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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 163 records · Page 9

An evaluation of selected NASA scientific and technical information products: Results of a pilot study

A pilot study was conducted to evaluate selected NASA scientific and technical information (STI) products. The study, which utilized survey research in the form of a self-administered mail questionnaire, had a two-fold purpose -- to gather baseline data regarding the use and perceived usefulness of selected NASA STI products and to develop/validate questions that could be used in a future study concerned with the role of the U.S. government technical report in aeronautics. The sample frame consisted of 25,000 members of the American Institute of Aeronautics and Astronautics in the U.S. with academic, government or industrial affiliation. Simple random sampling was used to select 2000 individuals to participate in the study. Three hundred fifty-three usable questionnaires (17 percent response rate) were received by the established cutoff date. The findings indicate that: (1) NASA STI is used and is generally perceived as being important; (2) the use rate for NASA-authored conference/meeting papers, journal articles, and technical reports is fairly uniform; (3) a considerable number of respondents are unfamiliar with STAR (Scientific and Technical Aerospace Reports), IAA (International Aerospace Abstracts), SCAN (Selected Current Aerospace Notices), and the RECON on-line retrieval system; (4) a considerable number of respondents who are familiar with these media do not use them; and (5) the perceived quality of NASA-authored journal articles and technical reports is very good.

Pinelli, Thomas E.↗

FOCIS: A forest classification and inventory system using LANDSAT and digital terrain data

Accurate, cost-effective stratification of forest vegetation and timber inventory is the primary goal of a Forest Classification and Inventory System (FOCIS). Conventional timber stratification using photointerpretation can be time-consuming, costly, and inconsistent from analyst to analyst. FOCIS was designed to overcome these problems by using machine processing techniques to extract and process tonal, textural, and terrain information from registered LANDSAT multispectral and digital terrain data. Comparison of samples from timber strata identified by conventional procedures showed that both have about the same potential to reduce the variance of timber volume estimates over simple random sampling.

Strahler, A. H.↗

The Oxygen Isotopic Composition of Samples Returned From Asteroid Ryugu With Implications for the Nature of the Parent Planetesimal

We present oxygen isotopic analyses of fragments of the near-Earth C b -type asteroid Ryugu returned by the Hayabusa2 spacecraft that reinforce the close correspondence between Ryugu and CI chondrites. Small differences between Ryugu samples and CI chondrites in ∆' 17 O can be explained at least in part by contamination of the latter by terrestrial water. The discovery that a randomly sampled C-complex asteroid is composed of CI-chondrite-like rock, combined with thermal models for formation prior to significant decay of the short-lived radioisotope 26 Al, suggests that if lithified at the time of alteration, the parent body was small (<<50 km radius). If the parent planetesimal was large (>50 km in radius), it was likely composed of high-permeability, poorly lithified sediment rather than consolidated rock.

Asteroids↗

The Role of Data Filtering in Open Source Software Ranking and Selection

Faced with more than 100M open source projects, a more manageable small subset is needed for most empirical investigations. More than half of the research papers in leading venues investigated filtering projects by some measure of popularity with explicit or implicit arguments that unpopular projects are not of interest, may not even represent "real" software projects, or that less popular projects are not worthy of study. However, such filtering may have enormous effects on the results of the studies if and precisely because the sought-out response or prediction is in any way related to the filtering criteria.This paper exemplifies the impact of this common practice on research outcomes, specifically how filtering of software projects on GitHub based on inherent characteristics affects the assessment of their popularity. Using a dataset of over 100,000 repositories, we used multiple regression to model the number of stars -a commonly used proxy for popularity- based on factors such as the number of commits, the duration of the project, the number of authors and the number of core developers. Our control model included the entire dataset, while a second filtered model considered only projects with ten or more authors. The results indicated that while certain characteristics of the repository consistently predict popularity, the filtering process significantly alters the relationships between these characteristics and the response. We found that the number of commits exhibited a positive correlation with popularity in the control sample but showed a negative correlation in the filtered sample. These findings highlight the potential biases introduced by data filtering and emphasize the need for careful sample selection in empirical research of mining software repositories. We recommend that empirical work should either analyze complete datasets such as World of Code, or employ stratified random sampling from a complete dataset to ensure that filtering is not biasing the results.

Malviya Thakur, Addi↗

Uncertainty Estimates for Fitting Zernike Polynomials to Discrete Data

Zernike polynomials are a widely used metric in modern optical analysis. They conveniently represent surfaces as a series of weighted terms corresponding to various optical aberrations. Ideally, each term is independent of others in the series, but Zernike polynomials lose this property when working with sets of discrete data. This gives rise to uncertainty in each polynomial’s actual contribution and affects metrology and simulation estimates of their relative weights. Several factors influencing these estimates are the number and arrangement of sample locations, the method for calculating the weights, and the total number of Zernike terms used in the calculation. Discussed is the uncertainty associated with linear regression using random sampling. Other topics reviewed are complex Zernike polynomials and vector spaces of functions.

