Rotary Kiln Research Articles

WEAR ANALYSIS OF VERTICAL COAL MILL PLATE

Vertical Coal Mill (VCM) is equipment for grinding and pulverizing coal into micron size. Rotary kilns then use the powders as fuel burners. The VCM has a housing section equipped with a lining plate as a wear and tear protector. The housing comprises segments with similar thicknesses and materials that are severe to wear due to gas-carrying solid particles hitting the surface. The specific material resilient to abrasion is required to extend operating services. This study aims to determine the wear properties of Hardlite and Everhard C500LE on the lining plate. Characterization of the samples, including composition, microstructure, hardness, and wear test. Microstructure observation shows that the more extensive and profound the wear marks formed, the higher the volume of exfoliated material. The test results show that the Fe-Cr-C hard-facing alloy significantly affects the hardness value of a material and its wear resistance. The hardness test results showed an average Hardlite overlay layer hardness value of 703 BHN (N/mm2), almost double that of Everhard C500LE.

Rotary Kiln, a Unit on the Border of the Process and Energy Industry—Current State and Perspectives

A rotary kiln is a unique facility with widespread applications not only in the process industry, such as building-material production, but also in the energy sector. There is a lack of a more comprehensive review of this facility and its perspectives in the literature. This paper gives a semi-systematic review of current research. Main trends and solutions close to commercial applications are found and evaluated. The overlap between process and energy engineering brings the opportunity to find various uncommon applications. An example is a biogas plant digestate treatment using pyrolysis in the rotary kiln. Artificial intelligence also finds its role in rotary kiln control processes. The most significant trend within rotary kiln research is the waste-to-energy approach in terms of various waste utilization within the process industry or waste pyrolysis in terms of new alternative fuel production and material utilization. Results from this review could open new perspectives for further research, which should be focused on integrated solutions using a process approach. New, complex solutions consider both the operational (mass calculations) and the energy aspects (energy calculations) of the integration as a basis for the energy sustainability and low environmental impact of rotary kilns within industrial processes.

Historical Lead Smelting Slag Harmlessness and Valuable Metals Recovery: A Co-Treatment of Lead Slag and Zinc-Bearing Material in Rotary Kiln

The harmless treatment of historical lead smelting slag (LSS) is of significance to ecological and environmental protection, but it is still challenging in terms of the economic feasibility of alone processing due to the low content of valuable metals. Here, we performed an industrialized test with a co-treatment of LSS and zinc oxide ore in a rotary kiln to evaluate the economic feasibility and solidification effect of harmful elements. The results revealed that more than 70% of Zn and Pb were recovered from LSS in the form of dust, while the nonvolatile part of Pb, Zn, and Cd were solidified in gangue as complex silicate phases. The nonvolatile part of As came into being Fe-As intermetallic compound which was encapsulated by gangue particles or was solidified in silicate phases. The entirely enclosed structure of water-quenched slag plays an important role in the stability of slag. The TCLP and SNAL leaching tests demonstrated the high stability of water-quenched slag. A zinc oxide ore addition of 20% was recommended for energy consumption and processing capacity. Our findings highlight that the valuable metals not only can be effectively recovered but also harmful elements are solidified in gangue, providing an economical and feasible technical route for the treatment of historical LSS.

Use of Multiscale Data-Driven Surrogate Models for Flowsheet Simulation of an Industrial Zeolite Production Process

The production of catalysts such as zeolites is a complex multiscale and multi-step process. Various material properties, such as particle size or moisture content, as well as operating parameters—e.g., temperature or amount and composition of input material flows—significantly affect the outcome of each process step, and hence determine the properties of the final product. Therefore, the design and optimization of such processes is a complex task, which can be greatly facilitated with the help of numerical simulations. This contribution presents a modeling framework for the dynamic flowsheet simulation of a zeolite production sequence consisting of four stages: precipitation in a batch reactor; concentration and washing in a block of centrifuges; formation of droplets and drying in a spray dryer; and burning organic residues in a chain of rotary kilns. Various techniques and methods were used to develop the applied models. For the synthesis in the reactor, a multistage strategy was used, comprising discrete element method simulations, data-driven surrogate modeling, and population balance modeling. The concentration and washing stage consisted of several multicompartment decanter centrifuges alternating with water mixers. The drying is described by a co–current spray dryer model developed by applying a two-dimensional population balance approach. For the rotary kilns, a multi-compartment model was used, which describes the gas–solid reaction in the counter–current solids and gas flows.

