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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 253 records · Page 14

Cancer Detection Using Neural Computing Methodology

This paper describes a novel learning methodology used to analyze bio-materials. The premise of this research is to help pathologists quickly identify anomalous cells in a cost efficient method. Skilled pathologists must methodically, efficiently and carefully analyze manually histopathologic materials for the presence, amount and degree of malignancy and/or other disease states. The prolonged attention required to accomplish this task induces fatigue that may result in a higher rate of diagnostic errors. In addition, automated image analysis systems to date lack a sufficiently intelligent means of identifying even the most general regions of interest in tissue based studies and this shortfall greatly limits their utility. An intelligent data understanding system that could quickly and accurately identify diseased tissues and/or could choose regions of interest would be expected to increase the accuracy of diagnosis and usher in truly automated tissue based image analysis.

liquid crystal tunable filters↗

Automated X-ray and Optical Analysis of the Virtual Observatory and Grid Computing

We are developing a system to combine the Web Enabled Source Identification with X-Matching (WESIX) web service, which emphasizes source detection on optical images,with the XAssist program that automates the analysis of X-ray data. XAssist is continuously processing archival X-ray data in several pipelines. We have established a workflow in which FITS images and/or (in the case of X ray data) an X-ray field can be input to WESIX. Intelligent services return available data (if requested fields have been processed) or submit job requests to a queue to be performed asynchronously. These services will be available via web services (for non-interactive use by Virtual Observatory portals and applications) and through web applications (written in the Django web application framework). We are adding web services for specific XAssist functionality such as determining .the exposure and limiting flux for a given position on the sky and extracting spectra and images for a given region. We are improving the queuing system in XAssist to allow for "watch lists" to be specified by users, and when X-ray fields in a user's watch list become publicly available they will be automatically added to the queue. XAssist is being expanded to be used as a survey planning 1001 when coupled with simulation software, including functionality for NuStar, eRosita, IXO, and the Wide Field Xray Telescope (WFXT), as part of an end to end simulation/analysis system. We are also investigating the possibility of a dedicated iPhone/iPad app for querying pipeline data, requesting processing, and administrative job control.

Ptak, A.↗

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↗

Analysis And Control System For Automated Welding

Automated variable-polarity plasma arc (VPPA) welding apparatus operates under electronic supervision by welding analysis and control system. System performs all major monitoring and controlling functions. It acquires, analyzes, and displays weld-quality data in real time and adjusts process parameters accordingly. Also records pertinent data for use in post-weld analysis and documentation of quality. System includes optoelectronic sensors and data processors that provide feedback control of welding process.

Powell, Bradley W.↗

Automation of Vapor-Diffusion Growth of Protein Crystals

Some improvements have been made in a system of laboratory equipment developed previously for studying the crystallization of proteins from solution by use of dynamically controlled flows of dry gas. The improvements involve mainly (1) automation of dispensing of liquids for starting experiments, (2) automatic control of drying of protein solutions during the experiments, and (3) provision for automated acquisition of video images for monitoring experiments in progress and for post-experiment analysis. The automation of dispensing of liquids was effected by adding an automated liquid-handling robot that can aspirate source solutions and dispense them in either a hanging-drop or a sitting-drop configuration, whichever is specified, in each of 48 experiment chambers. A video camera of approximately the size and shape of a lipstick dispenser was added to a mobile stage that is part of the robot, in order to enable automated acquisition of images in each experiment chamber. The experiment chambers were redesigned to enable the use of sitting drops, enable backlighting of each specimen, and facilitate automation.

Hamrick, David T.↗

Analysis and Review of NASA Earth Science Metadata: How Automation Plays a Role

The Analysis and Review of the Common Metadata Repository (CMR ARC) Team reviews all EOSDIS metadata. The team’s objective is to achieve consistency, correctness, and completeness for all metadata records in the CMR, as well as improve the discoverability of NASA's Earth Science data within the CMR framework. This work is currently being completed at Marshall Space Flight Center. CMR makes a single discovery point possible for NASA's Earth Science data users. The CMR team, in collaboration with three other core metadata teams, contributes to the stewardship of NASA's Earth Science data through a process of continual curation and the ongoing development of the Unified Metadata Model (UMM). A key tool now used in the curation process, referred to as the NASA CMR Dashboard, is an online curation dashboard developed in collaboration with software development company, Element 84. This tool facilitates the review of Earth Science metadata records and subsequent stakeholder collaboration on the resolution of identified issues. A key capability of the new tool is a suite of automated compliance checks written in Python 3.6 that verify the integrity of various metadata elements across multiple standards.

