Report of Apollo 13 Review Board. Baseline Data - Apollo 13 Flight Systems and Operations, Appendix a
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The evolution of quantitative models of the trapped radiation belts is traced to show how the knowledge of the various features has developed, or been clarified, by performing the required analysis and synthesis. The Starfish electron injection introduced problems in the time behavior of the inner zone, but this residue decayed away, and a good model of this depletion now exists. The outer zone electrons were handled statistically by a log normal distribution such that above 5 Earth radii there are no long term changes over the solar cycle. The transition region between the two zones presents the most difficulty, therefore the behavior of individual substorms as well as long term changes must be studied. The latest corrections to the electron environment based on new data are outlined. The proton models have evolved to the point where the solar cycle effect at low altitudes is included. Trends for new models are discussed; the feasibility of predicting substorm injections and solar wind high-speed streams make the modeling of individual events a topical activity.
The role of various infrared techniques in measurements of trace gases in the stratosphere were surveyed. Particular emphasis was placed on the role of instruments exhibiting ultrahigh resolution (i.e., less than or equal to 0.00/cm) such as laser heterodyne spectrometers.
Condensation effects are responsible for the minimum operating temperatures of cryogenic wind tunnels at total pressures up to about 9 atmospheres. The two primary modes of condensation homogeneous nucleation and heterogeneous nucleation and the conditions with which either may limit minimum operating temperatures are reveiwed. Previous hypersonic and supersonic condensation data are reviewed as are data taken in the nitrogen gas, Langley 0.3 Meter Transonic Cryogenic Tunnel. Analysis of data in the 0.3 m tunnel suggests that the onset of homogenous nucleation may be approximated by an analysis by sivier and that the onset of heterogeneous nucleation is only apparent just below free stream saturation. Extension of the results from the 0.3 m tunnel to other nitrogen gas cryogenic tunnels is discussed and is shown to depend on length scales, purity of the liquid nitrogen injected for cooling, number of particulates in the flow, and the extent to which the injected liquid nitrogen is evaporated.
Data is presented on the phase and frequency stability, over time periods extending to one week, of the new NR field operable hydrogen masers developed by the Applied Physics Laboratory (APL) and the older NX and NP field operable hydrogen masers developed by Goddard Space Flight Center and maintained and upgraded by Bendix Field Engineering Corporation (BFEC). Data is presented on the NR masers in the laboratory showing frequency stabilities well into the 10 to the -15th power range and phase stabilities well into the 100 ps range for periods of up to one day. Data is presented on upgraded NP masers in the laboratory showing that the frequency stability has been improved substantially to virtually the NR level. VLBI data is presented on the phase difference between NX-2 at Owens Valley, California and NR-2 at Fort Davis, Texas for a one week period showing, after removal of a constant frequency drift, a 350 ps RMS phase stability.
A geocoded data structure is a means for digitally representing a geographically referenced map or image. The characteristics of representative cellular, linked, and hybrid geocoded data structures are reviewed. The data processing requirements of Earth science projects at the Goddard Space Flight Center and the basic tools of geographic data processing are described. Specific ways that new geocoded data structures can be used to adapt these tools to scientists' needs are presented. These include: expanding analysis and modeling capabilities; simplifying the merging of data sets from diverse sources; and saving computer storage space.
The main objective in systems engineering is to devise a coherent total system design capable of achieving the stated requirements. Requirements should be rigid. However, they should be continuously challenged, rechallenged and/or validated. The systems engineer must specify every requirement in order to design, document, implement and conduct the mission. Each and every requirement must be logically considered, traceable and evaluated through various analysis and trade studies in a total systems design. Margins must be determined to be realistic as well as adequate. The systems engineer must also continuously close the loop and verify system performance against the requirements. The fundamental role of the systems engineer, however, is to engineer, not manage. Yet, in large, complex missions, where more than one systems engineer is required, someone needs to manage the systems engineers, and we call them 'systems managers.' Systems engineering management is an overview function which plans, guides, monitors and controls the technical execution of a project as implemented by the systems engineers. As the project moves on through Phases A and B into Phase C/D, the systems engineering tasks become a small portion of the total effort. The systems management role increases since discipline subsystem engineers are conducting analyses and reviewing test data for final review and acceptance by the systems managers.
LDEF greatly extended the range of data available for metals exposed to the low-Earth-orbital environment. The effects of low-Earth-orbital exposure on metals include meteoroid and debris impacts, solar ultraviolet radiation, thermal cycling, cosmic rays, solar particles, and surface oxidation and contamination. This paper is limited to changes in surface composition and texture caused by oxidation and contamination. Surface property changes afford a means to study the environments (oxidation and contamination) as well as in-space stability of metal surfaces. We compare thermal-optical properties for bare aluminum and anodized aluminum clamps flown on LDEF. We also show that the silicon observed on the LDEF tray clamps and tray clamp bolt heads is not necessarily evidence of silicon contamination of LDEF from the shuttle. The paper concludes with a listing of LDEF reports that have been published thus far that contain significant findings concerning metals.
