SEARCH · Search NASA

Results for “factorization machine”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11

All sources NASA NTRS DOE OSTI

NASA NTRS1989

A parallel finite-difference method for computational aerodynamics

A finite-difference scheme for solving complex three-dimensional aerodynamic flow on parallel-processing supercomputers is presented. The method consists of a basic flow solver with multigrid convergence acceleration, embedded grid refinements, and a zonal equation scheme. Multitasking and vectorization have been incorporated into the algorithm. Results obtained include multiprocessed flow simulations from the Cray X-MP and Cray-2. Speedups as high as 3.3 for the two-dimensional case and 3.5 for segments of the three-dimensional case have been achieved on the Cray-2. The entire solver attained a factor of 2.7 improvement over its unitasked version on the Cray-2. The performance of the parallel algorithm on each machine is analyzed.

Swisshelm, Julie M.↗

NASA NTRS2018

Modeling Key Predictors of Airport Runway Configurations Using Learning Algorithms

Advanced traffic flow management automation will need accurate predictions of airport runway configurations. Terminal area weather and traffic demand are generally considered to be the most significant factors in predicting runway configuration. Weather information is forecasted across multiple features, including wind direction, wind speed, gusts, cloud ceilings, visibility, temperature, and precipitation, among many others. We use machine learning techniques on historical weather and runway data to determine weather features that correlate well with runway configurations. We analyze the predictive capability of weather features using different learning models trained on data from four major U.S. airports: Atlanta (ATL), Washington – Dulles (IAD), New York – Kennedy (JFK), and San Francisco (SFO). Wind direction alone is strongly correlated with runway configurations above all other examined factors, as expected. This correlation is the most significant component of the ~80% prediction accuracy in selecting between the two most frequently used runway configurations. However, individual airports show variations on how well the runway configuration decisions correlate with wind direction. While wind direction was identified as the most significant indicator of configuration decisions in ATL, IAD, and JFK, it did not emerge as such at SFO. Traffic demand was not found to be a strong factor in predicting runway configurations at any of the airports analyzed. In rare instances, when high demand cannot be accommodated within the current configuration, temporary changes are likely to be attributable to demand. However, these occurrences are so limited in number that their overall effect is not sufficient to consider traffic demand as a major indicator of runway configuration at the airports analyzed.

Bilimoria, Karl D.↗

NASA NTRS2013

Miga Aero Actuator and 2D Machined Mechanical Binary Latch

Shape memory alloy (SMA) actuators provide the highest force-to-weight ratio of any known actuator. They can be designed for a wide variety of form factors from flat, thin packages, to form-matching packages for existing actuators. SMA actuators can be operated many thousands of times, so that ground testing is possible. Actuation speed can be accurately controlled from milliseconds to position and hold, and even electronic velocity-profile control is possible. SMA actuators provide a high degree of operational flexibility, and are truly smart actuators capable of being accurately controlled by onboard microprocessors across a wide range of voltages. The Miga Aero actuator is a SMA actuator designed specifically for spaceflight applications. Providing 13 mm of stroke with either 20- or 40-N output force in two different models, the Aero actuator is made from low-outgassing PEEK (polyether ether ketone) plastic, stainless steel, and nickel-titanium SMA wires. The modular actuator weighs less than 28 grams. The dorsal output attachment allows the Aero to be used in either PUSH or PULL modes by inverting the mounting orientation. The SPA1 actuator utilizes commercially available SMA actuator wire to provide 3/8-in. (approx. =.1 cm) of stroke at a force of over 28 lb (approx. = .125 N). The force is provided by a unique packaging of the single SMA wire that provides the output force of four SMA wires mechanically in parallel. The output load is shared by allowing the SMA wire to slip around the output attachment end to adjust or balance the load, preventing any individual wire segment from experiencing high loads during actuation. A built-in end limit switch prevents overheating of the SMA element following actuation when used in conjunction with the Miga Analog Driver [a simple MOSFET (metal oxide semiconductor field-effect transistor) switching circuit]. A simple 2D machined mechanical binary latch has been developed to complement the capabilities of SMA wire actuators. SMA actuators typically perform ideally as latch-release devices, wherein a spring-loaded device is released when the SMA actuator actuates in one direction. But many applications require cycling between two latched states open and closed.

Gummin, Mark A.↗

NASA NTRS2018

Software and Human-Machine Interface Development for Environmental Controls Subsystem Support

The Space Launch System (SLS) is the next premier launch vehicle for NASA. It is the next stage of manned space exploration from American soil, and will be the platform in which we push further beyond Earth orbit. In preparation of the SLS maiden voyage on Exploration Mission 1 (EM-1), the existing ground support architecture at Kennedy Space Center required significant overhaul and updating. A comprehensive upgrade of controls systems was necessary, including programmable logic controller software, as well as Launch Control Center (LCC) firing room and local launch pad displays for technician use. Environmental control acts as an integral component in these systems, being the foremost system for conditioning the pad and extremely sensitive launch vehicle until T-0. The Environmental Controls Subsystem (ECS) required testing and modification to meet the requirements of the designed system, as well as the human factors requirements of NASA software for Validation and Verification (V&V). This term saw significant strides in the progress and functionality of the human-machine interfaces used at the launch pad, and improved integration with the controller code.

