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2023, Concilium
The present investigation obtained a system of mathematical models of operation of the steel ingot heating furnaces. For this, the systems analysis and synthesis methodology were used, from which the conceptual mathematical model was derived, as well as the interrelation of the furnace with the rest of the plant systems. The model was validated under static and dynamic operating conditions by purchasing the values of the variables measured in a Case Study facility with the values obtained by simulation. In addition, objective function optimization tools were applied by exploring a network of variables with a penalty for breach of constraints. The system responded satisfactorily to the disturbances inherent in the production process.
2015
Reheating of continuous casting slabs, billets and blooms in walking beam furnace is an important step for further processing of the slabs by thermo-mechanical techniques like hot rolling and forging operations. The slabs are heated up to 1100 – 1250 o C, and since this is a high temperature and energy intensive process, prolonged or excess heating will cause productivity and energy loss, as well as oxidation and scale loss. On the other hand if it is heated very fast causing significant temperature difference between the surface and the core temperature, it can lead to excessive thermal stress, cracking or distortion. Furthermore, rapid heating of the surface to attain the specified temperature, without thermal homogenization of the slab can causes problems during hot rolling or forging operations, which may lead to cracking, roll stuck and forging problems. Therefore the aim of the heating process is to avoid any excessive thermal stress, particularly in the vulnerable ferrite to ...
Procedia Manufacturing, 2020
Nowadays, energy efficiency is a crucial factor for the competitiveness of manufacturing firms, due to the rising of world energy prices and as a consequence of the environmental consciousness concerned with the consumption of non-renewable energy resources. The furnaces for steel reheating are responsible for a large amount of energy consumption, where less than 50% of the energy supplied to the furnace (mainly gaseous fuel) is net energy of steel heating, the remaining is lost. A consistent set of studies, which investigates energy reduction initiatives for the reheating furnaces, can be found in literature. However, almost all the studies are focused on technology alternatives (such as regenerative burners), whereas some others focus their attention on measurement and control action, mainly obtained by IT investments. This study aims at providing a mathematical model for a reheating furnace, by considering the efficiency-temperature relationships of the furnace. The model permits the user to identify the most proper optimization of the temperature-time relations, in the different productive situations, capable of guaranteeing the most energy-efficient reheating operations by preserving logistics performances. In order to make a cost-benefit analysis, different options for the furnace setting and related process operations have been considered with reference to a specific industrial case. The model highlights how improving the operating policies for controlling the key process parameters may lead to energy savings and, consequently, economic benefits, as well as pursuing environmental preservation thanks to the rational use of non-renewable resources.
The Reheating Furnace Walking Hearth Type is the key of the different rolling steel process sizes. Steel in the furnace is heated to high temperature range from 950 to 1150 oC at least 30 minutes. Because of this reason, the system requires an optimal controller for control the temperature inside each zone of the furnace. If the temperature of the steel is not proper to the process, it will affect the quality of the rolling steel process such as damage in ironing broad and increase electrical energy consumption in rolling process. The factors affecting the price of wire rod are electrical power and oil fuel consumption. Consequently, the steel production manufacture select the time from 22:30 to 8:00 for steel production because it has low cost. In addition the process will stop during the day time. This paper presents the mathematical model of Reheating Furnace Walking Hearth Type using Genetic Algorithm. This method can estimate the parameters of the reheating furnace mathematical...
Some problems are known to have computationally demanding objective function, which could turn to be infeasible when large problems are considered. Therefore, fast approximations to the objective function are required. This paper employs portfolio of intelligent systems algorithms for optimising a metal reheat furnace scheduling problem. The proposed system has been evaluated for different techniques of the reheat furnace scheduling problem. Different optimisation methods have been used, namely: particle swarm optimisation (PSO), genetic algorithm (GA) with different classic and advanced versions: GA with chromosome differentiation (GACD), age GA (AGA), and sexual GA (SGA), and finally a mimetic GA (MGA), which is based on combining the GA as a global optimiser and the PSO as a local optimiser. Simulations have been performed to evaluate the systempsilas performance.
2015
Modeling of heat and mass transfer of fired heaters for refinery use was carried out to determine the equipment efficiency as well as the process and flue gas temperature variations. Previous research involving non-computational fluid dynamics (CFD) analysis of fired heaters modeled individual sections of the heater with little attention to the other. In this study, transfer models were developed and compiled in the MATLAB environment for validation. Upon which, simulations were run to determine the most influential parameters affecting the performance of fired heaters. Research papers referenced in this study developed models by incorporating correlations established in the early 1950s’. This study differs in a sense that the formulas used to develop the model are generally modified using common engineering sense to accommodate the dimensions of a refinery fired heater. Initially, the research involved the modeling of separate sections of the heater encompassing heat and mass balan...
