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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Develop advanced nonlinear signal analysis topographical mapping system

The SSME has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) Develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system. (2) Develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amounts of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. A high compression ratio can be achieved to allow the minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities. (3) Integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for a quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an ATMS system of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbo pump families.

Jong, Jen-Yi↗
NASA NTRS1994

Develop advanced nonlinear signal analysis topographical mapping system

The Space Shuttle Main Engine (SSME) has been undergoing extensive flight certification and developmental testing, which involves some 250 health monitoring measurements. Under the severe temperature, pressure, and dynamic environments sustained during operation, numerous major component failures have occurred, resulting in extensive engine hardware damage and scheduling losses. To enhance SSME safety and reliability, detailed analysis and evaluation of the measurements signal are mandatory to assess its dynamic characteristics and operational condition. Efficient and reliable signal detection techniques will reduce catastrophic system failure risks and expedite the evaluation of both flight and ground test data, and thereby reduce launch turn-around time. The basic objective of this contract are threefold: (1) develop and validate a hierarchy of innovative signal analysis techniques for nonlinear and nonstationary time-frequency analysis. Performance evaluation will be carried out through detailed analysis of extensive SSME static firing and flight data. These techniques will be incorporated into a fully automated system; (2) develop an advanced nonlinear signal analysis topographical mapping system (ATMS) to generate a Compressed SSME TOPO Data Base (CSTDB). This ATMS system will convert tremendous amount of complex vibration signals from the entire SSME test history into a bank of succinct image-like patterns while retaining all respective phase information. High compression ratio can be achieved to allow minimal storage requirement, while providing fast signature retrieval, pattern comparison, and identification capabilities; and (3) integrate the nonlinear correlation techniques into the CSTDB data base with compatible TOPO input data format. Such integrated ATMS system will provide the large test archives necessary for quick signature comparison. This study will provide timely assessment of SSME component operational status, identify probable causes of malfunction, and indicate feasible engineering solutions. The final result of this program will yield an ATMS system of nonlinear and nonstationary spectral analysis software package integrated with the Compressed SSME TOPO Data Base (CSTDB) on the same platform. This system will allow NASA engineers to retrieve any unique defect signatures and trends associated with different failure modes and anomalous phenomena over the entire SSME test history across turbo pump families.

Source record↗
NASA NTRS1995

Optimal Category-A Helicopter Flight Trajectories for Operation From a Clear Heliport

Engine failure represents a major safety hazard to helicopter operation. As a result, FA certifies helicopters according to their abilities to survive engine failures. Federal Aviation Regulation Part 29 specifies that transport helicopters must be certified as either category A or B. Category-B certification applies to either single or multi-engine helicopters with gross weight less than 20,000 lbs. A Category-B helicopter must be able to land safely in the case of one or all engine failures. There is no requirement for continued flight capability. In contrast, Category-A certification applies to multi-engine helicopters with independent engine systems. It requires that helicopter can continue flight with one engine inoperative (OEI). Therefore, Category-A helicopters are capable of operating from rooftops and oil rigs and flying to areas where no emergency landing sites are available. While there is no maximum weight limit, a Category-A helicopter must be able to satisfy OEI operation requirements within the available runway field. Additional information is contained in the original extended abstract.

Sharma, Vivek↗
NASA NTRSDate not supplied

X-57 Static Structural Requirements and Airworthiness Approach

The National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center (AFRC) (Edwards, California, U.S.A.) has been flying various types of aircraft, including experimental ones requiring structural modifications. Many of these aircraft aren’t typically certified by the Federal Aviation Administration (FAA) or the Department of Defense (DoD), but NASA can provide its own airworthiness certification utilizing a riskbased approach. The AFRC has established review processes and procedures to identify hazards, manage risks associated with flight programs, ensure safe flight operations, and satisfy programmatic requirements. The Aerostructures Branch at AFRC developed guidelines for the structural safety of flight, covering experimental aircraft, new components, payloads, and modifications. These guidelines detail structural design, analysis, instrumentation, ground testing, and flight-test operational aspects. The guidelines are followed for defining the airworthiness plan throughout the life cycle of a project. The guidelines can be tailored to the risk posture of each individual project. This paper documents the details of the structural airworthiness plan for the X-57 aircraft, including existing, modified, and newly developed structures. Additionally, it covers the design requirements and load cases specific to the X-57 aircraft.

