Systems reliability subject to multiple nonlinear constraints.
Reliability maximization computational procedure for multistage parallel systems subject to multiple nonlinear constraints
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Reliability maximization computational procedure for multistage parallel systems subject to multiple nonlinear constraints
Over the last two to three decades, the balance of influence within the electronics industry has shifted decisively towards the consumer electronics and information technology products, away from the defense or aerospace markets. This shift towards the commercial markets has changed certain ground rules in the electronics industry. Reliance of the aerospace industry, in particular, on components from supply chains dedicated to other products, or cross-vertical product integration, creates a supply web and introduces significant risks that are not necessarily present for volume-driven electronic products. Many of the unique risks in the aerospace industry emanate from the key characteristics of this industry. Although selection and usage of commercial electronics in NASA flight hardware is possible at a comparable (and in many cases lower) level of risk to that of employing parts that are screened to military or NASA specifications, for a large majority of flight projects it is difficult to distinguish the difference in on-orbit performance or reliability for parts screened at any level, or commercial parts that have no additional screening performed by the government. This paper identifies several bases for establishing context and developing unique or alternative approaches for successful parts selection and application within NASA and across the commercial space community.
The development of new products is dependent on product designs that incorporate high levels of reliability along with a design that meets predetermined levels of system cost. Additional constraints on the product include explicit and implicit performance requirements. Existing reliability and cost prediction methods result in no direct linkage between variables affecting these two dominant product attributes. A methodology to integrate reliability and cost estimates using a sequential linear approximation method is proposed. The sequential linear approximation method utilizes probability of failure sensitivities determined from probabilistic reliability methods as well a manufacturing cost sensitivities. The application of the sequential linear approximation method to a mechanical system is demonstrated.
The overall reliability and maintenance costs (R&MC's) of past and current turboprop systems were examined. Maintenance cost drivers were found to be scheduled overhaul (40%), lack of modularity particularly in the propeller and reduction gearbox, and lack of inherent durability (reliability) of some parts. Comparisons were made between the 501-D13/54H60 turboprop system and the widely used JT8D turbofan. It was found that the total maintenance cost per flight hour of the turboprop was 75% higher than that of the JT8D turbofan. Part of this difference was due to propeller and gearbox costs being higher than those of the fan and reverser, but most of the difference was in the engine core where the older technology turboprop core maintenance costs were nearly 70 percent higher than for the turbofan. The estimated maintenance cost of both the advanced turboprop and advanced turbofan were less than the JT8D. The conclusion was that an advanced turboprop and an advanced turbofan, using similar cores, will have very competitive maintenance costs per flight hour.
The paper discusses several of the challenges associated with developing a credible reliability estimate for a human-rated crew capsule thermal protection system. The process of developing such a credible estimate is subject to the quantification, modeling and propagation of numerous uncertainties within a probabilistic analysis. The development of specific investment recommendations, to improve the reliability prediction, among various potential testing and programmatic options is then accomplished through Bayesian analysis.
Software is playing increasingly important roles in avionics systems. It is widely used in navigation and, in some cases, in control loops that maintain aircraft stability. To guarantee the safety of flight systems, the FAA requires that critical components have a probability of failure no greater than 10(exp -9) per hour of flight. Software is being used to diagnose system components for failure. SIFT (Software Implemented Fault Tolerance) was a computer system developed to study the use of software to check for failure and manage processor reconfiguration. To guarantee that software satisfies its specifications, formal verification can be used. With this a program and its specification are viewed as mathematical objects, and a mathematical proof is used to show that the program and its specification are equivalent. In previous research, a theory of checking was developed to offer assistance in analyzing specifications and designing run-time checks. In the theory, checking is considered abstractly in terms of n-ary relations much like those of relational database theory. Within the theory check are categorized, checks on input and checks on results are considered, and formal attention is given to the minimization and logical combination of checks. The focus is upon input checks and the obstacles in checking input to critical systems. A central concern is with a property referred to as independence. The concern is with circumstances under which it is possible to apply isolated, independent checks to separate sensor inputs and be assure that all illegal input will be properly detected. Presently, independence is being investigated and checked in the context of the GCS (Guidance and Control System). The GCS simulator is intended for testing software that implements control laws for landing spacecraft. The large number of inputs and their complex interrelationships provide an exciting context in which to investigate independence and the difficulties of supplying input checks.