Modeling operational cement rotary kiln variables with explainable artificial intelligence methods – a “conscious lab” development

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.

Multi-objective optimization of explosive waste treatment process considering environment via Bayesian active learning

A fluidized bed is a next-generation explosive waste treatment reactor that is safer and emits less pollutants (e.g., NOx) than a rotary kiln. When a fluidized bed reactor is used to treat explosive waste, the design and operating conditions significantly impact the emission of pollutants. It is possible to reduce the pollutants to below the regulation level (90 ppm) through finding ideal design and operating conditions. However, there are many practical challenges, such as cost limitations. In addition, owing to the characteristics of explosive waste, designing and optimizing the process through real experiments without any guidelines is dangerous. Therefore, a computational fluid dynamics (CFD) simulation was performed to obtain high-accuracy data on the internal phenomena of the reactor first. In this situation, since a lot of variables and combinations should be considered, it is obvious to takes very long time for finding optimal point by only using CFD simulation. Thus, based on the simulation data, efficient search space exploration was performed using multi-objective Bayesian optimization and several promising points constituting the Pareto front were derived to find optimal conditions. As a result, six optimum points of operating and design conditions were obtained considering process cost and nitrogen oxide emissions simultaneously. The six Pareto solutions through above approach reduced 47.5% of NOx emission and 10.5% of cost compared to the previous studies. In addition, it is meaningful that this study could reduce optimization time even though the design conditions of explosive waste treatment process were considered.

Intermediate pyrolysis of Scenedesmus microalgae in a rotary kiln pyrolyser: Effect of temperature on bio-oil yields and composition

Intermediate pyrolysis of Scenedesmus microalgae in a rotary kiln pyrolyser: Effect of temperature on bio-oil yields and composition

Milligrams to Kilograms - Scaling Production of Cobalt Free Lithium Excess Cathode Materials through Rotary Calcination

Both Tesla and the Government of the United States have listed the elimination of cobalt and the resilience of the battery cathode supply chain as critical issues in need of advancement 1,2. This investigation answered this call to action through scaling the production of a high-performance cobalt free lithium excess cathode material using rotary calcination. The cathode in this investigation is of the chemical series Li[NixLi(1/3-2x/3)Mn(2/3-x/3)]O2 (where x = 0.25), and to our knowledge this marks the first time an investigation has demonstrated the scaling of this class of materials. In order to achieve the several orders of magnitude increase in production scale the precursor feedstock for rotary calcination required comparison of sol-gel, Pechini, and solid-state precursors routes. Viability of each precursor synthesis route required comparison of synthesis time, synthesis complexity, Thermogravimetric Analysis, Dynamic Scanning Calorimetry, X-Ray Diffraction of intermediate and final materials, as well as Galvanostatic cycling of final cathode materials. Modification and controlled decomposition of sol-gel processing was ultimately used for the scaled production of precursor powders. Once the precursor feedstocks were fed through the rotary kiln we used X-Ray Diffraction, X-Ray Fluorescence, Galvanostatic Testing, and Scanning Electron Microscopy of resultant materials to optimize rotary calcination conditions to find the pareto optimal conditions that allowed for maximized material quality, and output, with minimized energy and time costs. These materials were also compared to our baseline material, which was made in a box furnace in ambient conditions over the course of 24 hours. Synthesis conditions were also modified to allow for the inclusion rapid water quenching of final scaled material to ensure material quality.Sources: F. C. for A. Batteries, National blueprint for lithium batteries 2021–2030, (2021).E. Musk and R. Denholm, UPDATES TO 2020 ANNUAL MEETING OF STOCKHOLDERS AND BATTERY DAY EVENT, (2020).

MODAL ANALISIS PADA ROTARY KILN DENGAN MENGGUNAKAN METODE ELEMEN HINGGA

This research is based on the general damage to the rotary kiln due to continuous use. Then the results from the burned in a Rotary Kiln So we need a prevention to overcome it. Testing the vibration mode on a rotary kiln machine is a solution to overcome the limit on the use of the finite element menthod. With the completion procedure of finite element software with the step of Rotary Kiln Geometry Modeling Process, Rotary Kiln Geometry Import Process, Rotary Kiln Geometry Import Process, Material Data Input Process, Meshing Process, Determination of Boundary Conditions, Running Process, and Port Processing. The results of this study are from the finite element simulation obtained in the form of the frequency value of the natural response of the structure and the deflection due to vibrations that occur in the rotary kiln Indarung IV PT Semen Padang. And it was concluded that the vibration mode experienced by the rotary kiln has a natural frequency value, the vibration mode of the rotary kiln structure obtained a maximum value of 63.3 Hz, while the minimum value obtained a value of 41.805 Hz. The maximum deflection of the rotary kiln is obtained from the analysis results of 0.058981 mm while the minimum deflection value is 0.045 mm.

