{"title":"近红外光谱与紫外光谱化学计量学预测催化裂化原料性能的比较","authors":"C. Baldrich, L. Novoa, A. Bueno","doi":"10.29047/01225383.444","DOIUrl":null,"url":null,"abstract":"In this paper a comparison is made between the performance of models developed by applying chemometric analysis to NIR and UVVIS spectral data obtained from feedsctock samples corresponding to the different Ecopetrol S.A., Barrancabermeja Refinery FCC units for predicting some important physicochemical properties. The results show the utility of both methodologies here evaluated to follow up the quality of these types of refinery streams and present the advantages and disadvantages of each methodology for predicting the feedstock properties here evaluated.","PeriodicalId":55200,"journal":{"name":"Ct&f-Ciencia Tecnologia Y Futuro","volume":"164 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2010-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"COMPARISON BETWEEN NIR AND UVVIS SPECTRA CHEMOMETRICS FOR PREDICTING FCC FEEDSTOCKS PROPERTIES\",\"authors\":\"C. Baldrich, L. Novoa, A. Bueno\",\"doi\":\"10.29047/01225383.444\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper a comparison is made between the performance of models developed by applying chemometric analysis to NIR and UVVIS spectral data obtained from feedsctock samples corresponding to the different Ecopetrol S.A., Barrancabermeja Refinery FCC units for predicting some important physicochemical properties. The results show the utility of both methodologies here evaluated to follow up the quality of these types of refinery streams and present the advantages and disadvantages of each methodology for predicting the feedstock properties here evaluated.\",\"PeriodicalId\":55200,\"journal\":{\"name\":\"Ct&f-Ciencia Tecnologia Y Futuro\",\"volume\":\"164 1\",\"pages\":\"\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2010-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ct&f-Ciencia Tecnologia Y Futuro\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.29047/01225383.444\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ct&f-Ciencia Tecnologia Y Futuro","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.29047/01225383.444","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 1
摘要
本文比较了采用化学计量学分析方法建立的模型的性能,这些模型采用近红外和紫外可见光谱数据,从不同的Ecopetrol sa, Barrancabermeja炼油厂催化裂化装置对应的原料样品中获得,用于预测一些重要的物理化学性质。结果显示了本文所评估的两种方法在跟踪这些类型的炼油厂流的质量方面的效用,并展示了每种方法在预测所评估的原料特性方面的优缺点。
COMPARISON BETWEEN NIR AND UVVIS SPECTRA CHEMOMETRICS FOR PREDICTING FCC FEEDSTOCKS PROPERTIES
In this paper a comparison is made between the performance of models developed by applying chemometric analysis to NIR and UVVIS spectral data obtained from feedsctock samples corresponding to the different Ecopetrol S.A., Barrancabermeja Refinery FCC units for predicting some important physicochemical properties. The results show the utility of both methodologies here evaluated to follow up the quality of these types of refinery streams and present the advantages and disadvantages of each methodology for predicting the feedstock properties here evaluated.
期刊介绍:
The objective of CT&F is to publish the achievements of scientific research and technological developments of Ecopetrol S.A. and the research of other institutions in the field of oil, gas and alternative energy sources.
CT&F welcomes original, novel and high-impact contributions from all the fields in the oil and gas industry like: Acquisition and Exploration technologies, Basins characterization and modeling, Petroleum geology, Reservoir modeling, Enhanced Oil Recovery Technologies, Unconventional resources, Petroleum refining, Petrochemistry, Upgrading technologies, Technologies for fuels quality, Process modeling, and optimization, Supply chain optimization, Biofuels, Renewable energies.