Wesley W. Li↗
NASA NTRS2024

Recommendations on Evidence and Process for Certification of Learning-enabled Components in Aerospace Systems

This report primarily identifies a collection of relevant and necessary evidence for assurance of machine learnt components (MLCs)—also known as learning-enabled components—integrated into aircraft systems, and gives preliminary suggestions on the elements of a certification process that invoke the identified evidence. The main focus is on feedforward neural networks that are static and trained offline through supervised learning. A brief background on the generic elements of the lifecycle of an MLC is given to contextualize the assurance considerations and, consequently, the evidence that is relevant and necessary to support certification. At the level of an MLC, those considerations relate to: (i) the consistency and correctness of MLC contributions to system functions in the context of a validated functional intent; and (ii) the absence of MLC contributions to aircraft-level failure conditions. At an ML model level, confidence in model and data properties contribute to assurance of the containing MLC, in particular: (a) generalizability and robustness of models, in the presence of inputs not previously seen during training, disturbances to inputs, and unexpected inputs; and (b) valid data, i.e., data that are at least representative, relevant, complete, and accurate. Evidence for the above span the elements of the ML lifecycle, and includes, at a minimum, lifecycle artifacts that pertain to: (1) properties of requirements capturing functional intent, safety constraints, and aspects of the intended use and operating environment; (2) model performance, model complexity and design, and algorithm choice; (3) achievement of required performance at the levels of a trained model during model development, a trained model after model development is complete, and a trained model that is transformed into an executable equivalent; (4) model implementation aspects necessary for transforming a trained model into the executable equivalent; (5) integration of the executable trained model into the containing MLC, and eventually the larger system; and, (6) lastly, the verification and validation (V&V) of each of the above. Such V&V lifecycle artifacts themselves include: aspects of coverage, e.g., of various levels of requirements by the input space of the model and the data; traceability (where applicable); application of formal methods for property specification, analysis, and checking. Examples of evidence generation methods and tools further ground the discussion on what constitutes evidence, and the contribution to assurance during certification. The identified assurance considerations and supporting evidence is not a comprehensive set. Additionally, neither what should be considered as sufficient evidence relative to the assigned criticality of an MLC, nor how criticality ought to be determined and adjusted, have been considered in this report. However, suggestions are made for potential activities of the ML lifecycle that are aimed at providing confidence that an MLC can be relied upon when integrated into its containing (aircraft) system. Those activities are proposed as candidate elements of a certification process for MLCs. The main purpose of this report to inform regulatory guidance and consensus standards that may be used to meet the safety intent of the applicable regulations.

Aviation safety↗
NASA NTRS2005

Structural Analysis for the American Airlines Flight 587 Accident Investigation: Global Analysis

NASA Langley Research Center (LaRC) supported the National Transportation Safety Board (NTSB) in the American Airlines Flight 587 accident investigation due to LaRC's expertise in high-fidelity structural analysis and testing of composite structures and materials. A Global Analysis Team from LaRC reviewed the manufacturer s design and certification procedures, developed finite element models and conducted structural analyses, and participated jointly with the NTSB and Airbus in subcomponent tests conducted at Airbus in Hamburg, Germany. The Global Analysis Team identified no significant or obvious deficiencies in the Airbus certification and design methods. Analysis results from the LaRC team indicated that the most-likely failure scenario was failure initiation at the right rear main attachment fitting (lug), followed by an unstable progression of failure of all fin-to-fuselage attachments and separation of the VTP from the aircraft. Additionally, analysis results indicated that failure initiates at the final observed maximum fin loading condition in the accident, when the VTP was subjected to loads that were at minimum 1.92 times the design limit load condition for certification. For certification, the VTP is only required to support loads of 1.5 times design limit load without catastrophic failure. The maximum loading during the accident was shown to significantly exceed the certification requirement. Thus, the structure appeared to perform in a manner consistent with its design and certification, and failure is attributed to VTP loads greater than expected.

