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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

New Tools for Automating Arcjet Sample Recession Tracking and Analysis

Arcjet Computer Vision (arcjetCV) has been significantly upgraded to enhance accuracy and performance in tracking material recession and shock-material standoff in test videos. These improvements include integrating new machine learning models, developing a specialized edge detection class, and incorporating a more comprehensive training dataset. These upgrades have refined the software’s ability to automate time-resolved recession tracking, making it more precise and reliable for analyzing complex physical processes. In parallel, a new tool called STARscan (Spatial Targeting and Alignment Rig for Scanning) is being developed to capture detailed 3D surface data before and after testing. By comparing these pre- and post-test scans with arcjetCV’s automated video analysis results, users can achieve a more comprehensive assessment of material recession. This method enables cross-validation of results, improving confidence in the analysis of tested materials. The expanded capabilities of arcjetCV have been successfully demonstrated on videos from various facilities, including the NASA Ames arcjets, UIUC’s PlasmatronX, and the VKI Plasmatron. It has been adopted as a new standard for in-situ recession tracking by the Mars Sample Return Project and Orion. ArcjetCV’s improved efficiency and accuracy are critical for reducing testing uncertainties and validating heatshield material performance under extreme conditions. The software’s user-friendly graphical interface ensures ease of use, enabling seamless processing and precise analysis of arcjet videos, providing deeper insights into material behavior in hypersonic environments. ArcjetCV is now available on both PyPI and Conda, allowing easy installation via "pip install arcjetCV" or through the Conda package manager, ensuring broad accessibility and streamlined deployment for users across various platforms.

Ablation↗
NASA NTRSDate not supplied

Preliminary Design of Robotic Control Software for Mars Sample Return - Capture, Containment, and Return System

The Mars Sample Return (MSR) campaign aims to acquire and return to Earth a set of Mars samples for investigation in terrestrial laboratories. Mars 2020 has collected an adequate number of samples and deposited them in sealed sample tubes at a designated Martian depot. Sample tubes will be placed in cylindrical containers called Orbiting Samples (OS) by the Perseverance Rover, and later brought to Earth by the Earth Return Orbiter (ERO) and the MSR - Capture, Containment, and Return System (CCRS). Robot Software (RSW) is a set of software processes for commanding and monitoring the avionics that controls robotic mechanisms designed to sterilize and install OS into Earth Entry System (EES) for return to Earth. This paper describes a preliminary design of RSW including motion modes, architecture, and finite state machine. Additionally, software engineering procedures and testing of RSW is provided. A preliminary performance analysis is presented and the paper concludes with future work and a discussion of design decisions.

MSR↗
NASA NTRS1981

The Marshall Center: Its place in NASA

The organizational structure and facilities available at the Marshall Space Flight Center are described and the role of the Center in NASA program management is demonstrated in a review of the Center's past history and current development projects. Particular attention is given to space shuttle and the space transportation system; the preparation of experiments and management of Spacelab missions; and the development of the space telescope. Energy related activities discussed include the automatic guidance and control of the longwall shearing machine for coal extraction, systems for the solar heating and cooling of buildings, and the design of the solar power satellite. Products developed by Center personnel highlighted include the power factor controller to reduce electrical consumption by motors and the image enhancement process being used to restore early historical photographs. A free flying solar power source to increase mission duration of the orbiter and its payloads; techniques for the orbital assembly of large space structures; facilities for materials processing in space; the orbit transfer vehicle, solar electric propulsion systems; and the preparation of science and applications payloads are also described.

Source record↗
NASA NTRS1981

The Earth Resources Laboratory Applications Software (ELAS) in university research and education: An operator oriented geobased information system

Created for analyzing and processing digital data such as that collected by multispectral scanners or digitized from maps, ELAS is designed for ease of user operation and includes its own FORTRAN operating monitor and an expandable set of application modules which are FORTRAN overlays. On those machines that do not support FORTRAN overlaying, the modules exist as subprograms. The subsystem can be implemented on most 16-bit or 32-bit machines and is capable of, but not limited to, operating on low-cost minicomputer systems. The recommended hardware configuration for ELAS and a representative listing of some operating and application modules are presented.

