Hydrodynamics and Lateral Gas Dispersion in a High-Density Circulating Fluidized Bed Reactor with Bluff Internals

Effect of bluff internals on the hydrodynamics and lateral gas mixing was studied in a 0.186m ID high-density riser. With the bluff internals, the extremely non-uniform radial profiles of solid fraction and particle velocity become flat and the dense downflow layer near the wall disappears, indicating the significant enhancement of solid turbulence introduced by the internals. The fluctuation velocity and solid fraction transient signal analysis indicates a significant increase in fluctuation intensity near the wall region. The length influenced by the internals on the flow structure is about 1 meter. The lateral gas dispersion coefficient increases significantly as the bluff internals exist in the riser.

Damage mechanism of soil-rock mixture after freeze-thaw cycles

As a widely distributed geological and engineering material,the soil-rock mixture always undergoes frequentative and short-term freeze-thaw cycles in some regions.Its internal structure is destroyed seriously,but the damage mechanism is not clear.Based on the damage factor,the damage research of properties of soil-rock mixture after different times of freeze-thaw cycles is investigated.Firstly,the size-distributed subgrade gravelly soil samples are prepared and undergo different times of freeze-thaw cycles periodically(0,3,6,10),and indoor large-scale triaxial tests are completed.Secondly,the degradation degree of elastic modulus is considered as a damage factor,and applied to macro damage analysis of soil-rock mixture.Finally,the mesoscopic simulation of the experiments is achieved by PFC3D,and the influence on strength between soil-rock particles caused by freeze-thaw cycles is analyzed.The results show that freeze-thaw cycles cause internal damage of samples by weakening the strength between mesoscopic soil-rock particles,and ultimately affect the macro properties.After freeze-thaw cycles,on the macro-scale,elastic modulus and shear strength of soil-rock mixture both decrease,and the decreasing degree is related to the times of cycles with the mathmatical quadratic form;on the meso-scale,freeze-thaw cycles mainly cause the degradation of the strength between soil-rock particles whose properties are different significantly.

Theoretical analysis of fluid mixing time in liquid-continuous impinging streams reactor

The mixing time of impact zone in liquid-continuous impinging streams reactor(LISR) is theoretically calculated by empirical model and modern micromixing model of the fluid mixing process, and the variation laws of macromixing time and micromixing time are quantitatively discussed. The results show that under a continuous and stable operating condition, as the paddle speed increases, the macromixing time and micromixing time calculated by the two models both decrease, even in a linkage equilibrium state. Simultaneously, as the paddle speed increases, the results figured by the two models tend to be consistent. It indicates that two models both are more suitable for calculation of mixing time in high paddle speed. Compared with the existing experimental results of this type of reactor, the mixing time computed in the speed of 1500 r/min is closer to it. These conclusions can provide an important reference for systematically studying the strengthening mechanism of LISR under continuous mixing conditions.

Preparation and Characterization of a Perovskite-type Mixed Conducting SrFe0.6Cu0.3Ti0.1O3-δ Membrane for Partial Oxidation of Methane to Syngas

Dense membrane with the composition of SrFe0.6Cu0.3Ti0.1O3-δ （SFCTO） was prepared by solid state reaction method. Oxygen permeation flux through this membrane was investigated at operating temperature ranging from 750℃ to 950℃ and different oxygen partial pressure. XRD measurements indicated that the compound was able to form single-phased perovskite structure in which part of Fe was replaced by Cu and Ti. The oxygen desorption and the reducibility of SFCTO powder were characterized by thermogravimetric analysis and temperature programmed reduction analysis, respectively. It was found that SFCTO had good structure stability under low oxygen pressure at high temperature. The addition of Ti increased the reduction temperature of Cu and Fe. Performance tests showed that the oxygen permeation flux through a 1.5 mm thick SFCTO membrane was 0.35-0.96 ml·min ^-1·cm^-2 under air/helium oxygen partial pressure gradient with activation energy of 53.2 kJ·mol^-1. The methane conversion of 85%, CO selectivity of 90% and comparatively higher oxygen permeation flux of 5 ml·min^-1·cm^- 2 were achieved at 850℃, when a SFCTO membrane reactor loaded with Ni-Ce/Al2O3 catalyst was applied for the partial oxidation of methane to syngas.

