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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Micro-Ramp Flow Control for Oblique Shock Interactions: Comparisons of Computational and Experimental Data

Computational fluid dynamics was used to study the effectiveness of micro-ramp vortex generators to control oblique shock boundary layer interactions. Simulations were based on experiments previously conducted in the 15- by 15-cm supersonic wind tunnel at the NASA Glenn Research Center. Four micro-ramp geometries were tested at Mach 2.0 varying the height, chord length, and spanwise spacing between micro-ramps. The overall flow field was examined. Additionally, key parameters such as boundary-layer displacement thickness, momentum thickness and incompressible shape factor were also examined. The computational results predicted the effects of the microramps well, including the trends for the impact that the devices had on the shock boundary layer interaction. However, computing the shock boundary layer interaction itself proved to be problematic since the calculations predicted more pronounced adverse effects on the boundary layer due to the shock than were seen in the experiment.

Hirt, Stephanie M.↗
NASA NTRS2017

Assessing Tactical Scheduler Options for Time-Based Surface Metering

NASA is committed to demonstrating a concept of integrated arrival, departure, and surface operations by 2020 under the Airspace Technology Demonstration 2 (ATD2) sub-project. This will be accomplished starting with a demonstration of flight specific time-based departure metering at Charlotte Douglass International Airport (CLT). ATD2 tactical metering capability is based on NASAs Spot And Runway Departure Advisor (SARDA) which has been tested successfully in human-in-the-loop simulations of CLT. SARDA makes use of surface surveillance data and surface modeling to estimate the earliest takeoff time for each flight active on the airport surface or ready for pushback from the gate. The system then schedules each flight to its assigned runway in order of earliest takeoff time and assigns a target pushback time, displayed to ramp controllers as an advisory gate hold time. The objective of this method of departure metering is to move as much delay as possible to the gate to minimize surface congestion and engine on-time, while keeping sufficient pressure on the runway to maintain throughput. This flight specific approached enables greater flight efficiency and predictability, facilitating trajectory-based operations and surface-airspace integration, which ATD2 aims to achieve.Throughout ATD2 project formulation and system development, researchers have continuously engaged with stakeholders and future users, uncovering key system requirements for tactical metering that SARDA did not address. The SARDA scheduler is updated every 10 seconds using real-time surface surveillance data to ensure the most up-to-date information is used to predict runway usage. However, rapid updates also open the potential for fluctuating advisories, which Ramp controllers at a busy airport like CLT find unacceptable. Therefore, ATD2 tactical metering requires that all advisories freeze once flights are ready so that Ramp controllers may communicate a single hold time when responding to pilot ready calls.

Zelinski, Shannon↗
DOE OSTI2022

Real-Time On-Ramp Merging Control of Connected and Automated Vehicles using Pseudospectral Convex Optimization

Highway on-ramp merging can be a challenging task for human drivers due to the complex vehicle negotiations and interactions in limited time and space. Connected and automated vehicles (CAVs) have great potential to address the problem and offer many benefits in terms of safety, traffic efficiency, and fuel economy. However, real-time optimal control of CAVs still faces many challenges, including nonlinear dynamics, complex inter-vehicle interactions, and a highly dynamic and uncertain traffic environment. To address these challenges, we develop a novel control approach that balances the solution optimality and computational efficiency to determine optimal merging speed profiles in real time. Specifically, by employing a pseudospectral method and a sequential convex programming approach, two algorithms are proposed and implemented within the model predictive control (MPC) framework to enable real-time generation of optimal solutions for potential on-vehicle applications. The convergence and optimality of the proposed algorithms are validated by comparing with a general-purpose solver under different traffic scenarios.

