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NASA NTRSDate not supplied

A Data Analysis and Simulation Study of Urban Air Mobility

For the Urban Air Mobility (UAM) industry, NASA has defined a series of UAM Maturity Levels (UML) corresponding to increasingly more complex and operationally dense UAM operations. In support of the gradual progression towards higher UML levels, NASA is currently conducting a set of UAM air traffic simulations—collectively referred to as X4. This paper describes a set of system effectiveness measures, and their associated metrics, for data analysis of X4 simulations. The descriptions, rationales, and calculation procedures for two metrics to be used in data analysis of simulation results, the number of predicted demand-capacity imbalances and the pre-departure delays, are described. Results from data analysis of one set of simulation runs are presented to demonstrate how these metrics support the assessment of performance of the system architecture for X4 simulations and the verification of experiment requirements.

Urban Air Mobility↗

NASA NTRSDate not supplied

A PPE Use Case on Configuration Management Approach for MBSE

Systems engineers worldwide have been working to implement Model-based Systems Engineering (MBSE) environments, tools, and methodologies. MBSE is a formalized application of modeling to support systems engineering, including requirements, design, analysis, verification, and validation activities over the project’s lifecycle[1]; MBSE captures the system data into a digital environment. Significant benefits of MBSE includes a reduction in the time in performing systems engineering activities and an improvement higher fidelity data production. As more Systems Engineers are using MBSE, the models it produces are becoming the source of truth for Systems Engineering artifacts. As we move towards using these models as the source of truth, a more rigorous Configuration Management (CM) infrastructure is needed. Many of the MBSE tools provide CM options but utilizing them efficiently and effectively can be challenging. More rigorous methods and tools are needed to assist with keeping track of changes in the model, making sure inadvertent changes to baseline data did not occur, visibility of changes in the different model versions, and the impacts of changes to the models. System engineers and configuration management personnel from the Power and Propulsion Element (PPE) project at NASA Glenn Research Center have been working to develop a modeling construct that allows models to be the source of truth and maintain a configuration managed baseline. This paper presents a process that leverages the existing CM tools and describes how PPE used this process to manage changes more rigorously. It will describe the process behind building the model architecture that utilizes the MBSE tool capabilities and the configuration management process. It will contain some of the advantages and disadvantages of the architecture that the PPE project had settled upon utilizing, as well as some enhanced capabilities that the PPE MBSE team has developed.

MBSE↗

NASA NTRS2022

Perseverance Rover’s Robotic Arm and Turret Mounted Instruments’ Surface Commissioning

The Robotic Arm (RA) on the Perseverance rover is an integral component of the Sampling and Caching System necessary for completing the science goals of the Mars 2020 mission. While the Perseverance rover was based on the Curiosity rover which landed in 2012, the Robotic Arm was redesigned to carry a much larger turret with a new suite of payloads. Shortly after Perseverance landed in Jezero Crater, a series of checkouts was completed with the RA during the first 100 sols of the mission in order to ensure proper functionality of the RA and the instruments mounted on the turret. This period of time in the mission was called Surface Operations Transition (SOX). The objective of SOX was to systematically execute checkout activities for all the basic functionality so that the RA and instruments, as well as other rover components, could be released for scientific exploration.RA activities during SOX can be divided into a few different categories: Mechanism Checkouts, Rover Visual Inspections, Performance Characterization, and Instrument Functional Checkouts. Many of these checkouts built off of each other such that each subsequent activity would verify incrementally complex functionality. Many of the defined activities were executed several times throughout the development of the rover and served as a check that the RA’s performance is consistent with testing on Earth. Other activities were developed uniquely for SOX to respond to challenges discovered during development. They were designed to be verifiable without the help of ground support equipment or previous executions on the flight hardware to compare against.This paper discusses the formulation and conception of the various RA SOX checkout activities, verification and testing required to certify them for flight, execution of the activities on Mars, issues encountered, and finally results and findings as the mission transitioned to nominal science operations. We will be presenting the results and analysis using downlinked imaging and data from the flight vehicle to show how we verified the performance of the Robotic Arm and the turret mounted instruments in order to transition to science operations with a clean bill of health.

Edgett, Kenneth↗

NASA NTRS2022

Integrating FRET with Copilot: Automated Translation of Natural Language Requirements to Runtime Monitors

Runtime verification (RV) enables monitoring systems at runtime, to detect property violations early and limit their potential consequences. To provide the level of assurance required for ultra-critical systems, monitor specifications must faithfully reflect the original mission requirements, which are often written in ambiguous natural language. This paper presents an end-to-end framework to capture requirements in structured natural language and generate monitors that capture their semantics faithfully. We leverage NASA’s Formal Requirement Elicitation Tool (FRET), and the RV system Copilot. We extend FRET with mechanisms to capture additional information needed to generate monitors, and introduce OGMA, a new tool to bridge the gap between FRET and Copilot. With this framework, users can write requirements in an intuitive format and obtain real-time C monitors suitable for use in embedded systems. Our tool chain is available as open source.

