Search NASA⌕ Search

SEARCH · Search NASA

Results for “data generation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

Molecular Spectroscopy in Astrophysics: Interstellar PAHs

Polycyclic aromatic hydrocarbons (PAHs) are now considered to be an important and ubiquitous component of the organic material in space. PAHs are found in a large variety of extraterrestrial materials such as interplanetary dust particles (IDPs) and meteoritic materials. PAHs are also good candidates to account for the infrared emission bands (UIRs) and the diffuse interstellar optical absorption bands (DIBs) detected in various regions of the interstellar medium. The recent observations made with the Infrared Space Observatory (ISO) have confirmed the ubiquitous nature of the UIR bands and their carriers. PAHs are thought to form through chemical reactions in the outflow from carbon-rich stars in a process similar to soot formation. Once injected in the interstellar medium, PAHs are further processed by the interstellar radiation field, interstellar shocks and energetic particles. A long-term laboratory effort has been undertaken to measure the physical and chemical characteristics of these carbon molecules and their ions under experimental conditions that mimic the interstellar conditions. These measurements require collision-free conditions where the molecules and ions are cold and chemically isolated. The spectroscopy of PAHs under controlled conditions represents an essential diagnostic tool to study the evolution of extraterrestrial PAHs. The laboratory results will be discussed as well as the implications for astronomy and for molecular spectroscopy. A review of the data generated through laboratory simulations of space environments and the role these data have played in our current understanding of the properties of interstellar PAHs will be presented. We will also present the new generation of laboratory experiments that are currently being developed in order to provide a closer simulation of space environments and a better support to space missions.

Salama, Farid↗
NASA NTRS1975

Satellite system considerations for computer data transfer

Communications satellites will play a key role in the transmission of computer generated data through nationwide networks. This paper examines critical aspects of satellite system design as they relate to the computer data transfer task. In addition, it discusses the factors influencing the choice of error control technique, modulation scheme, multiple-access mode, and satellite beam configuration based on an evaluation of system requirements for a broad range of application areas including telemetry, terminal dialog, and bulk data transmission.

Cook, W. L.↗
NASA NTRS2000

Laboratory Astrochemistry: Interstellar PAHs

Polycyclic aromatic hydrocarbons (PAHs) are now considered to be an important and ubiquitous component of the organic material in space. PAHs are found in a large variety of extraterrestrial materials such as interplanetary dust particles (IDPs) and meteoritic materials. PAHs are also good candidates to account for the infrared emission bands (UIRs) and the diffuse interstellar optical absorption bands (DIBs) detected in various regions of the interstellar medium. The recent observations made with the Infrared Space Observatory (ISO) have confirmed the ubiquitous nature of the UIR bands and their carriers. PAHs are thought to form through chemical reactions in the outflow from carbon-rich stars in a process similar to soot formation. Once injected in the interstellar medium, PAHs are further processed by the interstellar radiation field, interstellar shocks and energetic particles. A major, dedicated, laboratory effort has been undertaken to measure the physical and chemical characteristics of these complex molecules and their ions under experimental conditions that mimic the interstellar conditions. These measurements require collision-free conditions where the molecules and ions are cold and chemically isolated. The spectroscopy of PAHs under controlled conditions represents an essential diagnostic tool to study the evolution of extraterrestrial PAHs. The Astrochemistry Laboratory program will be discussed through its multiple aspects: (1) objectives, (2) approach and techniques adopted, (3) adaptability to the nature of the problem(s), and (4) results and implications for astronomy as well as for molecular spectroscopy. A review of the data generated through laboratory simulations of space environments and the role these data have played in our current understanding of the properties of interstellar PAHs will be presented. The discussion will also introduce the newest generation of laboratory experiments that are currently being developed in order to provide a closer simulation of space environments and a better support to space missions.