Shi, Yang↗
NASA NTRS2015

SARDA HITL #6 Simulation: System Performance Analysis (Initial Results)

This presentation discusses the results of the 6th human-in-the-loop simulation of the Spot and Runway Departure Advisor (SARDA). SARDA is a research prototype decision support tool for both Air Traffic Control Tower controllers and airlines ramp controllers to assit in controlling surface traffic of a busy airport. Data was collected during the human-in-the-loop simulations of SARDA for ramp operatoins at Charlotte International Airport (Oct-Nov 2014). The performance results include taxi time, taxi delay, total delay, and runway usage.

surface management↗
NASA NTRS1997

Teamwork in the Terminal Area: Organizational Issues and Solutions

Dynamic growth and technology advances in commercial aviation have turned the terminal area into a complex, multi-organization workplace which requires the smooth coordination of many operational teams. In addition to pilots, cabin crew, air traffic controllers, and dispatch (who nominally work together throughout a flight), surface operations additionally involve local, ground and ramp controllers, ramp agents, maintenance, dozens of service contractors, and any number of teams who are responsible for airport operations. Under abnormal or emergency conditions, even more teams become actively involved. In order to accommodate growth and to meet productivity and safety challenges, numerous changes are being made in surface operations. Unfortunately, it is often the case that changes in technologies, organizational roles, procedures, and training are developed and implemented in isolated and piecemeal fashion without regard to cross organizational impact. Thus, there is a need for evaluation methodologies which assure integrated system safety for all organizations. Such methodologies should aid the understanding of how organizations work together and how changes in one domain affects the next. In this study, we develop one approach toward addressing these organizational issues. Examples of surface operations in abnormal situations are examined in regard to their impact on personnel in the terminal area. Timelines are given for the responses to incidents, along with the necessary communication links, the specific roles that members of terminal teams have, and any overlapping responsibilities. Suggestions to improve cross-operational teamwork are given. Methods of graphic representation are explored, both in regards to human links and access to information. The outcome of such an approach should enhance the understanding which is critical for resolving organizational conflicts and maximizing system effectiveness.

Parke, Bonny K.↗
NASA NTRS2000

Automated Traffic Management System and Method

A data management system and method that enables acquisition, integration, and management of real-time data generated at different rates, by multiple heterogeneous incompatible data sources. The system achieves this functionality by using an expert system to fuse data from a variety of airline, airport operations, ramp control, and air traffic control tower sources, to establish and update reference data values for every aircraft surface operation. The system may be configured as a real-time airport surface traffic management system (TMS) that electronically interconnects air traffic control, airline data, and airport operations data to facilitate information sharing and improve taxi queuing. In the TMS operational mode, empirical data shows substantial benefits in ramp operations for airlines, reducing departure taxi times by about one minute per aircraft in operational use, translating as $12 to $15 million per year savings to airlines at the Atlanta, Georgia airport. The data management system and method may also be used for scheduling the movement of multiple vehicles in other applications, such as marine vessels in harbors and ports, trucks or railroad cars in ports or shipping yards, and railroad cars in switching yards. Finally, the data management system and method may be used for managing containers at a shipping dock, stock on a factory floor or in a warehouse, or as a training tool for improving situational awareness of FAA tower controllers, ramp and airport operators, or commercial airline personnel in airfield surface operations.

Glass, Brian J.↗
DOE OSTI2020

Optimal Energy Storage Schedules for Load Leveling and Ramp Rate Control in Distribution Systems

Continued integration of distributed energy resources (DERs) into the grid, such as solar PVs, at a large-scale, contributes into the famous Duck Curve. New DER management algorithms are therefore deemed necessary to alleviate rapid variations within net load profiles of distribution systems. Herein this paper proposes a process to determine the optimal energy storage schedules for leveling the distribution circuit feederhead net load. A series of sensitivity analyses shows how the proposed method can be used to determine the optimal energy storage schedules with different capacities, state of charge requirements, and net load ramp rate limitations.

25 ENERGY STORAGE↗
DOE OSTI2023

Pseudospectral convex optimization for on-ramp merging control of connected vehicles

It can be a daunting task for human drivers to merge into highways because of the intricate vehicle negotiations and potential risk within limited time and space. Connected vehicle (CV) technologies could be a solution to this problem and offer many benefits to the road safety, traffic mobility, and energy efficiency. However, real-time optimal control of CVs is still an open challenge, due to the nonlinear vehicle dynamics, non-convex fuel consumption model, and highly dynamic uncertain inter-vehicle interactions. To tackle these issues, a novel real-time optimal control approach that balances the computational efficiency and solution optimality is proposed for the purpose of onboard application. To this end, the pseudospectral collocation method is integrated with a sequential convex programming approach to develop two new optimization algorithms, which are implemented within a model predictive control (MPC) framework to allow for real-time generation of optimal merging speed profiles. One algorithm leverages the line search technique to improve convergence, and the other benefits from the trust region method for better computational efficiency. The optimality and convergence process of both proposed algorithms are investigated by comparing their solutions with a popular non-linear solver. Furthermore, simulation results show that the proposed methods outperform the benchmark in terms of computational cost, fuel consumption, and traffic efficiency. In particular, the proposed fuel-economy merging rule can save 57.1% fuel consumption on average on four different traffic volumes. Meanwhile, the proposed optimal control algorithms can reduce 2.2% travel time on average comparing to the “first-in-first-out” merging rule.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2017

