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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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Minicomputer-controlled system automatically prepares and analyses blood samples and displays karyotype in pictorial form as primary output. System accuracy is assured by operator interaction at key points during process. System can process up to 576 specimens per day.
Attention is given to the robot stereo vision system which maintains the image produced by solid-state detector television cameras in a dynamic random access memory called RAPID. The imaging hardware consists of sensors (two solid-state image arrays using a charge injection technique), a video-rate analog-to-digital converter, the RAPID memory, and various types of computer-controlled displays, and preprocessing equipment (for reflexive actions, processing aids, and object detection). The software is aimed at locating objects and transversibility. An object-tracking algorithm is discussed and it is noted that tracking speed is in the 50-75 pixels/s range.
Hydrogen evolved by coliform bacteria transferred to separate measurement cell. Electroanalytic cell mounted in insulated temperature-control bath cycled between culturing temperature and sterilizing temperature. Flow of materials into and out of cell controlled by electrically operated valves.
A versatile laser characterization method is described for evaluating semiconductor lasers developed under R&D efforts and also commercially available lasers. This method features a high-resolution technique for measuring laser linewidth that was also found to introduce optical feedback to the laser. The modified delayed self-homodyne system is therefore utilized to collect a variety of laser characteristic measurements under dynamic operating conditions while simultaneously assessing the effects of optical feedback on the laser. Measurements employing scanning Fabry-Perot interferometers are described which supplement the data obtained from direct measurements and measurements made utilizing the self-homodyne system.
The topics are presented in view graph form and include the following: Computer Human Interaction Models (CHIMES) methodology; the CHIMES-2 prototype; and CHIMES future development.
A proposition to study the effect of filtering processes on range images and to evaluate the performance of two different laser range mappers is made. Median filtering was utilized to remove noise from the range images. First and second order derivatives are then utilized to locate the similarities and dissimilarities between the processed and the original images. Range depth information is converted into spatial coordinates, and a set of coefficients which describe 3-D objects is generated using the algorithm developed in the second phase of this research. Range images of spheres and cylinders are used for experimental purposes. An algorithm was developed to compare the performance of two different laser range mappers based upon the range depth information of surfaces generated by each of the mappers. Furthermore, an approach based on 2-D analytic geometry is also proposed which serves as a basis for the recognition of regular 3-D geometric objects.
A system which is to provide real-time failure analysis support to controllers at the NASA Johnson Space Center Control Center Complex (CCC) for both Space Station and Space Shuttle on-orbit operations is described. The system employs monitored systems' models of failure behavior and model evaluation algorithms which are domain-independent. These failure models are viewed as a stepping stone to more robust algorithms operating over models of intended function. The described system is designed to meet two sets of requirements. It must provide a useful failure analysis capability enhancement to the mission controller. It must satisfy CCC operational environment constraints such as cost, computer resource requirements, verification, and validation. The underlying technology and how it may be used to support operations is also discussed.
In order to develop scalable parallel applications, a number of programming decisions have to be made during the development of the program. Performance tools that help in making these decisions are few, if existent. Traditionally, performance tools have focused on exposing performance bottlenecks of small-scale executions of the program. However, it is common knowledge that programs that perform exceptionally well on small processor configurations, more often than not, perform poorly when executed on larger processor configurations. Hence, new tools that predict the execution characteristics of scaled-up programs are an essential part of an application developers toolkit. In this paper we discuss important issues that need to be considered in order to build useful scalability analysis tools for parallel programs. We introduce a simple tool that automatically extracts scalability characteristics of a class of deterministic parallel programs. We show with the help of a number of results on the Intel iPSC/860, that predictions are within reasonable bounds.
ATLAS is a generalized solution that can be used for launch vehicles. ATLAS is used to produce modal transient analysis and quasi-static analysis results (i.e., accelerations, displacements, and forces) for the payload math models on a specific Shuttle Transport System (STS) flight using the shuttle math model and associated forcing functions. This innovation solves the problem of coupling of payload math models into a shuttle math model. It performs a transient loads analysis simulating liftoff, landing, and all flight events between liftoff and landing. ATLAS utilizes efficient and numerically stable algorithms available in MSC/NASTRAN.
We introduce a framework that automates the process of assessing potential satellite conjunctions in space, and generating collision avoidance maneuvers to support mitigation efforts within a novel space traffic management (STM) architecture. A software implementation of the framework was developed in a MATLAB-STK integrated environment, however, the concept and framework is agnostic to the language or environment. The software pulls from existing catalogs of spaceborne objects and ingests user-defined parameters to produce conjunction data, which could potentially aid collision avoidance planning in the STM architecture. The utility of the software in maneuver planning and exploring a performance-based tradespace of actions is demonstrated using three example cases: one-to-one conjunction, one-versus-four conjunctions, and a near head-on collision. The framework also provides a test-bed for the use of application programming interfaces (APIs) to demonstrate machine-to-machine communication between entities in our proposed STM architecture. Results from this software implementation are expected to aid distributed decision-making among various stakeholders, and inform efficient, autonomous, structured but flexible concept of operations within STM.
