COMPUTER MODEL OF COPPER SMELTING PROCESS AND DISTRIBUTION BEHAVIORS OF ACCESSORY ELEMENTS

A computer model has been developed to simulate the distribution behaviors of Ni, Co. Sn. Ph,Zn, As, Sb, Bi, An and Ag in copper smelting process. The model assumes that the copper smelting furnaceis in thermodynamic equilibrium. As many as 21 elements (Cu. S, Fe. Ni, Co. Sn, As, Sb. Bi, Ph. Zn.An. Ag. O, N, C, H, Ca, Mg, Al, and St) and 73 compounds are considered. This model accounts forphysical entrainment in the melts. The predictions by the present computer model are compared with theknown commercial data from Guixi Smelter in China, Home Smelter in Canada and Naoshima Smelter inJapan. The agreements between the computer predictions and the commercial data are excellent, so that thepresent computer model can be used to monitor and optimize the actual industrial operations of copper smelting. It is applicable to simulation of almost all copper pyrometallurgical processes.

Modeling and Optimization of Copper Flash Smelting Process Based on Neural Network

The copper flash smelting process neural network model(CFSPNNM)was developed,its input layer includes eight nodes:oxygen grade(OG),oxygen volume per ton of concentrate(OVPTC),flux rate(FR)and quantifies of Cu,S,Fe,SiO_2 and MgO in copper concentrate;output layer includes three nodes:matte grade,matte temperature and Fe/SiO_2 in slag,and net structure was 8-13-10-3.Then,the internal relationship between the technological parameters and the objective parameters was built after the CFSPNNM was trained by us...

Extended adsorption transport models for permeation of copper ions through nanocomposite chitosan/polyvinyl alcohol thin affinity membranes

Transport of copper ions through nanocomposite chitosan/polyvinyl alcohol thin adsorptive membranes has been mathematically investigated in the current study. Unsteady-state diffusive transport model was coupled with the Freundlich isotherm to predict the concentration of the ions in dialysis permeation operation. Pristine model was not successful in predicting the experimental data based upon its low coefficients of determination（0.1

Water model experiments of multiphase mixing in the top-blown smelting process of copper concentrate

We constructed a 1：10 cold water experimental model by geometrically scaling down an Isa smelting furnace. The mixing processes at different liquid heights, lance diameters, lance submersion depths, and gas flow rates were subsequently measured using the conductivity method. A new criterion was proposed to determine the mixing time. On this basis, the quasi-equations of the mixing time as a function of different parameters were established. The parameters of the top-blown smelting process were optimized using high-speed photography. An excessively high gas flow rate or excessively low liquid height would enhance the fluctuation and splashing of liquid in the bath, which is unfavorable for material mixing. Simultaneously increasing the lance diameter and the lance submersion depth would promote the mixing in the bath, thereby improving the smelting efficiency.

Numerical modeling of Jinlong CJD burner copper flash smelting furnace

Fluid flow, heat transfer and combustion in Jinlong CJD concentrate burnerflash smelting furnace have been investigated by numerical modeling and flow visualization. Themodeling is based on the Eulerian approach for the gas flow equations and the Lagrangian approachfor the particles. Interaction between the gas phase and particle phase, such as frictional forces,heat and mass transfer, are included by the addition of sources and sinks. The modeling resultsincluding the fluid flow field, temperature field, concentration field of gas phase and thetrajectories of particles have been obtained. The predicted results are in good agreement with thedata obtained from a series of experiments and tests in the Jinlong Copper Smelter and thetemperature error is less than 20 K.

