人因失误的机理及其可靠性研究

随着科技的发展 ,在系统安全中 ,机器设备可靠性越来越高 ,由于人本身的复杂性 ,人因失误变得愈来愈严重。本文基于人行为的原理 ,对人因失误的机理、影响人失误的因素、人行为的模型和失误模型及其可靠性的量化进行了分析 ,建立了计算人可靠性的威布尔分布模型 ,并对其参数进行了讨论 ,可用此来评价人的可靠性。     

APPLICATION OF GREY MODEL TOWARD RUNOFF FORECASTING1

ABSTRACT: A reliable forecasting model is essential in real‐time flood forecasting for reducing natural damage. Efforts to develop a real‐time forecasting model over the past two decades have been numerous. This work applies the Grey model to forecast rainfall and runoff owing to the model's relative ability to predict the future using a small amount of historical data. Such a model significantly differs from the stochastic and deterministic models developed previously. Ten historical storm events from two catchment areas in northern Taiwan are selected to calibrate and verify the model. Results in this study demonstrate that the proposed models can reasonably forecast runoff one to four hours ahead, if the Grey error prediction method is further used to update the output of the model.     

Performance of a Bayesian state-space model of semelparous species for stock-recruitment data subject to measurement error

Measurement errors in spawner abundance create problems for fish stock assessment scientists. To deal with measurement error, we develop a Bayesian state-space model for stock-recruitment data that contain measurement error in spawner abundance, process error in recruitment, and time series bias. Through extensive simulations across numerous scenarios, we compare the statistical performance of the Bayesian state-space model with that of standard regression for a traditional stock-recruitment model that only considers process error. Performance varies depending on the information content in data, as determined by stock productivity, types of harvest situations, and amount of measurement error. Overall, in terms of estimating optimal spawner abundance S_MSY, the Ricker density-dependence parameter β, and optimal harvest rate h_MSY, the Bayesian state-space model works best for informative data from low and variable harvest rate situations for high-productivity salmon stocks. The traditional stock-recruitment model (TSR) may be used for estimating α and h_MSY for low-productivity stocks from variable and high harvest rate situations. However, TSR can severely overestimate S_MSY when spawner abundance is measured with large error in low and variable harvest rate situations. We also found that there is substantial merit in using h_MSY (or benchmarks derived from it) instead of S_MSY as a management target.     

Inverse modeling to estimate LNAPL plume release timing

Methodologies are presented for dating releases of light nonaqueous phase liquids (LNAPLs) using an inverse modeling approach with simple analytical models. Models for LNAPL plume migration are presented to predict LNAPL plume velocity in the unsaturated and saturated zones as a function of basic soil and fluid properties. A relative mobility factor is introduced for LNAPL movement at the water table that depends primarily on the van Genuchten n parameter (related to the breadth of the soil pore size distribution) and the magnitude of water table fluctuations. Estimated LNAPL plume velocities compare reasonably with more rigorous numerical models, which may be used in cases where data availability warrant the greater effort entailed.Two methods of estimating release timing and its uncertainty are investigated. A direct estimation method is described that determines travel time for a single observed travel distance based on estimated soil and fluid properties. Release date uncertainty may be determined using the first order (FO) or Monte Carlo (MC) methods. The second method for estimating release date involves nonlinear parameter estimation utilizing distance vs. time measurements and other data.A case study is presented for a field site where independent estimates of release timing were obtained from a numerical modeling analysis. Release timing estimates based on direct inversion of the analytical timing model agree well with the numerical analysis. Results for a second field site indicate that release date confidence limits estimated by the FO method, assuming log-normally distributed travel times, are close to values determined by the MC method, which makes no assumption regarding the form of the travel time probability distribution.Results for a hypothetical problem indicate that LNAPL velocity and travel time may be accurately estimated if sufficient data on travel distance vs. time are available. Incorporating prior information on relevant soil and fluid properties into the objective function reduces the uncertainty in release date if prior estimates are accurate. However, biased prior estimates may lead to over- or underestimation of release date uncertainty. Simultaneous estimation of soil and fluid properties and release date is possible if prior information is available to condition the parameter estimates.     

