B. Thomas, B. Petrus, D. Stephens, J. Bentsman, L. Chen, M. Milligan, Zhelin Chen, Z. Xu
{"title":"连铸过程中动态胀形引起的表面水平面波动建模","authors":"B. Thomas, B. Petrus, D. Stephens, J. Bentsman, L. Chen, M. Milligan, Zhelin Chen, Z. Xu","doi":"10.33313/380/090","DOIUrl":null,"url":null,"abstract":"Mold level fluctuations in continuous casting of steel slabs give rise to slag inclusions, strand surface cracks, and, in severe cases, breakouts. One of the main causes of mold level fluctuations is dynamic bulging, which arises due to periodic squeezing of the strand in the spray cooling zones beneath the mold. This paper presents two models to predict the effect of dynamic bulging on liquid level variations. The first model estimates mold level variations due to dynamic bulging based on two submodels: 1) a computational heat flow model of the continuous casting process that outputs strand surface temperature and shell thickness to an empirical equation to estimate the maximum inner-roll bulging amplitude under steady casting conditions, and 2) an analytical geometric model that calculates the dynamic shape of the bulged shell and the resulting mold level fluctuations, based on the output from the first model and an assumed frozen fraction history. The second model is a simple analytical calculation of the dynamic bulging effect based on the difference between two plant measurements: the mold level sensor data and the stopper rod position, together with a model that predicts the effect of inlet flow variations from the tundish through the SEN into the mold under transient conditions, caused by the measured stopper rod movements, including the effects of erosion. The predictions from these two models are compared to gain new insight into the mold level fluctuations caused by dynamic bulging. At present, this comparison shows quantitative similarities, but also noticeable discrepancy. Steps to improve the accuracy of both models are discussed. INTRODUCTION The quality of steel manufactured by continuous casting depends on controlling many different phenomena. Perhaps the most important factor affecting steel quality is ability to control transient fluctuations of the mold level. These fluctuations lead to severe quality problems, such as surface defects and the entrainment of mold slag that forms the inclusions. Level fluctuations also lead to large, detrimental slag rims, which prevent proper liquid mold slag infiltration. Severe mold level fluctuations also cause deep oscillation marks and increase the incidence of surface cracks [1], [2] and the chance of breakouts [3]. Currently,","PeriodicalId":226675,"journal":{"name":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling of the Dynamic-Bulging-Induced Surface Level Fluctuations in Continuous Casting\",\"authors\":\"B. Thomas, B. Petrus, D. Stephens, J. Bentsman, L. Chen, M. Milligan, Zhelin Chen, Z. Xu\",\"doi\":\"10.33313/380/090\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mold level fluctuations in continuous casting of steel slabs give rise to slag inclusions, strand surface cracks, and, in severe cases, breakouts. One of the main causes of mold level fluctuations is dynamic bulging, which arises due to periodic squeezing of the strand in the spray cooling zones beneath the mold. This paper presents two models to predict the effect of dynamic bulging on liquid level variations. The first model estimates mold level variations due to dynamic bulging based on two submodels: 1) a computational heat flow model of the continuous casting process that outputs strand surface temperature and shell thickness to an empirical equation to estimate the maximum inner-roll bulging amplitude under steady casting conditions, and 2) an analytical geometric model that calculates the dynamic shape of the bulged shell and the resulting mold level fluctuations, based on the output from the first model and an assumed frozen fraction history. The second model is a simple analytical calculation of the dynamic bulging effect based on the difference between two plant measurements: the mold level sensor data and the stopper rod position, together with a model that predicts the effect of inlet flow variations from the tundish through the SEN into the mold under transient conditions, caused by the measured stopper rod movements, including the effects of erosion. The predictions from these two models are compared to gain new insight into the mold level fluctuations caused by dynamic bulging. At present, this comparison shows quantitative similarities, but also noticeable discrepancy. Steps to improve the accuracy of both models are discussed. INTRODUCTION The quality of steel manufactured by continuous casting depends on controlling many different phenomena. Perhaps the most important factor affecting steel quality is ability to control transient fluctuations of the mold level. These fluctuations lead to severe quality problems, such as surface defects and the entrainment of mold slag that forms the inclusions. Level fluctuations also lead to large, detrimental slag rims, which prevent proper liquid mold slag infiltration. Severe mold level fluctuations also cause deep oscillation marks and increase the incidence of surface cracks [1], [2] and the chance of breakouts [3]. Currently,\",\"PeriodicalId\":226675,\"journal\":{\"name\":\"AISTech2020 Proceedings of the Iron and Steel Technology Conference\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AISTech2020 Proceedings of the Iron and Steel Technology Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33313/380/090\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AISTech2020 Proceedings of the Iron and Steel Technology Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33313/380/090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling of the Dynamic-Bulging-Induced Surface Level Fluctuations in Continuous Casting
Mold level fluctuations in continuous casting of steel slabs give rise to slag inclusions, strand surface cracks, and, in severe cases, breakouts. One of the main causes of mold level fluctuations is dynamic bulging, which arises due to periodic squeezing of the strand in the spray cooling zones beneath the mold. This paper presents two models to predict the effect of dynamic bulging on liquid level variations. The first model estimates mold level variations due to dynamic bulging based on two submodels: 1) a computational heat flow model of the continuous casting process that outputs strand surface temperature and shell thickness to an empirical equation to estimate the maximum inner-roll bulging amplitude under steady casting conditions, and 2) an analytical geometric model that calculates the dynamic shape of the bulged shell and the resulting mold level fluctuations, based on the output from the first model and an assumed frozen fraction history. The second model is a simple analytical calculation of the dynamic bulging effect based on the difference between two plant measurements: the mold level sensor data and the stopper rod position, together with a model that predicts the effect of inlet flow variations from the tundish through the SEN into the mold under transient conditions, caused by the measured stopper rod movements, including the effects of erosion. The predictions from these two models are compared to gain new insight into the mold level fluctuations caused by dynamic bulging. At present, this comparison shows quantitative similarities, but also noticeable discrepancy. Steps to improve the accuracy of both models are discussed. INTRODUCTION The quality of steel manufactured by continuous casting depends on controlling many different phenomena. Perhaps the most important factor affecting steel quality is ability to control transient fluctuations of the mold level. These fluctuations lead to severe quality problems, such as surface defects and the entrainment of mold slag that forms the inclusions. Level fluctuations also lead to large, detrimental slag rims, which prevent proper liquid mold slag infiltration. Severe mold level fluctuations also cause deep oscillation marks and increase the incidence of surface cracks [1], [2] and the chance of breakouts [3]. Currently,