Medjez II

Ce gisement princeps du faciès « Sétifïen* » joue un rôle majeur dans la caractérisation de la variabilité capsienne de l’Epipaléolithique du Maghreb, observée entre le VIII-Ve millénaire cal BC. On doit à Henriette Camps-Fabrer d’avoir souligné les éléments diagnostics d’une abondante et nouvelle documentation régionale. Recueillie lors de plusieurs campagnes de fouilles (entre 1963 et 1968), cette documentation est conservée à Alger, au CNRPAH. Bien après la première monographie sur le Caps..

Toward an optimal formulation of alternative jet fuels: Enhanced Oxidation and Thermal Stability by the addition of cyclic molecules

International audienceOxidation and thermal stability (OTS) are key concerns for the development of alternative jet fuels, as they imply complex physical and chemical phenomena such as autoxidation, pyrolysis, cooxidation reactions and transfer-limitation. The OTSof an alternative aviation fuel was characterized using PetroOxy test from 120-160°C and JFTOT test at 325°C. The alternative jet fuel is a Synthetic Paraffinic Keroseneproduced from Hydroprocessed Esters and Fatty Acids (HEFA-SPK). Results showed a high thermal stability of HEFA-SPK. However, a low oxidation stability was also observed. The oxidation stability of8model cyclicmolecules was evaluated. Results allowed to estimate the influence of the molecular structure of cyclic molecules on liquid phase reactivity involving the number and the hydrogenation of the aromatic rings and the number and chain-length of the aromatic alkyl groups.The addition of several alkylbenzenes increased almost linearly the induction period of HEFA-SPK. Tetralin and decalin acted as inhibitors of the radical chain mechanism at low concentration, although having inherently low oxidation stability. Besides offering a better oxidation stability, the addition of specific low fractions of several alkylbenzenes, tetralin and decalin to HEFA-SPK allowed to achieve a good thermal stability as well. These molecules represent good candidates to improve OTS of HEFA-SPK. This work opens the way for the development of future fit-for-purpose formulations of alternative jet fuels with an increased fraction of renewables

Production of Hydroprocessed Esters and Fatty Acids (HEFA) – Optimisation of Process Yield

Both Fischer-Tropsch (FT) and Hydroprocessed Esters and Fatty Acids (HEFA) Synthetic Paraffinic Kerosine (SPK) fuels are considered as leading alternative replacements for conventional jet fuel. To satisfy the requirements of Civil Aviation Authorities (CAA), their drop-in incorporations have been subjected to a rigorous certification process. To reach the ambitious incorporation targets, new routes for biofuels incorporation may need to emerge, involving optimizing the production processes and the blending strategies. This paper focuses on a new strategy for incorporating HEFA, allowing the process yield to be optimised. One of the major steps limiting the process yield for HEFA remains the isomerisation that allows production of a biofuel with very good cold flow properties. But this step introduces a substantial decrease of the overall yield (fuel component per kg of starting material) due to the production of light compounds, unsuitable for conventional jet fuel. In this work relaxing the freezing point requirement for the neat HEFA component (by decreasing the severity of the isomerisation step) is proposed in order to minimize the production of less valuable light compounds. This strategy could lead to a significant additional biofuel yield with respect to the oil compared to a process making a better freeze point component. This allows the land surface area necessary for HEFA feedstock cultivation to be reduced for a given amount of bio-jet fuel produced

Production of Hydroprocessed Esters and Fatty Acids (HEFA) – Optimisation of Process Yield

Both Fischer-Tropsch (FT) and Hydroprocessed Esters and Fatty Acids (HEFA) Synthetic Paraffinic Kerosine (SPK) fuels are considered as leading alternative replacements for conventional jet fuel. To satisfy the requirements of Civil Aviation Authorities (CAA), their drop-in incorporations have been subjected to a rigorous certification process. To reach the ambitious incorporation targets, new routes for biofuels incorporation may need to emerge, involving optimizing the production processes and the blending strategies. This paper focuses on a new strategy for incorporating HEFA, allowing the process yield to be optimised. One of the major steps limiting the process yield for HEFA remains the isomerisation that allows production of a biofuel with very good cold flow properties. But this step introduces a substantial decrease of the overall yield (fuel component per kg of starting material) due to the production of light compounds, unsuitable for conventional jet fuel. In this work relaxing the freezing point requirement for the neat HEFA component (by decreasing the severity of the isomerisation step) is proposed in order to minimize the production of less valuable light compounds. This strategy could lead to a significant additional biofuel yield with respect to the oil compared to a process making a better freeze point component. This allows the land surface area necessary for HEFA feedstock cultivation to be reduced for a given amount of bio-jet fuel produced

