Numerical modeling of destress blasting for strata separation

Destress blasting(DB)implemented along the perimeter of safety pillars is a special application of destressing in coal longwall mining.The goal is to separate relatively more deformed mined areas from safety pillars,such as shaft pillars or cross-cut pillars,to reduce the transfer of high stresses to the protective pillar.This case study aims to numerically simulate selected destress blasts in the Czech part of the Upper Silesian Coal Basin and examine its impact on stress transfer to the safety pillar area.To separate the area between the protective pillar and the longwall(LW),two fans of five 93-mm blast holes(length of 93e100 m)were drilled from the gate roads into the overburden strata.Each set of blast holes was fired separately in two stages without time delay.The explosive charge(gelatin-type of explosive)of each stage is 3450 kg.The two DB stages were fired when the longwall face was approximately 158 m and 152 m away from the blast.A 3D mine-wide model is built and validated with in situ stress measured with hydrofracturing.Mining and destressing in three 5-m thick coal seams are simulated in the region.Numerical modeling of DB is successfully conducted using a rock fragmentation factor a of 0.05 and a stress reduction/dissipation factor β of 0.95.Buffering of transfer of additional stress from the mining area into the safety pillar is evaluated by comparison of yielding volume before and after DB.It is shown that yielding volume drops after DB by nearly 80%in the area of the destressing panel and near the safety shaft pillar.

Particulate flow modelling in a spiral separator by using the Eulerian multi-fluid VOF approach

The Euler-Euler model is less effective in capturing the free surface of flow film in the spiral separator,and thus a Eulerian multi-fluid volume of fluid(VOF)model was first proposed to describe the particulate flow in spiral separators.In order to improve the applicability of the model in the high solid concentration system,the Bagnold effect was incorporated into the modelling framework.The capability of the proposed model in terms of predicting the flow film shape in a LD9 spiral separator was evaluated via comparison with measured flow film thicknesses reported in literature.Results showed that sharp air–water and air-pulp interfaces can be obtained using the proposed model,and the shapes of the predicted flow films before and after particle addition were reasonably consistent with the observations reported in literature.Furthermore,the experimental and numerical simulation of the separation of quartz and hematite were performed in a laboratory-scale spiral separator.When the Bagnold lift force model was considered,predictions of the grade of iron and solid concentration by mass for different trough lengths were more consistent with experimental data.In the initial development stage,the quartz particles at the bottom of the flow layer were more possible to be lifted due to the Bagnold force.Thus,a better predicted vertical stratification between quartz and hematite particles was obtained,which provided favorable conditions for subsequent radial segregation.

A velocity-difference-separation model for car-following theory

We introduce a velocity-difference-separation model that modifies the previous models in the literature. The improvement of this new model over the previous ones lies in that it not only theoretically retains many strong points of the previous ones, but also performs more realistically than others in the dynamical evolution of congestion. Furthermore, the proposed model is investigated with analytic and numerical methods, with the finding that it can demonstrate some complex physical features observed in real traffic such as the existence of three phases： free flow, synchronized flow, and wide moving jam; sudden flow drop in flow-density plane; and traffic hysteresis in transition between the free and the synchronized flow.

Study on the separation process of non-metallic inclusions at the steel-slag interface using water modeling

The separation process of non-metallic inclusions at the steel–slag interface was simulated by physical modeling. Three different kinds of particles(octahedral, plate-like, and spherical) and three different oils(kerosene, bean oil, and pump oil) were used to model inclusions and slags, respectively. The effects of inclusion geometry(shape and size) and slag properties(viscosity and interfacial tension) on the separation process were investigated. The results revealed that the variation of surface free energy and the viscosity of the slag are two significant factors affecting the separation process of inclusions at the steel–slag interface. The variation of surface free energy helped inclusions enter the slag phase, whereas the decrease of slag viscosity shortened the separation time. The deformation of the steel–slag interface could give rise to the resistance force, which would resist inclusions passing through the interface. A liquid film formed on the inclusion as it passed through the steel–slag interface, which might be related to the inclusion's shape.