Salama, Farid↗
NASA NTRS2000

Laboratory Astrochemistry: Interstellar PAH Analogs

Polycyclic aromatic hydrocarbons (PAHs) are now considered to be an important and ubiquitous component of the organic material in space. PAHs are found in a large variety of extraterrestrial materials such as interplanetary dust particles (IDPs) and meteoritic materials. PAHs are also good candidates to account for the infrared emission bands (UIRs) and the diffuse interstellar optical absorption bands (DIBs) detected in various regions of the interstellar medium. The recent observations made with the Infrared Space Observatory (ISO) have confirmed the ubiquitous nature of the UIR bands and their carriers. PAHs are though to form through chemical reactions in the outflow from carbon-rich stars in a process similar to soot formation. Once injected in the interstellar medium, PAHs are further processed by the interstellar radiation field, interstellar shocks and energetic particles. A major, dedicated, laboratory effort has been undertaken over the past years to measure the physical and chemical characteristics of these complex molecules and their ions under experimental conditions that mimic the interstellar conditions. These measurements require collision-free conditions where the molecules and ions are cold and chemically isolated. The spectroscopy of PAHs under controlled conditions represents an essential diagnostic tool to study the evolution of extraterrestrial PAHs. The Astrochemistry Laboratory program will be discussed through its multiple aspects: objectives, approach and techniques adopted, adaptability to the nature of the problem(s), results and implications for astronomy as well as for molecular spectroscopy. A review of the data generated through laboratory simulations of space environments and the role these data have played in our current understanding of the properties of interstellar PAHs will be presented. The discussion will also introduce the newest generation of laboratory experiments that are currently being developed in order to provide a closer simulation of space environments and a better support to space missions.

Salama, Farid↗
NASA NTRS2000

Laboratory Studies of Interstellar PAH Analogs

Polycyclic aromatic hydrocarbons (PAHs) are now considered to be an important and ubiquitous component of the organic material in space. PAHs are found in a large variety of extraterrestrial materials such as interplanetary dust particles (IDPs) and meteoritic materials. PAHs are also good candidates to account for the infrared emission bands (UIRs) and the diffuse interstellar optical absorption bands (DIBs) detected in various regions of the interstellar medium. The recent observations made with the Infrared Space Observatory (ISO) have confirmed the ubiquitous nature of the UIR bands and their carriers. PAHs are though to form through chemical reactions in the outflow from carbon-rich stars in a process similar to soot formation. Once injected in the interstellar medium, PAHs are further processed by the interstellar radiation field, interstellar shocks and energetic particles. A major, dedicated, laboratory effort has been undertaken over the past years to measure the physical and chemical characteristics of these complex molecules and their ions under experimental conditions that mimic the interstellar conditions. These measurements require collision-free conditions where the molecules and ions are cold and chemically isolated. The spectroscopy of PAHs under controlled conditions represents an essential diagnostic tool to study the evolution of extraterrestrial PAHs. The Astrochemistry Laboratory program will be discussed through its multiple aspects: objectives, approach and techniques adopted, adaptability to the nature of the problem(s), results and implications for astronomy as well as for molecular spectroscopy. A review of the data generated through laboratory simulations of space environments and the role these data have played in our current understanding of the properties of interstellar PAHs will be presented. The discussion will also introduce the newest generation of laboratory experiments that are currently being developed in order to provide a closer simulation of space environments and a better support to space missions.

Salama, Farid↗
NASA NTRS1998

Development and Testing of Automatically Generated ACS Flight Software for the MAP Spacecraft

