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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A semiparametric latent factor model for large scale temporal data with heteroscedasticity

Large scale temporal data have flourished in a vast array of applications, and their sophisticated structures, especially the heteroscedasticity among subjects with inter- and intra-temporal dependence, have fueled a great demand for new statistical models. In this paper, with covariate information, we consider a flexible model for large scale temporal data with subject-specific heteroscedasticity. Formally, the model employs latent semiparametric factors to simultaneously account for the subject-specific heteroscedasticity and the contemporaneous and/or serial correlations. The subject-specific heteroscedasticity is modeled as the product of the unobserved factor process and subject’s covariate effect, which is further characterized via additive models. For estimation, we propose a two-step procedure. First, the latent factor process and nonparametric loading are recovered through projection-based methods, and following, we estimate the regression components by approaches motivated from the generalized least squares. By scrupulously examining the non-asymptotic rates for recovering the factor process and its loading, we show the consistency and efficiency of estimated regression coefficients in the absence of prior knowledge of latent factor process and subject’s covariate effect. Here, the statistical guarantees remain valid even for finite time points that makes our method particularly appealing when the subjects significantly outnumber the observation time points. Using comprehensive simulations, we demonstrate the finite sample performance of our method, which corroborates the theoretical findings. Finally, we apply our method to a data set of air quality and energy consumption collected at 129 monitoring sites in the United States in 2015.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Test-Based Calibration of Safety Factors for Capacity Models

In this paper, a simple procedure to calibrate the safety factor of capacity models is presented. The calibration can be carried out based on any available database of experimental tests, even of limited size. The procedure aims to assess the model capability of predicting the test results and to calibrate the safety factor so that the capacity equation meets the target reliability level required by the code or sought by the calibrator. After predicting each test of the database with the capacity equation under consideration, the test-prediction pairs are checked for the property of linearity, and the relative error for the properties of homoscedasticity and normality. Once these properties are fulfilled—which may require a nonlinear transformation of the test values and/or the predictions—the closed-form equation proposed in this paper is employed to compute a target design value. The model safety factor is finally obtained by comparing such target design value with the design value obtained from the code. The paper also proposes two approximate analytical equations to compute the tolerance factor, used to attain any given fractile, as a function of the (even small) number of tests, with any assigned confidence level. A fundamental outcome of the procedure is that it yields an objective indicator of the model accuracy, measured by the standard deviation of its error, which may be regarded as a parameter useful for selecting the most reliable model among different competing ones. In the long run, the application of the proposed procedure will allow achieving a uniform reliability level throughout all capacity models used in codes and guidelines. A further advantage is that the partial safety factors so derived can be straightforwardly updated when more experiments become available. Finally, as an example, the proposed procedure is herein applied to the ACI 318 shear design capacity equation for concrete members unreinforced in shear.

42 ENGINEERING↗
DOE OSTI2017

Effective g factor of low-density two-dimensional holes in a Ge quantum well

Here we report the measurements of the effective g factor of low-density two-dimensional holes in a Ge quantum well. Using the temperature dependence of the Shubnikov-de Haas oscillations, we extract the effective g factor in a magnetic field perpendicular to the sample surface. Very large values of the effective g factor, ranging from ~13 to ~28, are observed in the density range of 1.4×10 10 cm -2 – 1.4×10 11 cm -2 . When the magnetic field is oriented parallel to the sample surface, the effective g factor is obtained from a protrusion in the magneto-resistance data that signify full spin polarization. In the latter orientation, a small effective g factor, ~1.3-1.4, is measured in the density range of 1.5×10 10 cm -2 –2×10 10 cm -2 . Finally, this very strong anisotropy is consistent with theoretical predictions and previous measurements in other 2D hole systems, such as InGaAs and GaSb.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Model-independent determination of the astrophysical S factor in laser-induced fusion plasmas

