Three-dimensional Modeling of Ore-forming Elements and Mineralization Prognosis for the Yechangping Mo Deposit,Henan Province,China

Three-dimensional geochemical modeling of ore-forming elements is crucial for predicting deep mineralization.This approach provides key information for the quantitative prediction of deep mineral localization,three-dimensional fine interpolation,analysis of spatial distribution patterns,and extraction of quantitative mineral-seeking markers.The Yechangping molybdenum(Mo)deposit is a significant and extensive porphyry-skarn deposit in the East Qinling-Dabie Mo polymetallic metallogenic belt at the southern margin of the North China Block.Abundant borehole data on oreforming elements underpin deep geochemical predictions.The methodology includes the following steps:(1)Threedimensional geological modeling of the deposit was established.(2)Correlation,cluster,and factor analyses post delineation of mineralization stages and determination of mineral generation sequence to identify(Cu,Pb,Zn,Ag)and(Mo,W,mfe)assemblages.(3)A three-dimensional geochemical block model was constructed for Mo,W,mfe,Cu,Zn,Pb,and Ag using the ordinary kriging method,and the variational function was developed.(4)Spatial distribution and enrichment characteristics analysis of ore-forming elements are performed to extract geological information,employing the variogram and w(Cu+Pb+Zn+Ag)/w(Mo+W)as predictive indicators.(5)Identifying the western,northwestern,and southwestern areas of the mine with limited mineralization potential,contrasted by the northeastern and southeastern areas favorable for mineral exploration.

Modeling and analysis of air combustion and steam regeneration in methanol to olefins processes

Light olefins is the incredibly important materials in chemical industry.Methanol to olefins(MTO),which provides a non-oil route for light olefins production,received considerable attention in the past decades.However,the catalyst deactivation is an inevitable feature in MTO processes,and regeneration,therefore,is one of the key steps in industrial MTO processes.Traditionally the MTO catalyst is regenerated by removing the deposited coke via air combustion,which unavoidably transforms coke into carbon dioxide and reduces the carbon utilization efficiency.Recent study shows that the coke species over MTO catalyst can be regenerated via steam,which can promote the light olefins yield as the deactivated coke species can be essentially transferred to industrially useful synthesis gas,is a promising pathway for further MTO processes development.In this work,we modelled and analyzed these two MTO regeneration methods in terms of carbon utilization efficiency and technology economics.As shown,the steam regeneration could achieve a carbon utilization efficiency of 84.31%,compared to 74.74%for air combustion regeneration.The MTO processes using steam regeneration can essentially achieve the near-zero carbon emission.In addition,light olefins production of the MTO processes using steam regeneration is 12.81%higher than that using air combustion regeneration.In this regard,steam regeneration could be considered as a potential yet promising regeneration method for further MTO processes,showing not only great environmental benefits but also competitive economic performance.

State of the art in applications of machine learning in steelmaking process modeling

With the development of automation and informatization in the steelmaking industry,the human brain gradually fails to cope with an increasing amount of data generated during the steelmaking process.Machine learning technology provides a new method other than production experience and metallurgical principles in dealing with large amounts of data.The application of machine learning in the steelmaking process has become a research hotspot in recent years.This paper provides an overview of the applications of machine learning in the steelmaking process modeling involving hot metal pretreatment,primary steelmaking,secondary refining,and some other aspects.The three most frequently used machine learning algorithms in steelmaking process modeling are the artificial neural network,support vector machine,and case-based reasoning,demonstrating proportions of 56%,14%,and 10%,respectively.Collected data in the steelmaking plants are frequently faulty.Thus,data processing,especially data cleaning,is crucially important to the performance of machine learning models.The detection of variable importance can be used to optimize the process parameters and guide production.Machine learning is used in hot metal pretreatment modeling mainly for endpoint S content prediction.The predictions of the endpoints of element compositions and the process parameters are widely investigated in primary steelmaking.Machine learning is used in secondary refining modeling mainly for ladle furnaces,Ruhrstahl–Heraeus,vacuum degassing,argon oxygen decarburization,and vacuum oxygen decarburization processes.Further development of machine learning in the steelmaking process modeling can be realized through additional efforts in the construction of the data platform,the industrial transformation of the research achievements to the practical steelmaking process,and the improvement of the universality of the machine learning models.

