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At least 1,567 records · Page 87

An Empirical Study on the Use of the Rancor Microworld Simulator to Support Full-scope Data Collection

A lack of data has been identified as a major challenge in human reliability analysis (HRA). Accordingly, several institutes and researchers have tried to collect HRA data from different data sources such as actual historical measurements, expert judgements, or simulator studies. While the most recent studies predominantly focus on collecting data using full-scope simulators with actual operators, Idaho National Laboratory (INL) has begun to collect HRA data using a simplified simulator, i.e., the Rancor Microworld simulator, with student participants. Full-scope studies have been known to have several intrinsic challenges to securing enough quantity of the data due to many reasons like the high cost for performing experiments or requiring actual operators’ cooperation. The ultimate goal of INL’s effort aims to infer actual operators’ data collected from a full-scope simulator on the basis of microworld data with student subjects as well as collect additional data that could be missed in the full-scope research. As a first step to achieve this goal, this paper projects an experimental plan for investigating the differences in human performance between individuals in two groups: 1) an actual operator and 2) a student when using the Rancor Microworld simulator. A randomized factorial experiment design has been developed with two independent variables, i.e., type of scenario and type of subject. Six human performance measures, i.e., 1) time, 2) error, 3) workload, 4) situation awareness, 5) patterns of attention and 6) the number of manipulations were selected. A couple of scenarios and their procedures available to the Rancor Microworld simulator have been developed.

99 GENERAL AND MISCELLANEOUS↗

Laser light scattering review

Since the development of laser light sources and fast digital electronics for signal processing, the classical discipline of light scattering on liquid systems experienced a strong revival plus an enormous expansion, mainly due to new dynamic light scattering techniques. While a large number of liquid systems can be investigated, ranging from pure liquids to multicomponent microemulsions, this review is largely restricted to applications on Brownian particles, typically in the submicron range. Static light scattering, the careful recording of the angular dependence of scattered light, is a valuable tool for the analysis of particle size and shape, or of their spatial ordering due to mutual interactions. Dynamic techniques, most notably photon correlation spectroscopy, give direct access to particle motion. This may be Brownian motion, which allows the determination of particle size, or some collective motion, e.g., electrophoresis, which yields particle mobility data. Suitable optical systems as well as the necessary data processing schemes are presented in some detail. Special attention is devoted to topics of current interest, like correlation over very large lag time ranges or multiple scattering.

Schaetzel, Klaus↗

Monthly mean global satellite data sets available in CCM history tape format

Satellite data for climate monitoring have become increasingly important over the past decade, especially with increasing concern for inadvertent antropogenic climate change. Although most satellite based data are of short record, satellites can provide the global coverage that traditional meteorological observations network lack. In addition, satellite data are invaluable for the validation of climate models, and they are useful for many diagnostic studies. Herein, several satellite data sets were processed and transposed into 'history tape' format for use with the Community Climate Model (CCM) modular processor. Only a few of the most widely used and best documented data sets were selected at this point, although future work will expand the number of data sets examined as well as update the archived data sets. An attempt was made to include data of longer record and only monthly averaged data were processed. For studies using satellite data over an extended period, it is important to recognize the impact of changes in instrumentation, drift in instrument calibration, errors introduced by retrieval algorithms and other sources of errors such as those resulting from insufficient space and/or time sampling.

Hurrell, James W.↗

Infrared Thermography Flight Experimentation

Analysis was done on IR data collected by DFRC on May 8, 2002. This includes the generation of a movie to initially examine the IR flight data. The production of the movie was challenged by the volume of data that needed to be processed, namely 40,500 images with each image (256 x 252) containing over 264 million points (pixel depth 4096). It was also observed during the initial analysis that the RTD surface coating has a different emissivity than the surroundings. This fact added unexpected complexity in obtaining a correlation between RTD data and IR data. A scheme was devised to generate IR data near the RTD location which is not affected by the surface coating This scheme is valid as long as the surface temperature as measured does not change too much over a few pixel distances from the RTD location. After obtaining IR data near the RTD location, it is possible to make a direct comparison with the temperature as measured during the flight after adjusting for the camera s auto scaling. The IR data seems to correlate well to the flight temperature data at three of the four RID locations. The maximum count intensity occurs closely to the maximum temperature as measured during flight. At one location (RTD #3), there is poor correlation and this must be investigated before any further progress is possible. However, with successful comparisons at three locations, it seems there is great potential to be able to find a calibration curve for the data. Moreover, as such it will be possible to measure temperature directly from the IR data in the near future.