Dobson, Matthew↗

NASA NTRS2017

Human Factors Engineering and Ergonomics in Systems Engineering

The study, discovery, and application of information about human abilities, human limitations, and other human characteristics to the design of tools, devices, machines, systems, job tasks and environments for effective human performance.

Whitmore, Mihriban↗

NASA NTRS2025

Improving Adhesive Bondline Time of Flight Predictions During Autoclave Cure Utilizing Machine Learning

Composite materials are increasingly being used in aerospace applications due to their superior strength-to-weight ratio compared to commonly used metals. A current limitation to widespread adoption is the certification of adhesively bonded joints. One approach to improving adhesive bonding in composites is accurately measuring the thickness of adhesive bondlines in composite laminates. Precise bondline thickness control is essential for aerospace applications where adhesive layer thickness directly affects joint fracture properties and structural performance. This study focused on implementing machine learning techniques to determine the ultrasonic time of flight (directly correlated to thickness) in adhesive bondlines throughout autoclave cure cycles. A high-temperature (use up to 180°C) ultrasonic scanning system was deployed in an autoclave to provide time of flight data through composite panels. Three experiments were conducted on the curing of 305 mm × 305 mm unidirectional composite panels. In the first experiment, a piecewise function was fit for the temperature correction factor to account for changing autoclave temperatures. Due to deficiencies in the first calibration experiment, a second experiment was run, and the results were used to train a machine learning model. The revised experiment, in combination with the machine learning model, significantly increased the accuracy of the bondline time of flight predictions (~14% error reduced to <1%). Data was processed using the Regression Learner Application in MATLAB®, with a Support Vector Machine selected for the model. The result was a machine learning algorithm capable of reliably quantifying ultrasonic time of flight through adhesive bondlines. The third experiment provided independent test data for the machine learning model, demonstrating that the model produces accurate predictions from data beyond its training set.

Machine Learning↗

NASA NTRS1975

Human factors in general aviation

The relation of the pilot to the aircraft in general aviation is considered. The human component is analyzed, along with general aviation facilities. The man-machine interface, and the man-environment interface are discussed.

Source record↗

NASA NTRS1990

National plan to enhance aviation safety through human factors improvements

The purpose of this section of the plan is to establish a development and implementation strategy plan for improving safety and efficiency in the Air Traffic Control (ATC) system. These improvements will be achieved through the proper applications of human factors considerations to the present and future systems. The program will have four basic goals: (1) prepare for the future system through proper hiring and training; (2) develop a controller work station team concept (managing human errors); (3) understand and address the human factors implications of negative system results; and (4) define the proper division of responsibilities and interactions between the human and the machine in ATC systems. This plan addresses six program elements which together address the overall purpose. The six program elements are: (1) determine principles of human-centered automation that will enhance aviation safety and the efficiency of the air traffic controller; (2) provide new and/or enhanced methods and techniques to measure, assess, and improve human performance in the ATC environment; (3) determine system needs and methods for information transfer between and within controller teams and between controller teams and the cockpit; (4) determine how new controller work station technology can optimally be applied and integrated to enhance safety and efficiency; (5) assess training needs and develop improved techniques and strategies for selection, training, and evaluation of controllers; and (6) develop standards, methods, and procedures for the certification and validation of human engineering in the design, testing, and implementation of any hardware or software system element which affects information flow to or from the human.

Foushee, Clay↗

NASA NTRS2024

Machine Learning for the Prediction of Local Asteroid Damages

Risk assessment studies of local asteroid hazards traditionally simulate the physics of meteors with engineering models tailored to analyze tens-of-millions of scenarios. However, these simplified approaches still need to solve time-dependent ODEs to model the entry process and the resulting ground damage. With a computational cost of O(0.01 CPU.s) per scenario, simulating these large numbers of potential entry conditions in risk assessment studies can take several days on local computers. To improve computational efficiency, we propose in this paper an orthogonal approach based on machine learning models to predict the size of damaged areas given a list of entry parameters. We train 5 machine learning methods and compare the predictions to the outputs of the PAIR model, first only with primitive entry condition variables, and then with more advanced features. We find that complex models like neural networks are well-suited to estimate blast hazards, while simpler linear models can accurately assess thermal damage. For both types of hazards, the radii of damaged areas can be predicted with around 10% average errors and a coefficient of determination (R2) of 0.99. The CPU time is decreased by a factor O(10 3 ) compared to the PAIR model, which enables the simulation of millions of scenarios in minutes, on a local computer. We then use the same machine learning approaches for a classification task where the models are trained to predict if an asteroid will produce a given level of damage. Results show that complex models like the gradient boosting classifier and the neural network can perform this task with 98% accuracy. Beyond surrogate models, we finally incorporate the machine learning algorithms to the state-of-the-art Shapley sensitivity analysis and present a ranking of the entry parameters based on their contributions to ground damages.

