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At least 37 records · Page 2

Design metrics for maintenance +

Results of a study to develop maintenance metrics based on structural software design characteristics are described. A characteristic metric set suited to explain and predict software maintenance behavior is defined. The maintenance aspects investigated are stability and modifiability. While stability addresses the average number of modules affected per change cause, modifiability characterizes the ease with which changes can be made within each of these modules. Additional interest is dedicated to the difference between characteristic design and implementation metric sets, and to the difference between change behavior during development and maintenance. The development of six software systems and controlled maintenance experiments using these system is examined.

Rombach, H. D.

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

Solar energy system installed at the North Georgia APDC office building

A hydronic, automatic drain-down solar heating and cooling system is described. The system provides solar heat exchange from a 2,001 square foot effective collector area and supplies 65-70 percent of the building's cooling demand, 90-95 percent of the heating demand, and domestic hot water. The acceptance test plan and results, system operation and maintenance, and predicted system performance are presented.

Source record

NASA IVHM Technology Experiment for X-vehicles (NITEX)

The purpose of the NASA IVHM Technology Experiment for X-vehicles (NITEX) is to advance the development of selected IVHM technologies in a flight environment and to demonstrate the potential for reusable launch vehicle ground processing savings. The technologies to be developed and demonstrated include system-level and detailed diagnostics for real-time fault detection and isolation, prognostics for fault prediction, automated maintenance planning based on diagnostic and prognostic results, and a microelectronics hardware platform. Complete flight The Evolution of Flexible Insulation as IVHM consists of advanced sensors, distributed data acquisition, data processing that includes model-based diagnostics, prognostics and vehicle autonomy for control or suggested action, and advanced data storage. Complete ground IVHM consists of evolved control room architectures, advanced applications including automated maintenance planning and automated ground support equipment. This experiment will advance the development of a subset of complete IVHM.

Sandra, Hayden

Hybrid Model Based Approaches for Systems Health Management and Prognostics

This is a previously approved and published presentation. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Present achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. In principle, data-driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data-driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety-critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Prognostics

Integrated Logistics Support Analysis of the International Space Station Alpha, Background and Summary of Mathematical Modeling and Failure Density Distributions Pertaining to Maintenance Time Dependent Parameters

The process of predicting the values of maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle costs, spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability and maintenance support costs. There are two types of parameters in the logistics and maintenance world: a. Fixed; b. Variable Fixed parameters, such as cost per man hour, are relatively easy to predict and forecast. These parameters normally follow a linear path and they do not change randomly. However, the variable parameters subject to the study in this report such as MTBF do not follow a linear path and they normally fall within the distribution curves which are discussed in this publication. The very challenging task then becomes the utilization of statistical techniques to accurately forecast the future non-linear time dependent variable arisings and events with a high confidence level. This, in turn, shall translate in tremendous cost savings and improved availability all around.

Sepehry-Fard, F.

The role of predicted solar activity in TOPEX/Poseidon orbit maintenance maneuver design

Following launch in June 1992, the TOPEX/Poseidon satellite will be placed in a near-circular frozen orbit at an altitude of about 1336 km. Orbit maintenance maneuvers are planned to assure all nodes of the 127-orbit 10-day repeat ground track remain within a 2 km equatorial longitude bandwidth. Orbit determination, maneuver execution, and atmospheric drag prediction errors limit overall targeting performance. This paper focuses on the effects of drag modeling errors, with primary emphasis on the role of SESC solar activity predictions, especially the 27-day outlook of the 10.7 cm solar flux and geomagnetic index used by a simplified version of the Jacchia-Roberts density model developed for this TOPEX/Poseidon application. For data evaluated from 1983-90, the SESC outlook performed better than a simpler persistence strategy, especially during the first 7-10 days. A targeting example illustrates the use of ground track biasing to compensate for expected orbit predictions errors, emphasizing the role of solar activity prediction errors.

Frauenholz, Raymond B.

Maintenance cost study of rotary wing aircraft

The feasibility was studied of predicting rotary wing operation maintenance costs by using several aircraft design factors for the aircraft dynamic systems. The dynamic systems considered were engines, drives and transmissions, rotors, and flight controls. Multiple regression analysis was used to correlate aircraft design and operational factors with manhours per flight hour, and equations for each dynamic system were developed. Results of labor predictions using the equations compare favorably with actual values.

Source record

Consideration for solar system exploration - A system to Mars

Biomedical issues related to a manned mission to Mars are reviewed. Consideration is given to cardiovascular deconditioning, hematological and immunological changes, bone and muscle changes, nutritional issues, and the development of physiological countermeasures. Environmental issues are discussed, including radiation hazards, toxic chemical exposure, and the cabin environment. Also, human factors, performance and behavior, medical screening of the crew, disease prediction, and health maintenance are examined.

Nicogossian, Arnauld E.

