Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “command and control”

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.

At least 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Numerical Predictor-Corrector Based Guidance Scheme For Aero-Gravity Assist at Titan For Enceladus Missions

Aero-gravity assist is a spacecraft maneuver than can enable a vehicle to insert into an orbit of one planetary body using the atmosphere and gravity field of a secondary body, reducing the required propellant mass relative to a fully-propulsive orbit insertion. The Fully Numerical Predictor-Corrector Aerocapture Guidance algorithm was modified to work with a direct force control blunt body vehicle, executing an aero-gravity assist at Titan to enter a Saturnian orbit and conduct fly-by at Enceladus. Additionally, a proportional-integral-derivative controller was implemented to command sideslip angles for control of the orbital inclination. Numerical simulation showed the developed guidance scheme was capable of minimizing the energy and inclination error at atmospheric exit, allowing Saturnian moon tour trajectories and Enceladus exploration at a small delta-V cost, on the order of 100 m/s, in the nominal case.

Daniel L. Engel↗
NASA NTRS1998

Design of the Remote Agent Experiment for Spacecraft Autonomy

This paper describes the Remote Agent flight experiment for spacecraft commanding and control. In the Remote Agen approach, the operational rules and constraints are encoded in the flight software, and the software may be considered to be an autonomous

Remote↗
NASA NTRS1994

Customizing the JPL Multimission Ground Data System: Lessons Learned

This paper will describe lessons learned in adapting JPL's Multimission Ground Data System (MGDS) to fly the Voyager, Galileo, and Mars Observer missions. We will explain how powerful, existing ground data systems can be adapted and packaged in a cost effective way for operations of small and large planetary missions. We will also describe how the MGDS was adapted to support operations within the Galileo Spacecraft Testbed. The Galileo testbed provided a unique opportunity to adapt MGDS to support command and control operations for a small autonomous operations team with a handful of engineers flying the Galileo Spacecraft flight system model.

ground↗
NASA NTRS2016

Mission-centric cyber security assessment of critical systems

We present a novel model-based, mission-centric approach to perform cyber security assessments for evaluating the impact of low-level cyber events on high-level mission objectives.We demonstrate the benefits of our approach using a system model and attack trees specific to the command-and-control system of a spacecraft. Specifically, we demonstrate how our approach enables a decision-maker to assess the security posture of the system, identify necessary mitigations and prioritize their deployment.

Tan, Kymie↗
NASA NTRSDate not supplied

Informing New Concepts for UAS and Autonomous System Safety Management using Disaster Management and First Responder Scenarios

