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In the new, dry-process method of cement production, the temperature of cement rotary kiln sintering zone is a key factor in ensuring the quality of cement clinker. Based on the auto-regressive with extra inputs model, a finite control set model predictive control with soft constraint of the generalized triangular interval is proposed in this paper for the characteristics of a cement rotary kiln calcination system with multi-variable, multi-time delay, bounded disturbance, and slow dynamic process. Simulation experiments show that the steady-state error of the control algorithm proposed in this paper is smaller with better anti-disturbance performance than that of the traditional reference-trajectory-constrained, predictive control algorithm. [ABSTRACT FROM AUTHOR]

This research paper gives the development data obtained for modern modified periclase‐spinel materials that have an increased adaptive ability to preserve the material integrity and the operational reliability of the refractories exposed to the effect of the sign‐alternating high‐gradient and thermal loads. Based on the research done, a concept was developed to improve the heat resistance of the periclase‐spinel materials and it includes both the known mechanisms of absorbing excess energy by cracks that are developed under the action of thermal shocks (in particular, the effect of heterophasicity and creation of a microcracked structure due to the difference in thermal efficiency coefficients (TEC) for different phases) and new mechanisms of the structure‐&‐phase adaptations preserving simultaneously the integrity of modified periclase‐spinel refractories. The use of the developed modified periclase‐spinel refractories results in the energy saving of up to 15 %, reduction of material costs due to the extension of the service life of the lining elements of rotary kilns; reduction of the resources required for the maintenance and an increase in the amount of overhaul sessions. [ABSTRACT FROM AUTHOR]

The cement industry is the second largest source of global man-made CO2 emissions after the power industry, and the adoption of O2/CO2 combustion technology for cement kilns is of great significance in reducing CO2 emissions. In this paper, the effects of pulverized coal mixed air combustion and pulverized coal mixed O2/CO2 combustion on the velocity field, temperature field, CO2 and NOx concentration distribution in rotary kiln were investigated by CFD technique. The results showed that there is no difference in the velocity distribution between the two atmospheres, and the speed difference between the primary and secondary air creates a re-circulation zone near the burner. The O2/CO2 atmosphere combustion decreased the maximum temperature, but improved the uniformity of the temperature field. The pulverized coal burnout rate under O2/CO2 atmosphere decreased by 3.55% compared to O2/N2 atmosphere. The mole fraction of CO2 at the rotary kiln outlet is 0.08 and 0.93 for O2/N2 and O2/CO2 combustion atmospheres, respectively. It is easier to achieve CO2 aggregation and capture under O2/CO2 atmosphere than under O2/N2. The NOx concentration at O2/CO2 is approximately one half of that at O2/N2, which can save the investment on denitrification equipment. The simulation results reasonably agree with the measured data. The findings of this work will provide a reference for the generalization and application of the O2/CO2 flue gas cycle calcinating cement technology. [ABSTRACT FROM AUTHOR]

A cement rotary kiln is the main part of the cement production process, which has always attracted many researchers attention. However, this complex nonlinear system has not been modeled efficiently, which can make an appropriate performance, especially in noisy condition. In this work, the type 2 Takagi-Sugeno neuro-fuzzy system (T2TSNFS) is used to identify the cement rotary kiln, and the gradient descent (GD) algorithm is applied for tuning the parameters of antecedent and consequent parts of fuzzy rules. In addition, the optimal inputs of the system are selected by the genetic algorithm (GA) to achieve less complexity in the fuzzy system. The data relating to the Saveh White Cement (SWC) factory is used in the simulations. The results demonstrate that the proposed identifier has an appropriate performance in noisy conditions. Furthermore, in this work, T2TSNFS is evaluated in noisy conditions, which had not been worked out before in related research works. Also, T2TSNFS and type 1 Takagi-Sugeno neuro-fuzzy system (T1TSNFS) are compared. The simulations show that T2TSNFS has more proper performance when the standard deviation of noise increases. [ABSTRACT FROM AUTHOR]

Regenerated magnesia-calcium brick samples with different aluminium oxide (Al2O3) contents were prepared using spent magnesia-calcium bricks and fused magnesia as the main raw materials and Al2O3 powders as the additive. The phase compositions, microstructures, room temperature, hot flexural strength, and kiln coating adherence of the regenerated samples were investigated. This indicates that the Al2O3 content increased, mainly resulting in the content of tetracalcium aluminoferrite (C4AF) and tricalcium aluminate (C3A) increasing in the regenerated samples. The bulk density, room temperature flexural strength, and kiln coating adherence all increased, whereas the hot flexural strength and corrosion resistance to cement clinker both deteriorated with an increase in the Al2O3 content. This was because, on the one hand, the low melting point phases of C4AF and C3A improved the sinterability of the regenerated samples during the burning stage, and on the other hand, they melted or existed in the liquid phase at the experimental temperature, which degraded the hot flexural strength and corrosion resistance but enhanced the kiln coating adherence as the wettability of the liquid phase. The content of Al2O3 in the regenerated magnesia-calcium brick should not be higher than 1.1 wt.%, considering its comprehensive performance for cement rotary kiln. [ABSTRACT FROM AUTHOR]

Digitalizing cement production plants to improve operation parameters' control might reduce energy consumption and increase process sustainabilities. Cement production plants are one of the extremest CO2 emissions, and the rotary kiln is a cement plant's most energy-consuming and energy-wasting unit. Thus, enhancing its operation assessments adsorb attention. Since many factors would affect the clinker production quality and rotary kiln efficiency, controlling those variables is beyond operator capabilities. Constructing a conscious-lab "CL" (developing an explainable artificial intelligence "EAI" model based on the industrial operating dataset) can potentially tackle those critical issues, reduce laboratory costs, save time, improve process maintenance and help for better training operators. As a novel approach, this investigation examined extreme gradient boosting (XGBoost) coupled with SHAP (SHapley Additive exPlanations) "SHAP-XGBoost" for the modeling and prediction of the rotary kiln factors (feed rate and induced draft fan current) based on over 3,000 records collected from the Ilam cement plant. SHAP illustrated the relationships between each record and variables with the rotary kiln factors, demonstrated their correlation magnitude, and ranked them based on their importance. XGBoost accurately (R-square 0.96) could predict the rotary kiln factors where results showed higher exactness than typical EAI models. [ABSTRACT FROM AUTHOR]

A rotary kiln is a central piece of equipment for the calcination of clinker in the production of cement. Biomass energy has been applied to rotary kilns, and solar energy has been introduced to assist the energy supply. Coupled optimization results for biomass energy and solar energy applications are compared to the single fossil energy used in the base period. A field survey and statistical analysis and integration of cement clinker production sites in China's Central Plains Economic Zone revealed a negative linear correlation between the consumption of raw coal in the cement production process and the environmental temperature and humidity parameters of the production lines. The energy consumption is large and the energy utilization of the system is low, with goodness of fit of R=0.962. Coupled solar and biomass energy use in the audit period and single energy use in the base period comparison revealed a 19.5% reduction in electricity consumption, a 25.4% reduction in coal consumption and a 4.39% increase in heavy oil consumption. From 2017 to 2020, the average annual consumption cost of electricity and raw coal decreased, while the average annual consumption cost of heavy fuel oil slowly increased. After verification during the audit period, compared with the base period, the total production cost of the case enterprise can be reduced approximately 5.17%, in which the energy cost decreased 0.9%. [ABSTRACT FROM AUTHOR]