FRET↗

NASA NTRS2020

Bridging the Gap Between Requirements and Model Analysis : Evaluation on Ten Cyber-Physical Challenge Problems

Formal verfication and simulation are powerful tools to validate requirements against complex systems. [Problem] Requirements are developed in early stages of the software lifecycle and are typically written in ambiguous natural language. There is a gap between such requirements and formal notations that can be used by verification tools, and lack of support for proper association of requirements with software artifacts for verification. [Principal idea] We propose to write requirements in an intuitive, structured natural language with formal semantics, and to support formalization and model/code verification as a smooth, well-integrated process. [Contribution] We have developed an end-to-end, open source requirements analysis framework that checks Simulink models against requirements written in structured natural language. Our framework is built in the Formal Requirements Elicitation Tool (fret); we use fret's requirements language named fretish, and formalization of fretish requirements in temporal logics. Our proposed framework contributes the following features: 1) automatic extraction of Simulink model information and association of fretish requirements with target model signals and components; 2) translation of temporal logic formulas into synchronous dataflow cocospec specifications as well as Simulink monitors, to be used by verification tools; we establish correctness of our translation through extensive automated testing; 3) interpretation of counterexamples produced by verification tools back at requirements level. These features support a tight integration and feedback loop between high level requirements and their analysis. We demonstrate our approach on a major case study: the Ten Lockheed Martin Cyber-Physical, aerospace-inspired challenge problems.

Mavridou, Anastasia↗

NASA NTRS2010

Aerospace Payloads Leak Test Methodology

Pressurized and sealed aerospace payloads can leak on orbit. When dealing with toxic or hazardous materials, requirements for fluid and gas leakage rates have to be properly established, and most importantly, reliably verified using the best Nondestructive Test (NDT) method available. Such verification can be implemented through application of various leak test methods that will be the subject of this paper, with a purpose to show what approach to payload leakage rate requirement verification is taken by the National Aeronautics and Space Administration (NASA). The scope of this paper will be mostly a detailed description of 14 leak test methods recommended.

Lvovsky, Oleg↗

NASA NTRS2010

Analysis, Simulation, and Verification of Knowledge-Based, Rule-Based, and Expert Systems

Mathematically sound techniques are used to view a knowledge-based system (KBS) as a set of processes executing in parallel and being enabled in response to specific rules being fired. The set of processes can be manipulated, examined, analyzed, and used in a simulation. The tool that embodies this technology may warn developers of errors in their rules, but may also highlight rules (or sets of rules) in the system that are underspecified (or overspecified) and need to be corrected for the KBS to operate as intended. The rules embodied in a KBS specify the allowed situations, events, and/or results of the system they describe. In that sense, they provide a very abstract specification of a system. The system is implemented through the combination of the system specification together with an appropriate inference engine, independent of the algorithm used in that inference engine. Viewing the rule base as a major component of the specification, and choosing an appropriate specification notation to represent it, reveals how additional power can be derived from an approach to the knowledge-base system that involves analysis, simulation, and verification. This innovative approach requires no special knowledge of the rules, and allows a general approach where standardized analysis, verification, simulation, and model checking techniques can be applied to the KBS.

Hinchey, Mike↗

NASA NTRS2013

Application Program Interface for the Orion Aerodynamics Database

The Application Programming Interface (API) for the Crew Exploration Vehicle (CEV) Aerodynamic Database has been developed to provide the developers of software an easily implemented, fully self-contained method of accessing the CEV Aerodynamic Database for use in their analysis and simulation tools. The API is programmed in C and provides a series of functions to interact with the database, such as initialization, selecting various options, and calculating the aerodynamic data. No special functions (file read/write, table lookup) are required on the host system other than those included with a standard ANSI C installation. It reads one or more files of aero data tables. Previous releases of aerodynamic databases for space vehicles have only included data tables and a document of the algorithm and equations to combine them for the total aerodynamic forces and moments. This process required each software tool to have a unique implementation of the database code. Errors or omissions in the documentation, or errors in the implementation, led to a lengthy and burdensome process of having to debug each instance of the code. Additionally, input file formats differ for each space vehicle simulation tool, requiring the aero database tables to be reformatted to meet the tool s input file structure requirements. Finally, the capabilities for built-in table lookup routines vary for each simulation tool. Implementation of a new database may require an update to and verification of the table lookup routines. This may be required if the number of dimensions of a data table exceeds the capability of the simulation tools built-in lookup routines. A single software solution was created to provide an aerodynamics software model that could be integrated into other simulation and analysis tools. The highly complex Orion aerodynamics model can then be quickly included in a wide variety of tools. The API code is written in ANSI C for ease of portability to a wide variety of systems. The input data files are in standard formatted ASCII, also for improved portability. The API contains its own implementation of multidimensional table reading and lookup routines. The same aerodynamics input file can be used without modification on all implementations. The turnaround time from aerodynamics model release to a working implementation is significantly reduced

