SEARCH · Search NASA

Results for “software failure model”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

NASA NTRS1979

Care 3, Phase 1, volume 1

A computer program to aid in accessing the reliability of fault tolerant avionics systems was developed. A simple mathematical expression was used to evaluate the reliability of any redundant configuration over any interval during which the failure rates and coverage parameters remained unaffected by configuration changes. Provision was made for convolving such expressions in order to evaluate the reliability of a dual mode system. A coverage model was also developed to determine the various relevant coverage coefficients as a function of the available hardware and software fault detector characteristics, and subsequent isolation and recovery delay statistics.

Stiffler, J. J.↗

NASA NTRS1994

Hardware and software reliability estimation using simulations

The simulation technique is used to explore the validation of both hardware and software. It was concluded that simulation is a viable means for validating both hardware and software and associating a reliability number with each. This is useful in determining the overall probability of system failure of an embedded processor unit, and improving both the code and the hardware where necessary to meet reliability requirements. The methodologies were proved using some simple programs, and simple hardware models.

Swern, Frederic L.↗

NASA NTRS1999

CARES/Life Ceramics Durability Evaluation Software Enhanced for Cyclic Fatigue

The CARES/Life computer program predicts the probability of a monolithic ceramic component's failure as a function of time in service. The program has many features and options for materials evaluation and component design. It couples commercial finite element programs--which resolve a component's temperature and stress distribution--to reliability evaluation and fracture mechanics routines for modeling strength-limiting defects. The capability, flexibility, and uniqueness of CARES/Life have attracted many users representing a broad range of interests and has resulted in numerous awards for technological achievements and technology transfer. Recent work with CARES/Life was directed at enhancing the program s capabilities with regards to cyclic fatigue. Only in the last few years have ceramics been recognized to be susceptible to enhanced degradation from cyclic loading. To account for cyclic loads, researchers at the NASA Lewis Research Center developed a crack growth model that combines the Power Law (time-dependent) and the Walker Law (cycle-dependent) crack growth models. This combined model has the characteristics of Power Law behavior (decreased damage) at high R ratios (minimum load/maximum load) and of Walker law behavior (increased damage) at low R ratios. In addition, a parameter estimation methodology for constant-amplitude, steady-state cyclic fatigue experiments was developed using nonlinear least squares and a modified Levenberg-Marquardt algorithm. This methodology is used to give best estimates of parameter values from cyclic fatigue specimen rupture data (usually tensile or flexure bar specimens) for a relatively small number of specimens. Methodology to account for runout data (unfailed specimens over the duration of the experiment) was also included.

Nemeth, Noel N.↗

NASA NTRS2016

Modeling in the State Flow Environment to Support Launch Vehicle Verification Testing for Mission and Fault Management Algorithms in the NASA Space Launch System

