Amin Moslemi Petrudi: Tehran University, Iran

Journal of Modeling and Simulation of Materials

Validation and Optimization of Thermophysical Properties for Thermal Conductivity and Viscosity of Nanofluid Engine Oil using Neural Network

10 Jun 2020

Amin Moslemi Petrudi, Masoud Rahmani

https://doi.org/10.21467/jmsm.3.1.53-60

In this study, the thermophysical properties of thermal conductivity and viscosity of a motor oil nanofluid were investigated using experimental data and artificial neural network. NSGA II optimization algorithm was used to maximize thermal conductivity and minimum viscosity with changes in temperature and volume fraction of nanofluids. Also, to obtain the viscosity and thermal conductivity values in terms of nanofluid temperature and volume fraction with 174 experimental data, neural network modeling was performed. Input data include temperature and volume fraction, and output is viscosity and thermal conductivity. Various indices such as R squared and Mean Square Error (MSE) have been used to evaluate the accuracy of modeling in the prediction of viscosity and thermal conductivity of nanofluids. The coefficient of determination R squared is 0.9989 indicating acceptable agreement with the experimental data. In order to optimize and finally results as an objective function, the optimization algorithm is presented and the Parto front and its corresponding optimum points are presented where the maximum optimization results of thermal conductivity and viscosity occur at 1% volume fraction.

Journal of Modeling and Simulation of Materials

Analytical Investigation of the Vibrational and Dynamic Response of Nano-Composite Cylindrical Shell Under Thermal Shock and Mild Heat Field by DQM Method

25 Mar 2020

Masoud Rahmani, Amin Moslemi Petrudi

https://doi.org/10.21467/jmsm.3.1.22-36

In this paper, the vibrations and dynamic response of an orthotropic thin-walled composite cylindrical shell with epoxy graphite layers reinforced with carbon nanotubes under heat shock and heat field loading are investigated. the carbon nanotubes were uniformly distributed along the thickness of the composite layer. The problem is that at first there is a temperature change due to the thermal field in the cylinder and the cylinder is coincident with the thermal field, then the surface temperature of the cylinder rises abruptly. Partial derivative equations of motion are coupled to heat equations. The differential quadrature method (DQM) is used to solve the equations. In this study, the effects of length, temperature, thickness and radius parameters on the natural frequencies and mid-layer displacement are investigated. The results show that increasing the outside temperature reduces the natural frequency and increases the displacement of the system. Radial displacement results were also compared with previous studies and were found to be in good agreement with previous literature. Increasing the percentage of carbon nanotubes also increased the natural frequency of the system and decreased the mobility of the middle layer.

Journal of Modeling and Simulation of Materials

Multi-objective Optimization to Increase Nusselt Number and Reduce Friction Coefficient of Water/Carbon Nanotubes via NSGA II using Response Surface Methodology

05 Mar 2020

Amin Moslemi Petrudi, Pourya Fathi, Masoud Rahmani

https://doi.org/10.21467/jmsm.3.1.1-14

Heat transfer science is one of the most important and most applied engineering sciences, with the importance of energy management and energy conservation being doubled. Because of their properties, nanofluids have been widely used in various industries, making them particularly important to study. In this paper, the Nusselt number and coefficient of friction with volume fraction ranging from 0 to 0.1 at approximately Reynolds numbers of 200 to 5000 are studied experimentally. Higher thermal conductivity, better stability, lower pressure drop was observed using nanoparticles of solid particles. NSGA II algorithm was used to maximize Nusselt number and minimum friction coefficient by changing temperature and volume fraction of nanoparticles. To obtain Nusselt number and friction coefficient based on the temperature and volume fraction of the nanoparticles, the experimental data response surface methodology was used and with increasing Reynolds number, the Nusselt number increased and the friction coefficient decreased. In order to evaluate the objective functions in the optimization, the response surface methodology is attached to the optimization algorithm. At the end, the Pareto Front and its corresponding optimal points are presented.

Periodica Polytechnica, Mechanical Engineering

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Optimization and Experimental Investigation of the Ability of New Material from Aluminum Casting on Pumice Particles to Reduce Shock Wave

30 Jun 2020

Masoud Rahmani, Amin Moslemi Petrudi

https://doi.org/10.3311/ppme.15983

Some materials, due to their inherent properties, can be used as shock and wave absorbers. These materials include foam and porous materials, in this study, specimens were made by casting aluminum on porous mineral pumice. Which can replace aluminum foam in some applications with lesser cost, at first, the material is compared with aluminum foam using compression test and quasi-static loading diagram. Which compares the diagrams of these two materials showing the similarity of their behavior in quasi-static loading. Initially, the elastic bending of the walls causes an elastic region in the stress-strain curve of the material. Then, the plastic collapsing of the cells forms a large and relatively smooth region along the elastic and after the plastic collapse of the cells, the area known as foam densification begins where the density of the foam closer to the density of its constituent material causes a sudden increase in the stress level in the specimen. These steps have also been seen in the quasi-static loading of aluminum foam. Then, by using numerical simulations with ANSYS AUTODYN and the shock tube test the ability of these specimens were investigated to reduce the shock wave. The behavior of the material in this case is also very similar to the results of previous studies on aluminum foam.

Amin Moslemi Petrudi

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Validation and Optimization of Thermophysical Properties for Thermal Conductivity and Viscosity of Nanofluid Engine Oil using Neural Network

Analytical Investigation of the Vibrational and Dynamic Response of Nano-Composite Cylindrical Shell Under Thermal Shock and Mild Heat Field by DQM Method

Multi-objective Optimization to Increase Nusselt Number and Reduce Friction Coefficient of Water/Carbon Nanotubes via NSGA II using Response Surface Methodology

Optimization and Experimental Investigation of the Ability of New Material from Aluminum Casting on Pumice Particles to Reduce Shock Wave

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