AI Surrogate Model for Distributed Computing Workloads
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97 MATHEMATICS AND COMPUTING↗
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An Approach to Dependence Assessment in Human Reliability Analysis: Application of Lag and Linger Effects
Dependence assessment refers to an approach used in human reliability analysis (HRA) to adjust a human error probability (HEP) for the following action by considering the impact of the preceding action. It has been known to significantly affect the overall results of probabilistic safety assessment (PSA). If the dependence assessment is not adequate, the result could be unconvincing for explaining the operator failures in the context of PSA. To date, several methods and some recent research have identified suggestions for treating dependence issues in HRA; however, these are still exclusively based on the intrinsic approach of the Technique for Human Error Rate Prediction (THERP), an HRA method. THERP inevitably has a challenge with the subjectivity of expert evaluation as well as the requirement for PSA and HRA expertise with resource-intensive and time-consuming processes. This paper suggests an approach to dependence assessment that could not only minimize the influence of expert judgment, but also saves time to perform the analysis with reasonable manpower. It modifies existing HRA methods with considering lag and linger effects to apply dependence effects for them. Based on a representative HRA method, i.e., Standardized Plant Analysis Risk - HRA (SPAR-H), guidance for how to apply lag and linger effects for the HRA method is suggested. Then, an investigation is carried out to compare quantification results of the revised HRA method with that of the original approach based on experimental data.
99 GENERAL AND MISCELLANEOUS↗
Analysis of flight test measurements in ground effect
Three sources of errors, introduced into the air-data measurements of altitude and airspeed as a result of ground proximity, are evaluated. It is shown that the primary error results from ground constraint of the wing lifting pattern. Smaller errors result from constraint of the flow over the fuselage and of the engine exhaust. Equations are derived to provide corrections for the three error contributions. The equations are general and can be applied to airplanes of different geometries operating in different conditions. Applications illustrating different types of flight operations (takeoff and landing) are presented using CV-990 data. Applications illustrating the effect of different static orifice locations (fuselage and nose-boom) are presented with YC-15 data. Finally, an application to trajectory reconstruction is illustrated using DC-10 data.
Parks, E. K.↗
Validation of multi-temperature nozzle flow code NOZNT
A computer code NOZNT (Nozzle in n-Temperatures), which calculates one-dimensional flows of partially dissociated and ionized air in an expanding nozzle, is tested against five existing sets of experimental data. The code accounts for: a) the differences among various temperatures, i.e., translational-rotational temperature, vibrational temperatures of individual molecular species, and electron-electronic temperature, b) radiative cooling, and c) the effects of impurities. The experimental data considered are: 1) the sodium line reversal and 2) the electron temperature and density data, both obtained in a shock tunnel, and 3) the spectroscopic emission data, 4) electron beam data on vibrational temperature, and 5) mass-spectrometric species concentration data, all obtained in arc-jet wind tunnels. It is shown that the impurities are most likely responsible for the observed phenomena in shock tunnels. For the arc-jet flows, impurities are inconsequential and the NOZNT code is validated by numerically reproducing the experimental data.
Park, Chul↗
Validation of Multitemperature Nozzle Flow Code
A computer code nozzle in n-temperatures (NOZNT), which calculates one-dimensional flows of partially dissociated and ionized air in an expanding nozzle, is tested against three existing sets of experimental data taken in arcjet wind tunnels. The code accounts for the differences among various temperatures, i.e., translational-rotational temperature, vibrational temperatures of individual molecular species, and electron-electronic temperature, and the effects of impurities. The experimental data considered are (1) the spectroscopic emission data; (2) electron beam data on vibrational temperature; and (3) mass-spectrometric species concentration data. It is shown that the impurities are inconsequential for the arcjet flows, and the NOZNT code is validated by numerically reproducing the experimental data.
Park, Chul↗
Ar-Ar Age of Shergottite Dhofar 378: Formation or Early Shock Event?