Analysis methods and testing processes are essential activities in the engineering development and verification of the National Aeronautics and Space Administration's (NASA) new Space Launch System (SLS). Central to mission success is reliable verification of the Mission and Fault Management (M&FM) algorithms for the SLS launch vehicle (LV) flight software. This is particularly difficult because M&FM algorithms integrate and operate LV subsystems, which consist of diverse forms of hardware and software themselves, with equally diverse integration from the engineering disciplines of LV subsystems. M&FM operation of SLS requires a changing mix of LV automation. During pre-launch the LV is primarily operated by the Kennedy Space Center (KSC) Ground Systems Development and Operations (GSDO) organization with some LV automation of time-critical functions, and much more autonomous LV operations during ascent that have crucial interactions with the Orion crew capsule, its astronauts, and with mission controllers at the Johnson Space Center. M&FM algorithms must perform all nominal mission commanding via the flight computer to control LV states from pre-launch through disposal and also address failure conditions by initiating autonomous or commanded aborts (crew capsule escape from the failing LV), redundancy management of failing subsystems and components, and safing actions to reduce or prevent threats to ground systems and crew. To address the criticality of the verification testing of these algorithms, the NASA M&FM team has utilized the State Flow environment6 (SFE) with its existing Vehicle Management End-to-End Testbed (VMET) platform which also hosts vendor-supplied physics-based LV subsystem models. The human-derived M&FM algorithms are designed and vetted in Integrated Development Teams composed of design and development disciplines such as Systems Engineering, Flight Software (FSW), Safety and Mission Assurance (S&MA) and major subsystems and vehicle elements such as Main Propulsion Systems (MPS), boosters, avionics, Guidance, Navigation, and Control (GN&C), Thrust Vector Control (TVC), liquid engines, and the astronaut crew office. Since the algorithms are realized using model-based engineering (MBE) methods from a hybrid of the Unified Modeling Language (UML) and Systems Modeling Language (SysML), SFE methods are a natural fit to provide an in depth analysis of the interactive behavior of these algorithms with the SLS LV subsystem models. For this, the M&FM algorithms and the SLS LV subsystem models are modeled using constructs provided by Matlab which also enables modeling of the accompanying interfaces providing greater flexibility for integrated testing and analysis, which helps forecast expected behavior in forward VMET integrated testing activities. In VMET, the M&FM algorithms are prototyped and implemented using the same C++ programming language and similar state machine architectural concepts used by the FSW group. Due to the interactive complexity of the algorithms, VMET testing thus far has verified all the individual M&FM subsystem algorithms with select subsystem vendor models but is steadily progressing to assessing the interactive behavior of these algorithms with LV subsystems, as represented by subsystem models. The novel SFE applications has proven to be useful for quick look analysis into early integrated system behavior and assessment of the M&FM algorithms with the modeled LV subsystems. This early MBE analysis generates vital insight into the integrated system behaviors, algorithm sensitivities, design issues, and has aided in the debugging of the M&FM algorithms well before full testing can begin in more expensive, higher fidelity but more arduous environments such as VMET, FSW testing, and the Systems Integration Lab7 (SIL). SFE has exhibited both expected and unexpected behaviors in nominal and off nominal test cases prior to full VMET testing. In many findings, these behavioral characteristics were used to correct the M&FM algorithms, enable better test coverage, and develop more effective test cases for each of the LV subsystems. This has improved the fidelity of testing and planning for the next generation of M&FM algorithms as the SLS program evolves from non-crewed to crewed flight, impacting subsystem configurations and the M&FM algorithms that control them. SFE analysis has improved robustness and reliability of the M&FM algorithms by revealing implementation errors and documentation inconsistencies. It is also improving planning efficiency for future VMET testing of the M&FM algorithms hosted in the LV flight computers, further reducing risk for the SLS launch infrastructure, the SLS LV, and most importantly the crew.

Trevino, Luis↗

NASA NTRS1983

Analytical redundancy management mechanization and flight data analysis for the F-8 digital fly-by-wire aircraft flight control sensors

The details are presented of an onboard digital computer algorithm designed to reliably detect and isolate the first failure in a duplex set of flight control sensors aboard the NASA F-8 digital fly-by-wire aircraft. The algorithm's successful flight test program is summarized, and specific examples are presented of algorithm behavior in response to software-induced signal faults, both with and without aircraft parameter modeling errors.

Deckert, J. C.↗

NASA NTRS2007

Simulating Flights of Future Launch Vehicles and Spacecraft

Marshall Aerospace Vehicle Representation in C (MAVERIC) is a computer program for generic, low-to-high-fidelity simulation of the flight(s) of one or more launch vehicle(s) or spacecraft. MAVERIC is designed to accommodate multi-staged vehicles, powered serially or in parallel, with multiple engines, tanks, and cargo elements. Engines can be of jet or conventional rocket types, using either liquid or solid propellants. MAVERIC includes generic subsystem software models for propulsion systems, mass properties, reaction control systems, aerodynamic properties, guidance systems, and navigation systems. Simulations can be started at points other than liftoff. Also included are guidance-system software models that accommodate the ascent, orbit, coasting, deorbiting, entry, terminal-area-energy-management, approach, and landing phases of flight. Options to use different wind profiles and atmospheres are included. A Monte Carlo capability is provided for modeling dispersions associated with atmospheric effects (including winds), propulsion, navigation, aerodynamics, and mass properties. Failures of engines and other subsystems can be modeled. The program is written in the C programming language, which makes it possible for the program to have high degrees of modularity, reusability, and maintainability, thereby also facilitating modification for modeling new vehicles.

McCarter, James W.↗

NASA NTRSDate not supplied

Modeling and Characterization of Crushable Composite Structures

The crushing response and the energy absorption capacity of a quasi-isotropic C-shaped composite panel is presented to simulate the progressive damage and failure mechanisms involved in the component testing. Crushable composite structures are widely used for impact applications, as because of their great high-energy absorption capability and lower weight. Simulating the crush characteristics of composite structures is challenging, as the conventional tools fail to accurately represent the failure mechanisms at the component level. Here, a cost-effective predictive tool ‘CZone’ is applied for simulating the crushing response of composite materials. CZone for Abaqus (CZA) is an add-on capability for Abaqus/Explicit and combines with the commercially available impact modeling capabilities included within the Abaqus finite element software package.

crush zone↗

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 NTRS1983

Computer Software Management and Information Center

Computer programs for passive anti-roll tank, earth resources laboratory applications, the NIMBUS-7 coastal zone color scanner derived products, transportable applications executive, plastic and failure analysis of composites, velocity gradient method for calculating velocities in an axisymmetric annular duct, an integrated procurement management system, data I/O PRON for the Motorola exorcisor, aerodynamic shock-layer shape, kinematic modeling, hardware library for a graphics computer, and a file archival system are documented.