Türkiye is one of the biggest developing countries and the second biggest cement exporter in the world. In 2021, the country exported around $1billion of cement, which is responsible for over 8% of emissions globally. In order to fulfill the EU norms, energy, emissions, and cost reduction investments continue in the country. The aim of this paper is to perform a detailed exergoeconomic assessment of a rotary burner to increase the energy and exergy performance and decrease energy consumption, exergy costs and environmental impacts of a real scale cement factory in Türkiye. During the 2-year period, detailed data has been obtained from the factory by real time detection of clinker manufacturing process. By applying the specific exergy costing (SPECO) method, energy and exergy destructions, and exergetic cost distributions for the rotary burner are calculated in detail. The 1st and 2nd law efficiencies of the overall factory, specific energy (SEC) and exergy (SExC) consumption, and SPECO for clinker production are calculated to be 59.84%, 39.04%, 4786.75 MJ/ton, 5230.38 MJ/ton, and 10.11 $/MJ, respectively. The use of magnesia-spinel composite refractory bricks and the anzast layer formation decreased the SPECO by 2.71% corresponding to a saving of $2,280,000 preventing 13.74 MtCO2 emissions yearly. [ABSTRACT FROM AUTHOR]

High-strength low-cement castables have been produced for the first time from waste of demolished glass furnaces. Adispersant of long-chain ionizable sodium tripolyphosphate (STPP, 0.2 wt.%) had a positive effect on electrostatic stabilization and improvement of the rheological characteristics of alumina-zirconia-silica (AZS) castable. Four castable mixes of various packing moduli (n = 0.22, 0.23, 0.24, and 0.25) have been formulated using the Andreasen equation. The castable of Andreasen packing modulus n = 0.25 demonstrated an outstanding compressive strength (1118.15 kg/cm2) and a moderate bulk density (2.65 g/cm3) when fired at 1375°C. It showed the highest dimensional stability and a permanent linear change of less than 0.6% at 1300°C. It displayed high thermal shock resistance (30 cycles) and high abrasion resistance (abrasion loss ~2.05% after 280 abrasion test cycles) when fired at 1300°C. Therefore, this castable can be used in high wear-rate sections of cement kilns and is an excellent choice in case of kiln instability. The results indicated that the castable with n = 0.25 is highly recommended for lining the inlet of rotary cement kilns at 1000 – 1300°C. The results open the door for the use of waste from demolished glass kilns to produce high-strength low-cement refractory castable for lining cement kiln inlets. [ABSTRACT FROM AUTHOR]

No alternatives are currently available to operate industrial furnaces, except for hydrocarbon fuels. Plant managers, therefore, face at least two challenges. First, environmental legislation demands emission reduction. Second, changes in the origin of the fuel might cause unforeseen changes in the heat release. This paper develops the hypothesis for the detailed control of the combustion process using computational fluid dynamic models. A full-scale mock-up of a rotary cement kiln is selected as a case study. The kiln is fired by the non-premixed combustion of Dutch natural gas. The gas is injected at Mach 0.6 via a multi-nozzle burner located at the outlet of an axially mounted fuel pipe. The preheated combustion air is fed in (co-flow) through a rectangular inlet situated above the attachment of the fuel pipe. The multi-jet nozzle burner enhances the entrainment of the air in the fuel jet. A diffusion flame is formed by thin reaction zones where the fuel and oxidizer meet. The heat formed is transported through the freeboard, mainly via radiation in a participating medium. This turbulent combustion process is modeled using unsteady Favre-averaged compressible Navier–Stokes equations. The standard k- ϵ equations and standard wall functions close the turbulent flow description. The eddy dissipation concept model is used to describe the combustion process. Here, only the presence of methane in the composition of the fuel is accounted for. Furthermore, the single-step reaction mechanism is chosen. The heat released radiates throughout the freeboard space. This process is described using a P1-radiation model with a constant thermal absorption coefficient. The flow, combustion, and radiative heat transfer are solved numerically using the OpenFoam simulation software. The equations for flow, combustion, and radiant heat transfer are discretized on a mesh locally refined near the burner outlet and solved numerically using the OpenFoam simulation software. The main results are as follows. The meticulously crafted mesh combined with the outlet condition that avoids pressure reflections cause the solver to converge in a stable manner. Predictions for velocity, pressure, temperature, and species distribution are now closer to manufacturing conditions. Computed temperate and species values are key to deducing the flame length and shape. The radiative heat flux to the wall peaks at the tip of the flame. This should allow us to measure the flame length indirectly from exterior wall temperature values. The amount of thermal nitric oxide formed in the flame is quantified. The main implication of this study is that the numerical model developed in this paper reveals valuable information on the combustion process in the kiln that otherwise would not be available. This information can be used to increase fuel efficiency, reduce spurious peak temperatures, and reduce pollutant emissions. The impact of the unsteady nature of the flow on the chemical species concentration and temperature distribution is illustrated in an accompanying video. [ABSTRACT FROM AUTHOR]

A rotary kiln is core equipment in cement calcination. Significant time delay, time-varying, and nonlinear characteristics cause challenges in the advance process control and operational optimization of the rotary kiln. However, the traditional mechanism model with many assumptions cannot accurately represent the dynamic kiln process because kinetic parameters are difficult to obtain. This paper proposes a novel hybrid strategy to develop a dynamic model of a rotary kiln by combining a process mechanism and a recurrent neural network to address this issue. A time delay mechanism is used to estimate the kiln's residence time to compensate for the time delay. A long short-term memory model that combines an attention mechanism and an ordinary differential equation solver is proposed to capture the time-varying and nonlinear behaviors of the kiln process. Case studies from two real-world cement plants with different processing loads are used to verify the effectiveness of the proposed hybrid modeling strategy. The results show that the proposed method has better accuracy and robustness than the traditional methods. The sensitivity analysis of the proposed model also makes it practical for t control system design and real-time optimization. • A hybrid modeling framework combined with mechanism and process data is proposed. • A LSTM model integrated with attention strategy and ODE solver, is used to model the kiln process. • The modeling methodology is verified by two mainstream cement plants. • The model accuracy, robustness, and applicability are discussed. [ABSTRACT FROM AUTHOR]