Automated fiber placement provides many advancements beyond traditional hand layups in terms of efficiency and reliability. However, there are also a variety of unique challenges that arise with automated fiber placement technology. In particular, steering of tows over doubly-curved tool surfaces can result in material overlaps and gaps due to path convergence/divergence, fiber angle deviation, as well defects in the tows themselves such as puckers and wrinkles. Minimization of these defects is traditionally considered a task for the manufacturing discipline. Manufacturing specifications are often created for these defects based on laminate testing and can be inflexible to avoid more tests. Recent efforts have been made under the National Aeronautics and Space Administration (NASA) Advanced Composites Project (ACP) to develop software tools and processes that provide automated coupling between design and manufacturing disciplines. The objective of this coupling is to provide information to the design discipline on the manufacturability of a laminate while the laminate is being designed. A variety of software tools, both existing commercial tools and research tools under development, will be used to achieve this objective: HyperSizer for laminate optimization, the Computer Aided Process Planning module for selection of manufacturing process parameters, Vericut Composite Programming for tow path simulation, and COMPRO for deposition and cure defects. The newly developed “Central Optimizer” tool will be used to tie the modules together and drive the design for manufacturing process.
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Faults in commercial buildings can cause energy waste and other performance problems such as reduced occupant comfort, reduced equipment longevity, and increased noise. However, it is currently unknown how commonly faults occur in different equipment types. A method has been developed to estimate the prevalence of faults in air handling units, air terminal units, and rooftop units. This method includes two types of data. The first is data from several automated fault detection and diagnostics (AFDD) software technologies. This type of data provides a large sample that represents a wide range of building types, geographical locations, and equipment types. It includes fault diagnoses from thousands of buildings around the United States, as well as anonymized metadata describing the building and equipment characteristics. The number of fault records is in the order of 107. However, despite the size and richness of the data sample, this data contains some degree of inaccuracy, i.e., false positive and false negative findings. Therefore, the study includes a second type of data, coming from manual inspection of buildings that have had the same AFDD methods applied to them (from the commercial AFDD offerings). Since the field tests are conducted in buildings with AFDD-generated fault prevalence data, they can be combined with the larger sample size to provide insight into the potential biases or lower sensitivity of the AFDD data. Once a library of fault prevalence data is built, it will be studied to provide further insight into the drivers of fault prevalence, for example, whether prevalence is correlated with building type, geographical location (which is tied to climate and to utility rates), building size, etc. This paper describes the methods developed for this study and illustrates them with preliminary data. It discusses some of the challenges of harmonizing disparate outputs from multiple AFDD vendors, application of a unifying fault taxonomy, and fault prevalence metrics.
Fast automated analysis of hyperspectral imagery can inform observation planning and tactical decisions during planetary exploration. Products such as mineralogical maps can focus analysts' attention on areas of interest and assist data mining in large hyperspectral catalogs. In this work, sparse spectral unmixing drafts mineral abundance maps with Compact Reconnaissance Imaging Spectrometer (CRISM) images from the Mars Reconnaissance Orbiter. We demonstrate a novel "superpixel" segmentation strategy enabling efficient unmixing in an interactive session. Tests correlate automatic unmixing results based on redundant spectral libraries against hand-tuned summary products currently in use by CRISM researchers.
The automated particle analysis (APA) method of scanning electron microscopy (SEM) energy dispersive X-ray spectroscopy (EDS/EDX) is a useful tool for analyzing the elemental and morphological data of particulate samples. Often, such datasets have many thousands of particles, and it can be difficult to sift through the data to find meaningful trends. EDXplorer is a software utility for processing APA data. They enable the user to easily load data and determine the important components and aspects of the datasets using a powerful and versatile library of data plotting functions, mainly centered around scatter plots and histograms. These programs are intended to fill a void in the data processing of data from certain instruments, where often the user must rely on their own code or other software that is not user-friendly. EDXplorer is intended as a general plotting utility for browsing through data and discovering data trends.
An automated dynamics data analysis and management systems implemented on a DEC VAX minicomputer cluster is described. Multichannel acquisition, Fast Fourier Transformation analysis, and an online database have significantly improved the analysis of wideband transducer responses from Space Shuttle Main Engine testing. Leakage error correction to recover sinusoid amplitudes and correct for frequency slewing is described. The phase errors caused by FM recorder/playback head misalignment are automatically measured and used to correct the data. Data compression methods are described and compared. The system hardware is described. Applications using the data base are introduced, including software for power spectral density, instantaneous time history, amplitude histogram, fatigue analysis, and rotordynamics expert system analysis.
The automated analysis of SSME injector assemblies has been investigated for the cases of LOX post surface defects and injector-baffle deterioration. Defects are isolated via 2D feature extraction from borescope and camera images; temporal-frequency transforms are then used to create a multiresolution set of feature vectors representing image contents. The potential flaws thus discriminated are then segmented and classified according to known categories. AI is applied in the form of a blackboard architecture that is controlled by a rule-based production system.
Halide perovskites (HPs) have remarkable optoelectronic properties, and in the last decade their photovoltaic power conversion efficiency and light-emitting diode efficiency have skyrocketed. Despite the surge in research on these burgeoning materials, two key challenges in the field remain: material irreproducibility and instability. Their behavior is especially dynamic in response to environmental stressors, due to complex interactions with the perovskite crystal lattice. Here, in this review, we survey the latest achievements in HP materials research accomplished with the assistance of artificial intelligence (AI), through the implementation of automated experimentation and machine learning (ML) data analysis. Automated synthesis and characterization tackle problems with material irreproducibility by systematically controlling parameters with very high precision, creating massive datasets, and allowing methodical comparisons from which unbiased conclusions can be drawn. AI can reveal otherwise unnoticed trends, inform future experiments with the highest potential information gain, and forecast future performance. The review concludes with a forward viewpoint of how human-assisted closed-loop laboratories and shared databases allow halide perovskite materials’ processing, properties, and performance to be potentially optimized with AI, accelerating the development of highly reproducible and stable optoelectronic devices.