Reliability evaluation of fire alarm systems using dynamic Bayesian networks and fuzzy fault tree analysis

In almost all industries, fire alarm systems play a vital role in the reducing the risks associated with fires and damages. Therefore, it is necessary to evaluate their reliability and performance in emergency situations. The present study aimed to use fault tree analysis (FTA) to determine the root causes involved in the failure of fire alarm systems, to use Fuzzy set theory and expert elicitation to determine relative probabilities, and finally, to evaluate the reliability of a fire alarm system using dynamic Bayesian networks (BNs) during a thirty-six months period. A total of 29 basic events were detected from the FT. The reliability of the fire alarm system was estimated at 0.954 according to the FT and 0.957 according to conventional BNs. The reliability of the fire alarm system after 36 months was estimated at 0.375 according to dynamic BNs. All the events involved in the failure of fire alarm systems were drawn in the fault tree diagram. The results indicate that remodeling of these systems and simultaneous construction activities are the most important factors in the failure of the fire alarm system. System reliability can also be increased to 0.965 by providing preventive and control measures to reduce the probability of critical events.     

康集生态农场土壤肥力改善的研究

本文采用对比研究的方法，分别对康集生态农场种植园、附近农用地和对照废窑地的主要土壤肥力指标进行了测定分析。结果表明，康集生态农场土壤肥力已从开发前的五级提高到与当地一般农用地相一致的三级水平。其中有机质、全氮、水解氮、速效磷含量明显提高，盐渍化程度有所下降，但仍有改善的潜力。     

Allocation of performance shaping factors in the risk assessment of an offshore installation

Offshore oil production is one of the most important human productive activities. There are many risks associated with the process of constructing a subsea well, pumping oil to the platform, and transporting it to refineries via underwater pipes or oil tankers. All actions performed by workers in those operations are influenced by specific working conditions, involving the use of complex systems. Contextual factors such as high noise, low and high temperatures and hazardous chemicals are considered to be contributors to unsafe human actions in accident analysis and also give a basis for assessing human factors in safety analysis. Some failure modes are particularly dangerous and can result in severe accidents and damage to humans, the environment and material assets. Fires and explosions on oil rigs are some of the most devastating types of offshore accidents and can result in long-term consequences. The most typical root causes related to accidents include equipment failure, human error, environmental factors, work organization, training and, communication, among others. The principal objective of this study is to propose a methodological framework to identify the factors that affect the performance of operators of an offshore unit for oil processing and treatment. In this phase, an ergonomics approach based on operators' work analysis is used as a supporting tool. After identification of factors that affect the performance of operators, a decision-making model based on AHP (analytic hierarchy process) is applied to rank and weight the principal performance shaping factors (PSFs) that influence safe operations. The next step involves the use of the SHELLO model to group the main PSFs in elements named software, hardware, environment, liveware and organization. In the last phase, a relevant accident that occurred aboard a floating production storage and offloading (FPSO) vessel is analyzed. The allocation process of the factors that affect the operator's performance in risk assessment was developed through fuzzy logic and the ISO 17776 standard.     

Critical Review of Environmental Forensic Techniques: Part II

A multitude of forensic techniques are available for age dating and source identification, including aerial photography interpretation, corrosion models, the commercial availability of a chemical, chemical associations with discrete types of equipment, chemical profiling, degradation models and contaminant transport models. The success of these techniques in environmental litigation and their applicability to a particular fact situation is rarely discussed in the literature. When these techniques are introduced as scientific evidence, their governing assumptions and the adequacy of the underlying data are rigorously scrutinized and often, successfully challenged. The purpose of this paper is to review selected forensic techniques and discuss their merits so that the user can select the technique or combination of techniques most appropriate for the factual elements of the case.     

劳动河水质的模糊综合评价及分析

利用劳动河8个点位的水质监测数据,以地面水环境质量为标准,运用模糊数学方法,分析劳动河各点位污染状况,综合评价劳动河水质污染程度,确定主要污染点位及主要污染因子,为劳动河污染控制提供科学依据。     

改进层次分析法在土壤重金属污染评价中的应用

将层次分析法进行了必要的改进 ,并应用于土壤重金属污染的评价 .评价结果表明 :改进层次分析法比模糊综合评判法以及一般层次分析法更为合理 .     

潜在有毒化学品优先控制名单筛选方法研究

在收集了国内外共37个不同化学品名单基础上,研究了我国潜在有毒化学品的筛选程序和评分系统。根据环境的9项指标和毒性的7项指标共16个参数,运用模糊数学方法计算了化学品的综合危害分值,藉此按其危害程度予以排序,从而选定了52种优先控制的有毒化学品名单,旨在对化学品应采取的适宜管理对策提供有效的科学依据。      

Estimation of pasture infectivity according to weather conditions through a fuzzy parametrized model for the free-living stage of Ostertagia ostertagi

Gastrointestinal parasitism is one of the diseases that has the highest economic impact on the Argentinian beef production system, rendering it inefficient. In the region of the Humid Pampas, it has been estimated that 22 million dollars are lost annually because of the death of calves and 170 million dollars are lost in sub-clinic costs. A mathematical model with fuzzy parameters was constructed for the analysis of the free-living stages of gastrointestinal parasites, with the purpose of estimating the pool of L3 larvae available for migration to pasture and the levels of infection in pasture at any time of the year under different climatic conditions. The model is formulated in terms of a system of three difference equations. These equations describe the abundance of parasites in each of the successive stages of the population development. The model was calibrated and tested with data gathered through fieldwork carried out in Tandil (37°19′S, 59°08′05″W), province of Buenos Aires (Argentina) and the corresponding weather data. A comparison between model simulations and fieldwork data obtained in other locations achieved satisfactory results.     

A hybrid approach using ISM and fuzzy TOPSIS for the selection of reverse logistics provider

Return of used products is becoming an important logistics activity due to government legislation and increasing awareness among the people to protect the environment and reduce waste. For industries, the management of return flow usually requires a specialized infrastructure with special information systems for tracking and dedicated equipment for the processing of returns. Therefore, industries are turning to third-party reverse logistics providers (3PRLPs). In this study, a multi-criteria group decision-making (MCGDM) model in fuzzy environment is developed to guide the selection process of best 3PRLP. The interactions among the criteria are also analyzed before arriving at a decision for the selection of 3PRLP from among 15 alternatives. The analysis is done through Interpretive Structural Modeling (ISM) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS). Finally the effectiveness of the model is illustrated using a case study on battery manufacturing industry in India.