Coker, B. L.↗
NASA NTRS1983

Preliminary evaluation of large area bonding processes for repair of graphite/polyimide composites

It is pointed out that graphite/polyimide (Gr/PI) composites are potential candidates for primary and secondary structural components in the next generation of reusable space vehicles and supersonic aircraft which are to possess operational capabilities involving the temperature range from 400 to 600 F. In connection with the considered applications, it is necessary to establish economic and reliable methods for the repair of Gr/PI composite components which have been damaged. The present investigation is concerned with the results of research conducted to develop a bonding process applicable to the repair of large areas in Gr/PI composite structural components. Attention is given to five repair techniques for Gr/PI composite materials. The techniques were employed to fabricate large panels from which flexure and short-beam-shear specimens were machined.

Deaton, J. W.↗
NASA NTRS1988

Design consideration in constructing high performance embedded Knowledge-Based Systems (KBS)

As the hardware trends for artificial intelligence (AI) involve more and more complexity, the process of optimizing the computer system design for a particular problem will also increase in complexity. Space applications of knowledge based systems (KBS) will often require an ability to perform both numerically intensive vector computations and real time symbolic computations. Although parallel machines can theoretically achieve the speeds necessary for most of these problems, if the application itself is not highly parallel, the machine's power cannot be utilized. A scheme is presented which will provide the computer systems engineer with a tool for analyzing machines with various configurations of array, symbolic, scaler, and multiprocessors. High speed networks and interconnections make customized, distributed, intelligent systems feasible for the application of AI in space. The method presented can be used to optimize such AI system configurations and to make comparisons between existing computer systems. It is an open question whether or not, for a given mission requirement, a suitable computer system design can be constructed for any amount of money.

Dalton, Shelly D.↗
NASA NTRS1996

Quantification of Gear Tooth Damage by Optimal Tracking of Vibration Signatures

This paper presents a technique for quantifying the wear or damage of gear teeth in a transmission system. The procedure developed in this study can be applied as a part of either an onboard machine health-monitoring system or a health diagnostic system used during regular maintenance. As the developed methodology is based on analysis of gearbox vibration under normal operating conditions, no shutdown or special modification of operating parameters is required during the diagnostic process. The process of quantifying the wear or damage of gear teeth requires a set of measured vibration data and a model of the gear mesh dynamics. An optimization problem is formulated to determine the profile of a time-varying mesh stiffness parameter for which the model output approximates the measured data. The resulting stiffness profile is then related to the level of gear tooth wear or damage. The procedure was applied to a data set generated artificially and to another obtained experimentally from a spiral bevel gear test rig. The results demonstrate the utility of the procedure as part of an overall health-monitoring system.

Choy, F. K.↗
NASA NTRS2015

Bayesian Safety Risk Modeling of Human-Flightdeck Automation Interaction

Usage of automatic systems in airliners has increased fuel efficiency, added extra capabilities, enhanced safety and reliability, as well as provide improved passenger comfort since its introduction in the late 80's. However, original automation benefits, including reduced flight crew workload, human errors or training requirements, were not achieved as originally expected. Instead, automation introduced new failure modes, redistributed, and sometimes increased workload, brought in new cognitive and attention demands, and increased training requirements. Modern airliners have numerous flight modes, providing more flexibility (and inherently more complexity) to the flight crew. However, the price to pay for the increased flexibility is the need for increased mode awareness, as well as the need to supervise, understand, and predict automated system behavior. Also, over-reliance on automation is linked to manual flight skill degradation and complacency in commercial pilots. As a result, recent accidents involving human errors are often caused by the interactions between humans and the automated systems (e.g., the breakdown in man-machine coordination), deteriorated manual flying skills, and/or loss of situational awareness due to heavy dependence on automated systems. This paper describes the development of the increased complexity and reliance on automation baseline model, named FLAP for FLightdeck Automation Problems. The model development process starts with a comprehensive literature review followed by the construction of a framework comprised of high-level causal factors leading to an automation-related flight anomaly. The framework was then converted into a Bayesian Belief Network (BBN) using the Hugin Software v7.8. The effects of automation on flight crew are incorporated into the model, including flight skill degradation, increased cognitive demand and training requirements along with their interactions. Besides flight crew deficiencies, automation system failures and anomalies of avionic systems are also incorporated. The resultant model helps simulate the emergence of automation-related issues in today's modern airliners from a top-down, generalized approach, which serves as a platform to evaluate NASA developed technologies