Ranking and selecting dangerous crash locations: correcting for the number of passengers and Bayesian ranking plots

INTRODUCTION: In this paper a sensitivity analysis is performed to investigate how big the impact would be on the current ranking of crash locations in Flanders (Belgium) when only taking into account the most serious injury per crash instead of all the injured occupants. RESULTS: Results show that this would lead to a different selection of 23.8% of the 800 sites that are currently considered as dangerous. CONCLUSIONS: Considering this impact quantity, the researchers want to sensitize government that giving weight to the severity of the crash can correct for the bias that occurs when the number of occupants of the vehicles are subject to coincidence. Additionally, probability plots are generated to provide policy makers with a scientific instrument with intuitive appeal to select dangerous road locations on a statistically sound basis. Impact on industry Considering the impact quantity of giving weight to the severity of the crash instead of to all the injured occupants of the vehicle on the ranking of crash sites, the authors want to sensitize government to carefully choose the criteria for ranking and selecting crash locations in order to achieve an enduring and successful traffic safety policy. Indeed, giving weight to the severity of the crash can correct for the bias that occurs when the number of occupants of the vehicles are subject to coincidence. However, it is up to the government to decide which priorities should be stressed in the traffic safety policy. Then, the appropriate weighting value combination can be chosen to rank and select the most dangerous crash locations. Additionally, the probability plots proposed in this paper can provide policy makers with a scientific instrument with intuitive appeal to select dangerous road locations on a statistically sound basis. Note that, in practice, one should not only rank the crash locations based on the benefits that can be achieved from tackling these locations. Future research is also needed to incorporate the costs of infrastructure measures and other actions that these crash sites require in order to enhance the safety on these locations. By balancing these costs and benefits against each other, the crash locations can then be ranked according to the order in which they should be prioritized.     

大气扩散模型计算结果析疑

扩散模型是大气污染物浓度预测最重要的工具。然而不同模型的预测结果差距很大,应该理性看待和应用其结果,本研究旨在通过实例说明这些问题。同时指出,同一类型的环评预测应该使用同一种模型,其结果才具有可比性。而最重要的还是要通过降低排放量来减少污染影响,不必过于计较模型观测结果。     

A framework for human error risk analysis of coal mine emergency evacuation in China

Evacuation from underground coal mine in emergency as soon as possible makes the difference between life and death. Human factors have an important impact on a successful evacuation, but literature review shows that there is a lack of consideration of human error risk during coal mine emergency evacuation in China. To address the above problems, in this paper, we established a framework for human error risk analysis of coal mine emergency evacuation, consisting of scenario and task analysis, risk assessment and risk reduction. A general evacuation procedure which is applicable for different causes is detailed through the scenario and task analysis. A new method based on expert judgment, named OGI-Model, is proposed to evaluate the reliability of human safety barrier. In this new approach, human safety barrier is divided into three sub-barriers, i.e., organization safety sub-barrier (OSSB), group safety sub-barrier (GSSB), and individual safety sub-barrier (ISSB). Each sub-barrier consists of a series of concrete measures against specific evacuation actions. An example is provided in this paper to demonstrate the use of this framework and its effectiveness.     

行为形成因子与人为差错模式的定性关联分析

为揭示人为差错的发生规律以便有效管理人为差错,研究行为形成因子与人为差错模式间的对应关系。将行为形成因子作为情景环境的表征,在SRK(skill,rule,knowledge)模型的基础上,将认知功能的效能分为3种指标:全面性、准确性和效率,将认知功能与效能指标相结合得到人为差错模式的分类。在此基础上,根据经验详细分析行为形成因子对认知功能3种效能指标的影响,得到行为形成因子与人为差错模式的关联关系表格。该关联关系是定性的,包含密切关联、重要关联、一般关联和没有关联4种关联程度,不但可以用于人为差错事件的调查,而且可以用于人为差错模式的预测。     

一种基于贝叶斯网络的机务维修差错调查模型算法

提出一种基于贝叶斯网络的机务维修差错调查模型算法,根据已经建立的机务人为诱因导致事故/事故征候模型,利用贝叶斯原理编程实现了该算法。利用该算法对中国民航飞行学院2001-2011年的机务人为有引导的事故/事故征候依次进行分析并验证,得到了相应的事故诱因概率排序。该算法克服了样本空间不足,在事故发生以后能够在引入其他证据的情况下根据以前的经验概率得到新的事故诱因概率排序,为民航机务维修差错调查提供了可靠的技术支持。