Reusable Rocket Engine Operability Modeling and Analysis

This paper describes the methodology, model, input data, and analysis results of a reusable launch vehicle engine operability study conducted with the goal of supporting design from an operations perspective. Paralleling performance analyses in schedule and method, this requires the use of metrics in a validated operations model useful for design, sensitivity, and trade studies. Operations analysis in this view is one of several design functions. An operations concept was developed given an engine concept and the predicted operations and maintenance processes incorporated into simulation models. Historical operations data at a level of detail suitable to model objectives were collected, analyzed, and formatted for use with the models, the simulations were run, and results collected and presented. The input data used included scheduled and unscheduled timeline and resource information collected into a Space Transportation System (STS) Space Shuttle Main Engine (SSME) historical launch operations database. Results reflect upon the importance not only of reliable hardware but upon operations and corrective maintenance process improvements.

Christenson, R. L.

The Launch Systems Operations Cost Model

One of NASA's primary missions is to reduce the cost of access to space while simultaneously increasing safety. A key component, and one of the least understood, is the recurring operations and support cost for reusable launch systems. In order to predict these costs, NASA, under the leadership of the Independent Program Assessment Office (IPAO), has commissioned the development of a Launch Systems Operations Cost Model (LSOCM). LSOCM is a tool to predict the operations & support (O&S) cost of new and modified reusable (and partially reusable) launch systems. The requirements are to predict the non-recurring cost for the ground infrastructure and the recurring cost of maintaining that infrastructure, performing vehicle logistics, and performing the O&S actions to return the vehicle to flight. In addition, the model must estimate the time required to cycle the vehicle through all of the ground processing activities. The current version of LSOCM is an amalgamation of existing tools, leveraging our understanding of shuttle operations cost with a means of predicting how the maintenance burden will change as the vehicle becomes more aircraft like. The use of the Conceptual Operations Manpower Estimating Tool/Operations Cost Model (COMET/OCM) provides a solid point of departure based on shuttle and expendable launch vehicle (ELV) experience. The incorporation of the Reliability and Maintainability Analysis Tool (RMAT) as expressed by a set of response surface model equations gives a method for estimating how changing launch system characteristics affects cost and cycle time as compared to today's shuttle system. Plans are being made to improve the model. The development team will be spending the next few months devising a structured methodology that will enable verified and validated algorithms to give accurate cost estimates. To assist in this endeavor the LSOCM team is part of an Agency wide effort to combine resources with other cost and operations professionals to support models, databases, and operations assessments.

Prince, Frank A.

Propellant-remaining modeling

A successful satellite mission is predicted upon the proper maintenance of the spacecraft's orbit and attitude. One requirement for planning and predicting the orbit and attitude is the accurate estimation of the propellant remaining onboard the spacecraft. Focuss is on the three methods that were developed for calculating the propellant budget: the errors associated with each method and the uncertainties in the variables required to determine the propellant remaining that contribute to these errors. Based on these findings, a strategy is developed for improved propellant-remaining estimation. The first method is based on Boyle's law, which related the values of pressure, volume, and temperature (PVT) of an ideal gas. The PVT method is used for the monopropellant and the bipropellant engines. The second method is based on the engine performance tests, which provide data that relate thrust and specific impulse associated with a propellant tank to that tank's pressure. Two curves representing thrust and specific impulse as functions of pressure are then generated using a polynomial fit on the engine performance data. The third method involves a computer simulation of the propellant system. The propellant flow is modeled by creating a conceptual model of the propulsion system configuration, taking into account such factors as the propellant and pressurant tank characteristics, thruster functionality, and piping layout. Finally, a thrust calibration technique is presented that uses differential correction with the computer simulation method of propellant-remaining modeling. Thrust calibration provides a better assessment of thruster performance and therefore enables a more accurate estimation of propellant consumed during a given maneuver.

Torgovitsky, S.

The development and application of composite complexity models and a relative complexity metric in a software maintenance environment

A great deal of effort is now being devoted to the study, analysis, prediction, and minimization of software maintenance expected cost, long before software is delivered to users or customers. It has been estimated that, on the average, the effort spent on software maintenance is as costly as the effort spent on all other software costs. Software design methods should be the starting point to aid in alleviating the problems of software maintenance complexity and high costs. Two aspects of maintenance deserve attention: (1) protocols for locating and rectifying defects, and for ensuring that noe new defects are introduced in the development phase of the software process; and (2) protocols for modification, enhancement, and upgrading. This article focuses primarily on the second aspect, the development of protocols to help increase the quality and reduce the costs associated with modifications, enhancements, and upgrades of existing software. This study developed parsimonious models and a relative complexity metric for complexity measurement of software that were used to rank the modules in the system relative to one another. Some success was achieved in using the models and the relative metric to identify maintenance-prone modules.

Hops, J. M.

