SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Automated interstellar space exploration is reviewed. The Titan demonstration mission is discussed. Remote sensing and automated modeling are considered. Nuclear electric propulsion, main orbiting spacecraft, lander/rover, subsatellites, atmospheric probes, powered air vehicles, and a surface science network comprise mission component concepts. Machine, intelligence in space exploration is discussed.
The history of planetary rovers in the U.S. space program is outlined in the context of the goals, mission and spacecraft designs, and operations designs. The American lunar rover work has had three main stages. In the early sixties, the capacity of Surveyor lunar landers to deliver rovers with a mass of about 50 kg to the Moon was exploited. Several such machines were built and tested beginning in 1964 but none went to the Moon. A manned 400 kg short range rover was then developed. Three of these operated on the Moon in 1971 and 1972 as part of the Apollo 15, 16 and 17 missions. Following these Apollo successes, attempts were made to provide two kinds of follow on models: automated or dual mode (human carrying or not) rovers in the few hundred kg size class, and multi-ton mobile habitats that could carry humans on extended traverses. With the closing of both Soviet and American lunar exploration in the seventies, neither of these proposals succeeded. In parallel with these lunar developments, a lengthy technology program on Martian roving has gone on in the U.S., sometimes coming close to preproject status and sometimes fading away, but never quite being abandoned. As a result it is possible today to contemplate a wide range of lunar and Martian roving missions that could be made practical within a few years. However, with today's funding constraints none of the well studied, larger mission concepts appear to fit. Therefore new efforts are being made toward developing much smaller rovers taking advantage of new miniature techniques, not only in mobility systems but also in the scientific instruments that a small rover can carry. Illustrations are included.
Electrical conduction in the heart shows many phenomena familiar from nonlinear dynamics. Among these phenomena are multiple basins of attraction, phase locking, and perhaps period-doubling bifurcations and chaos. We describe a simple cellular-automation model of electrical conduction which simulates normal conduction patterns in the heart as well as a wide range of disturbances of heart rhythm. In addition, we review the application of percolation theory to the analysis of the development of complex, self-sustaining conduction patterns.
The Intelligent Systems Project was responsible for much of NASA's programmatic investment in artificial intelligence and advanced information technologies. IS has completed three major project milestones which demonstrated increased capabilities in autonomy, human centered computing, and intelligent data understanding. Autonomy involves the ability of a robot to place an instrument on a remote surface with a single command cycle. Human centered computing supported a collaborative, mission centric data and planning system for the Mars Exploration Rovers and data understanding has produced key components of a terrestrial satellite observation system with automated modeling and data analysis capabilities. This paper summarizes the technology demonstrations and metrics which quantify and summarize these new technologies which are now available for future Nasa missions.
NASA's Aviation Safety Program (AvSP) develops and advances methodologies and technologies to improve air transportation safety. The Safety Analysis and Integration Team (SAIT) conducts a safety technology portfolio assessment (PA) to analyze the program content, to examine the benefits and risks of products with respect to program goals, and to support programmatic decision making. The PA process includes systematic identification of current and future safety risks as well as tracking several quantitative and qualitative metrics to ensure the program goals are addressing prominent safety risks accurately and effectively. One of the metrics within the PA process involves using quantitative aviation safety models to gauge the impact of the safety products. This paper demonstrates the role of aviation safety modeling by providing model outputs and evaluating a sample of portfolio elements using the Flightdeck Automation Problems (FLAP) model. The model enables not only ranking of the quantitative relative risk reduction impact of all portfolio elements, but also highlighting the areas with high potential impact via sensitivity and gap analyses in support of the program office. Although the model outputs are preliminary and products are notional, the process shown in this paper is essential to a comprehensive PA of NASA's safety products in the current program and future programs/projects.
Model-based Systems Engineering can be employed beyond management of the technical architecture development of a system to also manage the programmatics associated with Systems Engineering activities of a project. On NASA’s Asteroid Redirect Robotic Mission, MBSE has been successfully employed to manage, generate, and interact with the documentation-based deliverables associated with System Engineering activities. This has been involved in defining and tracking project document, milestone, and personnel metadata via the same modeling framework used for the technical architecture management. Additionally, it has focused on improving overall user experiences through linkage of documentation to technical content in the system model, automation of manually intensive tasks, and others stakeholderoriented features.
Combining linear stability calculations with computational fluid dynamics (CFD) simulations has great potential for the automated modeling of high-speed flows, especially when adequate information about the configuration and the disturbance environment is available. However, a significant impediment to the applicability of this technique is the lack of an efficient method to calculate the crucial amplification ratio corresponding to the onset of transition in hypersonic flows. This ratio, also known as the "transition N-factor," is dependent upon the freestream disturbance environment as well as the surface properties of the test article. In response to the need for an engineering solution to predict the transition N-factor within conventional hypersonic wind tunnels, this paper presents a data-driven correlation that expands the existing correlations from straight circular cones with a narrow range of half angles to a broader array of axisymmetric configurations. Furthermore, when tested against a chosen dataset that was not used in its calibration, the suggested correlation shows good predictive accuracy with an RMS error of only 6.9%. Although similar accuracy may also be achieved via existing correlations based on similar datasets, predictions based on the proposed correlation have the advantage of not requiring an extensive amount of configuration-specific data. Practical applications often have access to the input parameters needed for this correlation, such as the freestream disturbance intensity, Mach number, and body-based slenderness Reynolds number. Additionally, this correlation outperforms the traditional assumption of a constant N-factor, particularly for configurations with blunted nose geometries. The development of this correlation is grounded in an extensive dataset encompassing conical models with body half-angles varying between 5 degrees and 16 degrees, Mach numbers ranging from 5 to 14, and nosetip-based Reynolds numbers approaching the transition reversal limit for blunt-nosed cones.
