宏
过程(计算)
计算机科学
工艺工程
工程类
操作系统
程序设计语言
标识
DOI:10.1177/03019233241271512
摘要
Improving the quality of stainless-steel hinges significantly on precisely managing decarburisation within the argon-oxygen decarburisation (AOD) process. This study introduces a dynamic model capable of accurately predicting the composition and weight of steel and slag. To thoroughly investigate the refining processes, a systematic analysis was conducted, integrating three essential adiabatic zones within the AOD converter: the continuous stirred-tank reactor, slag bath and plug flow reactor, supported by circulation and recirculation streams. FactSage TM software and its macro facility were utilised to identify the different phases present in steel and slag. This dynamic model not only forecasts critical process parameters like temperature, composition and volume of multiple phases but also enables the prediction of the final chromium content for different initial carbon inputs, specifically at 2%, 1.5% and 1 wt.%. By comparing the model's predictions with actual plant data, it was observed that the transient compositions of steel and slag exhibited consistency, confirming the model's validity and reliability in simulating AOD refining processes.
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