A Variable Separation Approach to Solve the Integrable and Nonintegrable Models:Coherent Structures of the (2 + 1)-Dimensional KdV Eqnation

We study the localized coherent structures ofa generally nonintegrable (2+ 1 )-dimensional KdV equation via a variable separation approach. In a special integrable case, the entrance of some arbitrary functions leads to abundant coherent structures. However, in the general nonintegrable case, an additional condition has to be introduced for these arbitrary functions. Although the additional condition has been introduced into the solutions of the nonintegrable KdV equation, there still exist many interesting solitary wave structures. Especially, the nonintegrable KdV equation possesses the breather-like localized excitations, and the similar static ring soliton solutions as in the integrable case. Furthermor,in the integrable case, the interaction between two travelling ring solitons is elastic, while in the nonintegrable case we cannot find even the single travelling ring soliton solution.

Development of separation sharpness model for hydrocyclone

Hydrocyclones are mechanical devices used in classifying and separating many different types of materials.A classification function of the hydrocyclone has been continually developed for solid–liquid separation.In the classification process of solids from liquids,it is desirable to reduce the amount of misplaced material;therefore,the separation sharpness,α(alpha),is a parameter that helps in evaluating misplaced material and has been developed as a model to help the designer predict the performance of the classification.However,the problem with the separation sharpness model is that it cannot be used outside the range of conditions under which it was developed.Therefore,this research aimed to develop the separation sharpness model to predict more accurately and cover a wide range of conditions using the multiple linear regression method.The new regression model of separation sharpness was based on a wide range of both experimental and industrial data-sets of 431 tests collaborating with the additional experiments of 117 tests that were obtained from a total of 548 tests.The new model of separation sharpness can be used in the range of 30–762 mm hydrocyclone body diameters and feed solid concentrations in the range of 0.5 wt%–80 wt%.When compared with the experimental separation sharpness,the accuracy of the separation sharpness model prediction has an error of 4.53%and^of 0.973.

Testing the robustness of particle-based separation models for the magnetic separation of a complex skarn ore

Physical separation processes are best understood in terms of the behaviour of individual ore particles.Yet,while different empirical particle-based separation modelling approaches have been developed,their predictive performance has never been tested under variable process conditions.Here,we investigated the predictive performance of a state-of-the-art particle-based separation model under variable feed composition for a laboratory-scale magnetic separation of a skarn ore.Two scenarios were investigated:one in which the mass flow of the different processing streams could be measured and one in which it had to be estimated from data.In both scenarios,the predictive models were sufficiently general to predict the process outcomes of new samples of variable composition.Nevertheless,the scenario in which mass flow could be measured was4%more precise in predicting mass balances.The process behaviour of minerals present at concentrations above 0.1%by weight could be accurately predicted.Our findings indicate the potential use of this method to minimize the costs of metallurgical testwork while providing in-depth understanding of the recovery behaviour of individual ore particles.Moreover,the method may be used to establish powerful tools to forecast mineral recoveries for partly new ore types at a running mining operation.

Optimization of CO_2 separation technologies for Chinese refineries based on a fuzzy comprehensive evaluation model

This study aims at determining the optimal CO2 separation technology for Chinese refineries, based on current available technologies, by the method of comprehensive evaluation. Firstly, according to the characteristics of flue gas from Chinese refineries, three feasible CO2 separation technologies are selected. These are pressure swing adsorption （PSA）, chemical absorption （CA）, and membrane absorption （MA）. Secondly, an economic assessment of these three techniques is carried out in accordance with cash flow analysis. The results show that these three techniques all have economic feasibility and the PSA technique is the best. Finally, to further optimize the three techniques, a two-level fuzzy comprehensive evaluation model is established, including economic, technological, and environmental factors. Considering all the factors, PSA is optimal for Chinese refineries, followed by CA and MA. Therefore, to reduce Chinese refineries carbon emission, it is suggested that CO2 should be captured from off-gases using PSA.

