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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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The visible/infrared spin scan radiometer (VISSR) atmospheric sounder (VAS) rawinsonde field program is discussed. Specific items covered include: planning, personnel requirements and training, operational requirement and procedures, sounding times and dates, methods of data processing, data inventory, and status of data processing.
The present study is concerned with the mathematical modelling of aircraft dynamics on the basis of an investigation conducted with the aid of the Rotor System Research Aircraft (RSRA). The particular characteristics of RSRA make it possible to investigate aircraft properties which cannot be readily studied elsewhere, for example in the wind tunnel. The considered experiment had mainly the objective to develop an improved understanding of the physics of rotor flapping dynamics and rotor loads in maneuvers. The employed approach is based on a utilization of parameter identification methodology (PID) with application to helicopters. A better understanding of the contribution of the main rotor to the overall aircraft forces and moments is also to be obtained. Attention is given to the mathematical model of a rotorcraft system, an integrated identification method, flight data processing, and the identification of RSRA mathematical models.
Science experiments are routinely conducted on the NASA shuttle orbiter vehicles. Primarily, these experiments are operated on such missions to take advantage of the microgravity (low-level acceleration) environment conditions during on-orbit operations. Supporting accelerometer instruments are operated with the experiments to measure the microgravity acceleration environment in which the science experiments were operated. Tne Principal Investigator Microgravity Services (PIMS) Project at NASA Lewis Research Center interprets these microgravity acceleration data and prepares mission summary reports to aid the principal investigators of the scientific experiments in understanding the microgravity environment. Much of the information about the orbiter vehicle and the microgravity environment remains the same for each mission. Rather than repeat that information in each mission summary report, reference information is presented in this report to assist users in understanding the microgravity-acceleration data. The characteristics of the microgravity acceleration environment are first presented. The methods of measurement and common instruments used on orbiter missions are described. The coordinate systems utilized in the orbiter and accelerometers are described. Some of the orbiter attitudes utilized in microgravity related missions are illustrated. Methods of data processing are described and illustrated. The interpretation of the microgravity acceleration data is included with an explanation of common disturbance sources. Instructions to access some of the acceleration data and a description of the orbiter thrusters are explained in the appendixes. A microgravity environment bibliography is also included.
Forecasters at the US Air Force 45th Weather Squadron (45 WS) use wind and temperature data from the tower network over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to evaluate Launch Commit Criteria and to issue and verify temperature and wind advisories, watches, and warnings for ground operations. The Spaceflight Meteorology Group at the Johnson Space Center in Houston, TX also uses these data when issuing forecasts for shuttle landings at the KSC Shuttle Landing Facility. Systematic biases in these parameters at any of the towers could adversely affect an analysis, forecast, or verification for all of these operations. In addition, substantial geographical variations in temperature and wind speed can occur under specific wind directions. Therefore, the Applied Meteorology Unit (AMU), operated by ENSCO Inc., was tasked to develop a monthly and hourly climatology of temperatures and winds from the tower network, and identify the geographical variation, tower biases, and the magnitude of those biases. This paper presents a sub-set of results from a nine-year climatology of the KSC/CCAFS tower network, highlighting the geographical variations based on location, month, times of day, and specific wind direction regime. Section 2 provides a description of the tower mesonetwork and instrumentation characteristics. Section 3 presents the methodology used to construct the tower climatology including QC methods and data processing. The results of the tower climatology are presented in Section 4 and Section 5 summarizes the paper.
The long observational record is critical to our understanding of the Earths climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and to summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide an climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.
