Determination of the total acid number (TAN) of used mineral oils in aviation engines by FTIR using regression models

[EN] Total acid number (TAN) has been considered an important indicator of the oil quality of used oils. TAN is determined by potentiometric titration, which is time-consuming and requires solvent. A more convenient approach to determine TAN is based on infrared (IR) spectral data and multivariate regression models. Predictive models for the determination of TAN using the IR data measured from ashless dispersant oils developed for aviation piston engines (SAE 50) have been developed. Different techniques, including Projection Pursuit Regression (PPR), Partial Least Square, Support Vector Machines, Linear Models and Random Forest (RF), have been used. The used methodology involved a five folder cross validation to derive the best model. Then a full error measure over the whole dataset was taken. A backward variable selection was used and 25 highly relevant variables were extracted. RF provided an acceptable modelling technology with grouped dataset predictions that allowed transformations to be performed that fitted the measured values. A hybrid method considering group of bands as features was used for modelling. An innovative mechanism for wider features selection based on genetic algorithm has been implemented. This method showed better performance than the results obtained using the other methodologies. RMSE and MAE values obtained in the validation were 0.759 and 0.359 for PPR model respectively.The authors would like to thank Roland Tones of the Universidad Metropolitana for his collaboration in oil sample processing. BLDR acknowledges financial support from the Venoco Company. The authors also thank the Universidad Politecnica de Madrid for granting access to the CESVIMA (http://www.cesvima.upm.es/) HPC infrastructure. We would also like to thank the author Beatriz Leal de Rivas (in memoriam), for her efforts to conform this team of researchers from different areas of expertise, and we want to dedicate this work to her loving memory.Leal De-Rivas, BC.; Vivancos, J.; Ordieres Meré, J.; Capuz-Rizo, SF. (2017). Determination of the total acid number (TAN) of used mineral oils in aviation engines by FTIR using regression models. Chemometrics and Intelligent Laboratory Systems. 160:32-39. doi:10.1016/j.chemolab.2016.10.015S323916

Taking ethanol quality beyond fuel grade: A review

Ethanol production in the United States approached 15 billion gal/year in 2015. Only about 2.5% of this was food‐grade alcohol, but this represents a higher‐value product than fuels or other uses. The ethanol production process includes corn milling, cooking, saccharification, fermentation, and separation by distillation. Volatile byproducts are produced during the fermentation of starch. These include other alcohols, aldehydes, ketones, fatty acids and esters. Food‐grade ethanol is generally produced by wet milling, where starch and sugars are separated from the other corn components, resulting in much smaller concentrations of the impurities than are obtained from fermentation of dry‐milled corn, where cyclic and heterocyclic compounds are produced from lignin in the corn hull. Some of these volatile byproducts are likely to show up in the distillate and these fermentation byproducts in ethanol could cause unpleasant flavours and affect human health if used for human consumption. There is some interest in improving ethanol quality, since human consumption represents a higher value. Advanced purification techniques, such as ozone oxidation, currently used for drinking water and municipal wastewater treatment, offer possibilities for adaptation in ethanol quality improvement. The development of analytical techniques has enabled the detection of low‐concentration compounds and simple quality assurance of food‐grade alcohol. This review includes the most recent ethanol production methods, potential ethanol purification techniques and analytical techniques. Application of such techniques would aid in the development of simplified alcohol production

Exploiting Residue Curve Maps to Assess Thermodynamic Feasibility Boundaries under Uncertain Operating Conditions

The very first step of almost any separation process design procedure is the thermodynamic feasibility analysis. In the case of distillation, residue curve maps (RCMs) represent an essential tool to assess whether the separation is feasible or not. However, the analysis is generally carried out by referring to nominal operating conditions and product purities as specification. This means that, when process parameters are likely to undergo fluctuations, the prediction of the system response is not that obvious. An ABE/W (acetone−butanol−ethanol/water) mixture was then selected as a case study since it allows us to discuss several non-ideal thermodynamic behaviors and because of the renewed interest in biorefinery and sustainable processes during recent years. Residue curve mapping was then exploited to determine the thermodynamic feasibility range for multicomponent distillation processes as well as for distillation trains and process-intensified solutions taking into account both product purity and product recovery specifications. The final product of this study is a thorough procedure to determine the flexibility boundaries of feed and product compositions as well as an immediate and intuitive graphical representation from a binary standard distillation column to a complex multicomponent dividing wall column applicatio