Staton, Patrick↗

Design Oriented Structural Modeling for Airplane Conceptual Design Optimization

The main goal for research conducted with the support of this grant was to develop design oriented structural optimization methods for the conceptual design of airplanes. Traditionally in conceptual design airframe weight is estimated based on statistical equations developed over years of fitting airplane weight data in data bases of similar existing air- planes. Utilization of such regression equations for the design of new airplanes can be justified only if the new air-planes use structural technology similar to the technology on the airplanes in those weight data bases. If any new structural technology is to be pursued or any new unconventional configurations designed the statistical weight equations cannot be used. In such cases any structural weight estimation must be based on rigorous "physics based" structural analysis and optimization of the airframes under consideration. Work under this grant progressed to explore airframe design-oriented structural optimization techniques along two lines of research: methods based on "fast" design oriented finite element technology and methods based on equivalent plate / equivalent shell models of airframes, in which the vehicle is modelled as an assembly of plate and shell components, each simulating a lifting surface or nacelle / fuselage pieces. Since response to changes in geometry are essential in conceptual design of airplanes, as well as the capability to optimize the shape itself, research supported by this grant sought to develop efficient techniques for parametrization of airplane shape and sensitivity analysis with respect to shape design variables. Towards the end of the grant period a prototype automated structural analysis code designed to work with the NASA Aircraft Synthesis conceptual design code ACS= was delivered to NASA Ames.

Livne, Eli↗

Analysis-Driven Design Optimization of a SMA-Based Slat-Cove Filler for Aeroacoustic Noise Reduction

Airframe noise is a significant component of environmental noise in the vicinity of airports. The noise associated with the leading-edge slat of typical transport aircraft is a prominent source of airframe noise. Previous work suggests that a slat-cove filler (SCF) may be an effective noise treatment. Hence, development and optimization of a practical slat-cove-filler structure is a priority. The objectives of this work are to optimize the design of a functioning SCF which incorporates superelastic shape memory alloy (SMA) materials as flexures that permit the deformations involved in the configuration change. The goal of the optimization is to minimize the actuation force needed to retract the slat-SCF assembly while satisfying constraints on the maximum SMA stress and on the SCF deflection under static aerodynamic pressure loads, while also satisfying the condition that the SCF self-deploy during slat extension. A finite element analysis model based on a physical bench-top model is created in Abaqus such that automated iterative analysis of the design could be performed. In order to achieve an optimized design, several design variables associated with the current SCF configuration are considered, such as the thicknesses of SMA flexures and the dimensions of various components, SMA and conventional. Designs of experiment (DOE) are performed to investigate structural response to an aerodynamic pressure load and to slat retraction and deployment. DOE results are then used to inform the optimization process, which determines a design minimizing actuator forces while satisfying the required constraints.

Scholten, William↗

Automated clinical system for chromosome analysis

An automatic chromosome analysis system is provided wherein a suitably prepared slide with chromosome spreads thereon is placed on the stage of an automated microscope. The automated microscope stage is computer operated to move the slide to enable detection of chromosome spreads on the slide. The X and Y location of each chromosome spread that is detected is stored. The computer measures the chromosomes in a spread, classifies them by group or by type and also prepares a digital karyotype image. The computer system can also prepare a patient report summarizing the result of the analysis and listing suspected abnormalities.

Castleman, K. R.↗

Effects of adaptive task allocation on monitoring of automated systems

The effects of adaptive task allocation on monitoring for automation failure during multitask flight simulation were examined. Participants monitored an automated engine status task while simultaneously performing tracking and fuel management tasks over three 30-min sessions. Two methods of adaptive task allocation, both involving temporary return of the automated engine status task to the human operator ("human control"), were examined as a possible countermeasure to monitoring inefficiency. For the model-based adaptive group, the engine status task was allocated to all participants in the middle of the second session for 10 min, following which it was again returned to automation control. The same occurred for the performance-based adaptive group, but only if an individual participant's monitoring performance up to that point did not meet a specified criterion. For the nonadaptive control groups, the engine status task remained automated throughout the experiment. All groups had low probabilities of detection of automation failures for the first 40 min spent with automation. However, following the 10-min intervening period of human control, both adaptive groups detected significantly more automation failures during the subsequent blocks under automation control. The results show that adaptive task allocation can enhance monitoring of automated systems. Both model-based and performance-based allocation improved monitoring of automation. Implications for the design of automated systems are discussed.

Task Performance and Analysis↗

Trends in South American biomass burning detected with the GOES visible infrared spin scan radiometer atmospheric sounder from 1983 to 1991

Previous work demonstrated the ability to manually detect subpixel fire activity in selected areas of the selva and cerrado regions in South America with shortwave and longwave infrared data available from the Geostationary Operational Environmental Satellite (GOES) visible infrared spin scan radiometer atmospheric sounder (VAS). This paper presents the GOES VAS automated biomass-burning algorithm (ABBA) which was developed to determine basin-wide trends in fire activity in South America utilizing the GOES VAS archive. Comparisons between the manual and automated techniques revealed that overall, the ABBA proved to be more consistent in identifying fires and better suited for trend analysis. The automated algorithm was applied daily to a study area extending from 5 deg S to 15 deg S and from 45 deg W to 70 deg W for 2 weeks at the peak of the burning seasons in South America in 1983, 1988, 1989, and 1991 in an effort to measure the areal extent of burning in South American during the past decade and to provide additional insight into the diurnal signature in satellite detection of biomass-burning activities. The expansion of the regions of burning are readily detected in a comparison of these 4 years. From 1983 to 1991 the amount of burning detected by the GOES VAS ABBA during these 2-week periods nearly doubled in the selva and mixed regions and tripled in the cerrado. Diurnal analyses confirmed earlier results indicating that the optimum time to monitor biomass burning is around 1530 UTC.

