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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Determining Component Probability using Problem Report Data for Ground Systems used in Manned Space Flight

During the shuttle era NASA utilized a failure reporting system called the Problem Reporting and Corrective Action (PRACA) it purpose was to identify and track system non-conformance. The PRACA system over the years evolved from a relatively nominal way to identify system problems to a very complex tracking and report generating data base. The PRACA system became the primary method to categorize any and all anomalies from corrosion to catastrophic failure. The systems documented in the PRACA system range from flight hardware to ground or facility support equipment. While the PRACA system is complex, it does possess all the failure modes, times of occurrence, length of system delay, parts repaired or replaced, and corrective action performed. The difficulty is mining the data then to utilize that data in order to estimate component, Line Replaceable Unit (LRU), and system reliability analysis metrics. In this paper, we identify a methodology to categorize qualitative data from the ground system PRACA data base for common ground or facility support equipment. Then utilizing a heuristic developed for review of the PRACA data determine what reports identify a credible failure. These data are the used to determine inter-arrival times to perform an estimation of a metric for repairable component-or LRU reliability. This analysis is used to determine failure modes of the equipment, determine the probability of the component failure mode, and support various quantitative differing techniques for performing repairable system analysis. The result is that an effective and concise estimate of components used in manned space flight operations. The advantage is the components or LRU's are evaluated in the same environment and condition that occurs during the launch process.

Monaghan, Mark W.↗
NASA NTRS2016

Limitations of Reliability for Long-Endurance Human Spaceflight

Long-endurance human spaceflight - such as missions to Mars or its moons - will present a never-before-seen maintenance logistics challenge. Crews will be in space for longer and be farther way from Earth than ever before. Resupply and abort options will be heavily constrained, and will have timescales much longer than current and past experience. Spare parts and/or redundant systems will have to be included to reduce risk. However, the high cost of transportation means that this risk reduction must be achieved while also minimizing mass. The concept of increasing system and component reliability is commonly discussed as a means to reduce risk and mass by reducing the probability that components will fail during a mission. While increased reliability can reduce maintenance logistics mass requirements, the rate of mass reduction decreases over time. In addition, reliability growth requires increased test time and cost. This paper assesses trends in test time requirements, cost, and maintenance logistics mass savings as a function of increase in Mean Time Between Failures (MTBF) for some or all of the components in a system. In general, reliability growth results in superlinear growth in test time requirements, exponential growth in cost, and sublinear benefits (in terms of logistics mass saved). These trends indicate that it is unlikely that reliability growth alone will be a cost-effective approach to maintenance logistics mass reduction and risk mitigation for long-endurance missions. This paper discusses these trends as well as other options to reduce logistics mass such as direct reduction of part mass, commonality, or In-Space Manufacturing (ISM). Overall, it is likely that some combination of all available options - including reliability growth - will be required to reduce mass and mitigate risk for future deep space missions.

Owens, Andrew C.↗
NASA NTRS1983

Reliability considerations in the placement of control system components

This paper presents a methodology, along with applications to a grid type structure, for incorporating reliability considerations in the decision for actuator placement on large space structures. The method involves the minimization of a criterion that considers mission life and the reliability of the system components. It is assumed that the actuator gains are to be readjusted following failures, but their locations cannot be changed. The goal of the design is to suppress vibrations of the grid and the integral square of the grid modal amplitudes is used as a measure of performance of the control system. When reliability of the actuators is considered, a more pertinent measure is the expected value of the integral; that is, the sum of the squares of the modal amplitudes for each possible failure state considered, multiplied by the probability that the failure state will occur. For a given set of actuator locations, the optimal criterion may be graphed as a function of the ratio of the mean time to failure of the components and the design mission life or reservicing interval. The best location of the actuators is typically different for a short mission life than for a long one.