Young, Richard D.↗
NASA NTRS1994

John F. Kennedy Space Center, Safety, Reliability, Maintainability and Quality Assurance, Survey and Audit Program

This document is the product of the KSC Survey and Audit Working Group composed of civil service and contractor Safety, Reliability, and Quality Assurance (SR&QA) personnel. The program described herein provides standardized terminology, uniformity of survey and audit operations, and emphasizes process assessments rather than a program based solely on compliance. The program establishes minimum training requirements, adopts an auditor certification methodology, and includes survey and audit metrics for the audited organizations as well as the auditing organization.

Source record↗
NASA NTRS2005

Liquid Nitrogen Removal of Critical Aerospace Materials

Identification of innovative solutions to unique materials problems is an every-day quest for members of the aerospace community. Finding a technique that will minimize costs, maximize throughput, and generate quality results is always the target. United Space Alliance Materials Engineers recently conducted such a search in their drive to return the Space Shuttle fleet to operational status. The removal of high performance thermal coatings from solid rocket motors represents a formidable task during post flight disassembly on reusable expended hardware. The removal of these coatings from unfired motors increases the complexity and safety requirements while reducing the available facilities and approved processes. A temporary solution to this problem was identified, tested and approved during the Solid Rocket Booster (SRB) return to flight activities. Utilization of ultra high-pressure liquid nitrogen (LN2) to strip the protective coating from assembled space shuttle hardware marked the first such use of the technology in the aerospace industry. This process provides a configurable stream of liquid nitrogen (LN2) at pressures of up to 55,000 psig. The performance of a one-time certification for the removal of thermal ablatives from SRB hardware involved extensive testing to ensure adequate material removal without causing undesirable damage to the residual materials or aluminum substrates. Testing to establish appropriate process parameters such as flow, temperature and pressures of the liquid nitrogen stream provided an initial benchmark for process testing. Equipped with these initial parameters engineers were then able to establish more detailed test criteria that set the process limits. Quantifying the potential for aluminum hardware damage represented the greatest hurdle for satisfying engineers as to the safety of this process. Extensive testing for aluminum erosion, surface profiling, and substrate weight loss was performed. This successful project clearly demonstrated that the liquid nitrogen jet possesses unique strengths that align remarkably well with the unusual challenges that space hardware and missile manufacturers face on a regular basis. Performance of this task within the confines of a critical manufacturing facility marks a milestone in advanced processing.

Noah, Donald E.↗
NASA NTRS1972

Design certification review assessment report. Electron/proton spectrometer

The characteristics of the electron-photon spectrometer developed for the Skylab program are presented. The spectrometer is externally mounted on the Skylab module complex and provides omnidirectional measurement of electrons and protons which result from solar flares or enhancement of the radiation belts. The data are applied to the determination of relative biological effectiveness factors as a safety factor for manned space flight.

Source record↗
NASA NTRS2003

Advanced Durability and Damage Tolerance Design and Analysis Methods for Composite Structures: Lessons Learned from NASA Technology Development Programs

Aerospace vehicles are designed to be durable and damage tolerant. Durability is largely an economic life-cycle design consideration whereas damage tolerance directly addresses the structural airworthiness (safety) of the vehicle. However, both durability and damage tolerance design methodologies must address the deleterious effects of changes in material properties and the initiation and growth of microstructural damage that may occur during the service lifetime of the vehicle. Durability and damage tolerance design and certification requirements are addressed for commercial transport aircraft and NASA manned spacecraft systems. The state-of-the-art in advanced design and analysis methods is illustrated by discussing the results of several recently completed NASA technology development programs. These programs include the NASA Advanced Subsonic Technology Program demonstrating technologies for large transport aircraft and the X-33 hypersonic test vehicle demonstrating technologies for a single-stage-to-orbit space launch vehicle.

