Reliability Analysis of Systems Subject to First-Passage Failure

An obvious goal of reliability analysis is the avoidance of system failure. However, it is generally recognized that it is often not feasible to design a practical or useful system for which failure is impossible. Thus it is necessary to use techniques that estimate the likelihood of failure based on modeling the uncertainty about such items as the demands on and capacities of various elements in the system. This usually involves the use of probability theory, and a design is considered acceptable if it has a sufficiently small probability of failure. This report contains findings of analyses of systems subject to first-passage failure

Performance Analysis of IPv6 Transition Mechanisms over MPLS

 Exhaustion of current version of Internet Protocol version 4 (IPv4) addresses initiated development of next-generation Internet Protocol version 6 (IPv6). IPv6 is acknowledged to provide more address space, better address design, and greater security; however, IPv6 and IPv4 are not fully compatible. For the two protocols to coexist, various IPv6 transition mechanisms have been developed. This research will analyze a series of IPv6 transition mechanisms over the Multiprotocol Label Switching (MPLS) backbone using a simulation tool (OPNET) and will evaluate and compare their performances. The analysis will include comparing the end-to-end delay, jitter, and throughput performance metrics using tunneling mechanisms, specifically Manual Tunnel, Generic Routing Encapsulation (GRE) Tunnel, Automatic IPv4-Compatible Tunnel, and 6to4 Tunnel between Customer Edge (CE)-to-CE routers and between Provider Edge (PE)-to-PE routers. The results are then compared against 6PE, Native IPv6, and Dual Stack, all using the MPLS backbone. The traffic generated for this comparison are database access, email, File Transfer, File Print, Telnet, Video Conferencing over IP, Voice over IP, Web Browsing, and Remote Login. A statistical analysis is performed to compare the performance metrics of these mechanisms to evaluate any statistically-significant differences among them. The main objective of this research is to rank the aforementioned IPv6 transition mechanism and identify the superior mechanism(s) that offer lowest delay, lowest jitter, and highest throughput

Reducing Human/Pilot Errors in Aviation Using Augmented Cognition and Automation Systems in Aircraft Cockpit

Human errors cause the majority of aviation accidents. Augmented cognition and automation systems enhance pilot performance by evaluating system limitations and flight precision and performance. This study examines the human-machine interface in cockpit design using the tenets of augmented cognition and automation systems theory in terms of task allocation, attentional resources, and situational awareness. The study compares how these principles apply to and interact with each other and with a human/pilot in a closed-loop system. We present a method for integrating augmented cognition systems into airplane flight management systems. We demonstrate systems enhancement with an experiment in which test pilots flew two simulated flights, once without and once with an augmented cognition system. We measured pilot and airplane performance, pilots’ situational awareness, workload management, pilots’ use of cockpit checklists, and flight precision along four axes: (1) altitude, (2) course, (3) radial/bearing and heading, and (4) airspeed

Framework for Architecture Trade Study Using MBSE and Performance Simulation

Increasing complexity in modern systems as well as cost and schedule constraints require a new paradigm of system engineering to fulfill stakeholder needs. Challenges facing efficient trade studies include poor tool interoperability, lack of simulation coordination (design parameters) and requirements flowdown. A recent trend toward Model Based System Engineering (MBSE) includes flexible architecture definition, program documentation, requirements traceability and system engineering reuse. As a new domain MBSE still lacks governing standards and commonly accepted frameworks. This paper proposes a framework for efficient architecture definition using MBSE in conjunction with Domain Specific simulation to evaluate trade studies. A general framework is provided followed with a specific example including a method for designing a trade study, defining candidate architectures, planning simulations to fulfill requirements and finally a weighted decision analysis to optimize system objectives

Mitigating Cognitive Biases in Risk Identification: Practitioner Checklist for the Aerospace Sector

This research contributes an operational checklist for mitigating cognitive biases in the aerospace sector risk management process. The Risk Identification and Evaluation Bias Reduction Checklist includes steps for grounding the risk identification and evaluation activities in past project experiences, through historical data, and the importance of incorporating multiple methods and perspectives to guard against optimism and a singular project instantiation focused view. The authors developed a survey to elicit subject matter expert (SME) judgment on the value of the checklist to support its use in government and industry as a risk management tool. The survey also provided insights on bias mitigation strategies and lessons learned. This checklist addresses the deficiency in the literature in providing operational steps for the practitioner for bias reduction in risk management in the aerospace sector