Production of Hydroprocessed Esters and Fatty Acids (HEFA) – Optimisation of Process Yield

Seconde et troisième génération de biocarburants: développement durable et compétitivit

Prediction of Flash Points for Fuel Mixtures Using Machine Learning and a Novel Equation

In this work, a set of computationally efficient, yet accurate, methods to predict flash points of fuel mixtures based solely on their chemical structures and mole fractions was developed. Two approaches were tested using data obtained from the existing literature: (1) machine learning directly applied to mixture flash point data (the mixture QSPR approach) using additive descriptors and (2) machine learning applied to pure compound properties (the QSPR approach) in combination with Le Chatelier rule based calculations. It was found that the second method performs better than the first with the available databank and for the target application. We proposed a novel equation, and we evaluated the performance of the resulting, fully predictive, Le Chatelier rule based approach on new experimental data of surrogate jet and diesel fuels, yielding excellent results. We predicted the variation in flash point of diesel–gasoline blends with increasing proportions of gasoline

Wide Range Experimental and Kinetic Modeling Study of Chain Length Impact on <i>n</i>‑Alkanes Autoxidation

The control of deposit precursors formation resulting from the oxidative degradation of alternative fuels relies strongly on the understanding of the underlying chemical pathways. Although C₈–C₁₆ <i>n</i>-alkanes are major constituents of commercial fuels and well-documented solvents, their respective reactivities and selectivities in autoxidation are poorly understood. This study experimentally investigates the influence of chain length, temperature (393–433 K), purity, and blending on <i>n</i>-alkanes autoxidation kinetics under concentrated oxygen conditions, using both Induction Period (IP) and speciation analysis. It also numerically constructs new detailed liquid-phase chemical mechanisms for n-C₈–C₁₄ obtained with an automated mechanism generator. Macroscopic reactivity descriptors such as IP, combined to microscopic ones, obtained from GC-MS analyses, are herein used to emphasize similarities and discrepancies in <i>n</i>-alkanes autoxidation processes. Experimental results highlight a nonlinear IP evolution with <i>n</i>-alkanes chain length, a linear IP variation for two component paraffinic blends, and similarities among oxidation product families. Experimental data from the present study and from the literature are used to evaluate n-C₈–C₁₄ mechanisms on IP and on monohydroperoxides (ROOH) concentrations. Under pure O₂ conditions, mechanisms generally predict IPs within a factor of 3 for intermediate and high temperature and even lower when air is used instead of pure oxygen. In addition, the chain length impact is also well reproduced, with a reactivity increase from C₈ to C₁₂ and a plateau for higher chain length. Rate of Consumption (RoC) analyses of n-C₈ and n-C₁₂ mechanisms evidenced the main role of peroxy radicals in autoxidation through fuel consumption, and ROOH and polyhydroperoxides (R­(OOH)₂) formation

Prediction of Density and Viscosity of Biofuel Compounds Using Machine Learning Methods

In the present work, temperature dependent models for the prediction of densities and dynamic viscosities of pure compounds within the range of possible alternative fuel mixture components are presented. The proposed models have been derived using machine learning methods including Artificial Neural Networks and Support Vector Machines. Experimental data used to train and validate the models was extracted from the DIPPR database. A comparison between models using an ample range of molecular descriptors and models using only functional group count descriptors as inputs was performed, and consensus models were created by testing different combinations of the individual models. The resulting consensus models’ predictions were in agreement with the available experimental data. Comparisons were also made between predictions of our models and correlations validated by the DIPPR staff. Our models were used to predict densities and dynamic viscosities of compounds for which no experimental data exists. Our models were also used to estimate other properties such as kinematic viscosities, critical temperatures, and critical pressures for compounds in the database. Finally, predictions were used to study the main trends of density and viscosity at the aforementioned temperatures as a function of the number of carbon atoms for chemical families of interest