As emerging flight operations become more prevalent and increasingly automated and distributed, the capabilities for managing safety of vehicles and operations will also need to evolve. To address this challenge, the National Academies has envisioned an In-Time Aviation Safety Management System (IASMS) capability for a wide range of aviation operations including current commercial operations as well as new entrants envisioned with advanced air mobility (AAM). The suite of IASMS services, functions, and capabilities (SFCs) would be implemented in a federated approach and would address trends as well as individual operations. Through predictive modeling and data analysis, IASMS is envisioned to identify arising risks so that they can be mitigated, in-time, before a safety incident occurs. IASMS and its requisite set of SFCs must leverage a wide range of information to perform. To better understand these new needs, FSF worked with the aviation and humanitarian communities to develop and validate scenarios that include traditional aviation operations and UAS operations intermingled as they are deployed for disaster management and first responder (DMFR) situations. The three scenarios developed include: • Post Natural disaster response, such as a hurricane, involving multiple parties utilizing traditional aviation and UAS to support rescue operations, surveil damage, and locate survivors needing assistance. • Wildfire fighting in remote locations with traditional aircraft for transport and fire-retardant delivery combined with UAS for surveillance of fire locations as well as to track individual firefighter locations. • Medical Operations and AAM in Urban Environments including passenger-carrying helicopters and AAM vehicles, medical missions (such as transport of radio-pharmaceuticals), and other UAS delivery operations (such as the delivery of defibrillators). Each scenario was developed and validated by representatives with expertise in humanitarian operations, urban and rural emergency response, air traffic management, UAS operations, and traditional flight operations. The scenario definitions address roles and responsibilities of individual actors, the appropriate utilization of UAS, and the actions taken by those actors to appropriately manage risks associated with the mission and environment. The risks to aviation traffic and to people on the ground explored included potential risks arising from incompatibilities in calculating reference altitudes (eg, differing uses of AGL, MSL, barometric, or GPS-derived values), loss of command and control (C2) communications, rapid changes in weather and winds, and physical interference. For each risk, IASMS SFCs were postulated in the context of monitoring services, risk assessment capabilities, and identifying appropriate mitigation strategies. The identified SFC capabilities were envisioned from known services postulated for IASMS and for UTM. For these unique environments, IASMS SFCs are needed to address conditions such as hazardous payloads, micro-climates and urban canyons, and the need to keep uninvolved air traffic out of the area where DMFR operations are being conducted. The second phase of analysis focused on inferring the specific information needs and the SFCs for IASMS, utilizing a structure of 16 information classes to organize requirements. For each of the risks identified in the workshops, it was postulated what data sources would be necessary to monitor critical aspects of the risk (eg, surrounding air traffic, ground population, terrain, etc). to be directly measured as well as data that would be derived, which implies additional SFCs for different actors to understand what information would likely be exchanged between parties. For an IASMS to be effective, additional research is needed to develop the advanced algorithms that can address the increasingly autonomous and complex operations in differing environments and to develop means of identifying unknown risks. Looking at these scenarios highlighted a number of research issues. These include the ability to quickly "cordon off" airspace thru temporary flight restrictions (TFRs) or other means, developing clear definitions to enable automation-based algorithms for prioritizing operations, defining airspace density metrics, standardization of altitude reporting, and establishing a basis for safety data metrics definition and collection. This paper seeks to outline the development of an IASMS in the context of the DMFR scenarios and resulting demonstrations. Utilizing this contextual approach, NASA will generate recommendations for an assured safety framework for AAM operations that enables AAM operations to safely access the NAS.

In Time Aviation Safety Management System↗
NASA NTRSDate not supplied

Internal Architecture of the Common Habitat

The core stage liquid oxygen tank of the Space Launch System can be manufactured as a habitat instead of as a propellant tank, with a common design such that it is equally suitable for use in 0g, 1/6g, 3/8g, 1g, or variable artificial gravity. This Common Habitat can be the central element of a human spaceflight architecture that encompasses the Moon, Mars, and other destinations within the inner solar system. The Common Habitat is specifically used within an alternative architecture study (that is not part of the current NASA baseline) as the core habitation element within a Lunar Basecamp, Mars Basecamp, and the Deep Space Exploration Vehicle. The Common Habitat internal architecture applies a design philosophy to separate crew functions according to deck. The lower deck is reserved for private functions. It includes eight private crew quarters and four waste and hygiene clusters – each with a private waste management compartment, private full body hygiene compartment, and foyer/clothes changing area. The mid deck is primarily allocated to mission-related working functions. It includes an exercise facility, fabrication / maintenance / repair facility, physical science laboratory (physics, geology, and astronomy), and life science laboratory (biology and human research). The mid deck also has four external hatches, clocked one every 90 degrees, centered on the vehicle vertical centerline. Each hatch has a 60-inch tall by 40-inch wide opening with the mid deck floor 16 inches below the bottom lip of the hatch opening. The upper deck is primarily allocated to group or social functions. It includes a large galley, wardroom with projector and display screen, plant growth chambers, bulk stowage, command and control station, medical facility, hygiene compartment, and vehicle subsystems. A Vertical Translation System, based in part on results from a GrabCAD public challenge, enables crew and equipment traverse between habitat decks in 0g, 1/6g, 3/8g, and 1g. A 40-inch by 60-inch vertical translation corridor ensures that anything that can fit through the external hatches can also be moved from deck to deck. The system includes three component systems: a deploying floor to safety barrier system that folds down to become a traversable floor when vertical translation is not in use and deploys to become a safety barrier during vertical translations; a folding ladder that stows in the ceiling when not in use; and an elevator platform that can attach to the ladder for cargo or incapacitated crew member transport. This system is complemented by a Horizontal Translation System, also based in part on the same GrabCAD challenge, provides for horizontal crew translation in microgravity but requires no vehicle reconfiguration for fractional or whole gravity operation. It relies primarily on gecko-inspired grippers, originally developed at Stanford and NASA JPL, attached to footwear to enable crew to emulate walking. Some handrails are also strategically placed throughout the Common Habitat to aid translation in both gravity and microgravity environments.

