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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Avionics Configuration Assessment for Flightdeck Interval Management: A Comparison of Avionics and Notification Methods

Flightdeck Interval Management is one of the NextGen operational concepts that FAA is sponsoring to realize requisite National Airspace System (NAS) efficiencies. Interval Management will reduce variability in temporal deviations at a position, and thereby reduce buffers typically applied by controllers - resulting in higher arrival rates, and more efficient operations. Ground software generates a strategic schedule of aircraft pairs. Air Traffic Control (ATC) provides an IM clearance with the IM spacing objective (i.e., the TTF, and at which point to achieve the appropriate spacing from this aircraft) to the IM aircraft. Pilots must dial FIM speeds into the speed window on the Mode Control Panel in a timely manner, and attend to deviations between actual speed and the instantaneous FIM profile speed. Here, the crew is assumed to be operating the aircraft with autothrottles on, with autopilot engaged, and the autoflight system in Vertical Navigation (VNAV) and Lateral Navigation (LNAV); and is responsible for safely flying the aircraft while maintaining situation awareness of their ability to follow FIM speed commands and to achieve the FIM spacing goal. The objective of this study is to examine whether three Notification Methods and four Avionics Conditions affect pilots' performance, ratings on constructs associated with performance (workload, situation awareness), or opinions on acceptability. Three Notification Methods (alternate visual and aural alerts that notified pilots to the onset of a speed target, conformance deviation from the required speed profile, and reminded them if they failed to enter the speed within 10 seconds) were examined. These Notification Methods were: VVV (visuals for all three events), VAV (visuals for all three events, plus an aural for speed conformance deviations), and AAA (visual indications and the same aural to indicate all three of these events). Avionics Conditions were defined by the instrumentation (and location) used to present IM information to crews: (1) Integrated (IM information is embedded in extant PFD (Primary Flight Display), ND (Navigation Display), EICAS (Engine Indicating and Crew Alerting System) displays); (2) EFB_Aft (IM information is only supplied in an EFB and mounted in location similar to that for MITRE's UPS work); (3) EFB_Fore (IM information is only supplied in an EFB which is mounted more forward, under the side window), and (4) EFB_Aft plus use of an AGD (the same IM information is supplied in an EFB and on an AGD, both mounted in locations similar to that in MITRE's UPS work ). Twelve commercial pilot crews flew descent scenarios (VNAV Speed with the mode control panel (MCP) speed window open until flaps extended, then VNAV Path) in a commercial transport flight simulator with realistic visual scene and communications. The results of this study serve three practical aims: (1) contribute to the down-select of avionics configuration for future assessment of the ASTAR spacing algorithm at NASA; (2) provide information useful to the FAA Human Factors Division (ANG-C1)'s mission to identify issues pertinent to flight certification of, and flight standards; (3) identify methodological considerations in support of future FIM human-in-the-loop (HITL) investigations.

Latorella, Kara A.↗
NASA NTRS1999

Time-on-task decrements in "steer clear" performance of patients with sleep apnea and narcolepsy

Loss of attention with time-on-task reflects the increasing instability of the waking state during performance in experimentally induced sleepiness. To determine whether patients with disorders of excessive sleepiness also displayed time-on-task decrements indicative of wake state instability, visual sustained attention performance on "Steer Clear," a computerized simple RT driving simulation task, was compared among 31 patients with untreated sleep apnea, 16 patients with narcolepsy, and 14 healthy control subjects. Vigilance decrement functions were generated by analyzing the number of collisions in each of six four-minute periods of Steer Clear task performance in a mixed-model analysis of variance and linear regression equations. As expected, patients had more Steer Clear collisions than control subjects (p=0.006). However, the inter-subject variability in errors among the narcoleptic patients was four-fold that of the apnea patients, and 100-fold that of the controls volunteers; the variance in errors among untreated apnea patients was 27-times that of controls. The results of transformed collision data revealed main effects for group (p=0.006), time-on-task (p=0.001), and a significant interaction (p=0.022). Control subjects showed no clear evidence of increasing collision errors with time-on-task (adjusted R2=0.22), while apnea patients showed a trend toward vigilance decrement (adjusted R2=0.42, p=0.097), and narcolepsy patients evidenced a robust linear vigilance decrement (adjusted R2=0.87, p=0.004). The association of disorders of excessive somnolence with escalating time-on-task decrements makes it imperative that when assessment of neurobehavioral performance is conducted in patients, it involves task durations and analyses that will evaluate the underlying vulnerability of potentially sleepy patients to decrements over time in tasks that require sustained attention and timely responses, both of which are key components in safe driving performance.