In this paper, we present a new and general method for measuring the astrophysical S factor of nuclear reactions in laser-induced plasmas and we apply it to 2 H(d,n) 3 He. The experiment was performed with the Texas Petawatt Laser, which delivered 150–270 fs pulses of energy ranging from 90 to 180 J to D 2 or CD 4 molecular clusters (where D denotes 2 H). After removing the background noise, we used the measured time-of-flight data of energetic deuterium ions to obtain their energy distribution. We derive the S factor using the measured energy distribution of the ions, the measured volume of the fusion plasma, and the measured fusion yields. This method is model independent in the sense that no assumption on the state of the system is required, but it requires an accurate measurement of the ion energy distribution, especially at high energies, and of the relevant fusion yields. In the 2 H(d,n) 3 He and 3 He(d,p) 4 He cases discussed here, it is very important to apply the background subtraction for the energetic ions and to measure the fusion yields with high precision. While the available data on both ion distribution and fusion yields allow us to determine with good precision the S factor in the d+d case (lower Gamow energies), for the d+ 3 He case the data are not precise enough to obtain the S factor using this method. Our results agree with other experiments within the experimental error, even though smaller values of the S factor were obtained. This might be due to the plasma environment differing from the beam target conditions in a conventional accelerator experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Flavor dependence of the pion and kaon form factors and parton distribution functions

The separate quark flavor contributions to the pion and kaon valence quark distribution functions are studied, along with the corresponding electromagnetic form factors in the space-like region. The calculations are made using the solution of the Bethe-Salpeter equation for the model of Nambu and Jona-Lasinio with proper-time regularization. Both the pion and kaon form factors and the valence quark distribution functions reproduce many features of the available empirical data. The larger mass of the strange quark naturally explains the empirical fact that the ratio u(K) + (x)/u(pi) + (x) drops below unity at large x, with a value of approximately M$2\atop{u}$/Ms$2\atop{s}$ as x → 1. With regard to the elastic form factors we report a large flavor dependence, with the u-quark contribution to the kaon form factor being an order of magnitude smaller than that of the s-quark at large Q 2 , which may be a sensitive measure of confinement effects in QCD. Surprisingly though, the total K + and π + form factors differ by only 10%. Lastly, in general we find that flavor breaking effects are typically around 20%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Pion gravitational form factors in the QCD instanton vacuum. I

The pion form factors of the QCD energy-momentum tensor (EMT) are studied in the instanton liquid model (ILM) of the QCD vacuum. In this approach, the breaking of conformal symmetry is encoded in the form of stronger-than-Poisson fluctuations in the number of instantons. For the trace of the EMT, it is shown that the gluonic trace anomaly term contributes half the pion mass, with the other half coming from the quark-mass-dependent σ term. The Q 2 dependence of the form factors is governed by glueball and scalar meson exchanges. For the EMT, the spin-0 (trace) and spin-2 (traceless rank-2 tensor) form factors are computed at next-to-leading order in the instanton density using effective quark operators. Relations between the gluon and quark contributions to the EMT form factors are derived. The form factors are also expressed in terms of the pion light-front wave functions in the ILM. The results at the low resolution scale of the inverse instanton size are evolved to higher scales using the renormalization group equation. The ILM results compare well with those of recent lattice QCD calculations. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Axial-vector form factors of the nucleon from lattice QCD