Ancel, Ersin↗
NASA NTRS2020

High Resolution Global Coupled Chemistry-Meteorology Simulations Using the NASA GEOS Composition Forecast System, GEOS-CF

We will give an overview of the NASA Global Earth Observing System Composition Forecast system (GEOS-CF), a high-resolution (0.25 degree) global composition model developed by the NASA Global Modeling and Assimilation Office (GMAO). This system combines the GEOS weather and aerosol model with the GEOS-Chem chemistry module (version 12) to provide a holistic view of atmospheric composition that captures a wide range of air pollutants such as ozone, nitrogen oxides, volatile organic compounds, and fine particulate matter. The spatial resolution of 0.25 degrees (approx. 25 km) is fine enough to resolve local features such as nighttime ozone titration previously resolved only by urban or regional models. Furthermore, since there are no boundary conditions for a global model, the GEOS-CF captures large-scale processes such as long-range transport of air pollutants from forest fires. Comparisons against surface observations highlight the model’s overall capability to reproduce the diurnal variability of air pollutants under a variety of meteorological conditions. In addition, we show how machine learning techniques can be used to correct for sub-grid variability, which further improves model estimates at a given surface observation site. The GEOS-CF system offers a new tool for scientists and the public health community alike and is being developed jointly with several government and non-profit partners. As an example, we will show the use of GEOS-CF during the Satellite Coastal and Oceanic Atmospheric Pollution Experiment (SCOAPE). The campaign, conducted in collaboration between NASA and the Bureau of Ocean Energy Management (BOEM), aims to investigate the response of onshore air quality to Outer Continental Shelf (OCS) oil and gas exploration, development and production. Detailed gas-phase chemistry, as provided by GEOS-CF, is critical to understand the formation of air pollution related to hydrocarbon emissions from offshore oil and gas activities. The accuracy of GEOS-CF can be further improved by incorporating detailed offshore emissions compiled by BOEM.

Knowland, K. Emma↗
NASA NTRSDate not supplied

A Method for Validating Causal Diagrams of Human Health Risk in Space Flight

The complexity of cause-and-effect relationships between spaceflight hazards and resulting health conditions clouds understanding of the totality of human system risk in space. In response, NASA has introduced Directed Acyclic Graphs (causal diagrams) into the human systems risk management process. These diagrams allow for a common understanding of the mechanisms that lead from unique hazards of spaceflight to the health outcomes important to agencies and astronauts. However, the paucity of available biomedical data from spaceflight creates a need for methods of validating causal models that can accommodate data from spaceflight model analogs. Here we outline one approach utilizing open-access rodent bone datasets from the Ames Life Sciences Data Archive. The properties of directed acyclic graphs themselves can provide an epistemological and statistical framework for validation of a priori causal representations of human system risk in space flight. The assumed causal connections on the graph creates sets of logical implications: variables that – if the causal diagram is correct – should be correlated, as well as sets that should be conditionally independent. By testing these implied correlations and conditional independencies both statistically and heuristically, we can provide evidence for or against specific causal pathways on the causal diagram. In addition to validation of expert-generated causal diagrams, machine learning techniques can learn the most likely structure of a causal diagram from a given dataset. Comparison with and reconciliation between machine-learned causal diagrams and expert-generated diagrams is another technique for challenging assumptions and improving our understanding of causal mechanisms. Accurately representing complex causation is essential to systemic understanding of human health risks in space travel. Having a robust system of validating causal diagrams helps us arrive at more accurate representations of causal systems. This process will be integral to developing the countermeasures necessary for extended exploration of the moon and Mars.