Blanchard, Robert C.↗

A Decohesive Constitutive Formulation for Modeling Failure of Sea Ice

One of the dominant characteristics of Arctic ice as reflected by RADARSAT Geophysical Processor System data is the development and persistence of leads. Experimental data from small specimens as well as in situ data from Arctic ice suggest that failure may occur under compression. Presented here is a decohesive constitutive model for which one of the distinguishing new features is that failure is predicted under uniaxial compression. More generally, the model specifically indicates when a lead is initiated, provides the orientation of the lead, gives the mode of failure, and allows one to numerically determine the width of leads. In addition, the approach allows multiple failure planes, a feature that is necessary to simulate crack branching. Pre-existing planes of weakness such as those formed from previous leads can be incorporated. Sample calculations indicate how such a model can be used for large-scale numerical simulations.

Schreyer, H. L.↗

History and Status of ALSEP and the Apollo Lunar Data Project

A suite of automated scientific instruments (the Apollo Lunar Surface Experiment Package, or ALSEP) was installed at each of the landing sites of Apollo 12, 14, 15, 16, and 17 from 1969 to 1972. They operated from deployment until decommissioning on 30 September 1977. These data were continuously transmitted to Earth and saved on the Range Tapes, which were recorded at the Manned Space Flight Network stations. These data were also broken out by experiment and sent to the experiment Principal Investigators on what were called the P.I. Tapes. Starting in April 1973 the Range Tape data were stored in digital format on 7-track magnetic tapes, the ARCSAV Tapes. In February 1976, the handling of the Range Tapes was transferred to UT Galveston. They produced 9-track tapes referred to as the Work Tapes. Following the Apollo program the Range and ARCSAV tapes, which were never archived, were lost. The Work Tapes were archived at the National Space Science Data Center (NSSDC). Some investigators archived their individual experiment data with NSSDC as well, but much of the data had minimal documentation, were not in digital form, or were stored in difficult to translate formats. Data from many experiments were never delivered to the NSSDC. The Lunar Data Project was started to address the problem of both missing and not readily usable data. Our effort has resulted in recovery of some of the ARCSAV tapes, recovery and digitization of a large volume of Apollo scientific and technical documentation, and restoration of many ALSEP and other Apollo data collections. Restoration involves deciphering formats, assembling necessary ancillary data (metadata), and packaging data in digital format to be archived with the Planetary Data System (PDS). Recovery of the data from the ARCSAV tapes involved having the tapes read on special equipment and extracting the individual experiment data out of the integrated data stream. We will report on the history and status of the various recovery efforts.

Work Tapes↗

The Environmental Data Application for Analysis of Space Telemetry Data

Sensors on the International Space Station (ISS) and multiple spacecraft elsewhere in Earth orbit and in deep space continuously monitor and collect environmental data, transmitting this information back to Earth. These data include ionizing radiation and, on the ISS and spacecrafts, CO2, relative humidity levels, and temperature, and are of great importance to space biology research. Looking ahead to future long duration crewed missions beyond low Earth orbit, the ability to study how factors including CO2 levels, light cycle, temperature modulate the response to ionizing radiation and microgravity is essential. To date, access to these data has been fragmented across space agencies, spacecraft, and databases. To address this issue, NASA’s Open Science Data Repository (OSDR) has developed a user interface for interrogation of telemetry data: the Environmental Data Application (EDA). The EDA provides the capability to visualize telemetry and radiation data collected on the International Space Station and corresponding ground platforms during the Rodent Research missions. Telemetry data includes temperature, relative humidity, and CO2 levels. Radiation data includes galactic cosmic rays, the contribution of the South Atlantic Anomaly, total radiation dose rate, and accumulated radiation dose. The application allows users to view single missions, compare multiple missions, and view and download summary or full data tables. In summary, the EDA provides GUIs for data visualization and exploration, as well as means for data export, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

telemetry↗

Utah FORGE: Well 16A(78)-32 Perforation Images and Raw Data

This archive contains raw data of visual and acoustic mapping of perforations in Utah FORGE well 16A(78)-32 acquired during the August 2024 circulation program. The dataset includes downhole images captured by EV, a downhole visual analytics company, providing visual records of each perforation. Images are organized in two folders: one set with perforation visualization overlays and one without. An included Excel spreadsheet provides the organized raw data.