SMD↗

NASA NTRS1997

Team play with a powerful and independent agent: operational experiences and automation surprises on the Airbus A-320

Research and operational experience have shown that one of the major problems with pilot-automation interaction is a lack of mode awareness (i.e., the current and future status and behavior of the automation). As a result, pilots sometimes experience so-called automation surprises when the automation takes an unexpected action or fails to behave as anticipated. A lack of mode awareness and automation surprises can he viewed as symptoms of a mismatch between human and machine properties and capabilities. Changes in automation design can therefore he expected to affect the likelihood and nature of problems encountered by pilots. Previous studies have focused exclusively on early generation "glass cockpit" aircraft that were designed based on a similar automation philosophy. To find out whether similar difficulties with maintaining mode awareness are encountered on more advanced aircraft, a corpus of automation surprises was gathered from pilots of the Airbus A-320, an aircraft characterized by high levels of autonomy, authority, and complexity. To understand the underlying reasons for reported breakdowns in human-automation coordination, we also asked pilots about their monitoring strategies and their experiences with and attitude toward the unique design of flight controls on this aircraft.

NASA Discipline Space Human Factors↗

NASA NTRS1975

Combined bending-torsion fatigue reliability. III

Results generated by three, unique fatigue reliability research machines which can apply reversed bending loads combined with steady torque are presented. AISI 4340 steel, grooved specimens with a stress concentration factor of 1.42 and 2.34, and Rockwell C hardness of 35/40 were subjected to various combinations of these loads and cycled to failure. The generated cycles-to-failure and stress-to-failure data are statistically analyzed to develop distributional S-N and Goodman diagrams. Various failure theories are investigated to determine which one represents the data best. The effects of the groove, and of the various combined bending-torsion loads, on the S-N and Goodman diagrams are determined. Two design applications are presented which illustrate the direct useability and value of the distributional failure governing strength and cycles-to-failure data in designing for specified levels of reliability and in predicting the reliability of given designs.

Kececioglu, D.↗

NASA NTRS1984

Crewstation design and validation

The central problem in crewstation design, that of optimizing the exchange of information between the human and machine components of a system is addressed. The CAR, CUBITS, GROUP, ABBREV, VRAS, and HOS programs, products of the Navy's Human Factors Engineering Technology Development program are all discussed. They are representative to the type of technology which was previously indicated as necessary to move crewstation design and validation to a higher lever of maturity, one which takes cognizance of the multivariate nature of the problems faced by the crewstation designer and has a far less dependence of the whims of personal or subjective opinion.

Wherry, R. J., Jr.↗

NASA NTRS1989

Effect of grinding on the fatigue life of titanium alloy (5 Al-2.5 Sn) under dry and wet conditions

The principal factors in the performance of aerospace materials are strength-to-weight ratio, fatigue life, fracture toughness, survivability and, of course, reliability. Machining processes and, in particular, grinding under adverse conditions have been found to cause damage to surface integrity and affect the residual stress distribution in the surface and subsurface region. These effects have a direct bearing on the fatigue life. In this investigation the effects of grinding conditions on the fatigue life of Titanium 5 Al-2.5Sn were studied. This alloy is used in ground form in the manufacturing of some critical components in the space shuttle's main engine. It is essential that materials for such applications be properly characterized for use in severe service conditions. Flat sub-size specimens 0.1 inch thick were ground on a surface grinding machine equipped with a variable speed motor at speeds of 2000 to 6000 rpm using SiC wheels of grit sizes 60 and 120. The grinding parameters used in this investigation were chosen from a separate study. The ground specimens were then fatigued at a selected stress and the resulting lives were compared with that of the virgin material. The surfaces of the specimens were examined under a scanning electron microscope, and the roughness and hardness were measured using a standard profilometer and microhardness tester, respectively. The fatigue life of the ground specimens was found to decrease with the increase in speed for both dry and wet conditions. The fatigue life of specimens ground under wet conditions showed a significant increase at the wheel speed of 2000 rpm for both the grit sizes and thereafter decreased with increase profilometry, microhardness measurements and scanning electron microscopic examination.