Understanding and accounting for uncertainty in risk analysis is a critical step in the management and communication of risk in engineered systems. The component and system-level analysis to determine the probability of a negative outcome and its consequence is often quantified by a point estimate. Many Program and Enterprise decisions involving technical concerns and issues rely on reliability engineering activities to produce quantified risk analysis to inform the decision making process. At NASA, it is common to use a Probabilistic Risk Analysis (PRA) to inform the overall risk to Loss of Mission or Loss of Crew that involves integration across all spacecraft subsystem fault trees to produce an overall probability of mission failure. The point estimate is an estimate of this overall probability and is an immediate result of a fault tree model. It is the result of a model where the probability of each event is taken to be equal to its mean. The value provides an approximation of the overall mean without running any uncertainty calculations (e.g., no sampling). Using only the point estimate can lead to a false sense of precision and the point estimate may not match the resulting mean when uncertainty is taken into consideration. This paper will explore five conditions that can cause the PRA model mean to diverge from the point estimate and will provide engineers and managers insight into the importance of understanding uncertainty in the elements of PRA models.
Future crewed exploration missions beyond Low Earth Orbit (LEO) will operate farther from Earth and be logistically isolated for longer than any previous human spaceflight mission. Under these conditions, supportability and reliability willbestronger drivers of mission mass and risk than they have been in the past. Items with high failure rates, or uncertain failure rates, can result in high spares mass requirements and/or high risk on deep space missions. Testing is a critical element of system development which provides the opportunity to identify and resolve design issues, defects, or other failure modes before they cause problems during a mission. Reliability growth programs can reduce failure rates by identifying and remove failure modes via design changes, and long-duration life testing can provide valuable data to reduce failure rate estimate uncertainty and verify (to some level of confidence) that components are as reliable as expected. Testing activities take time and resources, however, and must be incorporated into program plans in order to be fully effective. This paper presents an integrated reliability test plan analysis and optimization methodology, which has been used to inform Advanced Exploration Systems (AES) Life Support Systems (LSS) ground test planning for future missions. The methodology determines the optimal number of test units to purchase and allocation of test time –split between reliability growth and uncertainty reduction testing –across a given set of items in order to minimize spares mass for a given mission under constraints on total test cost and schedule. Model outputs also include expected spares mass after testing and the expected number of modifications or refurbishments during testing, both of which can inform program planning. Discussion of the model, conclusions, and future work are also presented.
Future crewed exploration missions beyond Low Earth Orbit (LEO) will operate farther from Earth and be logistically isolated for longer than any previous human spaceflight mission. Under these conditions, supportability and reliability willbestronger drivers of mission mass and risk than they have been in the past. Items with high failure rates, or uncertain failure rates, can result in high spares mass requirements and/or high risk on deep space missions. Testing is a critical element of system development which provides the opportunity to identify and resolve design issues, defects, or other failure modes before they cause problems during a mission. Reliability growth programs can reduce failure rates by identifying and remove failure modes via design changes, and long-duration life testing can provide valuable data to reduce failure rate estimate uncertainty and verify (to some level of confidence) that components are as reliable as expected. Testing activities take time and resources, however, and must be incorporated into program plans in order to be fully effective. This paper presents an integrated reliability test plan analysis and optimization methodology, which has been used to inform Advanced Exploration Systems (AES) Life Support Systems (LSS) ground test planning for future missions. The methodology determines the optimal number of test units to purchase and allocation of test time –split between reliability growth and uncertainty reduction testing –across a given set of items in order to minimize spares mass for a given mission under constraints on total test cost and schedule. Model outputs also include expected spares mass after testing and the expected number of modifications or refurbishments during testing, both of which can inform program planning. Discussion of the model, conclusions, and future work are also presented.
