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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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Data comparing moderately hypofractionated intensity modulated radiation therapy (IMRT) and proton beam therapy (PBT) are lacking. We aim to compare late toxicity profiles of patients with early-stage prostate cancer treated with moderately hypofractionated PBT and IMRT.
This paper presents lossless data compression and decompression algorithms which can be easily implemented in software. The algorithms can be partitioned into their fundamental parts which can be implemented at various stages within a data acquisition system. This allows for efficient integration of these functions into systems at the stage where they are most applicable. The algorithms were coded in Forth to run on a Silicon Composers Single Board Computer (SBC) using the Harris RTX2000 Forth processor. The algorithms require very few system resources and operate very fast. The performance of the algorithms with the RTX enables real time data compression and decompression to be implemented for a wide range of applications.
Blade-to-coolant heat-transfer data and operating data were obtained with a natural-convection water-cooled turbine over range of turbine speeds and inlet-gas temperatures. The convective coefficients were correlated by the general relation for natural-convection heat transfer. The turbine data were displaced from a theoretical equation for natural convection heat transfer in the turbulent region and from natural-convection data obtained with vertical cylinders and plates; possible disruption of natural convection circulation within the blade coolant passages was thus indicated. Comparison of non dimensional temperature-ratio parameters for the blade leading edge, midchord, and trailing edge indicated that the blade cooling effectiveness is greatest at the midchord and least at the trailing edge.
In this study, we test whether an existing classification technique based on the integration of Landsat ETM+ and forest inventory data enables detailed characterization of successional stages in a wet tropical forest site. The specific objectives were: (1) to map forest age classes across the La Selva Biological Station in Costa Rica; and (2) to quantify uncertainties in the proposed approach in relation to field data and existing vegetation maps. Although significant relationships between vegetation height entropy (a surrogate for forest age) and ETM+ data were detected, the classification scheme tested in this study was not suitable for characterizing spatial variation in age at La Selva, as evidenced by the error matrix and the low Kappa coefficient (12.9%). Factors affecting the performance of the classification at this particular study site include the smooth transition in vegetation structure between intermediate and advanced successional stages, and the low sensitivity of NDVI to variations in vertical structure at high biomass levels.
A perennial bottleneck in distributed workflow analytics is long access latencies for remote data. We ask the question: assuming that data must be accessed remotely, can latencies be hidden? We present TAZeR, a framework that reduces data access latency while increasing data reuse. TAZeR transparently converts POSIX I/O into operations that interleave application work with data transfer, i.e. read, prefetching, and write stage-out. TAZeR ensures read data moves directly to application memory without synchronous intervention (soft zero-copy). TAZeR uses distributed bandwidth-aware staging to exploit reuse across application tasks and to manage the capacity constraints of fast hierarchical storage. We evaluate TAZeR on a High Energy Physics workflow that requests remote data at 48 Gb/s (over two 1 Gb/s WAN links) using complex access patterns. TAZeR is 12× and 22× faster than XRootD (state-of-the-art) and file copies (current approach), respectively; and within 7% of optimal. We discuss conditions when TAZeR can hide I/O accesses; and evaluate performance as effective staging sizes change.
The ATLAS detector at the Large Hadron Collider reads out particle collision data from over 100 million electronic channels at a rate of approximately $100$ kHz, with a recording rate for physics events of approximately 1 kHz. Before being certified for physics analysis at computer centres worldwide, the data must be scrutinised to ensure they are clean from any hardware or software related issues that may compromise their integrity. Prompt identification of these issues permits fast action to investigate, correct and potentially prevent future such problems that could render the data unusable. This is achieved through the monitoring of detector-level quantities and reconstructed collision event characteristics at key stages of the data processing chain. This paper presents the monitoring and assessment procedures in place at ATLAS during 2015-2018 data-taking. Through the continuous improvement of operational procedures, ATLAS achieved a high data quality efficiency, with 95.6% of the recorded proton-proton collision data collected at $\sqrt{s}=13$ TeV certified for physics analysis.
