Sharif Digital Repository

We use the detrended fluctuation analysis (DFA), the detrended cross correlation analysis (DCCA) and the magnitude and sign decomposition analysis to study the fluctuations in the turbulent time series and to probe long-term nonlinear levels of complexity in weakly and high turbulent flow. The DFA analysis indicate that there is a time scaling region in the fluctuation function, segregating regimes with different scaling exponents. We discuss that this time scaling region is related to inertial range in turbulent flows. The DCCA exponent implies the presence of power-law cross correlations. In addition, we conclude its multifractality for high Reynold's number in inertial range. Further, we... 

Adsorption of a methane molecule (CH 4) onto a defected and rippled graphene sheet is studied using ab initio and molecular mechanics calculations. The optimal adsorption position and orientation of this molecule on the graphene surface (motivated by the recent realization of graphene sensors to detect individual gas molecules) is determined and the adsorption energies are calculated. In light of the density of states, we used the SIESTA code. It is found that (i) classical force field yields adsorption energy comparable with experimental result and ab initio calculation; (ii) the periodic nature of the van der Waals potential energy stored between methane and perfect sheet is altered due to... 

The dynamical scattered light intensity and multiplicative cascade model was employed to characterize the anisotropic charged colloidal particles suspension during the so-called Sol-Gel transition. Generally we looked for finding a criterion to distinguish the properties of Sol and Gel states systematically. The probability density function (PDF) of the light scattering intensity shows an obvious change with proceeding of the sample aging process (during of gelation state). Our results confirmed that in the so-called Sol state, the value of non-Gaussian parameter, kW, as a function of time is larger than that of for weak-Gel or in coexistence Sol-Gel state. The number of cascades in the... 

Monodispersed semiconducting nanoparticles are usually synthesised in a liquid medium using injection of an appropriate solution. A key factor in attaining a narrow particle size distribution (PSD) is the temporal separation of the nucleation and growth stages, where the former takes place during the injection. Faster injection produces a larger number of nuclei and a narrower PSD. The injection speed is expected to affect the diffusion of the ions in the solution and to create uniformly high supersaturation for a short period of time. In this paper, we study the growth of CdS nanoparticles during the injection by molecular dynamics simulation. A solution of Cd ions is injected into the... 

The level crossing and inverse statistics analysis of DAX and oil price time series are given. We determine the average frequency of positive-slope crossings, να+, where Tα=1να+ is the average waiting time for observing the level α again. We estimate the probability P(K,α), which provides us the probability of observing K times of the level α with positive slope, in time scale Tα. For analyzed time series, we found that maximum K is about ≈6. We show that by using the level crossing analysis one can estimate how the DAX and oil time series will develop. We carry out the same analysis for the increments of DAX and oil price log-returns (which is known as inverse statistics), and provide the... 

Boron nitride quantum dots (BNQDs) functionalized with chemical ligands exhibit intriguing optoelectronic properties due to the quantum confinement effect. This paper presents peculiar insights on the effect of side defects on the electronic structure and optical properties of BNQDs functionalized with different chemical bonds including hydrogen (H), nitrogen (N), hydroxyl (OH), amine (NH2), and thiol groups (inspired by experimental reports of functionalized BN nanosheets and nanotubes) Weng, Chem. Soc. Rev. 45, 3989 (2016)0306-001210.1039/C5CS00869G. Hybrid density functional simulations and Green's function calculations indicate an intriguing coexistence of two different Peierls-like... 

Analysis of multi dimensional interactions of flow of energy in passenger vehicle is a complex task that necessitates development and utilization of analytical tools. Development of analytical tools with high complexity is usually based on conclusions of many concepts and theories from different scientific disciplines. In this approach, Passenger vehicle is supposed to be organized in the form of a firm and appears in the market that oriented towards establishing an effective energy supply system which may be identified as delivering the product (person kilometer or tone kilometer) with minimum operation costs. To this end, an optimization model named power software founded on theory of firm... 

Analysis of multi dimensional interactions of flow of energy in passenger vehicle is a complex task that necessitates development and utilization of analytical tools. Development of analytical tools with high complexity is usually based on conclusions of many concepts and theories from different scientific disciplines. In this approach, Passenger vehicle is supposed to be organized in the form of a firm and appears in the market that oriented towards establishing an effective energy supply system which may be identified as delivering the product (person per mileage removable) with minimum operation costs. To this end, an optimization model named POWER software founded on theory of firm of... 

In our investigation, the model of optimal energy flow in a passenger vehicle has been founded on the theory of firm microeconomics. Based on this theory, the car owner tries to minimize the total cost of the system (including the cost of time of the traveller) subject to the satisfaction of the required transport services and technological, economical, environmental and institutional constraints. The aforementioned model has been developed using a technique of mathematical programming. The model depicts the behaviour of a nonlinear system and it includes many nonlinear functions in the objective function and in the constraints. Solving the large nonlinear set of constraints and identifying...