15 GEOTHERMAL ENERGY↗

ET-AL: Entropy-targeted active learning for bias mitigation in materials data

Growing materials data and data-driven informatics drastically promote the discovery and design of materials. While there are significant advancements in data-driven models, the quality of data resources is less studied despite its huge impact on model performance. In this work, we focus on data bias arising from uneven coverage of materials families in existing knowledge. Observing different diversities among crystal systems in common materials databases, we propose an information entropy-based metric for measuring this bias. To mitigate the bias, we develop an entropy-targeted active learning (ET-AL) framework, which guides the acquisition of new data to improve the diversity of underrepresented crystal systems. We demonstrate the capability of ET-AL for bias mitigation and the resulting improvement in downstream machine learning models. This approach is broadly applicable to data-driven materials discovery, including autonomous data acquisition and dataset trimming to reduce bias, as well as data-driven informatics in other scientific domains.

36 MATERIALS SCIENCE↗

Data for “Tree root nutrient uptake kinetics vary with nutrient availability, environmental conditions, and root traits: A global analysis”

This data package contains data and code used in the paper “Tree root nutrient uptake kinetics vary with nutrient availability, environmental conditions, and root traits: A global analysis”. The central product is a global dataset of root inorganic nutrient uptake rates and kinetics parameters covering temperate, boreal, and sub/tropical tree species, representing a collection of nutrient uptake data from published studies. This dataset enables tree investigation of root nutrient uptake rates across species, space, and experimental conditions. The data can also be combined with supplementary data on root and soil traits or with external datasets (e.g. R scripts contained within use data from FRED 3.0; (Iversen et al., 2021)). Contained within is the main nutrient data “uptake_data.csv” as well as 4 additional .csv files that link uptake data to supplementary measurements, source references, taxonomic information, and additional nutrient uptake measurements across nutrient gradients, and 1 .csv file that records meta-analysis results for plotting with the R scripts. There are seven R scripts that support data analysis and creation of the figures in the related publication.

54 ENVIRONMENTAL SCIENCES↗

2024 Buildings Technology Baseline: Dataset Documentation

The Buildings Technology Baseline is a curated and regularly updated dataset of current and projected performance, retail, and installed price data for all major building energy technologies needed to enable cost/benefit analyses. Building technology analyses require an up-to-date understanding of installation costs and cost-effectiveness of key building energy efficiency technologies. The dataset was assembled by Guidehouse during fiscal year 2024. Data was gathered from the 2024 National Residential Efficiency Measures Database (NREMDB), the 2023 Energy Information Administration Updated Buildings Sector Appliance and Equipment Costs and Efficiencies ("EIA Building Data Report"), DOE Lighting Market Model, the 2023 RSMeans database, and the 2020 Grid-Interactive Efficient Building Technology Cost, Performance, and Lifetime Characteristics ("GEB Data Report"), Lawrence Berkeley National Laboratory, various literature, as well as new data from online retailers, stakeholder interviews, and contractor databases in 2023 and 2024. The dataset has been reviewed by subject matter experts at NREL and DOE. The 2024 dataset release is intended to be a starting point for interested users to provide feedback. This database is not intended to provide specific cost estimates for a specific project. The cost estimates do not include any rebates or tax incentives that may be available for the measures. Rather, it is meant to help determine which measures may be more cost-effective. The National Renewable Energy Laboratory (NREL) makes every effort to ensure accuracy of the data; however, NREL does not assume any legal liability or responsibility for the accuracy or completeness of the information.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Hyperspectral Infrared Observations of Arctic Snow, Sea Ice, and Non-Frozen Ocean from the RV Polarstern during the MOSAiC Expedition October 2019 to September 2020

This study highlights hyperspectral infrared observations from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) collected as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) deployment on the icebreaker RV Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The ARM M-AERI directly measures the infrared radiance emission spectrum between 520 cm –1 and 3000 cm –1 (19.2–3.3 μm) at 0.5 cm –1 spectral resolution. These ship-based observations provide a valuable set of radiance data for the modeling of snow/ice infrared emission as well as validation data for the assessment of satellite soundings. Remote sensing using hyperspectral infrared observations provides valuable information on sea surface properties (skin temperature and infrared emissivity), near-surface air temperature, and temperature lapse rate in the lowest kilometer. Comparison of the M-AERI observations with those from the DOE ARM meteorological tower and downlooking infrared thermometer are generally in good agreement with some notable differences. Operational satellite soundings from the NOAA-20 satellite were also assessed using ARM radiosondes launched from the RV Polarstern and measurements of the infrared snow surface emission from the M-AERI showing reasonable agreement.

