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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 505 records · Page 28

Initial Investigation of the Angular Dependence of the NOAA-20 VIIRS Solar Diffuser BRDF Change Factor

The NOAA-20 (formerly the Joint Polar Satellite System-1) satellite was launched on November 18, 2017. One of the five scientific instruments aboard the NOAA-20 satellite (N20) is the Visible Infrared Imaging Radiometer Suite (VIIRS). The VIIRS scans the earth surface in 22 spectral bands, of which 14 are denoted as the reflective solar bands (RSBs) with design band central wavelengths from 412 to 2250 nm. The VIIRS regularly performs on-orbit radiometric calibration of its RSBs, primarily through observations of an onboard sunlit solar diffuser (SD). The on-orbit change of the SD bidirectional reflectance distribution function (BRDF) value, denoted as the H-factor, is determined by an onboard solar diffuser stability monitor (SDSM). We have shown that the H-factor for the SD on the VIIRS instrument on the Suomi National Polar-orbiting Partnership (SNPP) satellite is both incident and outgoing sunlight direction dependent. This angular dependence profoundly affects the on-orbit radiometric calibration process and results. Here, we give preliminary results for the angular dependence for the N20 VIIRS SD H-factor, and compare the dependence with that for the SNPP VIIRS.

radiometric calibration↗

Calculating Factors of Safety and Margins of Safety from Interaction Equations

This report presents the derivation of the relationship between the factor of safety, the margin of safety, and a given interaction equation in two- or three-dimensional space. Factors of safety and margins of safety can be calculated from these interaction equations using either the closed-form solutions provided or the numerical methods mentioned in this report. The dual definition of the factor of safety is presented.

Factor of Safety↗

Maintenance Human Factors and Flight Safety

This chapter will chronicle the journey of the community of operators, regulators, and researchers who embarked upon the task of identifying critical human factors of maintenance and inspection, establishing a database and research tools, developing practical strategies for reducing the risks of maintenance and inspection errors, and understanding its critical role in preserving flight safety. We will take a historical perspective, developing a timeline that is largely driven by key events such as accidents and regulatory/government actions and initiatives. Part 1 focuses on how the field of maintenance human factors was built, beginning in the late 1980’s. Part 2 describes the development of methods and tools for meeting the maintenance human factors challenges identified. Finally, Part 3 updates the original chapter by focusing on issues that have persisted or emerged since 2010.

maintenance↗

Using Qualified On-Site Nuclear Power Plant Simulators in Human Factors Validations of Control Room Upgrades

Existing commercial nuclear power plants (NPPs) are valuable assets in the infrastructure portfolio of the United States (U.S.) because they safely and reliably generate about 1/5th of all the electricity used. The instrumentation and control (I&C) systems in commercial NPPs are the ‘eyes and ears' of the operator, allowing operators to maintain situation awareness, thereby allowing the plant to operate safely and efficiently for all phases of operation. Because the I&C systems in NPPs are still mostly based on analog technologies, which are reliable but not especially cost-effective, upgrading the existing I&C in com-mercial NPPs to new digital I&C is very important. Furthermore, simulators and simulation are critical human factors engineering tools for this I&C modernization work. NPP control room simulators are essential test beds to simulate normal, abnormal, and emergency operations that allow human factors researchers to safely and realistically evaluate early design phase prototypes of the upgraded digital I&C, and validate final as-built digital I&C systems that have been modernized deployed in NPPs. This paper describes research performed using qualified on-site NPP simulators to perform human factors validations of digital I&C control room upgrades.

99 GENERAL AND MISCELLANEOUS↗

ENABLING BUSINESS-DRIVEN INNOVATION THROUGH HUMAN FACTORS ENGINEERING IN NUCLEAR POWER PLANTS

For existing United States nuclear power plant fleet to remain economically viable, the nuclear industry needs to fundamentally change the way in which these plants are operated, maintained, and supported. A digital transformation is a key strategy to address this challenge. Though, guidance in this area is a continued effort. One framework to support innovation in the nuclear industry has taken a broader perspective by focusing on how technology can be used to meet specific business needs and work for the people and processes at hand. This work discusses the role and value of human factors engineering within this nuclear innovation framework. Human factors methods are presented here regarding how they address the phases of nuclear innovation. This work seeks to describe how human factors can be applied in nuclear innovation by strengthening the alignment of technology, people, processes, and regulations such that the needs of the business is addressed.

