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NASA NTRS2010

Integrated Analysis of Airport Capacity and Environmental Constraints

LMI conducted an integrated analysis of airport capacity and environmental constraints. identifying and ranking the key factors limiting achievement of NextGen capacity goals. The primary metric used was projected throughput, which was estimated for the years 2015 and 2025 based on the unconstrained demand forecast from the Federal Aviation Administration, and planned improvements including those proposed in the NextGen plan. A set of 310 critical airports was identified.. collectively accounting for more than 99 percent of domestic air traffic volume; a one-off analytical approach was used to isolate the constraint being assessed. The study considered three capacity constraints (runway.. taxiway, and gate) and three environmental constraints (fuel, NO(x) emissions, and noise). For the ten busiest airports, runway and noise are the primary and secondary constraints in both 2015 and 2025. For the OEP 35 airports and overall for the remaining airports, the most binding constraint is noise. Six of the 10 busiest airports, will face runway constraints in 2025, and 95 will face gate constraints. Nearly every airport will be subject to constraints due to emissions and NOx. Runway and taxi constraints are more concentrated in the large airports: environmental constraints are present at almost every airport regardless of size.

Hasan, Shahab↗

NASA NTRS1979

The 30/20 GHz fixed communications systems service demand assessment. Volume 1: Executive summary

Demand for telecommunications services is forecasted for the period 1980-2000, with particular reference to that portion of the demand associated with satellite communications. Overall demand for telecommunications is predicted to increase by a factor of five over the period studied and the satellite portion of demand will increase even more rapidly. Traffic demand is separately estimated for voice, video, and data services and is also described as a function of distance traveled and city size. The satellite component of projected demand is compared with the capacity available in the C and Ku satellite bands and it is projected that new satellite technology and the implementation of Ka band transmission will be needed in the decade of the 1990's.

Gamble, R. B.↗

NASA NTRS2017

Analysis of Convective Weather Impact on Pre-Departure Routing of Flights from Fort Worth Center to New York Center

In response to severe weather conditions, Traffic Managers specify flow constraints and reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options and associated airspace capacities would assist Traffic Managers in making more efficient decisions in response to convective weather. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. This paper describes the initial steps and methodology used towards this goal. The focus of this work is flights departing from Fort Worth Center destined for New York Center. Dominant routing structures used in the absence of convective weather are identified. A method to extract relevant features from the large volume of weather data available to quantify the impact of convective weather on this routing structure over a given time range is presented. Finally, a method of estimating flow rate capacity along commonly used routes during convective weather events is described. Results show that the flow rates drop exponentially as a function of the values of the proposed feature and that convective weather on the final third of the route was found to have a greater impact on the flow rate restriction than other portions of the route.

traffic flow management↗

NASA NTRS2008

The NPOESS Preparatory Project (NPP) Science Data Segment (SDS) Data Depository and Distribution Element (SD3E) System Architecture

The National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government's future low-Earth orbiting satellite system, will monitor global weather and environmental conditions. Serving as a risk reduction for NPOESS, the NPOESS Preparatory Project (NPP) will provide remotely sensed atmospheric, land, ocean, ozone, and sounder data that will serve the meteorological and global climate change scientific communities. The National Aeronautics and Space Administration (NASA) NPP Science Data Segment's (SDS) primary role is to independently assess the quality of the NPP science and environmental data records for their ability to support climate research. The SDS is composed of nine elements; an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. Each element requires a set of sensor specific science data products for their evaluation. There are four NPP sensors that will be flown on the NPP observatory. They are the Visible Infrared Imagining Radiometer Suite (VIIRS), the Advanced Technology Microwave Sounder (ATMS), the Cross-Track Infrared Sounder (CrIS), and the Ozone Mapper/Profiler Suite (OMPS). It is estimated that these four sensors combined will make daily data requests for approximately six terabytes of NPP science products from the operational data providers. As a result, issues associated with duplicate data requests, data transfers of large volumes of diverse products, and data transfer failures raised concerns with respect to the network traffic and bandwidth consumption. Therefore, a central data broker system for receiving and buffering data requests and data products for the SDS was developed. The data element for this system is called the SDS Data Depository and Distribution Element (SD3E). It supports science mission data assessment by assuring the timely and validated acquisition and subsequent transfer of the NPP Science Mission data to the SDS Elements and NPP Science Team. The six science elements that interface with the SD3E span across the NASA Goddard Space Flight Center (GSFC), the NASA Jet Propulsion Laboratory (JPL), and the University of Wisconsin. As the primary communication vehicle for the science elements and science team, the SD3E has an interface to the operational data providers: National Environment Satellite, Data, and Information Service (NESDIS) Interface Data Processing System (IDPS) and the National Oceanic Atmospheric Administration's (NOAA) Comprehensive Large Array-data Stewardship system (CLASS) Archive Data System (ADS), that are responsible for product generation and archive and distribution respectively. The SD3E is designed to be a semi-customizable and semi-automated system. This system is designed to provide flexibility and ease of use for the science users in accessing the latest data products by creating a rolling data cache that temporarily stores the products locally before transferring the data to the SDS Measurement based elements for the land, ocean, atmosphere, sounder, and ozone. This paper describes the design and architecture of one of the nine SDS elements, the SD3E, and how this system has provided a mechanism for efficient data exchange, how it has helped in alleviating some of the network traffic and usage, and how it has contributed to reducing operational costs.