A Mathematical Model for Diffusion-Controlled Monolithic Matrix Coated with outer Membrane System

A release model for diffusion-controlled monolithic matrix coated with outer membrane system is proposed and solved by using the refined double integral method. The calculated results are in satisfactory agreement with the experimental release data. The present model can be well used to describe the release process for all cd/cs values. In addition, the release effects of the monolithic matrix coated with outer membrane system are discussed theoretically.

A risk-based methodology for the optimal placement of hazardous gas detectors

Hazardous gas detection systems play an important role in preventing catastrophic gas-related accidents in process industries. Even though effective detection technology currently exists for hazardous gas releases and a majority of process installations have a large number of sensitive detectors in place, the actual operating performance of gas detection systems still does not meet the expected requirements. In this paper, a riskbased methodology is proposed to optimize the placement of hazardous gas detectors. The methodology includes three main steps, namely, the establishment of representative leak scenarios, computational fluid dynamics(CFD)-based gas dispersion modeling, and the establishment of an optimized solution. Based on the combination of gas leak probability and joint distribution probability of wind velocity and wind direction, a quantitative filtering approach is presented to select representative leak scenarios from all potential scenarios. The commercial code ANSYS-FLUENT is used to estimate the consequence of hazardous gas dispersions under various leak and environmental conditions. A stochastic mixed-integer linear programming formulation with the objective of minimizing the total leak risk across all representative leak scenarios is proposed, and the greedy dropping heuristic algorithm(GDHA) is used to solve the optimization model. Finally, a practical application of the methodology is performed to validate its effectiveness for the optimal design of a gas detector system in a high-sulfur natural gas purification plant in Chongqing, China. The results show that an appropriate number of gas detectors with optimal cost-effectiveness can be obtained, and the total leak risk across all potential scenarios can be substantially reduced. This methodology provides an effective approach to guide the optimal placement of pointtype gas detection systems involved with either single or mixed gas releases.

Mechanical properties of bimrocks with high rock block proportion

For the investigation of mechanical properties of the bimrocks with high rock block proportion,a series of laboratory experiments,including resonance frequency and uniaxial compressive tests,are conducted on the 64 fabricated bimrocks specimens.The results demonstrate that dynamic elastic modulus is strongly correlated with the uniaxial compressive strength,elastic modulus and block proportions of the bimrocks.In addition,the density of the bimrocks has a good correlation with the mechanical properties of cases with varying block proportions.Thus,three crucial indices(including matrix strength)are used as basic input parameters for the prediction of the mechanical properties of the bimrocks.Other than adopting the traditional simple regression and multi-regression analyses,a new prediction model based on the optimized general regression neural network(GRNN)algorithm is proposed.Note that,the performance of the multi-regression prediction model is better than that of the simple regression model,owing to the consideration of various influencing factors.However,the comparison between model predictions indicates that the optimized GRNN model performs better than the multi-regression model does.Model validation and verification based on fabricated data and experimental data from the literature are performed to verify the predictability and applicability of the proposed optimized GRNN model.

Modeling p VT Properties and Vapor-Liquid Equilibrium of Ionic Liquids Using Cubic-plus-association Equation of State

Combining Peng-Robinson （PR） equation of state （EoS） with an association model derived from shield-sticky method （SSM） by Liu et al., a new cubic-plus-association （CPA） EoS is proposed to describe the ther-modynamic properties of pure ionic liquids （ILs） and their mixtures. The new molecular parameters for 25 ILs are obtained by fitting the experimental density data over a wide temperature and pressure range, and the overall aver-age deviation is 0.22%. The model parameter b for homologous ILs shows a good linear relationship with their mo-lecular mass, so the number of model parameters is reduced effectively. Using one temperature-independent binary adjustable parameter kij, satisfactory correlations of vapor-liquid equilibria （VLE） for binary mixtures of ILs ＋ non-associating solvents and ＋ associating solvents are obtained with the overall average deviation of vapor pressure 2.91% and 7.01%, respectively. In addition, VLE results for ILs ＋ non-associating mixtures from CPA, lattice-fluid （LF） and square-well chain fluids with variable range （SWCF-VR） EoSs are compared.

Moving object detection method based on complementary multi resolution background models

A novel moving object detection method was proposed in order to adapt the difficulties caused by intermittent object motion,thermal and dynamic background sequences.Two groups of complementary Gaussian mixture models were used.The ghost and real static object could be classified by comparing the similarity of the edge images further.In each group,the multi resolution Gaussian mixture models were used and dual thresholds were applied in every resolution in order to get a complete object mask without much noise.The computational color model was also used to depress illustration variations and light shadows.The proposed method was verified by the public test sequences provided by the IEEE Change Detection Workshop and compared with three state-of-the-art methods.Experimental results demonstrate that the proposed method is better than others for all of the evaluation parameters in intermittent object motion sequences.Four and two in the seven evaluation parameters are better than the others in thermal and dynamic background sequences,respectively.The proposed method shows a relatively good performance,especially for the intermittent object motion sequences.