99 GENERAL AND MISCELLANEOUS↗

General-Purpose Unsupervised Cyber Anomaly Detection via Non-Negative Tensor Factorization

Distinguishing malicious anomalous activities from unusual but benign activities is a fundamental challenge for cyber defenders. Prior studies have shown that statistical user behavior analysis yields accurate detections by learning behavior profiles from observed user activity. These unsupervised models are able to generalize to unseen types of attacks by detecting deviations from normal behavior, without knowledge of specific attack signatures. However, approaches proposed to date based on probabilistic matrix factorization are limited by the information conveyed in a two-dimensional space. Non-negative tensor factorization, on the other hand, is a powerful unsupervised machine learning method that naturally models multi-dimensional data, capturing complex and multi-faceted details of behavior profiles. Herein, our new unsupervised statistical anomaly detection methodology matches or surpasses state-of-the-art supervised learning baselines across several challenging and diverse cyber application areas, including detection of compromised user credentials, botnets, spam e-mails, and fraudulent credit card transactions.

97 MATHEMATICS AND COMPUTING↗

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

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 fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow 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 (NMFk), 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. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗

Alterations in renal stone risk factors after space flight

Exposure to the microgravity environment of space produces a number of physiological changes of metabolic and environmental origin that could increase the potential for renal stone formation. Metabolic, environmental and physicochemical factors that influence renal stone risk potential were examined in 24-hour urine samples from astronauts 10 days before launch and on landing day to provide an immediate postflight assessment of these factors. In addition, comparisons were made between male and female crewmembers, and between crewmembers on missions of less than 6 days and those on 6 to 10-day missions. Results suggest that immediately after space flight the risk of calcium oxalate and uric acid stone formation is increased as a result of metabolic (hypercalciuria, hypocitraturia, pH) and environmental (lower urine volume) derangements, some of which could reflect residual effects of having been exposed to microgravity.

NASA Center JSC↗

Reproductive Factors and Endometrial Cancer Risk Among Women

Despite evidence of an association between reproductive factors and endometrial cancer risk, prospective studies have been conducted mainly in non-Asian countries. To assess the association between reproductive factors, such as number of deliveries, age at menarche, or menopause, and endometrial cancer risk. This cohort study used pooled individual data from 13 prospective cohort studies conducted between 1963 and 2014 in the Asia Cohort Consortium. Participants were Asian women. Data analysis was conducted from September 2019 to April 2023. Reproductive factors were assessed using a questionnaire in each cohort. The main outcome was time to incidence of endometrial cancer. A Cox proportional hazards model was used to calculate hazard ratios (HRs) and 95% CIs.

60 APPLIED LIFE SCIENCES↗

Toward Ultra‐High‐Quality‐Factor Wireless Masing Magnetic Resonance Sensing

It has recently been shown that a bolus of hyperpolarized nuclear spins can yield stimulated emission signals similar in nature to maser signals, potentially enabling new ways of sensing hyperpolarized contrast media, including most notably [1- 13 C]pyruvate that is under evaluation in over 50 clinical trials for metabolic imaging of cancer. The stimulated NMR signal emissions lasting for minutes do not require radio-frequency excitation, offering unprecedented advantages compared to conventional MR sensing. However, creating nuclear spin maser emission is challenging in practice due to stringent fundamental requirements, making practical in vivo applications hardly possible using conventional passive MR detectors. Here, in this study, we demonstrate the utility of a wireless NMR maser detector, the quality factor of which was enhanced 22-fold (to 1,670) via parametric pumping. This active-feedback technique breaks the intrinsic fundamental limit of NMR detector circuit quality factor. We show the use of parametric pumping to reduce the threshold requirement for inducing nuclear spin masing at 300 MHz resonance frequency in a preclinical MRI scanner. Indeed, stimulated emission from hyperpolarized protons was obtained under highly unfavorable conditions of low magnetic field homogeneity (T 2 * of 3 ms). Greater gains of the quality factor of the MR detector (up to 1 million) were also demonstrated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Association of female reproductive and hormonal factors with gallbladder cancer risk in Asia: A pooled analysis of the Asia Cohort Consortium

Abstract The female predominance of gallbladder cancer (GBC) has led to a hypothesis regarding the hormone‐related aetiology of GBC. We aimed to investigate the association between female reproductive factors and GBC risk, considering birth cohorts of Asian women. We conducted a pooled analysis of 331,323 women from 12 cohorts across 4 countries (China, Japan, Korea, and Singapore) in the Asia Cohort Consortium. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) to assess the association between reproductive factors (age at menarche, parity, age at first delivery, breastfeeding, and age at menopause) and GBC risk. We observed that a later age at menarche was associated with an increased risk of GBC (HR 1.4, 95% CI 1.16–1.70 for 17 years and older vs. 13–14 years), especially among the cohort born in 1940 and later (HR 2.5, 95% CI 1.50–4.35). Among the cohort born before 1940, women with a later age at first delivery showed an increased risk of GBC (HR 1.56, 95% CI 1.08–2.24 for 31 years of age and older vs. 20 years of age and younger). Other reproductive factors did not show a clear association with GBC risk. Later ages at menarche and at first delivery were associated with a higher risk of GBC, and these associations varied by birth cohort.