Ho, Evelyn L.↗

NASA NTRS2003

Frequency Reuse, Cell Separation, and Capacity Analysis of VHF Digital Link Mode 3 TDMA

The most recent studies by the Federal Aviation Administration (FAA) and the aviation industry have indicated that it has become increasingly difficult to make new VHF frequency or channel assignments to meet the aviation needs for air-ground communications. FAA has planned for several aggressive improvement measures to the existing systems, but these measures would not meet the projected voice communications needs beyond 2009. FAA found that since 1974 there has been, on the average, a 4 percent annual increase in the number of channel assignments needed to satisfy the air-ground communication traffic (approximately 300 new channel assignments per year). With the planned improvement measures, the channel assignments are expected to reach a maximum number of 16615 channels by about 2010. Hence, the FAA proposed the use of VDL Mode 3 as a new integrated digital voice and data communications systems to meet the future air traffic demand. This paper presents analytical results of frequency reuse; cell separation and capacity estimation of VDL Mode 3 TDMA systems that FAA has planned to implement the future VHF air-ground communications system by the year 2010. For TDMA, it is well understood that the frequency reuse factor is a crucial parameter for capacity estimation. Formulation of this frequency reuse factor is shown, taking into account the limitation imposed by the requirement to have a sufficient Signal to Co-Channel Interference Ratio. Several different values for the Signal to Co-Channel Interference Ratio were utilized corresponding to the current analog VHF DSB-AM systems, and the future digital VDL Mode 3. The required separation of Co-Channel cells is computed for most of the Frequency Protected Service Volumes (FPSV's) currently in use by the FAA. Additionally, the ideal cell capacity for each FPSV is presented. Also, using actual traffic for the Detroit air space, a FPSV traffic distribution model is used to generate a typical cell for channel capacity prediction. Such prediction is useful for evaluating the improvement of future VDL Mode 3 deployment and capacity planning.

Shamma, Mohammed A.↗

NASA NTRS1979

A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development, volume 1

A cross impact model of the U.S. telecommunications system was developed. It was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impact). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics throughout the telecommunications system.

Martino, J. P.↗

NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. It affects the efficiency of the National Airspace System (NAS) and both surface and airspace operations can benefit from better understanding future runway configurations. In this paper, we present a comprehensive implementation of predictive models for runway configuration estimation from large volumes of historical data. Specifically, operational data from two full years (2018 and 2019) is collected, analyzed, and fused together to build the data product used in this work. The data set differs from prior work in the field in terms of its scope, resolution, and variety of factors collected and considered. Meteorological data is collected from two different sources – current weather conditions from METAR (Meteorological Terminal Aviation Routine Weather Report) and forecast weather conditions from Localized Aviation MOS Program (LAMP). Operational data from the Federal Aviation Administration (FAA) Aviation System Performance Metrics (ASPM) related to scheduled and actual number of arrivals and departures, average taxi times, etc. are collected. NASA’s Sherlock Data Warehouse is used to identify critical information such as go-arounds, and other events that might impact RCM decision-making. All data is collected and aggregated over 15-minute intervals throughout the two years. This provides a resolution like the timescales that might be necessary for runway configuration management decision-making. A variety of supervised learning algorithms are tested including Support Vector Machine, Random Forest, Gradient Boosting, etc. including tuning of the model hyperparameters. The modeling process is applied and presented on two representative U.S. airports – Charlotte Douglas International Airport (KCLT) and Denver International Airport (KDEN). The two airports present different levels of complexity in terms of the total number of configurations used and provide a balanced perspective on the generalizability of the developed approach to other airports in the NAS. Initial results are promising (F1 score of 0.91 at KCLT and 0.83 at KDEN) for data in the test set. The final paper will contain a comprehensive comparison between different models and model building strategies as well as further refined results. Most important predictors for each airport will be identified along with a discussion and recommendations on adapting the framework to other scenarios.

