Reheating Furnace Research Articles

Optimal algorithms for solving green online reheat furnace scheduling problems with deterioration effect

Optimizing reheating furnace scheduling in terms of energy saving and reheating time reduction is a vital component in improving competitive advantage of the steel enterprises. However, current reheating furnace scheduling models are still limited since (1) most of the scheduling problems involving reheating furnace suppose that the steel orders and their information are known in advance and (2) the reheating time of a slab in reheating operation is a constant in the majority of current reheating furnace scheduling models. To address these issues, three online reheat furnace scheduling models with deterioration effect are proposed in order to minimize the maximum residence time, the maximum energy consumption as well as total energy consumption of all slabs in reheating operation, respectively. Furthermore, for these online scheduling problems, deterministic online algorithms are presented and shown to be optimal, respectively. In addition, the computational experiments confirm that the three online algorithms developed in this paper are particularly efficient and effective in practice.

Improving the energy efficiency in a walking hearth type reheating furnace by energy balance method and optimizing the resources

Most metal industries use reheating furnaces (RHF) for their finishing operations. This RHF is highly energy-consuming equipment that heats the material inside the chamber for rolling or shaping using the by-product gases, natural gas, or oil as fuel. It is necessary to minimize or optimize the fuel consumption to the extent possible. By analyzing the plant operating data, plant measurements, and energy balance calculation, this work aims to determine the potential for decreasing the fuel consumption of a billet reheating furnace. Predictions are made by modeling operating data to reveal the hidden problems and uncover underlying issues. The study results in increasing productivity by 11 ​% while oil consumption was reduced by 14 ​%. These actions significantly decreased carbon emissions considerably and generated significant cost savings.

Computational Modeling of Walking Beam Type Reheat Furnace for the Prediction of Slab Heating and Scale Formation

Abstract Computational modeling using the high-viscosity laminar flow approach was applied to study the effect of slab crossing time on slab heating and scale growth. Simulation of an existing industrial walking beam reheating furnace with four zones, outer refractory body, skid, slab, and fluid zone is considered. The fuel used was a mixture of coke oven and blast furnace gas. Preheated air is supplied co-axially with the fuel mixture. The combustion simulation is performed using the constrained equilibrium mixture fraction model. From the results, it has been observed that with an increase in slab residence time, the slab temperature and scale growth increase across the slab. For the system considered, with a fuel mass flowrate of 70,000 kg/h, 150–180 min of slab crossing time is appropriate to obtain desired slab temperature at the discharge end. The overall equivalence ratio is taken as Φ = 1 (fuel/air ratio is the same as stoichiometric ratio). The maximum slab scale thickness is evaluated as 2.4 mm at the discharged end for 180 min of slab crossing time.

PERANCANGAN TUNGKU RE-HEATING PORTABLE

Re-heating furnace is a furnace that is used as a metal heater in the forging process. Re-heating furnace is one of the needs of the material technology laboratory to carry out the practical process of metal forming with plastic deformation as a heating medium for the forging process. The manufacture of this re-heating furnace is to make tools using medium carbon metal with a target temperature of 800℃. The process of making the furnace uses K300 type concrete material, 8mm reinforcing steel so that the furnace can be strong and durable. The furnace manufacture has succeeded in reaching a temperature of 302.8°C in 10 seconds using an air velocity of 15.4 km/h, and reaching a temperature of 931.8°C in 100 seconds using an air velocity of 25.7 km/h. This Re-heating Furnace can heat low-high carbon steel for forging process.

REDUCING HEAT LOSS AND IMPROVING THE EFFECTIVENESS OF THE REHEATING FURNACE BY REDESIGNING THE REFRACTORY LINING

REDUCING HEAT LOSS AND IMPROVING THE EFFECTIVENESS OF THE REHEATING FURNACE BY REDESIGNING THE REFRACTORY LINING

Temperature Prediction for Reheating Furnace by Gated Recurrent Unit Approach

Reheating furnaces are used to homogeneously reheat the steel stock (Billets, blooms or slabs) at a temperature between 1000°C and 1250°C before hot rolling. Supply of accurate, stable, and reliable control of temperature is most important for reheating furnaces in hot-rolled steel production. The phenomenon of large time lags in temperature is an arduous problem that existed in the combustion system of furnaces, it causes control system big overshoot, continuous oscillation, and may even make the system unstable. In this paper, a prediction model based on gate recurrent unit (GRU) was established to forecast the inside temperature of the furnace by using temperature, fuel, and air time series. Moreover, this paper presents an approach which is combining a prediction model with a feedforward controller that can improve the stability of the temperature control system. Established prediction model of temperatures by collecting data from on-side, and evaluated the model and feedforward performance on the actual reheating furnace. Compared with other dynamic models (recurrent neural network and long short-term memory), the proposed models outperformed by 15.63% and 26.07% on average in terms of the mean absolute error and root mean square error, respectively. Moreover, the proposed control improve traditional PI controller by 33.43% and 19.92% on average in terms of the mean absolute error and root mean square error, respectively. The presented method can be used to reduce the temperature disturbances in the reheating furnaces.