NASA Discipline Space Human Factors↗
DOE OSTI2011

Factors affecting stranding of juvenile salmonids by wakes from ship passage in the Lower Columbia River

The effects of deep-draft vessel traffic in confined riverine channels on shorelines and fish are of widespread concern. In the Pacific Northwest of the United States, wakes and subsequent beach run-up from ships transiting the Lower Columbia River have been observed to strand juvenile salmon and other fish. As part of a before-and-after study to assess stranding effects that may be associated with channel deepening, we measured 19 co-variables from observations of 126 vessel passages at three low-slope beaches and used multiple logistic regression to discern the significant factors influencing the frequency of stranding. Subyearling Chinook salmon were 82% of the fish stranded over all sites and seasons. Given a low-slope beach, stranding frequencies for juvenile salmon were significantly related to river location, salmon density in the shallows, a proxy for ship kinetic energy, tidal height, and two interactions. The beach types selected for our study do not include all the beach types along the Lower Columbia River so that the stranding probabilities described here cannot be extrapolated river-wide. A more sophisticated modeling effort, informed by additional field data, is needed to assess salmon losses by stranding for the entire lower river. Such modeling needs to include river-scale factors such as beach type, berms, proximity to navigation channel, and perhaps, proximity to tributaries that act as sources of out-migrating juvenile salmon. At both river and beach scales, no one factor produces stranding; rather interactions among several conditions produce a stranding event and give stranding its episodic nature.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

A NEW ALGORITHM FOR RADIOISOTOPE IDENTIFICATION OF SHIELDED AND MASKED SNM/RDD MATERIALS

Detection and identification of shielded and masked nuclear materials is crucial to national security, but vast borders and high volumes of traffic impose stringent requirements for practical detection systems. Such tools must be be mobile, and hence low power, provide a low false alarm rate, and be sufficiently robust to be operable by non-technical personnel. Currently fielded systems have not achieved all of these requirements simultaneously. Transport modeling such as that done in GADRAS is able to predict observed spectra to a high degree of fidelity; our research is focusing on a radionuclide identification algorithm that inverts this modeling within the constraints imposed by a handheld device. Key components of this work include incorporation of uncertainty as a function of both the background radiation estimate and the hypothesized sources, dimensionality reduction, and nonnegative matrix factorization. We have partially evaluated performance of our algorithm on a third-party data collection made with two different sodium iodide detection devices. Initial results indicate, with caveats, that our algorithm performs as good as or better than the on-board identification algorithms. The system developed was based on a probabilistic approach with an improved approach to variance modeling relative to past work. This system was chosen based on technical innovation and system performance over algorithms developed at two competing research institutions. One key outcome of this probabilistic approach was the development of an intuitive measure of confidence which was indeed useful enough that a classification algorithm was developed based around alarming on high confidence targets. This paper will present and discuss results of this novel approach to accurately identifying shielded or masked radioisotopes with radiation detection systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1998

