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GIDEP Batching Tool

This software provides internal, automated search mechanics of GIDEP (Government- Industry Data Exchange Program) Alert data imported from the GIDEP government Web site. The batching tool allows the import of a single parts list in tab-delimited text format into the local JPL GIDEP database. Delimiters from every part number are removed. The original part numbers with delimiters are compared, as well as the newly generated list without the delimiters. The two lists run against the GIDEP imports, and output any matches. This feature only works with Netscape 2.0 or greater, or Internet Explorer 4.0 or greater. The user selects the browser button to choose a text file to import. When the submit button is pressed, this script will import alerts from the text file into the local JPL GIDEP database. This batch tool provides complete in-house control over exported material and data for automated batch match abilities. The batching tool has the ability to match capabilities of the parts list to tables, and yields results that aid further research and analysis. This provides more control over GIDEP information for metrics and reports information not provided by the government site. This software yields results quickly and gives more control over external data from the government site in order to generate other reports not available from the external source. There is enough space to store years of data. The program relates to risk identification and management with regard to projects and GIDEP alert information encompassing flight parts for space exploration.

Fong, Danny↗

Architecting the Human Space Flight Program with Systems Modeling Language (SysML)

The next generation of missions in NASA's Human Space Flight program focuses on the development and deployment of highly complex systems (e.g., Orion Multi-Purpose Crew Vehicle, Space Launch System, 21st Century Ground System) that will enable astronauts to venture beyond low Earth orbit and explore the moon, near-Earth asteroids, and beyond. Architecting these highly complex system-of-systems requires formal systems engineering techniques for managing the evolution of the technical features in the information exchange domain (e.g., data exchanges, communication networks, ground software) and also, formal correlation of the technical architecture to stakeholders' programmatic concerns (e.g., budget, schedule, risk) and design development (e.g., assumptions, constraints, trades, tracking of unknowns). This paper will describe how the authors have applied System Modeling Language (SysML) to implement model-based systems engineering for managing the description of the End-to-End Information System (EEIS) architecture and associated development activities and ultimately enables stakeholders to understand, reason, and answer questions about the EEIS under design for proposed lunar Exploration Missions 1 and 2 (EM-1 and EM-2).

scheduling↗

Feasibility of a Networked Air Traffic Infrastructure Validation Environment for Advanced NextGen Concepts

Abstract-Next Generation Air Transportation System (NextGen) applications reliant upon aircraft data links such as Automatic Dependent Surveillance-Broadcast (ADS-B) offer a sweeping modernization of the National Airspace System (NAS), but the aviation stakeholder community has not yet established a positive business case for equipage and message content standards remain in flux. It is necessary to transition promising Air Traffic Management (ATM) Concepts of Operations (ConOps) from simulation environments to full-scale flight tests in order to validate user benefits and solidify message standards. However, flight tests are prohibitively expensive and message standards for Commercial-off-the-Shelf (COTS) systems cannot support many advanced ConOps. It is therefore proposed to simulate future aircraft surveillance and communications equipage and employ an existing commercial data link to exchange data during dedicated flight tests. This capability, referred to as the Networked Air Traffic Infrastructure Validation Environment (NATIVE), would emulate aircraft data links such as ADS-B using in-flight Internet and easily-installed test equipment. By utilizing low-cost equipment that is easy to install and certify for testing, advanced ATM ConOps can be validated, message content standards can be solidified, and new standards can be established through full-scale flight trials without necessary or expensive equipage or extensive flight test preparation. This paper presents results of a feasibility study of the NATIVE concept. To determine requirements, six NATIVE design configurations were developed for two NASA ConOps that rely on ADS-B. The performance characteristics of three existing in-flight Internet services were investigated to determine whether performance is adequate to support the concept. Next, a study of requisite hardware and software was conducted to examine whether and how the NATIVE concept might be realized. Finally, to determine a business case, economic factors were evaluated and a preliminary cost-benefit analysis was performed.