Data-driven intelligent modeling framework for the steam cracking process

Steam cracking is the dominant technology for producing light olefins,which are believed to be the foundation of the chemical industry.Predictive models of the cracking process can boost production efficiency and profit margin.Rapid advancements in machine learning research have recently enabled data-driven solutions to usher in a new era of process modeling.Meanwhile,its practical application to steam cracking is still hindered by the trade-off between prediction accuracy and computational speed.This research presents a framework for data-driven intelligent modeling of the steam cracking process.Industrial data preparation and feature engineering techniques provide computational-ready datasets for the framework,and feedstock similarities are exploited using k-means clustering.We propose LArge-Residuals-Deletion Multivariate Adaptive Regression Spline(LARD-MARS),a modeling approach that explicitly generates output formulas and eliminates potentially outlying instances.The framework is validated further by the presentation of clustering results,the explanation of variable importance,and the testing and comparison of model performance.

HV Process Model of Software Development

Software Development Life Cycle (SDLC) is one of the major ingredients for the development of efficient software systems within a time frame and low-cost involvement. From the literature, it is evident that there are various kinds of process models that are used by the software industries for the development of small, medium and long-term software projects, but many of them do not cover risk management. It is quite obvious that the improper selection of the software development process model leads to failure of the software products as it is time bound activity. In the present work, a new software development process model is proposed which covers the risks at any stage of the development of the software product. The model is named a Hemant-Vipin (HV) process model and may be helpful for the software industries for development of the efficient software products and timely delivery at the end of the client. The efficiency of the HV process model is observed by considering various kinds of factors like requirement clarity, user feedback, change agility, predictability, risk identification, practical implementation, customer satisfaction, incremental development, use of ready-made components, quick design, resource organization and many more and found through a case study that the presented approach covers many of parameters in comparison of the existing process models. .

Modeling of an Automatic Optimization System of Cyanide Concentration in Carbon in Leach for Optimal Ore Processing in a Mining Company

The optimization system, which was the subject of our study, is an autonomous chain for the automatic management of cyanide consumption. It is in the phase of industrial automation which made it possible to use the machines in order to reduce the workload of the worker while keeping a high productivity and a quality in great demand. Furthermore, the use of cyanide in leaching tanks is a necessity in the gold recovery process. This consumption of cyanide must be optimal in these tanks in order to have a good recovery while controlling the concentration of cyanide. Cyanide is one of the most expensive products for mining companies. On a completely different note, we see huge variations during the addition of cyanide. Following a recommendation from the metallurgical and operations teams, the control team carried out an analysis of the problem while proposing a solution to reduce the variability around plus or minus 10% of the addition setpoint through automation. It should be noted that this automatic optimization by monitoring the concentration of cyanide, made use of industrial automation which is a technique which ensures the operation of the ore processing chain without human intervention. In other words, it made it possible to substitute a machine for man. So, this leads us to conduct a study on concentration levels in the real world. The results show that the analysis of the modeling of the cyanide consumption optimization system is an appropriate solution to eradicate failures in the mineral processing chain. The trend curves demonstrate this resolution perfectly.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

Finite Element Simulation of Radial Tire Building and Shaping Processes Using an Elasto-Viscoplastic Model

The comprehensive tire building and shaping processes are investigated through the finite element method(FEM)in this article.The mechanical properties of the uncured rubber from different tire components are investigated through cyclic loading-unloading experiments under different strain rates.Based on the experiments,an elastoviscoplastic constitutive model is adopted to describe themechanical behaviors of the uncured rubber.The distinct mechanical properties,including the stress level,hysteresis and residual strain,of the uncured rubber can all be well characterized.The whole tire building process(including component winding,rubber bladder inflation,component stitching and carcass band folding-back)and the shaping process are simulated using this constitutive model.The simulated green tire profile is in good agreement with the actual profile obtained through 3D scanning.The deformation and stress of the rubber components and the cord reinforcements during production can be obtained fromthe FE simulation,which is helpful for judging the rationality of the tire construction design.Finally,the influence of the parameter“drum width”is investigated,and the simulated result is found to be consistent with the experimental observations,which verifies the effectiveness of the simulation.The established simulation strategy provides some guiding significance for the improvement of tire design parameters and the elimination of tire production defects.

Computer Modeling: an Important Tool in Materials Processing

The development of techniques to control and use materials, especially metallic materials continues to play a key role in the technological advancement of modem day society. A variety of materials processes have been developed overtime, and are applied to design and fabricate products. Heat treatment of metallic materials has been the method of choice applied to improve mechanical properties such as strength, hardness, and toughness, as well as to improve the homogeneity of properties in materials such as corrosion resistance. The molt significant success stories in the application of materials processes involve the heat-treatment of steel. The reasons for this largely lie in the ease with which steel microstructures can be altered by controlled heating and cooling. The objective of computer modeling of materials processes is to maximize on the beneficial factors while keeping to a minimum the negating effects such as components distortion and residual stresses. Computer modeling is a powerful tool in achieving this objective in the sense that with it, the effect of parameters associated with materials processes can be analyzed systematically in order to optimize them before actual production begins.

