A review of system safety failure probability objectives for Unmanned Aircraft Systems

Unmanned Aircraft Systems (UAS) are one of a number of emerging aviation sectors. Such new aviation concepts present a significant challenge to National Aviation Authorities (NAAs) charged with ensuring the safety of their operation within the existing airspace system. There is significant heritage in the existing body of aviation safety regulations for Conventionally Piloted Aircraft (CPA). It can be argued that the promulgation of these regulations has delivered a level of safety tolerable to society, thus justifying the “default position” of applying these same standards, regulations and regulatory structures to emerging aviation concepts such as UAS. An example of this is the proposed “1309” regulation for UAS, which is based on the 1309 regulation for CPA. However, the absence of a pilot on-board an unmanned aircraft creates a fundamentally different risk paradigm to that of CPA. An appreciation of these differences is essential to the justification of the “default position” and in turn, to ensure the development of effective safety standards and regulations for UAS. This paper explores the suitability of the proposed “1309” regulation for UAS. A detailed review of the proposed regulation is provided and a number of key assumptions are identified and discussed. A high-level model characterising the expected number of third party fatalities on the ground is then used to determine the impact of these assumptions. The results clearly show that the “one size fits all” approach to the definition of 1309 regulations for UAS, which mandates equipment design and installation requirements independent of where the UAS is to be operated, will not lead to an effective management of the risks.

Protection of structural systems and mechanisms from catastrophic and life-threatening failure caused by unforeseeable events

Structural framing systems and mechanisms designed for normal use rarely possess adequate robustness to withstand the effects of large impacts, blasts and extreme earthquakes that have been experienced in recent times. Robustness is the property of systems that enables them to survive unforeseen or unusual circumstances (Knoll & Vogel, 2009). Queensland University of Technology with industry collaboration is engaged in a program of research that commenced 15 years ago to study the impact of such unforeseeable phenomena and investigate methods of improving robustness and safety with protective mechanisms embedded or designed in structural systems. This paper highlights some of the research pertaining to seismic protection of building structures, rollover protective structures and effects of vehicular impact and blast on key elements in structures that could propagate catastrophic and disproportionate collapse.

Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure

This article presents frequentist inference of accelerated life test data of series systems with independent log-normal component lifetimes. The means of the component log-lifetimes are assumed to depend on the stress variables through a linear stress translation function that can accommodate the standard stress translation functions in the literature. An expectation-maximization algorithm is developed to obtain the maximum likelihood estimates of model parameters. The maximum likelihood estimates are then further refined by bootstrap, which is also used to infer about the component and system reliability metrics at usage stresses. The developed methodology is illustrated by analyzing a real as well as a simulated dataset. A simulation study is also carried out to judge the effectiveness of the bootstrap. It is found that in this model, application of bootstrap results in significant improvement over the simple maximum likelihood estimates.

Optimal bounded control of first-passage failure of quasi-integrable Hamiltonian systems with wide-band random excitation

The optimal bounded control of quasi-integrable Hamiltonian systems with wide-band random excitation for minimizing their first-passage failure is investigated. First, a stochastic averaging method for multi-degrees-of-freedom (MDOF) strongly nonlinear quasi-integrable Hamiltonian systems with wide-band stationary random excitations using generalized harmonic functions is proposed. Then, the dynamical programming equations and their associated boundary and final time conditions for the control problems of maximizinig reliability and maximizing mean first-passage time are formulated based on the averaged It$\ddot{\rm o}$ equations by applying the dynamical programming principle. The optimal control law is derived from the dynamical programming equations and control constraints. The relationship between the dynamical programming equations and the backward Kolmogorov equation for the conditional reliability function and the Pontryagin equation for the conditional mean first-passage time of optimally controlled system is discussed. Finally, the conditional reliability function, the conditional probability density and mean of first-passage time of an optimally controlled system are obtained by solving the backward Kolmogorov equation and Pontryagin equation. The application of the proposed procedure and effectiveness of control strategy are illustrated with an example.

First-passage failure and its feedback minimization of quasi-partially integrable Hamiltonian systems

An n degree-of-freedom Hamiltonian system with r (1¡r¡n) independent 0rst integrals which are in involution is calledpartially integrable Hamiltonian system. A partially integrable Hamiltonian system subject to light dampings andweak stochastic excitations is called quasi-partially integrable Hamiltonian system. In the present paper, the procedures for studying the 0rst-passage failure and its feedback minimization of quasi-partially integrable Hamiltonian systems are proposed. First, the stochastic averaging methodfor quasi-partially integrable Hamiltonian systems is brie4y reviewed. Then, basedon the averagedIt ˆo equations, a backwardKolmogorov equation governing the conditional reliability function, a set of generalized Pontryagin equations governing the conditional moments of 0rst-passage time and their boundary and initial conditions are established. After that, the dynamical programming equations and their associated boundary and 0nal time conditions for the control problems of maximization of reliability andof maximization of mean 0rst-passage time are formulated. The relationship between the backwardKolmogorov equation andthe dynamical programming equation for reliability maximization, andthat between the Pontryagin equation andthe dynamical programming equation for maximization of mean 0rst-passage time are discussed. Finally, an example is worked out to illustrate the proposed procedures and the e9ectiveness of feedback control in reducing 0rst-passage failure.