Spheroidal graphite iron production of furnace roof hangers

The wire rod mill of the Ajaokuta Steel Company Limited produces coils, wire rods and re-bars of different sizes. Without the furnace hangers, it will be difficult for the mill to continue to operate. This paper describes the production of furnace roof hangers that are required for re-heating furnace using the spheroidal graphite iron (SGI), highlighting the sand-casting process, charge calculation, and the chemical compositions. The facilities within the foundry shop of the steel company are used to produce furnace roof hangers. The available materials used for the casting of the hangers are the pig iron, scrap ends, foundry returns and magnesium. The process of production was performed through the reheating furnace for the heating of 120 m x 120 m x 120 m billets. One ton induction furnace of low frequency was used as the melting vessel. Also, 6 kg of magnesium was introduced in the ladle before the liquid metal was teemed into it. A Spectro analytical instrument was used to determine the chemical compositions of the materials before and after the casting processes. The analysis of the chemical compositions of produced sample of SGI are presented and discussed.

Simulation of Organic Rankine Cycle – Quasi-steady state vs dynamic approach for optimal economic performance

Computer-based simulations of Organic Rankine Cycles (ORC) have been extensively used in the last two decades to predict the behaviour of existing plants or already in the design phase. For time-varying heat sources, researchers typically rely on either quasi-steady state or dynamic simulations. In this work, the two approaches are compared and the trade-off between them is analysed, taking as benchmark waste heat recovery with ORC from a billet reheating furnace. The system is firstly optimized in MATLAB® using a quasi-steady state approach. The results are then compared with a corresponding dynamic simulation in Dymola. In the case of waste heat from billet reheat furnace, the quasi-steady state approach can successfully capture the fluctuations in waste heat. For heat source ramps from 110% to 40% the nominal value in 30 s, dynamic effects lead to 1.1% discrepancies in ORC net power. The results highlight the validity of the quasi-steady state approach for techno-economic optimization of ORC for industrial waste heat and provide a valuable guideline for developers, companies and researchers when choosing the most suitable tool for their analysis, helping them save time and costs to find the most appropriate approach.

Variability and Determinants of Occupational Noise Exposure Among Iron and Steel Factory Workers in Tanzania.

BackgroundMachines, processes, and tasks in the iron and steel factories may produce noise levels that are harmful to hearing if not properly controlled. Studies documenting noise exposure levels and related determinants in sub-Saharan Africa, including Tanzania are lacking. The aim of this study was to document noise exposure and to identify determinants of noise exposure with a view to establishing an effective hearing conservation programme.MethodsA walk-through survey was conducted to describe the working environment in terms of noise sources in four metal factories (A–D) in Tanzania. Noise measurements were conducted by both personal, full-shift noise measurements (8 h) using dosimeters and area measurements (10-s measurements) using a sound level meter. A total of 163 participants had repeated personal noise measurements (Factory A: 46 participants, B: 43, C: 34, and D: 40). Workers were randomly selected and categorized into 13 exposure groups according to their job. Linear mixed effects models were used to identify significant determinants of noise exposure in the furnace section and the rolling mill section.ResultsThe average personal noise exposure in the four factories was 92.0 dB(A) (range of job group means; 85.4–96.2 dB(A)) (n = 326). Personal exposure was significantly higher in the rolling mill section (93.0 dB(A)) than in the furnace section (89.6 dB(A)). Among the job groups, the cutters located in the rolling mill section had the highest noise exposure (96.2 dB(A)). In the furnace section, furnace installation (below the ground floor), manual handling of raw materials/billets/crowbars, and billet weighing/transfer were significant determinants explaining 40% of the total variance in personal noise exposure. In the rolling mill section, the size of the cutting machine, steel billet weight and feeding re-heating furnace explained 46% of the total variance in personal noise exposure. The mean noise level of the area measurements was 90.5 dB(A) (n = 376).ConclusionWorkers in the four iron and steel factories in Tanzania were exposed to average noise of 92.0 dB(A), without using hearing protection, implying a high risk of developing hearing loss. Task and factory level determinants were identified in the furnace and the rolling mill sections of the plant, which can inform noise control in factories with similar characteristics.

Secondary steel mill furnace performance.