A Surface Tension Model for Liquid Mixtures Based on NRTL Equation

A new equation for predicting surface tension is proposed based on the thermodynamic definition of surface tension and the expression of the Gibbs free energy of the system. Using the NRTL equation to represent the excess Gibbs free energy, a two-parameter surface tension equation is derived. The feasibility of the new equation has been tested in terms of 124 binary and 16 multicomponent systems(13-ternary and 3-quaternary) with absolute relative deviations of 0.59% and 1.55% respectively. This model is also predictive for the temperature dependence of surface tension of liquid mixtures. It is shown that, with good accuracy, this equation is simple and reliable for practical use.

An efficient approach for shadow detection based on Gaussian mixture model

An efficient approach was proposed for discriminating shadows from moving objects. In the background subtraction stage, moving objects were extracted. Then, the initial classification for moving shadow pixels and foreground object pixels was performed by using color invariant features. In the shadow model learning stage, instead of a single Gaussian distribution, it was assumed that the density function computed on the values of chromaticity difference or bright difference, can be modeled as a mixture of Gaussian consisting of two density functions. Meanwhile, the Gaussian parameter estimation was performed by using EM algorithm. The estimates were used to obtain shadow mask according to two constraints. Finally, experiments were carried out. The visual experiment results confirm the effectiveness of proposed method. Quantitative results in terms of the shadow detection rate and the shadow discrimination rate(the maximum values are 85.79% and 97.56%, respectively) show that the proposed approach achieves a satisfying result with post-processing step.

Modeling of U-shaped Ba0.5Sr0.5Co0.8Fe0.2O3-δhollow-fiber membrane for oxygen permeation

A mathematic model is developed for the perovskite-type mixed ionic-electronic conducting(MIEC) membrane,which makes it possible to simulate the process of oxygen separation in the U-shaped Ba_(0.5)Sr_(0.5)Co_(0.8)Fe_(0.2)O_3-δhollow-fiber membrane. The model correlates the oxygen permeation flux to the measurable variables. The trends of calculated results for purge operation coincide well with the experimental data, therefore the model is considerable for flux prediction under vacuum operation. Higher oxygen separation efficiency can be achieved with vacuum operation than purge operation. Parameter study with vacuum operation reveals that oxygen permeation flux increases with higher vacuum levels, and vacuum pressure of around 1.013 × 10~3 Pa is the optimal.Also, vacuum operation on the lumen side is much more efficient to achieve higher oxygen permeation flux compared with compression mode on the shell side.

Effects of Atomic Mixing in Inertial Confinement Fusion by Multifluid Interpenetration Mix Model

The effects of atomic-level rnixing are systemically investigated in a multifluid interpenetration mix model ,and results are compared with the single-fluid model＇s simulations and experimental data. It is shown that increasing the model free parameter α, shock Mach number, and the initial density discontinuity makes the mix length and fraction of mixing particle increase, resulting in the lower shock temperatures compared with the results of single-fluid model without mixing. Recent high-compressibility direct-drive spherical implosions on OMEGA are simulated by the interpenetration mix modal. The calculations with atomic mixing between fuel and shell match quite well with the observations. Without considering any mixing, the calculated neutron yields and ion temperatures are overpredicted; while inclusion of the interpenetration mix model with the adjustable parameter α could fit the simulated neutron yields and ion temperatures well with experimental data.

Process Flow Model of Combined High Temperature Fuel Cell Operated with Mixture of Methane and Hydrogen