Vostok Subglacial Lake is the largest and best known sub-ice lake in Antarctica. The establishment of its water depth (>500 m) led to an appreciation that such environments may be habitats for life and could contain ancient records of ice sheet change, which catalyzed plans for exploration and research. Here we discuss geophysical data used to identify the lake and the likely physical, chemical, and biological processes that occur in it. The lake is more than 250 km long and around 80 km wide in one place. It lies beneath 4.2 to 3.7 km of ice and exists because background levels of geothermal heating are sufficient to warm the ice base to the pressure melting value. Seismic and gravity measurements show the lake has two distinct basins. The Vostok ice core extracted >200 m of ice accreted from the lake to the ice sheet base. Analysis of this ice has given valuable insights into the lake s biological and chemical setting. The inclination of the ice-water interface leads to differential basal melting in the north versus freezing in the south, which excites circulation and potential mixing of the water. The exact nature of circulation depends on hydrochemical properties, which are not known at this stage. The age of the subglacial lake is likely to be as old as the ice sheet (approx.14 Ma). The age of the water within the lake will be related to the age of the ice melting into it and the level of mixing. Rough estimates put that combined age as approx.1 Ma.
In this CIF project, we worked toward semi-automating knowledge discovery from anomaly detection algorithms through the use of active learning. Active learning is an area of research within machine learning that uses an "expert in the loop" to learn from large data sets that have very few annotations or labels available, and where providing such labels is expensive. In our case, the task can be defined as the identification of safety events from flight operational data. Since traditional anomaly detection algorithms cannot differentiate between operationally relevant and irrelevant statistical anomalies, Subject Matter Experts (SMEs) have a lengthy and expensive burden of investigating every example identified by the detection algorithm, classifying and labeling them as relevant or irrelevant. Active learningidentifies the unlabeled example for which a label would most improve the classifier, asks the domain expert for a label, and repeats this process until there are no more resources (time, budget) available for labeling or a minimum required performance is reached. A positive label indicates an operationally significant safety event whereas a negative label indicates otherwise. Based on these few labels we propose to build an active learning system that utilizes the SME's time in the most effective manner by iteratively asking for labels for as few informative instances as possible. Our work was proposed to be a stepping stone toward implementation and deployment of the system with user interface to be pursued by the Aviation Operations and Safety Program (AOSP) given its interest in safety monitoring and discovery of safety incidents.
Available experimental data dealing with critical heat flux (CHF) of liquid hydrogen (LH 2 ), liquid methane (LCH 4 ), and liquid oxygen (LO 2 ) in pool and flow boiling are compiled. The compiled data are compared with widely used correlations. Experimental pool boiling CHF data for the aforementioned cryogens are scarce. Based on only 25 data points found in five independent sources, the correlation of Sun and Lienhard (1970) is recommended for predicting the pool CHF of LH 2 . Only two experiments with useful CHF data for the pool boiling of LCH 4 could be found. Four different correlations including the correlation of Lurie and Noyes (1964) can predict the pool boiling CHF of LCH 4 within a factor of two for more than 70% of the data. Furthermore, based on the 19 data points taken from only two available sources, the correlation of Sun and Lienhard (1970) is recommended for the prediction of pool CHF of LO 2 . Flow boiling CHF data for LH 2 could be found in seven experimental studies, five of them from the same source. Based on the 91 data points, it is suggested that the correlation of Katto and Ohno (1984) be used to predict the flow CHF of LH 2 . No useful data could be found for flow boiling CHF of LCH 4 or LO 2 . The available databases for flow boiling of LCH 4 and LO 2 are generally deficient in all boiling regimes. This deficiency is particularly serious with respect to flow boiling.
Available experimental data dealing with critical heat flux (CHF) of liquid hydrogen (LH2), liquid methane (LCH4), and liquid oxygen (LO2) in pool and flow boiling are compiled. The compiled data are compared with widely used correlations. Experimental pool boiling CHF data for the aforementioned cryogens are scarce. Based on only 25 data points found in five independent sources, the correlation of Sun and Lienhard (1970) is recommended for predicting the pool CHF of LH2. Only two experiments with useful CHF data for the pool boiling of LCH4 could be found. Four different correlations including the correlation of Lurie and Noyes (1964) can predict the pool boiling CHF of LCH4 within a factor of two for more than 70% of the data. Furthermore, based on the 19 data points taken from only two available sources, the correlation of Sun and Lienhard (1970) is recommended for the prediction of pool CHF of LO2. Flow boiling CHF data for LH2 could be found in seven experimental studies, five of them from the same source. Based on the 91 data points, it is suggested that the correlation of Katto and Ohno (1984) be used to predict the flow CHF of LH2. No useful data could be found for flow boiling CHF of LCH4 or LO2. The available databases for flow boiling of LCH4 and LO2 are generally deficient in all boiling regimes. This deficiency is particularly serious with respect to flow boiling.