Common Habitat↗
NASA NTRSDate not supplied

Internal Architecture of the Common Habitat

The core stage liquid oxygen tank of the Space Launch System can be manufactured as a habitat instead of as a propellant tank, with a common design such that it is equally suitable for use in 0g, 1/6g, 3/8g, 1g, or variable artificial gravity. It is capable of sustaining a crew size of eight for missions up to 1200 days in duration. This Common Habitat can be the central element of a human spaceflight architecture that encompasses the Moon, Mars, and other destinations within the inner solar system. Within this archtiecture, the Common Habitat is specifically used as the core habitation element within a Lunar Base Camp, Mars Base Camp, and the Deep Space Exploration Vehicle. The Common Habitat internal architecture applies a design philosophy to separate crew functions according to deck. The lower deck is reserved for private functions. It includes eight private crew quarters and four waste and hygiene clusters – each with a private waste management compartment, private full body hygiene compartment, and private foyer/clothes changing area. The mid deck is primarily allocated to mission-related functions. It includes an exercise facility, fabrication / maintenance / repair facility, physical science laboratory (physics, geology, and remote sensing: astronomy, heliophysics, planetary science, and Earth science), and life science laboratory (biology and human research). The mid deck also has four external hatches, clocked one every 90 degrees, centered on the vehicle vertical centerline. Each hatch has a 60-inch tall by 40-inch wide opening with the mid deck floor 16 inches below the bottom lip of the hatch opening. The upper deck also includes some mission functions, but is primarily allocated to social functions. It includes a large galley, wardroom with projector and display screen, plant growth chambers, bulk stowage, command and control station, medical facility, hygiene compartment, and vehicle subsystems.

Habitability↗
NASA NTRSDate not supplied

Natural Language Processing Methods for Air Traffic Management Text and Speech Data

This presentation discusses two efforts of the NARI AI/ML Intern team during the Fall 2021 OSTEM Internship term. For Letters of Agreement (LoA), we have studied how LoAs are structured and explored the question ‘What is an LoA constraint?’ To do this, our approach is data-driven, iterative, and assisted by machine learning when available. In this presentation, we will walk through our tasks of manually scanning through documents, performing a preliminary entity labelling task, and our unsupervised analysis on LoA procedures sections. After this research phase, we define the smallest constraint unit in an LoA, and start to perform entity extraction. Looking towards constraint extraction, we are also exploring the use of a one-class support vector machine (OneClassSVM) model to identify patterns within the data. The second effort of our team this term is focused on Air Traffic Control System Command Center (ATCSCC) advisory meetings, and the subsequent advisory documents that get published from their content. These advisory documents are important to give readily accessible summaries of daily operations, so that data centers, airline officials, and other stakeholders can easily understand the context of these meetings in real time. In applying machine learning to this scenario, two natural language processing tasks are used. First is developing machine learning models to convert the meeting speech data into text. With this text, use of extractive and abstractive text summarization models are used to automatically generate preliminary versions of the advisory documents.

