Simultaneous determination of quality parameters of biodiesel/diesel blends using HATR-FTIR spectra and PLS, iPLS or siPLS regressions

Partial least-squares (PLS), interval partial least squares (iPLS) and synergy partial least squares (siPLS) regressions were used to simultaneous determination of quality parameters of biodiesel/diesel blends. Biodiesel amount, specific gravity, sulfur content and flash point were evaluated using spectroscopic data in the mid-infrared region obtained with a horizontal attenuated total reflectance (HATR) accessory. Eighty-five binary blends were prepared using biodiesel and two types of diesel, in concentrations from 0.2 to 30% (v/v). Fifty-seven samples were used as a calibration set, whereas 28 samples were used as an external validation set. All samples were characterized using the appropriated standard methods. The specific gravity values at 20 °C were in the range of 848.2-866.2 kg/m³. Flash point values lay between 47.0 and 79.5 °C. Sulfur content values varied from 312 to 1351 mg/kg. Raw spectra of the samples were corrected by multiplicative scatter correction (MSC) and were pre-processed using a mean-centered procedure. Algorithms iPLS and siPLS were able to select the most adequate spectral region for each property studied. For all the properties studied, the siPLS algorithm produced better models than the full-spectrum PLS, selecting the most important bands. The quantification of biodiesel was performed using two spectral regions between 650-1909 cm⁻¹ and 2746-3165 cm⁻¹, and an excellent correlation coefficient of R² = 0.9996 was obtained. The specific gravity was determined from the spectral region from 650 to 1070 cm⁻¹, which yielded a very good correlation coefficient of R² = 0.9987. The sulfur content was evaluated from the spectral regions of 1070-1491 cm⁻¹ and 2746-3165 cm⁻¹. A very good correlation coefficient of R² = 0.9995 was obtained, regardless of whether the samples were formulated with metropolitan or countryside diesel. Finally, the flash point was determined from the spectral region between 756 and 968 cm⁻¹ and a very good correlation coefficient of R² = 0.9982 was obtained.     

Catalytic cracking of rapeseed oil to high octane gasoline and olefins

Rapeseed is the most important energy crop in Europe. The basic idea of the presented work was to add vegetable oils to the standard FCC-feed in order to meet requirements on the increasing demand for climate-friendly produced fuels. The experimental test program was conducted in a fully continuously operated FCC pilot plant with internal CFB-design at Vienna University of Technology. Rapeseed oil was added in steps of 20 m% to the conventional feedstock, up to 100 m% addition. The influence on the process was observed. The obtained product spectrum at 550 °C was slightly modified in relation to standard feed VGO. The gasoline yield stayed roughly constant while the crack-gas yield decreased at higher ratios of rapeseed oil. Due to the oxygen content of rapeseed oil the additional lumps water and CO₂ are formed. Using pure rapeseed oil as feedstock for FCC leads to a total fuel yield on total feed of approximately 65 m% (23 m% gaseous hydrocarbons plus 42 m% gasoline). The gasoline achieved is oxygen free at high octane numbers of approximately RON 100 and MON 86.     

MIP-CGP工艺专用催化剂LDR-100HRB的工业应用

介绍中国石油石油化工研究院开发的LDR-100HRB催化剂在中国石油哈尔滨石化分公司600 kt·a~(-1)的MIP-CGP催化装置应用情况。在原料油性质变差条件下,LDR-100HRB催化剂表现出重油转化能力强、焦炭选择性好和汽油辛烷值高的特点。两次标定结果表明,干气产率降低0.38个百分点,油浆产率降低0.67个百分点,焦炭产率降低0.58个百分点,总液收增加1.63个百分点,汽油马达法辛烷值和研究法辛烷值分别增加1.5个单位和1.3个单位。     

Autoregressive modeling of near-IR spectra and MLR to predict RON values of gasolines

A new calibration method that accurately predicts the Research Octane Number (RON) values of gasoline fractions, based on their infrared spectra, is presented. This model combines Linear Predictive Coding (LPC) and multiple linear regression (MLR) as an integrated estimation technique. Spectral information from the 4800-3520 cm⁻¹ range was initially encoded into Linear Predictive (LP) coefficients, which were used as predictor variables in the MLR model against RON values. The model was trained and tested on an extensive data set (384 gasoline samples) and found to ensure prediction accuracy of 0.3 RON Root Mean Squared Error (RMSE). The LPC technique was found to be efficient in capturing spectral features of the entire range, related to the RON characteristics of the gasoline samples, without the need of any pretreatment on the experimental raw data. The small number of input variables in the regression model ensures a robust, easy-to-use and high accuracy prediction model.     

