Dynamic fault tree analysis using Monte Carlo simulation in probabilistic safety assessment

Traditional fault tree (FT) analysis is widely used for reliability and safety assessment of complex and critical engineering systems. The behavior of components of complex systems and their interactions such as sequence- and functional-dependent failures, spares and dynamic redundancy management, and priority of failure events cannot be adequately captured by traditional FTs. Dynamic fault tree (DFT) extend traditional FT by defining additional gates called dynamic gates to model these complex interactions. Markov models are used in solving dynamic gates. However, state space becomes too large for calculation with Markov models when the number of gate inputs increases. In addition, Markov model is applicable for only exponential failure and repair distributions. Modeling test and maintenance information on spare components is also very difficult. To address these difficulties, Monte Carlo simulation-based approach is used in this work to solve dynamic gates. The approach is first applied to a problem available in the literature which is having non-repairable components. The obtained results are in good agreement with those in literature. The approach is later applied to a simplified scheme of electrical power supply system of nuclear power plant (NPP), which is a complex repairable system having tested and maintained spares. The results obtained using this approach are in good agreement with those obtained using analytical approach. In addition to point estimates of reliability measures, failure time, and repair time distributions are also obtained from simulation. Finally a case study on reactor regulation system (RRS) of NPP is carried out to demonstrate the application of simulation-based DFT approach to large-scale problems.     

Identifying behaviour patterns of construction safety using system archetypes

Construction safety management involves complex issues (e.g., different trades, multi-organizational project structure, constantly changing work environment, and transient workforce). Systems thinking is widely considered as an effective approach to understanding and managing the complexity. This paper aims to better understand dynamic complexity of construction safety management by exploring archetypes of construction safety. To achieve this, this paper adopted the ground theory method (GTM) and 22 interviews were conducted with participants in various positions (government safety inspector, client, health and safety manager, safety consultant, safety auditor, and safety researcher). Eight archetypes were emerged from the collected data: (1) safety regulations, (2) incentive programs, (3) procurement and safety, (4) safety management in small businesses (5) production and safety, (6) workers’ conflicting goals, (7) blame on workers, and (8) reactive and proactive learning. These archetypes capture the interactions between a wide range of factors within various hierarchical levels and subsystems. As a free-standing tool, they advance the understanding of dynamic complexity of construction safety management and provide systemic insights into dealing with the complexity. They also can facilitate system dynamics modelling of construction safety process.     

First-order differential sensitivity analysis of a nuclear safety system by Monte Carlo simulation

In this paper we employ a Monte Carlo method to compute the first-order, differential sensitivity indexes of the basic events characterizing the reliability behavior of the containment spray injection system of a nuclear power plant. An exemplification is provided as to how the obtained sensitivity indexes can be used to drive improvements in the system design and operation.     

Structural reliability optimization using an efficient safety index calculation procedure

The objective of this paper is to conduct reliability-based structural optimization in a multidisciplinary environment. An efficient reliability analysis is developed by expanding the limit functions in terms of intermediate design variables. The design constraints are approximated using multivariate splines in searching for the optimum. The reduction in computational cost realized in safety index calculation and optimization are demonstrated through several structural problems. This paper presents safety index computation, analytical sensitivity analysis of reliability constraints and optimization using truss, frame and plate examples.     

Principles of engineering safety: Risk and uncertainty reduction

This article provides a systematised account of safety engineering practices that clarifies their relation to the goal of safety engineering, namely to increase safety. We list 24 principles referred to in the literature of safety engineering, dividing them into four major categories: Inherently safe design, Safety reserves, Safe fail and Procedural safeguards. It emerges from this systematisation that important aspects of these methods can be better understood with the help of the distinction between risk and uncertainty.     

Cognitive modeling and dynamic probabilistic simulation of operating crew response to complex system accidents: Part 5: Dynamic probabilistic simulation of the IDAC model

This is the last in a series of five papers that discuss the Information Decision and Action in Crew (IDAC) context for human reliability analysis (HRA) and example application. The model is developed to probabilistically predict the responses of the control room operating crew in nuclear power plants during an accident, for use in probabilistic risk assessments (PRA). The operator response spectrum includes cognitive, emotional, and physical activities during the course of an accident. This paper describes a dynamic PRA computer simulation program, accident dynamics simulator (ADS), developed in part to implement the IDAC model. This paper also provides a detailed example of implementing a simpler version of IDAC, compared with the IDAC model discussed in the first four papers of this series, to demonstrate the practicality of integrating a detailed cognitive HRA model within a dynamic PRA framework.     

