A robust decision-making methodology for evaluation and selection of simulation software package

Today, simulation has a broad range of applications from solving service problems to analyzing manufacturing problems such as warehousing and logistic systems. Simulation has become a popular methodology and selecting an appropriate simulation software package is one of the decisions that any industrial engineer may face at work. As a result, numerous types of simulation software packages have been developed for modeling simulation problems. The increasing variety of simulation software packages in the software market makes the selection of an appropriate simulation software package a critical decision. Selecting an inappropriate software package will be followed by many negative consequences. This paper will present a robust decision-making methodology based on Fuzzy Analytical Hierarchy Process (FAHP) for evaluating and selecting the appropriate simulation software package. The robust decision method aggregates the experts’ judgments for the criteria weights and the suitability of simulation software alternatives. The FAHP is used to prioritize and evaluate existing alternatives based on the proposed criteria for choosing the proper simulation software. The proposed methodology is applied to selecting the appropriate simulation software as an experiment and results are provided.     

Heterogeneous photocatalytic degradation of 4-chlorophenol by immobilization of cobalt tetrasulphophthalocyanine onto MCM-41

The photocatalytic activity of cobalt tetrasulphophthalocyanine immobilized onto MCM-41 was investigated for photocatalytic degradation of 4-chlorophenol (4-CP) in aqueous solutions. Immobilization of cobalt tetrasulphophthalocyanine complex to the walls of MCM-41 was performed by pre-anchorage of 3-(aminopropyl)-triethoxysilane (APTES) onto MCM-41 via post-synthesis method. X-ray diffraction, nitrogen physisorption, diffuse reflectance spectroscopy, energy-dispersive X-ray and FT-IR methods were used to characterize the product. Photocatalytic efficiency of the prepared photocatalyst for degradation of 4-CP was tested under illumination of UV-A and visible light. The reaction intermediates were identified by gas chromatography-mass spectrometry (GC-MS) technique.     

Location optimization of solar plants by an integrated hierarchical DEA PCA approach

Unique features of renewable energies such as solar energy has caused increasing demands for such resources. In order to use solar energy as a natural resource, environmental circumstances and geographical location related to solar intensity must be considered. Different factors may affect on the selection of a suitable location for solar plants. These factors must be considered concurrently for optimum location identification of solar plants. This article presents an integrated hierarchical approach for location of solar plants by data envelopment analysis (DEA), principal component analysis (PCA) and numerical taxonomy (NT). Furthermore, an integrated hierarchical DEA approach incorporating the most relevant parameters of solar plants is introduced. Moreover, 2 multivariable methods namely, PCA and NT are used to validate the results of DEA model. The prescribed approach is tested for 25 different cities in Iran with 6 different regions within each city. This is the first study that considers an integrated hierarchical DEA approach for geographical location optimization of solar plants. Implementation of the proposed approach would enable the energy policy makers to select the best-possible location for construction of a solar power plant with lowest possible costs.     

Empirical evaluation of river basin sustainability affected by inter‐basin water transfer using composite indicators

In this study, a practical approach to evaluate the sustainability of river basins subjected to an inter‐basin water transfer project is developed. Selection of appropriate evaluation indicators is pivotal to such approach. To make use of huge amount of data, composite indicators of sustainability (CIS) should be utilised. The proposed approach relies on 15 sustainability indicators (SI) that cover three major criteria namely (economic, social and environmental), and aggregates them into eight different types of sustainability indices for a more robust outcome. Two scenarios were considered within the source and recipient basins. Furthermore, multivariate principal component analysis (PCA) was applied to determine principal and non‐principal indicators for the two river basins. The ability of CIS and PCA methods were verified via correlation and simple regression methods respectively. The results demonstrated that inter‐basin water transfer may improve sustainability, provided that a proper water resource management is enforced.     

Successful Use of Geoelectrical Surveys in Area 3 of the Gol-e-Gohar Iron Ore Mine,Iran

Geoelectrical surveys were conducted in Area 3 of the Gol-e-Gohar iron ore mine to provide geological and hydrogeological information. Open pit mining is currently underway in the northern part of the Area, and underground mining operations are planned for the southern section. Groundwater has already been encountered in the open pit mine. Twenty five resistivity soundings were first performed in the mine area; then, induced polarization (IP) measurements were carried out to remove ambiguities between clay and water-bearing layers. To investigate fault zones as water conduits, combined resistivity profiling surveys were also carried out. These measurements provided a detailed structural map of the pit area. Resistivity and IP results have subsequently been confirmed by observations at three monitoring wells and the mine pit wall. Monitoring and piezometric wells will be drilled at locations suggested by the results of the geoelectrical surveys. Drainage galleries may be developed to dewater the open pit mine. However, another option being considered is to start the underground mining with the idea that it will initially simply serve as a dewatering mechanism.     

