حامد فرهادی

Coarse particle motion behavior plays a crucial role in sediment and hydraulic engineering, though its physics is still not fully understood. Disregarding the inherently stochastic nature of the sediment transport leads to various equations for bedload transport which are now being challenged due to their poor results. By applying sensors, like accelerometers and gyroscopes, particle transport physics could be carried out in a more scrutinized approach. In this study, an instrumented synthetic particle ("so-called" the smart particle) was designed and applied (with different densities) in sets of laboratory experiments that covered a hydraulics domain between low transport regime (near- and above-threshold) and higher transport regime (above threshold with a relatively high Reynolds number) conditions. Using the instrumented particle (smart-particle) could bring opportunities to learn more about the physics of the bed particle transport in rivers for different regimes and could bring data in hand for instantaneous particle changes throughout time (hear 0.004 seconds used for data sampling). Therefore, the kinetic energy as a parameter that delivers the behavior of particle energy interaction between the exposed particle and its surroundings (flow and the bed particles) was chosen to be studied. Since the dynamic features of the particle in transport are stochastic, the probability distribution functions, which could describe the particle behavior, were selected (Weibull, Lognormal, Normal, and Gamma distributions). In this case, it was shown that the Weibull distribution best described the particle kinetic energy in lower transport regimes, while for a higher transport regime, the Log-normal distribution worked better. Furthermore, the energy signals of the particle moving throughout the flume for different transport regimes were derived, and it was shown that the average energy gain and loss of the particle decreased exponentially as the particle Reynolds number increased. The presented results here could also be applied in similar hydraulic conditions in eco-hydraulic topics, specifically macro-plastic movement as bedload in river courses and the Aeolian research.

Sediment motion behavior plays an important role in the sediment and hydraulic engineering, though its physics is still not fully understood. Ignoring the stochastic nature of the sediment transport leads to various equations for bedload transport which are now being challenged due to their results. In this study, the non-suspended particle motion (bedload transport) in different hydraulic conditions was assessed by a particle tracking technique called the Particle Tracking Velocimetry (PTV). The results of the PTV were applied to describe the particle behavior throughout the probability distribution functions. Knowing the particle motion behavior would be a guidance to learn more about the parameter/s governing the particle transport in different sediment transport regimes. After calibrating and validating the frames (resulted from the PTV), the instantaneous particle velocity was measured. Different probability distribution functions were assessed with Kolmogorov-Smirnov criterion to find the best function which fits the collected data (i.e. the particle velocity). It was shown that the probability distribution function is Log-Normal for lower particle Reynolds number and on the other hand, in the higher particle Reynolds number, the Normal distribution is best describing the particle velocity. The results of this research also could be applied in similar hydraulic conditions in eco-hydraulic field, specifically macro-plastic movement as bedload in river courses.

Due to the complex nature of carbonate reservoirs, mechanisms behind low salinity water injection (LSWI) in these reservoirs are not well understood compared to sandstone ones. Using a limestone core and crude oil from one of the wells of the Shadegan oil field, a core injection test was performed with a sequence of high salinity-low salinity water. 10-time diluted seawater, as low salinity water, was able to recover 14.5% of initial oil in place (IOIP) following the secondary injection of seawater. In contrast, the tertiary injection of the low salinity bine into artificial pure calcite rock (with petrophysical properties similar to real rock) recovered only 3.4% of IOIP. Using the results of the contact angle test, the improved oil recovery by LSWI is attributed to wettability alteration towards a more water-wet state. However, the amount of wettability alteration in Shadegan oil field limestone (42°) is significantly higher than that of pure calcite rock (16°). Based on the results of zeta potential, the wettability alteration by low salinity water is attributed to the more negative electric charge of the crude oil/brine and rock/brine interfaces. The increasing trend of pH with decreasing the salinity showed that more CO32- adsorption at low salinity reduces the electric charge on the calcite surface. The electric charge of Shadegan oil field limestone, by reducing the salinity of injected water from seawater to 10-time diluted seawater, experienced a greater decrease (7.7 mV) than pure calcite (4.1 mV). XRF results attributed this behaviour to the presence of impurities such as silica, sulphate, and phosphate in the Shadegan oil field limestone.

Given the importance of gold prices in financial markets and the economic effects of price fluctuations, the trend of gold price changes in the national and global economy has attracted the attention of many researchers and economic analysts. Therefore, the main purpose of this study is to predict the trend of the global gold price movement. The purpose of this study was to introduce a combined model of the GARCH-Classic and the GARCH-Copula models and to compare them with the Garch family models in order to predict the global gold price trend in the period 01/04/2002 to 26/06/2018. The forecast horizons are 1, 5, 10, and 22 days. The prediction accuracy of these models has been evaluated and compared using RMSE error criterion. Results showed that in short-run prediction horizons, the normal Capula model with GARCH-t distribution and in long run prediction horizon, Capula- t model with the distribution of GARCH-t performs better than competing models. The hybrid model presented in this study has a high potential for predicting the trend of global gold price movement, so using this model for different sector investors, economic analysts, as well as country macro planners, can have valuable results.