Montgomery, R. C.↗
NASA NTRS1989

A non-homogeneous Markov model for phased-mission reliability analysis

Three assumptions of Markov modeling for reliability of phased-mission systems that limit flexibility of representation are identified. The proposed generalization has the ability to represent state-dependent behavior, handle phases of random duration using globally time-dependent distributions of phase change time, and model globally time-dependent failure and repair rates. The approach is based on a single nonhomogeneous Markov model in which the concept of state transition is extended to include globally time-dependent phase changes. Phase change times are specified using nonoverlapping distributions with probability distribution functions that are zero outside assigned time intervals; the time intervals are ordered according to the phases. A comparison between a numerical solution of the model and simulation demonstrates that the numerical solution can be several times faster than simulation.

Smotherman, Mark↗
NASA NTRS2003

Advanced Data Acquisition Systems

Current and future requirements of the aerospace sensors and transducers field make it necessary for the design and development of new data acquisition devices and instrumentation systems. New designs are sought to incorporate self-health, self-calibrating, self-repair capabilities, allowing greater measurement reliability and extended calibration cycles. With the addition of power management schemes, state-of-the-art data acquisition systems allow data to be processed and presented to the users with increased efficiency and accuracy. The design architecture presented in this paper displays an innovative approach to data acquisition systems. The design incorporates: electronic health self-check, device/system self-calibration, electronics and function self-repair, failure detection and prediction, and power management (reduced power consumption). These requirements are driven by the aerospace industry need to reduce operations and maintenance costs, to accelerate processing time and to provide reliable hardware with minimum costs. The project's design architecture incorporates some commercially available components identified during the market research investigation like: Field Programmable Gate Arrays (FPGA) Programmable Analog Integrated Circuits (PAC IC) and Field Programmable Analog Arrays (FPAA); Digital Signal Processing (DSP) electronic/system control and investigation of specific characteristics found in technologies like: Electronic Component Mean Time Between Failure (MTBF); and Radiation Hardened Component Availability. There are three main sections discussed in the design architecture presented in this document. They are the following: (a) Analog Signal Module Section, (b) Digital Signal/Control Module Section and (c) Power Management Module Section. These sections are discussed in detail in the following pages. This approach to data acquisition systems has resulted in the assignment of patent rights to Kennedy Space Center under U.S. patent # 6,462,684. Furthermore, NASA KSC commercialization office has issued licensing rights to Circuit Avenue Netrepreneurs, LLC , a minority-owned business founded in 1999 located in Camden, NJ.

Perotti, J.↗
NASA NTRS2009

Lunar Base Life Support Failures

Dynamic simulation of the lunar outpost habitat life support was undertaken to investigate the impact of life support failures and to investigate responses. Some preparatory static analysis for the Lunar Outpost life support model, an earlier version of the model, and an investigation into the impact of Extravehicular Activity (EVA) were reported previously. (Jones, 2008-01-2184, 2008-01-2017) The earlier model was modified to include possible resupply delays, power failures, recycling system failures, and atmosphere and other material storage failures. Most failures impact the lunar outpost water balance and can be mitigated by reducing water usage. Food solids, nitrogen can be obtained only by resupply from Earth. The most time urgent failure is a lass of carbon dioxide removal capability. Life support failures might be survivable if effective operational solutions are provided in the system design.

Jones, Harry W.↗
NASA NTRSDate not supplied

In-Time Safety Assessment & Risk Prediction for Unmanned Aerial Systems

One of the critical challenges in emerging autonomous systems is timely mitigation of hazards encountered during operation which may not be known or accounted for at the time of design. Efficient execution of unmanned systems therefore demands a paradigm shift from scheduled periodic maintenance to predictive risk analysis that includes condition-based-monitoring, real-time reliability assessment and hazard mitigation. Particularly, the state-of-health parameters needs to be computed at the component level, unit level as well as the integrated system level. While in the former two levels, the physics of health propagation may be based on underlying electro-mechanical properties, system level prognostics often relies on data-driven models. Further, uncertainty from model, measurements and input sources should be accurately quantified to generate meaningful prediction results that can be fed into reliable decision making processes. Finally, the expected risk and time to failure has to be computed based on the current state-of-health of the overall system. This talk presents a conceptual design of such an in-time safety assurance approach for unmanned aerial vehicles (UAV) operating at low altitudes near and over populated areas. Typical in-flight hazard incidents include unplanned detour, proximity to obstacles, mid-flight component faults, limited battery life and poor quality of GPS measurements. Safety assessment therefore comprises trajectory generation and re-plan, battery RUL computation, distributed fault diagnostics and uncertainty management of predicted trajectory based on GPS measurement noise. The entire monitoring framework will be demonstrated on simulated as well as real UAV flight experiments conducted at the NASA Langley Research Center. This tutorial will therefore guide the audience through a step-by-step tracking of an autonomous system with focus on in-time risk prediction in the presence of unforeseen hazards and uncertain environment.