Robert Reynolds↗
NASA NTRS2016

A Quantum Annealing Computer Team Addresses Climate Change Predictability

The near confluence of the successful launch of the Orbiting Carbon Observatory2 on July 2, 2014 and the acceptance on August 20, 2015 by Google, NASA Ames Research Center and USRA of a 1152 qubit D-Wave 2X Quantum Annealing Computer (QAC), offered an exceptional opportunity to explore the potential of this technology to address the scientific prediction of global annual carbon uptake by land surface processes. At UMBC,we have collected and processed 20 months of global Level 2 light CO2 data as well as fluorescence data. In addition we have collected ARM data at 2sites in the US and Ameriflux data at more than 20 stations. J. Dorband has developed and implemented a multi-hidden layer Boltzmann Machine (BM) algorithm on the QAC. Employing the BM, we are calculating CO2 fluxes by training collocated OCO-2 level 2 CO2 data with ARM ground station tower data to infer to infer measured CO2 flux data. We generate CO2 fluxes with a regression analysis using these BM derived weights on the level 2 CO2 data for three Ameriflux sites distinct from the ARM stations. P. Gentine has negotiated for the access of K34 Ameriflux data in the Amazon and is applying a neural net to infer the CO2 fluxes. N. Talik validated the accuracy of the BM performance on the QAC against a restricted BM implementation on the IBM Softlayer Cloud with the Nvidia co-processors utilizing the same data sets. G. Nearing and K. Harrison have extended the GSFC LIS model with the NCAR Noah photosynthetic parameterization and have run a 10 year global prediction of the net ecosystem exchange. C. Pellisier is preparing a BM implementation of the Kalman filter data assimilation of CO2 fluxes. At UMBC, R. Prouty is conducting OSSE experiments with the LISNoah model on the IBM iDataPlex to simulate the impact of CO2 fluxes to improve the prediction of global annual carbon uptake. J. LeMoigne and D. Simpson have developed a neural net image registration system that will be used for MODIS ENVI and will be converted to a BM algorithm implementation on the QAC. The first integer adder has been implemented on the D-Wave 2X by A. Shehab that will perform HAAR wavelets for image compression of MODIS scenes. Finally, based on the next generations of QACs, we are preparing a 5-year performance road map on the scalability of the current QAC algorithms.

Science Data Processing↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning (ML) Analysis Predicts Space-Exposed Murine Livers

NASA has employed high-throughput molecular assays to identify sub-cellular changes impacting human physiology during spaceflight. Machine learning (ML) methods hold the promise to improve our ability to identify important signals within highly dimensional molecular data. However, the inherent limitation of study subject numbers within a spaceflight mission minimizes the utility of ML approaches. To overcome the sample power limitations, data from multiple spaceflight missions must be aggregated while appropriately addressing intra- and inter-study variabilities. Here we describe an approach to log transform, scale and normalize data from six heterogeneous, mouse liver derived transcriptomics datasets (ntotal=137) which enabled ML-methods to perform well (AUC ≥ 0.87) in classifying spaceflown vs ground control animals rather than mission-of-origin. Concordance was found between liver-specific biological processes identified from harmonized ML-based analysis and study-by-study classical omics analysis. This work demonstrates the feasibility of applying ML methods on integrated, heterogeneous datasets of small sample size.

Machine Learning↗
NASA NTRS1978

Advanced ceramic material for high temperature turbine tip seals

Ceramic material systems are being considered for potential use as turbine blade tip gas path seals at temperatures up to 1370 1/4 C. Silicon carbide and silicon nitride structures were selected for study since an initial analysis of the problem gave these materials the greatest potential for development into a successful materials system. Segments of silicon nitride and silicon carbide materials over a range of densities, processed by various methods, a honeycomb structure of silicon nitride and ceramic blade tip inserts fabricated from both materials by hot pressing were tested singly and in combination. The evaluations included wear under simulated engine blade tip rub conditions, thermal stability, impact resistance, machinability, hot gas erosion and feasibility of fabrication into engine components. The silicon nitride honeycomb and low-density silicon carbide using a selected grain size distribution gave the most promising results as rub-tolerant shroud liners. Ceramic blade tip inserts made from hot-pressed silicon nitride gave excellent test results. Their behavior closely simulated metal tips. Wear was similar to that of metals but reduced by a factor of six.

Solomon, N. G.↗
NASA NTRS1991

Recent manufacturing advances for spiral bevel gears

The U.S. Army Aviation Systems Command (AVSCOM), through the Propulsion Directorate at NASA LRC, has recently sponsored projects to advance the manufacturing process for spiral bevel gears. This type of gear is a critical component in rotary-wing propulsion systems. Two successfully completed contracted projects are described. The first project addresses the automated inspection of spiral bevel gears through the use of coordinate measuring machines. The second project entails the computer-numerical-control (CNC) conversion of a spiral bevel gear grinding machine that is used for all aerospace spiral bevel gears. The results of these projects are described with regard to the savings effected in manufacturing time.