In this paper, we present results for the form factors of the isovector axial vector current in the nucleon state using large scale simulations of lattice QCD. The calculations were done using eight ensembles of gauge configurations generated by the MILC collaboration using the HISQ action with 2 + 1 + 1 dynamical flavors. These ensembles span three lattice spacings a ≈ 0.06 , 0.09, and 0.12 fm and light-quark masses corresponding to the pion masses M π ≈ 135, 225, and 310 MeV. High-statistics estimates allow us to quantify systematic uncertainties in the extraction of G A (Q 2 ) and the induced pseudoscalar form factor G P (Q 2 ) . We perform a simultaneous extrapolation in the lattice spacing, lattice volume and light-quark masses of the axial charge radius r A data to obtain physical estimates. Using the dipole ansatz to fit the Q 2 behavior we obtain r A | dipole = 0.49(3) fm , which corresponds to M A = 1.39(9) GeV , and is consistent with M A = 1.35(17) GeV obtained by the miniBooNE collaboration. The estimate obtained using the z -expansion is r A | z - expansion = 0.46(6) fm, and the combined result is r A | combined = 0.48(4) fm. Analysis of the induced pseudoscalar form factor G P (Q 2 ) yields low estimates for g* P and g π NN compared to their phenomenological values. To understand these, we analyze the partially conserved axial current (PCAC) relation by also calculating the pseudoscalar form factor. Lastly, we find that these low values are due to large deviations in the PCAC relation between the three form factors, and in the pion-pole dominance hypothesis.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Nucleon axial form factor from elementary target data

Precise neutrino-nucleon amplitudes are essential ingredients for predicting neutrino event rates in current and upcoming long-baseline neutrino oscillation experiments. A common neutrino interaction with a low reaction threshold and with most of the energy carried by two final state particles is quasielastic scattering, for which the nucleon axial form factor, 𝐹 𝐴⁡ (𝑄 2 ), is a dominant source of uncertainty. Improvements to the nucleon axial form factor rely on neutrino scattering data with elementary targets to reduce or eliminate the need for nuclear modeling systematics. This work examines constraints on the nucleon axial form factor that can be achieved from datasets of neutrino scattering on deuterium targets, Lattice QCD predictions, and from the recent hydrogen target data from the MINERvA Collaboration. Significant tension is found between hydrogen and deuterium target data, suggesting that extractions from deuterium underestimate both the central value and uncertainty of the form factor. Parametrizations for and uncertainties of the nucleon axial form factor using the 𝑧 expansion are provided.

FOS: Physical sciences↗
DOE OSTI2021

DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks

Abstract Background Due to the complexity of the biological systems, the prediction of the potential DNA binding sites for transcription factors remains a difficult problem in computational biology. Genomic DNA sequences and experimental results from parallel sequencing provide available information about the affinity and accessibility of genome and are commonly used features in binding sites prediction. The attention mechanism in deep learning has shown its capability to learn long-range dependencies from sequential data, such as sentences and voices. Until now, no study has applied this approach in binding site inference from massively parallel sequencing data. The successful applications of attention mechanism in similar input contexts motivate us to build and test new methods that can accurately determine the binding sites of transcription factors. Results In this study, we propose a novel tool (named DeepGRN) for transcription factors binding site prediction based on the combination of two components: single attention module and pairwise attention module. The performance of our methods is evaluated on the ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge datasets. The results show that DeepGRN achieves higher unified scores in 6 of 13 targets than any of the top four methods in the DREAM challenge. We also demonstrate that the attention weights learned by the model are correlated with potential informative inputs, such as DNase-Seq coverage and motifs, which provide possible explanations for the predictive improvements in DeepGRN. Conclusions DeepGRN can automatically and effectively predict transcription factor binding sites from DNA sequences and DNase-Seq coverage. Furthermore, the visualization techniques we developed for the attention modules help to interpret how critical patterns from different types of input features are recognized by our model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout

We introduce a task-parallel algorithm for sparse incomplete Cholesky factorization that utilizes a 2D sparse partitioned-block layout of a matrix. Our factorization algorithm follows the idea of algorithms-by-blocks by using the block layout. The algorithm-byblocks approach induces a task graph for the factorization. These tasks are inter-related to each other through their data dependences in the factorization algorithm. To process the tasks on various manycore architectures in a portable manner, we also present a portable tasking API that incorporates different tasking backends and device-specific features using an open-source framework for manycore platforms i.e., Kokkos. A performance evaluation is presented on both Intel Sandybridge and Xeon Phi platforms for matrices from the University of Florida sparse matrix collection to illustrate merits of the proposed task-based factorization. Experimental results demonstrate that our task-parallel implementation delivers about 26.6x speedup (geometric mean) over single-threaded incomplete Choleskyby- blocks and 19.2x speedup over serial Cholesky performance which does not carry tasking overhead using 56 threads on the Intel Xeon Phi processor for sparse matrices arising from various application problems.