Advanced Air Bag Technology Assessment

As a result of the concern for the growing number of air-bag-induced injuries and fatalities, the administrators of the National Highway Traffic Safety Administration (NHTSA) and the National Aeronautics and Space Administration (NASA) agreed to a cooperative effort that "leverages NHTSA's expertise in motor vehicle safety restraint systems and biomechanics with NASAs position as one of the leaders in advanced technology development... to enable the state of air bag safety technology to advance at a faster pace..." They signed a NASA/NHTSA memorandum of understanding for NASA to "evaluate air bag to assess advanced air bag performance, establish the technological potential for improved technology (smart) air bag systems, and identify key expertise and technology within the agency (i.e., NASA) that can potentially contribute significantly to the improved effectiveness of air bags." NASA is committed to contributing to NHTSAs effort to: (1) understand and define critical parameters affecting air bag performance; (2) systematically assess air bag technology state of the art and its future potential; and (3) identify new concepts for air bag systems. The Jet Propulsion Laboratory (JPL) was selected by NASA to respond to the memorandum of understanding by conducting an advanced air bag technology assessment. JPL analyzed the nature of the need for occupant restraint, how air bags operate alone and with safety belts to provide restraint, and the potential hazards introduced by the technology. This analysis yielded a set of critical parameters for restraint systems. The researchers examined data on the performance of current air bag technology, and searched for and assessed how new technologies could reduce the hazards introduced by air bags while providing the restraint protection that is their primary purpose. The critical parameters which were derived are: (1) the crash severity; (2) the use of seat belts; (3) the physical characteristics of the occupants; (4) the proximity of the occupants to the airbag module; (5) the deployment time, which includes the time to sense the need for deployment, the inflator response parameters, the air bag response, and the reliability of the air bag. The requirements for an advanced air bag technology is discussed. These requirements includes that the system use information related to: (1) the crash severity; (2) the status of belt usage; (3) the occupant category; and (4) the proximity to the air bag to adjust air bag deployment. The parameters for the response of the air bag are: (1) deployment time; (2) inflator parameters; and (3) air bag response and reliability. The state of occupant protection advanced technology is reviewed. This review includes: the current safety restraint systems, and advanced technology characteristics. These characteristics are summarized in a table, which has information regarding the technology item, the potential, and an date of expected utilization. The use of technology and expertise at NASA centers is discussed. NASA expertise relating to sensors, computing, simulation, propellants, propulsion, inflatable systems, systems analysis and engineering is considered most useful. Specific NASA technology developments, which were included in the study are: (1) a capacitive detector; (2) stereoscopic vision system; (3) improved crash sensors; (4) the use of the acoustic signature of the crash to determine crash severity; and (5) the use of radar antenna for pre-crash sensing. Information relating to injury risk assessment is included, as is a summary of the areas of the technology which requires further development.

Phen, R. L.↗
NASA NTRSDate not supplied

Machine Learning based Aircraft Performance Model Estimation for Trajectory Prediction

The accurate prediction of aircraft trajectory by ground-based decision support tools is a critical component of air traffic management in the US National Airspace System (NAS). Accurate predictions of where the aircraft will be in the future or when they will arrive at specific locations (e.g., fixes) is a key enabler for sequencing and efficient arrival management of flights. Traditional physics based aircraft trajectory prediction relies on a simplified point-mass total energy model whose parameters are referred to as Aircraft Performance Model (APM) parameters. Even though the performance coefficients and weight of an aircraft are a vital part of the aircraft performance model’s predictions and accuracy, these coefficients are proprietary in nature and therefore, unavailable to decision-support tools. Current approaches freeze some coefficients to default base of aircraft data (BADA) values and optimize others. However, the APM parameters are highly coupled by the flight dynamics and prioritizing one parameter over others leads to bias and skewed predictions. To alleviate this problem, we provide a combined optimization framework to predict all the critical (thrust, drag and weight) APM parameters. This paper is focused on training Machine Learning (ML) models that map historical flights to optimized APM parameters that provide the best fit (in terms of prediction error). Our dataset obtained from NASA’s Sherlock data warehouse is comprised of thousands of historical flights and includes weather and track data collected from 2019. Using different subsets of relevant features (e.g., aircraft type), we trained several ML models to estimate the aircraft’s take off weight, drag polar coefficients (both parasitic and lift induced), and thrust settings (multiplier applied to the maximum engine thrust). The chosen flights are from three of the most common aircraft types (B738, B737, and A320) arriving at four airports (LAX, DEN, MSP, and DFW). Our ML approach is comprised of two different solutions: 1- using a subset of features that are known prior to the flight departure and do not change during flight (such as engine type, current temperature at departure & destination airports, aircraft type) and 2 - using a subset of temporal features of the flight trajectory (such as cruise altitude, Mach, airspeed, and rate of climb) in addition to the pre-departure features from the first solution. The labels or target variables are the APM parameters that were obtained by an optimized ordinary differential equations (ODE) fitting process (applied to individual flights). The ODE-fitting is very time intensive and is therefore performed offline. Thus, training an ML model to learn the relationship between the flight features and ODE-generated labels enables faster estimation of the APM parameters and is therefore amenable to real-time prediction. Various ML models including linear regression, random forest, XGBoost, and neural network were trained, and the results are compared. After model validation and hyperparameter-tuning, we observed that the Random Forest model outperformed the other three models by the overall mean square error (MSE) of 2% for the first solution and 1.5% for the second solution. Finally, the ML-derived parameters are compared against default BADA APM parameters using NASA’s Autonomy Development toolkit (ADK) simulation software. The simulation results for one of each aircraft type is shown and discussed.