Fault monitoring based on mutual information feature engineering modeling in chemical process

A large amount of information is frequently encountered when characterizing the sample model in chemical process.A fault diagnosis method based on dynamic modeling of feature engineering is proposed to effectively remove the nonlinear correlation redundancy of chemical process in this paper.From the whole process point of view,the method makes use of the characteristic of mutual information to select the optimal variable subset.It extracts the correlation among variables in the whitening process without limiting to only linear correlations.Further,PCA(Principal Component Analysis)dimension reduction is used to extract feature subset before fault diagnosis.The application results of the TE(Tennessee Eastman)simulation process show that the dynamic modeling process of MIFE(Mutual Information Feature Engineering)can accurately extract the nonlinear correlation relationship among process variables and can effectively reduce the dimension of feature detection in process monitoring.

Numerical Modelling of Ore-forming Dynamics of Fractal Dispersive Fluid Systems

Based on an analysis of the fractal structures and mass transport mechanism of typical shear-fluid-ore formation system, the fractal dispersion theory of the fluid system was used in the dynamic study of the ore formation system. The model of point-source diffusive illuviation of the shear-fluid-ore formation system was constructed, and the numerical simulation of dynamics of the ore formation system was finished. The result shows that: (1) The metallogenic system have nested fractal structure. Different fractal dimension values in different systems show unbalance and inhomogeneity of ore-forming processes in the geohistory. It is an important parameter to symbolize the process of remobilization and accumulation of ore-forming materials. Also it can indicate the dynamics of the metallogenic system quantitatively to some extent. (2) In essence, the fractal dispersive ore-forming dynamics is a combination of multi-processes dominated by fluid dynamics and supplemented by molecule dispersion in fluids and fluid-rock interaction. It changes components and physico-chemical properties of primary rocks and fluids, favouring deposition and mineralization of ore-forming materials. (3) Gold ore-forming processes in different types of shear zones are quite different. (1) In a metallogenic system with inhomogeneous volumetric change and inhomogeneous shear, mineralization occurs in structural barriers in the centre of a shear zone and in geochemical barriers in the shear zone near its boundaries. But there is little possibility of mineralization out of the shear zone. (2) As to a metallogenic system with inhomogeneous volumetric change and simple shear, mineralization may occur only in structural barriers near the centre of the shear zone. (3) In a metallogenic system with homogeneous volumetric change and inhomogeneous shear, mineralization may occur in geochemical barriers both within and out of the shear zone.

Modeling the effects of ore properties on water recovery in the thickening process

A better understanding of solid-liquid separation would assist in improving the thickening performance and perhaps water recovery as well. The present work aimed to develop an empirical model to study the effects of ore properties on the thickening process based on pilot tests using a column. A hydro-cyclone was used to prepare the required samples for the experiments. The model significantly predicted the experimental underflow solid content using a regression equation at a given solid flux and bed level for different samples, indicating that ore properties are the effective parameters in the thickening process. This work confirned that the water recovery would be increased about 5% by separating the feed into two parts, overflow and underflow, and introducing two different thickeners into them separately. This is duo to the fact that thickeners are limited by permeability and compressibility in operating conditions.

Characteristics of Pegmatite-Related Fluids and Significance to Ore-Forming Processes in the Zhaxikang Pb-Zn-Sb Polymetallic Deposit,Tibet,China

The Zhaxikang Pb-Zn-Sb polymetallic deposit is one of the most important deposits in the newly recognized southern Tibet antimony-gold metallogenic belt.Compared to the porphyry deposits in the Gangdese belt,much less researches have addressed these deposits,and the genesis of the Zhaxikang deposit is still controversial.Based on field investigation,petrographic,microthermometric,Laser Raman Microprobe（LRM） and SEM/EDS analyses of fluid,melt-fluid,melt and solid inclusions in quartz and beryl from pegmatite,this paper documents the characteristics and the evolution of primary magmatic fluid which was genetically related to greisenization,pegmatitization,and silification in the area.The results show that the primary magmatic fluids were derived from unmixing between melt and fluid and underwent a phase separation process soon after the exsolution.The primary magmatic fluids are of low salinity,high temperature,and can be approximated by the H_2O-NaCl-CO_2 system.The presence of Mn-Fe carbonate in melt-fluid inclusions and a Zn-bearing mineral（gahnite） trapped in beryl and in inclusions from pegmatite indicates high Mn,Fe,and Zn concentrations in the parent magma and magmatic fluids,and implies a genetic link between pegmatite and Pb-Zn-Sb mineralization.High B and F concentrations in the parent magma largely lower the solidus of the magma and lead to late fluid exsolution,thus the primary magmatic fluids related to pegmatite have much lower temperature than those in most porphyry systems.Boiling of the primary magmatic fluids leads to high-salinity and high-temperature fluids which have high capacity to transport Pb,Zn and Sb.The decrease in temperature and mixing with fluids from other sources may have caused the precipitation of Pb-Zn-Sn（Au） minerals in the distal fault systems surrounding the causative intrusion.

