PickT: A Decision-Making Tool for the Optimal Pickling Process Operation
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Materials |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1944/16/16/5567 |
| _version_ | 1797584065580236800 |
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| author | Claudia Alice Crișan Elisabeta Cristina Timiș Horațiu Vermeșan |
| author_facet | Claudia Alice Crișan Elisabeta Cristina Timiș Horațiu Vermeșan |
| author_sort | Claudia Alice Crișan |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T23:46:59Z |
| format | Article |
| id | doaj.art-e6eaa9ee48b54d70b0b15e91a6ba3e91 |
| institution | Directory Open Access Journal |
| issn | 1996-1944 |
| language | English |
| last_indexed | 2024-03-10T23:46:59Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Materials |
| spelling | doaj.art-e6eaa9ee48b54d70b0b15e91a6ba3e912023-11-19T01:59:29ZengMDPI AGMaterials1996-19442023-08-011616556710.3390/ma16165567PickT: A Decision-Making Tool for the Optimal Pickling Process OperationClaudia Alice Crișan0Elisabeta Cristina Timiș1Horațiu Vermeșan2Department 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, RomaniaDepartment 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, RomaniaDepartment 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, RomaniaThis 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.https://www.mdpi.com/1996-1944/16/16/5567carbon steel corrosionpickling bath lifetimeoptimum corrosion inhibitor concentrationdynamic mathematical modellingpickling optimization |
| spellingShingle | Claudia Alice Crișan Elisabeta Cristina Timiș Horațiu Vermeșan PickT: A Decision-Making Tool for the Optimal Pickling Process Operation Materials carbon steel corrosion pickling bath lifetime optimum corrosion inhibitor concentration dynamic mathematical modelling pickling optimization |
| title | PickT: A Decision-Making Tool for the Optimal Pickling Process Operation |
| title_full | PickT: A Decision-Making Tool for the Optimal Pickling Process Operation |
| title_fullStr | PickT: A Decision-Making Tool for the Optimal Pickling Process Operation |
| title_full_unstemmed | PickT: A Decision-Making Tool for the Optimal Pickling Process Operation |
| title_short | PickT: A Decision-Making Tool for the Optimal Pickling Process Operation |
| title_sort | pickt a decision making tool for the optimal pickling process operation |
| topic | carbon steel corrosion pickling bath lifetime optimum corrosion inhibitor concentration dynamic mathematical modelling pickling optimization |
| url | https://www.mdpi.com/1996-1944/16/16/5567 |
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