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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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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Simulated final approach path captures using the microwave landing system

Computer simulation results are presented for intercepting final approach paths using various Microwave Landing System (MLS) path capture concepts. This study, conducted under the Advanced Transport Operating System (ATOPS) program, simulated these captures using the MD-80 aircraft as the study model. Several different capture concepts were investigated. Systems that could be retrofitted into existing aircraft with minimum hardware and software changes were considered. An enhanced ILS look-alike capture provided improved tracking performance over conventional ILS without using a full-up path computer. The other concepts used waypoint databases and path computers to provide smart captures. These captures included lateral path intercepts as well as vertical path control. Winds, turbulence, and MLS noise were included in the simulation. In all cases, acceptable tracking errors were obtained during transition to the final approach path.

Feather, J. B.↗
NASA NTRS2002

Technical Challenges in the Development of a NASA Synthetic Vision System Concept

Within NASA's Aviation Safety Program, the Synthetic Vision Systems Project is developing display system concepts to improve pilot terrain/situation awareness by providing a perspective synthetic view of the outside world through an on-board database driven by precise aircraft positioning information updating via Global Positioning System-based data. This work is aimed at eliminating visibility-induced errors and low visibility conditions as a causal factor to civil aircraft accidents, as well as replicating the operational benefits of clear day flight operations regardless of the actual outside visibility condition. Synthetic vision research and development activities at NASA Langley Research Center are focused around a series of ground simulation and flight test experiments designed to evaluate, investigate, and assess the technology which can lead to operational and certified synthetic vision systems. The technical challenges that have been encountered and that are anticipated in this research and development activity are summarized.

Bailey, Randall E.↗
NASA NTRS2003

Evaluation of Production Cross Sections of Li, Be, B in CR

Accurate evaluation of the production cross section of light elements is important for models of cosmic ray (CR) propagation, galactic chemical evolution, and cosmological studies. However, the experimental spallation cross section data are scarce and often unavailable to CR community while semi-empirical systematics are frequently wrong by a significant factor. Running sophisticated nuclear codes is not an option of choice for everyone either. We use the Los Alamos versions of the Quark-Gluon String Model code LAQGSM and the improved Cascade-Exciton Model code CEM2k together with all available data from Los Alamos Nuclear Laboratory (LANL) nuclear database to produce evaluated production cross sections of isotopes of Li, Be, and B suitable for astrophysical applications. The LAQGSM and CEM2k models have been shown to reproduce well nuclear reactions and hadronic data in the range 0.01-800 GeV/nucleon.

Moskalenko, I. V.↗
NASA NTRS2009

DSN Simulator

The DSN Simulator (wherein DSN signifies NASA's Deep Space Network) is an updated version of the software described in DSN Array Simulator (NPO-44506), Software Tech Briefs (Special supplement to NASA Tech Briefs), Vol. 32, No. 9 (September 2008), page 26. To recapitulate: This software is used for computational modeling of proposed DSN facilities comprising arrays of antennas and transmitting and receiving equipment for microwave communication with spacecraft on interplanetary missions. Such modeling is performed to estimate facility performance, evaluate requirements that govern facility design, and evaluate proposed improvements in hardware and/or software. The software includes a Monte Carlo simulation component that enables rapid generation of key mission-set metrics (e.g., numbers of links, data rates, and data volumes), and statistical distributions thereof as functions of time. The prior version of the software could model only one DSN facility at a time and included hard-coded, unconfigurable metrics. The present updated version is capable of modeling the entire DSN and provides for configurable metrics, making it possible to perform loading analyses for alternative future DSN architectures and mission-set scenarios. The present version also features an improved user interface and interfaces for exchange of data with other DSN software and with a DSN mission model database.

Fijany, Amir↗
NASA NTRS2012

Real-Time, Interactive Sonic Boom Display

The present invention is an improved real-time, interactive sonic boom display for aircraft. By using physical properties obtained via various sensors and databases, the invention determines, in real-time, sonic boom impacts locations and intensities for aircraft traveling at supersonic speeds. The information is provided to a pilot via a display that lists a selectable set of maneuvers available to the pilot to mitigate sonic boom issues. Upon selection of a maneuver, the information as to the result of the maneuver is displayed and the pilot may proceed with making the maneuver, or provide new data to the system in order to calculate a different maneuver.

Haering, Jr., Edward A.↗
NASA NTRS2001

SRTM on-orbit structural dynamics

The primary product of the Space Radar Topography Mission was a topographic database of 80 percent of the earth's land surface. The resulting digital terrain data set provides a significant improvement over currently existing global topography data sets.

