A Prediction Model for Internal Cracks during Slab Continuous Casting

The paper presents the comparison of optimization-regulation algorithms applied to the secondary cooling zone in continuous steel casting where the semi-product withdraws most of its thermal energy. In steel production, requirements towards obtaining defect-free semi-products are increasing day-by-day and the products, which would satisfy requirements of the consumers a few decades ago, are now far below the minimum required quality. To fulfill the quality demands towards minimum occurrence of defects in secondary cooling as possible, some regulation in the casting process is needed. The main concept of this paper is to analyze and compare the most known metaheuristic optimization approaches applied to the continuous steel casting process. Heat transfer and solidification phenomena are solved by using a fast 2.5D slice numerical model. The objective function is set to minimize the surface temperature differences in secondary cooling zones between calculated and targeted surface temperatures by suitable water flow rates through cooling nozzles. Obtained optimization results are discussed and the most suitable algorithm for this type of optimization problem is identified. Temperature deviations and cooling water flow rates in the secondary cooling zone, together with convergence rate and operation times needed to reach the stop criterium for each optimization approach, are analyzed and compared to target casting conditions based on a required temperature distribution of the strand. The paper also contains a brief description of applied heuristic algorithms. Some of the algorithms exhibited faster convergence rate than others, but the optimal solution was reached in every optimization run by only one algorithm.

Section: Conditions Towards High-quality Steel Castingmentioning

confidence: 99%

Comparison of Optimization-Regulation Algorithms for Secondary Cooling in Continuous Steel Casting

Březina

Mauder

Klimeš

et al. 2021

“…Poltarak et al [15] established a thermal-force finite element model for the continuous casting of round billets to calculate the stress acting on the solidification front to evaluate the internal crack risk under different casting conditions. Other scholars have also conducted similar studies to evaluate crack risk [16,17].…”

Section: Introductionmentioning

confidence: 99%

“…Among them, most expert systems are composed of sensor detection, database queries, data analysis, and expert knowledge. However, inflexible expert knowledge leads to unsatisfactory applications [16].…”

Section: Introductionmentioning

confidence: 99%

Internal Crack Prediction of Continuous Casting Billet Based on Principal Component Analysis and Deep Neural Network

Zou

Zhang

Han

et al. 2021

The accurate prediction of internal cracks in steel billets is of great importance for the stable production of continuous casting. However, it is challenging, owing to the strong nonlinearity, and coupling among continuous casting process parameters. In this study, an internal crack prediction model based on the principal component analysis (PCA) and deep neural network (DNN) was proposed by collecting sufficient industrial data. PCA was used to reduce the dimensionality of the factors influencing the internal cracks, and the obtained principal components were used as DNN input variables. The 5-fold cross-validation results demonstrate that the prediction accuracy of the DNN model is 92.2%, which is higher than those of the decision tree (DT), extreme learning machine (ELM), and backpropagation (BP) neural network models. Moreover, the variance analysis showed that the prediction results of the DNN model were more stable. The PCA-DNN model can provide a useful reference for real production, owing to its strong learning ability and fault-tolerant ability.

“…Hence, control of cracks formation is currently a crucial issue, as industry engineering develops rapidly [3]. The causes of cracks in various steel grades are different, and there are corresponding control methods for different types of cracks [4][5][6][7][8][9][10][11][12][13]. Wang et al [14] analyzed the effect of inclusions on the initiation of cracks.…”

Section: Introductionmentioning

confidence: 99%

“…Li et al [17] analyzed the effect of subsurface microstructure evolution on the transverse crack of micro-alloyed steel. Kong et al [11] predicted the formation of cracks by using mathematical model.…”

Section: Introductionmentioning

confidence: 99%

Study on Surface Longitudinal Crack Formation of Typical Hypoeutectoid Steel Produced on a Caster with Billet and Slab

Lü

Wang

Guo

et al. 2019

This paper investigates the formation mechanism of typical hypoeutectoid steel with longitudinal cracks produced on a caster with billet and slab. It was found that the microstructure of the proeutectoid ferrite is the most critical factor affecting the longitudinal crack. The formation conditions of the proeutectoid ferrite and the reasonable control direction were determined through experiments and calculations. High-temperature tensile experiments revealed that enhanced cooling did not cause additional cracks. Therefore, the final plan was to reduce the formation of proeutectoid ferrite by strengthening the cooling process. As a result, the optimized surface temperature quickly passed the phase transition region of the proeutectoid ferrite and no cracks were found in the optimized billet.