Experimental investigation,intelligent modeling and multi-characteristics optimization of dry WEDM process of Al–SiC metal matrix composite

Dry wire electrical discharge machining (WEDM) is an environmentally friendly modification of the oil WEDM process in which liquid dielectric is replaced by a gaseous medium. In the present work, parametric analysis has been fulfilled while dry WEDM of Al–SiC metal matrix composite. Experiments were designed and conducted based on L₂₇ Taguchi's orthogonal array to study the effect of pulse on time, pulse off time, gap voltage, discharge current, wire tension and wire feed on cutting velocity (CV) and surface roughness (SR). Firstly, a series of exploratory experiments has been conducted to identify appropriate gas and wire material based on the values of cutting velocity. After selection of best gas and best wire, they were used for later stage of experiments. Analysis of variances (ANOVA) has been performed to identify significant factors. In order to correlate relationship between process inputs and responses, an adaptive neuro-fuzzy inference system (ANFIS) has been employed to predict the process characteristics based on experimental observation. At the end, an artificial bee colony (ABC) algorithm has been associated with ANFIS models to maximize CV and minimize SR, simultaneously. Then the optimal solutions that obtained through ANFIS-ABC technique have been compared with numbers of confirmatory experiments. Results indicated that oxygen gas and brass wire guarantee superior cutting velocity. Also, according to ANOVA, pulse on time and discharge current were found to have significant effect on CV and SR. In modeling of CV and SR by ANFIS, it was resulted that the proposed method has superiority in prediction of them in the ranges of factors beyond the training condition. Also, association of ANFIS with ABC can find the optimal combination of process parameters accurately according to the confirmatory experiments.     

Estimation of Aerobic Capacity and Determination of Its Associated Factors Among Male Workers of Industrial Sector of Iran

Introduction. The aim of this study was to estimate maximal aerobic capacity (V_O2max), to determine its associated factors among workers of industrial sector of Iran and to develop a regression equation for subjects’ V_O2max. Methods. In this study, 500 healthy male workers employed in Shiraz industries participated voluntarily. The subjects’ V_O2max was assessed with the ergocycle test according to the Åstrand protocol. Required data was collected with a questionnaire covering demographic details (i.e., age, job tenure, marital status, education, nature of work, shift work, smoking and weekly exercises). Results. The subject’s mean V_O2max was 2.69 ± 0.263 L/min. The results showed that there was an association between V_O2max and age, BMI, hours of exercise and smoking, but there was no association between V_O2max and height, weight, nature of work and working schedule. On the basis of the results, regression equations were developed to estimate V_O2max. Conclusion. Final regression equation developed in this study may be used to estimate V_O2max reliably without the need to use other laboratory instruments for aerobic measurement.     

Chemometric application in identifying sources of organic contaminants in Langat river basin

Increasing urbanization and changes in land use in Langat river basin lead to adverse impacts on the environment compartment. One of the major challenges is in identifying sources of organic contaminants. This study presented the application of selected chemometric techniques: cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) to classify the pollution sources in Langat river basin based on the analysis of water and sediment samples collected from 24 stations, monitored for 14 organic contaminants from polycyclic aromatic hydrocarbons (PAHs), sterols, and pesticides groups. The CA and DA enabled to group 24 monitoring sites into three groups of pollution source (industry and urban socioeconomic, agricultural activity, and urban/domestic sewage) with five major discriminating variables: naphthalene, pyrene, benzo[a]pyrene, coprostanol, and cholesterol. PCA analysis, applied to water data sets, resulted in four latent factors explaining 79.0% of the total variance while sediment samples gave five latent factors with 77.6% explained variance. The varifactors (VFs) obtained from PCA indicated that sterols (coprostanol, cholesterol, stigmasterol, β-sitosterol, and stigmastanol) are strongly correlated to domestic and urban sewage, PAHs (naphthalene, acenaphthene, pyrene, benzo[a]anthracene, and benzo[a]pyrene) from industrial and urban activities and chlorpyrifos correlated to samples nearby agricultural sites. The results demonstrated that chemometric techniques can be used for rapid assessment of water and sediment contaminations.     

Application of network method as a tool for integrating biodiversity values in Environmental Impact Assessment

Highway construction or expansion projects are among major activities of economic development especially in developing countries. However, road development consistently can lead to major damages to the environment, including habitat fragmentation and ecological instabilities and a considerable threat to fauna and flora. At this point, Environmental Impact Assessment (EIA) in road developments is needed to address and evaluate the ecological issues in decision-making. The object of this study is to strengthen the consideration of ecological issues, i.e., biodiversity in the existing EIA tools. This paper regards a network method as a means to make informed planning decisions by the lessons from a case study. The results indicate that network method is well suited to be applied in ecological impacts assessment. However, some limitations such as complexity and time consumed make casual networks unpopular. Also, impact of traffic noise on acoustic communication (wildlife and human) was performed. It has been shown that sound level for human is much higher than admissible standards. Finally, the study expresses some mitigation measures to improve the acquisition for environmental impact assessment process.     

Decision-making for sustainable location of a cement plant in the state of Florida

Site selection is a typical strategic decision for many industries that deals with specifying the most appropriate location for a facility. In the context of sustainable development, site selection decisions need to be improved by adopting environmental, economic and social requirements. This study aims to frame sustainable location decisions by conducting a case study of siting a new cement plant in the state of Florida. As a part of the study, a wide range of technical and sustainability criteria has developed. These criteria can help decision-makers in the cement industry evaluate the selection of a location with the requirements of sustainable development. The sustainability characteristics of alternative sites in the state of Florida are evaluated based on the criteria to identify the most appropriate ones. The analytical hierarchy processand geographic information system techniques are utilized to weight the criteria and evaluate the characteristics of site candidates.     

Quantitative analysis and sorption of cadmium in environmental samples with a functionalized synthetic polymer

Quantitative analysis of cadmium in environmental samples was achieved with a polymeric sorbent synthesized by copolymerization of N,N-dimethylacrylamide and allyl glycidyl ether/iminodiacetic acid as chelating monomers with N,N′-methylenebisacrylamide as cross-linker. The polymer was characterized by Fourier transform infrared spectroscopy, thermogravimetric analysis, elemental analysis, and scanning electron microscopy. The sorption capacity of the functionalized sorbent was 70 mg g^?1. The equilibrium sorption data of Cd(II) on polymeric sorbent were analyzed using Langmuir, Freundlich, Temkin, and Redlich–Peterson models. Based on equilibrium adsorption data, the constants at pH 4.2 and 20 °C were determined for the first three as 0.33 (L mg^?1), 17.5 (mg g^?1) (L mg^?1)^1/n, and 12.9 (J mol^?1). Recovery of 94% of the metal ion was obtained with 0.5 mol L^?1 nitric acid as an eluting agent.