By integrating the attitude determination and control system (ACS) analysis and design, flight software development, and flight software testing processes, it is possible to improve the overall spacecraft development cycle, as well as allow for more thorough software testing. One of the ways to achieve this integration is to use code-generation tools to automatically generate components of the ACS flight software directly from a high-fidelity (HiFi) simulation. In the development of the Microwave Anisotropy Probe (MAP) spacecraft, currently underway at the NASA Goddard Space Flight Center, approximately 1/3 of the ACS flight software was automatically generated. In this paper, we will examine each phase of the ACS subsystem and flight software design life cycle: analysis, design, and testing. In the analysis phase, we scoped how much software we would automatically generate and created the initial interface. The design phase included parallel development of the HiFi simulation and the hand-coded flight software components. Everything came together in the test phase, in which the flight software was tested, using results from the HiFi simulation as one of the bases of comparison for testing. Because parts of the spacecraft HiFi simulation were converted into flight software, more care needed to be put into its development and configuration control to support both the HiFi simulation and flight software. The components of the HiFi simulation from which code was generated needed to be designed based on the fact that they would become flight software. This process involved such considerations as protecting against mathematical exceptions, using acceptable module and parameter naming conventions, and using an input/output interface compatible with the rest of the flight software. Maintaining good configuration control was an issue for the HiFi simulation and the flight software, and a way to track the two systems was devised. Finally, an integrated test approach was devised to support flight software testing at both the unit- and build-test levels using the HiFi simulation to generate data for performance verification. Another benefit of the simulation and code-generation application used on the MAP project is that it supported bringing flight software and test data into the HiFi simulation environment. It was possible to integrate parts of the hand-coded flight software into the HiFi simulation, and also possible to import flight software test data for comparison and performance verification. This capability was used to incorporate the flight software Kalman filter into the HiFi simulation. This enabled us to greatly increase the amount of testing that could be done on the filter, because we could exert a greater degree of control over the software-only simulation than over the flight software test environment. Also, since the simulation could be used to run the Kalman filter faster than real time, our testing efficiency was greatly increased. We will conclude our discussion with a summary of the lessons learned thus far using automatically- generated code for the MAP project, and the spacecraft status as we work towards our scheduled launch in the year 2000.

ODonnell, James R., Jr.↗
NASA NTRS2012

Generating Ground Reference Data for a Global Impervious Surface Survey

We are engaged in a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. The GLS data from Landsat provide an unprecedented opportunity to map global urbanization at this resolution for the first time, with unprecedented detail and accuracy. Moreover, the spatial resolution of Landsat is absolutely essential to accurately resolve urban targets such as buildings, roads and parking lots. Finally, with GLS data available for the 1975, 1990, 2000, and 2005 time periods, and soon for the 2010 period, the land cover/use changes due to urbanization can now be quantified at this spatial scale as well. Our approach works across spatial scales using very high spatial resolution commercial satellite data to both produce and evaluate continental scale products at the 30m spatial resolution of Landsat data. We are developing continental scale training data at 1m or so resolution and aggregating these to 30m for training a regression tree algorithm. Because the quality of the input training data are critical, we have developed an interactive software tool, called HSegLearn, to facilitate the photo-interpretation of high resolution imagery data, such as Quickbird or Ikonos data, into an impervious versus non-impervious map. Previous work has shown that photo-interpretation of high resolution data at 1 meter resolution will generate an accurate 30m resolution ground reference when coarsened to that resolution. Since this process can be very time consuming when using standard clustering classification algorithms, we are looking at image segmentation as a potential avenue to not only improve the training process but also provide a semi-automated approach for generating the ground reference data. HSegLearn takes as its input a hierarchical set of image segmentations produced by the HSeg image segmentation program [1, 2]. HSegLearn lets an analyst specify pixel locations as being either positive or negative examples, and displays a classification of the study area based on these examples. For our study, the positive examples are examples of impervious surfaces and negative examples are examples of non-impervious surfaces. HSegLearn searches the hierarchical segmentation from HSeg for the coarsest level of segmentation at which selected positive example locations do not conflict with negative example locations and labels the image accordingly. The negative example regions are always defined at the finest level of segmentation detail. The resulting classification map can be then further edited at a region object level using the previously developed HSegViewer tool [3]. After providing an overview of the HSeg image segmentation program, we provide a detailed description of the HSegLearn software tool. We then give examples of using HSegLearn to generate ground reference data and conclude with comments on the effectiveness of the HSegLearn tool.