Belite cement clinker from autoclaved aerated concrete waste – A contribution towards CO2‐reduced circular building materials

AbstractThe processing of belite cement clinker in a rotary kiln at about 1000oC is a new recycling option for autoclaved aerated concrete (AAC) waste that otherwise must be landfilled. The clinker produced can partially substitute ordinary portland cement (OPC) in AAC production. Waste quantities and landfill costs are minimized, while at the same time CO2 emissions and the primary resource consumption of AAC production are reduced. The technology is currently under development. New analytical possibilities and modeling have made it possible to optimize the process conditions to such an extent that the use of belite cement clinker in aerated concrete production has already been technically tested. Particularly large effects on CO2 emissions can be achieved through the electrical heating of the rotary kiln and the coupled sequestration of the released CO2 in other secondary products such as recycled aggregate for concrete production from waste concrete. Comparable concepts for the AAC cycle are currently being worked on together with the industry partner Xella. Although decentralized plant concepts would be useful in order to minimize transportation, small plants are currently not economical according to initial estimates. In the long term, emission‐free product cycles are aimed at.

The effect of pyrolysis temperature and feedstock on biochar agronomic properties

As biochar gains popularity within agricultural applications, proper selection of feedstocks and pyrolysis conditions are crucial to maximising its added value. In this study, biochars were characterised for elemental composition, potentially toxic elements, the sum of 16 US EPA polycyclic aromatic hydrocarbons and biochar agronomic properties (pH, acid-buffering capacity, biochar stability, electrical conductivity, cation exchange capacity and water holding capacity) to provide more insight concerning biochar properties and pyrolysis parameters that influence the biochar agronomic properties. Eighteen feedstocks for biochar production were screened based on four selection criteria: moisture content, ash content, fixed carbon content and the presence of potentially toxic elements. Eight feedstocks (spent peat, woody green waste, tree bark, applewood, flax shives, spent coffee grounds, insect frass and chicken manure) were selected and processed into 24 biochars (at three pyrolysis temperatures: 450, 600 and 750 °C) using slow pyrolysis in a pilot-scale rotary kiln reactor. The results showed that feedstock and pyrolysis temperature are crucial factors for biochar composition, toxicity and agronomic properties. The sum of 16 US EPA polycyclic aromatic hydrocarbons showed a significant increase for biochars produced at 750 °C compared to those produced in the 450–600 °C range.Furthermore, some potentially toxic elements (Zn, Cu, Cr) revealed a decrease in concentration above 600 °C. It is recommended not to exceed a pyrolysis temperature of 600 °C in the reactor configuration used. Lastly, feedstock-independent models were constructed for pH, electrical conductivity and acid-buffering capacity through the biochar properties measured. These models may provide a gateway to reverse engineer biochars based on suitable feedstock and pyrolysis temperature selection.

Can statistical methods optimize complex multicomponent mixtures for sintering ceramic granular materials? A case of success with synthetic aggregates

The relationship between the proportions of multicomponent mixtures with the technological properties of ceramic granular materials (synthetic aggregates) has been studied using statistical methods. The four phases involved in the formulations have been: kaolin (K) as aluminosilicate source; cork powder (C) as organic carbon source; sodium carbonate (N) as flux and pyrite (P) as source of iron and sulfur. The Mixture Experiments - Design of Experiments (ME-DOE) has been the statistical methodology applied from the initial configuration of the 36 starting formulations to the final validation of the models and optimums. After granulation, artificial aggregates have been obtained by sintering in a rotary kiln, and their main technological properties have been determined. Bloating index (BI), particle density (ρrd), water absorption (WA24) and crushing strength (S) were selected as the four key characteristics to be modeled and optimized, using response surface and effect plots to assess the effect of K, C, N and P on such properties. 32 out of 36 starting varieties met the density criteria for lightweight aggregates. In the optimum formulations obtained, the minimum percentage of K was 83 wt%, so that the variations in the percentages of P, C and N were the critical variables for determining the final properties of the aggregate. The contrast between experimental and estimated data has shown that the models fit adequately, indicating that this type of approach may have enormous potential for future research on artificial aggregates and other ceramic materials.