diagnostics↗
NASA NTRS1979

Vulnerability of Quick Disconnect Connectors to Carbon Fibers

Unprotected quick disconnect electrical connectors were exposed to fibers of 3mm, 7mm, and 12mm lengths. The average exposure to failure was determined. Results indicate that when the fiber length divided by the airgap is less than one, multiple fibers are required to bridge the gap, and the exposure time to failure rises rapidly.

Meyers, J. A.↗
NASA NTRS1995

Estimating Maintenance Demands Of A Space Station

RENEW computer program simulates maintenance events and estimates data pertinent to maintenance demands. Developed in support of Space Station Freedom Program (SSFP) Work Package 4. Uses data on reliability and maintainability (R&M) as well as logistical data to estimate both average and time-dependent maintenance demands. Estimates failure and repair times by use of Monte Carlo simulations. Written in BASIC and Assembly language.

Bream, B. L.↗
NASA NTRS2024

Extended Investigation into Fault-Tolerant Integrated Motor Drive for a Quadrotor Urban Air Mobility (UAM) Aircraft

Electric propulsor machines and their associated power electronics have been identified in past studies as low-reliability components in emerging Urban Air Mobility (UAM) Vertical Takeoff and Landing (VTOL) vehicles that raise their predicted catastrophic failure rates. This research effort extends previously presented work investigating the use of fault-tolerant (FT) motor drives in quadrotor aircraft as a promising approach to significantly increase their mean-time-to-failure (MTTF). In particular, fault-tolerant modular motor drives (FT-MMDs) are identified as strong candidates for closing the electric propulsor reliability gap. These FT-MMDs divide a machine drive into multiple redundant modules, each consisting of three phase stator windings and power electronics units, enabling continued machine operation after a module failure. Achieving the highest possible isolation between modules (physical, magnetic, thermal, electrical) is critically important in FT-MMDs to prevent the propagation of any failure between modules. Key additional requirements for achieving the highest possible reliability characteristics with FT-MMDs are high repair rates and aggressive suppression of all single-point failures.

quadrotor↗
NASA NTRS1977

Kinetic studies of stress-corrosion cracking

Use of time-to-failure curves for stress-corrosion cracking processes may lead to incorrect estimates of structural life, if material is strongly dependent upon prestress levels. Technique characterizes kinetics of crackgrowth rates and intermediate arrest times by load-level changes.

Noronha, P. J.↗
NASA NTRS2002

Advanced Self-Calibrating, Self-Repairing Data Acquisition System

An improved self-calibrating and self-repairing Data Acquisition System (DAS) for use in inaccessible areas, such as onboard spacecraft, and capable of autonomously performing required system health checks, failure detection. When required, self-repair is implemented utilizing a "spare parts/tool box" system. The available number of spare components primarily depends upon each component's predicted reliability which may be determined using Mean Time Between Failures (MTBF) analysis. Failing or degrading components are electronically removed and disabled to reduce power consumption, before being electronically replaced with spare components.