Physical Modeling of the Vacuum Circulation Refining Process of Molten Steel

The available studies in the literature on physical modeling of the vacuum circulation (RH, i.e. Ruhrstahl Heraeus) refining process of molten steel have briefly been reviewed. The latest advances made by the author with his research group have been summarized. Water modeling was employed to investigate the flow and mixing characteristics of molten steel under the RH and RH KTB (Kawasaki top blowing) conditions and the mass transfer features between molten steel and powder particles in the RH PTB (powder top blowing) refining. The geometric similarity ratio between the model and its prototype (a multifunction RH degasser of 90 t capacity) was 1:5. The effects of the related technological and structural factors were considered. These latest studies have revealed the flow and mixing characteristics of molten steel and the mass transfer features between molten steel and powder particles in these processes, and have provided a better understanding of the refining processes of molten steel.

Hybrid Data-Driven and Mechanistic Modeling Approaches for Multiscale Material and Process Design

The world’s increasing population requires the process industry to produce food,fuels,chemicals,and consumer products in a more efficient and sustainable way.Functional process materials lie at the heart of this challenge.Traditionally,new advanced materials are found empirically or through trial-and-error approaches.As theoretical methods and associated tools are being continuously improved and computer power has reached a high level,it is now efficient and popular to use computational methods to guide material selection and design.Due to the strong interaction between material selection and the operation of the process in which the material is used,it is essential to perform material and process design simultaneously.Despite this significant connection,the solution of the integrated material and process design problem is not easy because multiple models at different scales are usually required.Hybrid modeling provides a promising option to tackle such complex design problems.In hybrid modeling,the material properties,which are computationally expensive to obtain,are described by data-driven models,while the well-known process-related principles are represented by mechanistic models.This article highlights the significance of hybrid modeling in multiscale material and process design.The generic design methodology is first introduced.Six important application areas are then selected:four from the chemical engineering field and two from the energy systems engineering domain.For each selected area,state-ofthe-art work using hybrid modeling for multiscale material and process design is discussed.Concluding remarks are provided at the end,and current limitations and future opportunities are pointed out.

Physical and Mathematical Modeling of the Argon-Oxygen Decarburization Refining Process of Stainless Steel

The available studies in the literature on physical and mathematical modeling of the argon oxygen decarburization (AOD) process of stainless steel have briefly been reviewed. The latest advances made by the author with his research group have been summarized. Water modeling was used to investigate the fluid flow and mixing characteristics in the bath of an 18 t AOD vessel, as well as the 'back attack' action of gas jets and its effects on the erosion and wear of the refractory lining, with sufficiently full kinematic similarity. The non rotating and rotating gas jets blown through two annular tuyeres, respectively of straight tube and spiral flat tube type, were employed in the experiments. The geometric similarity ratio between the model and its prototype (including the straight tube type tuyeres) was 1:3. The influences of the gas flow rate, the angle included between the two tuyeres and other operating parameters, and the suitability of the spiral tuyere as a practical application, were examined. These latest studies have clearly and successfully brought to light the fluid flow and mixing characteristics in the bath and the overall features of the back attack phenomena of gas jets during the blowing, and have offered a better understanding of the refining process. Besides, mathematical modeling for the refining process of stainless steel was carried out and a new mathematical model of the process was proposed and developed. The model performs the rate calculations of the refining and the mass and heat balances of the system. Also, the effects of the operating factors, including adding the slag materials, crop ends, and scrap, and alloy agents; the non isothermal conditions; the changes in the amounts of metal and slag during the refining; and other factors were all considered. The model was used to deal with and analyze the austenitic stainless steel making (including ultra low carbon steel) and was tested on data of 32 heats obtained in producing 304 grade steel in an 18 t AOD vessel. The changes in the bath composition and temperature during the refining process with time can be accurately predicted using this model. The model can provide some very useful information and a reliable basis for optimizing the process practice of the refining of stainless steel and control of the process in real time and online.