Tilton, James C.↗
DOE OSTI2025

HPDR: High-Performance Portable Scientific Data Reduction Framework

The rapid growth in scientific data generation is outpacing advancements in computing systems necessary for efficient storage, transfer, and analysis, particularly in the context of exascale computing. With the deployment of first-generation exascale computing systems and next-generation experimental facilities, this gap is widening and necessitates effective data reduction techniques to manage enormous data volumes. Over the past decade, various data reduction methods, including lossless compression, error-controlled lossy compression, and data refactoring, have been developed to accelerate I/O in scientific workflows. Despite significant reductions in data volume, these methods introduce considerable computational overhead, which can become the new bottleneck in data processing. To mitigate this, GPU-accelerated data reduction algorithms have been introduced. However, challenges remain in their integration into exascale workflows, including limited portability across different GPU architectures, substantial memory transfer overhead, and reduced scalability on dense multi-GPU systems. To address these challenges, we propose HPDR, a high-performance and portable data reduction framework. HPDR is designed to enable the execution of state-of-the-art reduction algorithms across diverse processor architectures while reducing memory transfer overhead to 2.3 % of the original, resulting in up to 3.5× faster throughput compared to existing solutions. It also achieves up to 96% of the theoretical speedup in multi-GPU settings. In addition, evaluations on accelerating I/O operations at scale up to 1,024 nodes of the Frontier supercomputer demonstrate that HPDR can achieve up to 103 TB/s reduction throughput, providing up to 4× acceleration in parallel I/O performance compared to existing data reduction routines. This work highlights the potential of HPDR to significantly enhance data reduction efficiency in exascale computing environments.

Chen, Jieyang [University of Oregon]↗
DOE OSTI2026

Collaborative Research: Enabling multi-scale studies of magnetic reconnection with interpretable data-driven models

The development of accurate reduced descriptions and improved closures for magnetic reconnection is an important and a long‐standing challenge in plasma physics. The four‐fluid approach, and associated closures, that were investigated have the potential to improve the accuracy of plasma fluid models, capturing physical effects which would otherwise require a kinetic description. If successful, this approach could have an important impact for the modeling of laboratory and space plasmas. The major goals of this project were to develop new machine learning (ML) tools based on sparse and symbolic regression techniques, and to extract interpretable and generalizable reduced models (e.g., in the form of partial differential equations - PDEs) from data generated by first principles plasma simulations. Preserving interpretability of such data‐driven models is key to addressing the long‐standing theoretical and numerical challenges. Prior proof‐of‐principle studies have demonstrated the enormous potential of this approach, by recovering the well‐established hierarchy of plasma equations (from Vlasov to MHD) from data produced by particle‐in‐cell (PIC) simulations. Our goal in this project was to extend and apply these new tools to construct better kinetic closures for magnetic reconnection; to derive better models of particle injection and acceleration by this fundamental plasma process; and to use this understanding to accelerate the development of multi‐scale plasma algorithms. While our immediate focus was on the problem of magnetic reconnection, the tools that were will developed are general and applicable to other areas of plasma physics, and more broadly to many‐body phenomena. We anticipate that the development of these multi‐scale models will have a significant impact across different areas of plasma science, from fusion to space and astrophysical plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1978

Development of an improved method of consolidating fatigue life data

A fatigue data consolidation model that incorporates recent advances in life prediction methodology was developed. A combined analytic and experimental study of fatigue of notched 2024-T3 aluminum alloy under constant amplitude loading was carried out. Because few systematic and complete data sets for 2024-T3 were available in the program generated data for fatigue crack initiation and separation failure for both zero and nonzero mean stresses. Consolidations of these data are presented.