Pedro J Medelius↗
NASA NTRSDate not supplied

Lessons Learned from the Arecibo Observatory Auxiliary M4N Socket Analysis and Implications for Future Observatory Designs

The Arecibo Observatory collapsed after a progressive structural failure stemming from the failure of a single socket joint cable termination. A failure investigation was conducted to identify the cause of the first failed cable termination socket. Due to the nature of the suspended observatory receiver, the dominant source of loading in the suspension cables was due to deadload, with secondary contributions coming from environmental effects and observatory operation. The high ratio of deadload vs. live load applied to the cable over many years resulted in a creep failure mode of the cast zinc within the socket which further induced stress into the highly stress wires at the entrance of the socket. The design of the socket joint did not explicitly consider socket constituent stress margins and time-dependent damage mechanisms such as creep. Lessons learned from this investigation led to recommendations for revising civil engineering cable standards, and recommendations for manufacturers and designers. The design of cables employing socket terminations should consider the cumulative damage effects from creep and cyclic loading identify their corresponding worst-case inspectable defects or establish a sufficiently high factor of safety so that the design is sufficiently robust to defects and time-dependent failure modes. The design should specify end-of-life capability and set service life inspection intervals with pass/fail inspection criteria. Finally, trial studies on design iterations were conducted to increase the reliability of cables with socket joints.

Pavel Babuska↗
NASA NTRSDate not supplied

Reliability Growth Modeling and Testing

Reliability growth has been modelled as an exponential decline in the cumulative failure rate that continues indefinitely as long as testing continues. Contrary to this, most reliability growth data show a brief high initial failure rate due to infant mortality followed by a long period of constant low failure rate. A two part failure rate model with an initial exponential decline followed by a constant failure rate usually fits the data and provides a more realistic description of reliability growth. The reliability growth process consists of testing, experiencing failures, finding the failure causes, and redesigning the system to remove them. The cost of reliability growth increases with the number of inherent failure modes and the time needed for them to occur and be removed. The failure modes with the lower failure rates will tend to occur later, as their Mean Time Before Failure (MTBF) is the inverse of the failure rate. Reliability growth testing has diminishing returns, since it takes longer to find and remove the less probable failures.This paper first discusses the reliability bathtub curve and then explains that reliability growth is produced by testing, identifying failure causes, and designing to remove them. A simple model of reliability growth is introduced, with a brief group of early failures followed by a constant failure rate. The cumulative failure rate n(t)/t can decline as rapidly as1/t or t-1butdeclines more slowly if additiona lfailures occur. The 56-failure Crow data seti s used to demonstrate the two-phase model of reliability growth followed by a constant failure rate. 13 additional data sets are modeled, with 9 of the 14 data sets showing reliability growth approximately as n(t)/t =1/t or t-1and substantial final failure rates. The model fits most of the data sets, but 4of the 14 show no reliability growth. The reliability growth period typically includes six failures and extends one-quarter or half the total test time. As reliability growth testing continues, the cumulative failure rate should be tracked to estimate the reliability growth exponent and the final failure rate.

reliability growth modeling↗
NASA NTRSDate not supplied

Modeling Reliability Growth

Reliability growth has been modelled as an exponential decline in the cumulative failure rate that continues indefinitely as long as testing continues. Contrary to this, most reliability growth data show a brief high initial failure rate due to infant mortality followed by a long period of constant low failure rate. A two part failure rate model with an initial exponential decline followed by a constant failure rate usually fits the data and provides a more realistic description of reliability growth. The reliability growth process consists of testing, experiencing failures, finding the failure causes, and redesigning the system to remove them. The cost of reliability growth increases with the number of inherent failure modes and the time needed for them to occur and be removed. The failure modes with the lower failure rates will tend to occur later, as their Mean Time Before Failure (MTBF) is the inverse of the failure rate. Reliability growth testing has diminishing returns, since it takes longer to find and remove the less probable failures.This paper first discusses the reliability bathtub curve and then explains that reliability growth is produced by testing, identifying failure causes, and designing to remove them. A simple model of reliability growth is introduced, with a brief group of early failures followed by a constant failure rate. The cumulative failure rate n(t)/t can decline as rapidly as1/t or t-1butdeclines more slowly if additiona lfailures occur. The 56-failure Crow data seti s used to demonstrate the two-phase model of reliability growth followed by a constant failure rate. 13 additional data sets are modeled, with 9 of the 14 data sets showing reliability growth approximately as n(t)/t =1/t or t-1and substantial final failure rates. The model fits most of the data sets, but 4of the 14 show no reliability growth. The reliability growth period typically includes six failures and extends one-quarter or half the total test time. As reliability growth testing continues, the cumulative failure rate should be tracked to estimate the reliability growth exponent and the final failure rate.