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

This document serves as a user manual for the Observer Mode Ramp Traffic Console (RTC) in Charlotte Douglas International Airport Ramp Control Tower. It describes the elements of the full RTC interface and provides explanations for how to interact with the RTC while managing ramp traffic using one of the four RTC sector displays. The RTC provides digitally updated data for all flights including Earliest Off Block Times (EOBT) and Traffic Management Initiatives. Use of the RTC in observer mode allows only for observer and reading of data provided on RTC. In Observer Mode, the RTC may not be used to make data entries. This includes pushback, holds, and proceed inputs as well as updates to a flights data using the flight menu. However, using the RTC in Observer Mode allows for real time observation of ramp operations including pushback and hold entries made by the ramp sector controllers. The pushback advisories and Traffic Management Initiative information is also provided in Observer Mode. The RTC also provides notifications, runway departure counts and lists and near arrival flight lists as additional sources of information for management of ramp traffic. There are also detailed instructions for how to manage traffic with Surface Time Based Metering (STBM) advisories provided on RTC if in STBM mode. This document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) while performing ramp manager functions such as managing the priority flight list, setting ramp status, and setting the metering mode. The RTC and RMTC ramp tool are one component of a suite of ATD-2 Tools.

Stevens, Lindsay K.↗
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↗
NASA NTRS2014

Flow Separation Control Over a Ramp Using Sweeping Jet Actuators

Flow separation control on an adverse-pressure-gradient ramp model was investigated using various flow-control methods in the NASA Langley 15-Inch Wind Tunnel. The primary flow-control method studied used a sweeping jet actuator system to compare with more classic flow-control techniques such as micro-vortex generators, steady blowing, and steady- and unsteady-vortex generating jets. Surface pressure measurements and a new oilflow visualization technique were used to characterize the effects of these flow-control actuators. The sweeping jet actuators were run in three different modes to produce steady-straight, steady-angled, and unsteady-oscillating jets. It was observed that all of these flow-control methods are effective in controlling the separated flows on the ramp model. The steady-straight jet energizes the boundary layer by momentum addition and was found to be the least effective method for a fixed momentum coefficient. The steady-angled jets achieved better performance than the steady-straight jets because they generate streamwise vortices that energize the boundary layer by mixing high-momentum fluid with near wall low-momentum fluid. The unsteady-oscillating jets achieved the best performance by increasing the pressure recovery and reducing the downstream flow separation. Surface flow visualizations indicated that two out-of-phase counter-rotating vortices are generated per sweeping jet actuator, while one vortex is generated per vortex-generating jets. The extra vortex resulted in increased coverage, more pressure recovery, and reduced flow separation.

Koklu, Mehti↗
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 NTRS2013

Spot and Runway Departure Advisor

The Spot and Runway Departure Advisor (SARDA) is a research prototype of a decision support tool for ATC tower controllers to assist in manging and controlling traffic on the surface of an airport. SARDA employs a scheduler to generate an optimal runway schedule and gate push-back - spot release sequence and schedule that improves efficiency of surface operations. The advisories for ATC tower controllers are displayed on an Electronic Flight Strip (EFS) system. The human-in-the-loop simulation of the SARDA tool was conducted for east operations of Dallas-Ft. Worth International Airport (DFW) to evaluate performance of the SARDA tool and human factors, such as situational awareness and workload. The results indicates noticeable taxi delay reduction and fuel savings by using the SARDA tool. Reduction in controller workload were also observed throughout the scenario runs. The future plan includes modeling and simulation of the ramp operations of the Charlotte International Airport, and develop a decision support tool for the ramp controllers.

