Abstract-Industrial and urban development has resulted in the spread of plastic waste and the increase in the emissions of carbon dioxide resulting from the cement manufacturing process. The current research aims to produce green (environmentally friendly) concrete by using plastic waste as coarse aggregates in different proportions (10% and 20%) and nano silica sand powder as an alternative to cement in different proportions (5% and 10% by weight). The results showed that compressive strength decreased by 12.10% and 19.23% for 10% and 20% plastic waste replacement and increased by 12.89% and 20.39% for 5% and 10% silica sand replacement respectively at 28 days. Flexural strength decreased by 12.95% and 19.64% for 10% and 20% plastic waste replacement and increased by 11.16% and 19.86% for 5% and 10% silica sand replacement. Splitting tensile strength decreased by 12.74% and 20.22% for 10% and 20% plastic waste replacement and increased by 10.86% and 19.66% for 5% and 10% silica sand replacement. Dry density decreased by 4.51% and 7.83% for 10% and 20% plastic waste replacement and increased by 2.78% and 4.10% for 5% and 10% silica sand replacement respectively at 28 days.
Composting is one of the solid waste management (SWM) methods where the organic component decomposed biologically under controlled conditions. In this study, a 0.166 m3 bioreactor tank was designed to compose 59.2Kg of simulated common municipal solid food waste having a bulk density, organic matter, organic carbon, pH, nitrogen content, C/N and nitrification index (NH4-N/ NO3-N) of 536.62 kg/m3, 62.34%, 34.76%, 6.53, 1.86%, 23 and 0.34 respectively. The bioreactor operated aerobically for 30 days, and anaerobically for 70 days, until the end of the composting process. Results proved that the composting process could reduce the mass of the waste by 69%. Nitrogen content,
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In most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con
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Hot-wire cutting is one of the important, non-traditional thermomechanical way to cut polymer, usually expanded foam and extruded foam, in low volume manufacturing. The study and analysis of Hot-Wire cutting parameters play an important role to enhance the quality and accuracy of the process and products. The effects on the surface have been investigated by using experimental tests designed according to the Taguchi orthogonal array (OA). In this study, four parameters with five levels for each parameter have been used: [temperature of wire (A) (100, 120, 130, 150, 160) °C], [diameter of wire (B) (0.3,0.4,0.5,0.7,0.8) mm], [velocity of cutting (C) (200, 300,400,500,600) mm/min], [and density of foam (D) (0.01,0.0
... Show MoreThis study aims to explain the role of green target costing technique in improving the relationship with suppliers in a sample of industrial companies listed on the Iraq Stock Exchange. The descriptive analytical approach was used, where a questionnaire was designed that included a set of questions that were directed to a sample of 84 individuals including production managers, finance managers, quality managers, and purchasing managers in these companies. The study uses some statistical analyzes such as correlation analysis and regression analysis to analyze the questionnaires. The study finds a positive impact of the green target costing technique on improving the relationship with suppliers. The results indicate that the relation
... Show MoreBearing capacity of a concrete pile in fine grained cohesive soils is affected by the degree of saturation of the surrounding soil through the contribution of the matric suction. In addition, the embedded depth and the roughness of the concrete pile surface (expressed as British Pendulum Number BPN) also have their contribution to the shear strength of the concrete pile, consequently its bearing capacity. Herein, relationships among degree of saturation, pile depth, and surface roughness, were proposed as a mathematical model expressed as an equation where the shear strength of a pile can be predicted in terms of degree of saturation, depth, and BPN. Rel
... Show MoreBackground: The aim of this study was to evaluate the effect of thermo cycling and different pH of artificial saliva (neutral, acidic, basic) on impact and transverse strength of heat cure acrylic resin reinforced of with 5% silanated ZrO2 nano fillers. Materials and methods: 120 samples were prepared, 60 samples for impact strength test and another 60 samples for transverse strength test, for each test, samples were divided into two major groups (before and after thermo cycling), then each of these major groups were further subdivided into 3 subgroups according to the pH of prepared artificial saliva (neutral, acidic, basic). Charpy impact device was used for impact strength test and Flexural device was used for transverse strength test. R
... Show MoreThe purpose of this work is to concurrently estimate the UVvisible spectra of binary combinations of piroxicam and mefenamic acid using the chemometric approach. To create the model, spectral data from 73 samples (with wavelengths between 200 and 400 nm) were employed. A two-layer artificial neural network model was created, with two neurons in the output layer and fourteen neurons in the hidden layer. The model was trained to simulate the concentrations and spectra of piroxicam and mefenamic acid. For piroxicam and mefenamic acid, respectively, the Levenberg-Marquardt algorithm with feed-forward back-propagation learning produced root mean square errors of prediction of 0.1679 μg/mL and 0.1154 μg/mL, with coefficients of determination of
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