涂层大气腐蚀的模糊综合评定

此文将模糊理论应用于涂层的大气腐蚀试验,针对对比性腐蚀试验结果,提出了涂层保护性能大气腐蚀模糊综合评定方法。本法具有简捷、迅速、准确等优点。     

模糊综合评价法在疏散时间影响因素研究中的应用

人员疏散是一个复杂的运动过程,人员疏散时间受众多因素影响,具有一定的模糊性和随机性。该文将人员安全疏散作为一个系统进行分析,从疏散场所、疏散人员以及疏散环境三个角度分析影响人员疏散时间的因素,构建出人员疏散时间的评价指标体系。结合模糊综合评价法的基本原理和步骤,建立人员疏散时间影响因素的三级模糊综合评价模型,并应用该模型对某高层建筑火灾中影响人员疏散时间的因素进行模糊综合评价。     

基于模糊数学方法的门式起重机风险评估研究

本文采用模糊数学方法对门式起重机潜在风险因素（腐蚀、裂纹、强度及变形）导致的金属结构破坏进行风险评估。从主梁和支腿两个角度出发,建立了不同金属结构风险影响因素为子系统的多层次评判系统。该方法方便了门式起重机的综合安全风险评估,为提高其安全性能提供了方向。     

Continuous performance assessment and improvement of integrated HSE and maintenance systems by multivariate analysis in gas transmission units

In this study, an integrated “Health, Safety, and Environment (HSE)” and maintenance systems are presented. Multivariate analysis is used for continuous performance assessment and improvement of these systems. The two subjects of “Maintenance System” and “HSE” have been individually investigated several times in different studies. However, few studies have been done to integrate these two systems and provide an integrated system for their implementation. This study evaluates current maintenance and HSE systems of a Gas Transmission Unit by Data Envelopment Analysis (DEA) and Principal Component Analysis (PCA). Moreover, decision making units (DMUs) are examined and ranked. Employees are considered as DMUs. This is done through investigating and measuring their efficiencies and identifying the inefficient and less-efficient units. Since an increase in the number of inputs does not lead to an increase in the number of outputs with the same scale, an output-oriented DEA with a Variable Returns to Scale (VRS) is used. The Fuzzy DEA (FDEA) is also used in this research to decrease uncertainty existing in qualitative indicators and human error. Finally, suggestions are given to improve those DMUs. The managers and employees of the gas transmission unit constitute the statistical population of the study. To achieve the objectives of this study, standard questionnaires with respect to HSE and Maintenance system are completed by operators. The proposed approach would help policy makers and top managers of Gas Transmission Company to have a more comprehensive and thorough understanding the working conditions with respect to the maintenance and HSE features.     

Optimization of HSE in maintenance activities by integration of continuous improvement cycle and fuzzy multivariate approach: A gas refinery

Gas refineries have been continuously focusing on Health, Safety and Environment programs to improve maintenance activities. Several researches have studied on this area with different analysis methods. This study presents an integrated approach for optimization of factors contributing to the implementation of Health, Safety and Environment (HSE) in maintenance activities. HSE managers in each sector answered standard questionnaire whit respect to HES. The methodology is based on fuzzy data envelopment analysis (FDEA) and Deming's continuous improvement cycle. Also, this method is used to rank the relevant performance efficiencies in certain and uncertain conditions of each HSE sectors whit considering HSE in maintenance activities. It corresponds and integrates its registered HSE-MS with OHSAS 18001:2007 and ISO 14001:2004 to evaluate multiple inputs and outputs of over 36 subsidiary HSE divisions with parallel mission and objectives simultaneously. Also, it determines efficient target indices and could assure continuous improvement in the organization. This is the first study that introduces an integrated approach to improve HSE management programs in a gas refinery by a robust and continuous improvement approach.     

Fuzzy optimization of multi-period carbon capture and storage systems with parametric uncertainties

Carbon capture and storage (CCS) is an important technology option for reducing industrial greenhouse gas emissions. In practice, CO₂ sources are easy to characterize, while the estimation of relevant properties of storage sites, such as capacity and injection rate limit (i.e., injectivity), is subject to considerable uncertainty. Such uncertainties need to be accounted for in planning CCS deployment on a large scale for effective use of available storage sites. In particular, the uncertainty introduces technical risks that may result from overestimating the limits of given storage sites. In this work, a fuzzy mixed integer linear program (FMILP) is developed for multi-period CCS systems, accounting for the technical risk arising from uncertainties in estimates of sink parameters, while still attaining satisfactory CO₂ emissions reduction. In the model, sources are assumed to have precisely known CO₂ flow rates and operating lives, while geological sinks are characterized with imprecise fuzzy capacity and injectivity data. Three case studies are then presented to illustrate the model. Results of these examples illustrate the tradeoff inherent in planning CCS systems under parametric uncertainty.     

FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management

Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk.     

Modelling spatial distribution of hard bottom benthic communities and their functional response to environmental parameters

In this study we analyzed and modelled spatial distribution of hard bottom benthic communities in the Lagoon of Venice, and used the model to derive functional response of these communities to changing environmental conditions.     

Spatio-temporal dissolved oxygen dynamics in the Orbetello lagoon by fuzzy pattern recognition

This paper models the dissolved oxygen (DO) dynamics in the Orbetello lagoon as a function of the physico-chemical and ecological system variables, including the submerged vegetation, nutrients, and hydrodynamics. It should be viewed as the concluding sequel to a previous paper describing the dynamics of the lagoon ecosystem [Giusti, E., Marsili-Libelli, S., 2006. An integrated model for the Orbetello lagoon ecosystem, Ecol. Model. 196, 379–394] by introducing the missing DO dynamics. The model considers the oxygen demand originating from the decay of carbonaceous and nitrogenous compounds, as well as photosynthesis and natural reaeration by winds and currents as the oxygen producing processes. With a fixed-parameter set the model could accurately reproduce each single circadian DO cycle, but in the long run it failed to extend this fit and could not accommodate the large DO fluctuations induced by the seasonal variability. In order to enhance the model flexibility, a fuzzy pattern recognition algorithm was designed to classify the circadian DO patterns into four typical behaviours, related to the season, and estimate the corresponding parameters, with the overall model output being a fuzzy combination of these sets. The paper discusses several methods to patch the parameter sets and compares their performance in tracking long-term DO variations. A final assessment of the model validity is obtained by incorporating the whole DO dynamics (model, fuzzy pattern recognition and parameter combination) into the general lagoon model and producing a consistently correct series of DO daily distributions over a yearly cycle. Thus the paper contains both a practical and a methodological aspect. The practical one is the linking of all the lagoon dynamics to the dissolved oxygen kinetics in order to clarify to what extent macroalgae and macrophytes influence the oxygen balance. The methodological aspect consists of extending the validity of short-term models to long time-horizons through a patching technique supported by fuzzy pattern recognition.     

Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average

This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process.