Oxidation of metals can provide a functional oxide film or an oxide layer that can lead to material degradation causing performance limiting concerns. Because of the technological and economic impacts of oxidation, understanding early-stage oxidation growth and its mechanisms is of high importance. Unfortunately, poor empirical data during early-stage oxidation has left our current understanding of oxidation incomplete and woefully inadequate. Measurement techniques previously used for oxidation kinetics characterization include microbalance, x-ray diffraction, Fourier-transform infrared spectroscopy, and spectroscopic ellipsometry. However, these techniques lack the necessary time-resolution or vertical resolution in addition to not providing any spatial data, which is essential to early-stage oxidation studies to understand both oxidation kinetics and mechanisms. Here, a novel rapid and surface-sensitive data collection technique that provides three-dimensional spatial data of a growing oxide layer with sub-nanometer thickness resolution using white-light interferometry has been developed. This technique will be the first technique capable of providing real-time spatial results of early-stage oxidation growth. The effectiveness of this characterization tool is shown by observing the early-stage oxidation kinetics and film cracking of uranium heated to 90 °C under 500 torr of pure O 2 . Initially a parabolic oxidation growth is observed. Once the oxide layer reaches ≈ 30 nm, the epitaxial stresses between the uranium substrate and oxide film layer causes localized cracking in addition to the observed transition of the parabolic growth rate to a linear growth rate. The results of the white-light interferometry are verified by glancing incidence x-ray diffraction.
Although used in the design and costing of large projects such as linear colliders and fusion tokamaks, the theory of vacuum arcs and gradient limits is not well understood. Almost 120 years after the isolation of vacuum arcs, the exact mechanisms of the arcs and the damage they produce are still being debated. We describe our simple and general model of the vacuum arc that can incorporate all active mechanisms and aims to explain all relevant data. Our four stage model, is based on experiments done at 805 MHz with a variety of cavity geometries, magnetic fields, and experimental techniques as well as data from Atom Probe Tomography and failure analysis of microelectronics. The model considers the trigger, plasma formation, plasma evolution and surface damage phases of the RF arc. This paper also examines how known mechanisms can explain the observed sharp field dependence, fast breakdown times and observed surface damage. We update the model and discuss new features while also pointing out where new data would be useful in extending the model to a wider range of frequencies.
The author has identified the following significant results. Color-combined ERTS-1 MSS spectral slices were analyzed to determine the maximum (repeatable) level of meaningful forest resource classification data visually attainable by skilled forest photointerpreters for the following purposes: (1) periodic updating of the Minnesota Land Management Information System (MLMIS) statewide computerized land use data bank, and (2) to provide first-stage forest resources survey data for large area forest land management planning. Controlled tests were made of two forest classification schemes by experienced professional foresters with special photointerpretation training and experience. The test results indicate it is possible to discriminate the MLMIS forest class from the MLMIS nonforest classes, but that it is not possible, under average circumstances, to further stratify the forest classification into species components with any degree of reliability with ERTS-1 imagery. An ongoing test of the resulting classification scheme involves the interpretation, and mapping, of the south half of Itasca County, Minnesota, with ERTS-1 imagery. This map is undergoing field checking by on the ground field cooperators, whose evaluation will be completed in the fall of 1973.
Techniques developed from aircraft flights over the Washita watershed in central Oklahoma were applied to HCMM data analysis. Results show that (1) canopy temperatures were accurately measured remotely; (2) pasture surface temperature differences detected relative soil moisture differences; (3) pasture surface temperature differences were related to stress in nearby wheat fields; and (4) no relationship was developed between final yield differences, thermal infrared data, and soil moisture stress at critical growth stages due to a lack of satellite thermal data at critical growth stages. The HCMM thermal data proved to be quite adequate in detecting relative moisture differences; however, with a 16 day day/night overpass frequency, more frequent overpasses are required to analyze more cases within a 7 day period after the storm. Better normalization techniques are also required.
Mesoscale weather conditions can have an adverse effect on space launch, landing, ground processing, and weather advisories, watches, and warnings at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally-driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. These convective processes often last 60 minutes or less and pose a significant challenge to the local forecasters. Surface winds during the transition seasons (spring and fall) pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned local data assimilation (DA) and forecast model at a high resolution is needed to provide improved capability. To accomplish this, a number of sensitivity tests were performed using the Weather Research and Forecasting (WRF) model in order to determine the best DA/model configuration for operational use at each of the space launch ranges to best predict winds, precipitation, and temperature. A set of Perl scripts to run the Gridpoint Statistical Interpolation (GSI)/WRF in real-time were provided by NASA's Short-term Prediction Research and Transition Center (SPoRT). The GSI can analyze many types of observational data including satellite, radar, and conventional data. The GSI/WRF scripts use a cycled GSI system similar to the operational North American Mesoscale (NAM) model. The scripts run a 12-hour pre-cycle in which data are assimilated from 12 hours prior up to the model initialization time. A number of different model configurations were tested for both the ER and WFF by varying the horizontal resolution on which the data assimilation was done. Three different grid configurations were run for the ER and two configurations were run for WFF for archive cases from 27 Aug 2013 through 10 Nov 2013. To quantify model performance, standard model output will be compared to the Meteorological Assimilation Data Ingest System (MADIS) data. The MADIS observation data will be compared to the WRF forecasts using the Model Evaluation Tools (MET) verification package. In addition, the National Centers for Environmental Prediction's Stage IV precipitation data will be used to validate the WRF precipitation forecasts. The author will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for each space launch range.