2D layout↗
DOE OSTI2016

Systems Biology Model of Interactions between Tissue Growth Factors and DNA Damage Pathways: Low Dose Response and Cross-Talk in TGFβ and ATM Signaling

The etiology of radiation carcinogenesis has been described in terms of aberrant changes that span several levels of biological organization. Growth factors regulate many important cellular and tissue functions including apoptosis, differentiation and proliferation. A variety of genetic and epigenetic changes of growth factors have been shown to contribute to cancer initiation and progression. It is known that cellular and tissue damage to ionizing radiation is in part initiated by the production of reactive oxygen species, which can activate cytokine signaling, and the DNA damage response pathways, most notably the ATM signaling pathway. Recently, the transforming growth factor β (TGFβ) pathway has been shown to regulate or directly interact with the ATM pathway in the response to radiation. The relevance of this interaction with the ATM pathway is not known although p53 becomes phosphorylated and DNA damage responses are involved. However, growth factor interactions with DNA damage responses have not been elucidated particularly at low doses, and further characterization of their relationship to cancer processes is warranted. Our goal will be to use a systems biology approach to mathematically and experimentally describe the low-dose responses and cross-talk between the ATM and TGFβ pathways initiated by low- and high-LET radiation. We will characterize ATM and TGFβ signaling in epithelial and fibroblast cells using 2D models and ultimately extending to 3D organotypic cell culture models to begin to elucidate possible differences that may occur for different cell types and/or inter-cellular communication. We will investigate the roles of the Smad and Activating transcription factor 2 (ATF2) proteins as the potential major contributors to crosstalk between the TGFβ and ATM pathways, and links to cell cycle control and/or the DNA damage response, and potential differences in their responses at low and high doses. We have developed various experimental approaches to apply to these problems using confocal microscopy and flow cytometry to detail changes at low dose/dose-rate in order to understand individual cell responses, and will establish our mathematical models based on the experimental findings resulting from changes in DNA repair, apoptosis and proliferation.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

A User-Centered Design Exploration of Factors That Influence the Rideshare Experience

The rise of real-time information communication through smartphones and wireless networks enabled the growth of ridesharing services. While personal rideshare services (individuals riding alone or with acquaintances) initially dominated the market, the popularity of pooled ridesharing (individuals sharing rides with people they do not know) has grown globally. However, pooled ridesharing remains less common in the U.S., where personal vehicle usage is still the norm. Vehicle design and rideshare services may need to be tailored to user preferences to increase pooled rideshare adoption. Based on a large, national U.S. survey (N = 5385), the results of exploratory and confirmatory factor analyses suggested that four key factors influence riders’ willingness to consider pooled ridesharing: comfort/ease of use, convenience, vehicle technology/accessibility, and passenger safety. A binomial logistic regression was conducted to determine how the four factors influence one’s willingness to consider pooled ridesharing. The two factors that positively influence riders’ willingness to consider pooled ridesharing are vehicle technology/accessibility (B = 1.10) and convenience (B = 0.94), while lack of passenger safety (B = –0.63) and comfort/ease of use (B = –0.17) are pooled ridesharing deterrents. Understanding user-centered design and service factors are critical to increase the use of pooled ridesharing services in the future.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1964

