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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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NASA NTRSDate not supplied

Applying Machine Learning Tools for Runway Configuration Decision Support

Determining optimal runway configurations at airports, a responsibility assigned to air traffic controllers, is a challenging task. The decision-making process is intricate and involves consideration of many factors such as prevailing wind condition, convective weather, visibility, cloud ceilings, departure and arrival demand, traffic flow, equipment status, and other airport constraints. In a previous work, we developed a Runway Configuration Assistance tool using an offline reinforcement learning method called conservative Q-learning. In this paper, we evaluate and validate our Runway Configuration Assistance tool as a decision support for air traffic controllers. We validated our tool using three airports with differing levels of complexity: Charlotte Douglas International Airport, Denver International Airport, and Dallas Fort Worth International Airport. We quantified the performance of the Runway Configuration Assistance tool based on (1) agreement with historical air traffic controller decisions and (2) violation of decisions that would be obvious to subject-matter experts. Our tool showed promising results in both performance metrics for the three airports, despite the complexities in the runway configuration decision-making process. We also discuss challenges in using machine learning in general to aid air traffic management and identify deployment considerations for the Runway Configuration Assistance tool.

Runway Configuration Management↗

NASA NTRSDate not supplied

Machine Learning Tools for Runway Configuration Decision Support

Runway Configuration Management↗

NASA NTRS1982

The Orthogonal In-Situ Machining of Single and Polycrystalline Aluminum and Copper, Volume 1

Metal cutting is a unique deformation process characterized by large strains, exceptionally high strain rates and few constraints to the deformation. These factors, along with the difficulty of directly measuring the shear angle, make chip formation difficult to model and understand. One technique for skirting the difficulty of post mortem chip measurement is to perform a cutting experiment dynamically in a scanning electron microscope. The performance of the in-situ experiment with full instrumentation allows for component force measurement, orientation measurement (on a round single crystal disk) and a timing device, all superimposed below the deformation on the TV monitor and recorded for future viewing. This allows the sher angle to be directly measured for the screen along with the other needed information.

Cohen, P. H.↗

NASA NTRS1985

Lubrication of nonconformal contacts

Minimum film thickness results for piezoviscous-rigid regime of lubrication are developed for a compressible Newtonian fluid with Roelands viscosity. The results provide a basis for the analysis and design of a wide range of machine elements operating in the piezoviscous-rigid regime of lubrication. A new numerical method of calculating elastic deformation in contact stresses is developed using a biquadratic polynomial to approximate the pressure distribution on the whole domain analyzed. The deformation of every node is expressed as a linear combination of the nodal pressures whose coefficients can be combined into an influence coefficient matrix. This approach has the advantages of improved numerical accuracy, less computing time and smaller storage size required for influence matrix. The ideal elastohydrodynamic lubrication is extended to real bearing systems in order to gain an understanding of failure mechanisms in machine elements. The improved elastic deformation calculation is successfully incorporated into the EHL numerical scheme. Using this revised numerical technique and the flow factor model developed by Patir and Cheng (1978) the surface roughness effects on the elastohydrodynamic lubrication of point contact is considered. Conditions typical of an EHL contact in the piezoviscous-elastic regime entrained in pure rolling are investigated. Results are compared with the smooth surface solutions. Experiments are conducted to study the transient EHL effects in instrument ball bearings.

Jeng, Y. R.↗

NASA NTRS1992

Development of a fractional-step method for the unsteady incompressible Navier-Stokes equations in generalized coordinate systems

A fractional step method is developed for solving the time-dependent three-dimensional incompressible Navier-Stokes equations in generalized coordinate systems. The primitive variable formulation uses the pressure, defined at the center of the computational cell, and the volume fluxes across the faces of the cells as the dependent variables, instead of the Cartesian components of the velocity. This choice is equivalent to using the contravariant velocity components in a staggered grid multiplied by the volume of the computational cell. The governing equations are discretized by finite volumes using a staggered mesh system. The solution of the continuity equation is decoupled from the momentum equations by a fractional step method which enforces mass conservation by solving a Poisson equation. This procedure, combined with the consistent approximations of the geometric quantities, is done to satisfy the discretized mass conservation equation to machine accuracy, as well as to gain the favorable convergence properties of the Poisson solver. The momentum equations are solved by an approximate factorization method, and a novel ZEBRA scheme with four-color ordering is devised for the efficient solution of the Poisson equation. Several two- and three-dimensional laminar test cases are computed and compared with other numerical and experimental results to validate the solution method. Good agreement is obtained in all cases.

Rosenfeld, Moshe↗

NASA NTRS2007

Concepts for Distributed Engine Control

Gas turbine engines for aero-propulsion systems are found to be highly optimized machines after over 70 years of development. Still, additional performance improvements are sought while reduction in the overall cost is increasingly a driving factor. Control systems play a vitally important part in these metrics but are severely constrained by the operating environment and the consequences of system failure. The considerable challenges facing future engine control system design have been investigated. A preliminary analysis has been conducted of the potential benefits of distributed control architecture when applied to aero-engines. In particular, reductions in size, weight, and cost of the control system are possible. NASA is conducting research to further explore these benefits, with emphasis on the particular benefits enabled by high temperature electronics and an open-systems approach to standardized communications interfaces.

