• IE interfaces
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• v.25 no.4
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• pp.405-415
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• 2012

The reliability performance measures for low and high or continuous demand modes of operation of safety instrumented systems(SISs) are examined and compared by analyzing the official definitions in IEC 61508 standard. This paper also presents a status of common cause factor(CCF) models used in IEC 61508 and problems relating CCF modelling are discussed and ideas to solve these ones are suggested. An example with mixed M-out-of-N architecture is carried out to illustrate the proposed methods.

• Restorative Dentistry and Endodontics
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• v.46 no.2
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• pp.28.1-28.10
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• 2021

Objectives: This study evaluated the effect of repeated uses and autoclaving in the instrumented area, fracture resistance, and time of instrumentation of thermally treated nickel-titanium reciprocating systems. Materials and Methods: Two hundred simulated canals were instrumented using Reciproc Blue and WaveOne Gold. Each file was used up to 10 times or until fracture. The instrumented area was measured in pre- and post-operative images, using ImageJ software. Kaplan-Meier survival analysis evaluated the number of uses of instruments before fracture. Instrumented area and time of instrumentation were analyzed by Mann-Whitney U test and Kruskal-Wallis. Correlations among the number of uses and instrumented area were measured. The level of statistical significance was set at p < 0.05. Results: Reciproc Blue presented a higher estimated number of uses in comparison with WaveOne Gold (p = 0.026), but autoclaving did not affect the resistance to fracture of instruments (p > 0.05). The instrumented area was different among the evaluated groups (p = 0.039), and the instrumented area along the uses of both tested instruments was reduced. With the time of instrumentation, there was also a significant difference among the evaluated groups; the groups without sterilization cycles were faster, in comparison to those submitted to autoclaving (p = 0.010). Conclusions: Reciproc Blue was more resistant than WaveOne Gold, suffering later fracture. Additionally, the sterilization cycles did not influence the estimated number of uses of thermally treated reciprocating instruments, but the instrumented area of root canals was reduced along with the repeated uses of both instruments.

• Proceedings of the Safety Management and Science Conference
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• 2006.04a
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• pp.513-523
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• 2006

This paper is to introduce guidelines for risk management and analysis. International tandards such as IEC 60300-3-9, IEC 61511-3, ISO 14971-1 and ISO/IEC Guide 73 are considered. This study is to discuss risk analysis of technological systems, and guidelines in the application of hazard and risk analysis for functional safety instrumented system, and risk management of medical devices, and guidelines for use in risk management standards.

• Journal of the Society of Naval Architects of Korea
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• v.55 no.3
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• pp.222-235
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• 2018

The hydrocarbon gas leak in the offshore plant can cause large accidents and lead to significant damages to human, property and environment. For prevention of fire or explosion accidents from gas leak, a SIS(Safety Instrumented System) should be installed. In the early stage of the offshore design, required SIL(Safety Integrated Level) is determined and reliability analysis is performed to verify the design in reliability aspects. This study collected data, information related to reliability analysis and created knowledge model of safety design for the offshore system with MBSE(Model-Based Systems Engineering) concept. Knowledge model could support safety engineer's design tasks as the guidance of reliability analysis procedure of safety design and make good conversation with other engineers in yard, class, company, etc.

• Earthquakes and Structures
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• v.5 no.3
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• pp.359-378
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• 2013

The problem of identification of multi-component and (or) spatially varying earthquake support motions based on measured responses in instrumented structures is considered. The governing equations of motion are cast in the state space form and a time domain solution to the input identification problem is developed based on the Kalman and particle filtering methods. The method allows for noise in measured responses, imperfections in mathematical model for the structure, and possible nonlinear behavior of the structure. The unknown support motions are treated as hypothetical additional system states and a prior model for these motions are taken to be given in terms of white noise processes. For linear systems, the solution is developed within the Kalman filtering framework while, for nonlinear systems, the Monte Carlo simulation based particle filtering tools are employed. In the latter case, the question of controlling sampling variance based on the idea of Rao-Blackwellization is also explored. Illustrative examples include identification of multi-component and spatially varying support motions in linear/nonlinear structures.