Downstream Torrefaction of Wood Pellets in a Rotary Kiln Reactor—Impact on Solid Biofuel Properties and Torr-Gas Quality

Solid biofuels produced from torrefaction have improved coal-like properties in comparison to raw biofuels, yet ensuring uniform product quality is still a challenge. In this study, downstream torrefaction of wood pellets was performed at temperatures between 200 and 270 °C in a rotary kiln reactor to understand the effect of torrefaction temperature on product quality. The torrefied solid biofuel was compared with dedicated fuel properties defined in ISO/TS 17225-8:2016-12. Based on the results, the optimal temperature for downstream torrefaction was found at temperatures of 230 and 250 °C. Above this temperature, the effect of bulk density superimposes not only the increased net calorific value but also values for mechanical durability, amount of fines, and bulk density of the solid biofuel, which were below the thresholds of the fuel standard. Moreover, increasing process temperatures caused higher heavy metal concentrations in torrefied pellets. The composition of condensable and non-condensable fractions of the torr-gas substantially increased between temperatures of 230 and 250 °C and remained on a similar level at higher temperatures. Thus, the utilization of torr-gas for energy recovery purposes and as a precursor for the recovery of valuable chemicals should be balanced with the quality of the solid biofuel in the aforementioned range of torrefaction temperatures to enable the utilization of torrefaction products at further steps.

Production of Al(HI)-K(I)-Ti(IV)-sulphate-containing leach liquor from metakaolinite-containing ash derived from South African coal fines

South African discard coal fines and K2CO3 blends were heated in a laboratory-scale rotary kiln to produce ashes for H2SO4 leaching tests. The optimized H2SO4 leaching conditions of 6.12 mol.dm3 (M) H2SO4, solid to liquid ratios 1:5 and 1:10, and 8o°C for 8 hours were used. K2CO3 was added to increase the dissolution efficiency of K. The objective was to determine if the Al present in metakaolinite (Al2O3.2SiO2), the Al, K, and Ti in the alumino-silicate glasses, and the Ti in rutile (TiO2) in the ashes could be selectively dissolved in H2SO4. XRF results show that the ashes formed at 700°C dissolved more efficiently (87% Al, 89% K and 23% Ti) compared to the ashes formed at 1050°C. This can be attributed to the presence of Al2O3.2SiO2, K2CO3 melt, K2CO3 remnants, KAl(SO4)2, and K-aluminosilicate glass in these ashes. XRD results indicate that the ashes prepared at 1050°C contained anorthite (CaAl^Og), microcline (KAlSi3O8), pseudomullite (Al2.SiO2), and silicon spinel (2Al2O3.3SiO2), which are either insoluble or only sparingly soluble in H2SO4. These minerals resulted in the lower dissolution efficiencies of Al and K. Based on the high dissolution efficiencies of Al and K for the ashes produced at 700°C, coal fines blended with K2CO3 could possibly be utilized as feedstocks for the production of aluminium(III), potassium(I), and titanium(IV) and a sulphate-containing leach liquor. Furthermore, the environmental issues and costs associated with the handling and disposal of large volumes of coal fines will also be resolved.

An Implementation of Abrupt Changes Detection and Principal Component Analysis for Monitoring the Thermal Processes in a Cement Rotary Kiln

An Implementation of Abrupt Changes Detection and Principal Component Analysis for Monitoring the Thermal Processes in a Cement Rotary Kiln

Numerical Turbulent Flow Analysis through a Rotational Heat Recovery System

Herein, hydrodynamic analysis from a large-eddy simulation in Couette–Taylor–Poiseuille (CTP) geometry is numerically investigated. The present geometry is inspired by a previous experimental work in which heat transport phenomena were investigated in a heat recovery system devoted to a rotary kiln facility. The streamwise and spanwise components of the velocity and the Reynolds stress tensor are firstly validated using an experimental benchmark. The effect of the axial flow rates is studied at a fixed rotational velocity. It is shown that the streamwise velocity component damps the vortex flow organization known in Couette–Taylor (CT) flow. The bulk region and its wall footprint are therefore characterized by various methods (spectral and statistical analysis, Q-criterion). It is shown that the turbulent kinetic energy of the streamwise component in the near-wall region is augmented leading to a multi-scale nature of turbulence.