Biomedical and Human Factors Requirements for a Manned Earth Orbiting Station

The primary objective of this study is to determine which biomedical and human factors measurements must be made aboard a space station to assure adequate evaluation of the astronaut's health and performance during prolonged space flights. The study has employed, where possible, a medical and engineering systems analysis to define the pertinent life sciences and space station design parameters and their influence on a measurement program. The major areas requiring evaluation in meeting the study objectives include a definition of the space environment, man's response to the environment, selection of measurement and data management techniques, experimental program, space station design requirements, and a trade-off analysis with final recommendations. The space environment factors that are believed to have a significant effect on man were evaluated. This includes those factors characteristic of the space environment (e. g. weightlessness, radiation) as well as those created within the space station (e. g. toxic contaminants, capsule atmosphere). After establishing the general features of the environment, an appraisal was made of the anticipated response of the astronaut to each of these factors. For thoroughness, the major organ systems and functions of the body were delineated, and a determination was made of their anticipated response to each of the environmental categories. A judgment was then made on the medical significance or importance of each response, which enabled a determination of which physiological and psychological effects should be monitored. Concurrently, an extensive list of measurement techniques and methods of data management was evaluated for applicability to the space station program. The various space station configurations and design parameters were defined in terms of the biomedical and human factors requirements to provide the measurements program. Research design of experimental programs for various station configurations, mission durations, and crew sizes were prepared, and, finally, a trade-off analysis of the critical variables in the station planning was completed with recommendations to enhance the confidence in the measurement program.

EARTH ORBIT↗
NASA NTRS1999

Cloning the promoter for transforming growth factor-beta type III receptor. Basal and conditional expression in fetal rat osteoblasts

Transforming growth factor-beta binds to three high affinity cell surface molecules that directly or indirectly regulate its biological effects. The type III receptor (TRIII) is a proteoglycan that lacks significant intracellular signaling or enzymatic motifs but may facilitate transforming growth factor-beta binding to other receptors, stabilize multimeric receptor complexes, or segregate growth factor from activating receptors. Because various agents or events that regulate osteoblast function rapidly modulate TRIII expression, we cloned the 5' region of the rat TRIII gene to assess possible control elements. DNA fragments from this region directed high reporter gene expression in osteoblasts. Sequencing showed no consensus TATA or CCAAT boxes, whereas several nuclear factors binding sequences within the 3' region of the promoter co-mapped with multiple transcription initiation sites, DNase I footprints, gel mobility shift analysis, or loss of activity by deletion or mutation. An upstream enhancer was evident 5' proximal to nucleotide -979, and a silencer region occurred between nucleotides -2014 and -2194. Glucocorticoid sensitivity mapped between nucleotides -687 and -253, whereas bone morphogenetic protein 2 sensitivity co-mapped within the silencer region. Thus, the TRIII promoter contains cooperative basal elements and dispersed growth factor- and hormone-sensitive regulatory regions that can control TRIII expression by osteoblasts.

Non-NASA Center↗
NASA NTRS2016

Human Factors in Aeronautics at NASA

This is a briefing to a regularly meeting DoD group called the Human Systems Community of Interest: Mission Effectiveness. I was asked to address human factors in aeronautics at NASA. (Exploration (space) human factors has apparently already been covered.) The briefing describes human factors organizations at NASA Ames and Langley. It then summarizes some aeronautics tasks that involve the application of human factors in the development of specific tools and capabilities. The tasks covered include aircrew checklists, dispatch operations, Playbook, Dynamic Weather Routes, Traffic Aware Strategic Aircrew Requests, and Airplane State Awareness and Prediction Technologies. I mention that most of our aeronautics work involves human factors as embedded in development tasks rather than basic research.