Natural Language Processing↗
NASA NTRSDate not supplied

Effects of Unmanned Aircraft Voice Communication Delay on En Route Air Traffic Management Operations

The present study investigated the effects of remotely piloted unmanned aircraft (UA) voice communication delay on air traffic management operations with different background sector traffic-volume levels. Three one-way UA voice delay lengths of 400, 900, and 2,000 milliseconds (ms) were tested, representing the currently estimated transmission delays for terrestrial, satellite communication (SATCOM), and long SATCOM Command and Control Link System, respectively. All delay values exceeded 390 ms, the FAA’s current requirement for the maximum communication latency in the National Airspace System. Eight retired en route air traffic controllers (ATCs) and eight remote pilots (RPs) participated in a human-inthe-loop simulation study, where a simulated UA flight transitioned through an Oakland en route low-altitude sector to a local non-towered airport. The results showed that, when the 2,000-ms voice delay was present, radio transmission step-ons and detect-and-avoid (DAA) alert level elevations increased. In addition, ATC workload, ATC acceptability for the UA, and RP acceptability for the DAA were negatively affected only when the UA had a 2,000-ms voice delay under the high traffic-volume condition, but not in the other conditions.

remotely piloted unmanned aircraft, voice delay, s↗
NASA NTRS2022

Effects of Unmanned Aircraft Voice Communication Delay on En Route Air Traffic Management Operations

The present study investigated the effects of remotely piloted unmanned aircraft (UA) voice communication delay on air traffic management operations with different background sector traffic-volume levels. Three one-way UA voice delay lengths of 400, 900, and 2,000 milliseconds (ms) were tested, representing the currently estimated transmission delays for terrestrial, satellite communication (SATCOM), and long SATCOM Command and Control Link System, respectively. All delay values exceeded 390 ms, the FAA’s current requirement for the maximum communication latency in the National Airspace System. Eight retired en route air traffic controllers (ATCs) and eight remote pilots (RPs) participated in a human-in-the-loop simulation study, where a simulated UA flight transitioned through an Oakland en route low-altitude sector to a local non-towered airport. The results showed that, when the 2,000-ms voice delay was present, radio transmission step-ons and detect-and-avoid (DAA) alert level elevations increased. In addition, ATC workload, ATC acceptability for the UA, and RP acceptability for the DAA were negatively affected only when the UA had a 2,000-ms voice delay under the high traffic-volume condition, but not in the other conditions.

remotely piloted unmanned aircraft, voice delay, s↗
NASA NTRS2022

Preliminary Characterization of Unmanned Air Cargo Routes Using Current Cargo Operations Survey

The introduction of regional cargo unmanned aircraft systems into the National Airspace System is anticipated within the coming years. Because they are remotely piloted, these aircraft are expected to utilize increasing aircraft automation and autonomy, require special infrastructure accommodations for navigation, communication, command and control and potentially need special treatment from air traffic control. In order to assess the accessibility and impacts of these operations across the national airspace, this preliminary study investigates current and estimated future demand for air cargo operations in the continental United States. Air cargo demand is broken down by aircraft type and airport categories to produce a rough nation-wide classification of cargo operations. Then, the state of Texas is investigated as a focus region, where the impacts of regional cargo unmanned aircraft systems on the airspace are investigated in further detail. The potential technologies that can assist in regional cargo unmanned aircraft system accessibility are defined at airports across the focus region. A single airport, Fort Worth Alliance, is highlighted to discuss airport-level statistics. Finally, a qualitative classification of airports by the type of cargo operations is suggested.