Improved fuel conversion through oxygen carrier aided combustion during incineration of biomass-based solid waste in a rotary kiln

Solid waste (SW) incineration in a rotary kiln (RK) faces great CO fluctuations due to the batch-fired nature, resulting in incomplete SW combustion, which makes its optimization challenging. A method introducing an oxygen carrier (OC) material into the RK has been first proposed to improve SW conversion, lower the CO emission and reduce the fluctuation of emitted CO during the combustion. In this work, manganese and ilmenite ores have been investigated as OCs, and introduced into a lab-scale RK during the combustion of biomass-based SW. Results show that both the introduction of manganese and ilmenite ores have lowered the CO emission and alleviated the fluctuation of emitted CO under reduced oxygen supply. It has been demonstrated that the OC can increase the available oxygen for effective biomass-based SW combustion in the RK since it can continuously transfer lattice oxygen from the active layer to the passive layer with the bed rolling. Besides, the unconverted CO can be burnt more completely and evenly through the gas–solid redox reaction attributed to the reactivity of OCs over CO. In addition, the OCs can also react with the char through a solid–solid reaction at a high temperature over 1073 K. As a result, the carbon conversion can be increased in the presence of OCs.

An efficient method for computational flow-based simulation of heat transfer in a rotary kiln with pilot scale validation

• Counter-current rotary kiln 5.27 m long, operated with two different feeds of gravel. • Temperature measurements taken along the kiln under various operating conditions. • Novel fast efficient computational model developed to predict bed temperature. • Predicted temperature profile in reasonable agreement with the measurements. • Model allows rapid, but reliable assessment of kiln design and operating conditions. Rotary kilns are used to carry out heating and chemical transformation in several mineral processing operations. A series of experimental runs was carried out using the realistic but controlled arrangement of a pilot rotary kiln to obtain temperature data for the validation of a novel model that couples a computational fluid dynamics model of the flame to a granular bed model through heat transfer terms. The rotary kiln was 5.27 m long, with an internal diameter of 410 mm, and two different feeds of inert standard commercial gravel were used in the runs, with the kiln operating in counter-current operation. Each of the feeds was run through the kiln under various operating conditions (feed rate, kiln rotation speed, fuel rate and weir height), and kiln temperature profiles were measured during each run. The effect of various operating parameters on heat transfer within the kiln was then determined. A fast and efficient computational model of the pilot kiln was developed to predict the burner flame and heat transfer in the kiln; the granular bed was modelled using a one-dimensional model which was coupled in a pragmatic way to the computational fluid dynamics gas phase model. Dependence of the predicted temperature profile on operating parameters is in reasonable agreement with the measurements, and the model can be run rapidly for efficient assessment of a large number of design and operating condition options. While there have been an increasing number of papers published in recent years reporting very detailed models of the motion in granular beds in rotary drums that are extremely valuable for a fundamental understanding of issues such as segregation, such models are very computationally intensive, and are still not feasible for industrial-scale kilns in which the particles are small. This paper indicates that good predictions of process parameters such as bed temperature are possible without such very time-consuming computations. Moreover, the experimental temperature measurements will be useful for future rotary kiln studies.

Enhanced recovery of zinc and lead by slag composition optimization in rotary kiln

High-efficiency recovery of Zn and Pb from silicon-rich zinc leaching residues is realized in a rotary kiln. Characterizations by means of XRD, SEM, EDS and ICP reveal that the leaching residue contains 12.4 wt.% SiO2, 16.1 wt.% Zn, and 7.4 wt.% Pb. Thermodynamic analysis shows that metallic vapor of Zn and Pb can be easily generated from the zinc leaching residue at 1150−1250 °C inside the rotary kiln. Viscosities and melting points of 13 slag compositions were analyzed and three slag compositions (47wt.%SiO2−23wt.%CaO−30wt.%FeO, 40wt.%SiO2− 28wt.%CaO−32wt.%FeO, and 40wt.%SiO2−30wt.%CaO−30wt.%FeO) possessed the desirable physical properties, with the melting point and viscosity in the range of 1150−1280 °C and 0.2−0.5 Pa·s, respectively. The industrial tests show that adopting the optimized slag composition can contribute to very high recovery rates of Zn and Pb (97.3% for Zn and 94.5% for Pb), corresponding to slags with very low average contents of Zn and Pb (0.51 wt.% Zn and 0.45 wt.% Pb). The National-Standard leaching tests of the water-quenched slags result in 1.82 mg/L Zn, ~0.01 mg/L Cu, 0.0004 mg/L As, ~0.01 mg/L Cd, 0.08 mg/L Pb, and ~0.02 mg/L Hg in the leachate, verifying the detoxification of the zinc leaching residue at the same time.

Frame-Dilated Convolutional Fusion Network and GRU-Based Self-Attention Dual-Channel Network for Soft-Sensor Modeling of Industrial Process Quality Indexes

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.