MULTIPLE CRITERIA ANALYSIS FOR WATER QUALITY MANAGEMENT IN THE NITRA BASIN1

ABSTRACT: This paper presents the implementation of one element of a decision support system (DSS) for regional water quality management, applied to the Nitra River Basin in Slovakia. A model-based, aspiration-led methodology for multicriteria decision support has been used for the study. Several reusable, modular software tools have been developed and implemented: a problem-specific generator to produce the core part of the mathematical programming model, tools for the generation and interactive modification of multicriteria problems, and a solver for the resulting mixed-integer optimization problem. Provided in the paper are the following: a complete formulation of the mathematical model (including the imbedded water quality model), a summary of the aspiration-reservation-led multiple criteria optimization approach applied to decision support, and an overview of results that illustrate the applied approach and provide some interesting insights to the case study.     

A multi-objective optimization framework for surfactant-enhanced remediation of DNAPL contaminations

The occurrence of Dense Non-Aqueous Phase Liquid (DNAPL) contaminations in the subsurface is a threat for drinkwater resources in the western world. Surfactant-Enhanced Aquifer Remediation (SEAR) is widely considered as one of the most promising techniques to remediate DNAPL contaminations in-situ, be it with considerable additional costs compared to classical pump-and-treat remediations. A cost-effective design of the remediation set-up is therefore essential. In this work, a pilot SEAR test is executed at a DNAPL contaminated site in Belgium in order to collect data for the calibration of a multi-phase multi-component model. The calibrated model is used to assess a series of scenario-analyses for the full-scale remediation of the site. The remediation variables that were varied were the injection and extraction rate, the injection and extraction duration, and the surfactant injection concentrations. A constrained multi-objective optimization of the model was applied to obtain a Pareto set of optimal remediation strategies with different weights for the two objectives of the remediation: (i) the maximal removal of DNAPL and (ii) a total minimal cost. These Pareto curves can help decision makers to select an optimal remediation strategy in terms of cost and remediation efficiency. The Pareto front shows a considerable trade-off between the total remediation cost and the removed DNAPL mass.     

A robust approach for iterative contaminant source location and release history recovery

Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.     

Joint analysis of process and operator performance in chemical process operational safety

Independent studies of case histories by the Health and Safety Commission in the UK and by a Honeywell led industrial consortium world-wide showed that human errors represent the major cause of failure in process plant operation. In contrast to this discovery the majority of previous studies on computer aided systems for fault detection and diagnosis has focused on the process side. This paper presents a methodology, which can involve human factors into the development of systems for automatic identification and diagnosis of abnormal operations and develops methods and techniques that can be used to simultaneously capture, characterise and assess the performance of operators as well as of the process. A joint process–operator simulation platform is developed which is used as a test-bed for carrying out the study. The process part is a simulator, which simulates in high fidelity the dynamic behaviour of the process that is subject to the influence of various disturbances and operators’ interventions. The operator module is developed as a real-time expert system, which emulates operator’s behaviour in interpretation of received signals, and planning and execution of decisions. The interaction between the two modules is managed through an interaction module, which handles the real-time exchange of data using Dynamic Data Exchange. The interaction module also contains the toolkits for analysing the dynamic behaviour of the joint process–operator system. The method and system are illustrated using a simulated case study.     

基于SOM和多元分析的滇池沉积物污染特征空间模式研究

联合运用层次聚类分析(HCA)、判别分析(DA)和自组织映射神经网络(SOM)3种数值方法,对滇池2008—2010年17个底泥监测点位(10个常规点位及7个新增点位)9种污染物进行空间差异性和相似性分析,并评价各指标在空间的分布特征及监测点代表性.结果表明:滇池沉积物整体污染程度为草海>外海中部及南部>外海北部.As、Hg、Pb、Cd、Cu和Zn污染最严重的点位是断桥;草海中心的凯氏氮污染最严重,其他指标污染水平仅次于断桥;Cr和TP污染最严重的点位是新增点位盘龙江2;海埂是全局污染最轻的点位.现有的常规监测点位对整体污染特征的代表性较弱,建议取消异质性最低的白鱼口、观音山西、观音山东和罗家营站点;考虑污染特征和监测点位空间分布的均匀性,建议将盘龙江2、海埂和马料河设为常规监测点位.     

