乙醇柴油的储存稳定性研究

介绍了对乙醇柴油的相溶性、低温稳定性、自然储存稳定性进行的研究工作.以相分离温度来评价乙醇柴油的相溶性,结果显示在乙醇体积分数低于10%时,乙醇柴油的相分离温度基本不变,乙醇含量增大,相分离温度升高;在乙醇体积分数为50%时,相分离温度为最大值.加入助溶剂能明显增强乙醇柴油的相溶性并延长低温稳定时间.自然储存试验结果显示,乙醇柴油密封储存三个月没有明显的乙醇溶解不均匀或分层现象,储罐内各个位置油样中乙醇含量和水含量基本保持稳定.乙醇柴油开口储存导致乙醇含量和水含量发生变化,最后趋于稳定.     

乙醇柴油性能研究

 以常二线柴油、常三线柴油、催化裂化柴油、催化加氢柴油和0号轻柴油为基础油,分别配制了不同体积分数的乙醇柴油,对乙醇柴油的互溶性、理化性能和发动机性能进行了研究。结果表明,商品柴油与乙醇的互溶性能及稳定性能良好;水分会严重影响乙醇柴油的稳定性;助溶剂可以适当改善乙醇柴油的容水性;加入乙醇后,能不同程度地降低乙醇柴油的凝点和冷滤点;乙醇柴油的腐蚀试验结果能够达到国家燃油标准;乙醇的加入使得柴油的密封性能变差,闪点降低,从而增加了柴油的着火危险性;与商品柴油相比,乙醇柴油的燃料消耗率和排气烟度相当,NOx排放降低。     

碳酸二甲酯柴油混合燃料的助溶及性质研究

采用异辛醇、异戊醇、异丁醇为助溶剂添加到碳酸二甲酯(DMC)柴油混合燃料中进行改性研究,测定了柴油-DMC二元临界互溶曲线和柴油-DMC-助溶剂三元互溶平衡曲线,考察了助溶剂用量、温度与混合燃料比例的关系。结果表明,异辛醇的体积分数为3.38%即可保证混合燃料的稳定性,助溶效果较优;添加DMC和醇类助溶剂后,油品的密度增加、粘度降低、水分含量和酸度值升高,初馏点下降,50%馏出温度略下降,90%和95%馏出温度几乎不变,十六烷值指数降低超过10个单位。     

乙醇柴油对不同添加剂感受性的研究

研究了醇类助溶剂和表面活性剂对乙醇柴油容水量和相分离温度的影响，考察了加入助溶剂和表面活性剂以及其它柴油添加剂后乙醇柴油的氧化安定性、润滑性和低温流动性的变化。结果表明，醇类助溶剂中正癸醇对乙醇柴油的助溶效果最好，亲水亲油平衡值为5～10的表面活性剂对于改善乙醇柴油的容水稳定性效果较好。乙醇柴油无需加入抗氧化稳定剂，加有表面活性剂的乙醇柴油无需加入润滑性添加剂，但可加入流动改进剂和十六烷值改进剂。     

一种生物乙醇柴油混合燃料及其制备方法

该专利涉及一种生物乙醇柴油混合燃料及其制备方法。该生物乙醇柴油混合燃料各组分体积分数如下：浓度为95％的含水乙醇10％～20％;柴油40％-45％;生物柴油35％～40％;助溶剂5％。按体积分数取各组分,按扣下顺序混合：先将柴油与生物柴油混合,     

加氢/改质工艺组合满足清洁柴油的多种需求

介绍了抚顺石油化工研究院开发的深度脱硫加氢精制、MCI、临氢降凝、催化裂化(FCC)柴油深度脱芳烃等专有技术及其组合工艺的技术特点。应用加氢精制—临氢降凝组合工艺加工劣质柴油，拓宽了柴油临氢降凝原料来源，柴油凝点可降至—35℃以下，硫脱除率达95％以上；应用加氢精制—MCI组合工艺加工FCC柴油，柴油硫含量可障至50μg／g以下，十六烷值提高8—12个单位，柴油收率达95％-98％；应用MCI—降凝组合工艺加工FCC和直馏柴油，可使柴油的凝点降至—35℃以下，十六烷值提高10个单位；应用加氢/改质—脱芳烃组合工艺、单段工艺流程加工芳烃质量分数为71．2％、十六烷值低于24的FCC柴油，在氢分压为8．0MPa、反应温度为360℃、体积空速为0．6h^-1、氢油体积比为500的条件下，柴油芳烃质量分数降至29．6％，十六烷值提高至39．8，而采用该工艺两段工艺流程可使柴油的芳烃质量分数降至16．5％，十六烷值提高至44．7。     

