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At least 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Real Time Metrics and Analysis of Integrated Arrival, Departure, and Surface Operations

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

integrated arrival departure surface operations↗
NASA NTRS2017

Earth Observing System (EOS) Aqua & Aura Space Weather Effects on Operational Collision Avoidance

This presentation will describe recent EOS Aqua and Aura operational collision avoidance experience during periods of solar and geomagnetic storm activity. It will highlight challenges faced by the operations team during short-notice, high-risk predicted close approaches. The presentation will highlight the evolution of the operational collision avoidance process for the EOS Aqua and Aura missions. The presentation will highlight operational challenges that have occurred, process improvements that have been implemented and identify potential future challenges.

Operational collision avoidance↗
NASA NTRS2017

Systems Engineering Challenges for GSFC Space Science Mission Operations

The NASA Goddard Space Flight Center Space Science Mission Operations (SSMO) project currently manages19 missions for the NASA Science Mission Directorate, within the Planetary, Astrophysics, and Heliophysics Divisions. The mission lifespans range from just a few months to more than20 years. The WIND spacecraft, the oldest SSMO mission, was launched in 1994. SSMO spacecraft reside in low earth, geosynchronous,highly elliptical, libration point, lunar, heliocentric,and Martian orbits. SSMO spacecraft range in size from 125kg (Aeronomy of Ice in the Mesosphere (AIM)) to over 4000kg (Fermi Gamma-Ray Space Telescope (Fermi)). The attitude modes include both spin and three-axis stabilized, with varying requirements on pointing accuracy. The spacecraft are operated from control centers at Goddard and off-site control centers;the Lunar Reconnaissance Orbiter (LRO), the Solar Dynamics Observatory (SDO) and Magnetospheric MultiScale (MMS)mission were built at Goddard. The Advanced Composition Explorer (ACE) and Wind are operated out of a multi-mission operations center, which will also host several SSMO-managed cubesats in 2017. This paper focuses on the systems engineeringchallenges for such a large and varied fleet of spacecraft.

Spacecraft↗
NASA NTRS2018

Concept of Operations for Management by Trajectory

This document describes Management by Trajectory (MBT), a concept for future air traffic management (ATM) in which every flight operates in accordance with a four-dimensional trajectory (4DT) that is negotiated between the airspace user and the Federal Aviation Administration (FAA) to respect the airspace user's goals while complying with National Airspace System (NAS) constraints. In the present-day NAS, the ATM system attempts to predict the trajectory for each flight based on the approved flight plan and scheduled or controlled departure time. However, once the aircraft starts to move, controllers tactically manage the aircraft to implement traffic management restrictions, separate otherwise conflicting aircraft, and address arising NAS constraints. Tactical controller actions are not directly communicated to the automation systems or other stakeholders. Furthermore, the initial trajectory prediction does not anticipate these disruptions or how they will impact the flight. Consequently, and compounded by gaps in required data and models, trajectory predictions are less accurate than possible, which affects Traffic Flow Management (TFM) performance. A cornerstone of the MBT concept is that all air vehicles have, at all times, an assigned 4DT from their current state to their destination. These assigned trajectories consist of trajectory constraints and descriptions. Pilots and air traffic controllers, with the aid of automation, operate the aircraft to comply with the assigned trajectory, unless first negotiating a revision. Equipped aircraft have substantial responsibility for complying with the assigned trajectory without controller intervention. To maximize the operational flexibility available to the airspace user, the assigned trajectory only imposes trajectory constraints as required to achieve the ATM goals of NAS constraint compliance and aircraft separation. Trajectory descriptions are added to the assigned trajectory to ensure sufficient predictability. To further improve trajectory prediction accuracy, airspace users supplement the assigned trajectory by broadcasting intent information and updating it as necessary. Air vehicle intent is a more detailed description of the airspace user's plan for how the flight will fly the assigned trajectory. Air vehicle intent can change freely, without negotiation, as long as it remains in compliance with the assigned trajectory. Aircraft assigned trajectories, air vehicle intent, and predicted trajectories are shared, creating a common view among stakeholders. A NAS Constraint Service gathers and publishes information about all known NAS constraints, enabling airspace users to be informed participants in trajectory negotiation. Trajectory constraints in the assigned trajectory are mapped to NAS constraints to facilitate identifying which aircraft are affected when NAS constraints change. To support efficient trajectory negotiation, all aircraft provide current information about air vehicle capabilities. Assigned trajectories are constructed to satisfy all known NAS constraints, improving trajectory stability and predictability. Uncertainty and disruptions are handled by modifying the assigned trajectory as far in advance as possible. By proactively negotiating changes to the assigned trajectory, rather than relying on controller-selected tactical actions such as vectors to resolve traffic conflicts or implement miles-in-trail restrictions, MBT keeps aircraft on closed trajectories that are fully known to all stakeholders. Since reactive air traffic control actions cannot be predicted in advance, the downstream trajectory cannot be accurately predicted until they happen. Reliable trajectory predictions allow the system to identify needed modifications to trajectories further in advance, where they can be negotiated and communicated as amendments (i.e., additional or altered trajectory constraints) to the assigned trajectory. Decision Support Tools (DSTs) aid controllers in rapidly defining and communicating closed trajectories to the aircraft and support all stakeholders in trajectory negotiation. Anticipated MBT benefit mechanisms include more accurate trajectory predictions, improved ATM performance and robustness to off-nominal conditions, increased flexibility and operational efficiency, reduced impediments to emerging classes of airspace users accessing NAS resources, reduced environmental impacts, and enhanced safety.

