Е. N. Ivashkina, G. Nazarova, E. Ivanchina, А. М. Vorobyev, А. V. Antonov, Т. А. Kaliev, G. Burumbaeva, М. Y. Mezhova
{"title":"用非平稳数学模型预测真空馏分催化裂化装置运行","authors":"Е. N. Ivashkina, G. Nazarova, E. Ivanchina, А. М. Vorobyev, А. V. Antonov, Т. А. Kaliev, G. Burumbaeva, М. Y. Mezhova","doi":"10.32758/2782-3040-202-0-6-12-21","DOIUrl":null,"url":null,"abstract":"This work presents the development of catalytic cracking mathematical model which is based on the thermodynamic and kinetic patterns of hydrocarbon conversions and takes into account the catalyst deactivation. This model provides a prediction of the catalytic cracking performance when the mixture of vacuum distillate from heavy Kazakhstan and West Siberian oils converts. The mathematical model helps predict the yield and composition of products depending on the feedstock properties and the operating variables of the riser. We develop practical recommendations to organize the riser technological mode to ensure the maximum yield of gasoline (52.6-56.1 wt.%), PPF and BBF (8.3-11.2 and 15.2-20.1 wt.%) when saturated and resinous feedstock converts.","PeriodicalId":23763,"journal":{"name":"World of petroleum products","volume":"24 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of unit operation of vacuum distillate catalytic cracking using a non-stationary mathematical model\",\"authors\":\"Е. N. Ivashkina, G. Nazarova, E. Ivanchina, А. М. Vorobyev, А. V. Antonov, Т. А. Kaliev, G. Burumbaeva, М. Y. Mezhova\",\"doi\":\"10.32758/2782-3040-202-0-6-12-21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work presents the development of catalytic cracking mathematical model which is based on the thermodynamic and kinetic patterns of hydrocarbon conversions and takes into account the catalyst deactivation. This model provides a prediction of the catalytic cracking performance when the mixture of vacuum distillate from heavy Kazakhstan and West Siberian oils converts. The mathematical model helps predict the yield and composition of products depending on the feedstock properties and the operating variables of the riser. We develop practical recommendations to organize the riser technological mode to ensure the maximum yield of gasoline (52.6-56.1 wt.%), PPF and BBF (8.3-11.2 and 15.2-20.1 wt.%) when saturated and resinous feedstock converts.\",\"PeriodicalId\":23763,\"journal\":{\"name\":\"World of petroleum products\",\"volume\":\"24 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"World of petroleum products\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32758/2782-3040-202-0-6-12-21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"World of petroleum products","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32758/2782-3040-202-0-6-12-21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of unit operation of vacuum distillate catalytic cracking using a non-stationary mathematical model
This work presents the development of catalytic cracking mathematical model which is based on the thermodynamic and kinetic patterns of hydrocarbon conversions and takes into account the catalyst deactivation. This model provides a prediction of the catalytic cracking performance when the mixture of vacuum distillate from heavy Kazakhstan and West Siberian oils converts. The mathematical model helps predict the yield and composition of products depending on the feedstock properties and the operating variables of the riser. We develop practical recommendations to organize the riser technological mode to ensure the maximum yield of gasoline (52.6-56.1 wt.%), PPF and BBF (8.3-11.2 and 15.2-20.1 wt.%) when saturated and resinous feedstock converts.