In the Reliability and Quality Engineering Test Laboratory at the NASA Lewis Research Center a nondestructive, corona-vacuum test facility for testing power system components was developed using commercially available hardware. The test facility was developed to simulate operating temperature and vacuum while monitoring corona discharges with residual gases. This facility is being used to test various high voltage power system components.
A study to reduce operating costs of helicopters, particularly directed at the maintenance of the propulsion subsystem, is presented. The tasks of the study consisted of problem definition refinement, technology solutions, diagnostic system concepts, and emergency power augmentation. Quantifiable benefits (reduced fuel consumption, on-condition engine maintenance, extended drive system overhaul periods, and longer oil change intervals) would increase the initial cost by $43,000, but the benefit of $24.46 per hour would result in breakeven at 1758 hours. Other benefits not capable of being quantified but perhaps more important include improved aircraft avilability due to reduced maintenance time, potential for increased operating limits due to continuous automatic monitoring of gages, and less time and fuel required to make engine power checks. The most important improvement is the on-condition maintenance program, which will require the development of algorithms, equipment, and procedures compatible with all operating environments.
Rockwell International is conducting an ongoing program to develop avionics architectures that provide high intrinsic value while meeting all mission objectives. Studies are being conducted to determine alternative configurations that have low life-cycle cost and minimum development risk, and that minimize launch delays while providing the reliability level to assure a successful mission. This effort is based on four decades of providing ballistic missile avionics to the United States Air Force and has focused on the requirements of the NASA Cargo Transfer Vehicle (CTV) program in 1991. During the development of architectural concepts it became apparent that rendezvous strategy issues have an impact on the architecture of the avionics system. This is in addition to the expected impact on propulsion and electrical power duration, flight profiles, and trajectory during approach.
The objective of this project was to examine the corrosion resistance of 316L stainless steel in several urine pre-treat solutions. Four solutions were examined: untreated urine (control); urine pretreated with oxone (potassium peroxymonosulfate sulfate); urine pretreated with sodium hypochlorite (NaOCl); and urine pretreated with ozone (O3). In accordance with current procedures, all solutions but the control were acidified to a pH of 2.5 using sulfuric acid--this suppresses the generation of ammonia in the solutions and is intended to limit microbial growth. Welded and unwelded coupons were exposed to each solution. In addition, Titanium coupons (welded and unwelded) were exposed to biologically active environmental control and life support system (ECLSS) water. Microbial attachment and biofilm growth were monitored. Ozone was examined as a biocide/oxidizer/corrosion preventative (simultaneous addition) and as a remediation method (added one week after exposure). In an unrelated effort, HP 9-4-30 coupons were exposed to biologically active solutions. Corrosion rates for welded and unwelded samples were determined--results were correlated to the ongoing HP 9-4-30 weldment stress corrosion study.
Use of success and failure data in reliability engineering
System for switching circuits between on line and off line switching computers at NASA communications network /NASCOM/ primary and remote switching centers
A grouping into four classes is proposed for all reliability computations that are related to electronic equipment. Examples are presented of reliability computations in three of these four classes. Each of the three specific reliability tasks described was originally undertaken to satisfy an engineering need for reliability data. The form and interpretation of the print-out of the specific reliability computations is presented. The justification for the costs of these computations is indicated. The skills of the personnel used to conduct the analysis, the interfaces between the personnel, and the timing of the projects is discussed.
Goddard activities are reported for 1973. An eight-year flight schedule for projected space missions is presented. Data acquired by spacecraft in the following disciplines are described: stellar ultraviolet, stellar X-rays, stellar gamma rays, solar radiation, radio astronomy, particles/fields, magnetosphere, aurora, and the upper atmosphere.
The reliability of adaptive controls for future aircraft are discussed. The research, formulation, and experimentation for improved aircraft performance are considered.