Harris, Charles E.↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASAs Space Launch System

The engineering development of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS) requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The nominal and off-nominal characteristics of SLS's elements and subsystems must be understood and matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex systems engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model-based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model-based algorithms and their development lifecycle from inception through FSW certification are an important focus of SLS's development effort to further ensure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. To test and validate these M&FM algorithms a dedicated test-bed was developed for full Vehicle Management End-to-End Testing (VMET). For addressing fault management (FM) early in the development lifecycle for the SLS program, NASA formed the M&FM team as part of the Integrated Systems Health Management and Automation Branch under the Spacecraft Vehicle Systems Department at the Marshall Space Flight Center (MSFC). To support the development of the FM algorithms, the VMET developed by the M&FM team provides the ability to integrate the algorithms, perform test cases, and integrate vendor-supplied physics-based launch vehicle (LV) subsystem models. Additionally, the team has developed processes for implementing and validating the M&FM algorithms for concept validation and risk reduction. The flexibility of the VMET capabilities enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS, GNC, and others. One of the principal functions of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software test and validation processes. In any software development process there is inherent risk in the interpretation and implementation of concepts from requirements and test cases into flight software compounded with potential human errors throughout the development and regression testing lifecycle. Risk reduction is addressed by the M&FM group but in particular by the Analysis Team working with other organizations such as S&MA, Structures and Environments, GNC, Orion, Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission (LOM) and Loss of Crew (LOC) probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses to be tested in VMET to ensure reliable failure detection, and confirm responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - the ARINC 6535-partitioned Operating System, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by FSW. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure their effectiveness and performance in the exterior FSW development and test processes. This paper is outlined in a systematic fashion analogous to a lifecycle process flow for engineering development of algorithms into software and testing. Section I describes the NASA SLS M&FM context, presenting the current infrastructure, leading principles, methods, and participants. Section II defines the testing philosophy of the M&FM algorithms as related to VMET followed by section III, which presents the modeling methods of the algorithms to be tested and validated in VMET. Its details are then further presented in section IV followed by Section V presenting integration, test status, and state analysis. Finally, section VI addresses the summary and forward directions followed by the appendices presenting relevant information on terminology and documentation.

Trevino, Luis↗
NASA NTRS2015

A Vehicle Management End-to-End Testing and Analysis Platform for Validation of Mission and Fault Management Algorithms to Reduce Risk for NASA's Space Launch System