Zernike Polynomials↗

A Case Study in Assessing a Potential Severity Framework for Incidents from a Decadal Sample

In this study, the primary objective of this case study is to determine the applicability and feasibility of a framework that leverages occupational incident details to prospectively identify “potential Serious Injury or Fatality” (pSIF) cases. This study comprehensively reviewed a random sample of 1,081 injury and illness cases across 21 generalized incident types spanning over a decade at Lawrence Livermore National Laboratory (LLNL), a U.S. Department of Energy research and development facility with more than 9,000 employees. The review applied a general framework that classified each case on information suitability, potential severity, and future incident mitigation. The findings from the study indicate that 86.6% of the cases had sufficient information to make a high-confidence determination on potential severity, underscoring the feasibility of applying this general framework. Additionally, cases with a higher pSIF score had, on average, a higher level of institutional response. Implementing a simplified methodology for incident classification that emphasizes incidents that pose high potential severity, regardless of incident type, can help LLNL prioritize resources and tailor responses to such incidents using a graded approach. LLNL has recognized the value of this capability and is integrating the framework into their injury and illness process in the 2024 calendar year.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Computing the QRPA level density with the finite amplitude method

Here, we describe a new algorithm to calculate the vibrational nuclear level density of an atomic nucleus. Fictitious perturbation operators that probe the response of the system are generated by drawing their matrix elements from some probability distribution function. We use the Finite Amplitude Method to explicitly compute the response for each such sample. With the help of the Kernel Polynomial Method, we build an estimator of the vibrational level density and provide the upper bound of the relative error in the limit of infinitely many random samples. The new algorithm can give accurate estimates of the vibrational level density. Since it is based on drawing multiple samples of perturbation operators, its computational implementation is naturally parallel and scales like the number of available processing units.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

hiposa v0.1.0

Fast construction of hierarchical N-dimensional experimental design. The software allows construction of sampling strategies that are self-avoiding, tunable in resolution in N dimensions. This code is a drop-in replacement for seeding optimization runs often performed using uniform random sampling. The hierarchical approach allows for a rapid, top down method for construction the most effective design that drives towards a global optimum.

Zwart, PetrusH [Lawrence Berkeley National Laborat↗

Energy Delivery Systems with Verifiable Trustworthiness (Final Report)

Energy Delivery Systems (EDS) must be verified to be free from intrusive and malicious software. One way of verifying this software is to perform device scans to detect malicious code. Because it is possible to have “fileless” malware that exists only in device (volatile) memory, offline scanning and even many forms of online scanning is insufficient for detection. This project (“Verify”) addresses this need by performing direct sampling of memory during device operation to detect unexpected or modified software while not interfering with device operation. The Verify project provides a proof-of-concept of detection by random sampling combined with remote software- and timing-based attestation methods for robust detection of in-memory threats. An external review of Verify was performed by our partner, General Electric (GE), and a summary of their findings is provided.

97 MATHEMATICS AND COMPUTING↗

High-Dimensional Spectral Sampling

A wide variety of applications in science and engineering depend on effectively and efficiently exploring high- dimensional parameter spaces. Common examples are uncertainty quantification, inverse problems, or various optimization approaches. In such applications, the first step is to create an initial uniform, random sampling of the space to create a baseline of knowledge. The simulations evaluated at these samples are then used for subsequent processing. In its most generic form, the goal of sampling is to produce the maximal amount of information with the minimal number of samples. However, despite being the first step and thus influencing the performance of the entire workflow, the quality of the initial sample designs is rarely analyzed or optimized. This project develops a new spectral sampling theory for analyzing and creating experiment designs in high-dimensional spaces. Further, new algorithms for estimating sample properties and sample synthesis are designed. Finally, applications of the proposed spectral sampling tools in surrogate modeling, scientific machine learning and image analysis are presented.

97 MATHEMATICS AND COMPUTING↗

A Machine Learning-Based Vulnerability Analysis for Cascading Failures of Integrated Power-Gas Systems

This article proposes a cascading failure simulation (CFS) method and a hybrid machine learning method for vulnerability analysis of integrated power-gas systems (IPGSs). The CFS method is designed to study the propagating process of cascading failures between the two systems, generating data for machine learning with initial states randomly sampled. The proposed method considers generator and gas well ramping, transmission line and gas pipeline tripping, island issue handling and load shedding strategies. Then, a hybrid machine learning model with a combined random forest (RF) classification and regression algorithms is proposed to investigate the impact of random initial states on the vulnerability metrics of IPGSs. Extensive case studies are carried out on three test IPGSs to verify the proposed models and algorithms. Simulation results show that the proposed models and algorithms can achieve high accuracy for the vulnerability analysis of IPGSs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Large Ordinary Chondrite Shower in the Dominion Range