NASA's Office of Independent Program and Cost Evaluation (IPCE) has established a number of initiatives to improve its cost and schedule estimating capabilities. 12One of these initiatives has resulted in the JPL developed NASA Instrument Cost Model. NICM is a cost and schedule estimator that contains: A system level cost estimation tool; a subsystem level cost estimation tool; a database of cost and technical parameters of over 140 previously flown remote sensing and in-situ instruments; a schedule estimator; a set of rules to estimate cost and schedule by life cycle phases (B/C/D); and a novel tool for developing joint probability distributions for cost and schedule risk (Joint Confidence Level (JCL)). This paper describes the development and use of NICM, including the data normalization processes, data mining methods (cluster analysis, principal components analysis, regression analysis and bootstrap cross validation), the estimating equations themselves and a demonstration of the NICM tool suite.
Industrial data analytics methods play a central role in improving energy storage performance and efficiency, impacting the future of electrified transportation and renewable electricity generation. However, significant challenges hinder the large-scale deployment of batteries. Conventional methods rely on centralized collection and processing of fleet-level data, leading to database size issues and privacy concerns due to potential data breaches. To enable scalable deployment of battery management systems, this article proposes a federated battery diagnosis and prognosis model, which distributes the processing of battery standard current-voltage-time-usage data in a privacy-preserving manner. Instead of transferring the raw data, this approach communicates only the locally processed parameters, thus reducing communication load and preserving data confidentiality. The federated model offers a paradigm shift in battery health management through privacy-preserving distributed methods for battery data processing and lifetime prediction, ensuring the reliable and sustainable deployment of lithium-ion batteries in a rapidly evolving world.
Ways to access the IUE data base and methods for processing and analyzing the IUE data are discussed. The characteristics of the data base are described and the types of objects observed by the IUE are listed. The methods for searching the IUE catalogs and conducting multicatalog searches are considered. In addition, trends in the application of astronomical data bases are examined, including the prospects for future software packages for data processing and analysis.
The relationship existing between Guanabara Bay water quality ground truth parameters and LANDSAT MSS video data was investigated. The parameters considered were: chorophyll content, water transparency usng the Secchi disk, salinity, and dissolved ammonia. Data from two overflights was used, and methods of processing digital data were compared. Linear and nonlinear regression analyses were utilized, comparing original data with processed data by using the correlation coefficient and the estimation mean error. It was determined that better quality data are obtained by using radiometric correction programs with a physical basis, contrast ratio, and normalization. Incidental locations of floating vegetation, changes in bottom depth, oil slicks, and ships at anchor were made.
It has been demonstrated that image processing techniques can provide an effective means of simulating flight over remotely sensed data (Hussey et al. 1986). This paper explains the methods used to simulate and animate three-dimensional surfaces from two-dimensional imagery. The preprocessing techniques used on the input data, the selection of the animation sequence, the generation of the animation frames, and the recording of the animation is covered. The software used for all steps is discussed.
Cross section generation and data processing techniques for nuclear rocket shielding methods, modification, updating, and input data preparation - Vol. 3
One of the biggest challenges in developing scientific instruments is not just the build and testing of an instrument, but the method for processing the data and producing a consistent, well characterized data product that can be confidently used by the public and scientific community. Raw data products are frequently an array of numbers that are a read-out of voltages. The challenge is to convert these arrays into meaningful information as well as remove noise and interferences. Because this can be a tedious and time-consuming, the goal is to automate the process so that data ca be processed rapidly and be available in real-time for event monitoring. Here we present a rapid analysis method for Laser Heterodyne Radiometer (LHR) data that can be used to analyze data taken from a range of LHR observation modes (column, limb, etc.). This online tool uses the versatile Planetary Spectrum Generator (PSG) and allows LHR users to quickly analyze their own data using a NASA Goddard Space Flight Center (GSFC) monitored capability to ensure quality and reproducibility in the data products. Background: Development of a miniaturized LHR (mini-LHR) as a ground instrument for measuring carbon dioxide (CO 2 ) and methane (CH 4 ) in the atmospheric column started in 2009 with the commercial availability of distributive feedback lasers (DFB) in wavelengths that could measure absorption of gases in the near-IR. As new DFB lasers, detectors and hardware emerged at different wavelengths, additional gases were added to the capability. The mini-LHR was adapted into an occultation-viewing CubeSat with Lawrence Livermore National Laboratory (LLNL) for observing CO 2 , CH 4 , and H 2 O in the limb and was launched in 2019. Other versions of the LHR technology have been designed for observation of water vapor in the lunar exosphere as well as observations of trace gases in planetary atmospheres and plumes from icy moons. The PSG is an online tool developed at GSFC that can be used for synthesizing Earth and planetary spectra (atmospheres and surfaces) over a broad range of wavelengths (0.1 μm to 100 mm) for any observatory, orbiter or lander. Spectra are simulated by combining several state-of-the-art radiative transfer models, spectroscopic databases, planetary databases, as well as modern-era retrospective analysis for research and applications, version 2 (MERRA-2) data set which provides meteorological inputs such as modeled surface pressure for calculating dry-air columns.