Combining linear stability calculations with computational fluid dynamics (CFD) simulations has great potential for the automated modeling of high-speed flows, especially when adequate information about the configuration and the disturbance environment is available. However, a significant impediment to the applicability of this technique is the lack of an efficient method to calculate the crucial amplification ratio corresponding to the onset of transition in hypersonic flows. This ratio, also known as the "transition N-factor," is dependent upon the freestream disturbance environment as well as the surface properties of the test article. In response to the need for an engineering solution to predict the transition N-factor within conventional hypersonic wind tunnels, this paper presents a data-driven correlation that expands the existing correlations from straight circular cones with a narrow range of half angles to a broader array of axisymmetric configurations. Furthermore, when tested against a chosen dataset that was not used in its calibration, the suggested correlation shows good predictive accuracy with an RMS error of only 6.9%. Although similar accuracy may also be achieved via existing correlations based on similar datasets, predictions based on the proposed correlation have the advantage of not requiring an extensive amount of configuration-specific data. Practical applications often have access to the input parameters needed for this correlation, such as the freestream disturbance intensity, Mach number, and body-based slenderness Reynolds number. Additionally, this correlation outperforms the traditional assumption of a constant N-factor, particularly for configurations with blunted nose geometries. The development of this correlation is grounded in an extensive dataset encompassing conical models with body half-angles varying between 5 degrees and 16 degrees, Mach numbers ranging from 5 to 14, and nosetip-based Reynolds numbers approaching the transition reversal limit for blunt-nosed cones.
Efforts to develop an automated system, from ERTS data, for producing computer models and computer maps of land use and other environmental factors for the Phoenix quadrangle are outlined.
The objective of this Phase I project is to develop a highly automated software system for rapid geometry modeling and grid generation for turbomachinery applications. The proposed system features a graphical user interface for interactive control, a direct interface to commercial CAD/PDM systems, support for IGES geometry output, and a scripting capability for obtaining a high level of automation and end-user customization of the tool. The developed system is fully parametric and highly automated, and, therefore, significantly reduces the turnaround time for 3D geometry modeling, grid generation and model setup. This facilitates design environments in which a large number of cases need to be generated, such as for parametric analysis and design optimization of turbomachinery equipment. In Phase I we have successfully demonstrated the feasibility of the approach. The system has been tested on a wide variety of turbomachinery geometries, including several impellers and a multi stage rotor-stator combination. In Phase II, we plan to integrate the developed system with turbomachinery design software and with commercial CAD/PDM software.
The integrated monitoring and control commercial off-the-shelf system (IMACCS), which demonstrates the feasibility of automating spacecraft monitoring and control activities through the use of state modeling, is described together with its use. The use of the system for the control and ground support of the solar, anomalous and magnetic particle explorer (SAMPEX) spacecraft is considered. A key component of IMACCS is the Altair mission control system which implements finite state modeling as an element of its expert system capability. Using the finite state modeling and state transition capabilities of the Altair mission control system, IMACCS features automated monitoring, routine pass support, anomaly resolution and emergency 'lights on again' response. Automatic orbit determination and the production of typical flight dynamics products exists. These functionalities are described.
Techniques to identify aircraft aerodynamic characteristics from flight measurements and compute corrections to an existing simulation model of a research aircraft were investigated. The purpose of the research was to develop a process enabling rapid automated updating of aircraft simulation models using flight data and apply this capability to all flight regimes, including flight envelope extremes. The process presented has the potential to improve the efficiency of envelope expansion flight testing, revision of control system properties, and the development of high-fidelity simulators for pilot training.
The calculation of reliability measures using Markov models is required for life-critical processor-memory-switch structures that have standby redundancy or that are subject to transient or intermittent faults or repair. The task of specifying these models is tedious and prone to human error because of the large number of states and transitions required in any reasonable system. Therefore, model specification is a major analysis bottleneck, and model verification is a major validation problem. The general unfamiliarity of computer architects with Markov modeling techniques further increases the necessity of automating the model specification. Automation requires a general system description language (SDL). For practicality, this SDL should also provide a high level of abstraction and be easy to learn and use. The first attempt to define and implement an SDL with those characteristics is presented. A program named Automated Reliability Modeling (ARM) was constructed as a research vehicle. The ARM program uses a graphical interface as its SDL, and it outputs a Markov reliability model specification formulated for direct use by programs that generate and evaluate the model.
A model of controller and automation activities was used to design the controller-automation interactions necessary to implement a new terminal area air traffic management concept. The model was then used to design a controller interface that provides the requisite information and functionality. Using data from a preliminary study, the Crew Activity Tracking System (CATS) was used to help validate the model as a computational tool for describing controller performance.
Mission models for 1971 to 1981 for use in NASA launch vehicle planning
Explore the source record for details and available documents.
A method is developed and illustrated which finds minimum changes in analytical mass and stiffness matrices to make them consistent with a set of measured normal modes and natural frequencies. The corrected model is an improved base for studies of physical changes, changes in boundary conditions, and for prediction of forced responses. Features of the method are: efficient procedures not requiring solutions of the eigenproblem; the model may have more degrees of freedom than the test data; modal displacements at all the analytical degrees of freedom are obtained; the frequency dependence of the coordinate transformations are properly treated.
A method is described to improve a linear nonproportionally damped analytical model of a structure. The procedure finds the smallest changes in the analytical model such that the improved model matches the measured modal parameters. Features of the method are: (1) ability to properly treat complex valued modal parameters of a damped system; (2) applicability to realistically large structural models; and (3) computationally efficiency without involving eigensolutions and inversion of a large matrix.