计算机辅助汽油调合设计

引言 汽油调合是炼油生产的重要环节,由于汽油是炼油厂的主要产品,调合结果对炼油厂的经济效益影响甚大,因此,炼油企业均希望通过对调合汽油的生产优化获取更多的利润.     

多产柴油催化剂CC-20D与助剂CA-100在催化裂化装置上的混合应用

本文介绍了多产柴油催化剂CC-20D与高效助辛并增产液化气助剂CA-100在克拉玛依石化厂重催装置上的混合应用情况。结果表明CC-20D具有增产柴油效果明显。抗污染能力强。产品选择性好等优点;CA-100提高辛烷值和增产液化气能力强。使用CC-20D并配合使用3%的CA-100时,柴油产率提高3.27wt%,液化气提高1.9wt%,总液收提高1.81wt%,汽油RON提高1.7,MON提高0.8,创造了较好的经济效益。     

Multivariate calibration in Fourier transform infrared spectrometry as a tool to detect adulterations in Brazilian gasoline

In the present work, Fourier transform infrared spectroscopy (FTIR) in association with multivariate chemometrics classification techniques was employed to identify gasoline samples adulterated with diesel oil, kerosene, turpentine spirit or thinner. Results indicated that partial least squares (PLS) models based on infrared spectra were proven suitable as practical analytical methods for predicting adulterant content in gasoline in the volume fraction range from 0% to 50%. The results obtained by PLS provided prediction errors lower than 2% (v/v) for all adulterant determined. Additionally, Soft Independent Modeling of Class Analogy (SIMCA) was performed using all spectral data (650-3700 cm⁻¹) for sample classification into adulterant classes defined by training set and the results indicated that undoubted adulteration detection was possible but identification of the adulterant was subject to misclassification errors, specially for kerosene and turpentine adulterated samples, and must be carefully examined. Quality control and police laboratories for gasoline analysis should employ the proposed methods for rapid screening analysis for qualitative monitoring purposes.     

Determination of fluid catalytic cracking gasoline octane number by n.m.r. spectrometry

The correlation between octane number and fluid catalytic cracking gasoline chemical composition has been determined. The gasoline chemical composition is obtained by ¹H n.m.r. spectroscopy; the research octane number is determined according to the standard engine method (ASTM 2699) and the correlation is tested by applying a linear regression model. The method presented provides a determination of FCC gasoline RON from a small quantity of sample (⩽ 0.5 ml) in only 30min with a satisfactory level of accuracy (s = 0.451). The method is especially useful when only a small quantity of sample is available and where the standard engine method is not applicable.     

全馏分催化汽油加氢脱硫工艺的标定与运行分析

中海油惠州炼化为了满足全厂汽油升级至国Ⅳ、Ⅴ标准的要求,新建一套50万吨/年催化汽油加氢脱硫装置。该装置采用全馏分催化汽油选择性加氢脱硫技术（CDOS-FRCN）,催化剂采用海顺德公司的催化剂专利技术。装置标定情况说明,催化汽油经全馏分加氢精制后,加氢精制汽油硫质量分数达到11 μg/g,硫醇硫质量分数达到10 μg/g,汽油辛烷值损失小于1.5个单位。二反入口温度对脱硫效果和辛烷值损失有很大影响,温度越高,则脱硫率越高,但辛烷值损失偏大。CDOS-FRCN技术能够有效降低汽油硫含量,减少辛烷值损失,可为炼油厂生产硫含量小于50 μg/g甚至10 μg/g的清洁汽油提供经济、灵活的技术方案。     

Cleaner gasoline production by using glycerol as fuel extender

Glycerol, a major by-product of biodiesel production, was employed as a fuel extender in this study. The process was originally investigated by etherifying the entire fluidized catalytic cracking (FCC) gasoline with glycerol. The reactions were carried out in a pressurized liquid phase reactor in the presence of three different catalysts (i.e. Amberlyst 16, Amberlyst 15, and β-zeolite) at 70 °C and 2.6 MPa with a volume ratio of FCC gasoline to glycerol ratio of 84:16 for 10 h. The catalytic activity could be ordered as Amberlyst 16 > Amberlyst 15 >> β-zeolite. The properties of FCC and etherified FCC products were determined by the standard analysis of Research Octane Number (RON), blending Reid vapor pressure (bRvp), distillation temperature following the standard methods of ASTM D-2699, ASTM D-5191 and ASTM D-86, respectively. It was found that the olefin content decreased opposing with increasing of octane number due to ethers of glycerol formation and the etherified gasoline product has lower bRvp than that of original FCC gasoline. The process of FCC gasoline etherification with glycerol showed great environmental benefits; in addition, ethers produced renewably from glycerol could extend the gasoline volume.     

