Probability evaluation method for cable safety of long-span cable-stayed bridges

A method of cable safety analysis is proposed for safety evaluation of long-span cable-stayed bridges. The Daniels＇ effect and the probability of broken wires in the cable are introduced to develop the cable strength model and the reliability assessment technique for long-span cable-stayed bridges based on the safety factors analysis of stay cables in service. As an application of the proposed model, the cable safety reliability of the cable No. 25 of Zhaobaoshan cable-stayed bridge in China is calculated. The effects of various parameters on the estimated cable safety reliability are investigated. The results indicate that the proposed method can be used to assess the safety level of stay cables in cable-stayed bridges effectively. The Daniels＇ effect should be taken into account for assessment, and the probability of broken wires can be used to simulate the deterioration of stay cables in service.

Dynamic probability evaluation of safety levels of earth-rockfill dams using Bayesian approach

In order to accurately predict and control the aging process of dams, new information should be collected continuously to renew the quantitative evaluation of dam safety levels. Owing to the complex structural characteristics of dams, it is quite difficult to predict the time-varying factors affecting their safety levels. It is not feasible to employ dynamic reliability indices to evaluate the actual safety levels of dams. Based on the relevant regulations for dam safety classification in China, a dynamic probability description of dam safety levels was developed. Using the Bayesian approach and effective information mining, as well as real-time information, this study achieved more rational evaluation and prediction of dam safety levels. With the Bayesian expression of discrete stochastic variables, the a priori probabilities of the dam safety levels determined by experts were combined wfth the likelihood probability of the real-time check information, and the probability information for the evaluation of dam safety levels was renewed. The probability index was then applied to dam rehabilitation decision-making. This method helps reduce the difficulty and uncertainty of the evaluation of dam safety levels and complies with the current safe decision-making regulations for dams in China. It also enhances the application of current risk analysis methods for dam safety levels.

Genetic Algorithm Optimization Model for Determining the Probability of Failure on Demand of the Safety Instrumented System

A more accurate determination for the Probability of Failure on Demand(PFD)of the Safety Instrumented System(SIS)contributes to more SIS realiability,thereby ensuring more safety and lower cost.IEC 61508 and ISA TR.84.02 provide the PFD detemination formulas.However,these formulas suffer from an uncertaity issue due to the inclusion of uncertainty sources,which,including high redundant systems architectures,cannot be assessed,have perfect proof test assumption,and are neglegted in partial stroke testing(PST)of impact on the system PFD.On the other hand,determining the values of PFD variables to achieve the target risk reduction involves daunting efforts and consumes time.This paper proposes a new approach for system PFD determination and PFD variables optimization that contributes to reduce the uncertainty problem.A higher redundant system can be assessed by generalizing the PFD formula into KooN architecture without neglecting the diagnostic coverage factor(DC)and common cause failures(CCF).In order to simulate the proof test effectiveness,the Proof Test Coverage(PTC)factor has been incorporated into the formula.Additionally,the system PFD value has been improved by incorporating PST for the final control element into the formula.The new developed formula is modelled using the Genetic Algorithm(GA)artificial technique.The GA model saves time and effort to examine system PFD and estimate near optimal values for PFD variables.The proposed model has been applicated on SIS design for crude oil test separator using MATLAB.The comparison between the proposed model and PFD formulas provided by IEC 61508 and ISA TR.84.02 showed that the proposed GA model can assess any system structure and simulate industrial reality.Furthermore,the cost and associated implementation testing activities are reduced.