Aida Sharif Rohani↗
NASA NTRS2000

Antennas Designed for Advanced Communications for Air Traffic Management (AC/ATM) Project

The goal of the Advanced Communications for Air Traffic Management (AC/ATM) Project at the NASA Glenn Research Center at Lewis Field is to enable a communications infrastructure that provides the capacity, efficiency, and flexibility necessary to realize a mature free-flight environment. The technical thrust of the AC/ATM Project is targeted at the design, development, integration, test, and demonstration of enabling technologies for global broadband aeronautical communications. Since Ku-band facilities and equipment are readily available, one of the near-term demonstrations involves a link through a Kuband communications satellite. Two conformally mounted antennas will support the initial AC/ATM communications links. Both of these are steered electronically through monolithic microwave integrated circuit (MMIC) amplifiers and phase shifters. This link will be asymmetrical with the downlink to the aircraft (mobile vehicle) at a throughput rate of greater than 1.5 megabits per second (Mbps), whereas the throughput rate of the uplink from the aircraft will be greater than 100 kilobits per second (kbps). The data on the downlink can be narrow-band, wide-band, or a combination of both, depending on the requirements of the experiment. The AC/ATM project is purchasing a phased-array Ku-band transmitting antenna for the uplink from the test vehicle. Many Ku-band receiving antennas have been built, and one will be borrowed for a short time to perform the initial experiments at the NASA Glenn Research Center at Lewis Field. The Ku-band transmitting antenna is a 254-element MMIC phased-array antenna being built by Boeing Phantom Works. Each element can radiate 100 mW. The antenna is approximately 43-cm high by 24-cm wide by 3.3-cm thick. It can be steered beyond 60 from broadside. The beamwidth varies from 6 at broadside to 12 degrees at 60 degrees, which is typical of phased-array antennas. When the antenna is steered to 60 degrees, the beamwidth will illuminate approximately five satellites on the orbital arc. Spread spectrum techniques will be employed to keep the power impinging on the adjacent satellites below their noise floor so that no interference results. This antenna is power limited. If the antenna elements (currently 254) are increased by a factor of 4 (1024) or 16 (4096), the gain will increase and the beamwidth will decrease in proportion. For the latter two antenna sizes, the power must be "backed off" to prevent interference with the neighboring satellites. The receiving antenna, which is approximately 90-cm high, 60-cm wide, and 3.5-cm thick, is composed of 1500 phased-array elements. The system phased-array controller can control both a 1500-element receiving antenna and a 500-element transmitting antenna. For ground testing, this controller will allow manual beam pointing and polarization alignment. For normal operation, the system can be connected to the receiving antenna and the navigation system for real-time autonomous track operation. This will be accomplished by first pointing both antennas at the satellite using information from the aircraft data bus. Then, the system phased-array controller will electronically adjust the antenna pointing of the receiving antenna to find the peak signal. After the peak signal has been found, the beam of the transmitting antenna will be pointed to the same steering angles as the receiving antenna. For initial ground testing without an aircraft, the ARINC 429 data bus (ARINC Inc., Annapolis, Maryland) will be simulated by a gyro system purchased for the follow-on to the Monolithic Microwave Integrated Circuit (MMIC) Arrays for Satellite Communication on the Move (MASCOM) Project. MASCOM utilized the Advanced Communications Technology Satellite (ACTS) with a pair of Ka-band experimental phased-array antennas.

Zakrajsek, Robert J.↗