of a Zeolitic Imidazolate Framework-8 Film on Underlying Substrates

This paper discusses factors controlling electrochemistry-induced deposition of a zeolitic imidazolate framework-8 (ZIF-8) film on a planar substrate that is placed under an electrode. This method, which was recently demonstrated by us [T. Ito, et al. Cryst. Growth Des., 23, 6369 (2023)], provides a simple means to form a ZIF-8 film having lateral dimensions replicating those of a working electrode on an underlying substrate. We reported the effects of applied cathodic potential, electrode–substrate distance, and deposition time on the film formation, and proposed a mechanism involving cathodic base generation at a working electrode that promoted ligand deprotonation to form intermediate species, followed by their diffusion toward an underlying substrate. Here, we discuss details on the deposition mechanism by investigating the influences of other factors on the film deposition. We have investigated the effects of precursor concentration on film formation, and clarified that O 2 is a probase, rather than H 2 O. We have also shown the influences of substrate surface properties controlled by self-assembled monolayers on film thickness and morphology. Most notably, we successfully demonstrated the formation of microscale ZIF-8 films using an ultramicroelectrode, revealing the applicability of the electrochemistry-induced method for micropatterned film deposition on an underlying substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2022

bifacialVF - Bifacial PV View Factor model 2022 [SWR 17-58]

bifacialvf is a self-contained view factor (or configuration factor) model which replicates a 5-row PV system of infinite extent perpendicular to the module rows. Single-axis tracking is supported, and hourly output files based on TMY inputs are saved. Spatial nonuniformity is reported, with multiple rear-facing irradiances collected on the back of each module row. Bilinear interpolation code add-on to bifacialvf (description below) to pre-generate IV arrays and bifacial coefficients, and to examine the energy production with back side irradiance mismatch for either a portrait or landscape module. Included are IV curves and bifacial info for a Yingli (standard) module. Based on the publication: "A Practical Irradiance Model for Bifacial PV Modules" B. Marion, S. MacAlpine, C. Deline, A. Asgharzadeh, F. Toor, D. Riley, J. Stein, C. Hansen 2017 IEEE Photovoltaic Specialists Conference, Washington DC, 2017 URL: https://www.nrel.gov/docs/fy17osti/67847.pdf

Deline, Chris↗
DOE OSTI2026

EnergyPlus View Factor Calculation

The Python code takes EnergyPlus input files and creates input for the View3D program, executes the View3D program, then inserts the respective view factors into the EnergyPlus input file, thus streamlining the process of view factor calculation and modification of the EnergyPlus input file.

Kunwar, Niraj [Oak Ridge National Laboratory (ORNL↗
DOE OSTI2024

RAIS ICRP 30 Dose Conversion Factors for Radionuclides

Radionuclide dose conversion factors, also known as dose coefficients, are used for radionuclide dose calculations. Routes included are oral, inhalation, and external exposure. Separate datasets are maintained for ICRP 107, 60, and 30. The dose conversion factors from ICRP 30 (https://rais.ornl.gov/cgibin/tools/TOX_search?select=rad30) can be found in FGR 11. Results from all three tools can be downloaded in .xlsx format.

Noto, Katie [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2024

RAIS ICRP 60 Dose Conversion Factors for Radionuclides

Radionuclide dose conversion factors, also known as dose coefficients, are used for radionuclide dose calculations. Routes included are oral, inhalation, and external exposure. Separate datasets are maintained for ICRP 107, 60, and 30. The dose conversion factors from ICRP 60 (https://rais.ornl.gov/cgi-bin/tools/TOX_search?select=rad60) can be found in FGR 12. Results from all three tools can be downloaded in .xlsx format.