ConOps↗
NASA NTRS2018

Operational Impact of the Baseline Integrated Arrival, Departure and Surface System Field Demonstration

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA (Federal Aviation Administration) and industry known Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. As trajectory-based departure scheduling and collaborative decision making tools are introduced in order to reduce delays and uncertainties in taxi and climb operations across the National Airspace System, users of the tools across a number of roles benefit from a real time system that enables common situational awareness. A real time dashboard was developed to inform and present users notifications and integrated information regarding airport surface operations. The dashboard is a supplement to capabilities and tools that incorporate arrival, departure, and surface air-traffic operations concepts in a NextGen environment. In addition to shared situational awareness, the dashboard offers the ability to compute real time metrics and analysis to inform users about capacity, predictability, and efficiency of the system as a whole. This paper describes the architecture of the real time dashboard as well as an initial proposed set of metrics. The potential impact of the real time dashboard is studied at the site identified for initial deployment and demonstration in 2017: Charlotte-Douglas International Airport (CLT). The architecture of implementing such a tool as well as potential uses are presented for operations at CLT. Metrics computed in real time illustrate the opportunity to provide common situational awareness and inform users of system delay, throughput, taxi time, and airport capacity. In addition, common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are explored. The potential of the real time tool to inform users of the predictability and efficiency of using a trajectory-based departure scheduling system is also discussed.

air traffic optimization↗
NASA NTRS2018

LADEE Simulation for Mission Operations

The Lunar Atmosphere Dust Environment Explorer (LADEE) model-based spacecraft simulator has been discussed previously at the Workshop on Spacecraft Flight Software including the verification and validation of the flight software, hardware integration of payloads, and multi-domain simulation. In addition to flight software development and testing the LADEE simulator was used by Mission Operations to develop and test spacecraft command scripts, train operators during mission simulations, verification of all tactical command sequence files uploaded to spacecraft during flight.This presentation will discuss the experience of the LADEE operations team using the spacecraft simulator including implementation, processes and lessons learned. We will also discuss a specific instance where the simulator was used in operations to debug and design a software fix for a spacecraft anomaly experienced with the star tracker.

Operations↗
NASA NTRS2012

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, spacecraft vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery

Space Propulsion↗
NASA NTRS2016

Performance Analysis of Operational Ka-Band Link with Kepler

This paper presents some observations on the signal behavior from an analysis of Kepler Ka-band link. The goal is to characterize the link performance with operational data obtained from the Deep Space Network (DSN) tracking of Kepler spacecraft. Kepler is the first mission supported by the DSN that uses Ka-band as a primary means to return science data. We examine how operational data may differ from the expectation. Operational data often show many surprises where data variations occur without an apparent cause. We try to quantify the signal power fluctuation so that future missions can adequately plan for the link design, especially for missions that operate with lower margin. We also attempt to quantify the effect of rains/heavy clouds and high winds.

performance analysis↗
NASA NTRS2015

Assessing Resilience of Scheduled Performance-Based Navigation Arrival Operations

This paper assesses the resilience of scheduled Performance-Based Navigation (PBN) arrival operations. Resilience is defined as an ability to return to nominal operations following a schedule perturbation. Results from a Human-in-the- Loop (HITL) experiment that included off-nominal events to perturb the schedule are described. The schedule comes from a precision trajectory-based arrival manager. The experiment collected data regarding the response to perturbed schedules in three conditions, where: 1) a disturbance rejection algorithm made schedule adjustments automatically, 2) a Traffic Management Coordinator (TMC) participant made schedule adjustments manually, or 3) no schedule adjustments were made. Analyses showed that the simulation’s scheduled PBN operations have inherent resilience, recovering from more than half of the perturbed schedules even with no schedule adjustments. Resilience to the same off-nominal events improved with schedule adjustments; an increased proportion of perturbed schedules recovered within the length of operation run, and the average duration of the schedule’s perturbed state decreased. Compared to the manual schedule adjustments condition, a greater number of schedule adjustments occurred for the same off-nominal events in the automated condition. However, perturbed schedules were recovered more frequently and perturbations were less severe in the automated condition. Subjective and objective workload in the manual and the automated schedule adjustment conditions were similar to the no schedule adjustment condition.