54 ENVIRONMENTAL SCIENCES↗

An inference engine for embedded diagnostic systems

The implementation of an inference engine for embedded diagnostic systems is described. The system consists of two distinct parts. The first is an off-line compiler which accepts a propositional logical statement of the relationship between facts and conclusions and produces data structures required by the on-line inference engine. The second part consists of the inference engine and interface routines which accept assertions of fact and return the conclusions which necessarily follow. Given a set of assertions, it will generate exactly the conclusions which logically follow. At the same time, it will detect any inconsistencies which may propagate from an inconsistent set of assertions or a poorly formulated set of rules. The memory requirements are fixed and the worst case execution times are bounded at compile time. The data structures and inference algorithms are very simple and well understood. The data structures and algorithms are described in detail. The system has been implemented on Lisp, Pascal, and Modula-2.

Fox, Barry R.↗

Sensor fusion of range and reflectance data for outdoor scene analysis

In recognizing objects in an outdoor scene, range and reflectance (or color) data provide complementary information. Results of experiments in recognizing outdoor scenes containing roads, trees, and cars are presented. The recognition program uses range and reflectance data obtained by a scanning laser range finder, as well as color data from a color TV camera. After segmentation of each image into primitive regions, models of objects are matched using various properties.

Kweon, In SO↗

Analysis of notched metal matrix composites under tensile loading

This paper presents techniques based on a three-dimensional finite-element analysis for the analysis of continuous fiber reinforced metal matrix composite. Examples are shown for specific metal matrix composites such as boron/aluminum and silicon-carbide/aluminum. Specimen stress-strain behavior and stress at first fiber failure were predicted for boron/aluminum laminates containing circular holes and crack-like slits. The predictions compared very well with test data for laminates containing 0 deg fibers and reasonably well for (+/-45)2s laminates. Mesh configuration was shown to have an effect on the calculation of stresses local to the notch. The presence of thin interface layers of matrix material had a significant influence on the slit tip stress state, causing sharper stress gradients near the notch. Interface layers reduced the slit-tip fibers stress in a (+/-45)2s silicon-carbide/aluminum laminate but increased them in a (0/90)2s laminate.

Bigelow, C. A.↗

Thermal protection materials: Thermophysical property data

This publication presents a thermophysical property survey on materials that could potentially be used for future spacecraft thermal protection systems (TPS). This includes data that was reported in the 1960's as well as more current information reported through the 1980's. An attempt was made to cite the manufacturers as well as the data source in the bibliography. This volume represents an attempt to provide in a single source a complete set of thermophysical data on a large variety of materials used in spacecraft TPS analysis. The property data is divided into two categories: ablative and reusable. The ablative materials have been compiled into twelve categories that are descriptive of the material composition. An attempt was made to define the Arrhenius equation for each material although this data may not be available for some materials. In a similar manner, char data may not be available for some of the ablative materials. The reusable materials have been divided into three basic categories: thermal protection materials (such as insulators), adhesives, and structural materials.

Williams, S. D.↗

Hyperspectral Imaging and Related Field Methods: Building the Science

The proposal requested funds for the computing power to bring hyperspectral image processing into undergraduate and graduate remote sensing courses. This upgrade made it possible to handle more students in these oversubscribed courses and to enhance CSES' summer short course entitled "Hyperspectral Imaging and Data Analysis" provided for government, industry, university and military. Funds were also requested to build field measurement capabilities through the purchase of spectroradiometers, canopy radiation sensors and a differential GPS system. These instruments provided systematic and complete sets of field data for the analysis of hyperspectral data with the appropriate radiometric and wavelength calibration as well as atmospheric data needed for application of radiative transfer models. The proposed field equipment made it possible to team-teach a new field methods course, unique in the country, that took advantage of the expertise of the investigators rostered in three different departments, Geology, Geography and Biology.

Goetz, Alexander F. H.↗

What You Need to Know About the OMI NO2 Data Product for Air Quality Studies

The standard nitrogen dioxide (NO2) data product, produced from measurements by the Ozone Monitoring Instrument (OMI), are publicly available online from the NASA GESDISC facility. Important data fields include total and tropospheric column densities, as well as collocated data for cloud fraction and cloud top height, surface albedo and snow/ice coverage, at the resolution of the OMI instrument (12 km x 26 km, at nadir). The retrieved NO2 data have been validated, principally under clear-sky conditions. The first public-release version has been available since September 2006. An improved version of the data product, which includes a number of new data fields, and improved estimates of the retrieval uncertainties will be released by the end of 2007. This talk will describe the standard NO2 data product, including details that are essential for the use of the data for air quality studies. We will also describe the principal improvements with the new version of the data product.

Celarier, E. A.↗