DSO-FCC汽油加氢脱硫技术开发与应用

介绍了玉门炼油厂320 kt/a催化裂化汽油加氢脱硫装置,首次采用了中国石油石油化工研究院开发研究的DSO-FCC汽油加氢脱硫技术。结果表明:加氢后重汽油硫含量随原料硫含量波动,原料平均硫含量从451μg/g降到166μg/g,脱硫率为63.2%,RON平均损失0.35个单位,在大幅度降低硫含量的同时辛烷值损失较小,能够保证国Ⅲ清洁汽油的出厂。     

分数阶微分在红外光谱数据预处理中的应用

比较了Grumwald-Letnikov分数阶微分算法和常用的Savitzky-Golay算法对汽油样品近红外光谱数据1阶微分和2阶微分结果。对25个汽油样品和41个煤炭样品的近红外光谱数据通过Savitzky-Golay算法进行平滑,平滑后1阶微分和平滑后2阶微分处理;通过Grumwald-Letnikov算法进行平滑后的0.2～2.2阶的21个阶次的微分处理。汽油样品的处理数据结合汽油的辛烷值、初馏点指标数据和煤炭样品的处理数据结合煤炭挥发分、氢含量和氮含量指标数据分别通过PLS建立数据模型,利用留一法全交互验证选取最优主成分。通过预测残差平方和(PRESS)和相关系数(R)对数据,处理方法进行评估。结果表明:分数阶微分可以应用于近红外光谱的数据预处理,对于相同数据的不同指标取得最优值的分数阶微分的阶次是不同的。     

Application of FTIR Spectroscopy for the Determination of Virgin Coconut Oil in Binary Mixtures with Olive Oil and Palm Oil

Rapid Fourier transform infrared (FTIR) spectroscopy combined with attenuated total reflectance (ATR) was applied for quantitative analysis of virgin coconut oil (VCO) in binary mixtures with olive oil (OO) and palm oil (PO). The spectral bands correlated with VCO, OO, PO; blends of VCO and OO; VCO and PO were scanned, interpreted, and identified. Two multivariate calibration methods, partial least square (PLS) and principal component regression (PCR), were used to construct the calibration models that correlate between actual and FTIR-predicted values of VCO contents in the mixtures at the FTIR spectral frequencies of 1,120–1,105 and 965–960 cm⁻¹. The calibration models obtained were cross validated using the “leave one out” method. PLS at these frequencies showed the best calibration model, in terms of the highest coefficient of determination (R ²) and the lowest of root mean standard error of calibration (RMSEC) with R ² = 0.9992 and RMSEC = 0.756, respectively, for VCO in mixture with OO. Meanwhile, the R ² and RMSEC values obtained for VCO in mixture with PO were 0.9996 and 0.494, respectively. In general, FTIR spectroscopy serves as a suitable technique for determination of VCO in mixture with the other oils.     

Simultaneous polarographic determination of isoniazid and rifampicin by differential pulse polarography method and support vector regression

A differential pulse polarography (DPP) for the simultaneous determination of isoniazid and rifampicin was proposed. Under optimum experimental conditions (pH = 7, scan rate = 10 mV/s, pulse amplitude = −50 mV), serious overlapping polarographic peaks were observed in the mixture of these compounds. In this study, support vector regression (SVR) was applied to modeling the overlapped polarograms. Furthermore, a comparison was made between the performance of SVR and partial least square (PLS) on data set. The experimental calibration matrix was designed with 30 mixtures of these compounds. Calibration graphs were linear in the range of 6 × 10⁻⁸-10⁻⁴ and 10⁻⁷-10⁻⁴ M for isoniazid and rifampicin, respectively. The results demonstrated that SVR is a good well-performing alternative for the analysis and modeling of DPP data than the commonly applied PLS technique.     

降低催化汽油烯烃含量的灵活多效催化裂化工艺

在对催化裂化反应机理分析的基础上,提出了一种新的催化剂并联流动的双提升管催化裂化反应体系———灵活多效催化裂化(FDFCC)工艺。该工艺能显著降低催化裂化汽油的烯烃含量,中试及工业应用结果表明,烯烃含量可降低20%～30%,硫含量下降15%左右,改质汽油诱导期增加,马达法辛烷值(MON)和研究法辛烷值(RON)略有增加,苯含量基本维持不变,芳烃含量远小于规定指标。     

New methods for the preparation of high-octane components from catalytic cracking olefins