Resilience↗
NASA NTRS2020

Public Trust and Acceptance for Concepts of Remotely Operated Urban Air Mobility Transportation

There is building interest within industry and government to enable Urban Air Mobility (i.e., air-taxies). One concept envisions remotely piloted aircraft, yet it is unclear how this will impact public trust and acceptance. Method: Two hundred participants read vignettes describing remotely-piloted UAM operations and then responded to a series of questionnaires. The study employed a one-way between-subjects design manipulating five levels of Pilot-in-Command Distance: Onboard Pilot; Remote Control Pilot; Dedicated Remote Operator; Remote Operator; System Manager. Results: The Remote Control Pilot group indicated they would be less likely than the Onboard Pilot Group to use UAM, based on the mediating effect of trust in the automation. The Remote Control Pilot and Remote Operator groups indicated they would be less likely to use UAM than the Onboard Pilot group, based on the mediating effect of trust in the remote pilot/operator. Conclusion: Trust in UAM automation and remote pilots/operators will likely affect public acceptance of UAM.

MTurk↗
NASA NTRSDate not supplied

Model-Based Systems Engineering, Real-Time Operations, and Autonomy

Model-Based Systems Engineering has been enabled by the development of the SysML language and software tools to create systems models. Systems models described in SysML incorporate frames (Diagrams) that represent behaviors (activities, sequences, state machines, use cases), requirements, and structure (definitions, internal structure, parametric formulation, and packaging). The SysML models are, in turn, used by applications to do analysis and studies of the designs and operational capabilities. These uses of the model are based on simulations, and do not include hardware. This paper presents a software environment and processes that enables more comprehensive systems models for MBSE, and use of these rich models for real-time operations. The paper describes a software platform that enables creation of comprehensive models, beyond what is now possible with SysML and related software tools, called the NASA Platform for Autonomous Systems (NPAS). The platform encapsulates a paradigm and infrastructure for creating systems models with complexity levels comparable to the ones handled by SysML software tools, but with additional fidelity that includes detailed design diagrams encompassing sensors, components, and design topologies. Furthermore, NPAS enables incorporation of data, information, and knowledge (DIaK) to implement autonomy and Integrated System Health Management (ISHM) and the inherent integration of content encompassing SysML structure and behavior diagrams throughout the NPAS modelAnd lastly, the NPAS models are used in real-time operations, taking advantage of the fidelity and complexity encompassed in the models in order to implement “thinking” ISHM and/or autonomous operations. . Incorporation of SysML model content into an NPAS model is briefly discussed.

MBSE↗
NASA NTRS2021

High-Density Automated Vertiport Concept of Operations

The National Aeronautics and Space Administration (NASA) vision for Advanced Air Mobility (AAM) includes Urban Air Mobility (UAM) – a concept involving vertical takeoff and landing (VTOL) aircraft, decentralized (or federated) traffic management, and new infrastructure to support urban, suburban, and rural flight operations. High-density performance-based routes or corridors enable prompt transportation of people and goods from node to node, where each node represents a vertiport, defined as an identifiable ground or elevated area used for the takeoff and landing of VTOL aircraft. In the presence of uncertainty surrounding aircraft turnaround time on the ground, vertiports are the critical end points in scheduling, sequencing, and spacing (SSS) of aircraft in dense metropolitan environments. This Concept of Operations (ConOps) includes vertiports of varying sizes, configurations, service offerings, and locations. UAM air vehicles include conventional rotorcraft, unmanned VTOL aircraft, and novel piloted VTOL aircraft. This ConOps focuses on operations at a high-density vertiport, supported by a Vertiport Automation System (VAS) with high-throughput operation capabilities under conditions defined as NASA’s Urban Air Mobility Maturity Level Four (UML-4).

Urban Air Mobility↗
NASA NTRSDate not supplied

Uncrewed Lunar Surface Operations and Support Activities

This presentation summarizes the contents of the uncrewed lunar surface operations and support activities paper. It outlines the functions, features, and capabilities that support sustained human and robotic surface operations. It summarizes the complexities associated with the development and operation of autonomous systems and discusses a simulation tool for integrated surface operations planning.

Lunar↗
NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).