基于情景构建的应急预案体系优化策略及方法

为了进一步优化我国现有应急预案体系,从应急管理实践中分析梳理出4方面问题,包括:“在指导理念上依然没有充分体现应急准备的理念”“应急预案体系在微观、中观和宏观层面依然存在结构性问题”“应急预案的内容存在‘概念性’内容较多的情况,导致操作性和针对性不强”“预案动态管理滞后,持续改进机制尚未形成”;针对现存问题,提出基于情景构建的优化策略和方法,认为“情景构建”不但可以指导编制者分析应急需求、明确应急目标、规划应急程序,有效支撑应急预案的编制,而且可以派生出“基于情景链条的预案衔接策略”“基于任务协同的预案衔接策略”“基于资源约束的预案衔接策略”,进而从微观层面上推进预案体系的优化。研究结果可以作为各级政府和企业应急预案体系构建的参考和借鉴。     

A hybrid decision-making approach based on FCM and MOORA for occupational health and safety risk analysis

IntroductionWith the development of industries and increased diversity of their associated hazards, the importance of identifying these hazards and controlling the Occupational Health and Safety (OHS) risks has also dramatically augmented. Currently, there is a serious need for a risk management system to identify and prioritize risks with the aim of providing corrective/preventive measures to minimize the negative consequences of OHS risks. In fact, this system can help the protection of employees’ health and reduction of organizational costs. Method: The present study proposes a hybrid decision-making approach based on the Failure Mode and Effect Analysis (FMEA), Fuzzy Cognitive Map (FCM), and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) for assessing and prioritizing OHS risks. After identifying the risks and determining the values of the risk assessment criteria via the FMEA technique, the attempt is made to determine the weights of criteria based on their causal relationships through FCM and the hybrid learning algorithm. Then, the risk prioritization is carried out using the MOORA method based on the decision matrix (the output of the FMEA) and the weights of the criteria (the output of the FCM). Results: The results from the implementation of the proposed approach in a manufacturing company reveal that the score at issue can overcome some of the drawbacks of the traditional Risk Priority Number (RPN) in the conventional FMEA, including lack of assignment the different relative importance to the assessment criteria, inability to take into account other important management criteria, lack of consideration of causal relationships among criteria, and high dependence of the prioritization on the experts’ opinions, which finally provides a full and distinct risk prioritization.     

A hybrid model for human factor analysis in process accidents: FBN-HFACS

Human factors are the largest contributing factors to unsafe operation of the chemical process systems. Conventional methods of human factor assessment are often static, unable to deal with data and model uncertainty, and to consider independencies among failure modes. To overcome the above limitations, this paper presents a hybrid dynamic human factor model considering Human Factor Analysis and Classification System (HFACS), intuitionistic fuzzy set theory, and Bayesian network. The model is tested on accident scenarios which have occurred in a hot tapping operation of a natural gas pipeline. The results demonstrate that poor occupational safety training, failure to implement risk management principles, and ignoring reporting unsafe conditions were the factors that contributed most failures causing accident. The potential risk-based safety measures for preventing similar accidents are discussed. The application of the model confirms its robustness in estimating impact rate (degree) of human factor induced failures, consideration of the conditional dependency, and a dynamic and flexible modelling structure.     

海上溢油应急物资调度双目标规划模型

为最大程度降低溢油事故造成的不利影响,提出充分考虑海上油膜漂移特性及溢油点和漂移点对救援物资需求不确定等特点,基于鲁棒优化思想,建立救援应急成本最小、应急时间最短的双目标规划模型,并基于NSGA-Ⅱ算法设计求解方法。结果表明:决策者可根据自身对溢油事故规模的判断,得到不同应急物资调度方案,为应急出救点的选择和物资调度提供合理决策依据。     

瓦斯抽采PC-CAS基封孔材料优化及其膨胀作用分析*

为了研制以硅酸盐/铝酸盐水泥、生石灰、生石膏为主的PC-CAS基封孔材料,采用正交试验优化材料配比、开展膨胀力研究,并用扫描电镜观测料-煤胶结形貌。研究结果表明:材料的最优配比为A2B2C4,其具备优良的流动性、强度及致密性,造浆量达2 100 mL/kg;PC-CAS基材料具有显著的膨胀性,其膨胀力随时间先增大而后趋于稳定,并且该膨胀力随着径向约束的提高而增大;相比于FP材料,PC-CAS基材料产生的膨胀力能够显著降低材料-煤岩界面的空隙并在一定程度上压密煤体内部的裂隙;该材料产生的膨胀力可压密封孔段围岩、提高封孔质量,并为后期“二次注浆”提供保压条件。工业试验结果表明,采用PC-CAS基材料进行封孔可显著改善抽采效果,将原有平均浓度10.11%提升至20.08%。