A novel refined dynamic model of high-speed maglev train-bridge coupled system for random vibration and running safety assessment

Running safety assessment and tracking irregularity parametric sensitivity analysis of high-speed maglev train-bridge system are of great concern,especially need perfect refinement models in which all properties can be well characterized based on various stochastic excitations.A three-dimensional refined spatial random vibration analysis model of high-speed maglev train-bridge coupled system is established in this paper,in which multi-source uncertainty excitation can be considered simultaneously,and the probability density evolution method(PDEM)is adopted to reveal the system-specific uncertainty dynamic characteristic.The motion equation of the maglev vehicle model is composed of multi-rigid bodies with a total 210-degrees of freedom for each vehicle,and a refined electromagnetic force-air gap model is used to account for the interaction and coupling effect between the moving train and track beam bridges,which are directly established by using finite element method.The model is proven to be applicable by comparing with Monte Carlo simulation.By applying the proposed stochastic framework to the high maglev line,the random dynamic responses of maglev vehicles running on the bridges are studied for running safety and stability assessment.Moreover,the effects of track irregularity wavelength range under different amplitude and running speeds on the coupled system are investigated.The results show that the augmentation of train speed will move backward the sensitive wavelength interval,and track irregularity amplitude influences the response remarkably in the sensitive interval.

Safety assessment of Bifidobacterium longum JDM301 based on complete genome sequences

AIM： To assess the safety of Bifidobacterium/ongum （B. longum） JDM301 based on complete genome sequences. METHODS： The complete genome sequences of JDM301 were determined using the GS 20 system. Putative virulence factors, putative antibiotic resis- tance genes and genes encoding enzymes respon- sible for harmful metabolites were identified by blast with virulence factors database, antibiotic resistance genes database and genes associated with harmful metabolites in previous reports. Minimum inhibitory concentration of 16 common antimicrobial agents was evaluated by E-test RESULTS： JDM301 was shown to contain 36 genes as- sociated with antibiotic resistance, 5 enzymes related to harmful metabolites and 162 nonspecific virulence fac- tors mainly associated with transcriptional regulation, adhesion, sugar and amino acid transport. B. longum JDM301 was intrinsically resistant to ciprofloxacin, ami- kacin, gentamicin and streptomycin and susceptible to vancomycin, amoxicillin, cephalothin, chloramphenicol, erythromycin, ampicillin, cefotaxime, rifampicin, imi- penem and trimethoprim-sulphamethoxazol. JDM301 was moderately resistant to bacitracin, while an earlier study showed that bifidobacteria were susceptible to this antibiotic. A tetracycline resistance gene with the risk of transfer was found in JDM301, which needs to be experimentally validated. CONCLUSION： The safety assessment of JDM301 using information derived from complete bacterial ge- nome will contribute to a wider and deeper insight into the safety of probiotic bacteria.

Analyzing Effect of Demand Rate on Safety of Systems with Periodic Proof-tests

Quantitative safety assessment of safety systems plays an important role in decision making at all stages of system lifecycle, i.e., design, deployment and phase out. Most safety assessment methods consider only system parameters, such as configuration, hazard rate, coverage, repair rate, etc. along with periodic proof-tests （or inspection）. Not considering demand rate will give a pessimistic safety estimate for an application with low demand rate such as nuclear power plants, chemical plants, etc. In this paper, a basic model of IEC 61508 is used. The basic model is extended to incorporate process demand and behavior of electronic- and/or computer-based system following diagnosis or proof-test. A new safety index, probability of failure on actual demand （PFAD） based on extended model and demand rate is proposed. Periodic proof-test makes the model semi-Markovian, so a piece-wise continuous time Markov chain （CTMC） based method is used to derive mean state probabilities of elementary or aggregated state. Method to determine probability of failure on demand （PFD） （IEC 61508） and PFAD based on these state probabilities are described. In example, safety indices of PFD and PFAD are compared.

Quantitative assessment of flight safety under atmospheric icing conditions

A quantitative assessment method is proposed to sense the specific effects of atmospheric icing conditions on flight safety. A six degree-of-freedom computational flight dynamics model is used to study the effects of ice accretion on aircraft dynamics, and a pilot model is also involved. In order to investigate icing severity under different icing conditions, support vector regression is applied in establishing relationship between aircraft icing parameter and weather conditions. Considering the characteristics of aircraft icing accidents, a risk probability assessment model optimized by the particle swarm method is developed to measure the safety level. In particular, angle of attack is chosen as a critical parameter in this method. Results presented in the paper for a series of simulation show that this method captures the basic effects of atmospheric icing conditions on flight safety, which may provide an important theoretical reference for icing accidents avoidance.

