فهرست مطالب نویسنده:
k. r. kashyzadeh
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This study investigates the fatigue life prediction of Inconel 600 under multiaxial loading conditions as well as fatigue crack growth under mixed mode (I and II). Finite element simulations based on critical plane criteria were performed for fatigue analysis under combined tensile and shear loading in different non-proportional modes (i.e., phase difference between tensile and shear loads). To achieve this, fully reversed tensile stress with a maximum value of 480 MPa (mean stress: zero) was considered. Subsequently, a constant shear stress of 28 MPa was applied at different phase angles ranging from 0° to 90° in 10-degree intervals (i.e., 0°≤θ≤90°,∆θ=10° ). For all modes, hysteresis stress diagrams were extracted to investigate the cyclic behavior of the material. Furthermore, various fatigue damage models, including Fatemi-Socie, SWT, normal strain, and shear strain, were employed to assess the fatigue life of the samples under different loading modes using MSC software. The results showed that the Fatemi-Socie and shear strain criteria predict the shortest fatigue life for phase difference in the ranges of 0°-30° and 40°-90°, respectively. Therefore, selecting a more conservative criterion is not feasible as it depends on the loading conditions. Additionally, it was found that the most critical conditions occurred at phase difference of 50° and 60°. Next, in order to numerically investigate the crack growth behavior, a semi-Arcan fixture model was used. Simulations were performed for four different loading modes (i.e., fixture settings), considering variations in the loading angle with respect to the longitudinal axis of the crack (0°, 30°, 60°, and 90°). Eventually, crack length graphs were extracted in terms of loading cycles. The results indicated that the lowest and highest crack growth rates occurred when the angle between loading and the longitudinal axis of the crack was 0° and 90°, respectively.Keywords: Multiaxial Fatigue Life, Hysteresis Diagram, Mixed Mode Crack Growth, Inconel 600
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This study introduces an Enhanced Autoregressive Integrated Moving Average (E-ARIMA) model for anomaly detection in time-series data, using vibrations monitored by CA 202 accelerometers at the Kirkuk Gas Power Plant as a case study. The objective is to overcome the limitations of traditional ARIMA models in analyzing the non-linear and dynamic nature of industrial sensory data. The novel proposed methodology includes data preparation through linear interpolation to address dataset gaps, stationarity confirmation via the Augmented Dickey-Fuller Test, and ARIMA model optimization against the Akaike Information Criterion, with a specialized time-series cross-validation technique. The results show that E-ARIMA model has superior performance in anomaly detection compared to conventional Seasonal ARIMA (SARIMA) and Vector Autoregressive models. In this regard, Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) criteria were utilized for this evaluation. Finally, the most important achievement of this research is that the results highlight the enhanced predictive accuracy of the E-ARIMA model, making it a potent tool for industrial applications such as machinery health monitoring, where early detection of anomalies is crucial to prevent costly downtimes and facilitate maintenance planning.Keywords: Vibration monitoring, Time-series data, Anomaly Detection, Autoregressive integrated moving average, Gas power plant
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The main purpose of this paper is to assess the impact of the geometry and size of the aggregate, as well as the drying temperature on the compressive strength of the ordinary concrete. To this end, two aggregates with sharp and round corners were prepared in three different aggregate sizes. After preparing concrete samples, the drying operations were carried out in the vicinity of room temperature, cold wind, and hot wind. Next, the linear relationship between the concrete strength and the studied parameters was estimated using Multiple Linear Regression (MLR) method. Finally, the Taguchi Sensitivity Analysis (TSA) and Decision Tree Analysis (DTA) were applied in order to determine the importance of the parameters on the compressive strength of concrete. As a result, it is obtained that the aggregate size has the greatest influence on the compressive strength of the ordinary concrete followed by drying temperature as stated by method TSA and DTA. In addition, the influence percentages reported for each parameter by Taguchi approach and decision tree method are matched. The prediction of the strength obtained by Taguchi method and second-order regression with the experimental data are in a good agreement. It was concluded that the impact of drying temperature on the concrete strength is several times greater than the effect of the aggregate geometry. Finally, the main conclusion of this research is related to the application of cold wind for drying operation, which leads to an increase of the compressive strength by 8.67% and 11.55% for ordinary concrete containing a constant aggregate size of 20 and aggregate geometries of round and sharp corners, respectively.Keywords: Concrete, Compressive strength, aggregates, Drying process, Temperature
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In this study, it was attempted to design a high-performance single-walled carbon nanotube (SWCNT) bundle interconnects in a full adder. For this purpose, the circuit performance was investigated using simulation in HSPICE software and considering the technology of 32-nm. Next, the effects of geometric parameters including the diameter of a nanotube, distance between nanotubes in a bundle, and width and length of the bundle were analyzed on the performance of SWCNT bundle interconnects in a full adder using Taguchi approach (TA). The results of Taguchi sensitivity analysis (TSA) showed that the bundle length is the most effective parameter on the circuit performance (about 51% on the power dissipation and 47% on the propagation delay). Moreover, the distance between nanotubes greatly affects the response compared to other parameters. Also, response surface method (RSM) indicated that an increase in the length of interconnects (L) improves the output of power dissipation. As the width of interconnects (W) and diameter of CNTs (D) increase the power dissipation also increases. Decrease in the distance between CNTs in a bundle (d) leads to an increase in power dissipation. The highest value of power dissipation is achieved if the maximum values for the parameters of length and width of interconnects (L, W), and diameter of CNTs (D) and the minimum value of the distance between CNTs in a bundle (d) are considered. It is also revealed that an increase in the length of interconnects (L) increases the propagation delay. Eventually, the optimum parameters are reported and the performance of the optimized system is compared using different methods (TA and RSM). Results indicate that the difference between the performance of optimal design of SWCNT bundle interconnects in a full adder predicted by different methods is less than 6% which is acceptable according to engineering standards.Keywords: Carbon Nanotube Bundle Interconnects, full adder, Power dissipation, Propagation delay, response surface method, Taguchi approach
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