Kinetic modeling of copper bioleaching from low-grade ore from the Shahrbabak Copper Complex

The copper recovery from low-grade copper sulfide ore was investigated using microbial leaching. Several parameters substantially affect the bioleaching of copper; among them, pulp density and nutrient media were selected for investigation. The optimum conditions for copper recovery were a pulp density of 5 g/mL, a mixed-mineral salt medium of Acidithiobacillus thiooxidans(70vol%) and Acidithiobacillus ferrooxidans(30vol%), and 10vol% of inoculum. Under these conditions, the maximum bioleaching capacity of the medium for copper recovery was determined to be approximately 99%. The effect of pulp density on the kinetics of the bioleaching process was surveyed using both da Silva's method and constrained multilinear regression analysis. The kinetics of copper dissolution followed the shrinking core model, and the process was diffusion controlled at a pulp density of 5 g/mL. Nevertheless, at higher pulp densities, the process was controlled by chemical reaction.

Anomaly Models of Spatial Structures for Copper-Molybdenum Ore Deposits and their Application

This paper discusses the enrichment and depletion regularities for porphyry coppermolybdenum ore deposits in different regions and varied deposit genetic types in the same area, taking three porphyry copper-molybdenum ore deposits （i.e., the Chengmenshan in Jiangxi, Wunugetushan in Inner Mongolia, Baishantang in Gansu） and two copper deposits in Gansu Province （the Huitongshan skarn deposit and Gongpoquan composite deposit） as case studies. The results show that porphyry Cu-Mo deposits or skarn copper deposits include both enrichment of the ore-forming elements and associated elements, and depletion of some lithophile dispersed elements, rare earth elements （REE） and some major elements. And the depleted elements vary with deposits, having generality and their own features. On a deposit scale, the positive anomalies of enriched elements and negative anomalies of depleted elements follow in a sequence to comprise regular anomaly models of spatial structures. The exploration in the Tongchang deposit in Jiangxi and Huitongshan deposit in Gansu suggests that anomaly models play a key role in the identification of mineral occurrences and deposits compared to one single enriched element anomaly. And the anomaly models exert a critical effect on the optimization of prospecting targets and their potential evaluation.

Genetic Types and Metallogenic Model for the Polymetallic Copper–Gold Deposits in the Tongling Ore District, Anhui Province, Eastern China

The Tongling ore district is one of the most economically important ore areas in the Middle–Lower Yangtze River Metallogenic Belt, eastern China. It contains hundreds of polymetallic copper–gold deposits and occurrences. Those deposits are mainly clustered(from west to east) within the Tongguanshan, Shizishan, Xinqiao, Fenghuangshan, and Shatanjiao orefields. Until recently, the majority of these deposits were thought to be skarn-or porphyry–skarn-type deposits; however there have been recent discoveries of numerous vein-type Au, Ag, and Pb-Zn deposits that do not fall into either of these categories. This indicates that there is some uncertainty over this classification. Here, we present the results of several systematic geological studies of representative deposits in the Tongling ore district. From investigation of the ore-controlling structures, lithology of the host rock, mineral assemblages, and the characteristics of the mineralization and alteration within these deposits, three genetic types of deposits(skarn-, porphyry-, and vein-type deposits) have been identified. The spatial and temporal relationships between the orebodies and Yanshanian intrusions combined with the sources of the ore-forming fluids and metals, as well as the geodynamic setting of this ore district, indicate that all three deposit types are genetically related each other and constitute a magmatic–hydrothermal system. This study outlines a model that relates the polymetallic copper–gold porphyry-, skarn-, and vein-type deposits within the Tongling ore district. This model provides a theoretical basis to guide exploration for deep-seated and concealed porphyry-type Cu(–Mo, –Au) deposits as well as shallow vein-type Au, Ag, and Pb–Zn deposits in this area and elsewhere.

Modeling Operational Parameters of a Reactive Electro-Dialysis Cell for Electro-Refining Anodic Scrap Copper

This work will create an electro-dialysis cell model that has the purpose of refining anodic scrap copper—an element that currently must be returned to the copper conversion process. The cell modeling is based on Ohm’s Law, while the resulting copper deposit morphology is studied through the thickness of the layer deposited on the surface and the electric current lines traced from the anode to the cathode. The use of the model demonstrated that it is possible to effectively predict the specific energy consumption required for the refinement of the anodic scrap copper, and the morphology of the cathode obtained, with a margin of error of 9%.

