فهرست مطالب صادق صادق زاده

Superhydrophobic surfaces have gained significant attention as a promising approach for drag reduction of submerged objects. Accurate evaluation and prediction of drag reduction induced by these surfaces require expensive experimental measurements, numerical simulations, or the development of reliable models and correlations. In this paper, a model is proposed for calculating the skin friction coefficient and drag reduction of superhydrophobic flat surfaces. Utilizing previous data on the skin friction coefficient of flat surfaces under no-slip boundary conditions, a model is developed to estimate the skin friction reduction and skin friction coefficient of these surfaces after applying superhydrophobic coatings. The validity of the model is verified by comparing its results with those of computational fluid dynamics (CFD) simulations of flow over a flat plate at different velocities. The results of the model and simulations indicate that for inlet velocities of 1, 5, and 25 m/s and a slip length of 50 μm, drag reductions of 15%, 41%, and 77%, respectively, are expected. Additionally, the skin friction reduction increases with increasing flow Reynolds number. The developed model is validated for flat surfaces and its ability to accurately estimate the skin friction coefficient and drag force of these surfaces is thoroughly examined. However, further investigations are required to assess the model's validity for curved surfaces and variable slip lengths.

Graphene is one of the youngest member of the nano-carbon material with two-dimensional structure which has extraordinary mechanical and electrical properties. Graphene sheets can also be used as mass sensors. In this paper, the special applications of this substance as a mass sensor are considered. The vibrational behavior of a graphene mass sensor is studied by molecular dynamics simulation method. Also, the effects of increase the dimensions of the rectangular sheet in two zigzag and armchair directions has been studied on natural frequencies. For this purpose, a square graphene sheet has been created in the molecular dynamic environment and the particle displacement is obtained from the molecular dynamics method. The displacements are analyzed using the frequency domain decomposition method and the first natural frequency of the sheet is calculated. Then, the dimensions of graphene sheet have been changed in the zigzag and armchair directions, and the natural frequency of the sheet is also estimated. In order to validate the method, the estimated natural frequency is compared with the results of one of the improved theories of continuous mechanics. In the following, the ability of graphene sheet for detection of attached mass has been examined using the presence of concentrated gold particles. Finally, the sensitivity of graphene sheet to the attached masses is presented.

In this paper, by using the classical molecular dynamics and coarse grained molecular dynamics, the mechanism of automatic nanomanipulation with atomic force microscope nano-robot was modelled and it was shown that the rupture of tip is the most error source in the automatic nano-manipulation process, where is manipulation of particles on the substrate frequently. By this, to prevent from the non-favorable effects of deformation of tip on the result of nano-manipulation, a control plan was introduced. By definition of root mean squares as a criterion for measurement of the level of deformation, a simple feedback of it was used to control the system. After that the model proposed and validated in comparison with some experimental works, by using the coarsening the molecular dynamics, the system is converted into a relatively simple model and was suggested for implementation into the manipulation processes. By using this model, it was observed that although the aluminum tip leads to the worst result, by using the shape feedback, the positioning error has been reduced considerably. Positioning error without and with feedback was reported for a nickel tip as 37.77% and 17.77%, respectively. These values show the efficiency of the presented shape feedback approach.

In this study, numerical simulation of oscillating water column device is presented using a finite-volume method. For this purpose, the computational fluid dynamic model based on Navier-Stokes equations, was used. The cylindrical OWC was used and this kind of device has a symmetric ability for dealing with the waves. Analyses are divided into two sections. In the first section, the waves variables obtained from both experimental and numerical research with simulated waves are compared and similar results are obtained. In the second section, an investigation of the chamber geometry, the wave characters on the southern coast of Iran and different depths of submergence of OWC that provide the best device performance is carried out. It is found that both the different wave characters and depths of submergence of OWC tests indicate little influence over the device performance. Indeed, the device performance with a constant diameter has improved about 2.94 percent, with changes in amplitude and period. Also, the chamber diameter tests indicated that the device geometry has greatest influence in itsperformance, so that, when the device diameter has increased two and four times, the device performance has increased by 2.54 and 10.27 times, respectively.

In this paper, efficiency of defected graphene nano ribbon incorporating with additional nanoparticles on mass detection operations is studied via the Reverse Non Equilibrium Molecular Dynamics (RNEMD) method. Thermal conductivity management of this structure is challenging because of imposed losses in electrical conductivity and any procedure could manage the thermal conductivity of graphene will be useful. In this paper it is observed that on the mass detection operation, due to the porosity generation in the nano ribbon surface or even creation of external nanoparticles, thermal properties of graphene change considerably. This should be noted in calibration of graphene based mass sensors. In summary, results show that the graphene’s thermal conductivity would reduce by increasing the concentration of nanoparticles and thermal conductivity of graphene is higher when porosities and impurities are at the edges. This indicates that the location of vacancies and nanoparticles influences the thermal conductivity. For a better thermal management with the help of nanoparticles, wither respect to the porosities, addition of nanoparticles decrease the thermal conductivity more and more. By increasing the cavity’s diameter from 0.5nm to 4.4nm in a specific single layer graphene, thermal conductivity was reduced from 67 W/mk to 1.43 W/mk.