SRTM↗
DOE OSTI2024

CIGS Technology Advancement via Fundamental Modeling of Defect/Impurity Interactions (Final Technical Report)

The primary goals of the proposed work were to provide modeling tools (and the associated insight which comes along with model development) for design and optimization of CuIn x Ga 1-x Se 2 (CIGS) and CdSeTe (CST) solar cell manufacturing processes and to establish the foundation for comprehensive end-to-end predictive modeling tools to enable optimization of thin film photovoltaic technology for performance, cost, yield, and reliability. The initial focus of efforts within this project was to develop coupled process/optical/device models for CIGS PV technology and to work with Siva Power to apply that TCAD (technology computer-aided design) system to improve the efficiency and reduce manufacturing costs for CIGS solar cells. Our approach to that end was to generate an extensive database of DFT calculations and to use those calculations via statistical thermodynamics methods and Monte Carlo simulation to develop and characterize models for the behavior of native defects as well as intentional and unintentional impurities, including the redistribution of the primary components of CIGS films. Increased effort went toward coupling those models for defect behavior and composition evolution to the performance of multicrystalline CIGS solar cells via prediction of doping level and recombination lifetime as function of manufacturing process. In the second budget period, the project pivoted to developing a similar system for the CdSeTe system, focused especially on understanding the role of Se/Te alloy concentration. Execution of the project resulted in the successful development of TCAD systems for both CIGS and CdSeTe thin film PV within the Synopsys Sentaurus framework by utilizing the Alagator interface. In the first budget period of the project, we developed quantitative models for the major components of CIGS PV and implemented them within a framework that couples process, optical, and device simulation. From the insights we have gained, we identified novel opportunities for enhancing CIGS solar cell performance and have laid the groundwork to further optimize the layer structure, composition profile, and thermal cycles for substantially improved efficiency and lower manufacturing costs. For the CIGS system, process changes to achieve greater than 1% absolute enhancement in efficiency were identified, but testing of those approaches was stymied by lack of a domestic CIGS manufacturing partner after the closure of Siva Power as well as Miasole. For CdSeTe, a fully capable TCAD system only became ready to apply near the end of the project period, so substantial opportunities remain to apply those models to enhance the leading thin film PV technology.

14 SOLAR ENERGY↗
DOE OSTI2026

Quality Control of Silicon Sensor Modules for Particle Detectors

The High-Luminosity Large Hadron Collider (HL-LHC) will produce a higher rate of particle collisions than the current Large Hadron Collider (LHC), requiring important upgrades to the Compact Muon Solenoid (CMS) to handle an increased amount of data. An important upgrade is the Phase-2 Outer Tracker Upgrade, which consists of 13,000 silicon sensor modules made of two parallel silicon sensors and readout electronics. These modules undergo careful quality control checks both during and after module assembly to ensure precise and reliable detector performance. This project focuses on precision testing for quality control of silicon sensor modules at Fermilab. Hands-on work includes visual inspection, current-voltage testing, module testing, and ultraviolet (UV) light exposure of modules showing abnormal current-voltage behavior. The ultraviolet exposure process improves the abnormal sensor readout data by placing the selected sensor side of the module directly under the UV light inside a controlled box. In addition to laboratory testing and ultraviolet experiments, I developed a Python-based data tool that connects to a module database and allows selected testing conditions and module information to be retrieved and displayed efficiently. These different testing procedures, experimental processes, and computational tools support the broader goal of identifying module issues and improving modules that will be used in the CMS Outer Tracker Phase-2 Upgrade.

Siddiqui, Hooriya [DuPage Coll.] (ORCID:0009000151↗
DOE OSTI2026

Quality Control of Silicon Sensor Modules for Particle Detectors

The High-Luminosity Large Hadron Collider (HL-LHC) will produce a higher rate of particle collisions than the current Large Hadron Collider (LHC), requiring significant upgrades to the Compact Muon Solenoid (CMS) to handle the increased amount of data. An important upgrade is the Phase-2 Outer Tracker Upgrade, which consists of 13,000 silicon sensor modules made of two parallel silicon sensors and readout electronics. These modules undergo careful quality control checks both during and after module assembly to ensure precise and reliable detector performance. This project focuses on precision testing for quality control of silicon sensor modules at Fermilab. Hands-on work includes visual inspection, current-voltage testing, module testing, and ultraviolet (UV) light exposure of modules showing abnormal current-voltage behavior. The ultraviolet exposure process improves the abnormal sensor readout data by placing the selected sensor side of the module directly under the UV light inside a controlled box. In addition to laboratory testing and ultraviolet experiments, I developed a Python-based data tool that connects to a module database and allows selected testing conditions and module information to be retrieved and displayed efficiently. These different testing procedures, experimental processes, and computational tools support the broader goal of identifying module issues and improving modules that will be used in the CMS Outer Tracker Phase-2 Upgrade.

