Study on The Effect of Solid Properties on The Hydrodynamics in an Ebullated Bed Reactor

Published data on the hydrodynamics of ebullated- bed reactors (EBRs) used in the H-Oil process are scarce. In the present work, the effect of solid properties (e.g., particle size, and degree of hydrophobicity) on the hydrodynamics and foaminess in a lab-scale cold model of an (EBR) was investigated. 20wt. % MgSO4 solution was utilized as the liquid phase to imitate the hydrodynamic trends in the industrial-scale EBR of the hydro-conversion process. Experimental results depicted that the flow regime of the multiphase system can be readily evaluated by using the pressure drop technique. The turning from the bubbly to the turbulent system is enhanced with diminishing particle size, and decreasing particle hydrophobicity. Moreover, the degree of particle hydrophobicity was inversely proportional to the average gas holdup in the EBR. The reduction in average gas holdup was 7.9 % using hydrophobic particles more than that of the hydrophilic one. In the EBR, it was found that bubble sizes were increased with both gas velocity and the axial location far from the gas distributor while liquid velocity has negative impact on bubble size. The experimental work revealed that hydrophobic particles of smaller size (250 μrm) reduced foaming by 70% using 20 vol. % of solid loading and gas and liquid velocities of 10 and 0.15 cm s-1 respectively. This outcome revealed that the surface of catalyst particles used can be modified to act as foaminess- reducer in fluidized bed hydro conversion reactors.

Intermediate class of warm pseudoscalar inflation

High dissipative regime of warm pseudoscalar inflation model (Kamali in Phys Rev D 100:043520, arXiv:1901.01897 [gr-qc], 2019) with an approximately constant value of dissipation parameter Q is studied. Intermediate solution of the scale-factor related to the accelerated expansion of the Universe which is rolled out by observational data in the context of standard (cold) model of inflation is used. There is a region of free parameters phase-space of the model which is interestingly compatible with recent observational data. It is discussed that the model is also compatible with the swampland criteria in a broad range of parameters phase-space and TCC in a limited area of parameters.

Influence of Gas Density and Plug Diameter on Plume Characteristics by Ladle Stirring

The paper presents new results concerning the influence of the gas density and porous plug diameter on the nature of liquid steel stirring with an inert gas in the ladle. The tests were carried out on a cold model of a 30t ladle using particle image velocimetry (PIV) with a high-speed camera to analyse the plume zone formed during the supply of argon and helium as a stirring gas. The similarity criteria for the investigation of stirring processes in cold model in the past were discussed and compared. The modified Morton number was used in this paper to relate the gas flow rate in the model with real objects. The presented results constitute complete documentation of the influence of the plug diameter and gas density on the size of formed gas bubbles and the velocity of gas bubbles rising in different zones of the plume, plume, and spout geometry, including the expansion angle, spout height, open eye area, and gas hold-up.

Predicting the Effects of Climate Change on Water Temperatures of Roode Elsberg Dam Using Nonparametric Machine Learning Models

A nonparametric machine learning model was used to study the behaviour of the variables of a concrete arch dam: Roode Elsberg dam. The variables used were ambient temperature, water temperatures, and water level. Water temperature was measured using twelve thermometers; six thermometers were on each flank of the dam. The thermometers were placed in pairs on different levels: avg6 (avg6-R and avg6-L) and avg5 (avg5-R and avg5-L) were on level 47.43 m, avg4 (avg4-R and avg4-L) and avg3 (avg3-R and avg3-L) were on level 43.62 m, and avg2 (avg2-R and avg2-L) and avg1 (avg1-R and avg1-L) were on level 26.23 m. Four neural networks and four random forests were cross-validated to determine their best-performing hyperparameters with the water temperature data. Quantile random forest was the best performer at mtry 7 (Number of variables randomly sampled as candidates at each split) and RMSE (Root mean square error) of 0.0015, therefore it was used for making predictions. The predictions were made using two cases of water level: recorded water level and full dam steady-state at Representative Concentration Pathway (RCP) 4.5 (hot and cold model) and RCP 8.5 (hot and cold model). Ambient temperature increased on average by 1.6 °C for the period 2012–2053 when using recorded water level; this led to increases in water temperature of 0.9 °C, 0.8 °C, and 0.4 °C for avg6-R, avg3-R, and avg1-R, respectively, for the period 2012–2053. The same average temperature increase led to average increases of 0.7 °C for avg6-R, 0.6 °C for avg3-R, and 0.3 °C for avg1-R for a full dam steady-state for the period 2012–2053.

Cold Model Study on Melting of Ice Made by KCl Solution in Gas-Water Two-Phase Plume Area

With the increasing of scrap usage in steelmaking processes, the melting of scrap becomes a very important phenomenon that limits the productivity and tap-to-tap time. Ice-water systems have been widely used to study the melting of scrap and alloys. In this study, the melting rate of saturated KCl solution ice spheres in gas-water two-phase plume zone are studied as a function of height of location, gas flowrate, and melt temperature. The results show that the shape of the ice sphere gradually changes firstly from spherical to elliptical, and finally becomes an irregular state. 1) The decreasing of the distance between the ice sphere and the bottom plugs, 2) the increasing of the gas flowrate, 3) the slightly increasing of bath temperature will all benefits the melting rate of ice spheres.

A downscaling cold model for solid flow behaviour in a top gas recycling-oxygen blast furnace

The top gas recycling-oxygen blast furnace (TGR-OBF) is a reasonable method used to reduce both coke rate and energy consumption in the steel industry. An important feature of this process is shaft gas injection. This article presents an experimental study on the gas–solid flow characteristics in a TGR-OBF using a two-dimensional cold model. The experimental conditions and parameters were determined using a series of similarity criteria. The results showed that the whole flow area in the TGR-OBF can be divided into four distinct flow zones, namely, the stagnant zone, the plug flow zone in the upper part of the shaft, the converging flow zone and the quasi-stagnant flow zone, which is similar to that in a traditional blast furnace. Then the effects of batch weight and the ratio (X) of the shaft injected gas flow rate to the total gas flow rate on solid flow behaviour were investigated in detail. With the increase in batch weight, the shape of the stagnant zone tends to be shorter and thicker. Furthermore, with the increase in X value from 0 to 1, the stagnant zone gradually becomes thinner and higher. The results obtained from the experiments provide fundamental data and a validation for the discrete element method–computational fluid dynamics-coupled mathematical model for TGR-OBFs for future studies.