EXPERIMENTAL AND ANALYTICAL STOCHASTIC FATIGUE OF WELDED STEEL JOINTS

Thirty-nine welded steel specimens have been tested under variable amplitude loadings to determine the extent to which fatigue life is affected by the amplitude variability of the loading and by the high frequency components in the psd of the loading. Constant amplitude tests have also been run to determine the S-N curve so that comparisons can be made between the variable amplitude results and the commonly used analytical techniques such as rainflow analysis, the Rayleigh approximation and the peak counting method. Analytical predictions are based on an S-N curve corrected for the effect of weld residual stress. The twelve different variable amplitude loadings are classified into two groups. The variability of the amplitude of the group I loadings depends on the correlation between the successive extrema. The loadings vary from broadband to extremely narrowband, having peak to adjoining valley correlation values from zero to $-0.995$. Most of these loadings have Rayleigh distributed peaks and valleys. The group II loadings deal with the effect of high frequency components of psd for Gaussian processes. This includes variation of the relative frequency location of the high frequency component in a bimodal psd, and variation of the frequency of truncation of a smooth psd curve. The experimental fatigue lives for group I loadings are all significantly smaller than the predictions by either the Rayleigh approximation or rainflow analysis. The lowest fatigue life found is only 35% of the Rayleigh approximation. The experimental results for group II loadings indicate that the presence of a high frequency component can reduce the fatigue life substantially (as much as 46% for one case studied). Furthermore, it is found that neither of the commonly used analytical techniques can consistently predict the effect of high frequency components. A new damage model is also developed in an attempt to obtain predictions in agreement with the experimental results. The new theoretical results are in very good agreement with the experimental results for group I loadings and group II loadings with unimodal psd's. However, for the two group II loadings with bimodal psd's, the new damage model gives quite conservative predictions

Nonparametric Statistical Analysis of the Reliability of a Naval Aviation Propulsion System

The article of record as published may be located at http://dx.doi.org/10.1111/j.1559-3584.2009.00195.xThis paper reports the results of applying lifetime (or reliability database) statistical analysis methods to engine removal data recorded over the initial 8 years’ service of the General Electric F414-GE-400 turbofan engines propelling the F/A-18 E/F Super Hornet in service with the US Navy, with the intent of better understanding the reasons for engine removal and their impact on engine time on wing (TOW), and to gain an insight into the reliability of the modules and components from which the engine is assembled. It was found that ‘‘coloring’’ the engine removals into three classes of reasons for removal enabled lifetime data analysis revealing interesting and useful features of in-service engine reliability. Nonparametric statistical analysis provided actionable information on engine removal probability as a function of TOW and removal cause that should be applicable to planning flight operations, line maintenance, and support logistics. The analysis of engine removals due to hot section distress appears to disconfirm the presumption of independence between the three classes of removal. Opportunistic maintenance of modules made accessible due to engine removals to service other modules may significantly affect the observed engine removal distribution of the module of interest, i.e., competing risk masks the underlying module hazard functions

Positive Deviance Approach for Identifying Next-Generation System Engineering Best Practices

AbstractSystems Engineering practices, methods, and processes are rapidly evolving to keep pace with the accelerated advances occurring in complex systems development. Often, Systems Engineering curricula reflect methods and processes proven over time and as such don’t necessarily convey the changes occurring at the forefront of complex system development. This paper explores an alternative approach - Positive Deviance - for researching and identifying next-generation Systems Engineering best practices at this knowledge horizon. Positive Deviance has over two decades of proven use in social sciences disciplines as a means of identifying behavioral patterns. The intent of this paper is to demonstrate a method for maintaining a continuously refreshed repertoire of leading edge best practices to supplement traditional training curricula in Systems Engineering. This paper presents a proposed model (DISCO Model) for the integration of the Positive Deviance approach into current knowledge elicitation processes used to capture Systems Engineering best practices. This paper focuses on providing an exploratory discussion of useful steps and guidelines that prospective educators could use to capture next-generation Systems Engineering best practices for inclusion in their training and education curricula