Analyzing Crash-Prone Drivers in Multiple Crashes for Better Safety Educational and Enforcement Strategies

Crash-prone drivers should be effectively targeted for various safety education and regulation programs because their over-involvement in crashes presents a big adverse effect on highway safety. By analyzing seven years of crash data from Louisiana, this paper investigates crash-prone drivers’ characteristics and estimates their risk to have crashes in the seventh year based on these drivers’ crash history of the past six years. The analysis results show that quite a few drivers repeatedly had crashes;seven drivers had 13 crashes in seven years;and the maximum number of crashes occurring in a single year to a single driver is eight. The probability of having crash(es) in any given year is closely related to a driver’s crash history: less than 4% for drivers with no crash in the previous six years;and slightly higher than 30% for drivers with nine or more crashes in the previous six years. Based on the results, several suggestions are made on how to improve roadway safety through reducing crashes committed by drivers with much higher crash risk as identified by the analysis.

Safety Assessment for Autonomous Aerial Refueling Based on Reachability Analysis

Autonomous aerial refueling(AAR)has demonstrated significant benefits to aviation by extending the aircraft range and endurance.It is of significance to assess system safety for autonomous aerial refueling.In this paper,the reachability analysis method is adopted to assess system safety.Due to system uncertainties,the aerial refueling system can be considered as a stochastic system.Thus,probabilistic reachability is considered.Since there is a close relationship between reachability probability and collision probability,the collision probability of the AAR system is analyzed by using reachability analysis techniques.Then,the collision probability is accessed by using the Monte-Carlo experiment method.Finally,simulations demonstrate the effectiveness of the proposed safety assessment method.

Study on System Failure Probability Model Based on Dynamic Fault Tree

Aiming at the characteristics of complex logic relation and multiple dynamic gates in system,its failure probability model is established based on dynamic fault tree. For the multi-state dynamic fault tree,it can be transferred into Markov chain with continuous parameters. The state transfer diagram can be decomposed into several state transfer chains,and the failure probability models can be derived according to the lengths of the chains. Then,the failure probability of the dynamic fault tree analysis(DFTA) can be obtained by adding each chain's probability. The failure probability calculation of DFTA based on the continuous parameter Markov chain is proposed and proved. Given an example,the analytic method is compared with the conventional methods which have to solve the differential equation. It is known from the results that the analytic method can be applied to engineering easily.

Methods of spacecraft impulsive relative hovering and trajectory safety analysis

Based on the analytical solutions of T-H equations and its state transition matrix form,the open-loop control method of spacecraft impulsive relative hovering was studied,which is promising for practical engineering use.The true anomaly intervals of the hovering impulse were optimized by the nonlinear mathematical programming.Based on the calculation of collision probability,the method of safety analysis and risk management was proposed.The numerical simulations show that the introduced relative hovering method can be used for circular and elliptical reference orbits hovering.Furthermore,the local optimal solution can be obtained by applying the true anomaly intervals optimization method.The maximum collision probability and the minimum relative distance nearly appear at the same time.And,the smaller the relative distance is,the larger the collision probability.

Bayesian estimator of human error probability based on human performance data

A Bayesian method for estimating human error probability（HEP） is presented.The main idea of the method is incorporating human performance data into the HEP estimation process.By integrating human performance data and prior information about human performance together,a more accurate and specific HEP estimation can be achieved.For the time-unrelated task without rigorous time restriction,the HEP estimated by the common-used human reliability analysis（HRA） methods or expert judgments is collected as the source of prior information.And for the time-related task with rigorous time restriction,the human error is expressed as non-response making.Therefore,HEP is the time curve of non-response probability（NRP）.The prior information is collected from system safety and reliability specifications or by expert judgments.The（joint） posterior distribution of HEP or NRP-related parameter（s） is constructed after prior information has been collected.Based on the posterior distribution,the point or interval estimation of HEP/NRP is obtained.Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach.