McCormack, Michael J.↗

Architecture of High-Altitude Operations (HAO) Discovery and Synchronization Service (DSS)

The aviation industry is evolving at an unprecedented pace, necessitating the development of efficient, secure, and interoperable systems to manage increasingly complex air traffic. Moreover, the demand for High-Altitude Operations (HAO) is increasing. Furthermore, air traffic control services are limited in HAO environments. HAO industry participants will need airspace access and flexibility to perform their missions in this airspace that provides provisions for scalability. The Discovery and Synchronization Service (DSS) will be a cornerstone of the HAO ecosystem, enabling the effective sharing of critical airspace data, including operational intent, aircraft trajectories, and airspace usage among various stakeholders and operators. The DSS architecture addresses these challenges with a distributed, decentralized, and interoperable system that facilitates seamless integration across diverse airspaces. It prioritizes secure data exchange while safeguarding data ownership. This white paper presents the vision, architecture, and benefits of the DSS for HAO, underscoring its potential to streamline operations, reduce redundancies, and establish a foundation for safe and efficient airspace management.

HAO↗

The Utilization Profiles of the CCSDS Unified Space Link Protocol (USLP)

The purpose of this paper is to identify the utilization profiles for interfacing the Data Protocol Sublayer using the Unified Space Link Protocols (USLP) (reference 1) with the space link coding procedures as specified in the CCSDS Coding & Synchronization Blue Books (references 2 through 5), used in both telecommand and telemetry applications. This paper describes how the USLP Protocol utilizes the coding and synchronization sublayer to support: a. Direct to Earth (DTE) telemetry links for engineering and science data b. Direct to Earth (DTE) telemetry links for very high rate science data c. Direct from Earth (DFE) command, sequencing and flight software loads d. Space to Space Links (Proximity) utilized by orbiters for data exchange to/from surface bound assets. The CCSDS has divided the functions of the Data Link Layer into two sublayers: the Data Link Protocol Sublayer (DLP-SL) and the Coding and Synchronization Sublayer (CS-SL). The Data Link Protocol Sublayer (DLP-SL) interfaces to the users, accepting the data that is to be transported, on the sending side of the link, and delivering that data on the receiving end. The Transfer Frame is the data unit that is transferred across the Data Link Protocol Sublayer and the Coding and Synchronization Sublayer boundary. The Coding and Synchronization Sublayer (CS-SL) provides the encoding, randomization, and frame synchronization functions that prepares the USLP Transfer Frame for transport across the space link. The CS-SL is divided into 2 processes: 1) The Frame Interface Processes (FIP) performs the interface functions required to prepare the data for delivery to the Coding/Decoding Process (CDP). This process includes prepending a Frame Start Marker to the provided frame, when management has designated that the frame is not to be aligned to the codeblock or when there is no block code used. 2) The Coding/Decoding Process (CDP) performs the forward error correction processes that are used to optimize the performance of the link and minimize the error rate. The CDP creates the symbol stream that is delivered to the Physical Layer. The transfer of the USLP transfer frames across different types of space links is the focus of this paper. The Protocol Data Unit (PDU) that is passed in both directions between the Data Link Protocol Sublayer (DLP-SL) and Coding and Synchronization Sublayer (CS-SL) is the transfer frame. The USLP frame structure provides flexibility that can be constrained by the functions utilized within the CS-SL that prepare the transfer frame for transit. For example, the USLP transfer frame contains a length field that enables the frame to be of variable length but CS-SL under certain conditions may constrain the frame to be fixed in length. This paper describes 5 operational modes available for use by the Data Link Layer to provide data exchange across the USLP space link. These modes are different because different operational requirements apply to vastly different types of space links and thus the communications implementation requirements differ. The environmental issues include the power or energy available, the distance between the end points of the link, the complexity of the equipment available at those end points, the atmospheric conditions and radiometric frequency selection. The CS-SL utilizes different forward error correcting codes supported by specific operational modes to configure the data for transit. This paper describes all of the operational modes in a series of data models which decompose the functionality between the Data Link Protocol Sublayer and the Coding and Synchronization sublayer. The operational modes described are: 1. Uncoded Mode: has been used for short links that contain significant available power to provide an acceptable frame error rate. The frames in this mode can be variable in length and typically use an error detection algorithm (i.e., CRC) to determine if there are errors in the received frame. 2. Convolutional Only Mode: is currently the prime forward error correction coding used for the proximity links. The frames in this mode can be variable in length and typically use an error detection algorithm (i.e., CRC) to determine if there are errors in the received frame. 3. Variable Length Frame Aligned to Variable Length Codeblock (TC): is used for Direct from Earth links were power levels are high and the simple, least complex code i.e., the BCH code is used. This mode has been in use since the early 1970s. The BCH code is a short code and the decoder is easy to implement. 4. Fixed Length Frame Aligned to Fixed Length Codeblock (AOS/TM): was introduced when the concatenated Convolutional and Reed-Solomon Code was formulated to provide significant reduction in link data error rate and the ability to determine if there was an error in the decoded codeblock. The frame is aligned to the codeblock so that there is a one to one relationship of frame errors to codeblock errors without additional error detection coding being added. This mode requires the protocol frames to be the exact size of the message portion of the codeblock. 5. Frames Unaligned to Fixed Length Codeblocks (Currently used for very high rates and space to space links): This mode is currently used for missions that have a very high data rate that can be controlled adaptively as the environment changes and as the next generation operating mode for the proximity link. This mode from a coded data stream point of view is exactly like that described in 4. above, except that the frame need not be aligned to the codeblock. There is no requirement on frame length when using this mode. Thus when using USLP it can be used to support links that require short or long frames. There is also no mandatory requirement that frames cannot be separated by idle data reducing the tight data rate connection requirements between the data link protocol sublayer and the coding & synchronization sublayer. In conclusion, how these operational modes can be put to use in mission operational scenarios is described for Direct from Earth links (DFE), Direct to Earth links (DTE), and Proximity links.