Blind source separation of ship-radiated noise based on generalized Gaussian model

When the distribution of the sources cannot be estimated accurately, the ICA algorithms failed to separate the mixtures blindly. The generalized Gaussian model （GGM） is presented in ICA algorithm since it can model non- Ganssian statistical structure of different source signals easily. By inferring only one parameter, a wide class of statistical distributions can be characterized. By using maximum likelihood （ML） approach and natural gradient descent, the learning rules of blind source separation （BSS） based on GGM are presented. The experiment of the ship-radiated noise demonstrates that the GGM can model the distributions of the ship-radiated noise and sea noise efficiently, and the learning rules based on GGM gives more successful separation results after comparing it with several conventional methods such as high order cumnlants and Gaussian mixture density function.

Evaluation of a mathematical model using experimental data and artificial neural network for prediction of gas separation

In recent times, membranes have found wide applications in gas separation processes. As most of the industrial membrane separation units use hollow fiber modules, having a proper model for simulating this type of membrane module is very useful in achieving guidelines for design and characterization of membrane separation units. In this study, a model based on Coker, Freeman, and Fleming＇s study was used for estimating the required membrane area. This model could simulate a multicomponent gas mixture separation by solving the governing differential mass balance equations with numerical methods. Results of the model were validated using some binary and multicomponent experimental data from the literature. Also, the artificial neural network （ANN） technique was applied to predict membrane gas separation behavior and the results of the ANN simulation were compared with the simulation results of the model and the experimental data. Good consistency between these results shows that ANN method can be successfully used for prediction of the separation behavior after suitable training of the network

A unified Minorization-Maximization approach for estimation of general mixture models

The mixed distribution model is often used to extract information from heteroge-neous data and perform modeling analysis.When the density function of mixed distribution is complicated or the variable dimension is high,it usually brings challenges to the parameter es-timation of the mixed distribution model.The application of MM algorithm can avoid complex expectation calculations,and can also solve the problem of high-dimensional optimization by decomposing the objective function.In this paper,MM algorithm is applied to the parameter estimation problem of mixed distribution model.The method of assembly and decomposition is used to construct the substitute function with separable parameters,which avoids the problems of complex expectation calculations and the inversion of high-dimensional matrices.

Modeling and identification for soft sensor systems based on the separation of multi-dynamic and static characteristics

Data-driven soft sensor is an effective solution to provide rapid and reliable estimations for key quality variables online. The secondary variables affect the primary variable in considerably different speed, and soft sensor systems exhibit multi-dynamic characteristics. Thus, the first contribution is improving the model in the previous study with multi-time-constant. The characteristics-separation-based model will be identified in substep way,and the stochastic Newton recursive(SNR) algorithm is adopted. Considering the dual-rate characteristics of soft sensor systems, the proposed model cannot be identified directly. Thus, two auxiliary models are first proposed to offer the intersample estimations at each update period, based on which the improved algorithm(DAM-SNR) is derived. These two auxiliary models function in switching mechanism which has been illustrated in detail. This algorithm serves for the identification of the proposed model together with the SNR algorithm, and the identification procedure is then presented. Finally, the laboratorial case confirms the effectiveness of the proposed soft sensor model and the algorithms.

Modeling of Pervaporation Separation Benzene from Dilute Aqueous Solutions Through Polydimethylsiloxane Membranes

A modified solution-diffusion model was established based on Flory-Huggins thermodynamic theory and Fujita's free volume theory. This model was used for description of the mass transfer of removal benzene from dilute aqueous solutions through polydimethylsiloxane (PDMS) membranes. The effect of component concentration on the interaction parameter between components, that of the polymer membrane on the selectivity to benzene, and that of feed concentration and temperature on the permeation flux and separation factor of benzene/water through PDMS membranes were investigated. Calculated pervaporation fluxes of benzene and water were compared with the experimental results and were in good agreement with the experimental data.