First-passage failure of quasi-integrable Hamiltonian systems

The first-passage failure of quasi-integrable Hamiltonian si-stems (multidegree-of-freedom integrable Hamiltonian systems subject to light dampings and weakly random excitations) is investigated. The motion equations of such a system are first reduced to a set of averaged Ito stochastic differential equations by using the stochastic averaging method for quasi-integrable Hamiltonian systems. Then, a backward Kolmogorov equation governing the conditional reliability function and a set of generalized Pontryagin equations governing the conditional moments of first-passage time are established. Finally, the conditional reliability function, and the conditional probability density and moments of first-passage time are obtained by solving these equations with suitable initial and boundary conditions. Two examples are given to illustrate the proposed procedure and the results from digital simulation are obtained to verify the effectiveness of the procedure.

Risk assessment of patient handling with ambulance stretcher systems (ramp/(winch), easi-loader, tail-lift) using biomechanical failure criteria

The research aims to carry out a detailed analysis of the loads applied by the ambulance workers when loading/unloading ambulance stretchers. The forces required of the ambulance workers for each system are measured using a load cell in a force handle arrangement. The process of loading and unloading is video recorded for all the systems to register the posture of the ambulance workers in different stages of the process. The postures and forces exerted by the ambulance workers are analyzed using biomechanical assessment software to examine if the work loads at any stage of the process are harmful. Kinetic analysis of each stretcher loading system is performed. Comparison of the kinetic analysis and measurements shows very close agreement for most of the cases. The force analysis results are evaluated against derived failure criteria. The evaluation is extended to a biomechanical failure analysis of the ambulance worker's lower back using 3DSSPP software developed at the Centre for Ergonomics at the University of Michigan. The critical tasks of each ambulance worker during the loading and unloading operations for each system are identified. Design recommendations are made to reduce the forces exerted based on loading requirements from the kinetic analysis. © 2006 IPEM.

Success or failure in knowledge management systems: a universal issue

This paper takes a sociotechnical viewpoint of knowledge management system (KMS) implementation in organizations considering issues such as stakeholder disenfranchisement, lack of communication, and the low involvement of key personnel in system design asking whether KMS designers could learn from applying sociotechnical principles to their systems. The paper discusses design elements drawn from the sociotechnical principles essential for the success of IS and makes recommendations to increase the success of KMS in organizations. It also provides guidelines derived from Clegg’s Principles (2000) for KMS designers to enhance their designs. Our data comes from the application of a plurality of analysis methods on a large comprehensive global survey conducted from 2007 to 2011 of 1034 participants from 76 countries. The survey covers a variety of organizations of all types and sizes from a comprehensive selection of economic sectors and industries. Our results showed that users were not satisfied with the information and knowledge systems that they were being offered. In addition to multiple technology and usability issues, there were human and organisational barriers that prevented the systems from being used to their full potential. We recommend that users of KMS are integrated into the design team so that these usability and other barriers can be addressed during the feasibility stage as well as the actual design and implementation phases.

Stochastic Stability for Markovian Jump Linear Systems Subject to a Crucial Failure Event

This paper is concerned with the stability of discrete-time linear systems subject to random jumps in the parameters, described by an underlying finite-state Markov chain. In the model studied, a stopping time τ Δ is associated with the occurrence of a crucial failure after which the system is brought to a halt for maintenance. The usual stochastic stability concepts and associated results are not indicated, since they are tailored to pure infinite horizon problems. Using the concept named stochastic τ-stability, equivalent conditions to ensure the stochastic stability of the system until the occurrence of τ Δ is obtained. In addition, an intermediary and mixed case for which τ represents the minimum between the occurrence of a fix number N of failures and the occurrence of a crucial failure τ Δ is also considered. Necessary and sufficient conditions to ensure the stochastic τ-stability are provided in this setting that are auxiliary to the main result.

Influence of abutment-to-fixture design on reliability and failure mode of all-ceramic crown systems

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

An online failure prediction system for private IaaS platforms

The size and complexity of cloud environments make them prone to failures. The traditional approach to achieve a high dependability for these systems relies on constant monitoring. However, this method is purely reactive. A more proactive approach is provided by online failure prediction (OFP) techniques. In this paper, we describe a OFP system for private IaaS platforms, currently under development, that combines di_erent types of data input, including monitoring information, event logs, and failure data. In addition, this system operates at both the physical and virtual planes of the cloud, taking into account the relationships between nodes and failure propagation mechanisms that are unique to cloud environments.

Set agreement and the loneliness failure detector in crash-recovery systems

The set agreement problem states that from n proposed values at most n-1 can be decided. Traditionally, this problem is solved using a failure detector in asynchronous systems where processes may crash but not recover, where processes have different identities, and where all processes initially know the membership. In this paper we study the set agreement problem and the weakest failure detector L used to solve it in asynchronous message passing systems where processes may crash and recover, with homonyms (i.e., processes may have equal identities) and without a complete initial knowledge of the membership.

Phenomenological research on failure mechanisms of cord reinforced rubber systems. Phase I. Interim report.

National Highway Safety Bureau, Washington, D.C.

An automated failure mode and effect analysis based on high-level design specificication with behavior trees

Formal methods have significant benefits for developing safety critical systems, in that they allow for correctness proofs, model checking safety and liveness properties, deadlock checking, etc. However, formal methods do not scale very well and demand specialist skills, when developing real-world systems. For these reasons, development and analysis of large-scale safety critical systems will require effective integration of formal and informal methods. In this paper, we use such an integrative approach to automate Failure Modes and Effects Analysis (FMEA), a widely used system safety analysis technique, using a high-level graphical modelling notation (Behavior Trees) and model checking. We inject component failure modes into the Behavior Trees and translate the resulting Behavior Trees to SAL code. This enables us to model check if the system in the presence of these faults satisfies its safety properties, specified by temporal logic formulas. The benefit of this process is tool support that automates the tedious and error-prone aspects of FMEA.