• Energy Research

Abstract This study aimed at exploring influence of T-semi attached rib on the turbulent flow and heat transfer parameters of a silver-water nanofluid with different volume fractions in a three-dimensional trapezoidal microchannel. For this purpose, convection heat transfer of the silver-water nanofluid in a ribbed microchannel was numerically studied under a constant heat flux on upper and lower walls as well as isolated side walls. Calculations were done for a range of Reynolds numbers between 10,000 and 16,000, and in four different sorts of serrations with proportion of rib width to hole of serration width (R/W). The results of this research are presented as the coefficient of friction, Nusselt number, heat transfer coefficient and thermal efficiency, four different R/W microchannels. The results of numerical modeling showed that the fluid's convection heat transfer coefficient is increased as the Reynolds number and volume fraction of solid nanoparticle are increased. For R/W=0.5, it was also maximum for all the volume fractions of nanoparticle and different Reynolds numbers in comparison to other similar R/W situations. That's while friction coefficient, pressure drop and pumping power is maximum for serration with R/W=0 compared to other serration ratios which lead to decreased fluid-heat transfer performance.

Due to the extreme use of fossil fuels and increasing environmental problems, the steel industries have been always seeking solutions to decrease energy consumption. These efforts will not only reduce greenhouse gases (GHGs) but also decrease the costs of these industries. In this study, we investigated the effects of burners’ heating load distribution in a hot-rolling preheating furnace, by numerical modeling. This study incorporates a three-dimensional model for preheating furnaces with a given geometry and various heating loads’ distribution. Following the determination of boundary conditions, the simulation process will be carried out. This research will be evaluated in four different cases. In one case, the burners’ load distribution is uniform and in the other three cases the burners’ load distribution decreases exponentially along with the furnace. The results of this study indicate that the best scenario from a performance perspective is true, the exponential expression X−0.8 in which the energy consumption decreases up to 44 %, and the slab temperature will be reached to the given desired temperature in the furnace.

article i nfo The accuracy of soft computing technique was employed to predict the performance of micro- and nano-sized particle erosion in a 3-D 90° elbow. The process, capable of simulating the total and maximum erosion rate with adaptive neuro-fuzzy inference system (ANFIS), was constructed. The developed ANFIS network was with three neurons in the input layer, and one neuron in the output layer. The inputs included particle velocity, particlediameter,andvolumefractionof thecopperparticles.The sizeof these particleswasselectedintherange of10 nmto 100 μm.Numericalsimulationshave beenperformedwith velocities rangingfrom 5to20m/sandfor volume fractions of up to 4%. The governing differential equations have been discretized by the finite volume method for ANFIS training data extraction. The ANFIS results were compared with the CFD results using root- mean-square error (RMSE) and coefficient of determination (R 2 ). The CFD results show that an improvement in predictive accuracy and capability of generalization can be achieved by the ANFIS approach. The following characteristics were obtained: ANFIS model can be used to forecast the maximum and total erosion rate with high reliability and therefore can be applied for practical purposes.

The coronavirus pandemic is caused by intense acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Identifying the atomic structure of this virus can lead to the treatment of related diseases in medical cases. In the current computational study, the atomic evolution of the coronavirus in an aqueous environment using the Molecular Dynamics (MD) approach is explained. The virus behaviors by reporting the physical attributes such as total energy, temperature, potential energy, interaction energy, volume, entropy, and radius of gyration of the modeled virus are reported. The MD results indicated the atomic stability of the simulated virus significantly reduced after 25.33 ns. Furthermore, the volume of simulated virus changes from 182397 Å3 to 372589 Å3 after t = 30 ns. This result shows the atomic interaction between various atoms in coronavirus structure decreases in the vicinity of H2O molecules. Numerically, the interaction energy between virus and aqueous environment converges to -12387 eV and -251 eV values in the initial and final time steps of the MD study procedure, respectively.

Despite the widespread use of diffusers in various industries, there is no comprehensive research so far. This is expressive on how the flow diffuses throughout the diffuser geometry, the amount of non-uniformity of speed distribution at the outlet, and the rate of eddy flows at the corners. The present study simulated a three-dimensional diffuser with a square geometry at different divergence angles in order to obtain a better understanding of the flow diffusion across the geometry, velocity distribution at the outlet, and reverse flow. Moreover, the aspect ratio and the Reynolds number were considered constant in all cases. The turbulence model was used along with a high-resolution discretization and a root-mean-square convergence criterion to solve this problem. The speed was substantially reduced to nearly zero at corners of the diffuser with a square cross section. Reverse flow and eddy currents were also observed in the same regions. By increasing the divergence angle, this effect was further intensified, and in addition to the corners, flow separation and eddy currents were formed in the regions close to the wall due to the adverse pressure gradient. The maximum velocity and flow distribution at the outlet cross section was located in the central region, which was intensified by increasing the divergence angle. The deviation of the average velocity at the diffuser outlet with a divergence angle of 5°, with a completely uniform velocity distribution at the outlet, was observed to be 15.3%. This deviation grew with an increase in divergence angle and reached 128.9% at a divergence angle of 30°.

Abstract From the perspective of renewability and environmental pollution, biodiesels are appropriate alternatives to conventional diesel fuels due to their proper combustion behavior and atomization characteristics, which can be influenced by the viscosity as an essential factor. Therefore, the viscosity prediction would be of importance for blend of biodiesel/diesel fuels. For biodiesel/diesel mixtures, the blended viscosity has been predicted with numerous empirical correlations available in the literature. In this work, the viscosity of fuel mixtures was evaluated through Generalized regression neural network (GRNN), Radial Basis Neural Networks (RBFNN), Multi-Layer Perceptron Neural Network (MLPNN), and Cascade Feed-forward Neural Network (CFNN), based on various experimental data. These developed models were then compared in terms of predictive accuracy and available empirical correlations to select the best model. Finally, the proposed model was compared with the most prominent biodiesel viscosity models confirming that the developed model has been superior in predicting the value of viscosity for biodiesel blends with reported values of 0.9997 and 0.87% for parameters of the coefficient of determination (R2) and absolute average relative deviation (AARD%), respectively.

In this experimental research, the laminar forced convection of water–magnetite nanofluid (NF) in a horizontal twisted tube (TT) is examined under a rotating magnetic field (MF). The findings are compared with those of the plain tube (PT). The influence of nanoadditive concentration ( $$\varphi$$ ), Reynolds number (Re), twist pitch (P) and MF arrangement on the heat transfer, friction factor and overall thermohydraulic features of NF is assessed. The MF consists of two magnets that rotate around the tube. For each of the magnets, three modes of clockwise rotation, counterclockwise rotation and without rotation are considered. The findings showed that the combined use of TT and rotating MF entails an increase in the overall thermohydraulic features of water–magnetite NF. In addition, it was found that the overall thermohydraulic features of NF augment with boosting $$\varphi$$ , while they decline with boosting P and Re. Moreover, it was revealed that the best thermohydraulic features of the water–magnetite NF belonged to the case of $$\varphi$$ = 2%, Re = 500 and P = 10 mm in the presence of a rotating magnetic field resulting from the clockwise rotation of the first magnet and the counterclockwise rotation of the second magnet.