Robinson, Philip E.↗

NASA NTRS2018

External Contamination Integration of Visiting Vehicles on the International Space Station

The International Space Station (ISS) is an on-orbit platform for science utilization in low Earth orbit. The induced contamination environment can impact performance, mission success, and science utilization. Cargo and crew vehicles visiting the ISS represent significant sources of contamination. The Space Environments Team of the ISS Program Office has developed visiting vehicle requirements and methodologies to address the increasingly complex challenge of integrating multiple visiting vehicles while maintaining overall ISS contamination control requirements. The external contamination control requirements are summarized and the integration and verification process is described along with required data deliverables. Contamination characterization data deliverables address vacuum-exposed materials, thrusters, vacuum venting, and particulate releases. Visiting vehicle external contamination analyses are conducted by the ISS Space Environments Team to certify compliance with external contamination control requirements. Unpressurized cargo contamination analyses are also performed to characterize induced contamination to payloads while in transit to ISS. Efforts to confirm the visiting vehicle contamination modeling and analysis process based on on-orbit data are discussed.

outgassing↗

NASA NTRS2024

High-Rate Delay Tolerant Networking (HDTN) Software Requirements Analysis

This document serves as a detailed analysis of the main networking protocols implemented by HDTN. Sources of the protocol specifications include Internet Engineering Task Force (IETF) Request for Comments (RFC) and Consultative Committee for Space Data Systems (CCSDS) standards. The focus of this report is to derive software requirements suitable for NASA Procedural Requirements 7150.2D Class B compliance, including requirements traceability and software verification and validation, from the source specifications. This analysis will be incorporated into the finalized HDTN Software Requirements Specification (SRS) but does not encompass the full scope of the HDTN SRS. Requirements in this document are considered draft. The complete requirements will include bundle application requirements, interface requirements, computer resource requirements, software quality factors, and additional requirements as determined by the project. This document is publicly released to the greater community to receive feedback and foster collaboration opportunities.

Rachel Dudukovich↗

NASA NTRS1982

Geometric verification

Present LANDSAT data formats are reviewed to clarify how the geodetic location and registration capabilities were defined for P-tape products and RBV data. Since there is only one geometric model used in the master data processor, geometric location accuracy of P-tape products depends on the absolute accuracy of the model and registration accuracy is determined by the stability of the model. Due primarily to inaccuracies in data provided by the LANDSAT attitude management system, desired accuracies are obtained only by using ground control points and a correlation process. The verification of system performance with regards to geodetic location requires the capability to determine pixel positions of map points in a P-tape array. Verification of registration performance requires the capability to determine pixel positions of common points (not necessarily map points) in 2 or more P-tape arrays for a given world reference system scene. Techniques for registration verification can be more varied and automated since map data are not required. The verification of LACIE extractions is used as an example.

Grebowsky, G. J.↗

NASA NTRS1988

Thermal/structural design verification strategies for large space structures

Requirements for space structures of increasing size, complexity, and precision have engendered a search for thermal design verification methods that do not impose unreasonable costs, that fit within the capabilities of existing facilities, and that still adequately reduce technical risk. This requires a combination of analytical and testing methods. This requires two approaches. The first is to limit thermal testing to sub-elements of the total system only in a compact configuration (i.e., not fully deployed). The second approach is to use a simplified environment to correlate analytical models with test results. These models can then be used to predict flight performance. In practice, a combination of these approaches is needed to verify the thermal/structural design of future very large space systems.

