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Abstract: Because of the complicated nature of track and train, investigation of interactions between them has been always an complex problem in railway engineering. Perceiving of this interaction is an complex problem only in track with various defects but also in the track without defects. Estimating of the forces exerted on track and train will be much difficult when a defect such as rail corrugation is added to this interaction. If an accurate computer model is available, we can have a good forecast of these forces. However, precise estimating of them is only reached field measurement. In this study, we tried to present a good estimation of passenger and freight wagon forces on track with rail corrugation defect. The pressure between sleeper and ballast was calculated by these forces. Afterwards pressure (on ballast surface)-rail corrugation wavelength diagrams was determined. By using these diagrams, the rail corrugation wavelength where ballast stresses were beyond the permissible limit for each type of operation, was determined (it was named critical corrugation wavelength). A computer model was developed in ADAMS/Rail software for passenger and freight wagons with various speeds to estimate the forces exerted on the ballasted track with corrugation defect.

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The Direct Torque Control (DTC) of Interior Permanent Magnet Synchronous Motor (IPMSM) offers simple structure and fast torque response. The conventional Switching Table-based DTC (ST-DTC) presents some disadvantages like high torque and flux ripple and also variable switching frequency. This paper investigates the improved ST-DTC strategies to reduce both torque and flux ripple in DTC of IPMSM with emphasis on structure simplicity and fast dynamics. New switching table with only two active vectors for each sector is introduced and the torque control hysteresis band is replaced by duty cycle calculation unit. For flux ripple reduction, conventional hysteresis-based controller is replaced by simple dithering technique. The duty cycle calculation unit is implemented to operate on each selected vector with the aim of torque ripple RMS minimization. The increase of switching frequency in ST-DTC because of delay in torque and flux estimation process, actually, is not possible; even when hysteresis bands are sufficiently diminished. This paper incorporates the combination of duty cycle modulated DTC and dithering technique to enlarge switching frequency. It therefore provides smoother waveform concurrently for the motor torque and the flux.  In the proposed method waveform comparison structure for duty cycle calculation is used; hence, the merits of classical ST-DTC, such as fast dynamic and simple structure, are mostly preserved

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Recently, the use of coronary stents in interventional procedures has rapidly increased and different stent models, with different geometries and materials, have been introduced in the market. In order to select the most appropriate stent model, it is necessary to analyze and compare the mechanical behavior of different types of stent. In this paper, finite element method is used for investigating the effect of stent geometry and material properties on its behavior. Two commercially available stent designs with different geometries (the Palmaz–Schatz and NIR stents) and two different stent materials (stainless steel 304 and Cobalt alloy MP35N) are modeled and their behavior during the deployment is compared in terms of stress distribution in the stent and vessel, and outer diameter changes. Moreover, the effect of stent geometry and material properties on the restenosis after coronary stent placement is investigated by comparing the stress distribution in the arteries. According to the findings, the possibility of restenosis after coronary stenting is lower for NIR stent in comparison with Palmaz–Schatz stent. Moreover, stainless steel 304 is more suitable material for manufacturing stents, in comparison with the other one.