A new method has been suggested for the preparation of high-octane components from the butane–butylene fraction (BBF) in two stages. At the first stage, the BBF olefins are oxidized with N₂O into carbonyl compounds with high selectivity without forming the products of deep oxidation and water. The process occurs in the gas phase in a flow reactor without using a catalyst at a temperature of 400°C and a pressure of 2 MPa with high conversion of both olefins and nitrous oxide. The blending octane number of the oxidation product is 118–133 (RON) and 99–104 (MON). At the second stage, the mixture of carbonyl compounds is hydrogenated with hydrogen in the presence of the Ni/Al₂O₃ catalyst. The hydrogenation occurs at 150–160°C in a flow reactor in the gas phase. The aldehydes are completely transformed into alcohols, while the ketones can remain in the product under certain conditions. The blending octane number of the hydrogenation product is 111–112 (RON) and 95–96 (MON), which is smaller than for the BBF oxidation product, but larger than for the alkylate obtained in the course of conventional butene alkylation with isobutane (RON is 95–97 and MON is 93–95). Synthesis of high-octane components by this procedure can be useful in practice, especially in productions with huge release of nitrous oxide.     

Neural network (ANN) approach to biodiesel analysis: Analysis of biodiesel density, kinematic viscosity, methanol and water contents using near infrared (NIR) spectroscopy

The use of ethanol and biodiesel, which are alternative fuels or biofuels, has increased in the last few years. Modern official standards list 25 parameters that must be determined to certify biodiesel quality, and these analyses are expensive and time-consuming. Near infrared (NIR/NIRS) spectroscopy (4000-12,820 cm⁻¹) is a cheap and fast alternative to analyse biodiesel quality, when compared with infrared, Raman, or NMR methods, and quality control can be done in realtime (on-line).We compared the performance of linear and non-linear calibration techniques - namely, multiple linear regression (MLR), principal component regression (PCR), partial least squares regression (PLS), polynomial and Spline-PLS versions, and artificial neural networks (ANN) - for prediction of biodiesel properties from near infrared spectra. The model was created for four important biodiesel properties: density (at 15 °C), kinematic viscosity (at 40 °C), water content, and methanol content. We also investigated the influence of different pre-processing methods (Savitzky-Golay derivatives, orthogonal signal correction) on the model prediction capability. The lowest root mean squared errors of prediction (RMSEP) of ANN for density, viscosity, water percentage, and methanol content were 0.42 kg m⁻³, 0.068 mm² s⁻¹, 45 ppm, and 51 ppm, respectively. The artificial neural network (ANN) approach was superior to the linear (MLR, PCR, PLS) and “quasi”-non-linear (Poly-PLS, Spline-PLS) calibration methods.     

A new method for determining gossypol in cottonseed oil by FTIR spectroscopy

A new method was developed to determine the gossypol content in cottonseed oil using FTIR spectroscopy with a NaCl transmission cell. The wavelengths used were selected by spiking clean cottonseed oil to gossypol concentrations of 0–5% and noting the regions of maximal absorbance. Transmittance values from the wavelength regions 3600–2520 and 1900–800 cm⁻¹ and a partial least squares (PLS) method were used to derive FTIR spectroscopic calibration models for crude cottonseed, semirefined cottonseed, and gossypol-spiked cottonseed oils. The coefficients of determination (R ²) for the models were computed by comparing the results from the FTIR spectroscopy against those obtained by AOCS method Ba 8-78. The R ² were 0.9511, 0.9116, and 0.9363 for crude cottonseed, semirefined cottonseed, and gossypol-spiked cottonseed oils, respectively. The SE of calibration were 0.042, 0.009, and 0.060, respectively. The calibration models were cross-validated within the same set of oil samples. The SD of the difference for repeatability and accuracy of the FTIR method were better than those for the chemical method. With its speed (ca. 2 min) and ease of data manipulation, FTIR spectroscopy is a useful alternative to standard wet chemical methods for rapid and routine determination of gossypol in process and/or quality control for cottonseed oil.     

Revisiting of dimensional scaling of linear chains in dilute solutions

The dimensions of linear polymer chains are scaled to their molar mass (M) as R = kM^α with α = 1/2 and 3/5 in a theta and an athermal solvent, respectively. In a good solvent, both k and α are a function of the solvent quality and chain length range. A high-temperature laser light-scattering spectrometer was used to measure the average radius of gyration (〈R_g〉) and hydrodynamic radius (〈R_h〉) of a set of narrowly distributed linear polystyrene chains in decalin over a wide temperature range. k and α in the scaling experimentally varying with T over a chain length range was analyzed. The results reveal that for 〈R_g〉, α = 0.59 − 0.09exp(−τ/0.066) and k = 0.60τ^2α−1, reasonably agreeing with the thermal blob theory. For 〈R_h〉, α = 0.59 − 0.09exp(−τ/0.106), but k deviates from the relationship of k ∝ τ^2α−1, reflecting that the hydrodynamic interaction and chain draining are not considered in the thermal blob theory.