Greenberg, E.↗

Insights Gained from the Ongoing Integrated Arrival/Departure/Surface (IADS) Traffic Flow Operational Prototype

The Insights Gained from the Ongoing Integrated Arrival/Departure/Surface (IADS) Traffic Flow Operational Prototype presentation will include a definition of the learning objectives for the audience, an overview/explanation of the ATD-2 project, an overview of the ATC/Operator data exchange and integration that is foundational for advanced surface capability, and a description of the ATC/Operator data exchange and integration research questions and insights. It will also give an overview of the overhead stream around CLT and a preview of the operational integration benefits, research questions, and insights related to the overhead stream. It will continue with a surface metering process flow overview, a description of local surface demand/capacity imbalance, the benefits of collaborative surface metering, the associated research questions and insights, and wrap up with the next steps planned for ATD-2.

collaborative operational environment↗

A Blockchain Case Study for Urban Air Mobility Operational Intent

To realize the potential of Urban Air Mobility (UAM), an assurance of cybersecurity is critical for public acceptance. UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) aircraft to overcome increasing surface congestion. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. The intent of this work is to leverage a permissioned blockchain to simulate secure data exchange and storage for the UAM operational intent use case. In this case study, two vehicle operators are operating in the same airspace. Their intent is to fly vehicles that land at a shared vertiport, securely.

Urban Air Mobility↗

A Blockchain Case Study for Urban Air Mobility Operational Intent

To realize the potential of Urban Air Mobility (UAM), an assurance of cybersecurity is critical for public acceptance. UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) aircraft to overcome increasing surface congestion. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. The intent of this work is to leverage a permissioned blockchain to simulate secure data exchange and storage for the UAM operational intent use case.

UAM↗

A Blockchain Case Study for Urban Air Mobility Operational Intent

To realize the potential of Urban Air Mobility (UAM), an assurance of cybersecurity is critical for public acceptance. UAM is a concept that proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical takeoff and landing (VTOL) aircraft to overcome increasing surface congestion. The growth in the development of UAM systems, and the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. The intent of this work is to leverage a permissioned blockchain to simulate secure data exchange and storage for the UAM operational intent use case.

UAM↗

Flight Demonstration of the Tailored Arrival Manager

A flight demonstration of arrival traffic management automation was conducted in partnership between NASA, FAA and Boeing as an element of the latter’s ecoDemonstrator2020 flight program. For the demonstration, NASA’s prototype Tailored Arrival Manager(TAM) was used to compute efficient trajectory-based solutions to traffic management problems representing those encountered during time-based metering operations today. TAM solutions involving route modifications were uplinked to a Boeing 787 airplane using Controller Pilot Data Link Communications and seamlessly loaded into the airplane’s Flight Management System (FMS). The paper describes the concept and technology behind TAM along with the data exchanges and procedures involved with the demonstration. All TAM solutions were delivered in a timely manner and successfully integrated with the airplane’s FMS, thereby demonstrating the basic feasibility of trajectory-based arrival management using currently available data communications and avionics equipage. Although TAM solutions were not executed during this initial demonstration, a limited study of trajectory prediction accuracy was possible given that the airplane flew uninterrupted, automated descents with known route and speed intent. Analysis revealed that TAM meter-fix arrival time predictions were accurate to within ± 30 seconds for time horizons of 30 minutes or less, which matched closely with FMS predictions acquired through real-time data exchange. Top-of-descent predictions over similar time horizons were found accurate to within ± 5 nautical miles.