Optimization of Short Load Forecasting in Electricity Market of Iran Using Artificial Neural Networks

Accurate short-term load forecasting (STLF) is one of the essential requirements for power systems. In this paper, two different seasonal artificial neural networks (ANNs) are designed and compared in terms of model complexity, robustness, and forecasting accuracy. Furthermore, the performance of ANN partitioning is evaluated. The first model is a daily forecasting model which is used for forecasting hourly load of the next day. The second model is composed of 24 sub-networks which are used for forecasting hourly load of the next day. In fact, the second model is partitioning of the first model. Time, temperature, and historical loads are taken as inputs for ANN models. The neural network models are based on feed-forward back propagation which are trained and tested using data from electricity market of Iran during 2003 to 2005. Results show a good correlation between actual data and ANN outcomes. Moreover, it is shown that the first designed model consisting of single ANN is more appropriate than the second model consisting of 24 distinct ANNs. Finally ANN results are compared to conventional regression models. It is observed that in most cases ANN models are superior to regression models in terms of mean absolute percentage error (MAPE).     

The Electrochemical Behavior of Au/AuNPs/PNA/ZnSe-QD/ACA Electrode Towards CySH Oxidation

Nano-Micro Letters - This work describes the electrochemical behavior of azodicarboxamide (ACA) film immobilized on the surface of penicillamine (PNA)/ZnSe-quantum dot (ZnSe-QD) gold nanoparticle...     

An integrated DEA PCA numerical taxonomy approach for energy efficiency assessment and consumption optimization in energy intensive manufacturing sectors

This paper introduces an integrated approach based on data envelopment analysis (DEA), principal component analysis (PCA) and numerical taxonomy (NT) for total energy efficiency assessment and optimization in energy intensive manufacturing sectors. Total energy efficiency assessment and optimization of the proposed approach considers structural indicators in addition conventional consumption and manufacturing sector output indicators. The validity of the DEA model is verified and validated by PCA and NT through Spearman correlation experiment. Moreover, the proposed approach uses the measure-specific super-efficiency DEA model for sensitivity analysis to determine the critical energy carriers. Four energy intensive manufacturing sectors are discussed in this paper: iron and steel, pulp and paper, petroleum refining and cement manufacturing sectors. To show superiority and applicability, the proposed approach has been applied to refinery sub-sectors of some OECD (Organization for Economic Cooperation and Development) countries. This study has several unique features which are: (1) a total approach which considers structural indicators in addition to conventional energy efficiency indicators; (2) a verification and validation mechanism for DEA by PCA and NT and (3) utilization of DEA for total energy efficiency assessment and consumption optimization of energy intensive manufacturing sectors.     

Preparation of polymer-coated, scintillating ion-exchange resins for monitoring of 99Tc in groundwater

The present study was oriented to prepare new scintillating anion-exchange resins for measurement of (99)TcO(4)(-) in natural waters. The organic fluor 2-(1-naphthyl)-5-phenyloxazole was diffused into (chloromethyl)polystyrene resin. Thereafter, a thin layer of poly[[2-(methacryloyloxy)ethyl]trimethylammonium chloride] was grafted from the resin surface by surface-initiated atom transfer radical polymerization as an attempt to overcome potential problems related to the leaching of fluor molecules during usage. The residual chloromethyl groups of the polymer-coated resin were aminated by reaction with two different tertiary amines, triethylamine (TEA) and methyldioctylamine (MDOA). Off- and on-line quantification of (99)Tc was achieved with high detection efficiencies of 60.72 ± 1.93% and 72.83 ± 0.81% for resin with TEA and MDOA functional groups, respectively. The detection limit was determined to be less than the maximum contaminant level (33 Bq L(-1)) established under the Safe Drinking Water Act. The two functionalized resins were demonstrated to be selective for pertechnetate from synthetic groundwater containing up to 1000 ppm Cl(-), SO(4)(2-), and HCO(3)(-) and up to 1200 ppb Cr(2)O(7)(2-) in an acidic medium.