Combining Monte Carlo and finite difference methods for effective simulation of dam behavior

Monte Carlo simulation provides a probabilistic approach to evaluate the physical behavior of infrastructures. Therefore, the performance could be achieved in a more realistic manner. Within this framework, an innovative software code is developed by combining the Monte Carlo and finite difference methods to predict the behavior of embankment dams after impounding. In order to assess the efficiency of the method, the case study of Chahnimeh-4 dam, located at Southeast of Iran, has been investigated in detail. The behavior of this dam is predicted and compared with the field monitoring by using the Kolmogorov-Smirnov test. The results indicate the robustness of the proposed method and it can be then efficiently used in monitoring the dam responses with respect to the various factors like seepage, piping and settlement.     

Predicting Transition Velocities from Bubbling to Turbulent Fluidization by S-Statistics on Vibration Signals

Vibration signatures as the representatives of the fluidized bed nonlinear hydrodynamics were measured in a lab-scale fluidized bed of sand particles operated at ambient conditions. The experiments were carried out for three particle sizes, different velocities, and three probe heights. The S-statistic method was applied to the vibration signatures for the chaotic attractor comparison. The measured signatures of two different consecutive velocities in similar conditions were compared based on null hypothesis that they have same origin. According to this method, when the value of S is larger than 3, the null hypothesis is rejected with the confidence level of 95% indicating that the two signals are originated from different hydrodynamics. The results are compared with results obtained from common statistical methods and it is shown that attractor comparison can be a reliable method for detecting regime transition velocity.     

Effect of green GO/Au nanocomposite on in‐vitro amplification of human DNA

Recently nanomaterials have attracted interest for increasing efficiency of polymerase chain reaction (PCR) systems. Here, the authors report on the usefulness of green graphene oxide/gold (GO/Au) nanocomposites for enhancement of PCR reactions. In this study, green GO/Au nanocomposite was prepared with Matricaria chamomilla extract as reducing/capping agent for site‐directed nucleation of Au^o atoms on surface of GO sheets. The as‐prepared green GO/Au nanocomposites were then characterised with UV–VIS spectrophotometer and scanning electron microscopy. Later, the effect of these nanocomposites was studied on end‐point and real‐time PCR employed for amplification of human glyceraldehyde‐3‐phosphate dehydrogenase gene. The results indicated that GO/Au nanocomposite can improve both end‐point and real‐time PCR methods at the optimum concentrations, possibly through interaction between GO/Au nanocomposite and the materials in PCR reaction, and through providing increased thermal convection by the GO surface as well as the Au nanostructures. In conclusion, it can be suggested that green GO/Au nanocomposite is a biocompatible and eco‐friendly candidate as enhancer of in‐vitro molecular amplification strategies.Inspec keywords: graphene, molecular biophysics, nucleation, enzymes, gold, nanofabrication, nanocomposites, scanning electron microscopy, nanoparticles, DNA, nanomedicine, ultraviolet spectra, visible spectra, graphene compoundsOther keywords: green GO/Au nanocomposite, polymerase chain reaction systems, green graphene oxide/gold, PCR reaction, as‐prepared green GO/Au nanocomposites, real‐time PCR methods, Au nanostructures, in‐vitro amplification, human DNA, Matricaria chamomilla extract, site‐directed nucleation, Au, CO, CO‐Au     

Dominant Flow Structures in Gas–Solid Fluidized Beds Using Time and Frequency Domains Analyses

Time series analysis techniques in time domain and average cycle frequency were applied to characterize bubbling fluidization. The experiments were carried out in a laboratory scale fluidized bed, operated under ambient conditions and various sizes of particles, measurement heights, and different superficial gas velocities. It was found that a minimum in average cycle frequency and flatness and a shift of skewness from negative to positive against velocity correspond to shift from macrostructures and finer structures of the flow rather than transition velocity from the bubbling to turbulent regime. The power spectrum estimation of the measured pressure fluctuations shows that the peak dominant frequency of the pressure fluctuations is about 1.5–2.5 Hz which is corresponding to the macrostructures of the bed. Accordingly, the onset of turbulent fluidization regime was detected through standard deviation analysis. It was shown that the simple analysis techniques still have interesting information about hydrodynamics of fluidization and they can accurately estimate transition between dominant flow structures of a gas–solid fluidized bed.     

Effect of Fe-rich intermetallics on the wear behavior of eutectic Al–Si piston alloy (LM13)

In the present study, the effect of Fe-rich intermetallics has been investigated on the wear behavior of eutectic Al–Si alloy (LM13). Dry sliding wear tests have been conducted using a pin-on-disk machine under different normal loads of 18, 51, 74 and 100 N at a constant sliding speed of 0.3 m/s. Addition of 1.2% Fe to the LM13 alloy leads to the formation of the flake like β-intermetallic compounds. These hard compounds initiate micro cracks and can reduce the wear resistance of the alloy. The addition of Mn converts the flake like β-intermetallic compounds to the star-like α-intermetallics and decreases the detrimental effect of iron. Applying high cooling rate during solidification of the alloy containing Fe and Mn, resulted to the formation of finer α-intermetallic compounds and improved the wear behavior of the alloy to a great extent.     

Analysis and modeling of particle-wall contact time in gas fluidized beds

Although extensive studies have been conducted on convective heat transfer from a heat exchanger surface to a gas fluidized bed, the contribution through particle convection has not been adequately described, especially in turbulent fluidized beds. In this study, the role that dense bed hydrodynamics play on particle convection has been outlined. The existing models in the literature suggest a constant decrease of particle-wall contact time with an increase in the gas velocity. It has been experimentally demonstrated, however, that the contact time increases, both in bubbling and turbulent regimes, upon increasing the gas velocity. A comprehensive model has been developed to represent such a trend and improve agreement with experimental data presented in literature. The proposed model includes two constants for taking into account the wall effect on bubbles and clusters. The constants of the model have been evaluated based on the radial profiles of the distribution of bubbles and clusters using a radioactive particle tracking technique. A comparison of the predicted results with the experimental data from the literature confirms the validity of the present model for the dense bed region of a fluidized bed of sand particles.     

Monitoring the Moisture Content of Solids in Fluidized Bed Dryers by Analysis of Pressure Fluctuations

Perusing the hydrodynamic changes of fluidized bed dryer is important for online monitoring of the drying process. The present study investigates the drying process of wetted rice particles. Air at ambient conditions with superficial velocity of 1 ms^?1 was used for drying. Absolute pressure fluctuations were measured to monitor the fluidization status of the dryer. Fast Fourier transform, discrete wavelet transform, and statistical analyses of detailed signals were employed to evaluate the fluidization quality in the bubbling regime. Pressure fluctuations were decomposed by the wavelet transform to 10 subsignals. It was shown that the energy of subsignals is more sensitive to moisture changes than other studied parameters. Specifically, the energy of the subsignals corresponding to the macrostructure (large bubbles) can be used for determining the moisture content of the solids during the drying process. This method can be used for online monitoring of drying processes in a wide range of processing conditions in fluidized beds.