Noto, Katie [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2022

Impact of Meteorological Factors on the Mesoscale Morphology of Cloud Streets during a Cold-Air Outbreak over the Western North Atlantic

We report postfrontal clouds (PFC) are ubiquitous in the marine boundary layer, and their morphology is essential to estimating the radiation budget in weather and climate models. Here we examine the roles of sea surface temperature (SST) and meteorological factors in controlling the mesoscale morphology and evolution of shallow clouds associated with a cold-air outbreak that occurred on 1 March 2020 during phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE). Our results show that the simulated PFC structure and ambient conditions by the Weather Research and Forecasting (WRF) Model are generally consistent with observations from GOES-16 and dropsonde measurements. We also examine the thermodynamical and dynamical influences in the cloud mesoscale morphology using WRF sensitivity experiments driven by two meteorological forcing datasets with different domain-mean SST and spatial gradients, which lead to dissimilar values of hydrometeor water path and cloud core fraction. The SST from ERA5 leads to weaker stability and higher inversion height than the SST from FNL does. In addition, the use of large-scale meteorological forcings from ERA5 yields a distinctive time evolution of wind direction shear in the inner domain, which favors the formation and persistence of longer cloud rolls. Both factors contribute to a change in the time evolution of domain-mean water path and cloud core fraction of cloud streets. Our study takes advantage of the simulation driven by the differences between two large-scale forcing datasets to illustrate the importance of SST and wind direction shear in the cloud street morphology in a realistic scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Factors Influencing Willingness to Pool in Ride-Hailing Trips

In the past decade, transportation network companies (TNCs) such as Uber, Lyft, and Via have established themselves as a viable transportation alternative to other modes. However, the popularity of these services has come with a fair share of criticism for their negative externalities such as increasing vehicle miles traveled and congestion in cities. Pooled ride-hailing trips, in which all or a part of two individual (or group) trips are combined in and served by a single vehicle, have the potential to reduce these externalities. Pooling of rides is an effective solution to reduce congestion and travel cost, but pooled rides still represent a small percentage of the total trips served (and miles driven) by TNCs relative to single-occupancy (and without customer) vehicle miles. Both TNCs and cities alike will benefit from understanding what factors encourage or deter pooling a ride-hailing trip. In this study, newly available Chicago transportation network provider data were explored to identify the extent to which different socioeconomic, spatiotemporal, and trip characteristics affect willingness to pool (WTP) in ride-hailing trips. Furthermore, multivariate linear regression and machine-learning models were employed to understand and predict WTP based on location, time, and trip factors. The results show intuitive trends, with income level at drop-off and pickup locations and airport trips as the most important predictors of WTP. Results from this study can help TNCs and cities devise strategies that increase pooled ride-hailing, thereby reducing adverse transportation and energy impacts from ride-hailing modes.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Structure of coagulation factor VIII bound to a patient-derived anti-C1 domain antibody inhibitor

The development of pathogenic antibody inhibitors against coagulation factor VIII (FVIII) occurs in ~30% of congenital hemophilia A patients receiving FVIII replacement therapy as well as in all cases of acquired hemophilia A. KM33 is an anti-C1 domain antibody inhibitor previously isolated from a severe hemophilia A patient. In addition to potently blocking FVIII binding to von Willebrand factor and phospholipid surfaces, KM33 disrupts FVIII binding to lipoprotein receptor-related protein 1 (LRP1), which drives FVIII hepatic clearance and antigen presentation in dendritic cells. Here, we report on the structure of FVIII bound to NB33, a recombinant derivative of KM33, by single-particle cryo-electron microscopy. Furthermore, structural analysis reveals the NB33 epitope localizes to FVIII residues R2090-S2094 and I2158-R2159 which constitute membrane-binding loops in the C1 domain. Further analysis reveals multiple FVIII lysine and arginine residues, previously shown to mediate binding to LRP1, dock onto an acidic cleft at the NB33 variable domain interface, thus blocking a putative LRP1 binding site. Together, these results demonstrate a novel mechanism of FVIII inhibition by a patient-derived antibody inhibitor and provide structural evidence toward engineering FVIII with reduced LRP1-mediated clearance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

SAXS analysis of the intrinsic tenase complex bound to a lipid nanodisc highlights intermolecular contacts between factors VIIIa/IXa