Journal of Materials Processing Technology, 2006
This study presents the development of a mathematical and computational model for simulating and controlling of an annealing process of a silicon steel strip that occurs in an industrial combustion furnace. Both the combustion process and the strip heating are simulated by using energy and mass balances inside the industrial furnace. These balances are performed considering important variables, such as composition, temperature and pressure of gas components, adiabatic flame and environmental temperature. Besides the balances, an optimization technique is implemented in order to estimate the temperature distribution of the strip at any time. The optimization technique used is the Golden section algorithm that minimizes a least square function based on difference of the experimental and theoretical temperature in two different locations of the strip. All steps of the software development are presented here: the combustion and annealing process, the energy and mass balance and the fundamentals of the optimization process. The efficiency of the software is then demonstrated through an analysis and application of data acquired from operational conditions in continuous annealing lines of a steel company. This study is concluded presenting a discussion about the uncertainty and error sources the can be present in the results. The software SIMCO-RB2 seems to be a very powerful tool in the simulation of metal annealing processes.
Energy, 2006
The ethylene production process is one of the most important aspect of a petrochemical plant and the cracking furnace is the heart of the process. Since, ethylene is one of the raw materials in the chemical industry and the market situation of not only the feed and the product, but also the utility is rapidly changing, the optimal operation and control of the plant is important. A mathematical model, which describes the static and dynamic operations of a pilot plant furnace, was developed. The static simulation was used to predict the steady-state profiles of temperature, pressure and products yield. The dynamic simulation of the process was used to predict the transient behavior of thermal cracking reactor. Using a dynamic programming technique, an optimal temperature profile was developed along the reactor. Performances of temperature control loop were tested for different controller parameters and disturbances. The results of the simulation were tested experimentally in a computer control pilot plant. q
2010
The slab reheating process for iron rolling to the small diameter wire in Ratchasima Steel Products Co.,Ltd. factory (Nakron Ratchasima, Thailand) use the reheating furnace walking hearth type which control the temperature of the process about 1150-1200 Celsius (up to each zone) and consume time about 2 hours. The air fuel ratio control of this furnace is feedback control which use PID controller. The problems in the present are reducing production cost and increasing performance in energy consumption which most cost of the factory from in the slab reheating process. So the factory has the idea to change the energy source to the cheaper source such as nature gas, bio-gas etc and improve the performance of the temperature control of the reheating furnace walking hearth type in heating curve up process. Consequently the controller isn’t suitable for the slab reheating process in the present then can’t control the desired temperature and lose the energy. From the mentioned reason, we h...
Indian Journal of Science and Technology, 2016
Since the heating furnace system has emanated it has faced the problem of high power consumption, colossal amount of time to heat the substances and the vulnerability of getting exploded thus the objective of the paper is to achieve a system for same with less power consumption, whit time to heat the substances and making it safe from explosion. Using the mathematical way of modeling the dynamic critical systems the heating furnace is being modeled by using the damping, spring and mass elements. The integer order model of the system is being achieved by the Laplace transform and fractional order model for the same is obtained using the Grunwald-Letnikov formula. The Cohen-Coon tuning technique is being amalgamated with the Nelder-Mead, Interior-Point, Active-Set and Sequential Quadratic Programming optimization techniques respectively so as to design the FOPID controller for heating furnace. When the feedback systems were being formed then the outputs demonstrated that the system now consists the properties of less power consumption, less time to heat the substances along with less overshoot. Earlier the integer order model had the settling time (time taken to heat the substance), steady state error (power consumption) and overshoot (explosion) of 1500 seconds, 50% and 0% respectively. When the PID controller was designed for the same using Cohen-Coon tuning technique and forming a feedback system it had setting time of around 800 sec. and also the steady state error was brought to 0% but the overshoot went up to 35%. Therefore FOPID controller is being designed using the concocted technique that is the amalgamation of tuning technique and optimization techniques and forming and feedback system with FOM of heating furnace, the system yielded steady state error as 0%, where the settling time have been reduced to 300 seconds and overshoot between 7%-12%. Using the concocted technique that is the amalgamation of Cohen-Coon tuning technique with the optimization tuning techniques the FOPID controller was being formed for the FOM of the heating furnace which is being kept in feedback so as to form a system. Thus systems formed ameliorated the settling time i.e. time taken to heat the substance, the overshoot i.e. the vulnerability of getting exploded also remains low and the steady state error i.e. power consumption is also reduced drastically.