Benton, David↗

NASA NTRS2017

Mars 2020 Model Based Systems Engineering Pilot

The pilot study is led by the Integration Engineering group in NASA's Launch Services Program (LSP). The Integration Engineering (IE) group is responsible for managing the interfaces between the spacecraft and launch vehicle. This pilot investigates the utility of Model-Based Systems Engineering (MBSE) with respect to managing and verifying interface requirements. The main objectives of the pilot are to model several key aspects of the Mars 2020 integrated operations and interface requirements based on the design and verification artifacts from Mars Science Laboratory (MSL) and to demonstrate how MBSE could be used by LSP to gain further insight on the interface between the spacecraft and launch vehicle as well as to enhance how LSP manages the launch service. The method used to accomplish this pilot started through familiarization of SysML, MagicDraw, and the Mars 2020 and MSL systems through books, tutorials, and NASA documentation. MSL was chosen as the focus of the model since its processes and verifications translate easily to the Mars 2020 mission. The study was further focused by modeling specialized systems and processes within MSL in order to demonstrate the utility of MBSE for the rest of the mission. The systems chosen were the In-Flight Disconnect (IFD) system and the Mass Properties process. The IFD was chosen as a system of focus since it is an interface between the spacecraft and launch vehicle which can demonstrate the usefulness of MBSE from a system perspective. The Mass Properties process was chosen as a process of focus since the verifications for mass properties occur throughout the lifecycle and can demonstrate the usefulness of MBSE from a multi-discipline perspective. Several iterations of both perspectives have been modeled and evaluated. While the pilot study will continue for another 2 weeks, pros and cons of using MBSE for LSP IE have been identified. A pro of using MBSE includes an integrated view of the disciplines, requirements, and verifications leading up to launch. The model allows IE to understand the relationships between disciplines throughout test activities and verifications. Additionally, the relationships between disciplines and integration tasks are generally consistent. The model allows for the generic relationships and tasks to be captured and used throughout multiple mission models should LSP further pursue MBSE. A con of MBSE is the amount of time it takes upfront to understand MBSE and create a useful model. The upfront time it takes to create a useful model is heavily discussed in MBSE literature and is a consistent con throughout the known applications of MBSE. The need to understand SysML and the software chosen also poses the possibility of a "bottleneck" or one person being the sole MBSE user for the working group. The utility of MBSE will continue to be evaluated through the remainder of the study. In conclusion, the original objectives of the pilot study were to use artifacts from MSL to model key aspects of Mars 2020 and demonstrate how MBSE could be used by LSP to gain insight into the spacecraft and launch vehicle interfaces. Progress has been made in modeling and identifying the utility of MBSE to LSP IE and will continue to be made until the pilot study's conclusion in mid-August. The results of this study will produce initial models, modeling instructions and examples, and a summary of MBSE's utility for future use by LSP.

Dukes, Alexandra Marie↗

NASA NTRS1982

Structural assembly demonstration experiment

The experiment is of an operational variety, designed to assess crew capability in Large Space System (LSS) assembly. The six Structural Assembly Demonstration Experiment objectives include: (1) the establishment of a quantitative correlation between LSS neutral buoyancy simulation and on-orbit assembly operations in order to enhance the validity of those assembly simulations; (2) the quantitative study of the capabilities and mechanics of human assembly in an Extravehicular Activity environment; (3) the further corroboration of the LSS Assembly Analysis cost algorithm through the obtainment of hard data base information; (4) the verification of LSS assembly techniques and timeless, as well as the identification of crew imposed loads and assembly aid requirements and concepts; (5) verification of a Launch/Assembly Platform structure concept for other LSS missions; and (6) lastly, to advance thermal control concepts through a flexible heat pipe.

Stokes, J. W.↗

NASA NTRS1989

Development of an Automated Requirements Management System for the Space Station Freedom Program

The Automated Requirements Management System, which is being developed to support traceability and documentation of Space Station Freedom requirements, is described. The objectives of requirements management are validation and verification. Other benefits include comprehensive analytical capabilities, commonality and timeliness of requirements information availability across the program, and the reduction of information duplication and overlap.

Giffin, Geoff↗

NASA NTRS2017

Requirement Development Process and Tools

Requirements capture the system-level capabilities in a set of complete, necessary, clear, attainable, traceable, and verifiable statements of need. Requirements should not be unduly restrictive, but should set limits that eliminate items outside the boundaries drawn, encourage competition (or alternatives), and capture source and reason of requirement. If it is not needed by the customer, it is not a requirement. They establish the verification methods that will lead to product acceptance. These must be reproducible assessment methods.

Tools↗

NASA NTRSDate not supplied

Runtime Verification with Ogma

Ultra-critical systems require high-level assurance, which cannot always be guaranteed in compile time. The use of runtime verification (RV) enable monitoring these systems in runtime, to detect property violations early and limit their potential consequences. However, the introduction of monitors in ultra-critical systems poses a challenge, as failures and delays in the RV subsystem could affect other subsystems and threaten the mission as a whole. In this talk we discuss two systems: NASA's Ogma, a tool to transform high-level specifications into monitoring code, and Copilot, a runtime verification framework for real-time embedded systems. The toolchain can be used to translate structured natural language requirements into C code with static memory requirements, which can be compiled to run on embedded hardware.

Ogma↗

NASA NTRSDate not supplied

Runtime Verification with Ogma

Ogma↗