In the present study, a solar air heater U shaped turbulators integrated on the absorber plate with artificial roughness has been subjected to computational fluid dynamics (CFD) analysis. For simulation, Renormalization group (RNG) k- ɛ model has been used to investigate several fluid flow properties such as flow behaviour, temperature distribution along absorber plate, and velocity distribution. By taking into account the relative roughness height (e/D) varies from 0.018 to 0.038 and a turbulence intensity of 5%, the aforementioned fluid flow properties have been investigated. Reynolds' number has a value varied in between 3800 to 18000. Also, it has been discovered that effective efficiency reaches a maximum value of around 0.7396 for relative roughness height of 0.038 at Reynolds' number of 16000. Further, results obtained from simulation suggested that there has been a considerable rise of about 22°C in temperature of air after passing through the roughened solar air heater.

The use of cultivation techniques that can properly prepare the seed bed and plant the seeds at an almost uniform depth has become necessary more than ever. In this research, the plane sitting test was used for modeling. In the simulation, the soil was considered as an elastic plastic body with two criteria Mohr-Coulomb and Drucker-Prager and the influence of the tiller as a compressive force. This experiment was implemented using strip plots in the form of a completely randomized block design with four replications in the crop year 1401-1400. The design of the tools was done using SolidWorks software and the modeling was done using Abaqus software. The general purpose of this research was to introduce the best tiller with suitable planting arrangements for direct cultivation machinery in Iran. The results of modeling with Abaqus software showed that the Drucker-Prager behavior model with a correlation coefficient of 0.93% was in better agreement than the Mohr-Coulomb model and the amount of stress and displacement in the layers close to the loading level is greater and moving towards the lower layers. This value decreases. The overall results showed that the cruciferous cultivar has the most optimal type of cultivation arrangement.

Metal Bellows finds wide application in expansion joints, which are used in aerospace, chemical plants, power system, heat exchangers, automotive vehicle parts, piping system, petrochemical plant, refineries, etc. During service they are subjected to various stresses and exposed to different environments, which leads to failure. Hence there is a need for proper design of metal bellow as per the application. The main objective of the paper is to evaluate the stresses generated in the metal bellow and the cycle life working at different working pressures. In this paper, the stresses are calculated using Expansion Joint Manufacturing Association (EJMA) standards and compared with the results obtained using ANYS software for two different materials namely Inconel 625 and Inconel 718 for the pressure values ranging from 20 to 40 bar.

In this paper, we perform a detailed study of the spectral response of the gold U-shaped nano-structures for different geometrical parameters and polarizations in order to obtain significant localization factor in the wavelength 1. 55 μ m. The obtained near-field distribution of electric fields reveals that resonances in these nano-structures correspond to the even and odd plasmonic modes depending on the geometrical parameters and polarization directions. Considerably large localization factor is obtained for the first odd mode in specific geometrical parameters. Then, this structure is considered to be surrounded by a typical secondorder nonlinear dielectric. The effective susceptibility is calculated for the considered structure, using the nonlinear retrieval method, to demonstrate the enhanced second-harmonic generation quantitatively. In order to represent the applicability of the investigated structure in nano-scale light sources and frequency doublers, its second harmonic generation efficiency is compared with the efficiency of the nonlinear dielectric alone with the same dimensions.

In recent years, robots have been an eminent solution for manufacturers to facilitate their process and focus on a variety of their products. As the importance of robot usages, our paper focuses on the robotics assembly line. In this paper, we have considered the cycle time, robot operational costs, robot purchase costs, and robot energy consumptions. In the following, we add robot failure rates to have an efficient and high-quality assembly line. The presented model is a multi-objective problem, therefore, the linear programming methods as goal programming and augmented ε-constraint method are applied to optimize the problem. In the end, we have considered a case study to examine and show the applicability of the proposed model on the real situation.

Lateral intake and stream diversion facilities, which are widely used in irrigation, land drainage and municipal sewage systems, deal with sediment transport. In this research, using a numerical discrete phase model, simulation of the sediment transport phenomenon is carried out in a 180-degree channel bend with a lateral intake that is located at a position of 115 degrees outside the arc and with a 45-degree diversion angle. The numerical model was calibrated with laboratory data. Then, in 31 positions of the channel bend from the 10 to 140 degrees with 5 degrees' intervals and with 5 diversion angles of 10, 30, 50, 70 and 90 degrees, and for three diversion discharge ratios of 20%, 30% and 40%, the calibrated numerical model has been implemented and the percentage of sediment entered to the lateral intake were determined for each model. The results were used as the data necessary for training and validation of Artificial neural network (ANN) model. The inputs of ANN model were location of lateral intake in outer bank of channel bend (φ) and diversion angle of lateral intake (θ), diverted water discharge ratio (Qr). The output is diverted sediment ratio into the lateral intake (Gr). The data were used for training and validation of the ANN model and the best structure was obtained for the neural network models using R2, SSE and MARE criteria and compared to regression models. The best structure of ANN model was obtained as a 5-layer model with 3 membership functions for each input variable and 27 conditional rules. The accuracy of the results obtained from the models in terms of the mean absolute relative error (MARE) indicates the ability of the neural network models to predict the amount of sediment diverted to the lateral intake with respect to regression models. Then, by developing a new simulation-optimization method based on the Multi-Objective Genetic Algorithm Optimization model (NSGAII), the FLUENT numerical model and neural network models, the optimal position and diversion angle of the lateral intake in the U-shaped channel is determined to minimize the amount of sediment inflow into the lateral basin and maximize the rate of dewatering discharge. By connecting the best model obtained from the ANN model, to NSGA-II model, the Pareto Front contains a list of optimal positions and optimal diversion angle of lateral intake are obtained with respect to the objective function and its limitations in the U-shaped channel. Finally, to determine the optimal position and angle of the lateral basin in the U-shaped channel by connecting the Pareto front obtained from the Multipurpose Genetic Algorithm (NSGA-II) to the TOPSIS multi-criteria decision-making method, the best option is found among the Pareto front options. The results include the optimum position and optimum angle of lateral intake dewatering along with diversion discharge and sediment rates corresponding to these values. The results show that the optimum diversion angle obtained is 38-degree and the optimum position obtained is 127-degree