Source record↗

NASA NTRS1981

The SIFT computer and its development

Software Implemented Fault Tolerance (SIFT) is an aircraft control computer designed to allow failure probability of less than 10 to the -10th/hour. The system is based on advanced fault-tolerance computing and validation methodology. Since confirmation of reliability by observation is essentially impossible, system reliability is estimated by a Markov model. A mathematical proof is used to justify the validity of the Markov model. System design is represented by a hierarchy of abstract models, and the design proof comprises mathematical proofs that each model is, in fact, an elaboration of the next more abstract model.

Goldberg, J.↗

NASA NTRS2007

A Constitutive Model for Creep Lifetime of PBO Braided Cord

A constitutive model to describe the creep lifetime of PBO braided cord has been developed and fit to laboratory data. The model follows an approach proposed for p-aramid cord in similar applications, and has a Boltzman-type representation that arises from consideration of the failure phenomenon mechanism. The data were obtained using a hydraulic-type universal testing machine, and were analyzed according to Weibull statistics using commercially-available software. The application of concern to the author is NASA's Ultra- Long Duration Balloon and other gossamer spacecraft, but the motivations for the related p-aramid works suggest broader interest.

Sterling, W. J.↗

NASA NTRS2016

Topic Modeling of NASA Space System Problem Reports: Research in Practice

Problem reports at NASA are similar to bug reports: they capture defects found during test, post-launch operational anomalies, and document the investigation and corrective action of the issue. These artifacts are a rich source of lessons learned for NASA, but are expensive to analyze since problem reports are comprised primarily of natural language text. We apply topic modeling to a corpus of NASA problem reports to extract trends in testing and operational failures. We collected 16,669 problem reports from six NASA space flight missions and applied Latent Dirichlet Allocation topic modeling to the document corpus. We analyze the most popular topics within and across missions, and how popular topics changed over the lifetime of a mission. We find that hardware material and flight software issues are common during the integration and testing phase, while ground station software and equipment issues are more common during the operations phase. We identify a number of challenges in topic modeling for trend analysis: 1) that the process of selecting the topic modeling parameters lacks definitive guidance, 2) defining semantically-meaningful topic labels requires nontrivial effort and domain expertise, 3) topic models derived from the combined corpus of the six missions were biased toward the larger missions, and 4) topics must be semantically distinct as well as cohesive to be useful. Nonetheless,topic modeling can identify problem themes within missions and across mission lifetimes, providing useful feedback to engineers and project managers.

Data Mining↗

NASA NTRS2014

Wetware, Hardware, or Software Incapacitation: Observational Methods to Determine When Autonomy Should Assume Control

Control-theoretic modeling of human operator's dynamic behavior in manual control tasks has a long, rich history. There has been significant work on techniques used to identify the pilot model of a given structure. This research attempts to go beyond pilot identification based on experimental data to develop a predictor of pilot behavior. Two methods for pre-dicting pilot stick input during changing aircraft dynamics and deducing changes in pilot behavior are presented This approach may also have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot. With this ability to detect changes in piloting behavior, the possibility now exists to mediate human adverse behaviors, hardware failures, and software anomalies with autono-my that may ameliorate these undesirable effects. However, appropriate timing of when au-tonomy should assume control is dependent on criticality of actions to safety, sensitivity of methods to accurately detect these adverse changes, and effects of changes in levels of auto-mation of the system as a whole.

Trujillo, Anna C.↗

NASA NTRS1992

Implementation of an intelligent control system

A laboratory testbed facility which was constructed at NASA LeRC for the development of an Intelligent Control System (ICS) for reusable rocket engines is described. The framework of the ICS consists of a hierarchy of various control and diagnostic functions. The traditional high speed, closed-loop controller resides at the lowest level of the ICS hierarchy. Above this level resides the diagnostic functions which identify engine faults. The ICS top level consists of the coordination function which manages the interaction between an expert system and a traditional control system. The purpose of the testbed is to demonstrate the feasibility of the OCS concept by implementing the ICS as the primary controller in a simulation of the Space Shuttle Main Engine (SSME). The functions of the ICS which are implemented in the testbed are as follows: an SSME dynamic simulation with selected fault mode models, a reconfigurable controller, a neural network for sensor validation, a model-based failure detection algorithm, a rule based failure detection algorithm, a diagnostic expert system, an intelligent coordinator, and a user interface which provides a graphical representation of the event occurring within the testbed. The diverse nature of the ICS has led to the development of a distributed architecture consisting of specialized hardware and software for the implementation of the various functions. This testbed is made up of five different computer systems. These individual computers are discussed along with the schemes used to implement the various ICS components. The communication between computers and the timing and synchronization between components are also addressed.