Blind source separation based on generalized gaussian model

Since in most blind source separation(BSS)algorithms the estimations of probability density function(pdf)of sources are fixed or can only switch between one sup-Gaussian and other sub-Gaussian model,they may not be efficient to separate sources with different distributions.So to solve the problem of pdf mismatch and the separation of hybrid mixture in BSS,the generalized Gaussian model(GGM)is introduced to model the pdf of the sources since it can provide a general structure of univariate distributions.Its great advantage is that only one parameter needs to be determined in modeling the pdf of different sources,so it is less complex than Gaussian mixture model.By using maximum likelihood(ML)approach,the convergence of the proposed algorithm is improved.The computer simulations show that it is more efficient and valid than conventional methods with fixed pdf estimation.

Modeling of Coalescence and Separation of Liquid Droplets During Solidification of Immiscible Alloys

Directional solidification methods are being used f or in-situ production of metallic immiscible composites. A quantitative understa nding of the dynamic behavior and growth kinetics of the nucleated second phase during solidification is necessary to produce homogeneous dispersion in solidifi ed composites. This paper presents a mathematical model for describing the grow th of nucleated dispersed phase in the two-liquid phase region ahead of the sol idification front and the entrapment of these droplets by the moving solid-liqu id interface in vertical unidirectional solidification systems. The model has t wo components. A macro-heat transfer model for describing the temperature prof iles and the rate of advance of the solidification front. The dynamic behavior and coalescence and growth of nucleated droplets in the two-liquid phase region under the influence of effective gravity and thermocapillary forces were repres ented through the solution the droplet momentum and mass conservation equations in particle space. These two components of the models were coupled through a sp ecial algorithm for tracking the particle location and size with respect to movi ng solidification front in the solidification time scale. The model is used to study the particle size distribution in unidirectional solidified Zn-Bi hypermo notectic alloys at reduced gravity conditions. It has been found that the parti cle size and distribution in the solidified alloy depends on solidification rate and the ratio of effective gravity to thermocapillary forces. It was also foun d that uniform dispersion could only be obtained in a very narrow range of effec tive gravity values near zero gravity. The model predictions were compared agai nst experimental measurements obtained at different effective gravity conditions in a novel unidirectional solidification apparatus that uses electromagnetic fo rces to modulate gravitational forces. The model was found to reasonably predic t the experimentally measured particle size and distribution over the entire ran ge of effective gravity investigated as well as gravity conditions for settling and flotation of the second phase during solidification. The practical signific ance of these findings will be discussed.

THE SEPARATION OF LARGE VORTEXES AND THE CLOSED EQUATIONS OF TURBULENCE MODEL

This paper presents a new kind of everage for the loeally-generated large vortexes so that the physieal quantities of the locally-generated large vortexes and the external large vortexes canberigorously separated from the equal ions for the large vortexes proposed in a previous paper[1] To the equations for the two kinds of large vortexes, some auxiliary relations are introduced, and the value, of the length-scale lN of energy dissipation of the external large vortexes may he determined according to the actual circumstances of the disturbance of external sources. Thus the resulting equations of the second moments of turbulent velocity fluctuations for the two kinds of large vortexes can be made closed. Meanwhile, the corresponding coefficients of diffusion in the previous paper[1] are improved,Finally, a closed set of numerically-solvable equations of turbulence model are obtained.

Application of molecular interaction volume model in separation of Sn-Zn alloy by vacuum distillation

The activity of components of Sn-Zn binary alloy system was predicted based on the molecular interaction volume model(MIVM). The calculated values are in good agreement with available experimental data of activities, which indicates that this model is of stability and reliability because the MIVM has a good physical basis. The vapor–liquid phase equilibrium of Sn-Zn alloy system in vacuum distillation was calculated as a function of the activity coefficient. The results show that the content of Sn in vapor phase is 4.2×10-7(mass fraction) while in liquid phase it is 90%(mass fraction) at 1 073 K, and the content of Sn in vapor phase increases with increasing the melt temperature and content of Sn in liquid phase. Vacuum distillation experiments were carried out on Sn-Zn alloy for the proper interpretation of the results of the MIVM in the temperature range of 9731 273 K under pressures of 15 200 Pa. The experimental results show that the content of Sn in vapor phase is 5×10-6(mass fraction) while in liquid phase it is 90%(mass fraction) under the operational condition of 1 073 K, 100 min and 15 Pa. The experimental results are in good agreement with the predicted values of the MIVM for Zn-Sn binary alloy system.

