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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 271 records · Page 15
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NASA NTRS2020

Investigating Effects of Controlled Flights through Fast-Time Simulation

Departure flights at major U.S. airports are often subject to Traffic Management Initiatives to mitigate congestion and delay due to demand-capacity imbalances. These controlled flights can lead to inefficiency and delay on the airport surface. The integrated arrival, departure, and surface traffic management capabilities developed by NASA’s Airspace Technology Demonstration 2 (ATD-2) sub-project provide enhanced operational efficiency and predictability of flight operations through data exchange and integration, surface metering, and automated coordination of release time of controlled flights for overhead stream insertion. This paper evaluates the impacts of controlled flights on airport performance and assesses the ATD-2 benefits of pushback hold advisories for both controlled and non-controlled flights using fast-time simulation for Charlotte Douglas International Airport.

controlled flight↗
NASA NTRS2020

Strategic Surface Metering at Charlotte Douglas International Airport

NASA is conducting a field test of the Airspace Technology Demonstration2 (ATD-2) to evaluate an Integrated Arrival, Departure, and Surface (IADS) traffic management system. The IADS system was deployed to Charlotte Douglas International Airport (CLT) in 2017 for a three-year field evaluation. The Phase 1 field evaluation included tactical surface metering, which manages departure excess taxi time by tactically assigning gate holds. Phase 2 built upon the lessons learned from Phase 1 to extend surface metering into the strategic metering timeframes. In this paper, we describe the strategic metering capabilities of the ATD-2 IADS system and the operational results from CLT.

Airspace Technology Demonstration 2↗
NASA NTRS2020

Ramp Traffic Console (RTC) and Ramp Manager Traffic Console (RMTC) User Manual

This document serves as a user manual for the ATD-2 Ramp Traffic Console (RTC) (version 5.11) utilized by the Ramp Control Tower. It describes the elements of the RTC interface and provides step-by-step instructions for using the tool. RTC provides live flight information, including, flight state and location, departure/arrival schedules, gate conflicts, Traffic Management Initiative (TMI) restrictions, and gate advisories to support Surface Time-Based Metering (STBM). RTC facilitates information sharing with the Air Traffic Control (ATC) Tower. This document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) for Ramp Manager functions, such as managing the priority flight list and setting the ramp status. The RTC/RMTC ramp tools are components of the NASA Airspace Technology Demonstration 2 (ATD-2) sub-project.

Deborah Lee Bakowski↗
NASA NTRS2020

Web-Based Surface Metering Display (SMD) User Manual

This document serves as a user manual for the ATD-2 Web-Based Surface Metering Display (SMD) (version 5.11). It describes the elements of the SMD interface and provides step-by-step instructions for using the tool. The SMD can be used to select the type of metering, set specific metering parameters, and set excess queue time variables. Feedback can also be submitted through the site. The SMD is a component of the NASA Airspace Technology Demonstration 2 (ATD-2) sub-project.

Louise Kay Morgan Ruszkowski↗
NASA NTRS2020

Surface Trajectory-Based Operations (STBO) Client User Manual

This document serves as a user manual for the ATD-2 Surface Trajectory-Based Operations (STBO) Client (version 5.11) utilized by Air Traffic Control in the Tower. It describes the elements of the STBO Client interface and provides step-by-step instructions for using the tool. STBO Client functionality includes the display of live flight information, management of traffic restrictions, and prediction of expected traffic demand. The STBO Client is a component of the NASA Airspace Technology Demonstration 2 (ATD‑2) sub-project.

Louise Kay Morgan Ruszkowski↗
NASA NTRS2021

Metroplex Planner User Manual

This document serves as a user manual for the ATD-2 Metroplex Planner (version 6.1.2) for use by the Air Route Traffic Control Center (ARTCC), Terminal Radar Approach Control (TRACON), airport Air Traffic Control Tower, and airline Flight Operators. It describes the elements of the Metroplex Planner interface and provides step-by-step instructions for using the tool. In addition to live flight information, traffic management information, and demand/delay predictions, the Metroplex Planner supports Trajectory Option Set (TOS) rerouting. The Metroplex Planner is a component of the NASA Airspace Technology Demonstration 2 (ATD-2) sub-project.