decision support tool↗
NASA NTRS2017

Airspace Technology Demonstration II (ATD-2): American Airlines CLT Ramp Training RTC/RMTC: Baseline Integrated Arrival/ Departure/Surface (IADS) - ATD-2 Tech Transfer 1 - Phase 1

This training material was created to train CLT (Charlotte Douglas International Airport) ramp controllers on the ATD-2 (Airspace Technology Demonstration-2) system. It includes an overview of ATD-2 and the RTC/RMTC (Ramp Traffic Console/Ramp Manager Traffic Console). It discusses many interface details, data exchange and integration, metering modes, and scheduler advisories. It concludes with interactive exercises on all topics of the training course.

RTC/RMTC↗
NASA NTRS2018

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

This document serves as a user manual for the Ramp Traffic Console (RTC) in the Ramp Control Tower. It describes the elements of the RTC interface and provides explanations for how to utilize the RTC to manage ramp traffic. The RTC provides live data for all flights including Earliest Off-Block Times (EOBT) and Traffic Management Initiatives (TMI). The 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. If applicable, this document also provides instructions for use of the Ramp Manager Traffic Console (RMTC) for ramp manager functions of adjusting the priority flight list, and setting ramp status. The RTC/RMTC ramp tool are components of Airspace Technology Demonstration-2.

ATD-2 RMTC↗
DOE OSTI2021

A Cyber-Physical System for Freeway Ramp Meter Signal Control Using Deep Reinforcement Learning in a Connected Environment

Freeway bottlenecks such as on-ramp merging areas account for about 40% of recurring freeway congestion. It is generally agreed that building more roads and adding more lanes to existing infrastructure does not solve the congestion problem, and so dynamic traffic control measures offer a more cost-effective alternative. Ramp meters, traffic signal devices that regulate traffic flow entering freeways, are among the most effective measures to mitigate congestion at on-ramp merging areas on freeways. The confluence of deep reinforcement learning (RL) and connectivity provides a possible solution to advance ramp meter signal control. Deep RL is a group of machine-learning methods that enables an agent learning from the environment to improve its performance. In this study, three deep RL methods-proximal policy optimization (PPO), Ape-X deep Q-network (DQN), and asynchronous advantage actor-critic agents (A3C)-are explored for ramp meter signal control to maximize vehicle speed and traffic throughput, as well as to minimize energy consumption and emissions at freeway on-ramp merging areas in a connected environment. The low computational requirement and scalability of deep RL for deployment make it a powerful optimization tool for time-sensitive applications such as ramp meter signal control. The results of this study show that deep RL methods yield superior performance to both a fixed-time controller and ALINE A, a state-of-the-art feedback controller.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗
NASA NTRS1997

Surface Development and Test Facility (SDTF) New R&D Simulator for Airport Operations

A new simulator, the Surface Development and Test Facility (SDTF) is under construction at the NASA Ames Research Center in Mountain View, California. Jointly funded by the FAA (Federal Aviation Administration) and NASA, the SDTF will be a testbed for airport surface automation technologies of the future. The SDTF will be operational in the third quarter of 1998. The SDTF will combine a virtual tower with simulated ground operations to allow evaluation of new technologies for safety, effectiveness, reliability, and cost benefit. The full-scale level V tower will provide a seamless 360 degree high resolution out-the-window view, and a full complement of ATC (air traffic control) controller positions. The imaging system will be generated by two fully-configured Silicon Graphics Onyx Infinite Reality computers, and will support surface movement of up to 200 aircraft and ground vehicles. The controller positions, displays and consoles can be completely reconfigured to match the unique layout of any individual airport tower. Dedicated areas will accommodate pseudo-airport ramp controllers, pseudo-airport operators, and pseudo-pilots. Up to 33 total personnel positions will be able to participate in simultaneous operational scenarios. A realistic voice communication infrastructure will emulate the intercom and telephone communications of a real airport tower. Multi-channel audio and video recording and a sophisticated data acquisition system will support a wide variety of research and development areas, such as evaluation of automation tools for surface operations, human factors studies, integration of terminal area and airport technologies, and studies of potential airport physical and procedural modifications.

Dorighi, Nancy S.↗