Siddiqui, Hooriya [DuPage Coll.; Fermilab] (ORCID:↗
NASA NTRS2014

ENSO Effect on East Asian Tropical Cyclone Landfall via Changes in Tracks and Genesis in a Statistical Model

Improvements on a statistical tropical cyclone (TC) track model in the western North Pacific Ocean are described. The goal of the model is to study the effect of El Nino-Southern Oscillation (ENSO) on East Asian TC landfall. The model is based on the International Best-Track Archive for Climate Stewardship (IBTrACS) database of TC observations for 1945-2007 and employs local regression of TC formation rates and track increments on the Nino-3.4 index and seasonally varying climate parameters. The main improvements are the inclusion of ENSO dependence in the track propagation and accounting for seasonality in both genesis and tracks. A comparison of simulations of the 1945-2007 period with observations concludes that the model updates improve the skill of this model in simulating TCs. Changes in TC genesis and tracks are analyzed separately and cumulatively in simulations of stationary extreme ENSO states. ENSO effects on regional (100-km scale) landfall are attributed to changes in genesis and tracks. The effect of ENSO on genesis is predominantly a shift in genesis location from the southeast in El Nino years to the northwest in La Nina years, resulting in higher landfall rates for the East Asian coast during La Nina. The effect of ENSO on track propagation varies seasonally and spatially. In the peak activity season (July-October), there are significant changes in mean tracks with ENSO. Landfall-rate changes from genesis- and track-ENSO effects in the Philippines cancel out, while coastal segments of Vietnam, China, the Korean Peninsula, and Japan show enhanced La Nina-year increases.

simulation↗
NASA NTRS2005

Portfolio Analysis Tool

Portfolio Analysis Tool (PAT) is a Web-based, client/server computer program that helps managers of multiple projects funded by different customers to make decisions regarding investments in those projects. PAT facilitates analysis on a macroscopic level, without distraction by parochial concerns or tactical details of individual projects, so that managers decisions can reflect the broad strategy of their organization. PAT is accessible via almost any Web-browser software. Experts in specific projects can contribute to a broad database that managers can use in analyzing the costs and benefits of all projects, but do not have access for modifying criteria for analyzing projects: access for modifying criteria is limited to managers according to levels of administrative privilege. PAT affords flexibility for modifying criteria for particular "focus areas" so as to enable standardization of criteria among similar projects, thereby making it possible to improve assessments without need to rewrite computer code or to rehire experts, and thereby further reducing the cost of maintaining and upgrading computer code. Information in the PAT database and results of PAT analyses can be incorporated into a variety of ready-made or customizable tabular or graphical displays.

Barth, Tim↗
NASA NTRS2021

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗
NASA NTRS1996

Information Technology: A Tool to Cut Health Care Costs

Old Dominion University embarked on a project to see how current computer technology could be applied to reduce the cost and or to improve the efficiency of health care services. We designed and built a prototype for an integrated medical record system (MRS). The MRS is written in Tool control language/Tool kit (Tcl/Tk). While the initial version of the prototype had patient information hard coded into the system, later versions used an INGRES database for storing patient information. Currently, we have proposed an object-oriented model for implementing MRS. These projects involve developing information systems for physicians and medical researchers to enhance their ability for improved treatment at reduced costs. The move to computerized patient records is well underway, several standards exist for laboratory records, and several groups are working on standards for other portions of the patient record.

Mukkamala, Ravi↗
DOE OSTI2026

Machine-Learning-Driven Discovery of Water Splitting BaFe 2 O 4 and Human-in-the-Loop Improvement via Al-Substitution for Increased Thermal Stability

Thermochemical hydrogen (TCH) production offers a promising method for converting thermal energy into hydrogen fuel through heat-driven redox cycles of metal oxides. Here, in this work a defect graph neural network (dGNN) was used to predict oxygen vacancy formation energies ΔH V O combined with Materials Project predictions of oxygen chemical potential stability to screen candidate oxides via high-throughput database analysis. BaFe 2 O 4 was identified as a promising material for experimental validation based on its predicted ΔH V O , oxygen chemical potential stability range, and potential for tunable substitutions to improve thermal properties. Experimental validation using thermogravimetric analysis (TGA), stagnation flow reactor (SFR), X-ray diffraction (XRD), and electron microscopy confirmed positive water-splitting behavior but also revealed limitations in thermal stability under aggressive reduction conditions. To address this, a human-in-the-loop modification strategy was employed introducing Al substitution in BaFe 2–x Al x O 4 ; this modification improves thermal stability, alters the crystal structure and enhances overall performance. These results demonstrate a combined computational and experimental workflow in which machine learning accelerates identification of promising candidates, while targeted experimental design enables optimization of functional performance. This approach advances the development of robust, cost-effective TCH materials and highlights the importance of integrating data-driven discovery with human-guided materials design in paving the way for scalable hydrogen production technologies.