Understanding and tuning the performance of extreme-scale parallel computing systems demands a streaming approach due to the computational cost of applying offline algorithms to vast amounts of performance log data. Analyzing large streaming data is challenging because the rate of receiving data and limited time to comprehend data make it difficult for the analysts to sufficiently examine the data without missing important changes or patterns. To support streaming data analysis, we introduce a visual analytic framework comprising of three modules: data management, analysis, and interactive visualization. The data management module collects various computing and communication performance metrics from the monitored system using streaming data processing techniques and feeds the data to the other two modules. The analysis module automatically identifies important changes and patterns at the required latency. In particular, we introduce a set of online and progressive analysis methods for not only controlling the computational costs but also helping analysts better follow the critical aspects of the analysis results. Finally, the interactive visualization module provides the analysts with a coherent view of the changes and patterns in the continuously captured performance data. Through a multi-faceted case study on performance analysis of parallel discrete-event simulation, we demonstrate the effectiveness of our framework for identifying bottlenecks and locating outliers.
NASA Ames' Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade.In the last two years, we have participated in SUBSEA, a multi-institution collaborative project. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC). In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule.The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team's ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA's Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island's Graduate School of Oceanography (GSO). ISC is GSO's telepresence operations facility.
NASA Ames’ Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade. In the last two years, we have participated in SUBSEA, a multi-institution collaborative project*. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC)**. In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule. The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team’s ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. * SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA’s Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island’s Graduate School of Oceanography (GSO).
Los Alamos National Laboratory (LANL) operates four mesa-top meteorology towers: Technical Area (TA) 06, TA-49, TA-53, and TA-54. An additional tower is located in Mortandad Canyon (TA-5 MDCN), and a rain gauge at North Community (NCOM). A description of the meteorology monitoring network is found in Dewart and Boggs (2014). Mesa-top towers are instrumented at 1.2 meters (m), 11.5 m, 23 m, and 46 m. In addition, TA-06 is instrumented at 92 m. The TA-5 MDCN tower is 10 m in height and is instrumented at 1.2 m and 10 m. Data are collected every 15 minutes. Range checking is done on each measurement every 15 minutes; data that are beyond normal ranges are eliminated from the data set and replaced by a code for missing data. In addition, data are reviewed weekly by meteorologists to identify bad data not identified by range checking. The data steward eliminates these data from the data set and replaces them with a code for missing data. The instrument technicians also review that data and schedule instrument replacement as required. Data completeness is determined by the number of total 15-minute records available versus the total number of possible measurements for the entire year. As a rule, the meteorologists do not attempt to estimate data that are eliminated as bad data. Original datalogger records, containing bad data, can be recalled from program archival storage.
NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Non-random processes impacting organic matter chemistry are maximized in mid-order streams” submitted to Limnology and Oceanography (L&O) by Danczak et al. (in review). This package contains data and scripts used to investigate dissolved organic matter (DOM) molecular chemistry and diversification processes across 47 surface-water sampling sites in the Yakima River Basin, Washington, USA, during an August 2021 sampling campaign. The package contains analyses of ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), geochemical measurements, geospatial attributes, molecular diversity, and meta-metabolome ecological null models needed to reproduce the main manuscript results. The underlying field data were pulled from exising data packages at https://doi.org/10.15485/1892052 (Fulton et al., 2022) and https://doi.org/10.15485/1898914 (Grieger et al., 2022). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. We thank the following organizations for providing access to field locations for sample collection: the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, the Confederated Tribes and Bands of the Yakama Nation, and the Cowiche Canyon Conservatory. Research was conducted under Washington State Parks and Recreation Commission Scientific Research Permit #210901. We are grateful to the Yakama Nation Tribal Council and Yakama Nation Fisheries for their collaboration in facilitating sample collection and ensuring data usage aligns with their values and worldview. This data package contains an R-Markdown file for analyses and five folders: (1) Data, (2) Geospatial Data, (3) Supplemental_Files, (5) Figures_pdf, (4) and src. The Data folder contains tabular inputs and derived files used in the manuscript analysis. The Geospatial Data folder contains climate and water-balance, hydrologic, land-cover, population/regional water-use, stream, topographic, and stream-order attribute CSV files. The src folder contains scripts used to process data, run analyses, and generate figures. The Figures_pdf folder contains manuscript figure outputs. The Supplemental_Files folder contains supplemental analysis products. All files are .csv, .pdf, .html, .png, .R, .Rmd, .svg, or .tre. This data package is associated with the rcfsa-RC2-SPS_Null_Modeling repository found at https://github.com/river-corridors-sfa/rcfsa-RC2-SPS_Null_Modeling.
A careful review of the data from Skylab M558 was made in an effort to explain the apparent anomaly of the existence of radial concentration gradients whereas none should bave been observed. The very close modelling of the experimental axial concentration profiles by the unsteady-state one-dimensional solution of Fick's Law of self-diffusion in liquid zinc, and the condition of initial uniform concentration in the radioactive pellet portion of the experimental specimens would have precluded the appearance of such radial concentration gradients. Statistical analyses were used to test the significance of the observed deviation from radial-concentration homogeneity. A student t-distribution test of significance showed that, at 90% or even at 80% level of significance, there were no significant deviations from uniformity in radial concentrations. It was also concluded that the two likely causes of any deviation that existed were the zinc to zinc-65 bonding procedure and surface phenomena such as surface tension and capillary action.