Shin, Aesun↗

Factors influencing pregnancy, litter size, and reproductive parameters of invasive wild pigs

Abstract Reproduction is the most energetically expensive life stage with the demands of productivity representing a balance between physiological requirements and environmental conditions. Wild pigs ( Sus scrofa ) throughout most of North America are genetic hybrids of feral domestic pigs and wild boar and have the highest reproductive potential of any wild ungulate. The phenology of reproduction, extent of multiple reproductive events per year, how individual and extrinsic factors contribute to variability in productivity, and impact of genetic lineage on these parameters is not well understood in wild pigs. We quantified reproductive parameters in wild pigs relative to a suite of individual and environmental attributes across seasons and multiple years in South Carolina, USA, from March 2017 and May 2020. We hypothesized that individual attributes (mass, age class, number of teats, rump fat, relative genetic association to wild boar vs. domestic pigs) and extrinsic factors (mast availability) would influence probability of pregnancy and fetal litter size. Wild pigs produced offspring throughout all months with peaks in conception corresponding to a seasonal pulse in food availability. The likelihood of pregnancy was influenced by female mass and nutritional condition and was greatest during years with abundant resources. Similarly, litter size increased with female mass and age, implying larger and older females represent the most important group for population recruitment. In evaluating the relationship between reproductive output and ancestral associations to domestic pigs versus wild boar, the proportion of wild boar ancestry was not an important influence on productivity in our population. We determined juveniles reach a physiological threshold of sexual maturity at approximately 30 kg. Average litter size was comparable to other populations, and wild pigs maintain an average fetal litter size of 5.43 offspring despite 13.6% embryonic mortality. A thorough understanding of biotic and extrinsic factors influencing reproduction are important for realistic population models, which are necessary for identifying areas to focus management needs and implementation.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of biotic and abiotic factors on home range size and shape of invasive wild pigs ( Sus scrofa )

Determining factors influencing animal movements at a temporal scale that is similar to that at which management actions are conducted (e.g. weekly) is crucial for identifying efficient methods of wildlife conservation and management. Using global positioning system (GPS) data from 49 wild pigs in the southeast United States, we constructed weekly 50% and 95% utilization distributions to quantify the effects of biotic and abiotic factors on weekly core area and home range size, as well as home range shape. Here we found vegetative composition (i.e. proportion of bottomland hardwoods), season (based on forage availability), meteorological conditions (i.e. temperature and pressure), and sex influenced wild pig weekly home range and core area size, while vegetative composition (i.e. proportion of upland pines) and landscape features (i.e. distance to streams) also were important factors influencing home range shape. At close distances to streams, wild pigs had more elongate home ranges when their home ranges comprised less upland pine habitat; however, farther from streams, there was no change in home range shape across fluctuating proportions of upland pines. These results demonstrate that fine-scale wild pig home ranges and movements are pliable from week to week and influenced by several habitat, landscape, and meteorological attributes that can easily be quantified from available land use and meteorological databases. These findings are important for designing monitoring studies, identifying high risk zones for disease transmission, planning response to disease emergence events, and allowing more effective and efficient short-term management planning.

60 APPLIED LIFE SCIENCES↗

Multifrontal Non-negative Matrix Factorization

Non-negative matrix factorization (Nmf) is an important tool in high-performance large scale data analytics with applications ranging from community detection, recommender system, feature detection and linear and non-linear unmixing. While traditional Nmf works well when the data set is relatively dense, however, it may not extract sufficient structure when the data is extremely sparse. Specifically, traditional Nmf fails to exploit the structured sparsity of the large and sparse data sets resulting in dense factors. We propose a new algorithm for performing Nmf on sparse data that we call multifrontal Nmf (Mf-Nmf) since it borrows several ideas from the multifrontal method for unconstrained factorization (e.g. LU and QR). We also present an efficient shared memory parallel implementation of Mf-Nmf and discuss its performance and scalability. We conduct several experiments on synthetic and realworld datasets and demonstrate the usefulness of the algorithm by comparing it against standard baselines. We obtain a speedup of 1.2x to 19.5x on 24 cores with an average speed up of 10.3x across all the real world datasets.