Tejas G Puranik↗

NASA NTRS1983

Customer premises services market demand assessment 1980 - 2000. Volume 1: Executive summary

Estimates of market demand for domestic civilian telecommunications services for the years 1980 to 2000 are provided. Overall demand, demand or satellite services, demand for satellite delivered Customer Premises Service (CPS), and demand for 30/20 GHz Customer Premises Services are covered. Emphasis is placed on the CPS market and demand is segmented by market, by service, by user class and by geographic region. Prices for competing services are discussed and the distribution of traffic with respect to distance is estimated. A nationwide traffic distribution model for CPS in terms of demand for CPS traffic and earth stations for each of the major SMSAs in the United States are provided.

Gamble, R. B.↗

NASA NTRS1984

Advance Technology Satellites in the Commercial Environment. Volume 2: Final Report

A forecast of transponder requirements was obtained. Certain assumptions about system configurations are implicit in this process. The factors included are interpolation of baseline year values to produce yearly figures, estimation of satellite capture, effects of peak-hours and the time-zone staggering of peak hours, circuit requirements for acceptable grade of service capacity of satellite transponders, including various compression methods where applicable, and requirements for spare transponders in orbit. The graphical distribution of traffic requirements was estimated.

Source record↗

DOE OSTI2021

A Review and Outlook on Energy Consumption Estimation Models for Electric Vehicles

Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can accurately and reliably estimate electricity consumption. This paper reviews the state-of-the-art of EV energy consumption models, aiming to provide guidance for future development of EV applications. Here, we summarize influential variables of EV energy consumption into four categories: vehicle component, vehicle dynamics, traffic and environment related factors. We classify and discuss EV energy consumption models in terms of modeling scale (microscopic vs. macroscopic) and methodology (data-driven vs. rule-based). Our review shows trends of increasing macroscopic models that can be used to estimate trip-level EV energy consumption and increasing data-driven models that utilized machine learning technologies to estimate EV energy consumption based on large volume real-world data. We identify research gaps for EV energy consumption models, including the development of energy estimation models for modes other than personal vehicles (e.g., electric buses, electric trucks, and electric non-road vehicles); the development of energy estimation models that are suitable for applications related to vehicle-to-grid integration; and the development of multi-scale energy estimation models as a holistic modeling approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

AIS-based characterization of navigation conflicts along the US Atlantic Coast prior to development of wind energy

This study characterizes navigation conflicts in a region with a large traffic volume along the US Atlantic Coast, utilizing Automated Identification System (AIS) data for 2010. The region includes areas proposed for wind energy development. The characterization could be useful in evaluating the effect of offshore wind areas on navigation conflicts. The study processes the AIS data to provide pairwise comparisons of vessel interactions (encounters and near-misses) as they occurred. Using the vessel encounter data, analyses are made using a ‘blind’ vessel assumption to evaluate the potential for both near-misses and collisions. Then statistical analyses are made to estimate the point values and uncertainty for each type of encounter (crossing, head-on, overtaking). Examination of the frequency/number of collisions from actual observations is made. The examination of actual near-misses, potential near-misses, and potential collisions provides comparable results in the number of near-misses and collisions. The potential near-miss analyses include an examination of the timing of responses made by vessels to prevent near-misses. This informed the statistical analysis but may also have utility in the simulation of navigation conflicts.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1991