air traffic management↗

Flight Demonstration of the Tailored Arrival Manager

A flight demonstration of arrival traffic management automation was conducted in partnership between NASA, FAA and Boeing as an element of the latter’s ecoDemonstrator2020 flight program. For the demonstration, NASA’s prototype Tailored Arrival Manager(TAM) was used to compute efficient trajectory-based solutions to traffic management problems representing those encountered during time-based metering operations today. TAM solutions involving route modifications were uplinked to a Boeing 787 airplane using Controller Pilot Data Link Communications and seamlessly loaded into the airplane’s Flight Management System (FMS). The paper describes the concept and technology behind TAM along with the data exchanges and procedures involved with the demonstration. All TAM solutions were delivered in a timely manner and successfully integrated with the airplane’s FMS, thereby demonstrating the basic feasibility of trajectory-based arrival management using currently available data communications and avionics equipage. Although TAM solutions were not executed during this initial demonstration, a limited study of trajectory prediction accuracy was possible given that the airplane flew uninterrupted, automated descents with known route and speed intent. Analysis revealed that TAM meter-fix arrival time predictions were accurate to within ± 30 seconds for time horizons of 30 minutes or less, which matched closely with FMS predictions acquired through real-time data exchange. Top-of-descent predictions over similar time horizons were found accurate to within ± 5 nautical miles.

Air traffic managment↗

NASA’s Secured Airspace for Urban Air Mobility (UAM)

The Urban Air Mobility (UAM) architecture is leveraged from the Unmanned Traffic Management (UTM) concept of operations. Within the UAM environment, UAM operators work collaboratively to manage aerial vehicles in the urban environment. Providers of Services for UAM (PSU), UAM operators, and Supplemental Data Service Providers (SDSP) provide services to support flight operations within that environment. As a recognized need, various views of UAM flight information are provided to the public and public safety entities. To accomplish this, among other goals, the Federal Aviation Administration (FAA) can coordinate flight information between the FAA controlled National Airspace System (NAS) and the UAM environments through the FAA-Industry Data Exchange Protocol (FIDXP). This concept of UAM proposes to develop short-range, point-to-point transportation systems in metropolitan areas using vertical take-off and landing (VTOL) or short take-off and landing (STOL) aircraft to overcome increasing surface congestion. To garner the support of UAM and to realize its potential, an assurance of cybersecurity is critical for public acceptance. Understanding the various components communicating with one-another cybersecurity, like in other industries, has come to the forefront highlighting the need to protect these networks and systems from cyberattacks. With the planned growth and reach of UAM systems, it’s clear that the associated data exchange and service interactions will be at risk due to numerous types of cybersecurity attacks. Consequently, as these threats evolve, the UAM cybersecurity capabilities must adapt to these changes as well. While learning is always the goal, the overall intent of this workshop is to make recommendations on the following: (1) how future UAM environments can be protected against cyber-attacks, and (2) what mechanisms should be put in place to detect attacks against UAM environments.

UAM↗

Ramp Technology and Intelligent Processing in Small Manufacturing

To address the issues of excessive inventories and increasing procurement lead times, the Navy is actively pursuing flexible computer integrated manufacturing (FCIM) technologies, integrated by communication networks to respond rapidly to its requirements for parts. The Rapid Acquisition of Manufactured Parts (RAMP) program, initiated in 1986, is an integral part of this effort. The RAMP program's goal is to reduce the current average production lead times experienced by the Navy's inventory control points by a factor of 90 percent. The manufacturing engineering component of the RAMP architecture utilizes an intelligent processing technology built around a knowledge-based shell provided by ICAD, Inc. Rules and data bases in the software simulate an expert manufacturing planner's knowledge of shop processes and equipment. This expert system can use Product Data Exchange using STEP (PDES) data to determine what features the required part has, what material is required to manufacture it, what machines and tools are needed, and how the part should be held (fixtured) for machining, among other factors. The program's rule base then indicates, for example, how to make each feature, in what order to make it, and to which machines on the shop floor the part should be routed for processing. This information becomes part of the shop work order. The process planning function under RAMP greatly reduces the time and effort required to complete a process plan. Since the PDES file that drives the intelligent processing is 100 percent complete and accurate to start with, the potential for costly errors is greatly diminished.