Cement manufacturing is energy‐intensive (5Gj/t) and comprises a significant portion of the energy footprint of concrete systems. Incorporating modern monitoring, simulation and control systems will allow lower energy use, lower environmental impact, and lower costs of this widely used construction material. One of the goals of the CESMII roadmap project on the Smart Manufacturing of Cement included developing an analytical process model for clinker quality that includes the chemistry of the kiln feed and accounts for critical process variables. This predictive model will be used in nonlinear model predictive control system designed to significantly reduce process energy use while maintaining or improving product quality. In the cement manufacturing plant used in this study, the kiln feed (meal) is tested every 12 h and used to estimate the mineral composition of the cement kiln output (clinker) using the stoichiometry‐based Bogue's model and the expertise of the plant operators. During kiln operation, kiln output (clinker) is sampled and tested every 2 h to measure its chemical and mineral composition. The predicted and measured values of the clinker composition are used by the plant operators to adjust the kiln input stream and the production process characteristics to maintain stable operation and uniform product quality. However, the time delay between prediction and testing, along with inaccuracies inherent in the Bogue's model have made any process changes designed to minimize energy use problematic, especially in‐light of potential clinker quality issues that process changes often pose. A new analytical model that integrates quality information and process operation information has been developed from data collected from 2 years of production from an operating cement facility. To make the model fuel‐type‐independent, consumed heat energy was computed in the model instead of fuel type and amount. A Feedforward Network was trained and tailored from collected data. Many data‐based simulations were conducted to quantitatively evaluate the proposed model and the 5‐fold cross‐validation procedure was used to test the models. The resulting predictive model was shown to have a low root mean square error (MSE) with respect to the estimated clinker mineral composition compared to that using the industry standard "Bogue' model". The end goal of this work was to develop a single machine learning tool that allows the use of quality control data and process control variables to improve energy efficiency of the process in a continuous fashion. The proposed nonlinear model predictive control system (NMPC) can generate predicted kiln production characteristics based on manipulated variables in manner that accurately follows the target product quality values. Simulation results also show that the proposed model produced accurate predictions of kiln outputs that fell within the required constraints, while manipulating control variables within typical operational ranges. [ABSTRACT FROM AUTHOR]

Due to technical or economic limitations, timely measuring quality-relevant key performance indicators (KPIs) of complex industrial processes (CIPs), especially the chemical composition-related indexes, is intractable. Process monitoring image sequences (PMISs) usually involve significant information about the operation states and KPIs. Thus, soft sensor-based online KPI inference by incorporating process monitoring variables (TPMVs) and PMISs is more promising. However, the extremely inconsistent sampling rates with different expression forms and concerning aspects between PMISs and TPMVs lead to a great challenge in the soft sensor modeling by combining PMISs and TPMVs. In this article, a self-attention dual-channel deep network (SADCDN)-based soft sensor model for the end-to-end online KPI detection/prediction is proposed. Specifically, one channel adopts the gated recurrent unit (GRU) network to extract intrinsic time-series features in TPMVs, and simultaneously the other channel introduces a novel frame-dilated convolution fusion neural network (FDCFNN) to extract intrinsic spatiotemporal features from PMISs to address the sampling inconsistence between PMISs and TPMVs. Successively, dual-channel network features with different concerning aspects are weighted and fused based on an introduced self-attention mechanism to bridge the gap of sampling rates and concerning aspects between PMISs and TPMVs for the soft sensor modeling. Practical application results on two real industrial processes, the bauxite flotation process and the sintering process of a cement rotary kiln, have demonstrated the effectiveness and superiority of the proposed dual-channel model, laying a foundation for the process optimization of CIPs. [ABSTRACT FROM AUTHOR]

Copyright of Revista Tecno Lógicas is the property of Instituto Tecnologico Metropolitano and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Display omitted] • This study assessed the energetic efficiency of a precalcining rotary kiln process in a cement industry. • Energetic efficiency was estimated as 61.30 % using Aspen Plus process simulator and artificial neural network (ANN) model predict with correlation coefficient (R2) of 0.991. • Optimal energy efficiency of 61.5 % was established for the operation parameters; kiln feed of 205050 kg/hr, kiln fuel gas of 2821 kg/hr, calciner fuel gas of 5648 kg/hr, clinker cooling air of 247463 kg/hr and primary air of 7309 kg/hr. Cement production has been increasing rapidly leading to energy consumption, with serious cost implications and environmental challenges. Energy efficiency is a key component required to maintain the cement company's environmental strategy. In this study, Aspen Plus process model and neural networks are used to assess the energetic efficiency of a precalcining rotary kiln in a cement production process. Aspen Plus process simulator estimated energy efficiency at 61.30 % using the first law of thermodynamic. Further, for the ANN model, kiln feed, kiln gas, calciner gas, clinker cooling air, and primary air were the operation parameters inputs. ANN model is validated and demonstrated it is capable of predicting cement rotary kiln energy efficiency accurately with a correlation coefficient (R2) of 0.991. In conclusion, the Bootstrap aggregated neural network (BANN) was used to search the optimal operational parameters in achieving the lowest mean square error (MSE) of the energy efficiency. The MSE for training, testing, and validation data sets were 3.64 × 10-5, 3.70 × 10-5, and 5.00 × 10-5 for in the estimation of rotary kiln system energy efficiency. To achieve this optimal condition of 61.5 % energy efficiency, the optimal parameters as determined by ANN (BANN) were kiln feed of 205050 kg/hr, kiln fuel gas of 2821 kg/hr, calciner fuel gas of 5648 kg/hr, clinker cooling air of 247463 kg/hr and primary air of 7309 kg/hr. Consequently, it is recommended that ANN should be combined with Bootstrap aggregated neural network (BANN) for effective prediction and monitoring of energy efficiency for precalcining rotary kiln system. [ABSTRACT FROM AUTHOR]

• The behaviour of Cd and Pb are closely related to the presence of Cl−1. • The concentrations of Cd and Pb increased sharply after recycling of kiln dust. • Thermodynamic software can effectively simulate the fixation of heavy metals. • Using model can optimize kiln control strategy and ash recirculation ratio. Fly ash produced from incineration of municipal solid wastes (MSW) contains heavy metals, such as Cd and Pb, that make this material difficult to manage and dispose of safely. Because the composition of fly ash is similar to cement raw meal, partial replacement of raw meal with fly ash may be a feasible way to reduce the health and environmental hazards of the ash, provided that the heavy metals can be effectively stabilized in the solid phase. This research employs proprietary thermochemical software to simulate the thermodynamic behavior and single-step fixation of Cd and Pb in industrial cement kilns. The effect of Cd, Pb and Cl loadings on the fixation and/or evaporation of Cd and Pb during the sintering process is analyzed using data from industrial cement kilns. A simplified model is created based on elemental mass balance to evaluate multi-step fixation of Cd and Pb with cement kiln dust recycle.The results indicate that Cd forms Cd(OH) 2 (g) in a highly alkaline environment, while nearly 90% Pb is volatilized as PbCl 2 (g). In the clinker, increased Cl−1 decreased the proportion of Pb and Cd, moreover, Pb and Cd increased in kiln dust with Cl−1 increased; Calculations using a kiln dust recycle model showed that, the concentrations of Pb and Cd in both kiln dust and clinker increased sharply after recycling of kiln dust in steady state. Under unstable conditions, the concentrations of Pb and Cd in kiln dust increased, as well as the heavy metals re-entering the cement kiln. [ABSTRACT FROM AUTHOR]