2021
The decision to adopt a certain heating conditions must consider the need to avoid dangerous thermal stresses that could cause products deformation, especially those with complex configuration, or even damage to their integrity and at the same time a minimum value of heating time, with direct consequences on technological consumption and productivity, so costs.Starting from the premise that in furnaces with discontinuous operation the heating is most frequently performed in thermal conditions characterized by constant value of heat flux (q =Jc = ct., corresponding to the 2 oder limit conditions), until the heating chamber attain the required equilibrum temperature (Tc = Tt + 20÷40 C) subsequently passes into Tc = ct (3 rd order limit conditions), it is particularly important to anticipate the value of the temperature drop during the first stage of heating (q=Jc = ct.), to conclude whether the power stage adopted was correct or not, so what technological measures must be taken so tha...
2012
"Most of the physical processes are dynamical and nonlinear in nature. Modeling of such systems using physical principles is a complicated task involving a lot of time and effort. Artificial neural networks with their self-learning and general function approximation capabilities are effective tools to cope with nonlinear modeling. In this paper we propose static and dynamic predictor models for a real walking beam furnace using nonlinear sub-system identification based on neural network (NNP) model which naturally follows a multi-layer perceptron. For training the network, weights and biases values are updated by Levenberg-Marquardt optimization algorithm. Identification and evaluation of NNP these models were performed using the recorded data of Iran Alloy Steel Company (in the centre of Iran)."
a mathematical model for simulation of refinery furnaces is proposed. It consists of two different submodels, one for the process side and another for the flue gas side. The process side is appropriately modeled as a plug flow due to the high velocity of the fluid inside the tubes. The flue gas side is composed by a radiative chamber and a convective section both connected by a shield tube zone. Both models are connected by the tube surface temperature. As the flue gas side model uses this temperature as input data, the process side model recalculates this temperature. The procedure is executed until certain tolerance is achieved. This mathematical model has proved to be a useful tool for furnace analysis and simulation.
Transactions of the Indian Institute of Metals, 2013
In view of scarcity and depletion in the quality of raw materials as well as stringent environmental regulations, judicious use of resource and adoption of optimal operating practices have become the prime concern in iron and steel industries. Real time forecasting and supervision of the process behavior is an important step in addressing these issues. As a part of the tool termed ''Real Time Process Simulator (RTPS)'', containing several reduced order models for real time monitoring and prediction of the internal dynamics of iron making blast furnace, a mathematical model for material and thermal analysis has been developed, mainly to predict the top gas composition, raw material consumption and overall heat balance. The model predictions have been tested against actual plant data. The raceway adiabatic flame temperature has been calculated using data similar to that of an operating plant. The calculated heat distribution of the process has been presented in the form of a SHANKEY diagram. The RTPS, containing the present model has been implemented in an Indian integrated steel plant. Prior to implementation, the model has been tested and validated in the plant operational range with the help of a virtual platform.
Archives of Metallurgy and Materials, 2013
Heating of materials is energy and costly operations. On those reasons optimization is highly desirable. One of the possible solutions to optimize heating in real time is to use a large number of fast simulations on the basis of them the optimization algorithms have chosen the most appropriate option of the heating control. This solution implies the use of extremely fast but sufficiently accurate simplified mathematical models of heating, the structure and parameters of them are defined based on accurate modelling using computationally intensive but slower classical mathematical-physical models. Based on the operating data of the reheating furnace was build an accurate model of heating. Using the simplified model simulation of heating was done with different heating conditions with downtime during heating. Proposed algorithms including the simulations show that the proposed strategy leads to verifiable savings during heating.
