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PickT:优化酸洗工艺操作的决策工具。

PickT: A Decision-Making Tool for the Optimal Pickling Process Operation.

作者信息

Crișan Claudia Alice, Timiș Elisabeta Cristina, Vermeșan Horațiu

机构信息

Department of Environmental Engineering and Sustainable Development Entrepreneurship, Faculty of Materials and Environmental Engineering, Technical University of Cluj-Napoca, 103-105 Muncii Boulevard, 400641 Cluj-Napoca, Romania.

Department of Chemical Engineering, Faculty of Chemistry and Chemical Engineering, Computer Aided Process Engineering Research Centre, Babeș Bolyai University, 11 Arany János Street, 400028 Cluj-Napoca, Romania.

出版信息

Materials (Basel). 2023 Aug 10;16(16):5567. doi: 10.3390/ma16165567.

Abstract

This research approaches knowledge gaps related to the pickling process dynamic modelling (the lack of predictability and simplicity of existing models) and answers the practical need for a software tool to facilitate the optimum process operation (by delivering estimations of the optimum corrosion inhibitor addition, optimum pickling bath lifetime, corrosion rate dynamic evolution, and material mass loss). A decision-making tool, PickT, has been developed and verified with the help of measurements from two different pickling experiments, both involving steel in hydrochloric acid. The first round of experiments lasted 336 h (each pickling batch duration was 24 h) and Cetilpyridinium bromide (CPB) was the corrosion inhibitor in additions from 8% to 12%. The collected dataset served for the tool development and first verification. The second round of experiments lasted 10 h (each batch duration was 2 h) and involved metformin hydrochloride (MET) in additions between 3.3 g/L and 10 g/L. This dataset served to test the transferability of PickT to other operating conditions in terms of corrosion inhibitor type, additions, batch duration and pickling bath lifetime magnitude. In both cases PickT results are in accordance with experimental findings. The tool advantages consist of the straightforward applicability, the low amount of field data required for reliable forecasts and the accessibility for untrained professionals from the industry.

摘要

本研究针对与酸洗过程动态建模相关的知识空白(现有模型缺乏可预测性和简单性),并满足了对一种软件工具的实际需求,该工具可促进最佳工艺操作(通过提供最佳缓蚀剂添加量、最佳酸洗槽寿命、腐蚀速率动态演变以及材料质量损失的估计)。已开发出一种决策工具PickT,并借助来自两个不同酸洗实验的测量数据进行了验证,这两个实验均涉及钢在盐酸中的酸洗。第一轮实验持续了336小时(每个酸洗批次持续24小时),溴化十六烷基吡啶(CPB)作为缓蚀剂,添加量为8%至12%。收集的数据集用于工具开发和首次验证。第二轮实验持续了10小时(每个批次持续2小时),涉及盐酸二甲双胍(MET),添加量在3.3克/升至10克/升之间。该数据集用于测试PickT在缓蚀剂类型、添加量、批次持续时间和酸洗槽寿命大小等方面对其他操作条件的可转移性。在这两种情况下,PickT的结果均与实验结果一致。该工具的优点包括适用性直接、可靠预测所需的现场数据量少以及行业内未经培训的专业人员也可使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e376/10456836/66cca4099b17/materials-16-05567-g001.jpg

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