Spindle speed variation and adaptive force regulation to suppress regenerative chatter in the turning process

Chatter suppression in machining processes results in more material removal rate, high precision and surface quality. In this paper, two control strategies are developed to suppress chatter vibration in the turning process including a worn tool. In the first stage, a sinusoidal spindle speed variation around the mean speed is modulated to disturb the regenerative mechanism. The optimal amplitudes of the speed modulations are found based on a genetic algorithm such that the input energy to the turning process is minimized. In the second stage, to improve the response of the system which is associated with small ripples under the steady state condition, an adaptive controller is designed. In this stage, the provided external force (e.g., by a piezo-actuator) is the input variable. Results are provided for each control strategy. It is shown that if both control approaches are applied simultaneously, chatter vibration is suppressed in less time without any ripples at the steady state condition.     

Performance of a pilot scale up-flow septic tank for on-site decentralized treatment of residential wastewater

The aim of this research was to study the on-site anaerobic treatment of a medium-strength residential wastewater in a pilot-scale up-flow septic tank (UST). The effects of three different hydraulic retention times (HRTs) of 24, 12 and 6 h on the UST performance were investigated. The UST removed 85, 77, and 86% of biochemical oxygen demand (BOD₅), chemical oxygen demand (COD) and total suspended solids (TSS), respectively, at steady state operation and with a 24 h HRT. Decreasing the HRT to 12 and then 6 h resulted in deteriorated effluent quality and significantly reduced reactor performance. The sludge showed a high specific methanogenic activity (SMA) of 15.2 mL CH₄ g^?1 VSS d^?1 with raw wastewater substrate. The solids accumulated in the tank by the end of the experiment had a VSS/TSS of 0.57, demonstrating significant stabilization. Overall, the UST is concluded to be a technically and economically promising alternative to conventional septic tanks for the on-site decentralized treatment of residential wastewater, particularly in the rural communities of developing countries.     

Hospital admissions in Iran for cardiovascular and respiratory diseases attributed to the Middle Eastern Dust storms

Environmental Science and Pollution Research - The main objective of this study was to assess the possible effects of airborne particulate matter less than 10 μm in diameter (PM10)...     

Application of Artificial Neural Networks to Predict Total Dissolved Solids at the Karaj Dam

We applied multilayer perceptron (MLP) and radial basis function (RBF) neural networks using data from two water quality monitoring stations at the Karaj Dam in Iran. Input data were calcium ions (Ca²⁺), magnesium ions (Mg²⁺), sodium ions (Na⁺), chloride ions (Cl^?), sulfate (), and pH, and the output data were total dissolved solids (TDS). An MLP with one hidden layer containing eight neurons was selected for the upstream water quality station using normalized input data. We developed a second MLP neural network for the downstream station with one hidden layer containing 10 neurons in the hidden layer using normalized input data. Considering applying normalized input data and one hidden layer, the coefficient of determination (R ²) and index of agreement (IA) between the observed and the predicted data for the upstream and downstream monitoring stations using the MLP neural networks were 0.985, 0.84, 0.99, and 0.92, respectively. The RBF neural network with 100 neurons in its hidden layer reached the minimum errors between the observed and the predicted results in upstream and downstream stations. The R ² between observed and predicted data for upstream and downstream monitoring stations for the RBF was 0.999 and 0.998, respectively. Data normalization improved the performance of the MLP neural networks. Sensitivity analysis indicated that magnesium is the most effective water quality parameter for predicting TDS, and sulfate is the second most effective water quality parameter affecting TDS prediction at the Karaj Dam.     

Statistical source identification of major and trace elements in groundwater downward the tailings dam of Miduk Copper Complex, Kerman, Iran

Identifying the possible sources of potential harmful metals in groundwater systems plays a crucial role in evaluating the potential risks to residents and local plant cover. An attempt was made to define the origin of Al, Cd, Cu, Fe, Mo, Ni, and Pb in groundwater using multivariate statistic approaches [principal component analysis (PCA), hierarchical cluster analysis], and tailings sequential extraction by the method of Tessier et al. The concentrations of studied elements were measured in 42 samples collected from 15 stations surrounding and downward the tailings dam of Miduk Copper Complex, central province of Kerman, Iran. According to the PCA results, confirmed by cluster dendrogram and metal content measurement of tailings sequential extracts, two components accounting for nearly 73% of the total variance, controlled the heavy metal variability and classified the possible source of groundwater contamination into two categories: (1) upper seepage which controls the variability of Cd, Cu, Fe, Ni, and Pb and (2) toe seepage of tailings dump affecting on Mo and Al concentration in downstream groundwater.     

Predicting Particulate Matter (PM2.5) Concentrations in the Air of Shahr‐e Ray City,Iran, by Using an Artificial Neural Network

Particulate matter (PM), along with other air pollutants, pose serious hazards to human health. The Artificial Neural Network (ANN) is a branch of artificial intelligence that has an ability to make accurate predictions. In this article, the authors describe such methods and how historical data on air quality, moisture, wind velocity, and temperature in Shahr‐e Ray City, located at the southern tip of Tehran, was used to train an ANN to provide accurate predictions of PM concentrations. The availability of such predictions can offer significant assistance to those who are working to reduce air pollution.     

Removal of manganese and zinc from Kahrizak landfill leachate using daily cover soil and lime

The possibility of in situ removal of heavy metals found in leachate generated at municipal solid waste landfills was studied through amendment of daily cover soil. Kahrizak landfill, which receives the waste generated at Tehran, was selected as the source of leachate and soil samples. Manganese and zinc were selected in this study. The soil sample taken from the Kahrizak site contained about 17% clay, which was presumed to have significant capability for removing manganese and zinc. This capability was assumed to be enhanced further through the addition of lime and consequently to improve the potential for chemical precipitation of the selected metals. The in situ removal experiment was accomplished through a set of seven columns filled with the sampled soil with varying contents of lime (i.e., from 0% to 6% by dry weight). Fresh leachate of low pH was added to the columns on a daily basis. Concentrations of manganese and zinc were measured in the influent and effluent during 40 days when biological clogging resulted in a condition of almost no outflow in the columns. The results indicated a substantial increase in removal efficiency through the addition of lime to the daily cover soil. Desorption resulting from the low pH of fresh leachate occurs at later stages compared to the column with no lime addition.     

Association between Blastocystis sp. infection and immunocompromised patients: a systematic review and meta-analysis

Environmental Science and Pollution Research - The significance of opportunistic infections in immunocompromised patients and the enigmatic pathogenicity of Blastocystis directed us to conduct the...     

Soil reinforcement with recycled carpet wastes.

A root or fibre-reinforced soil behaves as a composite material in which fibres of relatively high tensile strength are embedded in a matrix of relatively plastic soil. Shear stresses in the soil mobilize tensile resistance in the fibres, which in turn impart greater strength to the soil. A research project has been undertaken to study the influence of synthetic fibrous materials for improving the strength characteristics of a fine sandy soil. One of the main objectives of the project is to explore the conversion of fibrous carpet waste into a value-added product for soil reinforcement. Drained triaxial tests were conducted on specimens, which were prepared in a cylindrical mould and compacted at their optimum water contents. The main test variables included the aspect ratio and the weight percentage of the fibrous strips. The results clearly show that fibrous inclusions derived from carpet wastes improve the shear strength of silty sands. A model developed to simulate the effect of the fibrous inclusions accurately predicts the influence of strip content, aspect ratio and confining pressure on the shear strength of reinforced sand.