CCD近红外光谱仪在柴油生产控制分析中的应用

介绍了电荷耦合器件（ Ｃ Ｃ Ｄ）近红外光谱仪在柴油生产控制分析中的应用,通过对直馏柴油、加氢精制柴油及成品柴油十六烷值、密度、凝点、闪点及馏程等质量指标的测定及与标准测定方法的对比,验证了近红外光谱测定柴油性质的可靠性。试验证明,近红外方法具有分析速度快、重现性好、分析成本低等特点。     

劣质原料油加氢改质技术的应用优化研究

研究了两种不同劣质原料油通过加氢改质反应生产优质国Ⅵ柴油调合组分。首先,在相同工艺条件下,考察了原料油性质对加氢改质产品分布以及性质的影响;其次,以此两种劣质原料油加氢改质所得的混合柴油为对象,考察轻、重柴油切割点对柴油密度、组成、十六烷值等性质的影响。结果表明：随着轻、重柴油切割点的提高,轻柴油与重柴油的密度、链烷烃含量以及十六烷值均逐渐增加;轻柴油十六烷值低,是劣质的柴油调合组分,但可以作为催化裂化原料;重柴油十六烷值高,但由于其凝点高,需要将其中更重的组分切出后,才能够作为优质的0号国Ⅵ柴油调合组分;对于上述两种混合柴油,轻、重柴油切割点控制在230℃,在控制凝点为0℃的前提下,重柴油组分收率最高,而且十六烷值能够满足国Ⅵ柴油标准要求。     

聚甲氧基二甲醚对柴油质量性能的影响

将聚甲氧基二甲醚(PODEn)分别加入到0号车用柴油和0号普通柴油中,考察其对柴油质量性能的影响。结果表明,当PODEn加剂量为10%(体积分数)时,柴油的十六烷值、校正磨斑直径、馏程、酸度均符合相应国家标准的要求;柴油的十六烷指数降低8~10个单位,密度有所增加,闪点(闭口)有所下降,部分样品的性能指标已不符合相应国家标准的要求。在低密度、合适馏程的0号基础柴油中加入10%(体积分数)PODEn,调合后柴油试样能够满足GB 19147—2013《车用柴油(Ⅴ)》标准要求。     

两段法柴油深度加氢处理的探索研究

对采用两段法加氢工艺加工某催化裂化柴油得到的芳烃质量分数低于25％的产品柴油窄馏分的性质进行了分析。结果显示,经两段加氢得到产物270—300℃馏分段的密度和芳烃含量最高;十六烷值随馏程增加而升高,当油品的沸点在150～300℃时,十六烷指数与十六烷值基本一致;沸点再升高,油品的十六烷指数与十六烷值的差值变大。据此推测出适当提高催化裂化柴油的终馏点,二段装填孔结构有利于270—300℃馏分扩散的、具有一定开环裂化功能的加氢催化剂是进一步改善该类工艺的方向。     

Near Infrared Spectroscopic Determination of Diesel Fuel Parameters Using Genetic Multivariate Calibration

The use of full spectral region from near infrared spectroscopic analysis does not always end up with a good multivariate calibration model as many of the wavelengths do not contain necessary information. Due to the complexity of the spectra, some of the wavelengths or regions may, in fact, disturb the model-building step. Genetic algorithms are one of the useful tools for solving wavelength selection problems and may improve the predictive ability of conventional multivariate calibration methods. This study demonstrates application of genetic algorithm-based multivariate calibration to near infrared spectroscopic determination of several diesel fuel parameters. The parameters studied are cetane number, boiling and freezing point, total aromatic content, viscosity, and density. Multivariate calibration models were generated using genetic inverse least squares (GILS) method and used to predict the diesel fuel parameters based on their near infrared spectra. For each property, a different data set was used and in all cases the number of samples was around 250. Overall, percent standard error of prediction (%SEP) values ranged between 2.48 and 4.84% for boiling point, total aromatics, viscosity, and density. However, %SEP results for cetane number and freezing point were 11.00% and 14.86%, respectively.     