A Dugdale model based geometrical amplifier enables the measurement of separation-to-failure for a cohesive interface

Regardless of all kinds of different formulae used for the traction-separation relationship in cohesive zone modeling,the peak tractionσ_m and the separation-to-failureδ_0(or equivalently the work-to-separationΓ) are the primary parameters which control the interfacial fracture behaviors. Experimentally,it is hard to determine those quantities,especially forδ_0,which occurs in a very localized region with possibly complicated geometries by material failure.Based on the Dugdale model,we show that the separation-to-failure of an interface could be amplified by a factor of L/r_p in a typical peeling test,where L is the beam length and r_p is the cohesive zone size.Such an amplifier makesδ_0 feasible to be probed quantitatively from a simple peeling test. The method proposed here may be of importance to understanding interfacial fractures of layered structures,or in some nanoscale mechanical phenomena such as delamination of thin films and coatings.

Polyurethane-SAPO-34 mixed matrix membrane for CO_2/CH_4 and CO_2/N_2 separation

SAPO-34 nanocrystals(inorganic filler) were incorporated in polyurethane membranes and the permeation properties of CO_2, CH_4,and N_2 gases were explored. In this regard, the synthesized PU-SAPO-34 mixed matrix membranes(MMMs) were characterized via SEM, AFM, TGA, XRD and FTIR analyses. Gas permeation properties of PU-SAPO-34 MMMs with SAPO-34 contents of 5 wt%, 10 wt% and 20 wt% were investigated. The permeation results revealed that the presence of 20 wt% SAPO-34 resulted in 4.45%, 18.24% and 40.2% reductions in permeability of CO_2,CH_4,and N_2, respectively, as compared to the permeability of neat polyurethane membrane. Also,the findings showed that at the pressure of 1.2 MPa, the incorporation of 20 wt% SAPO-34 into the polyurethane membranes enhanced the selectivity of CO_2/CH_4 and CO_2/N_2, 14.43 and 37.46%, respectively. In this research, PU containing 20 wt% SAPO-34 showed the best separation performance. For the first time, polynomial regression(PR) as a simple yet accurate tool yielded a mathematical equation for the prediction of permeabilities with high accuracy(R^2>99%).

A continuous and high-efficiency process to separate coal bed methane with porous ZIF-8 slurry:Experimental study and mathematical modelling

Coal bed methane has been considered as an important energy resource.One major difficulty of purifying coal bed methane comes from the similar physical properties of CH_4 and N_2.The ZIF-8/water-glycol slurry was used as a medium to separate coal bed methane by fluidifying the solid adsorbent material.The sorption equilibrium experiment of binary mixture(CH_4/N_2)and slurry was conducted.The selectivity of CH_4 to N_2 is within the range of 2-6,which proved the feasibility of the slurry separation method.The modified Langmuir equation was used to describe the gas-slurry phase equilibrium behavior,and the calculated results were in good agreement with the experimental data.A continuous absorption-adsorption and desorption process on the separation of CH_4/N_2 in slurry is proposed and its mathematical model is also developed.Sensitivity analysis is conducted to determine the operation conditions and the energy performance of the proposed process was also evaluated.Feed gas contains 30 mol%of methane and the methane concentration in product gas is 95.46 mol%with the methane recovery ratio of 90.74%.The total energy consumption for per unit volume of product gas is determined as 1.846 kWh Nm^(-3).Experimental results and process simulation provide basic data for the design and operation of pilot and industrial plant.