Microwave landing system modeling with application to air traffic control

Compared to the current instrument landing system, the microwave landing system (MLS), which is in the advanced stage of implementation, can potentially provide significant fuel and time savings as well as more flexibility in approach and landing functions. However, the expanded coverage and increased accuracy requirements of the MLS make it more susceptible to the features of the site in which it is located. An analytical approach is presented for evaluating the multipath effects of scatterers that are commonly found in airport environments. The approach combines a multiplane model with a ray-tracing technique and a formulation for estimating the electromagnetic fields caused by the antenna array in the presence of scatterers. The model is applied to several airport scenarios. The reduced computational burden enables the scattering effects on MLS position information to be evaluated in near real time. Evaluation in near real time would permit the incorporation of the modeling scheme into air traffic control automation; it would adaptively delineate zones of reduced accuracy within the MLS coverage volume, and help establish safe approach and takeoff trajectories in the presence of uneven terrain and other scatterers.

Poulose, M. M.↗

NASA NTRS1992

Microwave landing system modeling with application to air traffic control automation

Poulose, M. M.↗

NASA NTRS2012

Satellite-based Estimates of Ambient Air Pollution and Global Variations in Childhood Asthma Prevalence

Background: The effect of ambient air pollution on global variations and trends in asthma prevalence is unclear. Objectives: Our goal was to investigate community-level associations between asthma prevalence data from the International Study of Asthma and Allergies in Childhood (ISAAC) and satellite-based estimates of particulate matter with aerodynamic diameter < 2.5 microm (PM2.5) and nitrogen dioxide (NO2), and modelled estimates of ozone. Methods: We assigned satellite-based estimates of PM2.5 and NO2 at a spatial resolution of 0.1deg × 0.1deg and modeled estimates of ozone at a resolution of 1deg × 1deg to 183 ISAAC centers. We used center-level prevalence of severe asthma as the outcome and multilevel models to adjust for gross national income (GNI) and center- and country-level sex, climate, and population density. We examined associations (adjusting for GNI) between air pollution and asthma prevalence over time in centers with data from ISAAC Phase One (mid-1900s) and Phase Three (2001-2003). Results: For the 13- to 14-year age group (128 centers in 28 countries), the estimated average within-country change in center-level asthma prevalence per 100 children per 10% increase in center-level PM2.5 and NO2 was -0.043 [95% confidence interval (CI): -0.139, 0.053] and 0.017 (95% CI: -0.030, 0.064) respectively. For ozone the estimated change in prevalence per parts per billion by volume was -0.116 (95% CI: -0.234, 0.001). Equivalent results for the 6- to 7-year age group (83 centers in 20 countries), though slightly different, were not significantly positive. For the 13- to 14-year age group, change in center-level asthma prevalence over time per 100 children per 10% increase in PM2.5 from Phase One to Phase Three was -0.139 (95% CI: -0.347, 0.068). The corresponding association with ozone (per ppbV) was -0.171 (95% CI: -0.275, -0.067). Conclusion: In contrast to reports from within-community studies of individuals exposed to traffic pollution, we did not find evidence of a positive association between ambient air pollution and asthma prevalence as measured at the community level.

Air pollution↗

NASA NTRS1983

Mobile radio alternative systems study. Volume 1: Traffic model

The markets for mobile radio services in non-urban areas of the United States are examined for the years 1985-2000. Three market categories are identified. New Services are defined as those for which there are different expressed ideas but which are not now met by any application of available technology. The complete fulfillment of the needs requires nationwide radio access to vehicles without knowledge of vehicle location, wideband data transmission from remote sites, one- and two way exchange of short data and control messages between vehicles and dispatch or control centers, and automatic vehicle location (surveillance). The commercial and public services market of interest to the study is drawn from existing users of mobile radio in non-urban areas who are dissatisfied with the geographical range or coverage of their systems. The mobile radio telephone market comprises potential users who require access to the public switched telephone network in areas that are not likely to be served by the traditional growth patterns of terrestrial mobile telephone services. Conservative, likely, and optimistic estimates of the markets are presented in terms of numbers of vehicles that will be served and the radio traffic they will generate.