In this study, the potential of Support Vector Machine (SVM (in the prediction of peak outflow due to dam failure was evaluated. Huge volume deposited behind dam may cause a large casualty in case of sudden release of it to downstream. Head and volume of water at the time of failure were considered as inputs to SVM model. To train these models, 70% of 112 gathered data from literature was used as training subset and the rest 30% was used to test the model as test subset, at the same time these two subsets were selected in a way to be statistically similar. After studying four SVM models with different kernel functions, i.e. Linear, Polynomial, Radial Basis Function and Sigmoid, it was found that SVM with Radial Basis Kernel function outperforms other models. Results of the statistical evaluation of the proposed model are satisfying with R2=0.96, RMSE=0.03 for training phase and R2=0.94, RMSE=0.05 for the test phase. A comparison was made between some conventional empirical equations and the proposed model in which results shows proposed SVM model surpasses empirical equations in predicting peak outflow due to embankment dam failure.

Foam injection for the purpose of Enhanced Oil Recovery (EOR) process is one of the approaches of chemical EOR. In this method, in addition to using the surfactant, other chemical additives are used to achieve ultralow IFT which result in mobilizing the residual oil of the primary and secondary recovery stage. Foam generation causes to achieve the mobility ratio of less than 1, and then the foam generation improves volumetric sweep efficiency. In foam flooding, foam stability is one of the determining parameters for increasing oil recovery. Generating the most stable foam is one of the subjects of the recent researches on this kind of EOR process in stand point of selection of type and concentration of chemicals. In this study, effects of salinity, surfactant concentration, and the type and the concentration of co-solvent were investigated on foam stability. Optimized stability was gained in different co-solvents. This optimum was used in flooding process to investigate its effect on oil recovery. Butyric acid and 1-butanol were two used co-solvent. The most stable foam was resulted from the samples which utilized butyric acid as co-solvent. Maximum oil recovery of 44% of OOIP has observed in solution with 1-butanol as co-solvent, which is not displaced by water flooding. Moreover, observing the maximum oil recovery validates the efficacy of this technique.

The aim of this work is to study stability and mobility of modified nanoparticle-stabilized foam. Adding oppositely charged surfactant to the hydrophilic silica nanoparticle leads to variation in the hydrophobicity of nanoparticles. Surfactant’s adsorption on the nanoparticle’s surface is compared with different mixtures by a new criterion which is calculated by measuring conductivity. The adsorption criterion in domain of surfactant concentration has a maximum close to 1 CMC where nanoparticle reaches to maximum hydrophobicity. NPS-stabilized CO2 foam formed with simultaneous injection of CO2 and foam agent dispersion through a glass bead pack at reservoir pressure. Nanoparticle alone is not surface active. By adding appropriate surfactant concentration to nanoparticle dispersion¡ it becomes surface active. The complementary study of both pressure behaviour and morphology of foam using foam’s dynamic characterization apparatus¡ shown in the domain of surfactant concentration¡ apparent viscosity of the foam has a maximum about 6.034 cp which is consistent with the maximum adsorption criterion. Also¡ adding nanoparticle to the solution of surfactant forms more uniform¡ and the smaller foams and the apparent viscosity increase significantly. Increasing at a CO2 injection rate will also increase the size of the bubbles and reduce the apparent viscosity which means an increase in mobility.

cartilage grafts have a fundamental role in reconstructive and aesthetic surgeries. Preservation of these grafts in suitable Medias can provide them for revision surgeries. Previous studies have shown that ethanol is a suitable media to preserve garfts . In this study, we assess the effect of Dexamethasone addition on viability of cartilage grafts and documented this with histopathological studies.
fifteen male New zealand rabbits that were purchased by Pasteur institute,Karaj, Iran, were evaluated in this study from March 2014 to July 2014. Cartilage grafts of rabbit ear with preservation of perichondrium preserved in 70 % Ethanol with and without adding of 10 microgram of dexamethasone stored in 4 c. After 45 and 90 days, these samples evaluated by histopahtological H&E staining and viability of chondrocytes determined by evidence of karyorrhexis and kariolysis in each sample.
viability of chondrocytes in ethanol 70 was 77.29±9.23 and viability in ethanol and dexamethasone media was 89.42±10.71after 45 days (paddition of dexamethasone in preserving medias of cartilage grafts can increase the viability of chondrocytes and viable chondrocytes have a fundamental role in graft stability and make them usable for revision surgeries.