Abstract The intrinsic tenase (Xase) complex, formed by factors (f) VIIIa and fIXa, forms on activated platelet surfaces and catalyzes the activation of factor X to Xa, stimulating thrombin production in the blood coagulation cascade. The structural organization of the membrane-bound Xase complex remains largely unknown, hindering our understanding of the structural underpinnings that guide Xase complex assembly. Here, we aimed to characterize the Xase complex bound to a lipid nanodisc with biolayer interferometry (BLI), Michaelis–Menten kinetics, and small-angle X-ray scattering (SAXS). Using immobilized lipid nanodiscs, we measured binding rates and nanomolar affinities for fVIIIa, fIXa, and the Xase complex. Enzyme kinetic measurements demonstrated the assembly of an active enzyme complex in the presence of lipid nanodiscs. An ab initio molecular envelope of the nanodisc-bound Xase complex allowed us to computationally model fVIIIa and fIXa docked onto a flexible lipid membrane and identify protein–protein interactions. Our results highlight multiple points of contact between fVIIIa and fIXa, including a novel interaction with fIXa at the fVIIIa A1–A3 domain interface. Lastly, we identified hemophilia A/B-related mutations with varying severities at the fVIIIa/fIXa interface that may regulate Xase complex assembly. Together, our results support the use of SAXS as an emergent tool to investigate the membrane-bound Xase complex and illustrate how mutations at the fVIIIa/fIXa dimer interface may disrupt or stabilize the activated enzyme complex.

Hematology↗
DOE OSTI2021

Machine learning to identify geologic factors associated with production in geothermal fields: a case-study using 3D geologic data, Brady geothermal field, Nevada

Abstract In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fluid-flow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fluid-flow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k -means clustering (NMF k ), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes.

58 GEOSCIENCES↗
DOE OSTI2021

Reverse annealing for nonnegative/binary matrix factorization

It was recently shown that quantum annealing can be used as an effective, fast subroutine in certain types of matrix factorization algorithms. The quantum annealing algorithm performed best for quick, approximate answers, but performance rapidly plateaued. In this paper, we utilize reverse annealing instead of forward annealing in the quantum annealing subroutine for nonnegative/binary matrix factorization problems. After an initial global search with forward annealing, reverse annealing performs a series of local searches that refine existing solutions. The combination of forward and reverse annealing significantly improves performance compared to forward annealing alone for all but the shortest run times.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Factors Influencing Building Demand Flexibility

The U.S. Department of Energy’s National Roadmap for Grid-interactive Efficient Buildings (GEB) acknowledged that building demand flexibility (DF) is both an important strategy to decarbonizing the buildings sector and an important resource for meeting the changing needs of the electrical grid such as improving grid reliability. However, understanding the complexity and uncertainties in real building field performance of DF strategies is a large gap hindering stakeholders on both grid and buildings side to make investments on deploying such strategies. The research work in this report intended to advance understanding of the variability and influential factors in building demand flexibility. Adding such knowledge based on lab testing results and measured performance data from real buildings is an important contribution. The report uses standardized metrics and methods to quantify DF performance from field-measured DF datasets of two significant building groups of big-box retail and medium office buildings to present the challenge of building DF variability in multiple dimensions. The report presents findings related to how several key factors influence building demand flexibility from implementing a common, cost-effective DF control strategy (i.e., adjusting zone temperatures). The findings are supported by full-scale lab testing, field data analysis and simulation research. The authors also provided application-oriented recommendations to stakeholders such as building aggregators, utility program design professionals, sophisticated building portfolio owners, and more.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Loss Factors for Small Distributed Wind Turbines Based on Field Data in the United States

While wind energy production loss due to unavailability, environmental impacts, curtailment, and other causes has been studied and characterized at the utility-scale wind farm level, observation-based characterization of project loss is lacking for distributed wind energy, particularly for projects involving small wind turbines. Contemporary tools and research that support pre-construction distributed wind energy characterization present a wide range of default loss factors to convert gross energy estimates to net: 7-18%. We hypothesize that we can use generation observations from operational distributed wind projects to develop more accurate representations of loss. Using a density-based filtering technique on distributed wind power generation timeseries, we determine periods of typical performance and use them with regression algorithms in a measure-correlate-predict fashion to simulate what the generation would have been during periods of atypical or unreported performance. From there, the actual versus predicted generation leads to the establishment of observation-informed loss factors (median = 17%) for small, single turbine installation distributed wind projects.

17 WIND ENERGY↗