A dead-time compensator robust H∞ state feedback controller (DTC-H∞-SFC) for the temperature control in a precalciner of a cement rotary kiln is designed. A mathematical model of the process under study with ARMAX structure was obtained. A dead-time compensator robust H∞ state feedback controller is therefore designed. The results of the comparative evaluation of the DTC-H∞-SFC vs. DTC+PI designed controllers showed that the DTC-H∞-SFC gives improved performance of the control system. [ABSTRACT FROM AUTHOR]

This study presents novel lightweight periclase-composite (Mg 8-x Fe x + y Al 16-y O 32) spinel refractories (LPSR) for the high temperature zone of cement rotary kilns. The LPSR was prepared by using microporous magnesia aggregates instead of sintered magnesia aggregates in traditional periclase-composite spinel refractories (TPSR). Hercynite-corundum composite aggregates, as well as microporous magnesia aggregates with a median pore size of 3.50 μm and a 20.1% lower bulk density than those of the sintered magnesia aggregates were used as raw materials. The microstructures, fracture behavior and strength of the LPSR in contrast with those of the TPSR were determined by SEM and three-point bending tests. After substituting the microporous magnesia aggregates for the sintered magnesia aggregates, a rougher surface of the microporous aggregates and wider transition-layer containing a solid solution spinel phase at the microporous magnesia aggregate/composite spinel aggregate interfaces were observed. Thus, a better bonding at the microporous magnesia aggregate/matrix interfaces as well as of the microporous magnesia aggregate/composite spinel aggregate interfaces was achieved. The wider transition-layer and better interfaces impeded crack propagation along the aggregate/matrix interface and increased the percentage of crack propagation within the aggregates. Thus, the mechanical strength of the LPSR was significantly enhanced. Compared with the TPSR, the LPSR had a lower bulk density of 2.56 g/cm3, but also a higher apparent porosity of 27.8% and a higher compressive strength of 46.4 MPa. [ABSTRACT FROM AUTHOR]

Reliability is one of engineering indicators for describing the performance of an item or system by probability functions. Reliability is defined as the rob ability that an item or system is capable of performing its intended function in a specified time under given working conditions. Modern industry has property of contrast and fastness of products development, so that the high costs that occur because of failure machines due to failure. Therefore, analysis reliability is an important factor from point of view of the factory managers and the costumer. This research focuses on studying and evaluating the reliability of one of production system factory as a basis to study the reliability of systems and the ways of calculating it which consists of A) Failure Data collection, B) Failure representation, simulation and drawing graphically the histogram and Probability plot in order to calculate Time to Repair (TTR) and Time Between Failure (TBF), C) Calculate the β-value of weibull distribution for the plant, D) Analyzing the charts to determine the age stage from parts and to calculate the optimistic prediction maintenance time, and E) Analyzing the effect of failure mode in order to calculate the risk estimation. Data analysis has been done with the support of a computer aided program. It is clear from the analysis of the data of the plant that for Kiln and some components of department are in the third stage (last stage) of their cycle life, which is the wear-out and aging stage. This is due to the β-value of weibull distribution which was β=4.22 so that we focus more on the analysis of their data as a case-study for the factory. [ABSTRACT FROM AUTHOR]

Copyright of Ceramica is the property of Associacao Brasileira de Ceramica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this work is to deepen the understanding of the aerodynamics of a diffusion flame in a rotary cement kiln. The kiln is a rotary with a cylindrical shaped, long and equipped with a burner, and it is the seat of a diffusion flame with an axisymmetric turbulent jet. The kiln has a capacity of 8,000 Nm3 to 13,000 Nm3 of natural gas and primary air at T=25°C which interacts with a secondary hot air volume at T=800 °C. The aerodynamic modelling of the furnace is achieved using the turbulence model RNG k-e, which is able to handle the turbulence and capture the vortex shedding process. The Ansys/Fluent code, based on the finite volume approach to solve the Reynolds averaged Navier-Stokes (RANS), was used in this study. The interactions between turbulence and diffusion flame were handled by the PDF (Probability Density Function) approach. The numerical simulations have been validated by experiments from the kiln considered. Based on the findings obtained, it is concluded that the recirculation zone seems of paramount importance when combustion is taken into account because the reverse flow improves the flame stability and affects the combustion efficiency. In addition, limiting the secondary air flow through the furnace is major to improve combustion and avoid disturbing the advancement of the material along the kiln. [ABSTRACT FROM AUTHOR]

Free lime (f-CaO) content is a crucial quality parameter for cement clinkers in rotary cement kiln. Due to lack of hardware sensors, f-CaO content in cement clinker is mostly obtained by offline laboratory measurement, making timely control rather difficult and even impossible. In this work, a soft sensor approach named as support vector machine ensemble (ESVM) model is proposed to estimate f-CaO content. The process data employed to train and test the model were collected from a cement plant in China, covering a time span of about 30 days. The raw data were preprocessed by filters and time-series matching. The processed data were then clustered by fuzzy c-means clustering algorithm to capture process features at different operating conditions. For each individual cluster, a base SVM regressor was trained to estimate f-CaO content. Finally, an ensemble model consisting of four base SVM regressors was established to estimate f-CaO content at multifarious process conditions. The effectiveness of the proposed ESVM model was investigated by comparing it with manual measurements and other models available in literature. The results demonstrate that the proposed ESVM model achieves improvements in model accuracy as well as generalization capability. The proposed ESVM model has a broad application space in cement production process for automatic monitoring of f-CaO content. • A novel SVM ensemble model for cement clinker quality estimation is developed. • Process features at various operating conditions are captured by the model. • The effect of time lag between inputs and output is considered in the model. • The model is compared with soft sensor models available in literature. • The prediction accuracy and generalization ability of the model are improved. [ABSTRACT FROM AUTHOR]

The cement industry is one of the largest pollutant emitters. One way to cope with high pollutant emissions is to co‐combust biomass with pulverized coal. A mathematical model was developed, which is detailed enough to consider the complex physical and chemical behavior of the co‐combustion process but simple enough to perform simulations with a real geometry of cement rotary kiln within reasonable time. Numerical simulation with a 20‐% share of pulverized biomass of total fuel heating value was performed. An industrial rotary kiln geometry was simulated; temperature and velocity fields along with mass fractions of released volatiles and combustion products were analyzed. The model allows better insights in the co‐firing process with the main goal to reduce CO2 emissions by optimizing the combustion process inside the rotary kiln. [ABSTRACT FROM AUTHOR]

