Research approaches to alleviation of airport community noise.
Research approaches to alleviation of airport community noise
NOISE ATTENUATION↗
SEARCH · Engineering Papers
Results for “Airport”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
NextGen-Airportal Project Technologies: Systems Analysis, Integration, and Evaluation (SAIE)
NASA has been conducting Concept & Technology (C&T) research to enable capacity, efficiency, and safety improvements under the Airspace Systems Program, Aeronautics Research Mission Directorate (ARMD). These C&Ts provide various benefits (e.g., improved airport departure/arrival throughputs, fuel saving, and taxi efficiency) with costs and benefits apportioned among various Air Traffic Management (ATM) system stakeholders (e.g., FAA, aircraft operators, or public).
SAIE↗
SARDA: An Integrated Concept for Airport Surface Operations Management
The Spot and Runway Departure Advisor (SARDA) is an integrated decision support tool for airlines and air traffic control tower enabling surface collaborative decision making (CDM) and departure metering in order to enhance efficiency of surface operations at congested airports. The presentation describes the concept and architecture of the SARDA as a CDM tool, and the results from a human-in-the-loop simulation of the tool conducted in 2012 at the FutureFlight Central, the tower simulation facility. Also, presented is the current activities and future plan for SARDA development. The presentation was given at the meeting with the FAA senior advisor of the Surface Operations Office.
surface collaborative decision making↗
Effects of Airport Tower Controller Decision Support Tool on Controllers Head-Up Time
Despite that aircraft positions and movements can be easily monitored on the radar displays at major airports nowadays, it is still important for the air traffic control tower (ATCT) controllers to look outside the window as much as possible to assure safe operations of traffic management. The present paper investigates whether an introduction of the NASA's proposed Spot and Runway Departure Advisor (SARDA), a decision support tool for the ATCT controller, would increase or decrease the controllers' head-up time. SARDA provides the controller departure-release schedule advisories, i.e., when to release each departure aircraft in order to minimize individual aircraft's fuel consumption on taxiways and simultaneously maximize the overall runway throughput. The SARDA advisories were presented on electronic flight strips (EFS). To investigate effects on the head-up time, a human-in-the-loop simulation experiment with two retired ATCT controller participants was conducted in a high-fidelity ATCT cab simulator with 360-degree computer-generated out-the-window view. Each controller participant wore a wearable video camera on a side of their head with the camera facing forward. The video data were later used to calculate their line of sight at each moment and eventually identify their head-up times. Four sessions were run with the SARDA advisories, and four sessions were run without (baseline). Traffic-load levels were varied in each session. The same set of user interface - EFS and the radar displays - were used in both the advisory and baseline sessions to make them directly comparable. The paper reports the findings and discusses their implications.
airport surface operations↗
Identification of Safety Metrics for Airport Surface Operations
A large fraction of safety incidents occurs on the ground during airport surface operations. Although these incidents are mostly non-fatal with a few exceptions, they are high profile incidents that remain a source of concern for the National Transportation Safety Board (NTSB), the Federal Aviation Administration (FAA), major airlines, and other stakeholders of the National Airspace System (NAS). These incidents have historically been mitigated by implementing changes to regulations, policies, and procedures over time. This approach has minimized but not eliminated the risk of occurrences. It is thus important to develop integrated techniques to assess, model, and prevent these incidents by analyzing the risk and likelihood of occurrence and communicating results of the analysis to decision-making personnel who can mitigate and prevent incidents in real time. The research presented in this report builds on prior work of researchers at the NASA Ames Research Center who developed an automated framework, Real-Time Safety Monitoring (RTSM), to enable monitoring and prediction of the safety of the NAS. In the RTSM framework, hazards to flight are translated to safety metrics such as wake vortex encounters or loss of separation, that can be modeled and analyzed offline and also predicted and monitored in real time (online). The intent of this report is to integrate predictable incidents that occur during surface and ground operations into the safety portfolio of the RTSM project by (i) identifying suitable information sources from which ground incidents can be studied, (ii) developing safety metrics correlated with surface operations, and (iii) recommending suitable data sources that can be quantified and used for the computation of pertinent safety metrics.
ground operations↗
Impact of Data Exchange Provided by ATD2 Tools at Charlotte-Douglas International Airport
Data Exchange and Integration is necessary for progress towards an Integrated Arrival, Departure, and Surface (IADS) traffic management capability. In collaboration with the FAA, NASA has introduced new data exchange elements to Charlotte-Douglas International Airport air traffic facilities, including the American Airlines ramp, as part of the Airspace Technology Demonstration 2 (ATD2). This paper describes the new tools that deliver these elements, and the human factors impact of the tools as measured by post-bank surveys. Workload was unaffected by ATD2 tool use, and situational awareness was improved in the Tower and with Ramp controllers in the second round of surveys. Respondents described their tools as more helpful if they included ATD2 tools 1) in the Tower for insuring compliance for aircraft under a Traffic Management Initiative, 2) in the TRACON when actively used for many TRACON tasks, and 3) in the Ramp in the second round of surveys.