Simon, D. L.↗

NASA NTRS2023

Progressive Damage and Failure Analysis of Thermoplastic Composites in Low Velocity Impact Using MAT299

As part of the NASA Hi-Rate Composite Aircraft Manufacturing (HiCAM) Project, state-of-the-art progressive damage and failure analysis (PDFA) tools developed for use with thermosets are being evaluated for use in modeling alternative material systems, like thermoplastics. Experimental low-velocity impact data of a thermoplastic material system, AS4D/PEKK-FC, is presented and includes characterization of the impact damage mechanisms as well as associated load and displacement data. Following the presentation of experimental results, two simulation approaches using the PDFA tool MAT299 in the commercial off-the-shelf finite element software LS-DYNA are employed to predict damage area and force-displacement responses of thermoplastic panels subjected to various impact energies. The first modeling method uses solid elements with a high-density mesh and a ply-by-ply modeling approach similar to previously published work for thermosets. This method has the capability of capturing individual crack development, progression, and delamination on a per ply basis. The second modeling method uses TSHELL elements that have in-plane dimensions that are an order of magnitude larger than the elements used in the solid element approach and reduces the number of elements through the thickness of the laminate. The second method produces a lower-fidelity model with reduced run times that is incapable of monitoring every delamination plane and damage within each ply. Results from both simulation methods are compared to experiment, and limitations of the methods are discussed.

Composite material↗

NASA NTRS2023

Progressive Damage and Failure Analysis of Thermoplastic Composites in Low Velocity Impact Using MAT299

Composite material↗

NASA NTRSDate not supplied

NASA Spacecraft Trade Modeling System (NSTRDMS)

A rapid mission analysis tool is developed to support the ongoing design of the Lunar Transit trajectory of the Power and Propulsion Element (PPE). A 50-kW class electric propulsion system is envisioned to transit a massive vehicle be-tween a Medium Earth Orbit (MEO) parking orbit and a lunar L2 southern Near Rectilinear Halo Orbit (NRHO). A parameterization is developed by which the Lunar Transit can be analyzed in the context of varying vehicle mass, solar elec-tric propulsion (SEP) configurations, and solar array power output. A rapid and novel mission analysis tool enables a wide array of these trade analyses to be completed without the need for extensive computing resources or time. This tool is shown to be useful in the analysis of a reference trajectory, where changes to the baseline vehicle architecture or off-nominal operational scenarios (such as electric thruster failures) can be rapidly assessed by the mission designer.

Low thrust↗

NASA NTRS2006

Numerical Evaluation of Mode 1 Stress Intensity Factor as a Function of Material Orientation For BX-265 Foam Insulation Material

Foam; a cellular material, is found all around us. Bone and cork are examples of biological cell materials. Many forms of man-made foam have found practical applications as insulating materials. NASA uses the BX-265 foam insulation material on the external tank (ET) for the Space Shuttle. This is a type of Spray-on Foam Insulation (SOFI), similar to the material used to insulate attics in residential construction. This foam material is a good insulator and is very lightweight, making it suitable for space applications. Breakup of segments of this foam insulation on the shuttle ET impacting the shuttle thermal protection tiles during liftoff is believed to have caused the space shuttle Columbia failure during re-entry. NASA engineers are very interested in understanding the processes that govern the breakup/fracture of this complex material from the shuttle ET. The foam is anisotropic in nature and the required stress and fracture mechanics analysis must include the effects of the direction dependence on material properties. Material testing at NASA MSFC has indicated that the foam can be modeled as a transversely isotropic material. As a first step toward understanding the fracture mechanics of this material, we present a general theoretical and numerical framework for computing stress intensity factors (SIFs), under mixed-mode loading conditions, taking into account the material anisotropy. We present mode I SIFs for middle tension - M(T) - test specimens, using 3D finite element stress analysis (ANSYS) and FRANC3D fracture analysis software, developed by the Cornel1 Fracture Group. Mode I SIF values are presented for a range of foam material orientations. Also, NASA has recorded the failure load for various M(T) specimens. For a linear analysis, the mode I SIF will scale with the far-field load. This allows us to numerically estimate the mode I fracture toughness for this material. The results represent a quantitative basis for evaluating the strength and fracture properties of anisotropic foam insulation material.

Knudsen, Erik↗