Sao, Piyush↗

Weak neutral current axial form factor using $ \left(\overline{\nu}\right)\nu $-nucleon scattering and lattice QCD inputs

We present a determination of the neutral current weak axial charge $G$ $^{Z}_{A}$(0) = –0.654(3) stat (5) sys using the strange quark axial charge $G$ $^{s}_{A}$(0) calculated with lattice QCD. We then perform a phenomenological analysis, where we combine the strange quark electromagnetic form factor from lattice QCD with (anti)neutrino-nucleon scattering differential cross section from MiniBooNE experiments in a momentum transfer region 0.24 ≲ Q 2 ≲ 0.71 GeV 2 to determine the neutral current weak axial form factor $G$ $^{Z}_{A}$(Q 2 ) in the range of 0 ≲ Q 2 ≤ 1 GeV 2 . This yields a phenomenological value of $G$ $^{Z}_{A}$(0) = –0.687(89)stat(40)sys. The value of $G$ $^{Z}_{A}$(0) constrained by the lattice QCD calculation of $G$ $^{s}_{A}$(0), when compared to its phenomenological determination, provides a significant improvement in precision and accuracy and can be used to provide a constraint on the fit to $G$ $^{Z}_{A}$(Q 2 ) for Q 2 > 0. This constrained fit leads to an unambiguous determination of (anti)neutrino-nucleon neutral current elastic scattering differential cross section near Q 2 = 0 and can play an important role in numerically isolating nuclear effects in this region. We show a consistent description of $G$ $^{Z}_{A}$(Q 2 ) obtained from the (anti)neutrino-nucleon scattering cross section data requires a nonzero contribution of the strange quark electromagnetic form factor. We demonstrate the robustness of our analysis by providing a post-diction of the BNL E734 experimental data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A three-point form factor through five loops

We bootstrap the three-point form factor of the chiral part of the stress­tensor supermultiplet in planar $\mathcal{N}$ = 4 super-Yang-Mills theory, obtaining new results at three, four, and five loops. Our construction employs known conditions on the first, second, and final entries of the symbol, combined with new multiple-final-entry conditions, “extended-Steinmann-like” conditions, and near-collinear data from the recently-developed form factor operator product expansion. Our results are expected to give the maximally transcendental parts of the gg → Hg and H → ggg amplitudes in the heavy-top limit of QCD. At two loops, the extended-Steinmann-like space of functions we describe contains all transcendental functions required for four-point amplitudes with one massive and three massless external legs, and all massless internal lines, including processes such as gg → Hg and γ * → $q\overline{q}g$. We expect the extended-Steinmann-like space to contain these amplitudes at higher loops as well, although not to arbitrarily high loop order. We present evidence that the planar $\mathcal{N}$ = 4 three-point form factor can be placed in an even smaller space of functions, with no independent ζ values at weights two and three.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Asymptotic behavior of meson transition form factors

One of the open issues in evaluations of the contribution from hadronic light-by-light scattering to the anomalous magnetic moment of the muon (g - 2)µ concerns the role of heavier scalar, axial-vector, and tensormeson intermediate states. The coupling of axial vectors to virtual photons is suppressed for small virtualities by the Landau–Yang theorem, but otherwise there are few rigorous constraints on the corresponding form factors. In this paper, we first derive the Lorentz decomposition of the two-photon matrix elements into scalar functions following the general recipe by Bardeen, Tung, and Tarrach. Based on this decomposition, we then calculate the asymptotic behavior of the meson transition form factors from a light-cone expansion in analogy to the asymptotic limits for the pseudoscalar transition form factor derived by Brodsky and Lepage. Finally, we compare our results to existing data as well as previous models employed in the literature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Two-loop MHV form factors from the periodic Wilson loop

We discuss how to compute maximal-helicity-violating (MHV) form factors for the chiral part of the stress-tensor supermultiplet from periodic light-like polygon Wilson loops in planar $\mathcal{N}$ = 4 super Yang-Mills theory beyond the one-loop level. We show that the periodicity imposes path ordering on points on different edges, which explains the appearance of square roots coming from non-planar Feynman diagrams. Taking such diagrams into account, we provide the integrand of the two-loop n-particle MHV form factor, compute all diagrams, prove the cancellation of divergences and finally compute the two-loop 5-particle and 6-particle form factors as examples.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