Leis, B. N.↗
NASA NTRS1982

LANDSAT-D assessment system library computer compatible tape (LASLIB-CCT/LAS-CCT)

The format for computer compatible tapes containing thematic mapper archival data and product data generated by the LANDSAT-D Assessment System (LAS). These data tapes are engineering products developed primarily for LAS internal use to assist in the early evaluation of thematic mapper data quality and ground data processing algorithms during the limited period of one year following the launch of LANDSAT-D.

Source record↗
NASA NTRS1984

TM digital image products for applications

The image characteristics of digital data generated by LANDSAT 4 thematic mapper (TM) are discussed. Digital data from the TM resides in tape files at various stages of image processing. Within each image data file, the image lines are blocked by a factor of either 5 for a computer compatible tape CCT-BT, or 4 for a CCT-AT and CCT-PT; in each format, the image file has a different format. Nominal geometric corrections which provide proper geodetic relationships between different parts of the image are available only for the CCT-PT. It is concluded that detector 3 of band 5 on the TM does not respond; this channel of data needs replacement. The empty bin phenomenon in CCT-AT images results from integer truncations of mixed-mode arithmetric operations.

Barker, J. L.↗
NASA NTRS2016

Ontologies for Aviation Data Management

Managing complex aviation data can be a significant challenge for any enterprise – whether a government agency, airline, airframe manufacturer, or aviation service provider. To handle this challenge, data models are typically developed to characterize and manage the data generated, used, and stored by a given enterprise. Unfortunately, different data providers employ qualitatively different data models, and this gives rise to problems exchanging data across organizational boundaries. Over the past decade, these problems have motivated data producers and consumers to look toward standardized data exchange models to address data interoperability. In this paper we examine some of these standardized data exchange models and compare them with a new type of data model based on ontologies. Ontology models have emerged in recent years from a confluence of research in the artificial intelligence, semantic web, and information science communities. This paper introduces ontology models, provides several use cases for ontologies relevant to aviation data management, and summarizes state of the art aviation prototype applications that utilize ontologies.

artificial intelligence↗
NASA NTRS2022

Unique NISTAR-Based Climate GCM Diagnostics of the Earth’s Planetary Albedo and Spectral Absorption Through Longitudinal Data Slicing

Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation permit a unique model/data comparison perspective that is not readily available from other satellite data. The key factor is the unique Lissajous orbital viewing geometry from the Lagrangian L1 point, which enables a continuous view of Earth’s sunlit hemisphere. The National Institute of Standards and Technology Advanced Radiometer (NISTAR) is the DSCOVR Mission energy budget instrument, which views the reflected and emitted radiation of the Earth’s sunlit hemisphere by means of single pixel active cavity full-spectrum (Band-A, 0.2–100 μm) and filtered solar wavelength (Band-B, 0.2–4.0 μm; and Band-C, 0.7–4.0 μm) radiometer measurements. An additional solar wavelength photodiode channel (0.3–1.1 μm) provides a calibration reference. The objective of this study is the assessment of climate GCM performance via direct model/data comparisons. Such comparisons are difficult due to quasi-chaotic natural variability present in real-world observational data and in climate GCM simulations. This is where the unique DSCOVR viewing geometry makes possible the longitudinal data slicing methodology for more direct model/data comparison. The key point of the longitudinal slicing approach is that data integration over the entire sunlit hemisphere eliminates the quasi-chaotic meteorological weather-scale noise, while preserving intra-seasonal and planetary-scale variability. The rotation of the Earth that retrieves this climate-style, large-scale longitudinal and seasonal variability. The hemispheric averaging is accomplished automatically in NISTAR measurements with its single-pixel view of the Earth. For climate GCMs, this requires implementing the Sunlit Hemisphere Sampling (SHS) scheme to operate on the GCM run-time output data, utilizing the DSCOVR Satellite Ephemeris data to assure precise viewing geometry between NISTAR measurements and GCM output data, while averaging out the meteorological weather noise. However, GCM generated data are radiative fluxes, while NISTAR (and EPIC) measurements are near-backscattered radiances. Conversing NISTSR measurements into radiative fluxes cannot be accomplished using NISTAR data alone, even with detailed support from conventional satellite data. But the identical viewing geometry of Earth’s sunlit hemisphere, and synergistic analyses of EPIC data make it feasible for this conversion of NISTAR near-backscatter radiances into radiative fluxes.