A Fuzzy Logic Model to Predict the Bioleaching Efficiency of Copper Concentrates in Stirred Tank Reactors

Multiplicity of the chemical, biological, electrochemical and operational variables and nonlinear behavior of metal extraction in bioleaching environments complicate the mathematical modeling of these systems. This research was done to predict copper and iron recovery from a copper flotation concentrate in a stirred tank bioreactor using a fuzzy logic model. Experiments were carried out in the presence of a mixed culture of mesophilic bacteria at 35° C, and a mixed culture of moderately thermophilic bacteria at 50° C. Input variables were method of operation (bioleaching or electrobioleaching), the type of bacteria and time (day), while the recoveries of copper and iron were the outputs. A relationship was developed between stated inputs and the outputs by means of “if-then” rules. The resulting fuzzy model showed a satisfactory prediction of the copper and iron extraction and had a good correlation of experimental data with R-squared more than 0.97. The results of this study suggested that fuzzy logic provided a powerful and reliable tool for predicting the nonlinear and time variant bioleaching processes.

Grade and Tonnage Model of Contact Metasomatic Copper Deposit in China

Grade-tonnage model is one of the research frontiers of systematical exploration theory. Based on the “Reserve Database of Mineral Resources in China (1997)”, this paper establishes the geological model, grade model, tonnage model, grade-tonnage model and tonnage-sequence model of contact metasomatic copper deposits in China. The mathematical properties of these models are described in detail.

A Genetic Model for Ore Magma of the Chibaisong Copper-Nickel Sulphide Deposit, Jilin

In the early 1980's, the author proposed his view that copper-nickel sulphide deposts are of ore magma origin. For more than ten years, this view has aroused attention of his colleagues at home and abroad. In this paper an attempt is made to deal with the genetic model for ore magma of copper-nickel sulphide deposits in more details on the basis of geological, geochemical, petrophysico - chemical and thermodynamic studies of the Chibaisong copper-nickel sulphide deposit in the Changbai Mountains, Jilin province.

Geological - Geophysical - Geochemical Exploration Models of Copper - Iron Deposits in Southeastern Hubei

This paper discusses geological-geophysical-geochemical models of such typical deposits as the Tieshan-type Fe-Cu deposit, the Tonglushan-type Cu-Fe deposit, the Yehuaxiang-type Cu deposit, the Jiguanzui-type Cu-Au deposit, and the Tongshankou-type Cu (Mo) deposit. The models were established based on practical data of the polymetallic deposits dominated by copper ore in southeastern Hubei. These models, which are graphically illustrated in the paper, systematically summarize the metallogenic geological conditions and the geophysical-geochemical characteristics of copper deposits in this area. The models are of practical significance for studying copper deposits, predicting mineral resources, choosing exploration methods, and searching for ore deposits based on existing ones in the study area.

Mathematical model of pyritic smelting process for copper-nickel mineral in oxygen top-blown furnace

Mathematical model for mass transfer of chemical reactions on the surface of the smelting bath pit in oxygen top blown smelting furnace was put forward. Additionally, one of two mathematical models for mass transfer of chemical reactions forming copper matte in smelting bath and the other for parameters of smelting process were developed. The verification tests were simultaneously carried out in a pilot scale furnace and the experimental results show that these mathematical models are convincing. Thus, these numerical models are reliable to simulate pyritic smelting process for copper nickel mineral in oxygen top blown furnace.