Unsafe acts and unsafe outcomes in aircraft maintenance

Road safety studies using the Driver Behaviour Questionnaire (DBQ) have provided support for a three-way distinction between violations, skill-based errors and mistakes, and have indicated that a tendency to commit driving violations is associated with an increased risk of accident involvement. The aims of this study were to examine whether the three-way distinction of unsafe acts is applicable in the context of aircraft maintenance, and whether involvement in maintenance safety occurrences can be predicted on the basis of self-reported unsafe acts. A Maintenance Behaviour Questionnaire (MBQ) was developed to explore patterns of unsafe acts committed by aircraft maintenance mechanics. The MBQ was completed anonymously by over 1300 Australian aviation mechanics, who also provided information on their involvement in workplace accidents and incidents. Four factors were identified: routine violations, skill-based errors, mistakes and exceptional violations. Violations and mistakes were related significantly to the occurrence of incidents that jeopardized the quality of aircraft maintenance, but were not related to workplace injuries. Skill-based errors, while not related to work quality incidents, were related to workplace injuries. The results are consistent with the three-way typology of unsafe acts described by Reason et al. (1990) and with the DBQ research indicating an association between self-reported violations and accidents. The current findings suggest that interventions addressed at maintenance quality incidents should take into account the role of violations and mistakes, and the factors that promote them. In contrast, interventions directed at reducing workplace injury are likely to require a focus on skill-based errors.

Maintenance/manpower/methods

Transmission overhaul estimates for partial and full replacement at repair

Timely transmission overhauls increase in-flight service reliability greater than the calculated design reliabilities of the individual aircraft transmission components. Although necessary for aircraft safety, transmission overhauls contribute significantly to aircraft expense. Predictions of a transmission's maintenance needs at the design stage should enable the development of more cost effective and reliable transmissions in the future. The frequency is estimated of overhaul along with the number of transmissions or components needed to support the overhaul schedule. Two methods based on the two parameter Weibull statistical distribution for component life are used to estimate the time between transmission overhauls. These methods predict transmission lives for maintenance schedules which repair the transmission with a complete system replacement or repair only failed components of the transmission. An example illustrates the methods.

Savage, M.

Down-Selection of Four Common Habitat Variants

The Common Habitat is a large habitat developed as an alternative architecture study, not part of the current NASA baseline, that uses the SLS core stage liquid oxygen tank as its primary structure. It has a gravity-independent internal architecture, such that identical units can be used on the lunar surface, Mars surface, and in microgravity. In developing the habitat, two key architectural questions emerged. Should the internal layout use a vertical or horizontal orientation of the tank? Should the crew size be four or eight? This led to the design of four variants: a four-crew horizontal, four-crew vertical, eight-crew horizontal, and eight-crew vertical. The four-crew variants use a shortened version of the tank while the eight-crew variants use the entire tank. The primary consideration applied for down-selection is the crew experience living and working in the habitat, inclusive of crew productivity, well-being, and survivability. Based on this consideration, a series of seven assessments were performed to compare the variants. This analysis was performed as an unfunded, volunteer activity leveraging civil servants across multiple field centers, most with expertise working in various Artemis teams. Additionally, the evaluation was limited to the use of CAD models, images, and spreadsheet data, with no resources available for mockups or Virtual Reality. A logistics analysis developed a standard logistics module and then estimated how much stowage could be carried onboard each Common Habitat and how many logistics modules are required by each variant for a given mission duration. It also considered the amounts of water to be stored in each variant. A functional analysis identified and compared the living and working functions across the habitats, ranking them relative to each other. A crew time assessment first estimated the total crew time, building a weekly crew timeline for both four and eight-person crews. It then allocated time to activities linked to living and working functions, comparing how much time was available for each function in each variant. A science productivity assessment developed a relative metric using crew time, science stowage, and assumed rates of experiment consumables use to analytically compare the four variants. It also comparatively ranked the habitats with respect to a number of subjective parameters and a workstation acceptability rating. A maintenance capacity assessment identified and compared eleven generic maintenance capabilities across the variants and also ranked them for their predicted ability to complete twelve fabrication, maintenance, and repair scenarios. A contingency responsiveness analysis examined twelve serious in-flight contingencies. For each scenario, the number of crew needed to respond were predicted and acceptability of various aspects of contingency response were evaluated, comparing the variants against each other. Finally, in a habitability assessment, 120 habitability characteristics reflecting 13 major categories were evaluated for each habitat. These results were compared to identify the most acceptable habitat in each category. Ultimately, the data favored the horizontal orientation over the vertical and an eight-person crew over four. Implications of selecting this variant are discussed, including specific architectural challenges that result from the use of the full tank.

Habitability

Applying reliability models to the maintenance of Space Shuttle software

Software reliability models provide the software manager with a powerful tool for predicting, controlling, and assessing the reliability of software during maintenance. We show how a reliability model can be effectively employed for reliability prediction and the development of maintenance strategies using the Space Shuttle Primary Avionics Software Subsystem as an example.

Schneidewind, Norman F.