Fast assessment of diene values in pyrolysis gasoline by UV-visible spectroscopy and multivariate calibration

Hilgemann, Maurício; Nascimento, Paulo Cı́cero do; Dias, Daiane; Guterres, Marcos V.; Stringhini, Fabiane M.; Carvalho, Leandro Machado de; Bohrer, Denise

doi:10.1016/j.petrol.2011.03.001

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…It requires collecting and sending the oil sample to a skilled chemical laboratory for off-line titration. Other laboratory-based analytical approaches , including liquid chromatography, near-infrared spectroscopy, and UV–vis spectroscopy have also been applied for oil-quality determination. For example, Cayuela et al used near-infrared spectroscopy (NIRS) to estimate the α-tocopherol and total tocopherol contents in oil at the same time .…”

mentioning

confidence: 99%

Contactless and Simultaneous Measurement of Water and Acid Contaminations in Oil Using a Flexible Microstrip Sensor

Xue

Tang

et al. 2019

ACS Sens.

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The assessment of the petroleum product quality often involves multiple indicators, among which water content and acid value are two major parameters. The complexity of an oil sample and the narrow space in pipeline transport make it difficult to monitor the oil quality in real-time. Considering the practical requirements, a new type of flexible microstrip sensor is proposed in this work. The shape and line width of the microstrip sensor are studied and optimized by theory and experiments. The proposed square spiral-based microstrip sensor has good water content detection resolution at high frequencies with less acid interference, and it can determine the acid value in the low-frequency band. The sensor surface is further passivated, protecting it from direct contact with the oil sample to enhance the electrochemical robustness, and still achieves good detection linearity and high sensitivity. After encapsulation on a flexible substrate, the proposed microstrip sensor realized the non-contact determination of the water content and acid value of oil at the same time, which is only a few millimeters in size and can conform to various tubing wall shapes. Due to the fact that the manufacture of the sensor is CMOS-compatible, we expect it to be readily applied to many other miniaturized chemical-sensing applications.

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mentioning

confidence: 99%

Contactless and Simultaneous Measurement of Water and Acid Contaminations in Oil Using a Flexible Microstrip Sensor

Xue

Tang

et al. 2019

ACS Sens.

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“…Root mean square error of calibration (RMSEC) and prediction (RMSEP) [31,45] were used to assess the precision of 9). The root mean square error of crossvalidation (RMSECV), as reported by Kehimkar et al [46] and Issa [31] as shown in Equation ( 10), was employed using the leave-one-out (LOO) and k-fold cross-validation approaches to compare the performance of PLSR, NLR, and NPR approaches, with and without outliers.…”

Section: Regression Analysis and Model Developmentmentioning

confidence: 99%

Parametric and Nonparametric Approaches of Reid Vapor Pressure Prediction for Gasoline Containing Oxygenates: A Comparative Analysis Using Partial Least Squares, Nonlinear, and LOWESS Regression Modelling Strategies with Physical Properties

Issa

2024

Modelling and Simulation in Engineering

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This study provides insights into the challenges involved in predicting the Reid vapor pressure (RVP) of gasoline-oxygenate blends (GOB), which is an important indicator of fuel quality and compliance with environmental and performance standards. Given the enormous variety of gasoline compositions and ratios available, there is a significant demand for a fast, straightforward, and cost-effective technique to predict RVP without relying on costly instruments or complicated spectral measurements that involve numerous input variables. A comparative performance analysis has been performed for different regression modelling strategies for predicting RVP in GOB, which is valuable for researchers and practitioners in the petroleum industry for saving time and money. Parametric and nonparametric approaches were compared using partial least squares regression (PLSR), nonlinear regression (NLR), and nonparametric regression (NPR) models. Locally weighted scatterplot smoothing (LOWESS) approach was applied to the NPR model. The gasoline’s physical characteristics (distillation curves and density) formed the basis for the analysis of these models’ performances. Acceptable error metrics have been reached for root mean square error of calibration and prediction (RMSEC and RMSEP) values, for the PLSR, NLR, and NPR models, which are 4.790, 6.235, 4.739, 6.149, 3.968, and 6.029, respectively, which are close for those reported in literature. The NPR model eliminates parametric constraints and allows for a different kind of data structure to emerge. The established models here demonstrate a sound ability to overcome barriers by omitting the use of inconvenient spectral measurements to save expense and simplify data calibration, making them a promising approach for RVP detection of GOB. This finding aids in the development of more accurate RVP prediction models and contributes to the optimization of fuel formulations.

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HPLC Method for Monitoring the Conjugated Dienes and Olefins in FCC, Coker Gasolines, and their Hydrogenated Products

Yadav

Kagdiyal

Arun

et al. 2015

Journal of Liquid Chromatography & Related Technologies

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The conjugated dienes if present in gasoline have the tendency to polymerize and cause fouling during various refinery processes. Therefore the conjugated dienes need to be reduced. While the conjugated dienes in gasoline are undesirable, the olefins are desirable and act as octane booster. The selective hydrogenation unit selectively reduces conjugated dienes keeping the content of olefins more or less intact. A method based on HPLC-UV-RI has been reported to simultaneously monitor the conjugated dienes and olefins content in the gasoline range samples. The reported method has the detection level of 0.02 (w/W)% for the total conjugated dienes with respect to 2,4-dimethyl 1,3-pentadiene (DMP). The calibration curve for DMP is drawn in the range 0.2-2.5% (w/W) and the R 2 is found to be 0.9972. The method is also applicable for the estimation of olefins content above 10% (w/W) level with respect to 1-octene. The calibration curve is drawn in the range 10-50% (w/W) of 1-octene and the R 2 is found to be 0.9995.

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Fast assessment of diene values in pyrolysis gasoline by UV-visible spectroscopy and multivariate calibration

Cited by 4 publications

References 7 publications

Contactless and Simultaneous Measurement of Water and Acid Contaminations in Oil Using a Flexible Microstrip Sensor

Contactless and Simultaneous Measurement of Water and Acid Contaminations in Oil Using a Flexible Microstrip Sensor

Parametric and Nonparametric Approaches of Reid Vapor Pressure Prediction for Gasoline Containing Oxygenates: A Comparative Analysis Using Partial Least Squares, Nonlinear, and LOWESS Regression Modelling Strategies with Physical Properties

HPLC Method for Monitoring the Conjugated Dienes and Olefins in FCC, Coker Gasolines, and their Hydrogenated Products

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