Handschuh, Robert F.↗
NASA NTRS1991

Recent manufacturing advances for spiral bevel gears

The U.S. Army Aviation Systems Command (AVSCOM), through the Propulsion Directorate at NASA Lewis Research Center, has recently sponsored projects to advance the manufacturing process for spiral bevel gears. This type of gear is a critical component in rotary-wing propulsion systems. Two successfully completed contracted projects are described. The first project addresses the automated inspection of spiral bevel gears through the use of coordinate measuring machines. The second project entails the computer-numerical-control (CNC) conversion of a spiral bevel gear grinding machine that is used for all aerospace spiral bevel gears. The results of these projects are described with regard to the savings effected in manufacturing time.

Handschuh, Robert F.↗
NASA NTRS1994

A versatile nondestructive evaluation imaging workstation

Ultrasonic C-scan and eddy current imaging systems are of the pointwise type evaluation systems that rely on a mechanical scanner to physically maneuver a probe relative to the specimen point by point in order to acquire data and generate images. Since the ultrasonic C-scan and eddy current imaging systems are based on the same mechanical scanning mechanisms, the two systems can be combined using the same PC platform with a common mechanical manipulation subsystem and integrated data acquisition software. Based on this concept, we have developed an IBM PC-based combined ultrasonic C-scan and eddy current imaging system. The system is modularized and provides capacity for future hardware and software expansions. Advantages associated with the combined system are: (1) eliminated duplication of the computer and mechanical hardware, (2) unified data acquisition, processing and storage software, (3) reduced setup time for repetitious ultrasonic and eddy current scans, and (4) improved system efficiency. The concept can be adapted to many engineering systems by integrating related PC-based instruments into one multipurpose workstation such as dispensing, machining, packaging, sorting, and other industrial applications.

Chern, E. James↗
NASA NTRS2009

Intermetallic Nickel-Titanium Alloys for Oil-Lubricated Bearing Applications

An intermetallic nickel-titanium alloy, NITINOL 60 (60NiTi), containing 60 wt% nickel and 40 wt% titanium, is shown to be a promising candidate material for oil-lubricated rolling and sliding contact applications such as bearings and gears. NiTi alloys are well known and normally exploited for their shape memory behavior. When properly processed, however, NITINOL 60 exhibits excellent dimensional stability and useful structural properties. Processed via high temperature, high-pressure powder metallurgy techniques or other means, NITINOL 60 offers a broad combination of physical properties that make it unique among bearing materials. NITINOL 60 is hard, electrically conductive, highly corrosion resistant, less dense than steel, readily machined prior to final heat treatment, nongalling and nonmagnetic. No other bearing alloy, metallic or ceramic encompasses all of these attributes. Further, NITINOL 60 has shown remarkable tribological performance when compared to other aerospace bearing alloys under oil-lubricated conditions. Spiral orbit tribometer (SOT) tests were conducted in vacuum using NITINOL 60 balls loaded between rotating 440C stainless steel disks, lubricated with synthetic hydrocarbon oil. Under conditions considered representative of precision bearings, the performance (life and friction) equaled or exceeded that observed with silicon nitride or titanium carbide coated 440C bearing balls. Based upon this preliminary data, it appears that NITINOL 60, despite its high titanium content, is a promising candidate alloy for advanced mechanical systems requiring superior and intrinsic corrosion resistance, electrical conductivity and nonmagnetic behavior under lubricated contacting conditions.

DellaCorte, C.↗
NASA NTRSDate not supplied

Stereo Camera Simulation for Lunar Surface Photogrammetry

During the rocket-powered landing of a vehicle on a planetary body, the interaction between the rocket plume and the surface material beneath the vehicle plays a significant role in the descent dynamics and the safety of powered descent. However, in-situ data taken to investigate plume-surface interaction has been limited. The upcoming flight and lunar landing of the Intuitive Machines Nova-C will be equipped with the Stereo Cameras for Lunar Plume-Surface Studies (SCALPSS) science package, enabling the direct measurement of plume-induced surface cratering during powered descent. In this work, we present the engineering constraints, design iteration process, and simulation results that drove the design selection for the SCALPSS camera system. The chosen design will provide 3D-imaging coverage of 84 percent of the lunar surface directly under the landed Nova-C, in addition to some coverage of the neighboring surface. SCALPSS will provide a total 3D-imaging coverage area of approximately 13 square meters. With the anticipated Nova-C landing in October of 2021, SCALPSS will provide the first dedicated in-situ measurement of plume-induced surface cratering.

Ryan J. Thompson↗