• Journal of Computing Science and Engineering
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• v.3 no.2
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• pp.73-87
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• 2009

A hybrid system is a dynamical system in which states can be changed continuously and discretely. Simulation based on numerical methods is the widely used technique for analyzing complicated hybrid systems. Numerical simulation of hybrid systems, however, is subject to two types of numerical errors: truncation error and round-off error. The effect of such errors can make an impossible transition step to become possible during simulation, and thus, to generate a simulation behavior that is not allowed by the model. The possibility of an incorrect simulation behavior reduces con.dence in simulation-based analysis since it is impossible to know whether a particular simulation trace is allowed by the model or not. To address this problem, we define the notion of Instrumented Hybrid Automata (IHA), which considers the effect of accumulated numerical errors on discrete transition steps. We then show how to convert Hybrid Automata (HA) to IRA and prove that every simulation behavior of IHA preserves the discrete transition steps of some behavior in HA; that is, simulation of IHA is sound with respect to HA.

• Restorative Dentistry and Endodontics
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• v.32 no.1
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• pp.61-68
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• 2007

The purpose of this study was to compare the centering abilities of four root canal instrument systems and the amounts of dentin removed after root canal shaping using them. The mesial canals of twenty extracted mandibular first molars having $10-20^{\circ}$ curvature were scanned using X-ray micro-computed tomography (XMCT)-scanner before root canals were instrumented. They were divided into four groups (n = 10 per group). In Group 1, root canals were instrumented by the step-back technique with stainless steel K-Flexofile after coronal flaring. The remainders were instrumented by the crown-down technique with Profile (Group 2), ProTaper (Group 3) or K3 system (Group 4). All canals were prepared up to size 25 at the end-point of preparation and scanned again. Scanned images were processed to reconstruct three-dimensional images using three-dimensional image software and the changes of total canal volume were measured. Pre-and post-operative cross-sectional images of 1, 3, 5, and 7 mm from the apical foramen were com pared. For each level, centering ratio were calculated using Adobe Photoshop 6.0 and image software program. ProTaper and K3 systems have a tendency to remove more dentin than the other file systems. In all groups, the lowest value of centering ratio at 3 mm level was observed. And except at 3 mm level, ProTaper system made canals less centered than the other systems (p < 0.05).

• Journal of the Korean Institute of Gas
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• v.21 no.2
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• pp.32-40
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• 2017

Safety Instrumented Systems (SIS) have wide application area. They are of vital importance at process plants to detect the onset of hazardous events, for instance, a release of some hazardous material, and for mitigating their consequences to humans, material assets, and the environment. The integrated safety systems, where electrical, electronic, and/or programmable electronic (E/E/PE) devices interact with mechanical, pneumatic, and hydraulic systems are governed by international safety standards like IEC 61508. IEC 61508 organises its requirements according to a Safety Life Cycle (SLC). Fulfilling these requirements following the SLC can be complex without the aid of SIS supporting tools. This paper presents simple SIS support tool which can greatly help the user to implement the design phase of the safety lifecycle. This tool is modelled in the form of Android application which can be integrated with a Web-based data reading and modifying system. This tool can reduce the computation time spent on the design phase of the SLC and reduce the possible errors which can arise in the process. In addition, this paper presents an optimization approach to SISs based on cost measures. The multi-objective genetic algorithm has been used for the optimization to search for the best combinations of solutions without enumeration of all the solution space.

• Smart Structures and Systems
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• v.20 no.2
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• pp.139-150
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• 2017

The structural strain plays a significant role in structural condition assessment of in-service bridges in terms of structural bearing capacity, structural reliability level and entire safety redundancy. Therefore, it has been one of the most important parameters concerned by researchers and engineers engaged in structural health monitoring (SHM) practices. In this paper, an SHM system instrumented on the Jiubao Bridge located in Hangzhou, China is firstly introduced. This system involves nine subsystems and has been continuously operated for five years since 2012. As part of the SHM system, a total of 166 fiber Bragg grating (FBG) strain sensors are installed on the bridge to measure the dynamic strain responses of key structural components. Based on the strain monitoring data acquired in recent two years, the strain-based structural condition assessment of the Jiubao Bridge is carried out. The wavelet multi-resolution algorithm is applied to separate the temperature effect from the raw strain data. The obtained strain data under the normal traffic and wind condition and under the typhoon condition are examined for structural safety evaluation. The structural condition rating of the bridge in accordance with the AASHTO specification for condition evaluation and load and resistance factor rating of highway bridges is performed by use of the processed strain data in combination with finite element analysis. The analysis framework presented in this study can be used as a reference for facilitating the assessment, inspection and maintenance activities of in-service bridges instrumented with long-term SHM system.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.