The engineering development of the new Space Launch System (SLS) launch vehicle requires cross discipline teams with extensive knowledge of launch vehicle subsystems, information theory, and autonomous algorithms dealing with all operations from pre-launch through on orbit operations. The characteristics of these spacecraft systems must be matched with the autonomous algorithm monitoring and mitigation capabilities for accurate control and response to abnormal conditions throughout all vehicle mission flight phases, including precipitating safing actions and crew aborts. This presents a large and complex system engineering challenge, which is being addressed in part by focusing on the specific subsystems involved in the handling of off-nominal mission and fault tolerance with response management. Using traditional model based system and software engineering design principles from the Unified Modeling Language (UML) and Systems Modeling Language (SysML), the Mission and Fault Management (M&FM) algorithms for the vehicle are crafted and vetted in specialized Integrated Development Teams (IDTs) composed of multiple development disciplines such as Systems Engineering (SE), Flight Software (FSW), Safety and Mission Assurance (S&MA) and the major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GNC), Thrust Vector Control (TVC), and liquid engines. These model based algorithms and their development lifecycle from inception through Flight Software certification are an important focus of this development effort to further insure reliable detection and response to off-nominal vehicle states during all phases of vehicle operation from pre-launch through end of flight. NASA formed a dedicated M&FM team for addressing fault management early in the development lifecycle for the SLS initiative. As part of the development of the M&FM capabilities, this team has developed a dedicated testbed that integrates specific M&FM algorithms, specialized nominal and off-nominal test cases, and vendor-supplied physics-based launch vehicle subsystem models. Additionally, the team has developed processes for implementing and validating these algorithms for concept validation and risk reduction for the SLS program. The flexibility of the Vehicle Management End-to-end Testbed (VMET) enables thorough testing of the M&FM algorithms by providing configurable suites of both nominal and off-nominal test cases to validate the developed algorithms utilizing actual subsystem models such as MPS. The intent of VMET is to validate the M&FM algorithms and substantiate them with performance baselines for each of the target vehicle subsystems in an independent platform exterior to the flight software development infrastructure and its related testing entities. In any software development process there is inherent risk in the interpretation and implementation of concepts into software through requirements and test cases into flight software compounded with potential human errors throughout the development lifecycle. Risk reduction is addressed by the M&FM analysis group working with other organizations such as S&MA, Structures and Environments, GNC, Orion, the Crew Office, Flight Operations, and Ground Operations by assessing performance of the M&FM algorithms in terms of their ability to reduce Loss of Mission and Loss of Crew probabilities. In addition, through state machine and diagnostic modeling, analysis efforts investigate a broader suite of failure effects and associated detection and responses that can be tested in VMET to ensure that failures can be detected, and confirm that responses do not create additional risks or cause undesired states through interactive dynamic effects with other algorithms and systems. VMET further contributes to risk reduction by prototyping and exercising the M&FM algorithms early in their implementation and without any inherent hindrances such as meeting FSW processor scheduling constraints due to their target platform - ARINC 653 partitioned OS, resource limitations, and other factors related to integration with other subsystems not directly involved with M&FM such as telemetry packing and processing. The baseline plan for use of VMET encompasses testing the original M&FM algorithms coded in the same C++ language and state machine architectural concepts as that used by Flight Software. This enables the development of performance standards and test cases to characterize the M&FM algorithms and sets a benchmark from which to measure the effectiveness of M&FM algorithms performance in the FSW development and test processes.

Trevino, Luis↗
NASA NTRS2022

NASA Commercial Crew Program Crew Transportation System Certificate of Flight Readiness Plan

NASA Commercial Crew Program (CCP) Crew Transportation System (CTS) Certification of Flight Readiness (CoFR) is the authorization granted by the Agency that certifies the flight readiness of a Commercial Provider’s CTS to conduct a flight test or mission to transport NASA Crew to and from the ISS. The Commercial Provider is responsible for developing and executing its plan for certifying the flight readiness of its CTS. The CCP with the International Space Station (ISS) Program must substantiate the Commercial Provider’s CoFR assertion to ensure compliance with NASA requirements and NASA Crew safety. NASA CCP CTS CoFR is the approval of the Commercial Provider’s evidence that: • The physical as-built CTS was produced, assembled, integrated, and tested within the approved production and operational constraints. • The mission specific requirements are enveloped within the certified CTS capabilities. • The CTS personnel are trained and certified to support the mission. • All aspects of the CTS are ready for the mission.

Certification of Flight Readiness↗
NASA NTRS2018

UAS-NAS NASA 870 Ikhana UAS No Chase COA (NCC) Flights, Flight Test Report

This document is a flight test report from the operational perspective for the No Chase Certificate of Waiver or Authorization (COA) flights, or NCC flights, a major milestone of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) project. Discussions of a demonstration event began as early as 2014 and the actual flight of the Ikhana UAS into the NAS without a safety chase vehicle in Class A, E, and D airspace was accomplished on 12 June, 2018. The major goal of this flight was to demonstrate an alternate means of compliance to the see and avoid regulations for a UAS using Detect and Avoid (DAA) technology. Participants in this flight activity and planning included the National Aeronautics and Space Administration (NASA) Ames Research Center, NASA Armstrong Flight Research Center, General Atomics Aeronautical Systems, Inc. (GA-ASI), Honeywell International, Inc., and the Federal Aviation Administration (FAA).

Marston, Mike↗
NASA NTRS1972

STOL research at NASA.