Process Modeling and Dynamic Simulation for EAST Helium Refrigerator

In this paper,the process modeling and dynamic simulation for the EAST helium refrigerator has been completed.The cryogenic process model is described and the main components are customized in detail.The process model is controlled by the PLC simulator,and the realtime communication between the process model and the controllers is achieved by a customized interface.Validation of the process model has been confirmed based on EAST experimental data during the cool down process of 300-80 K.Simulation results indicate that this process simulator is able to reproduce dynamic behaviors of the EAST helium refrigerator very well for the operation of long pulsed plasma discharge.The cryogenic process simulator based on control architecture is available for operation optimization and control design of EAST cryogenic systems to cope with the long pulsed heat loads in the future.

Fluid Evolution and Ore-forming Processes of the Jiama Cu Deposit, Tibet： Evidence from Fluid Inclusions

The Jiama deposit is a large copper deposit in Tibet. Mineralization occurs in three different host rocks： skarn, hornfels and porphyry. A detailed fluid inclusion study was conducted for veins in the different host rocks to investigate the relationship between fluid evolution and ore-forming processes. Based on examination of cores from 36 drill holes, three types of veins （A, B and D） were identified in the porphyries, four types （I, II, III and IV） in the skarn, and three （a, b and c） in the hornfels. The crosscutting relationships of the veins and that of the host rocks suggest two hydrothermal stages, one early and one late stage. Fluid inclusions indicate that the Jiama hydrothermal fluid system underwent at least two episodes of fluid boiling. The first boiling event occurred during the early hydrothermal stage, as recorded by fluid inclusions hosted in type A veins in the porphyries, type a veins in the hornfels, and wollastonite in the skarns. This fluid boiling event was associated with relatively weak mineralization. The second boiling event occurred in the late hydrothermal stage, as determined from fluid inclusions hosted in type B and D veins in the porphyries, type I to IV veins in the skarns, and type b and c veins in the hornfels. This late boiling event, together with mixing with meteoric water, was responsible for more than 90% of the metal accumulation in the deposit. The first boiling only occurred in the central part of the deposit and the second boiling event took place across an entire interlayered structural zone between hornfels and marble. A spatial zoning of ore-elements is evident, and appears to be related to different migration pathways and precipitation temperatures of Cu, Mo, Pb, Zn, Au and Ag.

A Process Oriented Integration Model for Smart Health Services

Cities are facing challenges of high rise in population number and con-sequently need to be equipped with latest smart services to provide luxuries of life to its residents.Smart integrated solutions are also a need to deal with the social and environmental challenges,caused by increasing urbanization.Currently,the development of smart services’integrated network,within a city,is facing the bar-riers including;less efficient collection and sharing of data,along with inadequate collaboration of software and hardware.Aiming to resolve these issues,this paper recommended a solution for a synchronous functionality in the smart services’integration process through modeling technique.Using this integration modeling solution,atfirst,the service participants,processes and tasks of smart services are identified and then standard illustrations are developed for the better understand-ing of the integrated service group environment.Business process modeling and notation(BPMN)language based models are developed and discussed for a devised case study,to test and experiment i.e.,for remote healthcare from a smart home.The research is concluded with the integration process model application for the required data sharing among different service groups.The outcomes of the modeling are better understanding and attaining maximum automation that can be referenced and replicated.

Offshore Software Maintenance Outsourcing Process Model Validation:A Case Study Approach

The successful execution and management of Offshore Software Maintenance Outsourcing(OSMO)can be very beneficial for OSMO vendors and the OSMO client.Although a lot of research on software outsourcing is going on,most of the existing literature on offshore outsourcing deals with the outsourcing of software development only.Several frameworks have been developed focusing on guiding software systemmanagers concerning offshore software outsourcing.However,none of these studies delivered comprehensive guidelines for managing the whole process of OSMO.There is a considerable lack of research working on managing OSMO from a vendor’s perspective.Therefore,to find the best practices for managing an OSMO process,it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s perspective.This study validated the preliminary OSMO process model via a case study research approach.The results showed that the OSMO process model is applicable in an industrial setting with few changes.The industrial data collected during the case study enabled this paper to extend the preliminary OSMO process model.The refined version of the OSMO processmodel has four major phases including(i)Project Assessment,(ii)SLA(iii)Execution,and(iv)Risk.