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In Carbon monoxide (CO) is one of the main air pollutant parameters in the atmosphere of Tehran, Iran. Generally, it is difficult to predict and control CO concentration because it is essentially nonlinear time-varying system. Recently, in particular, environmental control such as CO concentration level control is regarded as one of the most important factors in environmental protections. This paper describes forecasting and more specifically uncertainty determination of CO concentration during the modeling process using a support vector machine (SVM) technique. Uncertainty of the air pollution modeling studies highly affected the simulation results. In this regards, it is very important to determine the uncertainty of air pollution models due to consequences on health of people exposed to the pollution. Therefore, this research aims to calibrate, verify, and also determine the uncertainty of support vector machine (SVM) in the process of air pollution modeling in the atmosphere of Tehran. To achive this goal, the SVM model was selected to predict arithmetic average of daily measured CO concentration in the atmosphere of Tehran. In this regards, the SVM model was calibrated and verified using six daily air pollutants include particulate matter with diameter equal or less than 10 micrometer (PM10), total hydrocarbons (THC), nitrogen oxides (NOx), methane (CH4), sulfur dioxide (SO2) and ozone (O3) and also six daily meteorological variables include pressure (Press), temperature (Temp), wind direction (WD), wind speed (WS) and relative humidity (Hum). The data was collected from Gholhak station located in the north of Tehran, Iran, during 2004-2005. Thereafter, the best developed SVM model for predicting the CO concentration was chosen based on determination of coefficient (R2). Finally, to determine the SVM uncertainty, the model was run many times with different calibration data. It led to many different results because of the model sensitivity to the selected calibration data. Then, the model uncertainty in the CO prediction process was evaluated using the width of uncertainty band (d-factor) and the percentage of measured data bracketed by the 95 percent prediction uncertainties (95PPU). Generally, the results confirmed the strong performance of the SVM model in predicting CO concentration in the atmosphere of Tehran. The predicted average daily CO concentrations by SVM model had a good agreement with the measured ones in the Gholahak air quality monitoring station. It was found that the determination of coefficient for calibration and validation of SVM model were equal to 0.89 and 0.88, respectively. Furthermore, the results indicated that the SVM model has an acceptable level of uncertainty in prediction of CO concentration in which the level of d-factor and the percentage of measured data bracketed by the 95PPU in the validation step were 0.74 and 76, respectively. Therefore, The obtained results indicated that the SVM model had an acceptable level of uncertainty in prediction of CO concentration. Therefore, it can be concluded that the SVM model is able to predict the CO concentration in the atmosphere of Tehran while it resulted an acceptable level of uncertainty. Finally, due to the proposed methodology is general, the authors suggest to apply it for analyzing the uncertainty of SVM model in other fields of science and engineering.

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The use of porous scaffolds for repairing the damaged bone tissues has been increased in recent years. As exploration of the mechanical properties of the scaffolds on the basis of experiments is time consuming and uneconomic, mathematical models are increasingly being introduced into the field, but most of them rely on finite element method and theoretical studies are rarely found in the literature. In this paper, different micromechanical models are presented for obtaining the effective elastic properties of bone scaffolds. Using these models, the mechanical properties of different scaffolds, including ceramic and composite bone scaffolds, are investigated. Single scale and multi-scale modeling approaches are used to simulate the ceramic and composite scaffolds, respectively. Furthermore, because of the wide application of hydroxyapatite in fabrication of bone scaffolds, the mechanical properties of hydroxyapatite scaffolds in different porosities are obtained in the current study by means of the presented methods. Results show that Dewey, self-consistent and differential schemes are the best methods in calculation of the value of Young’s modulus of these scaffolds in porosity ranges of less than 30 %, 30 to 60 % and more than 60 %, respectively. Moreover, self-consistent scheme gives good estimation of the value of Poisson’s ratio of hydroxyapatite scaffolds in different porosities. By obtaining the values of the mechanical properties of the scaffolds in different porosities by these models and using the statistical analysis, the mathematical relationship between the porosity and the mechanical properties of this kind of scaffolds (Young’s modulus and Poisson’s ratio) is obtained.

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High nutritional properties and therapeutic effects of sheep milk and dairy products can help many of the body's needs with its beneficial effects. Different percentages of cow's and sheep's milk (25, 50, 75 and 100%) were used in the preparation of traditional ice cream. Physicochemical and sensory tests such as pH, acidity (Dornik), fat percentages, melting resistance, dry matter and sensorial features such as flavor, odour, texture, sweetness and acceptability were studied. This research has 5 treatments and all tests were performed with 3 replications. Duncan's multiple range test was used to determine the difference between means at 95% confidence level and SPSS software was used for statistical analysis. The percentage of overrun in all samples was 30% as the same. The higher the percentage of cow's milk in the ice cream formulation, the lower the acidity, and conversely, the higher the percentage of sheep's milk in the ice cream formulation, the higher the acidity was observed. The pH of sample containing 100% cow's milk was highest. Traditional ice cream containing 75% of sheep's milk, had the highest percentages of fat, dry matter and melt resistance.  According to the 5-point Hedonic sensorial features treatment containing 50% of cow's milk and 50% sheep had a higher sensory rating than other treatments, and also in terms of characteristics Sensory senses are closer to the control treatment and are introduced as superior treatments.