Rangaswamy, Partha↗

NASA NTRS1991

Mark 4A antenna control system data handling architecture study

A high-level review was conducted to provide an analysis of the existing architecture used to handle data and implement control algorithms for NASA's Deep Space Network (DSN) antennas and to make system-level recommendations for improving this architecture so that the DSN antennas can support the ever-tightening requirements of the next decade and beyond. It was found that the existing system is seriously overloaded, with processor utilization approaching 100 percent. A number of factors contribute to this overloading, including dated hardware, inefficient software, and a message-passing strategy that depends on serial connections between machines. At the same time, the system has shortcomings and idiosyncrasies that require extensive human intervention. A custom operating system kernel and an obscure programming language exacerbate the problems and should be modernized. A new architecture is presented that addresses these and other issues. Key features of the new architecture include a simplified message passing hierarchy that utilizes a high-speed local area network, redesign of particular processing function algorithms, consolidation of functions, and implementation of the architecture in modern hardware and software using mainstream computer languages and operating systems. The system would also allow incremental hardware improvements as better and faster hardware for such systems becomes available, and costs could potentially be low enough that redundancy would be provided economically. Such a system could support DSN requirements for the foreseeable future, though thorough consideration must be given to hard computational requirements, porting existing software functionality to the new system, and issues of fault tolerance and recovery.

Briggs, H. C.↗

NASA NTRS1940

Experiments on Ball and Roller Bearings Under Conditions of High Speed and Small Oil Supply

This report describes a testing machine on which 35 millimeter bearings (bore) can be run at speeds of the order of 21,000 rpm, while the following factors are recorded: 1) oil circulation through bearing and oil temperature. 2) maximum temperature of outer bearing ring, 3) radial and axial load on bearing, 4) radial, axial, and angular clearance of bearing, 5) power consumption of bearing. The experiments show that the lubrication was most reliable and oil consumption lowest when the oil was introduced through a hole in the outer or inner ring of the bearing.

Getzlaff, Gunter↗

NASA NTRS1998

Exploring the Unknown: Selected Documents in the History of the US Civilian Space Program: Using Space - Volume 3

One of the most important developments of the twentieth century has been the movement of humanity into space with machines and people. The underpinnings of that movement -why it took the shape it did; which individuals and organizations were involved; what factors drove a particular choice of scientific objectives and technologies to be used; and the political, economic, managerial, and international contexts in which the events of the space age unfolded- are all important ingredients of this epoch transition from an earthbound to spacefaring people. This desire to understand the development of spaceflight in the United States sparked this documentary history series. 'Exploring the Unknown' is a multi-volume series containing a selection of key documents in history of the U.S. civil space program. This current volume, Volume III, focusing on the use of space for practical applications, prints 112 key documents on the history of satellite communications, remote sensing of earth, and space as an investment in economic growth, edited for ease of use. Each is introduced by a headnote providing context, bibliographical information, and background information necessary to understanding the document.

Logsdon, John M.↗

NASA NTRS1987

Smart Houses

GWS takes plans for a new home and subjects them to intensive computerized analysis that does 10,000 calculations relative to expected heat loss and heat gain, then provides specifications designed specifically for each structure as to heating, cooling, ventilation and insulation. As construction progresses, GWS inspects the work of the electrical, plumbing and insulation contractors and installs its own Smart House Radiant Barrier. On completion of the home, GWS technicians use a machine that creates a vacuum in the house and enables computer calculation of the air exchanged, a measure of energy efficiency. Key factor is the radiant barrier, borrowed from the Apollo program. This is an adaptation of a highly effective aluminized heat shield as a radiation barrier holding in or keeping out heat, cold air and water vapor.

Source record↗

NASA NTRS2018

Numerical Simulation of AFP Nip Point Temperature Prediction for Complex Geometries

Material placement at the ideal nip point temperature over complex surfaces with uniformity across the width of the compaction rollers results in optimized part properties for Automated Fiber Placement (AFP) processes. However, current AFP systems utilize heat control models and methodologies, based on multiple process parameters such as feed-rate and orientation, that are mostly open-loop. Here, infrared (IR) heater input is calibrated as a function of process parameters during machine qualification. This work presents a numerical simulation to predict arrayed-infrared (AIR) emitter radiation onto a substrate that includes view factor implementation, IR radiative heat flow calculation, energy rate balance, and a transient heat transfer model. The purpose of this numerical model is to predict nip point temperature on complex surfaces, serving as a baseline for a new arrayed-infrared (AIR) thermoset heater to improve AFP process control. It is anticipated that this simulation will accurately control the temperature for high-speed AFP layup of complex geometries. An anticipated result of an AIR heater system is that material calibration and testing will be reduced as temperature is instantaneously monitored and controlled. Therefore, temperature across the roller width will be uniform during placement of complex parts, independent of their geometry.

Xia, Kaishu↗