The US Antarctic Meteorite Program has visited the Dominion Range in the Transantarctic Mountains during several different seasons, including the 1985, 2003, 2008, 2010, and 2014 seasons. Total recovered meteorites from this region is over 2000. The 2008 and 2010 seasons have been fully classified and, respectively) revealing the presence of a large meteorite shower that comprises approximately 60% of all samples recovered in those two seasons. The oil immersion classification suggests that this shower is LL chondrite material, whereas published magnetic susceptibility (MS; log chi) measurements yield L chondrite values. However, usually random sampling of a large collection like this would uncover EOC material for which we have prepared thin sections. In this case, no LL chondrite materials have been found in thin section, suggesting that the shower might instead be an L chondrite. L and LL chondrites are notoriously difficult to distinguish using oil immersion techniques. To better characterize this large group of samples, we have decided to examine some of the large members of this group, using EMPA analysis of the olivines to verify the classifications. With a compositional link between this subset of samples, and the MS measurements, we can more confidently classify the samples making up this pairing group. Subsequently, more accurate and meaningful comparisons may be drawn between this pairing group and some other Antarctic pairing groups such as from the Queen Alexandra Range (QUE), and Lewis Cliffs Ice Tongue (LEW). electron microprobe analysis

Satterwhite, C. E.↗

Survey of Antihomology Research

Homology has been gaining traction as a tool for studying patterns in real-world datasets. During the past year, I have sought to understand a slight variant on the typical computation of homology of a metric space which we term antihomology . This exposition will survey that work. In section 2, I begin with findings from computations on samples from common spaces (the circle, the disc, and the square). Section 3 presents one conjecture and one lemma regarding 1-dimensional cycles on the circle with evenly space points and the circle with random sampling. In section 4, I applied antihomology to power grid datasets and compared results with more traditional data reduction techniques. Lastly, section 5 reveals the connection between antihomology and location covering problems.

97 MATHEMATICS AND COMPUTING↗

Understanding the Awareness, Knowledge and Perceptions of Interventional Radiology Amongst Undergraduates in the UK

Introduction: The role of interventional radiology (IR) in health care is rapidly expanding in the United Kingdom (UK). However, the presence of IR in the current undergraduate curriculum is lacking. Purpose: This study investigates the awareness, knowledge and perceptions of IR in undergraduates through the clinical years of medical school to suggest future interventions. Methods: A total of 360 questionnaires, designed to test undergraduates’ knowledge of, and exposure to, IR were distributed over a 14-day period in a UK medical institution. Results: Of the 312 respondents (86.7%), the majority had never formally shadowed a radiologist (65.4%) or encountered teaching from an interventional radiologist (54.5%). Most students (88.5%) felt their knowledge of IR was lower than other specialties. Students’ knowledge of IR procedures did not statistically increase through the clinical years. Students were most cognisant of vascular procedures and least aware of IR’s role in oncology. Only 10.9% would consider a career in IR, with 39.7% citing the lack of knowledge and 18.6% citing patient contact as the top reasons for this. Conclusion: Current students have poor exposure to IR through the undergraduate curriculum. Consequently, there is no increase in knowledge of IR clinical practice through the clinical years. Multi-level interventions, incorporating universities and radiological societies are required to increase undergraduate awareness and promote IR as a career. Level of Evidence: Level 3, Local non-random sample.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Deconsolidation and Leach Burn Leach of Seven As Irradiated AGR 5/6/7 TRISO Fuel Compacts from Capsules 2, 3, 4, and 5

Seven as-irradiated Advanced Gas Reactor (AGR) 5/6/7 compacts underwent destructive post-irradiation examination via deconsolidation-leach-burn leach at Idaho National Laboratory (INL). The selection of the compacts extended the upper and lower limits of time-average volume-average (TAVA) temperature for compacts that had gone through deconsolidation-leach-burn leach so far. The measured inventories of fission products and actinides in the compact matrix and outer pyrolytic carbon were reported. Results indicated unexpectedly higher rates of fuel kernel leaching compared to compacts from AGR-1 and AGR-2. These failure rates were attributed to damage during post-irradiation sample handling, rather than irradiation itself. AGR-5/6/7 compacts have little or no matrix coverage for some particles at the top and bottom ends of cylindrical fuel compacts, making them more fragile. Sixty particles were randomly sampled from each compact, and the gamma results were reported. Three SiC shells from were identified, one of which showed signs of chemical attack in the high-irradiation temperature compact.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Statistical Sampling Plan for AGR-5/6/7 Fuel Materials

Kernels, coated particles, and compacts will be manufactured to predefined specifications for irradiation in the AGR 5/6/7 experiments. Many tests will be performed for quality assurance and most of these tests correspond to criteria that have to be met with 95% confidence, based on random samples. This report describes the statistical acceptance testing methods and gives minimum sample sizes for kernels to achieve 95% confidence. Coated particles and compacts will be addressed in revisions to this report. The methods used for sample size determination are described in detail in INL/EXT 05 00349, Statistical Methods Handbook for Advanced Gas Reactor Fuel Materials (Einerson 2005). The statistical approach is to collect a representative sample, apply an acceptance test to the sample, and accept or reject the product based on this test for each criterion. The criteria or “product specifications” are contained in SPC-1352, “AGR 5/6/7 Fuel Specification,” Revision 1 and are duplicated in this plan.