Sharif Digital Repository

Macroscopic and microscopic characteristics of spray of a Modified Bio-diesel Fuel (MBF), applying direct injection system have been explored and compared with those of conventional diesel fuel. MBF is a new combination of bio-diesel, molasses bio-ethanol, and water, which has been kept as a single-phase bio-fuel, employing an emulsifier. Lower emissions and production costs, higher oxygen content and cetane number are the key advantages of the MBF to be replaced by conventional fossil fuels in internal combustion engines. Applying atomization model, the spray atomization properties such as Ohnesorge number and Sauter Mean Diameter (SMD) have been investigated. Air entrainment analysis has... 

In the present work, the spray characteristics of bio-ethanol and its blends have been experimentally and theoretically investigated. To have a comprehensive study, the effects of ambient condition and injection pressure on the spray of different blends have been considered. Macroscopic and microscopic characteristics of spray such as tip penetration length, cone angle, projected area, volume, Sauter Mean Diameter (SMD), and Ohnesorge number are investigated precisely. Besides, air entrainment and atomization analyses have been carried out to improve mixture formation process. Using curve fitting and least squares method, theoretical correlations have been suggested in such a way to predict... 

Norouzak oil seeds that are the source of bio-diesel (Norouzak) fuel grow mostly in Gonabad and Kashmar located in Khorasan, north east of Iran. Spray characteristics of Norouzak bio-diesel have been experimentally and theoretically studied in this work. Norouzak fuel is added to the conventional diesel fuel, and mixture formations of several blends have been investigated and compared with each other. Moreover, by varying ambient and injection conditions, behaviors of spray of different blends have been explored. Microscopic and macroscopic properties of spray such as Sauter Mean Diameter (SMD), Ohnesorge number, spray tip penetration, spray cone angle, spray projected area and volume have... 

To increase heat transfer, ferrofluids have been utilized to study the effective parameters of pool boiling. Changes and possible enhancement of pool boiling heat transfer of magnetic fluids is a function of magnetic field and concentration of nanoparticles. To the best knowledge of the authors, no systematic experiments have been conducted to visualize the phenomena during the boiling of ferrofluids with different concentrations. In this study an experimental investigation has been conducted, by designing and fabricating a novel hele-shaw vessel with glass sides, to explore via visualizations some details in the pool boiling of ferrofluids. Boiling patterns of ferrofluids at various... 

Pulsating heat pipes (PHPs) are one of the new devices used for cooling in several applications such as electronic and aerospace systems. Their low cost, effectiveness at various conditions, being equipped for passive energy conversion, and well distribution of temperature compared to conventional heat pipes are among the reasons of their popularity. To investigate the effect of surface tension of the working fluid on the behavior of PHPs, a copper heat pipe is fabricated with inner and outer diameters of 2 mm and 4 mm, respectively. Five different concentrations of cetrimonium bromide (C-Tab) surfactant are dissolved in water and are tested with a filling ratio of 50% (± 1%). A piece of... 

The inflow pattern of liquid into a droplet is studied experimentally using a surface active dye and compared with results of CFD simulations. The results show visual agreement between experiments and simulations. The CFD simulations show also good agreement with the surface tension measured by drop profile analysis tensiometry (PAT). The inflow of the surfactant induces a Marangoni instability caused by the local arrival of the surfactant at the drop surface. The onset of this Marangoni instability observed experimentally has a delay of about 10. s when compared with the simulation results. Different scenarios are discussed, including a boundary layer barrier, a kinetic-controlled... 

In order to safe design and optimize performance of some industrial systems, it's often needed to categorize two-phase flow into different regimes. In each flow regime, flow conditions have similar geometric and hydrodynamic characteristics. Traditionally, flow regime identification was carried out by flow visualization or instrumental indicators. In this research3 kind of neural networks have been used to predict system characteristic and flow regime, and results of them were compared: radial basis function neural networks, self organized and Multilayer perceptrons (supervised) neural networks. The data bank contains experimental pressure signalfor a wide range of operational conditions in... 

This paper is focused on video event recognition based on frame level CNN descriptors. Using transfer learning, the image trained descriptors are applied to the video domain to make event recognition feasible in scenarios with limited computational resources. After fine-tuning of the existing Convolutional Neural Network (CNN) concept score extractors, pre-trained on ImageNet, the output descriptors of the different fully connected layers are employed as frame descriptors. The resulting descriptors are hierarchically post-processed and combined with novel and efficient pooling and normalization methods. As major contributions of this work to the video event recognition, we present a... 

This paper is focused on video event recognition based on frame level convolutional neural network (CNN) descriptors. Using transfer learning, the image trained descriptors are applied to the video domain to make event recognition feasible in scenarios with limited computational resources. After fine-tuning of the existing CNN concept score extractors, pretrained on ImageNet, the output descriptors of the different fully connected layers are employed as frame descriptors. The resulting descriptors are hierarchically postprocessed and combined with novel and efficient pooling and normalization methods. As major contributions of this paper to the video event recognition, we present a... 

This paper is focused on video event recognition based on frame level convolutional neural network (CNN) descriptors. Using transfer learning, the image trained descriptors are applied to the video domain to make event recognition feasible in scenarios with limited computational resources. After fine-tuning of the existing CNN concept score extractors, pretrained on ImageNet, the output descriptors of the different fully connected layers are employed as frame descriptors. The resulting descriptors are hierarchically postprocessed and combined with novel and efficient pooling and normalization methods. As major contributions of this paper to the video event recognition, we present a... 

In this work, a supersonic turbulent flow over a long axisymmetric body was investigated, both experimentally and computationally. The experimental study consisted of a series of wind tunnel tests for the flow over an ogive-cylinder body at a Mach number of 1.6 and at a Reynolds number of 8 × 10 6, at angles of attack between -2 and 6 degrees. It included the surface static pressure and the boundary layer profile measurements. Further, the flow around the model was visualized using a Schlieren technique. All tests were conducted in the trisonic wind tunnel of the Qadr Research Center (QRC). Also, the same flow at zero angle of attack was computationally simulated using a multi-block grid...