Unmanned Aircraft↗
NASA NTRS2022

Preliminary Characterization of Unmanned Air Cargo Routes Using Current Cargo Operations Survey

The introduction of regional cargo unmanned aircraft systems into the National Airspace System is anticipated within the coming years. Because they are remotely piloted, these aircraft are expected to utilize increasing aircraft automation and autonomy, require special infrastructure accommodations for navigation, communication, command and control and potentially need special treatment from air traffic control. In order to assess the accessibility and impacts of these operations across the national airspace, this preliminary study investigates current and estimated future demand for air cargo operations in the continental United States. Air cargo demand is broken down by aircraft type and airport categories to produce a rough nation-wide classification of cargo operations. Then, the state of Texas is investigated as a focus region, where the impacts of regional cargo unmanned aircraft systems on the airspace are investigated in further detail. The potential technologies that can assist in regional cargo unmanned aircraft system accessibility are defined at airports across the focus region. A single airport, Fort Worth Alliance, is highlighted to discuss airport-level statistics. Finally, a qualitative classification of airports by the type of cargo operations is suggested.

Unmanned Aircraft, Unmanned Aircraft Systems, UAS,↗
NASA NTRS2022

RF Environment Data Analysis for UAS Operations

As the usage of radio frequency spectrum and uncrewed aircraft systems continue to grow, the radio frequency environment and its implications to flight safety should be understood. This is important to ensure control and command links as well as data collection links maintain strong communications during flight. NASA System-Wide Safety (SWS) is currently developing standards of flight safety but lacks methods for establishing confidence in the availability of radio frequency space to make a go/no-go decision for drone flights. This study examines information about the radio modules used by SWS and how they interact with the RF environment though analysis of historical spectrum data. This review studies the potential effectiveness of observing the power spread and occupancy methods as they apply to the flight system radios. It has been determined that viewing the frequency and time when the environment is greater than a threshold which indicates potential interference levels may give insight into the patterns of spectrum usage.

Radio Frequency↗
NASA NTRS2022

NASA's Responsible AI Plan

Artificial Intelligence (AI) is an integral part of today’s process of conducting science and technology development. At NASA, AI has become an integral and important tool for researchers, engineers, data scientists, and technologists in pursuing the ground-breaking discoveries that we are known for, including the command and controlling of our spacecraft and other supporting infrastructures. Consequently, research and engineering efforts incorporating AI have permeated almost every area of our work. It is contributing to NASA’s drive toward the future, not just of space science, but for society here at home. We are dedicated to continuing the use of AI in a safe and fully transparent approach so that the public can have high confidence in the outcomes and benefits. We believe that the plan outlined here will be responsive and contribute to the call for openness across the federal government. NASA is committed to responsible use of AI in all of its activities and in all phases of development and deployment of its space and terrestrial programs missions. NASA does not deliberately focus on “AI Research” as a separate field (we have no single “AI office” or “AI program”), rather NASA uses AI to build tools for its programs. This plan, being put forward, adheres to the Responsible AI (RAI) principles set and laid down by the White House in its Presidential Executive Order 13960. Our research, engineering and technical communities have been made aware of these guidelines and we are committed to an on-going process of educating and monitoring its implementation to ensure adherence to those principles. The vast majority of NASA’s use cases, which number almost 75 today, are geared toward analyzing the petabytes of data that NASA collects from its fleet of spacecraft across all disciplines, in human space exploration, and in aeronautics, etc.

Artificial Intelligence↗
NASA NTRS2022

Spectrum Research for Aviation Final Report

Task TO-G-026 was established to identify possible spectrum allocations to support the Scalable Traffic Management for Emergency Response Operations (STEReO) Project’s approach of applying Unmanned Aircraft Systems (UAS) Traffic Management (UTM) concepts to the management of disaster response. Both large and small unmanned aircraft have been found to provide significant benefits in disaster response. However, application of unmanned aircraft is limited by the difficulty in managing disaster area airspace. UTM concepts can greatly increase the ability to safely apply UAS to many disaster response requirements. The use of UAS requires communication links to provide command and control, telemetry, delivery of mission payload data, and situational awareness/navigation functionality to enable safe operations. The outcome of Task TO-G-026 research provides guidance in identifying appropriate potential spectrum bands required to support STEReO disaster response operations. This report presents these research results.

Robert J. Kerczewski↗