安全人性学的方法论研究

为正确利用和改善安全人性及有效开展安全教育,有必要开展宏观层面的安全人性方法论研究。首先,给出安全人性学方法论的定义及研究内容。基于人性学方法论和安全科学方法论等,构建包括时间维、数量维、专业文化维、环境维、技术维和理论维的安全人性学方法论的多维结构体系。其次,从学科特性出发,描述了安全人性学的研究方法,确立了安全人性学研究的一般步骤;并在此基础上,建立安全人性学研究的范式体系。研究表明,安全人性学方法论是在安全人性学原理以及相关理论的指导下所形成的系统化和程式化思想,对安全人性学的研究有理论指导作用。     

A methodological framework and tool for assessing the climate change related risks in the banking sector

Although climate change risks have been studied for a number of economic sectors, banking has received relatively little attention. The paper proposes a methodology and an associated decision-support tool for quantifying, in monetary terms, the risks for banks from the exposure of their loan recipients and/or applicants to climate change. The framework and tool are applied to a case study based on input from a Greek bank; results indicate that climate change risks for banks are considerable, and thus decision makers need to estimate their magnitude and possibly consider these within the credit management process, and in environmental planning.     

Success and failure assessment methodology for wastewater and faecal sludge treatment projects in low-income countries

Many factors influence success and failure of large-scale faecal sludge and wastewater treatment projects in low-income countries. Benchmarking indicators and multicriteria analysis were adapted to define key institutional, technical and financial factors, to analyse their interrelations, and understand priorities to consider when planning and managing treatment plants. For the first time, these methods have been combined in a quantitative manner to assess planned and on-going treatment plant projects. This new methodology will aid sanitation utilities, private consultants, and funding institutions to prioritise activities and organise the operation of treatment plants.     

Optimization and evaluation of an air-recirculated stripping for ammonia removal from the anaerobic digestate of pig manure

An air-recirculated stripping involved two processes and did not require any pretreatment. First, stripping CO₂ decreased the buffer capacity of the anaerobic digestate, thereby reducing the amount of lime used to achieve a high pH. Second, lime was added to increase pH and remove ammonia from the anaerobic digestate of pig manure. pH increased from 8.03 to 8.86 by stripping CO₂ in the first process (gas-to-liquid ratio = 180) and further reached 12.38 in the second process (gas-to-liquid ratio = 300). During process optimization, the maximum ammonia removal efficiency reached 96.78% with a lime dose of 22.13 g. The value was close to 98.25%, which was the optimal result predicted by response surface methodology using the software Design-Expert 8.05b. All these results indicated that air-recirculated stripping coupled with absorption was a promising technology for the removal and recovery of nitrogen in the anaerobic digestate of pig manure.     

Investigation of affecting parameters on treating high-strength compost leachate in a hybrid EGSB and fixed-bed reactor followed by electrocoagulation–flotation process

In this research, treatability of high-load compost leachate in a hybrid expanded granular sludge bed (EGSB) and fixed-bed (FB) bioreactor followed by electrocoagulation–flotation (ECF) system was examined. The operational factors in EGSB–FB were influent chemical oxygen demand (COD), hydraulic retention time (HRT) and COD/nitrogen ratio (COD/N). And, their interactive effects on the efficiency of COD removal and biogas production rate (BPR) as responses were analyzed and correlated by response surface methodology (RSM). The optimum conditions of the hybrid EGSB–FB reactor were acquired at COD = 7800 mg/L, HRT = 35 h, COD/N = 70, in which COD removal efficiency was 83% and BPR 94 mL/h. The amount of confidence interval was 95%. COD (relevant coefficient = 9.8) and HRT (relevant coefficient = −24) were resulted respectively as the most effective parameters on COD removal and BPR. Yet, COD/N parameter imposed negative effect on COD removal and BPR in values less than about 100. The outcomes indicated that operated ECF as post-treatment in constant conditions (electrolysis time = 75 min, electrodes distance = 3 cm, voltage = 20 V) successfully satisfied discharge criteria in the most part of experimental domains.     