有限元仿真方法评价护栏安全性能的可行性

建立多种车辆和护栏有限元仿真模型,运用多次碰撞试验数据对仿真模型计算结果进行比对,对采用有限元仿真方法评价护栏安全性能的可行性进行分析。研究结果表明,仿真计算可以得到车辆行驶轨迹、结构防护导向、乘员风险和动态变形等护栏安全评价的各项指标,仿真结果与试验结果一致,误差在10%以内,验证了建模方法的正确性,运用有限元仿真方法评价护栏安全性能具有较高可行性。强调运用评价护栏安全性能的仿真模型须通过碰撞试验校核,同时建议通过法规和准则对从事护栏评价CAE工程师进行职业管理。     

Sensitivity and uncertainty analysis in optimization programs using an evolutionary approach: a maintenance application

Indirect-Grouping Maintenance Strategy requires the calculation of an optimum (global) according to a minimization program P. However the model on which the optimal is based may be incomplete in the sense that important uncertainties have not been considered. In order to evaluate the effects of the uncertainty of the parameters or how the uncertainty is propagated in the optimization program, the decision-maker needs to evaluate the range of variation of program P.In this work an innovative two step evolutionary approach to analyze uncertainties in Indirect-Grouping Maintenance Strategies is presented. The proposed approach combines the two proven techniques of Cellular Evolutionary Strategies (CES) and Evolutionary Strategies (ES) for the optimization problem. The approach does not guarantee the global optimum, but the experiments show that the results are very close to the real one. The examples presented confirm that the approach produces very good approximations for the range of the minimum when there is uncertainty in the model parameters and can be used as a tool for uncertainty/sensitivity analysis in other areas.     

集成电路封装的三维热模拟与分析

以有限元方法为基础的计算机模拟技术在集成电路封装热设计中是一种重要的热模拟和分析工具。本文运用有限元方法对多热源条件下集成电路封装的热场进行了模拟和分析。模拟结果与测量值非常接近，证实了模拟方法的有效性。模拟结果表明：在本模拟条件下，由芯片到封装外壳底面的热通路为散热的主要通道，其它表面的对流条件对热场分布影响不大。     

Impact factors for a composite steel bridge using non-linear dynamic simulation

Traditionally, bridges are designed using static loads that are increased by the dynamic load allowance (DLA) factor (or dynamic amplification factor). The DLA factor is a function of span or first flexural natural frequency of the bridge, and indirectly incorporates the dynamic effects of moving vehicles in the design. This article firstly reviews the literature on impact loading of bridge decks. Analytical methods published previously are evaluated and the bridge–vehicle interaction is found to be the most reliable method among them. The article then presents a 3D finite element model to study the bridge–vehicle interaction. Finite elements are developed to simulate the trucks, the road surface and the composite girder bridge itself. Truck parameters include the body, suspension and tires, with variables being the total weight and the speed. The bridge superstructure is treated as a 3D composite steel girder bridge incorporating special end springs that simulate the elastomeric bearings. A parametric study is performed to identify the effect of various parameters on DLA, such as vehicle speed, aspect ratio of steel girders, stiffness of neoprene, type of vehicle, vehicle lane eccentricity and initial bounce of the vehicle due to road surface roughness. The results indicate that the DLA is correlated well with the velocity of the truck, especially at high speed. DLA is vehicle dependent and the dynamic and static live loads can be considered uncorrelated, except when the truck weight is less than 10 percent of the total deck weight, for which a low degree of correlation is observed. The DLA is decreased as the vehicle lane eccentricity (with respect to the deck centerline) is increased, and the same relationship exists with the bridge span length. No distinctive correlation is observed between the DLA and the initial bounce of vehicle at the time of entrance to span.     

Dynamic simulation of human motion: numerically efficient inclusion of muscle physiology by convex optimization