Near Infrared Spectroscopic Determination of Diesel Fuel Parameters Using Genetic Multivariate Calibration

Abstract

The use of full spectral region from near infrared spectroscopic analysis does not always end up with a good multivariate calibration model as many of the wavelengths do not contain necessary information. Due to the complexity of the spectra, some of the wavelengths or regions may, in fact, disturb the model-building step. Genetic algorithms are one of the useful tools for solving wavelength selection problems and may improve the predictive ability of conventional multivariate calibration methods. This study demonstrates application of genetic algorithm-based multivariate calibration to near infrared spectroscopic determination of several diesel fuel parameters. The parameters studied are cetane number, boiling and freezing point, total aromatic content, viscosity, and density. Multivariate calibration models were generated using genetic inverse least squares (GILS) method and used to predict the diesel fuel parameters based on their near infrared spectra. For each property, a different data set was used and in all cases the number of samples was around 250. Overall, percent standard error of prediction (%SEP) values ranged between 2.48 and 4.84% for boiling point, total aromatics, viscosity, and density. However, %SEP results for cetane number and freezing point were 11.00% and 14.86%, respectively.     

NEURAL NETWORK PREDICTION OF CETANE NUMBERS FOR ISOPARAFFINS AND DIESEL FUEL

A backpropagation neural network was used to correlate and predict the cetane numbers of isoparaffins and diesel fuels. For the isoparaffins, the correlation was made between the chemical structure of the branched paraffins and their cetane number. Thirteen branched paraffins were employed to train the network. The group additivity method was used to express the degree of branching of the isoparaffins. According to their positions in the molecule structure, three carbon groups (methylene [-CH₂-] subdivided into methylene α, β and γ, or further, to a carbon that is not a methylene, methyne [>CH-] and quaternary carbon [>C<]) were regrouped into four categories, and included along with normal boiling points, as the network inputs. For the selected diesel fuels, different combinations of physical properties such as density, viscosity, aniline point, and distillation temperatures were tested as the neural network input. The best model was obtained using density, viscosity, aniline point and ASTM D86 measured distillation temperatures (IBP, 10%, 50%, 90% and FBP) as inputs. The trained network models, when applied to predict the cetane number of other isoparaffins and diesel fuel, were quite accurate.     

煤油与柴油按不同比例调合对油品特性的影响

将大连西太平洋炼油厂出口的成品煤油和柴油（混有少量进口柴油）按不同比例调合后,对调合油品的密度、粘度、倾点、闪点、硫含量、馏程、十六烷指数等性质进行了测定,考察了煤油与柴油按不同比例调合后上述各种性质的变化情况,为了解和掌握煤油与柴油调合后的特性变化,在油品检验数据上提供了参考.     

Properties Correlations and Characterization of Athabasca Oil Sands-derived Synthetic Crude Oil

Narrow fractions of Athabasca oil sands-derived synthetic crude oil (SCO) from Canada were obtained by distillation at 20 oC to 500 oC and characterized. The yield and properties, such as density, refractive index, viscosity, freezing point, sulfur and nitrogen content and UOP K-index, were correlated as a function of boiling temperature (Tb). The properties of naphtha fractions, jet fuel and diesel fractions could be predicted accurately with the correlations, which are useful for process design considerations, such as optimizing operating conditions of refinery processing units. The other key properties and characteristics of naphtha fractions, jet fuel, diesel and vacuum gas oil were also determined.     

柴油深度加氢脱硫脱芳烃工艺技术的研究与开发

对不同性质的柴油，可采用不同的加氢脱硫脱芳烃工艺技术生产清洁柴油。直馏柴油和焦化柴油采用单段加氢工艺技术，在适宜的工艺条件下，可以生产硫质量分数低于300μg／g、芳烃质量分数低于25％、十六烷值大于53的清洁柴油；劣质催化裂化柴油采用单段加氢工艺及催化剂匹配装填技术，在适宜的工艺条件下，可以生产密度0．8576g／cm^3、硫质量分数5．0μg／g、芳烃质量分数29．6％、十六烷值39.8的清洁柴油组分；劣质催化裂化柴油采用两段加氢工艺技术，可以生产密度0．8506g/cm^3、硫质量分数1．2μg／g、芳烃质量分数16．5％的清洁柴油组分。