Sharif Digital Repository

Pulsating heat pipes (PHPs) are heat transfer devices which are widely utilized in electronic devices and energy systems. Improvement in thermal performance of PHPs will lead to higher heat transfer capacity and enhancement in the efficiency of systems which PHPs are applied. In this study, an experimental investigation was performed on the thermal performance of a pulsating heat pipe by applying graphene oxide nanofluid as working fluid. Four concentrations of graphene oxide (0.25, 0.5, 1, and 1.5 g/lit) in water as base fluid were used in the PHP. Results indicate that adding graphene oxide sheets increased thermal conductivity and viscidity of the base fluid. Moreover, utilizing graphene... 

Uncertainties associated with bus loading and components' availability lead to uncertainties in different system variables based on the system physical and economical relationships. Line flows, bus voltages, different prices, and other variables and indices, such as available transfer capacity (ATC), are stochastic and cannot be expressed as a determined quantity. Traditionally, in order to model the stochastic nature of power systems, a stochastic power flow algorithm is used. In this paper, stochastic-algebraic method is applied to find the probability density function (pdf) of ATC. The algorithm linearizes the optimal power flow formulation and uses Gram-Charlier expansion to find the pdf... 

Thermal conductivity of nanofluids plays key rol in heat transfer capacity of fluids. adding nanoparticles to a base fluid can lead to enhancement in thermal conductivty ratio. CuO/Ethyle Glycol (EG) is one of the most applicable nanofluids for heat transfer purposes. In the present study, thermal conductivty ratio of CuO/EG nanofluid is modeled by applying Group Method of Data Hnadling and Least Square Support Vector Machine – Gentic Algorithm approaches. Results indicated that the utilized model are very accurate in predicting thermal conductivty ratio of the nanofluid. The R-squared values for the proposed model are equal to 0.994 and 0.991 by applying Group Method of Data Handling and...