The Ar-39-Ar40 data for 16 stepwise temperature extractions of mixed mesostasis plus plagioclase show the following major characteristics. Changes in the K/Ca ratio and in the differential rate of Ar-39 release with extraction temperature suggest three distinct, but overlapping Ar diffusion domains: <13%, 13-45%, and >45% cumulative Ar-39 release:. The youngest Ar-Ar age, approx.162-165 Myr is observed at approx.28-40% Ar-39 release, which we attribute primarily to the mesostasis. Extractions releasing >45% Ar-39, probably from plagioclase, suggest older Ar-Ar ages and indicate release of trapped martian Ar-40. An isochron plot for 8 extractions, releasing 3-45% of the Ar-39 and corrected for 36Arcos using directly measured 36Arcos, gives an Ar-Ar age of 143+/-4 Myr (where the +/- ignores the uncertainty in applying a correction for Ar-36cos). Applying a correction assuming only one-half of the measured Ar-36cos gives an age of 159+/-2 Myr. Correcting for cos-Ar-36 using the minimum measured Ar-36/Ar-37 ratio gives a minimum possible age of 138+/-5 Myr. All of these ages are within combined uncertainties of the Sm-Nd age of 157+/-24 Myr [4]. The trapped Ar-40/Ar-36 ratio obtained from the isochron is largely defined by the highest [K] data.
Park, J.↗
Significant Wave Height Comparisons Between TOPEX and Platform Harvest
Two sources of H1/3 estimates were available at Platform harvest; a NOAA buoy and CU depth sensor highrate data.
H1/3 Platform Harvest TOPEX NOAA↗
Low Boom Configuration Analysis with FUN3D Adjoint Simulation Framework
Off-body pressure, forces, and moments for the Gulfstream Low Boom Model are computed with a Reynolds Averaged Navier Stokes solver coupled with the Spalart-Allmaras (SA) turbulence model. This is the first application of viscous output-based adaptation to reduce estimated discretization errors in off-body pressure for a wing body configuration. The output adaptation approach is compared to an a priori grid adaptation technique designed to resolve the signature on the centerline by stretching and aligning the grid to the freestream Mach angle. The output-based approach produced good predictions of centerline and off-centerline measurements. Eddy viscosity predicted by the SA turbulence model increased significantly with grid adaptation. Computed lift as a function of drag compares well with wind tunnel measurements for positive lift, but predicted lift, drag, and pitching moment as a function of angle of attack has significant differences from the measured data. The sensitivity of longitudinal forces and moment to grid refinement is much smaller than the differences between the computed and measured data.
Park, Michael A.↗
Late Bombardment of the Lunar Highlands Recorded in MIL 090034, MIL 090036 and MIL 090070 Lunar Meteorites
The Kaguya mission detected small but widespread outcrops of nearly pure ferroan anorthosite in and around large impact basins on the Moon. Along with certain lunar rocks, highly feldspathic lunar meteorites such as MIL 090034 (M34), 090036 (M36), and 090070 (M70) may provide samples of this material. We have measured the Ar-40/Ar-39 release patterns and cosmogenic Ar-38 concentrations of several small (<200 microg) samples separated from M34,36, and 70. From petrographic observations concluded that "some of the clasts and grains experienced generations of modifications," a conclusion that we examine in light of our data.
Park, J.↗
Ar-Ar and Rb-Sr Ages of the Tissint Olivine-phyric Martian Shergottite
The fifth martian meteorite fall, Tissint, is an olivine-phyric shergottite that contains olivine macrocrysts (approximately 1.5 mm) [1]. [2] reported the Sm-Nd age of Tissint as 596 plus or minus 23 Ma along with Rb-Sr data that defined no isochron. [3] reported Lu-Hf and Sm-Nd ages of 583 plus or minus 86 Ma and 616 plus or minus 67 Ma, respectively. The cosmic-ray exposure ages of Tissint are 1.10 plus or minus 0.15 Ma based on 10Be [4], and 1.0-1.1 Ma, based on 3He, 21Ne, and 38Ar [5,6].We report Ar-Ar ages and Rb-Sr data.