Culley, Dennis E.↗

NASA NTRSDate not supplied

Development of Solar Flare and Energetic Particle Prediction Portal (SEP 3 )

Solar activity is a primary factor determining the state of the Earth’s space environment, geomagnetic and ionospheric disturbances, and radiation hazards. In the current state of knowledge, machine learning (ML) methods provide essential tools for processing data, investigating relationships among various physical properties and characteristics, uncovering hidden connections, and predicting hazardous solar events. The primary difficulty in developing and applying modern machine-learning tools in heliophysics is that the essential data are scattered among over a hundred data repositories developed by instrument teams of space missions and ground-based observatories. In addition, statistical and ML methods require long time series of homogeneous measurements. To facilitate ML-ready data preparation and access, we have developed an interactive database of solar flares integrating the most essential datasets (https://solarflare.njit.edu/). The database performs an initial data processing and is automatically updated. In addition, we are developing the Solar Energetic Particle Prediction Portal (SEP3, https://sun.njit.edu/SEP3), which hosts web applications that allow users to retrieve the database records. The Portal has a search page for browsing the events from the most widely used catalogs and a dedicated space to share the most recent achievements of the team. The interactive widget can display soft X-ray and proton flux time series from GOES satellites and the flare records. The data portal has been used to evaluate the forecasts of solar proton events and investigate machine-learning approaches to SEP prediction.

SMD↗

NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The development of the Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large complex systems engineering challenge being addressed in part by focusing on the specific subsystems handling of off-nominal mission and fault tolerance. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML), the Mission and Fault Management (M&FM) algorithms are crafted and vetted in specialized Integrated Development Teams composed of multiple development disciplines. NASA also has formed an M&FM team for addressing fault management early in the development lifecycle. This team has developed a dedicated Vehicle Management End-to-End Testbed (VMET) that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. The flexibility of VMET enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the algorithms utilizing actual subsystem models. The intent is to validate the algorithms and substantiate them with performance baselines for each of the vehicle subsystems in an independent platform exterior to flight software test processes. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test processes. Risk reduction is addressed by working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and detection and responses that can be tested in VMET and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM. The plan for VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗

NASA NTRS1973

International Symposium on Remote Sensing of Environment, 8th, University of Michigan, Ann Arbor, Mich., October 2-6, 1972, Proceedings. Volumes 1 & 2.

Recent developments in remote sensing techniques and applications are described in papers dealing with (1) ground-based, airborne, and space-borne sensor systems, (2) machine assisted data analysis and interpretation, and (3) specific uses of sensing techniques by various government units. Topics covered include monitoring of environmental quality factors, delineation of geological formations and mineral deposits, watershed management, observation of vegetative parameters in forestry and agriculture, design and performance details of various sensor systems and equipment, interpretation of multispectral imagery, and applications of ERTS-1 satellite imagery in resource study programs. Individual items are announced in this issue.

Source record↗

NASA NTRS1986

Hitts Law? A test of the relationship between information load and movement precision

Recent technological developments have made viable a man-machine interface heavily dependent on graphics and pointing devices. This has led to new interest in classical reaction and movement time work by Human Factors specialists. Two experiments were designed and run to test the dependence of target capture time on information load (Hitt's Law) and movement precision (Fitts' Law). The proposed model linearly combines Hitt's and Fitts' results into a combination law which then might be called Hitts' Law. Subjects were required to react to stimuli by manipulating a joystick so as to cause a cursor to capture a target on a CRT screen. Response entropy and the relative precision of the capture movement were crossed in a factorial design and data obtained that were found to support the model.

Zaleski, M.↗

NASA NTRS1992

The design and implementation of a parallel unstructured Euler solver using software primitives

This paper is concerned with the implementation of a three-dimensional unstructured grid Euler-solver on massively parallel distributed-memory computer architectures. The goal is to minimize solution time by achieving high computational rates with a numerically efficient algorithm. An unstructured multigrid algorithm with an edge-based data structure has been adopted, and a number of optimizations have been devised and implemented in order to accelerate the parallel communication rates. The implementation is carried out by creating a set of software tools, which provide an interface between the parallelization issues and the sequential code, while providing a basis for future automatic run-time compilation support. Large practical unstructured grid problems are solved on the Intel iPSC/860 hypercube and Intel Touchstone Delta machine. The quantitative effect of the various optimizations are demonstrated, and we show that the combined effect of these optimizations leads to roughly a factor of three performance improvement. The overall solution efficiency is compared with that obtained on the CRAY-YMP vector supercomputer.

Das, R.↗

NASA NTRS1993

An application of machine learning to the organization of institutional software repositories

Software reuse has become a major goal in the development of space systems, as a recent NASA-wide workshop on the subject made clear. The Data Systems Technology Division of Goddard Space Flight Center has been working on tools and techniques for promoting reuse, in particular in the development of satellite ground support software. One of these tools is the Experiment in Libraries via Incremental Schemata and Cobweb (ElvisC). ElvisC applies machine learning to the problem of organizing a reusable software component library for efficient and reliable retrieval. In this paper we describe the background factors that have motivated this work, present the design of the system, and evaluate the results of its application.