One of the main challenges of biogas and syngas use as fuel in hybrid solid oxide fuel cell （SOFC） cycles is the variable nature of their composition, which may cause significant changes in plant performance. On the other hand, hydrogen is one of the main components in some types of gasified biomass and syngas. Therefore, it is vital to investigate the influences of hydrogen fraction in inlet fuel on the cycle performance. In this work, a steady-state simulation of a hybrid tubular SOFC-gas turbine （GT） cycle is first presented with two configurations： system with and without anode exhaust recirculation. Then, the results of the model when fueled by syngas, biofuel, and gasified biomass are analyzed, and significant dependency of system operational parameters on the inlet fuel composition are investigated. The analysis of impacts of hydrogen concentration in the inlet fuel on the performance of a hybrid tubular SOFC and gas turbine cycle was carried out. The simulation results were considered when the system was fueled by pure methane as a reference case. Then, the performance of the hybrid SOFC-GT system when methane was partially replaced by H2 from a concentration of 0% to 95% with an increment of 5% at each step was investigated. The system performance was monitored by investigating parameters like temperature and flow rate of streams in different locations of the cycle; SOFC and system thermal efficiency; SOFC, GT, and cycle net and specific work; air to fuel ratio; as well as air and fuel mass flow rate. The results of the sensitivity analysis demonstrate that hydrogen concentration has significant effects on the system operational parameters, such as efficiency and specific work.

The melilite-type compound (Sr_(1-x),A_x)_2MnGe_2S_6O(A=K,La) being a room temperature ferromagnetic semiconductor

The seeking of room temperature ferromagnetic semiconductors, which take advantages of both the charge and spin degrees of freedom of electrons to realize a variety of functionalities in devices integrated with electronic, optical, and magnetic storage properties, has been a long-term goal of scientists and engi- neers. Here, by using the spin-polarized density functional theory calculations, we predict a new series of high temperature ferromagnetic semiconductors based on the melilite-type oxysulfide Sr2MnGe2S60 through hole （K） and electron （La） doping. Due to the lack of strong antiferromagnetic superexchange between Mn ions, the weak antiferromagnetic order in the parent compound Sr2MnGe2S60 can be sup- pressed easily by charge doping with either p-type magnetic order. At a doping concentration of or n-type carriers, giving rise to the expected ferro- 25%, both the hole-doped and electron-doped compounds can achieve a Curie temperature （To） above 300 K. The underlying mechanism is analyzed. Our study provides an effective approach for exploring new types of high temperature ferromagnetic semiconductors.

General moving objects recognition method based on graph embedding dimension reduction algorithm

Effective and robust recognition and tracking of objects are the key problems in visual surveillance systems. Most existing object recognition methods were designed with particular objects in mind. This study presents a general moving objects recognition method using global features of targets. Targets are extracted with an adaptive Gaussian mixture model and their silhouette images are captured and unified. A new objects silhouette database is built to provide abundant samples to train the subspace feature. This database is more convincing than the previous ones. A more effective dimension reduction method based on graph embedding is used to obtain the projection eigenvector. In our experiments, we show the effective performance of our method in addressing the moving objects recognition problem and its superiority compared with the previous methods.

INEQUALITIES FOR MIXED INTERSECTION BODIES

In this paper, some properties of mixed intersection bodies are given, and inequalities from the dual Brunn-Minkowski theory (such as the dual Minkowski inequality, the dual Aleksandrov-Fenchel inequalities and the. dual Brunn-Minkowski inequalities) are established for mixed intersection bodies.

Numerical Simulation and Experiment Analyses for the Gas-liquid Two-phase Vortex Pump

Based on the gas-liquid two-phase mixture transportation test, the k-c-A; turbulence model was applied to simulate the two-phase turbulent flow in a vortex pump. By comparing the simulation and experiment results, inner flow features were revealed. The bubbles in the channel distribute mainly at the pressure side of the blades, and the aggregation degree of the bubbles is enhanced with an increase in inlet gas volume fraction. Experimental results indicate that the influence of the gas phase on vortex pump performance is small when the gas volume fraction is less than 10%. When the gas volume fraction contiuuously increases to 15%, the characteristic curves abruptly drop due to the gas blocking phenomenon.

Geometric effects of fuel regression rate in hybrid rocket motors

The geometric configuration of the solid fuel is a key parameter affecting the fuel regression rate in hybrid rocket motors. In this paper, a semi-empirical regression rate model is developed to investigate the geometric effect on the fuel regression rate by incorporating the hydraulic diameter into the classical model. The semi-empirical model indicates that the fuel regression rate decreases with increasing hydraulic diameter and is proportional to dh?0.2 when convective heat transfer is dominant. Then a numerical model considering turbulence, combustion, solid fuel pyrolysis, and a solid–gas coupling model is established to further investigate the geometric effect. Eight motors with different solid fuel grains are simulated, and four methods of scaling the regression rate between different solid fuel grains are compared. The results indicate that the solid fuel regression rates are approximate the same when the hydraulic diameters are equal. The numerical results verify the accuracy of the semi-empirical model.