Deborah L Bakowski↗
NASA NTRS2023

Numerical Investigation of Occupant Injury Risks During A Realistic Transport Aircraft Crash Conditions

Researchers at the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) have conducted a full-scale crash test of a Fokker F28 MK1000 aircraft to investigate the performance of transport aircraft under realistic crash conditions. This crash test was computationally recreated using finite element (FE) human body models (HBMs) to further explore potential injury risks to occupants and analyze the utilization of HBMs in the aerospace crash environment. The Global Human Body Model Consortium (GHBMC) male 50th percentile occupant detailed model (v6.0) and the Toyota Human Model for Safety (THUMS) male 50th percentile occupant model (v6.1) were selected to be used in the crash simulations. The HBMs were simulated in conditions matching those of anthropomorphic test device (ATD) experiments included within the aircraft cabin during the crash test. Seven occupant locations within the cabin were simulated utilizing each of the models. The models were positioned in a neutral upright posture with hands resting on the legs and the feet contacting the floor. Head, brain, neck, and lumbar vertebra injury metrics were calculated for all trials. Both HBM models required minor modifications to stabilize these simulations. The GHBMC model required added erosion for six parts while the THUMS model only required one in order to complete the full simulation. The THUMS model, however, required a much smaller timestep for stability and therefore took significantly more computational time. In addition the GHBMC model includes integrated instrumentation while the THUMS model requires development and implementation of instrumentation. Both models predicted 100% injury risk for lumbar vertebra fracture in all test conditions. This prediction was in family with high lumbar load values measured by the ATDs during the crash test. The THUMS model consistently predicted lower injury risks than the GHBMC model in all three other metrics varying depending on the crash pulse. Overall, the THUMS model required less modifications to allow for this study. However, the GHBMC models significantly faster run time and integrated instrumentation make it a more intuitive model for this research.

Crashworthiness↗
DOE OSTI2025

Towards Content Authenticity: Multimodal Fake News Detection and AI-Generated Text Identification

In today’s digital world, the spread of fake news and the rise of AI-generated text have become major threats to content authenticity and public trust. This thesis addresses both challenges through two complementary research directions: detecting fake news using multimodal features, and identifying AI-generated text using semantic and structural reasoning. The first part of the work focuses on fake news detection by introducing a novel model that combines text and image features through a unique rotational attention mechanism. Unlike traditional attention methods, this approach rotates the roles of query, key, and value across modalities to capture deeper interactions. Additionally, the model incorporates external domain information by linking news posts to top-ranked websites from Google search results, which helps assess the credibility of content based on its broader web context. This results in a more reliable and accurate fake news detection system that outperforms existing state-of-the-art methods. The second part presents SGG-ATD, a new framework for detecting AI-generated text. It uses masked language modeling to measure sentence coherence, followed by constructing a graph where keywords—both original and predicted—are connected based on semantic and contextual similarity. A Graph Convolutional Network (GCN) is then used to learn structural relationships within the text for final classification. Experimental results demonstrate that SGG-ATD achieves high F1-scores and consistently outperforms strong baselines. This method contributes to robust AI text detection, supporting accountability and resilience against AI-driven misinformation.

Gupta, Nidhi↗
NASA NTRS2014

Overview of Research Transition Products

Demonstrate increased, more consistent use of Performance‐ Based Navigation (PBN). Accelerate transfer of NASA scheduling and spacing technologies for inclusion in late mid‐term NAS. During high‐fidelity human‐in‐the‐loop simulations of Terminal Sequencing and Spacing, air traffic controllers have significantly improved their use of PBN procedures during busy traffic periods without increased workload. Executed an aggressive, short timeframe development schedule. Developed TSS prototype based upon FAA operational systems. Conducted multiple joint FAA/NASA human‐in‐the‐loop simulations. Performed repeated incremental deliveries of tech transfer material to non‐traditional RTT stakeholders. Will continue to participate in later phases of FAA acquisition process. ATD‐1 transferred Terminal Sequencing and Spacing (TSS) technologies to the FAA. TSS enables routine use of underutilized advanced avionics and PBN procedures. Potential benefits to airlines operating at initial TSS sites estimated to be $300‐400M/year. FAA is planning for an initial capability in the NAS in 2018.