Bailin, Sidney↗

NASA NTRS1994

Design and implementation of a parallel unstructured Euler solver using software primitives

This paper is concerned with the implementation of a three-dimensional unstructured-grid Euler solver on massively parallel distributed-memory computer architectures. The goal is to minimize solution time by achieving high computational rates with a numerically efficient algorithm. An unstructured multigrid algorithm with an edge-based data structure has been adopted, and a number of optimizations have been devised and implemented to accelerate the parallel computational rates. The implementation is carried out by creating a set of software tools, which provide an interface between the parallelization issues and the sequential code, while providing a basis for future automatic run-time compilation support. Large practical unstructured grid problems are solved on the Intel iPSC/860 hypercube and Intel Touchstone Delta machine. The quantitative effects of the various optimizations are demonstrated, and we show that the combined effect of these optimizations leads to roughly a factor of 3 performance improvement. The overall solution efficiency is compared with that obtained on the Cray Y-MP vector supercomputer.

Das, R.↗

NASA NTRS1995

Dynamics and control of instrumented harmonic drives

Since torque in harmonic drives is transmitted by a pure couple, harmonic drives do not generate radial forces and therefore can be instrumented with torque sensors without interference from radial forces. The installation of torque sensors on the stationary component of harmonic drives (the Flexipline cup in this research work) produce backdrivability needed for robotic and telerobotic compliant maneuvers. Backdrivability of a harmonic drive, when used as torque increaser, means that the output shaft can be rotated via finite amount of torque. A high ratio harmonic drive is non-backdrivable because its output shaft cannot be turned by applying a torque on it. This article first develops the dynamic behavior of a harmonic drive, in particular the non-backdrivability, in terms of a sensitivity transfer function. The instrumentation of the harmonic drive with torque sensor is then described. This leads to a description of the control architecture which allows modulation of the sensitivity transfer function within the limits established by the closed-loop stability. A set of experiments on an active hand controller, powered by a DC motor coupled to an instrumented harmonic drive, is given to exhibit this method's limitations.

NASA Discipline Space Human Factors↗

NASA NTRS1996

A Framework for Modeling Human-Machine Interactions

Modern automated flight-control systems employ a variety of different behaviors, or modes, for managing the flight. While developments in cockpit automation have resulted in workload reduction and economical advantages, they have also given rise to an ill-defined class of human-machine problems, sometimes referred to as 'automation surprises'. Our interest in applying formal methods for describing human-computer interaction stems from our ongoing research on cockpit automation. In this area of aeronautical human factors, there is much concern about how flight crews interact with automated flight-control systems, so that the likelihood of making errors, in particular mode-errors, is minimized and the consequences of such errors are contained. The goal of the ongoing research on formal methods in this context is: (1) to develop a framework for describing human interaction with control systems; (2) to formally categorize such automation surprises; and (3) to develop tests for identification of these categories early in the specification phase of a new human-machine system.

Shafto, Michael G.↗

NASA NTRS1979

A 200-kW wind turbine generator conceptual design study

A conceptual design study was conducted to define a 200 kW wind turbine power system configuration for remote applications. The goal was to attain an energy cost of 1 to 2 cents per kilowatt-hour at a 14-mph site (mean average wind velocity at an altitude of 30 ft.) The costs of the Clayton, New Mexico, Mod-OA (200-kW) were used to identify the components, subsystems, and other factors that were high in cost and thus candidates for cost reduction. Efforts devoted to developing component and subsystem concepts and ideas resulted in a machine concept that is considerably simpler, lighter in weight, and lower in cost than the present Mod-OA wind turbines. In this report are described the various innovations that contributed to the lower cost and lighter weight design as well as the method used to calculate the cost of energy.

Source record↗

NASA NTRS2015

Auralization of Tonal Rotor Noise Components of a Quadcopter Flyover

The capabilities offered by small unmanned vertical lift aerial vehicles, for example, quadcopters, continue to captivate entrepreneurs across the private, public, and civil sectors. As this industry rapidly expands, the public will be exposed to these devices (and to the noise these devices generate) with increasing frequency and proximity. Accordingly, an assessment of the human response to these machines will be needed shortly by decision makers in many facets of this burgeoning industry, from hardware manufacturers all the way to government regulators. One factor of this response is that of the annoyance to the noise that is generated by these devices. This paper presents work currently being pursued by NASA toward this goal. First, physics-based (CFD) predictions are performed on a single isolated rotor typical of these devices. The result of these predictions are time records of the discrete tonal components of the rotor noise. These time records are calculated for a number of points that appear on a lattice of locations spread over the lower hemisphere of the rotor. The source noise is then generated by interpolating between these time records. The sound from four rotors are combined and simulated-propagation techniques are used to produce complete flyover auralizations.

Christian, Andrew W.↗

NASA NTRSDate not supplied

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