and surface traffic management; human factors asse↗
Identification of Safety Metrics for Airport Surface Operations
A large fraction of safety incidents occurs on the ground during airport surface operations. Although these incidents are mostly non-fatal with a few exceptions, they are high profile incidents that remain a source of concern for the National Transportation Safety Board (NTSB), the Federal Aviation Administration (FAA), major airlines, and other stakeholders of the National Airspace System (NAS). These incidents have historically been mitigated by implementing changes to regulations, policies, and procedures over time. This approach has minimized but not eliminated the risk of occurrence of safety incidents. It is thus important to develop integrated techniques to assess, model, and prevent these incidents by analyzing the risk and likelihood of occurrence and communicating results of the analysis to decision-making personnel who can mitigate and prevent incidents in real time. The work presented in this paper builds on a previously developed architecture for safety, Real-Time Safety Monitoring (RTSM), to enable monitoring and prediction of the safety of the NAS. In the RTSM framework, hazards to flight are translated to safety metrics such as wake vortex encounters or loss of separation, that can be modeled and analyzed offline and also predicted and monitored in real time (online). The intent of this paper is to integrate predictable incidents that occur during surface and ground operations into the safety portfolio of the RTSM project by (i) identifying suitable information sources from which ground incidents can be studied, (ii) developing safety metrics correlated with surface operations, and (iii) recommending suitable data sources that can be quantified and used for the computation of pertinent safety metrics.
safety↗
Machine Learning (ML) Airport Surface Model
This presentation was presented to SWS Data Mining and Prediction RTT subgroup on behalf of DMTA ML/AI processes RTT subgroup. The slides presented a review of ML airport surface model and showed validation results at KDFW.
Machine Learning↗
Optimization and Electrification of Airport Shuttle Bus Fleets
Interim results from the Athena project show that Dallas-Fort Worth International Airport could achieve up to 50% energy savings with targeted shuttle bus electrification.
ADVANCED PROPULSION SYSTEMS↗
Airport Traffic Management and Planning Framework
Initial results from the Athena project show that high-performance computing and high-fidelity traffic simulation can help guide airport traffic management decisions and understand operating bottlenecks.
ADVANCED PROPULSION SYSTEMS↗
Airport Surface Transportation Digital Twin Framework
Interim results from the Athena project show that combining demand forecast with a traffic microsimulation framework can help airports navigate operational challenges with increased travel.
ADVANCED PROPULSION SYSTEMS↗
Airport Infrastructure Expansion Under Uncertainty
Multistage stochastic optimization can help transportation hubs like airports and seaports plan for future infrastructure expansion while considering risks from emerging technologies and changes in demand.
ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
Learnings From the 2022 NREL Partner Forum: Research Needs for Airport Ground Infrastructure and Operations
During the 2022 Partner Forum at the National Renewable Energy Laboratory (NREL), stakeholders and experts from across aviation came to the whiteboard to outline common goals, align interests, understand technologies, and discuss steps for safely and seamlessly decarbonizing aviation. Attendees identified challenges, strategies, and needed research on aviation fuels, infrastructure, and aircraft. Initial insights, strategies, and high-level suggestions from an airport ground infrastructure and operations workshop are summarized below, including potential barriers and synergies for achieving bold decarbonization goals.
airport↗
Short–Term Forecasting of Wind Gusts at Airports Across CONUS Using Machine Learning
Short–term forecasting of wind gusts, particularly those of higher intensity, is of great societal importance but is challenging due to the presence of multiple gust generation mechanisms. Wind gust observations from eight high–passenger–volume airports across the continental United States (CONUS) are summarized and used to develop predictive models of wind gust occurrence and magnitude. These short–term (same hour) forecast models are built using multiple logistic and linear regression, as well as artificial neural networks (ANNs) of varying complexity. A suite of 19 upper–air predictors drawn from the ERA5 reanalysis and an autoregressive (AR) term are used. Stepwise procedures instruct predictor selection, and resampling is used to quantify model stability. All models are developed separately for the warm (April–September) and cold (October–March) seasons. Results show that ANNs of 3–5 hidden layers (HLs) generally exhibit higher hit rates than logistic regression models and also improve skill with respect to wind gust magnitudes. However, deeper networks with more HLs increase false alarm rates in occurrence models and mean absolute error in magnitude models due to model overfitting. For model skill, inclusion of the AR term is critical while the majority of the remaining skill derives from wind speeds and lapse rates. A predictive ceiling is also clearly demonstrated, particularly for the strong and damaging gust magnitudes, which appears to be partially due to ERA5 predictor characteristics and the presence of mixed wind climates.