An in-depth understanding of the rings growth behaviors and formation mechanism is helpful for process parameters optimization to control the growth of rings and reduce breakdown ratio of the rotary kiln. This study quantitatively characterized the mineralogical characteristics of the rings within an ore pre-reduction rotary kiln through X-ray diffraction (XRD-Rietveld) and field emission scanning electron microscope (FESEM) coupled to an energy dispersive X-Ray spectrometer (EDS). The results indicated that the rings in the kiln have a distinct layered structure which can be divided into the dense layer and the loose layer. The mineral composition of the rings is hematite (16.6%), magnetite (29.6%), spinel (33.6%), and diopside (20.2%). Mineral evolution and consolidation mechanism of the dense layer and the loose layer were further studied through a series of experiments with various roasting temperature, roasting time and alkali metal contents. Research findings showed that the mass of the liquid phase increased as the roasting temperatures rise, and the roasting temperature was deemed to the main factor of solidification strength. The results also confirmed that the addition of Na 2 O contents in the raw material will not only help to increase the liquid contents and the compressive strength, but also improve the fluidity of the liquid phase. In all, a "layer-by-layer" formation mechanism of the rotary kiln for pre-reduction was proposed based on the experimental results and theoretical analysis. Unlabelled Image • Spinel and diopside are newly formed products in the rings. • The structure of the rings can be divided into the dense layer and the loose layer. • Na 2 O could increase the liquid contents and promote the growth of rings. • A layer-by-layer formation mechanism of the rings for pre-reduction was proposed. [ABSTRACT FROM AUTHOR]

The cement industry is ranked first among the energy consuming industries. This is the reason why the efficient use of energy has always been a priority in that kind of industries. This process requires very high temperatures in order to initiate the reaction and phase changes required to form the complex of mineral compounds that confer to the cement its unique properties. Significant energy consumption and greenhouse emissions are caused by the overall process. Heat losses occur through different process levels, such as furnace casing, exhaust, clinker outlet, dust, etc. The heat loss through the furnace shell by radiation and convection is very important. This work has been devoted to the evaluation of radiation and convection heat losses in the process; it includes the acquisition and use of data for evaluation and heat loss at the furnace shell. The results indicate that almost 4% of the energy supplied to the furnace is lost through the wall. Therefore, improved energy efficiency can reduce cement production costs that can be achieved through energy management, by using more efficient processing equipment, replacing old facilities with new ones or by new types of cement production processes, carrying out the research and development needed to develop new cement plants. An energy balance has been made on a kiln of a Moroccan process of cement production, based on data measured on it, showing the amount of energy loss and the importance of development of a new system of energy saving. [ABSTRACT FROM AUTHOR]

Cement rotary kiln is the main device utilized for industrial cement production in large scale. The shell temperature can reach several hundred Celsius degrees. Therefore, a thermoelectric waste heat recovery system can be utilized based on its advantages. In this study, an arc shaped absorber is designed and temperature distribution along the absorber circumference is obtained numerically. The calculated temperature is considered as the hot side temperature of thermoelectric generators (TEGs) that recover thermal energy on the absorber. In situations where the heat is free, the metric for designing a thermoelectric system is to reach the maximum power output. In order to reach regional optimal power from parametric design, the absorber length is divided into several sections. For efficient design of the TEG in each section, effect of significant parameters such as leg length and fill factor of the TEG and thermal resistance of the heat sink are studied. Effect of variation of the temperature and velocity magnitudes of the air next to the heat sinks is considered on thermal resistance and performance of the pin-fin heat sinks along the absorber. β-phase zinc antimonide (Zn 4 Sb 3) and magnesium tin silicide (Mg 2 SiSn) are chosen as the p- and n-leg thermoelectric materials of the TEGs, respectively, because of their relatively high performance over the considered range of operating temperature. The results show that, staggered arrangement of the pin-fins is more effective for higher power generation and system performance compared to in-line arrangement of the fins. Moreover, by evaluation of the results, maximum matched power output in each section versus the fill factor and leg length can be determined in this study. The results show that, low fill factors between 0.05 and 0.2 can provide relatively a same maximum power as high fill factors. Furthermore, an economic evaluation is carried out to find optimal design of the TEG device for highest power generation and lowest investment cost. Various parameters of the cost function, such as cost of the bulk raw material (C B), manufacturing cost associated with processing bulk material (C M,B), areal manufacturing cost (C M,A), heat exchanger cost (C H-EX), balance of the system cost (C BoS) and the installation cost (C I) are taken into account in this study. The results show dominant parameter in the system cost is the heat sink. • The best place along the rotary cement kiln is found for waste heat recovery purpose. • Design and optimization of arc shaped thermoelectric system around the kiln is done. • Temperature distribution on absorber as hot side reservoir of TEG is obtained by CFD. • A mathematical model by FEM is developed to design the arc shaped TEG system. • Various design parameters of TEG and pin-fin heat sink are studied. [ABSTRACT FROM AUTHOR]

Five models that predict the Mean Residence Time (MRT) of solids in a rotary kiln are tested on three materials and validated experimentally. Furthermore, the influence of the kiln rotational speed and incline on the MRT was investigated. Determination and modelling of the MRT in pilot-scale reactors (length/diameter = 10.5) without a discharge dam, has not been studied yet. The prediction of the MRT with existing models gave poor results, therefore adaptions were necessary. The Saeman's model that was corrected with a new boundary condition decreased the mean absolute error on the experimental results from 54.5% to 15.3%. While the empirically corrected models of Saeman, Sullivan, Chatterjee and U.S. geological survey predicted the solid's MRT with an error <10% for kiln inclinations <1°. It was concluded that the MRT and the kiln's rotation relate inversely proportional, while the kiln's inclination relates logarithmically to the MRT. Unlabelled Image • MRT can be determined accurately by empirically adapting different models. • The modified Sullivan's model works best for the prediction of the MRT. • Relation between MRT and kiln rotation at constant incline is inversly proportional. • Relation between MRT and kiln incline at constant rotation is logaritmic. [ABSTRACT FROM AUTHOR]

Cement clinker calcination in rotary kiln is an energy intensive process. Heat recovery from the kiln shell surface is a potential way to improve energy efficiency to make cement production cleaner and more sustainable. In this work, methods were proposed to assess the heat loss through the kiln shell and its influencing factors, using an industrial cement kiln in China as study case. By use of infrared thermography, the shell temperature and the heat loss through kiln shell were monitored for 19 days. Calculation shows that the daily heat loss through kiln shell in the calcination zone of the investigated kiln is about 140 GJ, and the heat losses by radiation and convection are comparable, accounting for 54% and 46%, respectively. Five main operating variables that greatly affect the heat loss are identified jointly by Random Forest and Pearson correlation coefficient. Results of this work will help company administrators create a strong awareness about improving energy efficiency of the kiln system, so that appropriate strategies are designed to reduce the heat loss through kiln shell. The work can also contribute to a better understanding of rotary kiln operation to reduce the heat loss. The work makes the cement clinker calcination process more sustainable by laying the foundation for recycling or reducing the waste heat loss through kiln shell. • Heat loss through a cement rotary kiln shell in the calcination zone is assessed. • Heat losses through radiation and convection of the investigated kiln are comparable. • Economic analysis of the heat loss through kiln shell is performed. • Influencing factors on heat loss through kiln shell are analyzed using RF and PCC. • This work is helpful to make clinker production process cleaner and more sustainable. [ABSTRACT FROM AUTHOR]