reliability growth modeling↗
NASA NTRS1994

Matrix Failure Modes and Effects Analysis as a Knowledge Base for a Real Time Automated Diagnosis Expert System

Failure Modes and Effects Analysis contain a wealth of information that can be used to create the knowledge base required for building automated diagnostic Expert systems. A real time monitoring and diagnosis expert system based on an actual NASA project's matrix failure modes and effects analysis was developed. This Expert system Was developed at NASA Ames Research Center. This system was first used as a case study to monitor the Research Animal Holding Facility (RAHF), a Space Shuttle payload that is used to house and monitor animals in orbit so the effects of space flight and microgravity can be studied. The techniques developed for the RAHF monitoring and diagnosis Expert system are general enough to be used for monitoring and diagnosis of a variety of other systems that undergo a Matrix FMEA. This automated diagnosis system was successfully used on-line and validated on the Space Shuttle flight STS-58, mission SLS-2 in October 1993.

Herrin, Stephanie↗
NASA NTRS1989

Orbiter post-tire failure and skid testing results

An investigation was conducted at the NASA Langley Research Center's Aircraft Landing Dynamics Facility (ALDF) to define the post-tire failure drag characteristics of the Space Shuttle Orbiter main tire and wheel assembly. Skid tests on various materials were also conducted to define their friction and wear rate characteristics under higher speed and bearing pressures than any previous tests. The skid tests were conducted to support a feasibility study of adding a skid to the orbiter strut between the main tires to protect an intact tire from failure due to overload should one of the tires fail. Roll-on-rim tests were conducted to define the ability of a standard and a modified orbiter main wheel to roll without a tire. Results of the investigation are combined into a generic model of strut drag versus time under failure conditions for inclusion into rollout simulators used to train the shuttle astronauts.

Daugherty, Robert H.↗
NASA NTRS2016

Mass and Reliability System (MaRS)

The Safety and Mission Assurance (S&MA) Directorate is responsible for mitigating risk, providing system safety, and lowering risk for space programs from ground to space. The S&MA is divided into 4 divisions: The Space Exploration Division (NC), the International Space Station Division (NE), the Safety & Test Operations Division (NS), and the Quality and Flight Equipment Division (NT). The interns, myself and Arun Aruljothi, will be working with the Risk & Reliability Analysis Branch under the NC Division's. The mission of this division is to identify, characterize, diminish, and communicate risk by implementing an efficient and effective assurance model. The team utilizes Reliability and Maintainability (R&M) and Probabilistic Risk Assessment (PRA) to ensure decisions concerning risks are informed, vehicles are safe and reliable, and program/project requirements are realistic and realized. This project pertains to the Orion mission, so it is geared toward a long duration Human Space Flight Program(s). For space missions, payload is a critical concept; balancing what hardware can be replaced by components verse by Orbital Replacement Units (ORU) or subassemblies is key. For this effort a database was created that combines mass and reliability data, called Mass and Reliability System or MaRS. The U.S. International Space Station (ISS) components are used as reference parts in the MaRS database. Using ISS components as a platform is beneficial because of the historical context and the environment similarities to a space flight mission. MaRS uses a combination of systems: International Space Station PART for failure data, Vehicle Master Database (VMDB) for ORU & components, Maintenance & Analysis Data Set (MADS) for operation hours and other pertinent data, & Hardware History Retrieval System (HHRS) for unit weights. MaRS is populated using a Visual Basic Application. Once populated, the excel spreadsheet is comprised of information on ISS components including: operation hours, random/nonrandom failures, software/hardware failures, quantity, orbital replaceable units (ORU), date of placement, unit weight, frequency of part, etc. The motivation for creating such a database will be the development of a mass/reliability parametric model to estimate mass required for replacement parts. Once complete, engineers working on future space flight missions will have access a mean time to failures and on parts along with their mass, this will be used to make proper decisions for long duration space flight missions

Barnes, Sarah↗