Energy in a steel re-rolling mill is mainly consumed in furnaces. Therefore, furnace performance is very important and its contribution in the cost of product is very high. Data has been collected for two different furnaces in Stackle mill and analyzed for performance of furnace. In this paper, effect of furnace performance on secondary steel sector is analyzed. These data about performance is collected on Walking beam furnace in Stackle mill and Re-heating furnace.

Optimization of Combustion Organization of Regenerative Reheating Furnace

Regenerative reheating furnace is an important energy consuming equipment in petroleum industry. So it is very important to optimize the combustion organization of the heating furnace. In this paper, a gas consumption regenerative reheating furnace of oil field was taken as the research object. The impact of air excess ratio, preheating temperature of combustion-supporting air and the ratio of the primary air and secondary air on the generation of NOx in the radiant tube was analyzed by the combination of orthogonal test and numerical simulation. The conclusion was made that when the air excess ratio was 1.05, preheating temperature of combustionsupporting air was 900 °C, the ratio of primary air and secondary air was 20%: 80 %, the concentration of NOx in the radiant tube was only 1.1 ppm. The discharge quantity of NOx was reduced to the lowest limitation. And it is an ideal solution to reduce the NOx emissions.

Evaluating Heat Flux Profiles in Aluminum Reheating Furnace with Regenerative Burner

Properly understanding heat flux characteristics is a crucial prerequisite to efficiently applying a regenerative burner in an aluminum reheating furnace. A series of experiments was conducted in this study in order to establish a database of the best available burners according to furnace temperature, excess air ratio, and flame combustion mode as they affect heat flux characteristics at the burner plane (Z = 0 mm). A heat flux model was developed to estimate heat transfer in the furnace, and the heat flux proportions of the other two horizontal levels (Z = 400 mm and Z = 750 mm) were investigated. The contour profile of heat flux indicates that total heat flux (THF) and radiation heat flux (RHF) increases with furnace temperature increment (900–1100 °C). Low excess air ratio (1.2–1.3, at furnace temperature 1100 °C) not only reduced the heat flux gradient, but also contributed to enlarge high THF areas and the maximum RHF. The flameless combustion mode displayed larger average THF and RHF uniformity than that of conventional combustion mode. Therefore, the burning effect of operating condition 1 (gas velocity, 90 m/s; excess air ratio, 1.2; flameless combustion) is better than the other conditions. A change of furnace temperature and excess air ratio had mildly effect on convection coefficient, but combustion mode was in contrast. The estimated heat flux distribution from the measured heat flux at the whole burner plane was in agreement with the fitted line of the axis of burner B. Although the intercept of the simulated equation was slightly underestimated, the error can be eliminated by improving the experimental conditions. The results presented here similarly apply to all regenerative burners. A comparison of heat flux among the three horizontal levels indicated that the RHF proportion comprised about 80% of the THF at each level, and a slightly increase (21.1 kW/m2) of THF in the high level from the low levels.

Fuel Costs Minimization on a Steel Billet Reheating Furnace Using Genetic Algorithms

Metallurgy industries often use steel billets, at a proper temperature, to achieve the desired metallurgical, mechanical, and dimensional properties of manufactured products. Optimal operation of steel billet reheating furnaces requires the minimization of fuel consumption while maintaining a homogeneous material thermal soak. In this study, the operation of a reheating furnace is modeled as a nonlinear optimization problem with the goal of minimizing fuel cost while satisfying a desired discharge temperature. For this purpose, a genetic algorithms approach is developed. Computational simulation results show that it is possible to minimize costs for different charge temperatures and production rates using the implemented method. Additionally, practical results are validated with actual data, in a specific scenario, showing a reduction of 3.36% of fuel consumption.

A numerical analysis of slab heating characteristics in a rolling type reheating furnace with pulse combustion

Numerical analysis of slab heating characteristics in a reheating furnace was accomplished using fluid dynamics software FLUENT. The complicated geometry of the mesh using finite volume method (FVM) simulation was built based on the practical aspects of the reheat furnace. The effect of slab of flow field and temperature distribution inside the furnace on heating efficiency and uniformity in heating was studied. The phenomena in the furnace were periodically transient when slabs were heated with controlled time interval. A user-defined function (UDF) program was developed to process the sequence pulse combustion because FLUENT cannot handle the movement using its default functions. The numerical results were in good agreement with the corresponding experimental data. In order to improve the heating efficiency, the heating precision and the temperature uniformity of the medium and heavy slab, a basic model is proposed. The study is directly applicable in optimizing the process.