Highlights • A full-scale oxy-fuel cement rotary kiln of 3,000 ton/year clinker capacity has been numerically investigated. • The CFD study was part of an iterative optimization procedure with the process modelling of the whole cement plant with full oxy-fuel capture. • The optimal rotary kiln operating conditions has an oxygen concentration of 52.1% in the primary oxidizer stream. Abstract Oxy-fuel combustion has been shown to be an attractive technology to be implemented in cement production with CO 2 capture from a process point of view. Due to the market situations and future perspectives it is necessary that the technology can be retrofitted into existing plants. As part of the H2020 EU project CEMCAP, the study presented here investigates the retrofitting of oxy-fuel combustion technology on a typical full-scale cement rotary kiln of 3000 ton/year clinker capacity. The flame generated by a commercial burner has been modelled by CFD with a seven steps combustion reaction model, the k-omega SST turbulence model, and the discrete ordinates radiation model with the Weighted Sum Grey Gas model. The burner is composed of an annular outlet where coal is fed and nozzles from which angled high velocity jets generate a swirling motion for flame stabilization and mixing purposes. As in all rotary cement kilns, a high temperature low velocity secondary oxidizer stream coming from the clinker cooler flows coaxially to the burner in the kiln for heat efficiency purposes. A flame developing in air has been used as a reference case and several oxy-fuel flames have been characterized and compared. The oxy-fuel inlet parameters that are varied in the study are the oxidizer composition and flow rates in both the primary and secondary streams. The work presented is part of an optimization procedure based on iterative interaction with the process modelling of the whole cement plant with full oxy-fuel capture (not presented in this article). With retrofit application in mind, the objective was to reproduce a heat radiation profile to the clinker equivalent to that obtained in the air reference case. The optimized oxy-fuel case is characterized by a primary burner oxidizer of lower flow rate, but with higher oxygen concentration of up to 52.1% to generate the necessary heat in the near burner region. [ABSTRACT FROM AUTHOR]

A coating collapse occurs when large parts of coating break away from the refractory of a rotary kiln in a cement plant. If the collapse is more conspicuous, the cooler may become filled with excessive material, causing the clinker transport systems to overload and the temperature in the cooler outlet to rise excessively. An unstable coating quickly causes problems with the refractory material, resulting in a loss of energy that disturbs the stable operation of the kiln. Variable amounts of coating in the burning zone also influence the kiln torque. A coating collapse is normally detected by the operator through the trend curve of kiln drive amps. This paper explains the application of empirical mode decomposition with a fuzzy inference system and a fuzzy neural network to identify a kiln coating collapse and predict refractory failure in the cement process. The results show that the proposed method improved considerably upon the original. [ABSTRACT FROM AUTHOR]

• A dynamic time-delay calculation algorithm based on MI and adaptive sliding window (MIDTA) is proposed. • MIDTA algorithm is used to solve the problem of long time-delay of cement kiln. • An algorithm of residual network and bidirectional novel gated recurrent unit (ResNet-BiNGRU) is proposed. • A Gaussian-weighted multi-model fusion method is proposed. • MIDTA-ResNet-BiNGRU multi-model fusion algorithm can be used to measure the temperature of cement rotary kiln with high precision. China's cement production energy consumption accounts for more than 10% of the country's total energy consumption, and its emissions account for about 60% of the country's industrial emissions. The temperature of a cement rotary kiln directly affects the quality of the final product, the energy consumption of a plant, and emissions. Therefore, it is necessary to measure, to a high degree of accuracy, the temperature of a cement rotary kiln to reduce energy consumption, emissions, and improve product quality. However, the conditions in cement kilns are complex and variable; and there are large time-delays, while temperatures are affected by historical working conditions, making temperature measurement extremely difficult. In this paper, a modelling algorithm with a residual network and a bidirectional novel gated cycle unit is used to predict the clinker exit temperature of the rotary kiln. In addition, to solve the problem of large time-delays in cement kilns, a dynamic time-delay calculation algorithm based on Mutual information and adaptive sliding windows is proposed for time series data reconstruction, and finally a Gaussian-weighted multi-model fusion is applied to the prediction results for cement rotary kilns that produce a wide range of working conditions. To verify the advantages and feasibility of the proposed method, experimental validation is carried out using original production data from a large cement manufacturing enterprise in South China. The results demonstrate that the single step prediction time of the presented approach is 0.66 s, which can predict cement kiln temperatures quickly and accurately, compared to a single conventional forecasting algorithm, the average temperature difference dropped from 11.76 °C to 3.51 °C, R2 increased from 0.43 to 0.89, 94% of the depicted temperature errors are at ± 10 °C This will provide an effective solution for online decision-making during actual cement production. [ABSTRACT FROM AUTHOR]

Alkali vapor release during alternative fuel combustion severely attacked bauxite-SiC refractories in cement rotary kiln. The present work investigated the effect of chemical compositions on microstructure, refractoriness under load and alkali attack resistance of bauxite-SiC refractories by the incorporation of different amount of micron sized α-Al 2 O 3 and microsilica powders. Results showed that the addition of α-Al 2 O 3 improved the refractoriness under load of specimens, whereas alkali attack products, e.g. KAlSiO 4 and KAlSi 2 O 6 phases were largely formed in the alumina-rich matrix, leading to the large volume expansion and cracks formation. By comparison, the addition of microsilica resulted in the decrease of refractoriness under load. Moreover, the volume expansion during alkali exposure can be controlled by increasing amounts of microsilica, which was attributed to the fact that less K-aluminosilicate phases mentioned above and more liquid were formed. In this case, the newly formed liquid blocked up some pores and further prevented the penetration of K vapor into the matrix. Alkali attack resistance and refractoriness under load of bauxite-SiC refractories can be balanced when the mole fraction of Al 2 O 3 was approximately 0.6 in the matrix of refractories. [ABSTRACT FROM AUTHOR]

• The co-firing tests of the RDF/petcoke/biomass/hydrogen in the pilot-scale facility were conducted. • The CFD model of the multifuel rotary kiln burner was established and validated. • The possibility of the high shares of RDF combustion in the rotary kiln has been evaluated. • An influence of hydrogen on RDF combustion in the full-scale cement kiln burner was assessed. Rotatory kilns fed with fossil fuels, which are widely used in cement industry, are responsible for significant CO 2 emissions to atmosphere, increasing the stress on the environment. Substantial energy consumption, associated with the cement production process, leads to significant environmental and economical footprint in Europe and beyond, thus measures for reducing fossil fuel usage and decreasing an environmental impact are sought. One of the implemented measures is the substitution of the typical fossil fuels used in the kilns (coal or petcoke) by alternative fuels, such as biomass, RDF (refuse-derived fuel), sewage sludge or MSW (municipal solid waste). The objective is to reduce the greenhouse gas emissions, achieve the circular economy goals and decrease the production costs. This study presents the results of the pilot-scale tests (conducted in the 1 MW combustion facility at the Institute of Power Engineering), CFD simulations of both pilot-scale and full-scale burner for the cement rotary kiln. On the basis of the experimental data, a numerical investigations of the 1 MW pilot facility was made and validated. The numerical modelling, in a pilot-scale burner, was also intended to check the possibility to co-fire petcoke (as a base fuel) with alternative fuels such as MSW, biomass and hydrogen. Finally, the combustion in the industrial scale 75 MW cement rotary kiln burner was numerically analysed to analyse the conditions inside the reference cement installation and to propose a possible solutions to allow substitution of fossil fuels with RDF. The results showed that it is possible to co-fire a high shares of the alternative fuels in the rotary kiln without the negative effects on the combustion performance. It was also found, that the base fuel (petcoke) can be almost completely replaced with the alternative fuels such as RDF or biomass, while addition of the hydrogen to the fuel mixture can even improve the combustion characteristics. [ABSTRACT FROM AUTHOR]