Park, J.↗
Qualitative and Quantitative Evaluation for Representative Human Reliability Analysis Methods
The Korea Institute of Nuclear Safety (KINS) is the regulatory expert organization established by the Korean government to strengthen the nation’s technical capabilities relating to nuclear safety regulation. KINS oversees the technical aspects of nuclear safety regulation, including safety reviews, inspections, education, and safety research—all conducted based on technical knowledge and accumulated regulatory experience. In 2023, KINS requested that Idaho National Laboratory (INL) validates representative human reliability analysis (HRA) methods used throughout the world, thus affording KINS with a basis for determining an HRA method adequate for its domestic regulatory purposes. The present paper mainly examines INL’s efforts in this regard. The resulting INL study covered four representative HRA methods widely used by nuclear utilities and regulatory institutes. These methods were qualitatively evaluated by applying specific evaluation criteria and determining how well each method reflected critical HRA issues. For this assessment, INL benchmarked the Halden International HRA Empirical Study. Using the Halden empirical data, along with information on human failure events (HFEs), the present study employed the selected HRA methods to estimate human error probabilities (HEPs) for the HFEs. It also performed statistical analyses to compare the HEPs predicted via the HRA methods against those from the Halden empirical data.
99 - GENERAL AND MISCELLANEOUS↗
Temperature, Humidity, and Time-Lapse Video Data from Yosemite National Park, Water Year 2024
This dataset contains time-lapse imagery and distributed measurements of air temperature, relative humidity, dew point, and soil temperature across Yosemite National Park from October 2023 to September 2024. Instruments were deployed at 10 sites in two cross-valley transects as part of the DOE Grant: Seasonal Cycles Unravel Mysteries of Missing Mountain Water organized by Jessica Lundquist (University of Washington), Rosemary Carroll (Desert Research Institute), and Ethan Gutmann (National Center for Atmospheric Research). The data are intended to support hydrologic modeling efforts to better resolve the fate of mountain water, and are published to support studies of surface climate or hydrologic processes in complex terrain. Measurements were collected with low-cost data loggers installed 2 m high on evergreen trees or buried just below the soil surface. A time-lapse camera at one site captures valley-scale seasonal snow cover variability.Dataset files are organized by site and variable (air measurements, ground measurements, or time-lapse video). Air and ground measurements are packaged in LoggerData.zip, and time-lapse imagery is compiled into a short video stored in TimelapseVideos.zip. File-level metadata contains details for each file included in the dataset. A data dictionary provides units and descriptions for column or row names in all files. The locations metadata file describes site characteristics, locations, and associated GPS methods.
54 ENVIRONMENTAL SCIENCES↗
Central Park Ecological Conservation: Assessing Tree Health Conditions in New York City’s Central Park with Earth Observation Data
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Jack Graziano↗
Proposal for a study of computer mapping of terrain using multispectral data from ERTS-A for the Yellowstone National Park test site
The author has identified the following significant results. A terrain map of Yellowstone National Park showed plant community types and other classes of ground cover in what is basically a wild land. The map comprised 12 classes, six of which were mapped with accuracies of 70 to 95%. The remaining six classes had spectral reflectances that overlapped appreciably, and hence, those were mapped less accurately. Techniques were devised for quantitatively comparing the recognition map of the park with control data acquired from ground inspection and from analysis of sidelooking radar images, a thermal IR mosaic, and IR aerial photos of several scales. Quantitative analyses were made in ten 40 sq km test areas. Comparison mechanics were performed by computer with the final results displayed on line printer output. Forested areas were mapped by computer using ERTS data for less than 1/4 the cost of the conventional forest mapping technique for topographic base maps.