The first Clouds and the Earth's Radiant Energy System (CERES) instrument will be launched in 1997 to collect data on the Earth's radiation budget. The data retrieved from the satellite will be processed through twelve subsystems. The Single Satellite Footprint (SSF) plot generator software was written to assist scientists in the early stages of CERES data analysis, producing two-dimensional plots of the footprint radiation and cloud data generated by one of the subsystems. Until the satellite is launched, however, software developers need verification tools to check their code. This plot generator will aid programmers by geolocating algorithm result on a global map.
An experimental investigation was performed in the NASA/Ames Research Center 3.5-foot Hypersonic Wind Tunnel to obtain supersonic heat-distribution data in areas between the orbiter and external tank using phase-change paint techniques. The tests used Novamide SSV Model 56-OTS in the first and second-stage ascent configurations. Data were obtained at a nominal Mach number of 5.3 and a Reynolds number per foot of 5 x 10 to the 6th power with angles of attack of 0 deg, +/- 5 deg, and sideslip angles of 0 deg and +/- 5 deg.
We describe an ongoing series of virtual experiments conducted collaboratively by four United States National Laboratories: Sandia National Laboratories, Los Alamos National Laboratory, Lawrence Livermore National Laboratory, and Pacific Northwest National Laboratory. These Dynamic Network Experiments (DNEs) provide an experimental framework to evaluate the potential impact of new research tools on nuclear explosion monitoring. The second DNE (DNE2), completed in 2024, exploited waveform data (seismic, infrasound, and electromagnetic) that was recorded by multi-modal sensors within and near the Nevada National Security Site and synthetic radionuclide signatures over multiple time periods. During the execution of DNE2, we processed and analyzed data through a multi-stage event processing pipeline that ingested raw data, performed quality control, detected signals, built events from these signals, located these events, and characterized the events’ source types and sizes. For each stage and over the entire event processing pipeline, we evaluated performance changes by comparing the performance of new data processing methods, models, and algorithms against a baseline. We also performed an additional execution phase to assess event processing pipeline function, speed, and efficiency against that of an expert analyst, including computational and manual efforts. Finally, we assessed the impact and effort of modern computing infrastructure on the monitoring pipeline. This paper describes key elements of the DNEs, from formulation through execution, as demonstrated in DNE2. The DNEs introduce several novel concepts to quantitatively measure the potential impact of new methods on explosion monitoring, including the collaborative design of multi-modal datasets, performance and logistical metrics, and integrated analyses.
An orbital transfer vehicle OTV engine study program was undertaken to provide additional expander and staged combustion cycle data in the design definition of the OTV engine. The proposed program effort optimizes the expander cycle engine concept (consistent with identified OTV engine requirements), investigates the feasibility of kitting the staged combustion cycle engine to provide extended low thrust operation, and conducts in-depth analysis of development risk, crew safety, and reliability for both cycles. Additional tasks to establish the cost of a 10K thrust expander cycle engine and to render support of OTV systems study contractors are reported.
This report provides a technical overview of how to go from raw to curated data in three stages using a lakehouse approach. We focus on the application of open source tools in scientific use cases (while noting parallels to enterprise and commercial alternatives). Our goal is to provide scientific data managers and infrastructure providers with a common frame of reference for understanding and applying modern lakehouse technologies and approaches.
The current Phase A-Extension of the OTV engine study program seeks to provide additional expander and staged combustion cycle data that will lead to design definition of the OTV engine. The proposed program effort will optimize the expander cycle engine concept (consistent with identified OTV engine requirements), investigate the feasibility of kitting the stage combustion cycle engine to provide extended low thrust operation, and conduct in-depth analysis of development risk, crew safety, and reliability for both cycles. Additional task will address costing of a 10k thrust expander cycle engine and support of OTV systems study contractors.
The current Phase A-Extension of the OTV engine study program aims to provide additional expander and staged combustion cycle data that will lead to design definition of the OTV engine. The proposed program effort seeks to optimize the expander cycle engine concept (consistent with identified OTV engine requirements), investigate the feasibility of kitting the staged combustion cycle engine to provide extended thrust operation, and conduct in-depth analysis of development risk, crew safety, and reliability for both cycles. Additional tasks address the costing of a 10/K thrust expander cycle engine and support of OTV systems study contractors.