organic↗
NASA NTRS2002

Decades of Data: Extracting Trends from Microgravity Crystallization History

The reduced acceleration environment of an orbiting spacecraft has been posited as an ideal environment for biological crystal growth since buoyancy driven convection and sedimentation are greatly reduced. Since the first sounding rocket flight in 1981 many crystallization experiments have flown with some showing improvement and others not. To further explore macromolecule crystal improvement in microgravity we have accumulated data from published reports and reports submitted by individual investigators to NASA, forming a database called BIOSEArCH (Biological Space Experiment Archive of Crystallization History). To date it contains information from 63 missions including, the Space Shuttle program, unmanned satellites, the Russian Space Station MIR and sounding rocket experiments, containing reports for more than 736 macromolecule experiments. While it is not at this point in time a comprehensive record of all flight crystallization experimental results, there is however sufficient information for emerging trends to be identified. These trends will be highlighted.

Judge, Russell A.↗
NASA NTRS2006

Calculation of Free-Atom Fractions in Hydrocarbon-Fueled Rocket Engine Plume

Free atom fractions (Beta) of nine elements are calculated in the exhaust plume of CH4- oxygen and RP-1-oxygen fueled rocket engines using free energy minimization method. The Chemical Equilibrium and Applications (CEA) computer program developed by the Glenn Research Center, NASA is used for this purpose. Data on variation of Beta in both fuels as a function of temperature (1600 K - 3100 K) and oxygen to fuel ratios (1.75 to 2.25 by weight) is presented in both tabular and graphical forms. Recommendation is made for the Beta value for a tenth element, Palladium. The CEA computer code was also run to compare with experimentally determined Beta values reported in literature for some of these elements. A reasonable agreement, within a factor of three, between the calculated and reported values is observed. Values reported in this work will be used as a first approximation for pilot rocket engine testing studies at the Stennis Space Center for at least six elements Al, Ca, Cr, Cu, Fe and Ni - until experimental values are generated. The current estimates will be improved when more complete thermodynamic data on the remaining four elements Ag, Co, Mn and Pd are added to the database. A critique of the CEA code is also included.

Verma, Satyajit↗
NASA NTRS2012

ALSSAT Version 6.0

Advanced Life Support Sizing Analysis Tool (ALSSAT) at the time of this reporting has been updated to version 6.0. A previous version was described in Tool for Sizing Analysis of the Advanced Life Support System (MSC- 23506), NASA Tech Briefs, Vol. 29, No. 12 (December 2005), page 43. To recapitulate: ALSSAT is a computer program for sizing and analyzing designs of environmental-control and life-support systems for spacecraft and surface habitats to be involved in exploration of Mars and the Moon. Of particular interest for analysis by ALSSAT are conceptual designs of advanced life-support (ALS) subsystems that utilize physicochemical and biological processes to recycle air and water and process human wastes to reduce the need of resource resupply. ALSSAT is a means of investigating combinations of such subsystems technologies featuring various alternative conceptual designs and thereby assisting in determining which combination is most cost-effective. ALSSAT version 6.0 has been improved over previous versions in several respects, including the following additions: an interface for reading sizing data from an ALS database, computational models of a redundant regenerative CO2 and Moisture Removal Amine Swing Beds (CAMRAS) for CO2 removal, upgrade of the Temperature & Humidity Control's Common Cabin Air Assembly to a detailed sizing model, and upgrade of the Food-management subsystem.

Yeh, Hue-Hsia↗
NASA NTRS2016

Acoustic Measurements of a Large Civil Transport Main Landing Gear Model

Microphone phased array acoustic measurements of a 26 percent-scale, Boeing 777-200 main landing gear model with and without noise reduction fairings installed were obtained in the anechoic configuration of the Virginia Tech Stability Tunnel. Data were acquired at Mach numbers of 0.12, 0.15, and 0.17 with the latter speed used as the nominal test condition. The fully and partially dressed gear with the truck angle set at 13 degrees toe-up landing configuration were the two most extensively tested configurations, serving as the baselines for comparison purposes. Acoustic measurements were also acquired for the same two baseline configurations with the truck angle set at 0 degrees. In addition, a previously tested noise reducing, toboggan-shaped fairing was re-evaluated extensively to address some of the lingering questions regarding the extent of acoustic benefit achievable with this device. The integrated spectra generated from the acoustic source maps reconfirm, in general terms, the previously reported noise reduction performance of the toboggan fairing as installed on an isolated gear. With the recent improvements to the Virginia Tech tunnel acoustic quality and microphone array capabilities, the present measurements provide an additional, higher quality database to the acoustic information available for this gear model.

Ravetta, Patricio A.↗