Technology Transfer↗
NASA NTRS2017

Comparison of Taxi Time Prediction Performance Using Different Taxi Speed Decision Trees

In the STBO modeler and tactical surface scheduler for ATD-2 project, taxi speed decision trees are used to calculate the unimpeded taxi times of flights taxiing on the airport surface. The initial taxi speed values in these decision trees did not show good prediction accuracy of taxi times. Using the more recent, reliable surveillance data, new taxi speed values in ramp area and movement area were computed. Before integrating these values into the STBO system, we performed test runs using live data from Charlotte airport, with different taxi speed settings: 1) initial taxi speed values and 2) new ones. Taxi time prediction performance was evaluated by comparing various metrics. The results show that the new taxi speed decision trees can calculate the unimpeded taxi-out times more accurately.

taxi time prediction↗
NASA NTRS2016

Distributed Schemes for Integrated Arrival Departure Surface (IADS) Scheduling

The objective of the NRA is to investigate and develop integrated scheduling solutions for arrival, departure and surface operations. The option year briefing summarizes simulation-based analyses of the departure metering process to investigate strategic queue management strategies and their robustness to uncertainty, assess the impact of delaying departures at their gates on blocking the arrivals destined for the same gates, and evaluate the effects and benefits of relaxing current-day MIT constraints when ATD-2 is in operation.

ATD-2↗
NASA NTRS2018

On-Time Performance ASPM Non-Parametric Statistical Analysis

The purpose of this analysis is to provide a data-driven examination of two selected flight metrics, i.e., (1) total taxi-out time and (2) actual off time minus scheduled off block time. More specifically, Aviation System Performance Metrics (ASPM) data were analyzed to determine any possible differences in CLT (Charlotte Douglas International Airport) departure flights on these two metrics when comparing pre-IADS (Integrated Arrival, Departure, and Surface Operations) against post-IADS metering operations. This was originally presented to the ATD-2 (Airspace Technology Demonstration-2) Analytics team in August 2018.

tech transfer↗
NASA NTRS2018

What-If System

The What-If System is meant to be a "sandbox" to be able to view the potential impact of system wide changes on the tower side and metering decisions on the ramp side without actually making changes to the system. The What-If System is a tool within which with STBO, RMTC and DASH may be used such that proposed changes and updates can be made to determine their impact in isolation. The What-If System is a prototype tool, we welcome suggestions for improving the What-If utility. Improvements will be incorporated in later builds beyond phase-1 of ATD-2.

User Manual↗
NASA NTRS2019

STBO Client User Manual

This document serves as a user manual for the STBO Client utilized by ATC in the Tower. It describes the elements of the STBO Client and provides explanations for how to interact with the interface. STBO Client functionality includes the display of live flight information and management of traffic restrictions. The STBO Client is a component of the NASA Airspace Technology Demonstration 2 (ATD-2) sub-project.

Surface Decision Support Tool↗
NASA NTRS2019

Web-Based Surface Metering Display (SMD) User Manual

This document serves as a manual for the ATD-2 Web-Based Surface Metering Display (SMD) Version 4.6.0. It describes the elements of the full SMD interface and provides explanations for how to interact with the SMD. The document provides instructions for selecting the type of metering, entering specific metering parameters, and setting excess queue time variables. There are instructions for submitting system feedback and bug reports as well.

Surface Metering↗
NASA NTRS2019

Ramp Traffic Console (RTC) Ramp Manager Traffic Console (RMTC) User Manual

This document serves as a user manual for the Ramp Traffic Console (RTC) Version 4.6.0 in the Ramp Control Tower. It describes the elements of the RTC interface and provides explanations for how to utilize RTC to manage ramp traffic. RTC provides live data for all flights including Earliest Off-Block Times (EOBTs) and Traffic Management Initiatives (TMIs). RTC augments management of ramp traffic by providing notifications of runway configurations, and lists flight arrivals, near arrivals, and departures as additional sources of information. This document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) for Ramp Manager functions, such as adjusting the priority flight list and setting the ramp status. The RTC/RMTC ramp tools are components of the NASA Airspace Technology Demonstration 2 (ATD-2) sub-project.

Airport surface decision support tool↗