Prediction of the heating characteristic of billets in a walking hearth type reheating furnace using CFD

A natural-gas fired walking hearth type furnace for the reheating of steel billets was investigated in this work. A novel numerical approach was used to predict the gas phase combustion, heat transfer and transient heating characteristics of the billets in the furnace. In contrast to conventional coupled simulation of the heat transfer and the heating characteristics, the iterative solution procedure used considers steady-state gas phase combustion of the furnace and unsteady simulation of the billets separately. Due to the steady flamelet model for combustion modelling the calculation time was kept to a minimum although a detailed reaction mechanism with 17 species and 25 reversible reactions was used. The reaction mechanism is applicable for different combustion environments and can be used for future investigations of the furnace after adaption for oxygen enriched combustion. Burner geometry was modelled in detail for a high accuracy prediction of the flame shape of the flat flame burners as well as temperature and species concentrations in the vicinity of the burner. The simulation revealed that 93% of the total heat flux to the billets was contributed by radiation. Transient heating showed a maximum temperature difference inside the billets in the heating zone at 192K decreasing to a value between 42 and 49K at the end of the furnace.

Design Features of Air and Gas Double Preheating Regenerative Burner Reheating Furnace

Abstract Over the past decade, with the development of China's iron and steel industry, a lot of steel rolling reheating furnaces and heat treatment furnaces have been built, most of the furnaces adopt low calorific blast furnace gas and producer gas, and adopt regenerative burner. The air and gas double preheating regenerative burner firstly developed by Shenwu, China can preheat both air and gas to above 1000 oC, not only can increase the theoretical combustion temperature of low calorific value gas, but also can have higher heat recovery rate. This paper introduces the design features of burner structure type, burner arrangement and installation mode, special furnace wall structure, combustion system, flue gas exhausting system, reversing and combustion control, combustion system safety measures, etc. of double preheating regenerative burner reheating furnace.

Three Dimensional Analysis of the Slab Reheating Furnace

This paper studies the chemical combustion reaction of coke oven gas coupled with radiation heat transfer in the slab reheating furnace. Three dimensional temperature distributions of the produced gases and slabs in the combustion furnace are investigates numerically. Numerical results reveal that the radiation heat transfer dominates the heating process in the combustion furnace; it is around 95% of total input heating energy. The heating efficiency is examined for the sake of energy saving in the combustion furnace.

Dynamic Optimization of a Slab Reheating Furnace With Consistent Approximation of Control Variables

A dynamic optimization method is developed for temperature control of steel slabs in a continuous reheating furnace. The work was stimulated by the need for furnace control concepts that are computationally undemanding, robust, accurate, and capable of non-steady-state operating scenarios, where the properties and the temperature goals of slabs may vary significantly. The proposed hierarchical control structure is based on a continuous-time switched nonlinear model and uses the furnace zone temperatures as intermediate control variables. Consistent approximation is applied to obtain a parametric optimization problem that can be efficiently solved with the quasi-Newton method. Constraints on system states and control variables are considered by penalty terms in the cost function and saturation functions, respectively. The optimization method plans temperature trajectories for both the furnace and the slabs, which may be useful for open-loop control and feedforward branches of two-degrees-of-freedom control structures. The capabilities of the method are demonstrated in an example problem.

Application of the Tabu Search Algorithm on Solving the Optimum Heating Institution of Reheating Furnace

With the aim of minimizing the energy consumption cost and taking the billet heating quality as the constraint condition, a mathematical model was established based on the billet heating model to solve the optimum heat institution of the reheating furnace. The tabu search algorithm was employed to solve the model. The results of the industrial production data optimization showed that the proposed mathematical model and the solving method could fully meet the practical production demand of the reheating furnace. In addition to satisfying the heating quality requirements, the energy consumption is reduced and the oxidation loss is decreased. Compared with the original one, the heating institution obtained from the mentioned model and algorithm had a better performance on energy efficiency.

Air pollutant emissions prediction by process modelling – Application in the iron and steel industry in the case of a re-heating furnace

Monitoring air pollutant emissions of large industrial installations is necessary to ensure compliance with environmental legislation. Most of the available measurement techniques are expensive, and measurement conditions such as high-temperature emissions, difficulty of access, are often difficult. That is why legislation can not impose a permanent emission monitoring in many countries. The possibility to replace it with predictive models based on the routine measurements of the main control parameters of the installation is analysed in this paper. In order to identify these models, a special measurement campaign of emissions must be performed or, alternatively, a deterministic modelling of the process can be developed. This study was carried out in the case of a real installation in the steel industry i.e. a billet re-heating furnace. Physical phenomena involved in combustion within the furnace were complex enough to prefer an empirical black-box modelling of the furnace over a deterministic approach. A 3-week monitoring campaign of fume emissions at the stack was performed; furnace process parameters during the same period were available. The relationship between CO 2 emissions and furnace process parameters could successfully be expressed linearly, while NO 2 emission modelling required a non-linear model. Artificial neural networks modelling revealed a good ability to predict NO 2 and CO 2 emissions.