A Safety Relay Selection Method Based on Network Coding

A method of cooperative relay selection based on network coding security is proposed for relay selection problem of cooperative communication system security in networked multi-relay scenarios, which is different from the existing relay node selection method. The algorithm not only merged with timestamp and homomorphic signature to construct the node degree of safety to find reliable relay, at the same time to considers the received signal to noise ratio at all relay nodes value and the channel gain to the source node. The simulation results show that the proposed method can improve the achievable rate of the destination node and reduce the outage probability on the basis of guaranteeing the safety of the relay node.

Handling Uncertainty in Human Cognitive Reliability Method for Safety Assessment Based on DSET

Human Reliability Analysis(HRA)is an important part in safety assessment of a large complex system.Human Cognitive Reliability(HCR)model is a method of evaluating the probability that operators fail to complete during diagnostic decision making within a limited time,which is widely used in HRA.In the application of this method,cognitive patterns of humans are required to be considered and classified,and this process often relies on the evaluation opinions of experts which is highly subjective and uncertain.How to effectively express and process this uncertain and subjective information plays a critical role in improving the accuracy and applicability of HCR.In this paper,a new model was proposed to deal with the uncertain information which exists in the processes of cognitive pattern classification in HCR.First,an evaluation panel was constructed based on expert opinions and processing including setting corresponding anchor points and qualitative indicators of different cognitive patterns,and mapping them to fuzzy numbers and unit intervals.Second,based on the evaluation panel,different analysts judge the cognitive pattern types of actual specific events and provide the level of confidence he or she has in the judgments.Finally,the evaluation opinions of multiple analysts were expressed and fused based on the Dempster-Shafer Evidence Theory(DSET),and the fused results were applied to the HCR model to obtain the Human Error Probability(HEP).A case study was used to demonstrate the procedure and effectiveness of the proposed method.

故障树和模糊贝叶斯网络在管廊运维风险评估中的应用研究

地下综合管廊是城市的生命线,一旦出现问题就会对人们生命财产安全造成巨大损害。为了系统地分析管廊运维风险,建立了基于模糊贝叶斯网络的风险评估框架。首先,通过分析管廊运维风险源与风险形成的原因以确定风险事件和风险类别;其次,建立管廊运维风险故障树来梳理风险因素之间的逻辑关系,将故障树映射为贝叶斯网络;最后,结合专家模糊评价,构建地下综合管廊运维风险评估模型。案例分析结果显示:中间事件“火灾、爆炸”与“危害气体浓度过高”的发生概率较高。敏感性分析结果显示:“运维人员操作和维护不当”是导致管廊运维风险发生的根本事件,因此需要制定严格管理措施及规范,加强对运维人员的素质培训,以降低管廊运维过程中各种风险的发生概率。

区间概率下基于证据理论的引信安全失效率评估方法

针对底事件基础数据匮乏给引信安全性评估带来的难题,采用证据理论对区间概率下的引信安全失效率进行分析和评估。通过构造基本信任分配函数来表征底事件区间概率的不确定性;在此基础上,利用累积似然函数和累计信任函数,基于故障树的结构函数将不确定性逐层传递,最终获得顶事件的概率包络。仿真结果表明,该方法不仅给出了引信安全失效率的上下界限,同时提供了其所有可能的累积分布函数,适用于对引信安全失效率进行评估和不确定性量化。