deep space climate observatory↗
DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗
NASA NTRSDate not supplied

More than RBE: Exploring Two Decades of Space Radiation Quality and Carcinogenesis Research and How NASA Manages Cancer Risk

NASA’s Space Radiation Element (SRE), both as a stand-alone entity and as part of the Human Research Program, has invested heavily into investigating how the different qualities of radiation and low dose rates relevant to the space environment and how these factors effect long term carcinogenesis risk. NASA’s current model to assess astronaut excess cancer risk due to radiation exposure utilizes data generated from both in vitro and in vivo models to inform quality factor and dose-rate functions that scales risk estimates originally established from human cohorts exposed to terrestrial radiation, most notably the Lifespan Study of atomic bomb survivors (LSS). As part of an effort to update these quality function, the SRE hosted a workshop in on radiation quality in September 2021 and a workshop on dose-rate at NASA HRP’s Investigators’ Workshop in February 2022 where current and former grantees presented data that could potentially be incorporated into assessing carcinogenic risk. This presentation is intended to both inform the broader research community of the outcome of those workshops and generate a discussion as to what biological data should be generated to better inform NASA’s risk estimates. Additionally, NASA’s current risk disposition for cancer assessment will be discussed and clarified. We look forward to hearing feedback from the Radiation Research Society community!

Brock J Sishc↗
NASA NTRS1996

Study of Critical Heat Flux and Two-Phase Pressure Drop Under Reduced Gravity

The design of the two-phase flow systems which are anticipated to be utilized in future spacecraft thermal management systems requires a knowledge of two-phase flow and heat transfer phenomena in reduced gravities. This program was funded by NASA headquarters in response to NRA-91-OSSA-17 and was managed by Lewis Research Center. The main objective of this program was to design and construct a two-phase test loop, and perform a series of normal gravity and aircraft trajectory experiments to study the effect of gravity on the Critical Heat Flux (CHF) and onset of instability. The test loop was packaged on two aircraft racks and was also instrumented to generate data for two-phase pressure drop. The normal gravity tests were performed with vertical up and downflow configurations to bound the effect of gravity on the test parameters. One set of aircraft trajectory tests was performed aboard the NASA DC-9 aircraft. These tests were mainly intended to evaluate the test loop and its operational performance under actual reduced gravity conditions, and to produce preliminary data for the test parameters. The test results were used to demonstrate the applicability of the normal gravity models for prediction of the two-phase friction pressure drop. It was shown that the two-phase friction multipliers for vertical upflow and reduced gravity conditions can be successfully predicted by the appropriate normal gravity models. Limited critical heat flux data showed that the measured CHF under reduced gravities are of the same order of magnitude as the test results with vertical upflow configuration. A simplified correlation was only successful in predicting the measured CHF for low flow rates. Instability tests with vertical upflow showed that flow becomes unstable and critical heat flux occurs at smaller powers when a parallel flow path exists. However, downflow tests and a single reduced gravity instability experiment indicated that the system actually became more stable with a parallel single-phase flow path. Several design modifications have been identified which will improve the system performance for generating reduced gravity data. The modified test loop can provide two-phase flow data for a range of operating conditions and can serve as a test bed for component evaluation.

Abdollahian, Davood↗
NASA NTRS2012

Big Data Challenges for Large Radio Arrays

Future large radio astronomy arrays, particularly the Square Kilometre Array (SKA), will be able to generate data at rates far higher than can be analyzed or stored affordably with current practices. This is, by definition, a "big data" problem, and requires an end-to-end solution if future radio arrays are to reach their full scientific potential. Similar data processing, transport, storage, and management challenges face next-generation facilities in many other fields.

Combining↗