NASA↗
DOE OSTI2016

Human Factors Principles in Information Dashboard Design

When planning for control room upgrades, nuclear power plants have to deal with a multitude of engineering and operational impacts. This will inevitably include several human factors considerations, including physical ergonomics of workstations, viewing angles, lighting, seating, new communication requirements, and new concepts of operation. In helping nuclear power utilities to deal with these challenges, the Idaho National Laboratory (INL) has developed effective methods to manage the various phases of the upgrade life cycle. These methods focus on integrating human factors engineering processes with the plant’s systems engineering process, a large part of which is the development of end-state concepts for control room modernization. Such an end-state concept is a description of a set of required conditions that define the achievement of the plant’s objectives for the upgrade. Typically, the end-state concept describes the transition of a conventional control room, over time, to a facility that employs advanced digital automation technologies in a way that significantly improves system reliability, reduces human and control room-related hazards, reduces system and component obsolescence, and significantly improves operator performance. To make the various upgrade phases as concrete and as visible as possible, an end-state concept would include a set of visual representations of the control room before and after various upgrade phases to provide the context and a framework within which to consider the various options in the upgrade. This includes the various control systems, human-system interfaces to be replaced, and possible changes to operator workstations. This paper describes how this framework helps to ensure an integrated and cohesive outcome that is consistent with human factors engineering principles and also provide substantial improvement in operator performance. The paper further describes the application of this integrated approach in the strategic modernization program at a nuclear power plant where legacy systems are upgraded to advanced digital technologies through a systematic process that links human factors principles to the systems engineering process. This approach will help to create an integrated control room architecture beyond what is possible for individual subsystem upgrades alone. In addition, several human factors design and evaluation methods were used to develop the end-state concept, including interactive sessions with operators in INL’s Human System Simulation Laboratory, three-dimensional modeling to visualize control board changes.

3D Modeling↗
DOE OSTI2019

Development of a Fleet-Level Human Factors Engineering Program to Support the Digital Modernization of Multiple Turbine Control Systems

A number of years ago, Duke Energy and the United States (U.S.) Department of Energy (DOE) entered into a collaboration to support Duke’s digital upgrade activities for the main control rooms at three of their commercial nuclear power stations. The collaboration specifically focused on the human factors engineering (HFE) aspects of Duke’s plans to upgrade the legacy turbine control systems (TCS) at their Brunswick, Robinson, and Harris plants. This TSC upgrade involved installing a common digital control system (DCS), or distributed instrumentation and control (I&C) system platform, which multiple digital plant control systems can be integrated onto as the control rooms are modernized over time. Given the breadth and depth of the scope of this upgrade, DOE researchers at Idaho National Laboratory (INL) with expertise in human factors collaborated with Duke throughout the entire HFE life cycle to help ensure the upgrade was performed in a manner consistent with regulatory human factors review criteria, such as the U.S. Nuclear Regulatory Commission’s (NRC) Human Factors Engineering Program Review Model (NUREG 0711, 2012). This paper describes the HFE researchers performed through the early and middle phases of these TCS upgrades. Specific HFE activities include: 1) the development of a human factors program management plan, 2) performing an operational experience review, 3) evaluating the design human system interface while it was still in the early stages of development, and 4) developing a framework to help map these HFE activities to NUREG-0711 to help understand and catalog the value of different types and phases of human performance data collection. These four HFE activities are described in more detail below.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Understanding Bifacial PV Modeling: Raytracing and View Factor Models

As part of the PV Magazine Webinar 'View-factor vs. ray tracing - which bifacial modelling techniques should you use?,' the second part lead by NREL will explore the different rear-irradiance calculation software, which fall into two categories: view-factor and ray-tracing models. View factor models assume isotropic scattering of reflected rays, allowing for calculation of irradiance by integration. Due-diligence software such as PVSyst or SAM use the view-factor model. Ray-tracing models simulate multipath reflection and absorption of individual rays entering a scene. Raytracing software such as bifacial_radiance, which is the only available open-source toolkit, offers the possibility of reproducing complex scenes, including shading or finite-system edge effects. This can be useful to evaluate specific system geometries, shading and obstructions, areas of different albedo and electrical mismatch, all topics of interest to the prediction of bifacial performance. Model agreement for view factors and bifacial_radiance software is improving and has been shown to be between 2% (absolute) when compared with measured results.

14 SOLAR ENERGY↗