Mathematical and Numerical Modelling of Copper Tube Extrusion after Optimizing Geometrical and Operating Parameters

This study aimed to optimize cross-sectional area of the extruder and the flow rate of the material through the extruder. Extrusion process was first modelized using the continuum mechanics method before being simulated with the commercial software LS-DYNA using the Johnson-Cook model based on the finite element method after optimization of the factors with simplex algorithm. The study was carried out on a connecting rod: diameter of 145 mm, cross-section of 1.65 m2, length of 0.25 m, volume of 0.41 m3 and a mass of 37 kg. Optimum parameters obtained were temperature of 850℃, flow rate of 0.237 m/s, die diameter of 19.2 mm, pin diameter of 14 mm, extrusion strength of 565.6 kN and press pressure of 245 GPa. From these factors, a blank was obtained with external and internal diameters of 19.2 and 14 mm respectively over a length of 28 m with a thickness of 2.6 mm. Simulation using LS-DYNA software resulted in a difference in values of 7.4% between optimization and simulation when the difference of 2.4% was found between modelling and simulation. These values make the process optimal for industrial application to improve the extrusion requirements of copper tubes.

STUDY ON GREY FORECASTING MODEL OF COPPER EXTRACTION RATE WITH BIOLEACHING OF PRIMARY SULFIDE ORE

A model GM （grey model） （1,1） for forecasting the rate of copper extraction during the bioleaching of primary sulphide ore was established on the basis of the mathematical theory and the modeling process of grey system theory. It was used for forecasting the rate of copper extraction from the primary sulfide ore during a laboratory microbial column leaching experiment. The precision of the forecasted results were examined and modified via ＂posterior variance examination＂. The results show that the forecasted values coincide with the experimental values. GM （1,1） model has high forecast accuracy; and it is suitable for simulation control and prediction analysis of the original data series of the processes that have grey characteristics, such as mining, metallurgical and mineral processing, etc. The leaching rate of such copper sulphide ore is low. The grey forecasting result indicates that the rate of copper extraction is approximately 20% even after leaching for six months.

Model Calculation of ln γ_i^0 for Solute Elements in Copper-base Alloy Systems

A calculation formula of ln γ i 0 for solute element i in liquid alloys was derived by use of free volume theory and Miedema formation enthalpy model. The values of ln γ i 0 of solute elements in liquid copper at 1273 K were obtained. The results obtained show that the coincidence rate of sign (positive or negative) was 90% for the calculated and experimental values, which were basically in the same magnitude.

3D Integrated Geological Modeling in Tongshan Copper Deposit,Heilongjiang Province,China

In this paper,3D-GIS reconstruction and interpolation approach,additional virtual borehole technology and BP network technology are used to explore the concealed ore body.The virtual borehole has same function as reality borehole due to the multi-information check and validation in

Intelligent prediction model of matte grade in copper flash smelting process

Due to the importance of detecting the matte grade in the copper flash smelting process, the mechanism model was established according to the multi-phase and multi-component mathematic model. Meanwhile this procedure was a complicated production process with characteristics of large time delay, nonlinearity and so on. A fuzzy neural network model was set up through a great deal of production data. Besides a novel constrained gradient descent algorithm used to update the parameters was put forward to improve the parameters learning efficiency. Ultimately the self-adaptive combination technology was adopted to paralleled integrate two models in order to obtain the prediction model of the matte grade. Industrial data validation shows that the intelligently integrated model is more precise than a single model. It can not only predict the matte grade exactly but also provide optimal control of the copper flash smelting process with potent guidance.

Mathematical model of multistage and multiphase chemical reactions in flash furnace

A mathematical model of multistage and multiphase reactions in flash smelting furnace, which based on the description of chemical reactions and reaction rate, is presented. In this model, main components of copper concentrate are represented as FeS 2 and CuFeS based on experiment, intermediate products are assumed to be S 2 and FeS, and the final products are assumed as FeS, FeO, SO 2, Cu 2S, FeO and FeO(SiO 2) 2. The model incorporates the transport of momentum, heat and mass, reaction kinetics between gas and particles, and reactions between gas and gas. The k-ε model is used to describe gas phase turbulence. The model uses the Eulerian approach for the gas flow equations and the Lagrangian approach for the particles. The coupling of gas and particle equations is performed through the particle source in cell(PSIC) method. Comparison between the model predictions and the plant measurements shows that the model has high reliability and accuracy.