Review of the overall goals, individual objects of ongoing and proposed programs, target dates, and fund requests of NASA's STOL research effort. The realization of a separate STOL short-haul transportation system with a 2000-foot field length capability is shown likely to reduce airport acreage requirements to less than one tenth, approach speed to nearly one half, and airspace required for terminal maneuvering to less than 10% of what conventional high-performance jet aircraft necessitate, and to promise terminal congestion alleviation in areas of high traffic density, improved safety in steep approach, noise abatement, and community annoyance reduction. NASA's described programs will provide the technical foundation upon which industry can base the design and development of aircraft and avionics for the new STOL systems in the latter 1970s, and upon which the government can establish criteria for the certification and regulation of such systems.

Kayton, G. G.↗
NASA NTRS2006

Case Study: Test Results of a Tool and Method for In-Flight, Adaptive Control System Verification on a NASA F-15 Flight Research Aircraft

Adaptive control technologies that incorporate learning algorithms have been proposed to enable autonomous flight control and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments [1-2]. At the present time, however, it is unknown how adaptive algorithms can be routinely verified, validated, and certified for use in safety-critical applications. Rigorous methods for adaptive software verification end validation must be developed to ensure that. the control software functions as required and is highly safe and reliable. A large gap appears to exist between the point at which control system designers feel the verification process is complete, and when FAA certification officials agree it is complete. Certification of adaptive flight control software verification is complicated by the use of learning algorithms (e.g., neural networks) and degrees of system non-determinism. Of course, analytical efforts must be made in the verification process to place guarantees on learning algorithm stability, rate of convergence, and convergence accuracy. However, to satisfy FAA certification requirements, it must be demonstrated that the adaptive flight control system is also able to fail and still allow the aircraft to be flown safely or to land, while at the same time providing a means of crew notification of the (impending) failure. It was for this purpose that the NASA Ames Confidence Tool was developed [3]. This paper presents the Confidence Tool as a means of providing in-flight software assurance monitoring of an adaptive flight control system. The paper will present the data obtained from flight testing the tool on a specially modified F-15 aircraft designed to simulate loss of flight control faces.

Jacklin, Stephen A.↗
NASA NTRS2015

Workmanship Training Industry

Special processes require special skills, knowledge and experienced application. For over 15 years, the NASA Johnson Space Center's Receiving, Inspection and Test Facility (RITF) has provided Workmanship Standards compliance training, issuing more than 500 to 800 training completion certificates annually. It is critical that technicians and inspectors are trained and that they maintain their proficiency to implement the applicable standards and specifications. Training services include 'hands-on' training to engineers, technicians, and inspectors in the areas of electrostatic discharge (ESD), soldering, fiber optics, lithium battery handling, torque and wire safety, and wire wrapping.

Patterson, Ashley↗
NASA NTRS2008

Guidance and Control Software Project Data - Volume 2: Development Documents

The Guidance and Control Software (GCS) project was the last in a series of software reliability studies conducted at Langley Research Center between 1977 and 1994. The technical results of the GCS project were recorded after the experiment was completed. Some of the support documentation produced as part of the experiment, however, is serving an unexpected role far beyond its original project context. Some of the software used as part of the GCS project was developed to conform to the RTCA/DO-178B software standard, "Software Considerations in Airborne Systems and Equipment Certification," used in the civil aviation industry. That standard requires extensive documentation throughout the software development life cycle, including plans, software requirements, design and source code, verification cases and results, and configuration management and quality control data. The project documentation that includes this information is open for public scrutiny without the legal or safety implications associated with comparable data from an avionics manufacturer. This public availability has afforded an opportunity to use the GCS project documents for DO-178B training. This report provides a brief overview of the GCS project, describes the 4-volume set of documents and the role they are playing in training, and includes the development documents from the GCS project. Volume 2 contains three appendices: A. Guidance and Control Software Development Specification; B. Design Description for the Pluto Implementation of the Guidance and Control Software; and C. Source Code for the Pluto Implementation of the Guidance and Control Software

Hayhurst, Kelly J.↗