• The work herein presented analyses a failure that occurred in a rotary satellite kiln located in a cement production line. • The failure was recently detected in a programmed overhaul. • The rotary satellite kiln was redesigned to improve the equipment life expectancy. • The maximum stresses present in the redesigned structure were reduced by 57%. • The fatigue life expectancy of the redesigned structure is 5.7 times longer than that of the original design. The work herein presented aims to analyse the existing failures in a rotary satellite kiln of a cement production line, more specifically, the last 32 m of the equipment, which is responsible for the abrupt forced cooling of the clinker (cement component) throughout satellite coolers. This device undergoes pronounced temperature variation and, consequently, is subjected to high thermal induced stresses which are superimposed, due to its large dimensions, to structure's deadweight and the influence of a reduced angular rotation speed. The main failures observed in the equipment were the existence of cracks along the circumferentially weld bead of the outside nozzle to the kiln ferrule and the cracking of the kiln ferrule near the openings that allow the clinker to exit into the satellite coolers. The solution proposed to mitigate these failures was the implementation of reinforcement collars around the critical nozzles, in order to achieve a better local distribution of stresses. Through the numerical simulations carried out using the Finite Element Method, it was verified that the average value of the first principal stress without the reinforcement collars was about 176 MPa. In the simulation with the implementation of the reinforcement collars, this value decreased to 75 MPa (approximately 57% lower). This should increase the equipment's durability. [ABSTRACT FROM AUTHOR]

In India, chromite is used for making magnesia chrome bricks due to its low modulus of elasticity. But the use of magnesia chrome bricks in the sintering zone of cement rotary kilns causes environmental pollution due to the formation of Cr+6 compounds. In order to meet the above challenges and to satisfy the operational demands due to use of alternative fuels, now-a-days, galaxite spinel is being used in place of chromite as a chrome free material. Galaxite is not available in nature and electro fusion is the main process by virtue of which it is industrially manufactured. However, the main drawback of electro-fusion process is both time and energy consumption. In such a backdrop, the present work has been carried out which describes the synthesis of galaxite by plasma fusion process and also the characterization of its refractory properties for application in cement rotary kilns. This alternative process is absolutely new, faster in approach and also economically viable. The developed magnesia galaxite brick shows higher performance rate and is also economically cost effective as compared to the conventional magnesia chrome and magnesia galaxite bricks, presently available in the market. [ABSTRACT FROM AUTHOR]

Volatile organic compounds (VOCs) are major precursors of ozone (O 3) and secondary organic aerosols (SOA), which degrade air quality and pose a serious risk to human health and ecological systems. Previous studies on the emission characteristics of VOCs have predominantly focused on petrochemical and solvent-using sources, while localized studies on the cement industry are scarce in China. Field measurements for four cement plants were carried out in this study to investigate the emission levels, source profiles, and secondary pollutant generation potential of 98 VOCs species emitted from rotary and shaft kilns in China. Furthermore, a species-differentiated VOCs emission inventory was compiled for the Chinese cement industry in 2019. The results demonstrated that the mass concentration of VOCs emitted from shaft kiln was more than 20-fold higher than that emitted from rotary kilns, and the alkanes was the dominant species (56%) in shaft kilns, while oxygenated VOCs (OVOCs) and halocarbons were the main species in rotary kilns. Moreover, alkenes & alkyne were the dominant contributors to ozone formation potential (OFP) in shaft kilns, whereas alkenes & alkyne and OVOCs were comparable and prominent contributors in rotary kilns. In contrast, secondary organic aerosol potential (SOAP) for the two types of kilns was dominated by aromatics. In 2019, approximately 18.18 kt VOCs were emitted from cement production and were found to be largely concentrated in the southeast and central provinces of China. Considering the influence on environmental conditions, high OFP-contributing species in cement kilns are suggested to be a priority in the pollution mitigation of O 3. This study provides a new, comprehensive, and reasonable cognition of the current VOCs emissions from both rotary and shaft kilns in China, which will aid in a better understanding of VOCs emission characteristics and guide future policy-making. [Display omitted] • Oxygenated VOCs (32%) and halocarbons (28%) are the main species in rotary kilns. • Alkanes is the dominant species (56%) in shaft kilns. • VOCs emission factors of the shaft and rotary kilns are 0.32 and 0.01 g/kg-clinker. • About 18.18 kt VOCs emissions were emitted from cement kilns in China in 2019. • Emissions are highly concentrated in the central and southeast provinces of China. [ABSTRACT FROM AUTHOR]

High strength or construction bloating clay is widely used in construction operations especially in construction of roads, bridges, airfield pavement. It replaces crushed stone as an aggregate. Technology of high strength bloating clay requires essential changes in its stoving curve in comparison with the production of light bloating clay. It is shown that in order to solve an urgent construction problem of bloating clay release it is necessary to conduct monitoring of temperature pattern in a rotary kiln in several distinctive cross sections and conduct management of a kiln as an object with distributed constants with the use of several, especially three, concentrated control actions. The developed mathematical model of stoving process and methodology of computing experiment, exemplified by the 40×2,5м kiln, allowed to find operating areas of condition and management of an automated object, focused on bloating clay release with assigned strength. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid method for fault diagnosis of rotary kiln based on a Fuzzy Levenberg-Marquardt (FLM) and Genetic Algorithm (GA). The huge datasets with great number of fuzzy rules will not only significantly slow the learning phase, but also confuse the classifier due to unusable or redundant rules. To overcome this problem, a selection method is proposed for identifying the relevant rules and removing the irrelevant, redundant or noisy ones. In other words, the goal of FLM-GA method is to improve classification accuracy with an appropriate rule subset. However, a key aspect of our framework relies on the concept of condition based on maintenance (CBM) in order to make better informed maintenance decisions. Two methods are investigated and compared to determine the best one. Finally, an experimental case is conducted to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Principal Component Analysis (PCA)-based approach for fault detection is a simple and accurate data-driven technique for feature extraction and selection. However, PCA performs poorly if the data used has nonlinear characteristics where this type of data is widely present in most industrial processes. To overcome this drawback, Kernel PCA (KPCA) is an alternative technique used to work on this type of data but it requires more computation time and memory storage space for large-sized data sets. Many size reduction techniques have been developed to select the most relevant observations that will be employed by KPCA. This, known as Reduced KPCA (RKPCA), consequently requires less computation time and memory storage space than KPCA. Besides, it possesses the advantages of both KPCA and standard PCA. In this paper, a reduction in the size of a data set based on a multivariate variogram is proposed. According to its conventional formalism, the uncorrelated observations are selected and kept to form a reduced training data set. Afterward, the KPCA model is built through this data set for faults detection purposes. The proposed RKPCA scheme is tested using an actual involuntary process fault and various simulated sensor faults in a cement plant. Compared to other RKPCA techniques, the developed one yields better results. • A novel Reduced Kernel Principle Component (RKPCA) is proposed. • RKPCA method is addressed to solve the high computation time and storage space introduced in the ordinary KPCA. • The developed technique avoids the highly correlated observations using variogram to build a reduced size of the training dataset. • RKPCA is applied to AEK cement rotary kiln process, to evaluate the efficiency of the proposed model in fault detection. [ABSTRACT FROM AUTHOR]