Methods developed for measuring blade and rotor-shaft system response include optical systems, transient instruments, and special digital data processing equipment. Optical methods offer some distinct benefits for blade vibration measurement. Transient and steady state measurements of the response of rotor-shaft systems strongly affect analytical methods development. Digital computing systems allow processing of large volumes of high speed data from rotating blade sets. Also, digital systems develop useful vibration response signatures from randomly excited systems. Research facilities include the spin rig facility and the transient rotor response lab.
The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed.
The heat capacity mapping mission (HCMM), a low cost modular spacecraft built for the Applications Explorer Missions (AEM), was designed to allow scientists to determine the feasibility of using day/night thermal infrared remote sensor-derived data to: (1) discriminate various rock types and locate mineral resources; (2) measure and monitor surface soil moisture changes; (3) measure plant canopy temperatures at frequent intervals to determine transpiration of water and plant stress; and (4) measure urban heat islands. The design of the spacecraft (AEM-A), its payload, launch vehicle, orbit, and data collection and processing methods are described. Projects in which the HCMM data will be applied by 12 American and 12 foreign investigators are summarized.
The NASA GeneLab project (genelab.nasa.gov) seeks to get the most from space-relevant biology experiments by providing and maintaining a public database consisting of DNA, RNA, protein, and metabolite data from spaceflight experiments. Since these types of data, referred to as omics data, are difficult to understand for non-bioinformaticians, the GeneLab data processing team works with the scientific community to develop methods to process these data. The processed data found on GeneLab reveals information about which genes are turned on and turned off in the space environment, which helps us understand how space changes our biology and how we can best mitigate these effects to travel deeper into space.
The Aeroelastic Prediction Workshop brought together an international community of computational fluid dynamicists as a step in defining the state of the art in computational aeroelasticity. This workshop's technical focus was prediction of unsteady pressure distributions resulting from forced motion, benchmarking the results first using unforced system data. The most challenging aspects of the physics were identified as capturing oscillatory shock behavior, dynamic shock-induced separated flow and tunnel wall boundary layer influences. The majority of the participants used unsteady Reynolds-averaged Navier Stokes codes. These codes were exercised at transonic Mach numbers for three configurations and comparisons were made with existing experimental data. Substantial variations were observed among the computational solutions as well as differences relative to the experimental data. Contributing issues to these differences include wall effects and wall modeling, non-standardized convergence criteria, inclusion of static aeroelastic deflection, methodology for oscillatory solutions, post-processing methods. Contributing issues pertaining principally to the experimental data sets include the position of the model relative to the tunnel wall, splitter plate size, wind tunnel expansion slot configuration, spacing and location of pressure instrumentation, and data processing methods.
We can extend robustly the radio occultation data record by 6 years (+60%) by developing a singlefrequency processing method for GPS/MET data. We will produce a calibrated data set with profile-byprofile data characterization to determine robust upper bounds on ionospheric bias. Part of an effort to produce a calibrated RO data set addressing other key error sources such as upper boundary initialization. Planned: AIRS-GPS water vapor cross validation (water vapor climatology and trends).