Procedia Technology, 2012
Reactive annealing of semi-processed electrical steels is an important process to reduce electro-magnetic losses. The annealing process involves heating of the steel strip, which is passed continuously through the furnace, to a certain temperature. The heated steel strip gets decarburised and annealed in a warm gas atmosphere containing N 2 -H 2 -H 2 O-CO-CO 2 mixture. The composition of the warm gas atmosphere plays a major role in both the decarburisation and selective oxidation of carbon from the steel strip. The furnace settings are often changed to cater for products with different metallurgical properties and varying dimensions. Often the line speed of the process too needs to be changed to cater to varying input parameters of the steel strip such as composition, width, thickness etc. Thus an advanced mathematical model based system is desired to optimize the running of the furnace to achieve the desired properties at improved productivity.For effective control of system, mathematical model for the heating of the steel strip is developed. Decarburisation model for the steel strip has been coupled with the thermal model. The model takes in various inputs like line speed, composition of the steel strip, width and its thickness. Temperatures in the different zones of the furnace along with the decarburising gas flow rate, H 2 /H 2 O ratio etc, are taken as input parameters. The model predicts the thermal profile of the steel strip inside the furnace. It also predicts the carbon composition in the steel strip along the length of the furnace. Based on optimized temperature and carbon profile for different grades, the model suggests the desired line speed and the temperature settings in the different zones of the furnace. If there is a mismatch in the desired and the actual line speed the model also generates the desired set points of temperature for increasing or decreasing the furnace temperature which is downloaded to PLC in order to control the furnace parameters in real-time.
2012
In this paper we will elaborate the hybrid system design approach in modeling of high consumption industrial furnace. The operating point of the furnace depends on the temperature profile that we want to achieve. The most used temperature profile in this furnace is when we need to regulate the temperature near 1000 • Celsius. Nevertheless, if we want to use the furnace for heating of different types of pipes, we need to stabilize the output temperature to different operating points e.g. 500, 700 or 1100 degrees etc. Additionally there are several discrete parameters that significantly influence the furnace behavior. The state that represents the presence of pipe in each of the furnace zones has great impact on the coefficients for the increase/decrease of the temperature in the respective zone. Also the state of the doors (open/closed) at the beginning and at the end of the furnace impacts the cooling of the furnace.
Sciprints, 2016
Industries, which are mainly responsible for high energy consumptions, need to invest in research projects in order to develop new managing systems for rational energy use and to tackle the devastating effects of climate change caused by human behavior. The study reported in this paper concerns the forging industry, where the production processes generally start with the heating of the steel in furnaces and continue with other processes, such as heat treatments and mechanical machining. One of the most critical operations, in terms of energy loss, is the opening of the furnace doors for the insertion and extraction operations. During this time, the temperature of the furnaces decreases by hundreds of degrees in a few minutes. Because the dispersed heat needs to be supplied again through the combustion of fuel, increasing the consumption of energy and the pollutant emissions, the evaluation of the amount of the lost energy is crucial for the development of operating or mechanical sys...
2007
We present the implementation of an online mathematical model for billet reheating in the OFU walking-beam furnace at the [tore Steel d.o.o. steelworks in Slovenia. For the real-time operation of the simulation model the data about furnace charging and real-time measurements in the furnace are needed. The simulation model is connected to the existing information system of the OFU furnace, which can ensure the required data. The simulation is performed for all the billets (up to 125) that are currently charged in the furnace. The modeling of the reheating process in a gas-fired walking-beam furnace consists of descriptions of complex partial mechanisms. For the validation of the model, measurements of the billet reheating in the OFU furnace were made. These measurements involved a test billet and five trailing thermocouples. The comparison of the measurements and the simulation results, which are stored in a local database, shows good agreement across the whole temperature range of t...
2013
Heating of material in continuous reheating furnaces is often accompanied by uneven betting material to the furnace, which has an effect on the resulting parameters of the heated material. Too long heating leads to the exceeding of optimal temperatures and operating inefficiency, too short heating leads to insufficient heating of the material. Deviations from the standard set of parameters hot material may occur with subsequent further processing in successive forming technologies. To determine the optimal heating of the material in the furnace is a complex and difficult task. The aim of the article will examine possible modes of heating in a continuous furnace with respect to establishing the criteria of heating in order to optimize heating process.
The recent years showed a significant increase both in energy costs and social awareness for environmental concerns. In the industrial sector, these aspects affected revenues and sustainability of the most intensive energy plants, such as steel mills. The present paper describes how simulation may powerfully support production planning and the related decisions. The application proposed refers to a steel plant feeding its Continuous Casting line by an electric Arc Furnace. The optimization of the production plan is pursued by an objective function which takes into account both traditional targets (e.g., lead times and due dates) and the need for an efficient use of energy. To this end, a discrete/continuous si mulation model was developed: stochastic laws, suitable for temperature variations modelling, were implemented to forecast energy requirements at the Ladle Furnaces and/or the Vacuum Degasser. Final results showed how the simulation-based Decision Support System may lead to a ...
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