Abstract: Some of the most serious problems related to the reliability of cement kiln are bearings failures and damages to the roller carrying surface, both of which often occur without apparent warnings. Although the root causes of these problems can be understood, their on-time detection still remains a problem. This paper presents a new methodology for proactive monitoring of such machines and provides on-line information pointing to potential failure. Both, theoretical and practical considerations are discussed. [Copyright &y& Elsevier]

A new form of periclase-forsterite refractory is presented as an alternative to magnesia-spinel objects used for lining rotary kilns for firing cement clinker. [ABSTRACT FROM AUTHOR]

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Abstract: A first principles model of a cement kiln is used to control and optimize the burning of clinker in the cement production process. The model considers heat transfer between a gas and a feed state via convection and radiation. Furthermore, it contains effects such as chemical reactions, feed transport, energy losses and energy input. A model predictive controller is used to stabilize a temperature profile along the rotary kiln, guarantee good combustion conditions and maximize production. Moving horizon estimation was used for online estimation of selected model parameters and unmeasured states. Results from the pilot site are presented. [ABSTRACT FROM AUTHOR]

Abstract: We present a new approach to the fast determination of structural deformations and stresses in the refractory-reinforced body of a cement rotary kiln. The proposed approach builds on a comprehensive neuro-finite element simulation of the kiln shell. Three-dimensional stresses and deformations in the rotating tubular shell are first determined for a finite number of input vectors using a validated finite element model of the kiln. The resulting data are then used to train a Multi-Layer Perceptron (MLP) Neural Network which would predict – accurately enough – values of stresses and deformations throughout the kiln body for any given input vector. The resulting neural simulator would serve as a replacement for the computationally expensive cost-function evaluators that are traditionally used in numerical optimization algorithms. To demonstrate the applicability of the proposed approach, we analyze a typical rotary kiln using the Neuro-FE method and compare the results with those obtained from traditional method. [Copyright &y& Elsevier]

Abstract: In this paper, we use system identification methods for abnormal condition detection in a cement rotary kiln. After selecting proper inputs and output, an input–output model is identified for the plant’s normal conditions. A novel approach is used in order to estimate the delays of the input channels of the kiln before identification part. This method eases the identification since with determining the input channels delays, the dimension of search space in the identification part reduces. Afterward, to identify the kiln’s model, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOcally LInear MOdel Tree (LOLIMOT) algorithm which is an incremental tree-structure algorithm. Finally, with the model for normal condition of the kiln, the incident of abnormalities in output are detected based on the length of duration and magnitude of difference between the real output and model’s output. We distinguished three abnormal conditions in the kiln, two of which are known as common abnormal conditions and another one which was not characteristically known for cement experts either. [Copyright &y& Elsevier]

• A CCS clustering with multiple CO 2 industrial emitters and a shared capture infrastructure is developed. • Ca-looping CCS system in a cement plant is used to centralize carbon capture. • A value of 20 €/ton CaO, (25.5 €/tonCO 2) allow economic feasibility of the concept. • This study is a first approximation as there are many and very uncertain variables that influence the feasibility. • If carbon market cost is higher than 30 €/ton CO 2 profitability increases. The concept of CCS cluster brings together multiple CO 2 industrial emitters using shared capture and/or transportation infrastructure and offers several advantages for network partners compared with point-to-point individual projects. It reduces costs for CCS, and enables CO 2 capture from small volume industrial facilities. The proposed concept connects a cluster of industrial sites with significant heat demands with a cement plant through the implementation of a Ca-looping CCS system. This system treats the flue gas from all the industrial emitters in independent boiler/carbonators while uses the kiln furnace as calciner for the cement and the capture plant. The carbonator reactors located in each one of the industry sites are fed by CaO from the cement plant to capture the CO 2 content of their own flue gas. After carbonation reaction, the exhaust sorbent is transported back to the cement plant for regeneration in the kiln furnace. The aim of this work is to analyse the techno-economic feasibility of the proposed Ca-looping CCS cluster. The economic assessment, assuming 20 €/ton CaO and carbon market 30 €/ton CO 2 points out the feasibility of this kind of centralized carbon capture system to handle the carbon from small emitters. Results show that the operating costs of small companies that use coal or natural gas reduce from 21.3 M€ to 18.8 M€ or from 25.5 to 23.0 M€. For the cement industry this income lessens its operating costs 1.9 M€ lower than a reference situation where CCS is only implemented in cement plant. [ABSTRACT FROM AUTHOR]

The accurate recognition of the burning state of cement rotary kiln is of great significance to improve the qualified rate of clinker quality, ensure the safe operation of rotary kiln and reduce the production coal consumption of enterprises. In this paper, a recognition method of the burning state of cement rotary kiln based on Otsu-Kmeans flame image segmentation and support vector machine (SVM) was proposed. Firstly, the flame image of the clinker burning core region in the rotary kiln was obtained by using advanced vision detection technology, and then the Otsu-Kmeans image segmentation method was used to realize the effective segmentation of the target region of a flame image. The target region of flame image includes radiation region, flame burning region and high-temperature region. On this basis, 10 feature parameters of the target region were extracted as state recognition features. Then, with the one-minute statistical average value of the extracted feature parameters as input, and the three typical burning states of the rotary kiln as output, an SVM-based recognition model for the burning state of the rotary kiln was established. Finally, the established SVM state recognition model was used to classify the flame image, and the two parameters in the model were optimized by the K-fold cross-validation K − C V algorithm. The results show that for 30 sets of test samples, the SVM-based burning state recognition model can correctly identify 28 sets of samples, which provided a feasible method for the recognition of the burning state of cement rotary kilns. [ABSTRACT FROM AUTHOR]

The effect of raw material composition and additions of water-soluble polymers on the drying kinetics of raw slurries, the strength of granules forming in the drying zone, and the self-adhesion properties of dust formed in the cold zone of the kiln are considered. The possibility is demonstrated of reducing dust carry-over from a rotary roasting kiln as a result of introducing additions of commercial grade lignosulfonates, a latex mixture or sodium carboxymethylcellulose into the slurry. [ABSTRACT FROM AUTHOR]