54 ENVIRONMENTAL SCIENCES↗
Study of eVTOL Charging Impact on Airport Electrical Grids
Growth in commercial air traffic has increased the aviation industry's contribution to global emissions. Aircraft electrification can reduce greenhouse gas emissions along with being efficient and reliable. Advanced air mobility introduces the idea of an advanced and more efficient air transportation system. Electric and hybrid aircraft designs, such as electric vertical takeoff and landing (eVTOL), are being considered for a number of applications, such as urban air mobility, cargo delivery, and medical emergencies. Although the electrification of aircraft provides environmental benefits, their charging needs will place significant demand on the electrical grid. This work presents a grid impact study and infrastructure upgrade requirements analysis of eVTOL charging on a realistic distribution grid through power flow simulation analysis. The case study results show that the eVTOL charging can lead to power quality issues, such as undervoltage and equipment capacity overloading. Grid infrastructure, such as lines and transformers, would need to be upgraded, and voltage management strategies would need to be deployed to accommodate eVTOL charging at an existing airport.
advanced air mobility (AAM)↗
Acoustic Observations of the OSIRIS-REx Sample Return Capsule Re-Entry from Wendover Airport
The Origins, Spectral Interpretation, Resource Identification, and Security‐Regolith Explorer sample return capsule (SRC) re‐entered the Earth’s atmosphere at hypersonic speeds from interplanetary space on 24 September 2023. The current work reports on 18 ground‐based acoustic sensors deployed at Wendover Airport, the same location that the Genesis and Stardust SRC re‐entries were recorded. Four different sensors (Chaparral Physics, Gem, Wilson Engineering Research and Development [WERD], and RedVox) were deployed in close proximity to compare their performance. All the sensors captured an N‐wave signal associated with the SRC re‐entry shock wave followed by a broadband coda. The Chaparral Physics array served as the high‐fidelity reference measurement. The N‐wave signal had a peak‐to‐peak amplitude of 4.07 Pa with a fundamental frequency of 4.98 Hz from 167.5° measured clockwise from north, nearly perpendicular to the SRC trajectory. In addition, high coherence in the coda was shown to be associated reflections from the surrounding mountains. In general, the more economical sensors (Gem, WERD, and RedVox) produced results that were consistent with these observations and sensor specifications. Beamforming with these single sensors arranged as an array showed agreement with the high‐fidelity array to within a couple of degrees. Furthermore, the current high‐fidelity results were compared with the measurements during the Genesis and Stardust SRC re‐entries. All three entries produced a broadband fundamental peak at a frequency that was inversely related to the SRC diameter as well as evidence of reflections from the surrounding topography.
KC, Real J. [Oklahoma State University, Stillwater↗
Impacts of Regional Air Mobility and Electrified Aircraft on Local Grid Infrastructure and Airport Electricity Demand
The goal of this work is to analyze the electrical infrastructure that may be necessary to serve electrified aviation at a subset of airports where potential electrified flight demand has been provided. Additionally, this work will estimate the amount of onsite distributed energy resources (i.e., solar photovoltaics and battery energy storage systems) that could be used to serve EA in cost effective scenarios.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Cybersecurity Considerations for Hydrogen Infrastructure in Airport Environments
This report explores key cybersecurity concerns and best practices within environments that serve as reference points for the development of hydrogen fueling infrastructure for aviation. This cybersecurity analysis leverages prior NREL studies: 1) hydrogen fueling station component validation to identify vulnerabilities and failure events documented in physical equipment, and 2) electric aircraft charging infrastructure analysis to explore primary cybersecurity vulnerabilities. It reviews the criticality of digitized technologies in sustaining hydrogen fuel production, storage, and fueling systems, noting cybersecurity concerns that are universal to power systems and industrial control systems in general. In considering cybersecurity vulnerabilities within a future landscape of hydrogen energy for aviation applications, a reference architecture was intended to reveal the points of connection between assets and the potential sensors that are vulnerable to manipulation in the event of compromised access or communication within a SCADA system. A generalized reference architecture can help stakeholders, engineers, or strategists understand connections, criticalities, and standard practices when it comes to designing and planning for new systems. There are several gaps to account for in assessing the future of hydrogen production, storage, and fueling for aviation. Engaging stakeholders, including aircraft manufacturers, electric utilities, site property owners, and local communities, will inform decision-making around site structure, operations, and resources for future hydrogen fueling infrastructure to understand operational needs and cybersecurity awareness. Cybersecurity mitigation strategy must consider physical attack vectors that emerge with the integration of hydrogen systems into existing airport security requirements. The cybersecurity risk assessment contained in this report is an entry point into potential future granular-level analyses to be conducted as part of hazard and risk assessments for safe aviation hydrogen infrastructure, determining how the scale of hydrogen fuel infrastructure for aviation impacts the volume of cyber attack vectors, and what, if any, are the vulnerabilities associated with different types of on-board hydrogen systems. In this nascent development phase, assessing how best to integrate cybersecurity practices into an evolving U.S. aviation landscape provides critical insights into building increased awareness and stakeholder engagement to support a cyber-resilient infrastructure.
08 HYDROGEN↗