改进的MVO-GRNN神经网络岩爆预测模型研究

准确预测岩爆烈度等级能有效指导岩爆灾害的防控。根据影响岩爆发生及烈度等级的3个因素构建岩爆评价指标体系,提出一种基于改进多元宇宙算法(Improved Multi-Verse Optimizer,IMVO)优化广义回归神经网络(General Regression Neural Network,GRNN)的岩爆预测模型。在普通多元宇宙算法(MVO)的基础上,运用自适应平衡机制调节MVO算法中的虫洞存在概率(V_(WEP))和旅行距离率(V_(TDR))两个重要参数来改进该算法;再运用改进的多元宇宙算法优化广义回归神经网络的光滑度,通过训练数据优选出最佳光滑因子σ,得到IMVO-GRNN神经网络岩爆烈度预测模型;最后结合工程实例验证模型的性能。研究表明,该模型相比传统模型寻优能力更强,精度更高,为岩爆预测提供了一种新的思路。

基于蒙特卡罗方法的煤矿爆破作业风险评估

为量化分析煤矿爆破作业各作业步骤造成的风险以及全面客观地对其进行风险评估,借助蒙特卡罗方法建立煤矿爆破作业步骤风险评估模型,对作业流程的行为风险后果值进行累积概率分布,最终依据蒙特卡罗方法模拟的均值结果和作业流程总体风险结果判定各作业步骤的风险大小和风险等级,并提出控制此类不安全行为发生的措施。结果表明:爆破作业流程风险大小顺序依次为清退物品入库、装药、连线、警戒、起爆后安全检查、领取并检查爆破物品、起爆、运送爆破物品、接受爆破任务、作业前安全检查、起爆前安全检查、封孔。

常泰长江大桥船撞抗力研究及安全性评估

为确保常泰长江大桥建设和服役安全,对大桥进行船撞抗力研究及安全性评估。采用单位荷载法计算各涉水下部结构船撞抗力及其船撞破坏控制模式;基于船-桥碰撞概率模型得到各墩碰撞概率,明确常泰长江大桥船撞风险等级,通过对比数值模拟和经验公式计算的船撞力,确定设防船型碰撞各下部结构船撞力;以船撞安全系数和实际防撞吨位为指标进行船撞安全评估。结果表明:1~4号墩船撞破坏模式均由碰撞截面抗剪强度控制,5号和6号塔船撞破坏模式均由基底地基竖向承载力控制;在目前船舶流量下全桥船舶年碰撞概率为1.58次/年,与同类桥梁相比船舶碰撞风险较低且处于安全可控水平,大桥孔跨布置和航道规划合理;全桥涉水下部结构船撞安全系数为1.10~6.54,各下部结构实际防撞吨位均大于相应设防船型吨位,常泰长江大桥涉水下部结构抗船撞性能满足要求。

考虑随机场的盾构下穿条件下既有高铁交会行车安全性

针对路基段高铁行车安全分析常将地基土视作具有确定性参数的介质的问题,文中基于随机场理论,将地基土视为具有纵向一致性的三维介质,建立了盾构下穿既有高铁的数值模型,并基于数论选点方法模拟地基土横截面的参数随机性。为更进一步研究盾构下穿高速铁路对高铁行车安全性的影响,文中建立了31自由度的高铁列车模型,结合Fluent 3D流体仿真软件和动网格技术,获得了高速列车的气动荷载时程曲线。基于概率密度演化理论分析了高铁列车以300、350和400 km/h的速度交会时的脱轨系数及其概率密度演化信息。结果表明:随机场的存在使得车辆的轮重减载率和脱轨系数具有一定的概率分布范围;在气动荷载和隧道下穿引起的既有高铁线路基变形影响下,垂向轮轨力曲线有明显的波动情况;轮重减载率最大值出现在地表沉降最大值两侧的下降段;垂向气动荷载大于横向气动荷载;随着车速的增加,轮重减载率及脱轨系数的各上限均在逐渐增大,为保证高铁交会行车的安全性,建议在盾构下穿既有线地段的高铁列车运行速度应不超过300 km/h。