Determining the muscle forces that underlie some experimentally observed human motion, is a challenging biomechanical problem, both from an experimental and a computational point of view. No non-invasive method is currently available for experimentally measuring muscle forces. The alternative of computing them from the observed motion is complicated by the inherent overactuation of the human body: it has many more muscles than strictly needed for driving all the degrees of freedom of the skeleton. As a result, the skeleton’s equations of motion do not suffice to determine the muscle forces unambiguously. Therefore, muscle force determination is often reformulated as a (large-scale) optimization problem. Generally, the optimization approaches are classified according to the formalism, inverse or forward, adopted for solving the skeleton’s equations of motion. Classical inverse approaches are fast but do not take into account the constraints imposed by muscle physiology. Classical forward approaches, on the other hand, do take the muscle physiology into account but are extremely costly from a computational point of view. The present paper makes a double contribution. First, it proposes a novel inverse approach that results from including muscle physiology (both activation and contraction dynamics) in the inverse dynamic formalism. Second, the efficiency with which the corresponding optimization problem is solved is increased by using convex optimization techniques. That is, an approximate convex program is formulated and solved in order to provide a hot-start for the exact nonconvex program. The key element in this approximation is a (global) linearization of muscle physiology based on techniques from experimental system identification. This approach is applied to the study of muscle forces during gait. Although the results for gait are promising, experimental study of faster motions is needed to demonstrate the full power and advantages of the proposed methodology, and therefore is the subject of subsequent research.     

Road safety risk evaluation and target setting using data envelopment analysis and its extensions

Currently, comparison between countries in terms of their road safety performance is widely conducted in order to better understand one's own safety situation and to learn from those best-performing countries by indicating practical targets and formulating action programmes. In this respect, crash data such as the number of road fatalities and casualties are mostly investigated. However, the absolute numbers are not directly comparable between countries. Therefore, the concept of risk, which is defined as the ratio of road safety outcomes and some measure of exposure (e.g., the population size, the number of registered vehicles, or distance travelled), is often used in the context of benchmarking. Nevertheless, these risk indicators are not consistent in most cases. In other words, countries may have different evaluation results or ranking positions using different exposure information. In this study, data envelopment analysis (DEA) as a performance measurement technique is investigated to provide an overall perspective on a country's road safety situation, and further assess whether the road safety outcomes registered in a country correspond to the numbers that can be expected based on the level of exposure. In doing so, three model extensions are considered, which are the DEA based road safety model (DEA-RS), the cross-efficiency method, and the categorical DEA model. Using the measures of exposure to risk as the model's input and the number of road fatalities as output, an overall road safety efficiency score is computed for the 27 European Union (EU) countries based on the DEA-RS model, and the ranking of countries in accordance with their cross-efficiency scores is evaluated. Furthermore, after applying clustering analysis to group countries with inherent similarity in their practices, the categorical DEA-RS model is adopted to identify best-performing and underperforming countries in each cluster, as well as the reference sets or benchmarks for those underperforming ones. More importantly, the extent to which each reference set could be learned from is specified, and practical yet challenging targets are given for each underperforming country, which enables policymakers to recognize the gap with those best-performing countries and further develop their own road safety policy.     

Reliability-based design optimization using a generalized subset simulation method and posterior approximation

The evaluation of the probabilistic constraints in reliability-based design optimization (RBDO) problems has always been significant and challenging work, which strongly affects the performance of RBDO methods. This article deals with RBDO problems using a recently developed generalized subset simulation (GSS) method and a posterior approximation approach. The posterior approximation approach is used to transform all the probabilistic constraints into ordinary constraints as in deterministic optimization. The assessment of multiple failure probabilities required by the posterior approximation approach is achieved by GSS in a single run at all supporting points, which are selected by a proper experimental design scheme combining Sobol’ sequences and Bucher’s design. Sequentially, the transformed deterministic design optimization problem can be solved by optimization algorithms, for example, the sequential quadratic programming method. Three optimization problems are used to demonstrate the efficiency and accuracy of the proposed method.     

Risk assessment for civil engineering facilities: critical overview and discussion

The present paper should be seen as a basis for discussion of important aspects of risk analysis and assessment, as well as attempting to describe risk assessment in accordance with the present state of the art. Risk assessment is thus presented in an overview form from the viewpoint of being a means for decision-making and thus within the formal framework of decision theory. First the motivation for risk analysis is given and the theoretical basis together with the practical aspects, methodologies and techniques for the implementation of risk assessment in civil engineering applications are explained and discussed. The paper furthermore addresses the problems associated with risk acceptance criteria, risk aversion and value of human life and attempts to provide suggestions for the rational treatment of these aspects. Finally a number of problem areas are highlighted and the needs for further education, research and dissemination are stressed.     

RADS — a computer package for refrigeration analysis, design and simulation

A commercially available computer package for refrigeration analysis, design and simulation is described. Its main applications are heat load determination, multi-stage compression plant layout design, and simulation of the interactions between refrigerant plant, applications and control systems.     