Prins, Elain M.↗

Nuclear Space System Analysis and Modelling (NSSAM): A Software Tool to Efficiently Analyze the Design Space of Space Reactor Systems

Space reactors have the potential to play a key role in future NASA exploration activities due to their capability to enable sustainable power and advanced propulsion systems. To enable assessment of the space reactor design space, the nuclear space system analysis and modelling (NSSAM) software was developed by Analytical Mechanics Associates. NSSAM leverages a scalable and extensible software architecture which automates reactor analysis to perform coupled engine-reactor and reactor physics-thermal hydraulics calculations. This allows space reactor systems to be evaluated by a wider number of users with a consistent analysis approach to compare designs. NSSAM has been developed with multiple use cases to tailor the analysis to the level of detail desired by the user and computing resources. This summary overviews the NSSAM architecture and development approach, current capabilities (including design variants and use cases) and analysis approach for reactor and system component models.

nuclear thermal propulsion↗

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Jong, Jen-Yi↗

Design for Manufacturing of Structures with Automated Fiber Placement via Integration of Analysis and Process Planning

Under the Design for Manufacturing (DFM) task in the NASA HiCAM program, significant process has been made towards establishing a fully automated optimization process that spans the structural analysis, design, and manufacturing process planning for Automated Fiber Placement (AFP) structures. Previous efforts in this area established the data formats and mapping processes needed to exchange data between disciplines. The software tools used in the framework are HyperX (structural optimization), CAPP (process planning), and VCP (AFP path generation). The work has culminated with automation of data exchanges and an optimization process that drives the three software toward convergence. Within this framework, HyperX is used to generate mass-optimum composite designs which are iterated with VCP and CAPP to improve manufacturability of the designs. As the ply manufacturing process is adjusted by CAPP and VCP, HyperX continually re-assesses the structural integrity of the part and makes adjustments to the laminate as needed. For example, the position of fiber steering and tow overlaps/gaps can necessitate changes to the laminate design. Once the design converges, the end result is a stack of plies that meets both structural and manufacturing requirements. This paper presents the details of the framework and demonstrations the automated process on several parts with significant double-curvature.

HiCAM↗

Dynamic analysis of flexible gear trains/transmissions - An automated approach

In this paper an automated algorithmic method is presented for the dynamic analysis of geared trains/transmissions. These are treated as a system of interconnected flexible bodies. The procedure developed explains the switching of constraints with time as a result of the change in the contacting areas at the gear teeth. The elastic behavior of the system is studied through the employment of three-dimensional isoparametric elements having six degrees-of-freedom at each node. The contact between the bodies is assumed at the various nodes, which could be either a line or a plane. The kinematical expressions, together with the equations of motion using Kane's method, strain energy concepts, are presented in a matrix form suitable for computer implementation. The constraint Jacobian matrices are generated automatically based on the contact information between the bodies. The concepts of the relative velocity at the contacting points at the tooth pairs and the subsequent use of the transmission ratios in the analysis is presented.

Amirouche, F. M. L.↗

Data-driven surface traversability analysis for Mars 2020 landing site selection

This paper is to describe the engineering challenges in the surface mobility of the Mars 2020 Rover mission that are considered in the landing site selection process, introduce new automated traversability analysis capabilities, and present the preliminary analysis results for top candidate landing sites.

Heverly, Matthew↗

SSME Post Test Diagnostic System: Systems Section

An assessment of engine and component health is routinely made after each test firing or flight firing of a Space Shuttle Main Engine (SSME). Currently, this health assessment is done by teams of engineers who manually review sensor data, performance data, and engine and component operating histories. Based on review of information from these various sources, an evaluation is made as to the health of each component of the SSME and the preparedness of the engine for another test or flight. The objective of this project - the SSME Post Test Diagnostic System (PTDS) - is to develop a computer program which automates the analysis of test data from the SSME in order to detect and diagnose anomalies. This report primarily covers work on the Systems Section of the PTDS, which automates the analyses performed by the systems/performance group at the Propulsion Branch of NASA Marshall Space Flight Center (MSFC). This group is responsible for assessing the overall health and performance of the engine, and detecting and diagnosing anomalies which involve multiple components (other groups are responsible for analyzing the behavior of specific components). The PTDS utilizes several advanced software technologies to perform its analyses. Raw test data is analyzed using signal processing routines which detect features in the data, such as spikes, shifts, peaks, and drifts. Component analyses are performed by expert systems, which use 'rules-of-thumb' obtained from interviews with the MSFC data analysts to detect and diagnose anomalies. The systems analysis is performed using case-based reasoning. Results of all analyses are stored in a relational database and displayed via an X-window-based graphical user interface which provides ranked lists of anomalies and observations by engine component, along with supporting data plots for each.

Bickmore, Timothy↗