Rentz, Richard E.↗

CCSDS - An approach to the definition of common standards for understanding space-related data

International cooperation for space data projects requires common data processing goals and unique data exchange mechanisms. The absence of standards has led to project unique interface definitions and special software on diverse systems. To address this problem, CCSDS Panel 2 is creating a set of standards to support self description of data using standard structures. The proposed standard data interchange mechanism - the Standard Formatted Data Unit (SFDU) - reduces information loss in data transfers, increases automated information exchange, and extends the lifetime of data. Data interchange structures, languages, and services are being developed with necessary control functions to provide these benefits. A set of recommendations for agency review has been issued this year to be the basis for future data exchange and to enhance access to older mission data sets. Space agencies and other space data handling facilities are being encouraged to implement the SFDU concept for ongoing and planned projects.

Drexler, Manfred↗

Querying Semi-Structured Data

The amount of data of all kinds available electronically has increased dramatically in recent years. The data resides in different forms, ranging from unstructured data in the systems to highly structured in relational database systems. Data is accessible through a variety of interfaces including Web browsers, database query languages, application-specic interfaces, or data exchange formats. Some of this data is raw data, e.g., images or sound. Some of it has structure even if the structure is often implicit, and not as rigid or regular as that found in standard database systems. Sometimes the structure exists but has to be extracted from the data. Sometimes also it exists but we prefer to ignore it for certain purposes such as browsing. We call here semi-structured data this data that is (from a particular viewpoint) neither raw data nor strictly typed, i.e., not table-oriented as in a relational model or sorted-graph as in object databases. As will seen later when the notion of semi-structured data is more precisely de ned, the need for semi-structured data arises naturally in the context of data integration, even when the data sources are themselves well-structured. Although data integration is an old topic, the need to integrate a wider variety of data- formats (e.g., SGML or ASN.1 data) and data found on the Web has brought the topic of semi-structured data to the forefront of research. The main purpose of the paper is to isolate the essential aspects of semi- structured data. We also survey some proposals of models and query languages for semi-structured data. In particular, we consider recent works at Stanford U. and U. Penn on semi-structured data. In both cases, the motivation is found in the integration of heterogeneous data.

DATA MANAGEMENT↗

Development and Evaluation of an Airborne Separation Assurance System for Autonomous Aircraft Operations

NASA Langley Research Center is developing an Autonomous Operations Planner (AOP) that functions as an Airborne Separation Assurance System for autonomous flight operations. This development effort supports NASA s Distributed Air-Ground Traffic Management (DAG-TM) operational concept, designed to significantly increase capacity of the national airspace system, while maintaining safety. Autonomous aircraft pilots use the AOP to maintain traffic separation from other autonomous aircraft and managed aircraft flying under today's Instrument Flight Rules, while maintaining traffic flow management constraints assigned by Air Traffic Service Providers. AOP is designed to facilitate eventual implementation through careful modeling of its operational environment, interfaces with other aircraft systems and data links, and conformance with established flight deck conventions and human factors guidelines. AOP uses currently available or anticipated data exchanged over modeled Arinc 429 data buses and an Automatic Dependent Surveillance Broadcast 1090 MHz link. It provides pilots with conflict detection, prevention, and resolution functions and works with the Flight Management System to maintain assigned traffic flow management constraints. The AOP design has been enhanced over the course of several experiments conducted at NASA Langley and is being prepared for an upcoming Joint Air/Ground Simulation with NASA Ames Research Center.

Barhydt, Richard↗

ATD-2 Update for TBFM/TFDM Ops Teams

This presentation was developed to update the TBFM/TFDM operational teams on ATD-2 Phase 2 progress and Phase 3 plans. It includes top-level compliance data and APREQ delay data, processes for data exchange between ATD-2 and TBFM and surface metering, and potential benefits of EOBTs.

ATD-2↗

UTM Data Working Group Demonstration 1: Final Report

This document summarizes activities defining and executing the first demonstration of the NASA-FAA Research Transition Team (RTT) Data Exchange and Information Architecture (DEIA) working group (DWG). The demonstration focused on testing the interactions between two key components in the future UAS Traffic Management (UTM) System through a collaborative and distributed simulation of key scenarios. The summary incorporates written feedback from each of the participants in the demonstration. In addition to reporting the activities, this report also provides some insight into future steps of this working group.

UAS Traffic Management↗