Tucker, W. T.↗

NASA NTRS1978

An analysis of long and medium-haul air passenger demand, volume 1

A basic model was developed which is a two equation pair econometric system in which air passenger demand and airline level-of-service are the endogenous variables. The model aims to identify the relationship between each of these two variables and its determining factors, and to identify the interaction of demand and level-of-service with each other. The selected variable for the measure of air passenger traffic activity in a given pair market is defined as the number of passengers in a given time that originate in one region and fly to the other region for purposes other than to make a connection to a third region. For medium and long haul markets, the model seems to perform better for larger markets. This is due to a specification problem regarding the route structure variable. In larger markets, a greater percentage of nonlocal passengers are accounted for by this variable. Comparing the estimated fare elasticities of long and medium haul markets, it appears that air transportation demand is more price elastic in longer haul markets. Long haul markets demand will saturate with a fewer number of departures than will demand in medium haul markets.

Eriksen, S. E.↗

NASA NTRS1981

Automatic helical rotorcraft descent and landing using a Microwave Landing System

A helical-approach concept is presented for Instrument Flight Rules (IFR) operation of rotorcraft into congested terminal areas where separation from high-speed jet traffic is highly desirable and the airport-precision-approach aid is a Microwave Landing System (MLS). The concept takes advantage of the fact that rotorcraft need not land on the main runway but can operate from a pad that lies on an MLS radial offset from the centerline. The results of 48 flights using a UH-1H helicopter and a research avionics system are presented. Three levels of navigation sophistication were also investigated. It is shown that an approach helix can be contained in a relatively small volume and that being within the Instrument Landing System (ILS) Category II window at a 30-m (100-ft) altitude is not a requirement for a successful hover over a landing pad. Only two of the three navigation systems provided estimates that allowed all flights to descend from hover to touchdown.

Mcgee, L. A.↗

NASA NTRS2019

Human Performance Contributions to Safety in Commercial Aviation

Every day in aviation, pilots, air traffic controllers, and other front-line personnel perform countless correct judgments and actions in a variety of operational environments. These judgments and actions are often the difference between an accident and a non-event. Ironically, data on these behaviors are rarely collected or analyzed. Data-driven decisions about safety management and design of safety-critical systems are limited by the available data, which influence how decision makers characterize problems and identify solutions. Large volumes of data are collected on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that result in routine successful outcomes, safety management and system design decisions are based on a small sample of nonrepresentative safety data. This assessment aimed to find and document “safety successes” made possible by human operators. With many Aeronautics Research Mission Directorate (ARMD) Programs and Projects focusing on increased automation and autonomy and decreased human involvement, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant risk — a risk that has not been recognized to date. Without understanding how humans contribute to safety, any estimate of predicted safety of autonomous capabilities is incomplete and inherently suspect. Furthermore, understanding the ways in which humans contribute to safety can promote strategic interactions among safety technologies, functions, procedures and the people using them. Without this understanding, the full benefits of an integrated, optimized human/technology or autonomous system will not be realized. Historically, safety has been consistently defined in terms of the occurrence of accidents or recognized risks (i.e., in terms of things that go wrong). These adverse outcomes are explained by identifying their causes, and safety is restored by eliminating or mitigating these causes. An alternative to this approach is to focus on what goes right and identify how to replicate that process. Focusing on the rare cases of failures attributed to “human error” provides little information about why human performance routinely prevents adverse events. Hollnagel has proposed that things go right because people continuously adjust their work to match their operating conditions. These adjustments become increasingly important as systems continue to grow in complexity. Thus, the definition of safety should reflect not only “avoiding things that go wrong” but “ensuring that things go right.” The basis for safety management requires developing an understanding of everyday activities. However, few mechanisms to monitor everyday work exist in the aviation domain, which limits opportunities to learn how designs function in reality. This concept of safety thinking and safety management is reflected in the emerging field of resilience engineering. According to Hollnagel, a system is resilient if it can sustain required operations under expected and unexpected conditions by adjusting its functioning prior to, during, or following changes, disturbances, and opportunities. To explore “positive” behaviors that contribute to resilient performance in commercial aviation, the assessment team examined a range of existing sources of data about pilot and air traffic control (ATC) tower controller performance, including subjective interviews with domain experts and objective aircraft flight data records. These data were used to identify strategies that support resilient performance, methods for exploring and refining those strategies in existing data, and proposed methods for capturing and analyzing new data.

Null, Cynthia H.↗