Real-Time Streaming Data Architecture↗
NASA NTRSDate not supplied

Space Shuttle Program Dual Docked Operations

Due to the ever-increasing visiting vehicle traffic to and from the International Space Station (ISS) during mated Orbiter/ISS missions, it became apparent to both the ISS Program (ISSP) and the Space Shuttle program (SSP) that there would arise occasions where a visiting vehicle docking and/or undocking could overlap when the Space Shuttle Orbiter was docked to the ISS, referred to as Dual Docked Operations (DDO). The primary concerns were that plumes from the visiting vehicles would cause contamination, corrosion, and erosion to Space Shuttle surfaces and present a toxicity hazard to ground personnel when processing the Space Shuttle after landing. This potential conflict provided the genesis for evaluating risk mitigations to gain maximum flexibility for managing potential visiting vehicle traffic to and from the ISS and to maximize launch and landing opportunities for all visiting vehicles. The overarching goal of this effort was to assess the viability and readiness of the SSP to protect for DDO on any given mission. To assess the viability of performing DDO, the ISSP delivered plume particle fluence (i.e., number of particles per unit area) and contamination deposition based on the visiting vehicle’s proximity operations to the SSP for evaluation. This paper summarizes the concept definition, studies, and analysis results generated by the SSP, ISSP, and Mission Operations Directorate (MOD) for implementing DDO involving the Orbiter and Russian vehicles (RVs). Discussion and results presented herein represent a generic assessment of the SSP and ISSP integrated safety and technical evaluations of DDO involving the Orbiter and RVs. Mission-specific analysis and operational impacts were conducted flight-by-flight as they arose.

Launch vehicles↗
NASA NTRSDate not supplied

Space Shuttle Program Dual Docked Operations

- Dual Docked Operations (DDO) is the docking or undocking of a Russian Vehicle (RV) during Space Shuttle Orbiter/International Space Station (ISS) mated operations. - This paper and presentation summarizes the concept definition, studies, and analysis results generated by the Space Shuttle Program (SSP), ISS Program (ISSP), and Mission Operations Directorate for implementing DDO during mated Orbiter/ISS missions. [1] - Due to the ever-increasing visiting vehicle traffic to and from the ISS, it became apparent to both the ISSP and the SSP that there would arise occasions where conflicts between a visiting vehicle docking and/or undocking could overlap with a planned Space Shuttle launch and/or during mated Orbiter/ISS operations. - This potential conflict provided the genesis for evaluating risk mitigations to gain maximum flexibility for managing potential visiting vehicle traffic to and from the ISS and to maximize launch and landing opportunities for all visiting vehicles. - Reviews were conducted to assess the viability and readiness of the SSP to protect for DDO on any given mission and it was found to be t echnically feasible

Launch vehicles↗
NASA NTRS2023

Space Shuttle Program Dual Docked Operations

- Dual Docked Operations (DDO) is the docking or undocking of a Russian Vehicle (RV) during Space Shuttle Orbiter/International Space Station (ISS) mated operations. - This paper and presentation summarizes the concept definition, studies, and analysis results generated by the Space Shuttle Program (SSP), ISS Program (ISSP), and Mission Operations Directorate for implementing DDO during mated Orbiter/ISS missions. [1] - Due to the ever-increasing visiting vehicle traffic to and from the ISS, it became apparent to both the ISSP and the SSP that there would arise occasions where conflicts between a visiting vehicle docking and/or undocking could overlap with a planned Space Shuttle launch and/or during mated Orbiter/ISS operations. - This potential conflict provided the genesis for evaluating risk mitigations to gain maximum flexibility for managing potential visiting vehicle traffic to and from the ISS and to maximize launch and landing opportunities for all visiting vehicles. - Reviews were conducted to assess the viability and readiness of the SSP to protect for DDO on any given mission and it was found to be t echnically feasible

Launch vehicles↗
NASA NTRSDate not supplied

A Preliminary Development of The Intelligent Change Detection System (ICDS): Using Machine Learning to Combat Change Blindness in Remote Operation Environments

The emergence of Advance Air Mobility (AAM) will increase the number and types of aerial vehicles operating in shared airspaces, which will subsequently affect the amount of actionable data that ground control station operators (GCSOs) will be expected to manage. In this environment, GCSOs are particularly susceptible to the visual perceptual phenomenon known as change blindness, in which a stimulus undergoes a change without the change being noticed by its observer. A machine agent designed to detect change blindness and mitigate the effects could improve human agent performance in a data-saturated remote operations environment. The objective of this paper is to describe a proof-of-concept system architecture that integrates real-time eye tracking and vehicle telemetry data to prevent human-agent errors resulting from change blindness while operating aircraft from a remote ground control station (GCS).

Real-Time Streaming Data Architecture↗