An evaluation of a supplementary road safety package

A Supplementary Road Safety Package (SRSP) was developed in New Zealand in 1995/1996 to supplement the compulsory breath test (CBT) and speed camera programmes introduced in 1993. A major feature of the package was the use of emotion and shock advertising campaigns not only to affect high risk driving attitudes and behaviours towards speeding and drink-driving but also to encourage the use of safety belts. Furthermore, the SRSP also emphasised targeting enforcement to these three areas. This package continued for 5 years. This paper estimates the effect of the package on road trauma. The analysis shows that the Package made substantial impact on road safety and saved over 285 lives over the 5-year period.     

高土石坝工程安全评价与预警信息管理系统

基于现场监测数据及先进的数值分析方法,建立土石坝全生命周期的工程安全评价及预警信息系统,是目前土石坝发展的必然趋势。以糯扎渡高心墙堆石坝为依托,开发了理论严密、方法先进且可靠实用的大坝工程安全评价与预警信息管理系统。该系统由系统管理模块、安全指标模块、监测数据与工程信息模块、数值计算模块、反演分析模块、安全预警与应急预案模块和数据库及管理模块共7个模块构成。其中,数值计算和反演分析模块可利用所取得的坝体监测数据,进行渗流、大坝应力变形、坝体裂缝、地震动力反应和坝坡稳定等土石坝关键计算分析,是本系统的核心部分。利用工程前期已经取得的坝体变形监测数据,对坝体进行了变形反演分析并对大坝关键时间结点的形态进行了预测分析。     

Risk analysis of a biomass combustion process using MOSAR and FMEA methods

Thermal and chemical conversion processes that convert in energy the sewage sludge, pasty waste and other pre-processed waste are increasingly common, for economic and ecological reasons. Fluidized bed combustion is currently one of the most promising methods of energy conversion, since it burns biomass very efficiently, and produces only very small quantities of sulphur and nitrogen oxides. The hazards associated with biomass combustion processes are fire, explosion and poisoning from the combustion gases (CO, etc.). The risk analysis presented in this paper uses the MADS-MOSAR methodology, applied to a semi-industrial pilot scheme comprising a fluidization column, a conventional cyclone, two natural gas burners and a continuous supply of biomass. The methodology uses a generic approach, with an initial macroscopic stage where hazard sources are identified, scenarios for undesired events are recognized and ranked using a grid of SeverityxProbability and safety barriers suggested. A microscopic stage then analyzes in detail the major risks identified during the first stage. This analysis may use various different tools, such as HAZOP, FMEA, etc.: our analysis is based on FMEA. Using MOSAR, we were able to identify five subsystems: the reactor (fluidized bed and centrifuge), the fuel and biomass supply lines, the operator and the environment. When we drew up scenarios based on these subsystems, we found that malfunction of the gas supply burners was a common trigger in many scenarios. Our subsequent microscopic analysis, therefore, focused on the burners, looking at the ways they failed, and at the effects and criticality of those failures (FMEA). We were, thus, able to identify a number of critical factors such as the incoming gas lines and the ignition electrode.     

电主轴冷却系统设计与仿真优化

为解决电主轴因内部温度场复杂而造成冷却效果差的问题,设计了一种用于电主轴冷却的水冷机系统。根据电主轴热特性分析结果,提出了水冷机冷却方案,计算了相关的传热参数,并建立了电主轴温度-流速控制模型。然后,利用ANSYS Fluent软件对电主轴进行了流体冷却有限元仿真,并通过电主轴冷却实验对仿真结果进行了验证。通过对比仿真结果和实验结果可知,冷却后电主轴电机定子最高温度约下降了60%,转轴的形变量约降低了70%。结果表明：利用水冷机系统对电主轴进行冷却具有良好的冷却效果,这可为高精密机床主动热控制技术的研究提供一定的借鉴和参考。     

Stability assessment of earth slope using modified particle swarm optimization

This paper has proposed an effective method to determine the minimum factor of safety (FS) and associated critical failure surface in slope stability analysis. The search for the minimum FS based on limit equilibrium methods is a complex optimization problem as the objective function is non-smooth and non-convex. Recently, particle swarm optimization (PSO) as a meta-heuristic optimization algorithm has been developed with success in treating various types of problems. In the current study, a new approach of PSO is proposed to calculate the safety factor of earth slopes. The safety factors of the general slip surfaces are calculated using Spencer method of slices, and each new slip surface is randomly generated by straight line technique. The reliability and efficiency of the proposed algorithm are examined by considering a number of published cases. The results indicate that the new method can predict a more critical failure mechanism with a lower FS and can outperform the other methods in the literature as well as standard PSO. Finally, the proposed method will be validated by considering an existing slope failure in Ulu Klang, Malaysia.