Optimization of biodiesel production from the waste cooking oil using response surface methodology

In this research, transesterification of the waste cooking oil has been studied. Response surface methodology (RSM) based on Box–Behnken design was used to investigate the effects of the main operating parameters, including the methanol to oil molar ratio, catalyst concentration, and reaction temperature, on the biodiesel yield. The results revealed that the catalyst concentration is the most important parameter. The maximum biodiesel yield under the optimized conditions was 99.38 wt.%. Thermogravimetric analysis (TGA) was used for the determination of biodiesel conversion and the results were compared with that of gas chromatography (GC) analysis, showing a very small difference. Furthermore, an empirical quadratic equation has been presented to show the relation between biodiesel conversion and product viscosity.     

Modeling and optimization of turning duplex stainless steels

The attractive combination of high mechanical strength, good corrosion resistance and relatively low cost has contributed to making duplex stainless steels (DSSs) one of the fastest growing groups of stainless steels. As the importance of DSSs is increasing, practical information about their successful machining is expected to be crucial. To address this industrial need, standard EN 1.4462 and super EN 1.4410 DSSs are machined under constant cutting speed multi-pass facing operations. A systematic approach which employs different modeling and optimization tools under a three phase investigation scheme has been adopted. In phase I, the effect of design variables such as cutting parameters, cutting fluids and axial length of cuts are investigated using the D-Optimal method. The mathematical models for performance characteristics such as; percentage increase in radial cutting force (%F_r), effective cutting power (P_e), maximum tool flank wear (VB_max) and chip volume ratio (R) are developed using response surface methodology (RSM). The adequacy of derived models for each cutting scenario is checked using analysis of variance (ANOVA). Parametric meta-heuristic optimization using Cuckoo search (CS) algorithm is then performed to determine the optimum design variable set for each performance. In the phase II, comprehensive experiment-based production cost and production rate models are developed. To overcome the conflict between the desire of minimizing the production cost and maximizing the production rate, compromise solutions are suggested using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The alternatives are ranked according to their relative closeness to the ideal solution. In the phase III, expert systems based on fuzzy rule modeling approach are adopted to derive measures of machining operational sustainability called operational sustainability index (OSI). Artificial neural network (ANN) based models are developed to study the effect of design variables on computed OSIs. Cuckoo search neural network systems (CSNNS) are finally utilized to constrainedly optimize the cutting process per each cutting scenario. The most appropriate cutting setup to ensure successful turning of standard EN 1.4462 and super EN 1.4410 for each scenario is selected in accordance with conditions which give the maximum OSI.     

The theoretical value of encounters with parasitized hosts for parasitoids

A female parasitoid searching for hosts in a patch experiences a diminishing encounter rate with unparasitized and thus suitable hosts. To use the available time most efficiently, it constantly has to decide whether to stay in the patch and continue to search for hosts or to search for and travel to another patch in the habitat. Several informational cues can be used to optimize the searching success. Theoretically, encounters with unparasitized hosts should lead to a prolonged search in a given patch if hosts are distributed contagiously. The results of empirical studies strongly support this hypothesis. However, it has, to date, not been investigated theoretically whether encounters with already parasitized hosts (which usually entail time costs) provide a parasitoid with valuable information for the optimization of its search in depletable patches, although the empirical studies concerning this question so far have produced ambiguous results. Building on recent advances in Bayesian foraging strategies, we approached this problem by modeling a priori searching strategies (which differ in the amount of information considered) and then testing them in computer simulations. By comparing the strategies, we were able to determine whether and how encounters with already parasitized hosts can yield information that can be used to enhance a parasitoid’s searching success.

A STOCHASTIC DYNAMIC PROGRAMMING MODEL FOR THE OPTIMUM OPERATION OF A MULTI-PURPOSE RESERVOIR1

ABSTRACT: The main objective of this paper is to present a stockastic dynamic programming model useful in determining the optimal operating policy of a single multipurpose surface reservoir. It is the unreliability of forecasting the amount of future streamflow which makes the problem of a reservoir operation a stochastic process. In this paper the stochastic nature of the streamflow is taken into account by considering the correlation between the streamflows of each pair of consecutive time intervals. This interdependence is used to calculate the probability of transition from a given state and stage to its succeeding ones. A dynamic programming model with a physical equation and a stochastic recursive equation is developed to find the optimum operational policy. For illustrative purposes, the model is applied to a real surface water reservoir system.