Smedes, H. W.↗
Semi-Supervised Eigenbasis Novelty Detection
Recent discoveries in high-time-resolution radio astronomy data have focused attention on a new class of events. Fast transients are rare pulses of radio frequency energy lasting from microseconds to seconds that might be produced by a variety of exotic astrophysical phenomena. For example, X-ray bursts, neutron stars, and active galactic nuclei are all possible sources of short-duration, transient radio signals. It is difficult to anticipate where such signals might appear, and they are most commonly discovered through analysis of high-time- resolution data that had been collected for other purposes. Transients are often faint and difficult to detect, so improved detection algorithms can directly benefit the science yield of all such commensal monitoring. A new detection algorithm learns a low-dimensional linear manifold for describing the normal data. High reconstruction error indicates a novel signal that does not match the patterns of normal data. One unsupervised portion of the manifold model adapts its representation in response to recent data. A second supervised portion of the model is made of a basis trained in advance using labeled examples of RFI; this prevents false positives due to these events. For a linear model, an orthonormalization operation is used to combine these bases prior to the anomaly detection decision. Another novel aspect of the approach lies in combining basis vectors learned in an unsupervised, online fashion from the data stream with supervised basis vectors learned in advance from known examples of false alarms. Adaptive, data-driven detection is achieved that is also informed by existing domain knowledge about signals that may be statistically anomalous, but are not interesting and should therefore be ignored. The method was evaluated using data from the Parkes Multibeam Survey. This data set was originally collected to search for pulsars, which are astronomical sources that emit radio pulses at regular periods. However, several non-pulsar anomalies have recently been discovered in this dataset, making it a compelling test case. By explicitly filtering known false alarm patterns, the approach yields significantly better performance than current transient detection methods.
Wagstaff, Kiri L.↗
Preprocessing of multispectral data and simulation of ERTS data channels to make computer terrain maps of a Yellowstone National Park test site
The possibility of improving the accuracy of terrain classification by preprocessing spectral data was investigated. Terrain maps were made using the following techniques: 1) preprocessing by scan angle function transformation, using the computer-selected best set of three channels; and 2) preprocessing by ratio transformation, using the specified ERTS data channels, simulated by fitting the spectral response of each of the 12 data channels to the ERTS channels by a set of weighting coefficients. By using a simple technique during printout, the maps were produced in color. The normalized scan angle function transformation resulted in the most accurate classification. The best ratio transformation for the Yellowstone Park data was the ratio of each channel to the sum of all channels. A supervised training program involving maximum likelihood decision for selecting the best spectrometer channels and similar techniques for digitizing the data of the analog magnetic tapes were used. Cloud shadows were recognized in addition to eight classes of terrain. Preprocessing of data resulted in more accurate maps, required fewer training areas (hence less preparation and computer time), and enabled much of the area formerly classified as shadow to be reclassified according to actual terrain type.
Smedes, H. W.↗
Analyzing remote sensing geobotanical trends in Quetico Provincial Park, Ontario, Canada, using digital elevation data
A 10 x 13-km area in Quetico Provincial Park, Canada has been studied using a digital elevation model to separate different drainage classes and to examine the influence of site factors and lithology on vegetation. Landsat Thematic Mapper data have been classified into six forest classes of varying deciduous-coniferous cover through nPDF, a procedure based on probability density functions. It is shown that forests growing on mafic lithologies are enriched in deciduous species, compared to those growing on granites. Of the forest classes found on mafics, the highest coniferous component was on north facing slopes, and the highest deciduous component on south facing slopes. Granites showed no substantial variation between site classes. The digital elevation derived site data is considered to be an important tool in geobotanical investigations.
Warner, Timothy A.↗
Feature discrimination/identification based upon SAR return variations
A study of the statistics of The look-to-look variation statistics in the returns recorded in-flight by a digital, realtime SAR system are analyzed. The determination that the variations in the look-to-look returns from different classes do carry information content unique to the classes was illustrated by a model based on four variants derived from four look in-flight SAR data under study. The model was limited to four classes of returns: mowed grass on a athletic field, rough unmowed grass and weeds on a large vacant field, young fruit trees in a large orchard, and metal mobile homes and storage buildings in a large mobile home park. The data population in excess of 1000 returns represented over 250 individual pixels from the four classes. The multivariant discriminant model operated on the set of returns for each pixel and assigned that pixel to one of the four classes, based on the target variants and the probability distribution function of the four variants for each class.
Rasco, W. A., Sr.↗