Studying pyrolysis products of bottom-of-the-barrel fuel with Py-GCxGC- TOF/CSD/FID

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A chemical kinetics approach for heavy fuel oils gasification modelling

reportRefinery oil residue commonly considered the bottom of the barrel, can no longer be a waste. The increasing energy demand and the constant depletion of light oil supply make it crucial to find a suitable way to convert residual oils into valuable fuels. The gasification process represents a possible solution to this problem. Gasification is a thermo-process conducted in poor oxygen conditions, intending to obtain a hydrogen and carbon monoxide mixture, commonly named syngas. Gasification is widely implemented on an industrial scale to treat complex combinations such as biomasses, plastic waste, and coal. Most of the studies in the literature approach gasification modelling by studying the chemical equilibrium or with Computational fluid dynamics (CFD). However, the chemical equilibrium approach is well-performing in predicting the major gasification products, like hydrogen, carbon monoxide, carbon dioxide, and water. Thus, missing some crucial information like side-products formation or the evolution of conditions along the reactor, like temperature and species profile. The CFD approach overtakes the problems of the equilibrium approach, thus requiring a high level of complexity and being computationally expensive. The approach here proposed to model heavy oil gasification is based on the definition of a suitable kinetics model to target the evolution of all the essential variables along the reactor, thus with very low computational cost. The gasification process results from three different steps with different characteristic times. The first step is feed pyrolysis; liquid or solid feeds are exposed to very high temperatures. This triggers the thermal-decomposition reactions resulting in the volatilization of the feed in smaller gas molecules and the formation of a solid residue (CHAR). The second step is the partial combustion of gas compounds in homogeneous gas phase reactions. Finally, the last and slowest step is gasifying the solid products generated during the pyrolysis. The modelling approach is based on defining different reactive pathways for the three steps. The major challenge in modelling the first step is defining a proper framework for the feed characterization. A surrogate mixture is used to mimic feed chemical and physical properties. The surrogate is defined according to practical information on the feed; specifically, the SARA (Saturates, Aromatics, Resins, Asphaltenes) analysis and the elemental characterization are used to define the appropriate surrogate starting from a poll of nineteen key molecules. The pyrolysis of each surrogate molecule is described by a first-order irreversible reaction leading to the formation of gas and solid products (CHAR). The partial combustion is then described by coupling a gas phase mechanism. Depending on the required details, the gas phase mechanism can be either detailed or reduced. The gas phase mechanism accounts for the combustion of gas species released during the previous step. The last step describes the gasification of the CHAR generated in the first step, modelled with a series of global reactions defined empirically. The kinetics approach described above allows estimating major gasification products and eventual side products according to the level of details desired. It permits an assessment of much more information that cannot be extrapolated using a chemical-equilibrium approach like the reactor thermal profile and species evolution, and computational cost is much lower than CFD simulations

Kinetics mechanism of asphaltenes liquid-phase pyrolysis

The world energy demand is continuously increasing while the energy supply is still strongly related to fossil fuel, and likely to say so in the near future. However, the availability of high-quality crude oil feedstocks is constantly depleting. Heavy Fuel Oils (HFOs) are expected to play a vital role in the future of the energy supply as fuels for power generation and marine shipping. This work presents the first step in the formulation of a kinetics model aimed to reconstruct the HFOs pyrolytic behavior as the weighted sum of their SARA (Saturates, Aromatics, Resins, Asphaltenes) fractions contribution. In this work, details of the model to describe the asphaltenes pyrolysis is reported. The development of the model followed two main steps. The first one concerned the formulation of a suitable characterization framework being HFOs and asphaltenes complex mixtures made by thousands of different compounds. The characterization framework is based on the design of five pseudo components which are used to generate surrogate mixtures to mimic actual asphaltenes samples. The surrogate mixture is generated as the linear combination of pseudo components to reproduce the sample’s elemental composition. The pseudo components structure was designed taking advantage of experimental information from literature and in-house experiments performed at King Abdullah University of Science and Technology (KAUST). The second step was the development of the pyrolysis kinetics scheme. The formulation of the kinetic model proceeded through chemistry-related considerations intending to reproduce the all-significant pyrolysis products. A reaction pathway is assigned to each pseudo component with the task to approximate the overall kinetics. Model parameters such as activation energy, pre-exponential factors, and stoichiometric coefficients of each reaction were tuned following a data fitting approach to match experimental evidence. The model obtained is predictive and versatile being able to reproduce the pyrolytic behavior of different asphaltenes samples just knowing their elemental composition. The mechanism of asphaltenes represents a first step in the formulation of a comprehensive kinetics scheme for HFOs, which can be adopted for design, tuning, and optimization of combustion modeling processes

Sonoprocessing of oil: Asphaltene declustering behind fine ultrasonic emulsions

Despite the transition toward carbon-free energy carriers, liquid fossil fuels are expected to occupy an important market share in the future. Therefore, it is crucial to develop innovative technology for better combustion reducing the emissions of pollutants associated with their utilization. Water in oil (w/o) emulsions contribute to greener combustion, increasing carbon efficiency and reducing emissions. Water content, emulsions stability, and droplet size distributions are key parameters in targeting the efficient use of emulsions as combustibles. In particular, for fixed water content, the finer the emulsion, the better its beneficial effect on combustion. In this work, two emulsions, mechanically and ultrasonically generated, were compared. Cryogenic scanning electron microscopy (cryo-SEM) allowed the visualization of water droplets inside the oily matrix. No surfactants were added to the oil, due to its high asphaltenic content. Asphaltene molecular aggregates, namely clusters, act as natural surfactants stabilizing the emulsions by arranging at w/o interface and forming a rigid film. The asphaltenic rigid film is clearly visualized in this work and compared for the two emulsions. The results showed finer water droplets in the ultrasonically generated emulsion, together with a reduction in the thickness of the asphaltenic film. Ultrasonically induced cavitation favored the de-clustering (breakage of intermolecular forces) of asphaltene molecules. Thus, smaller clusters allowed to stabilize smaller water droplets resulting in an ultra-fine emulsion, which improves the combustion performances of the fuel

Chemical kinetics of SARA fractions pyrolysis: Resins

This work presents a predictive and generally applicable approach to resin pyrolysis modeling. Resins extracted from heavy fuel oil 380 (HFO) and vacuum residue oil (VRO) were tested for elemental composition, chemical structure, thermal degradation behavior, and distribution of pyrolysis products using different state-of-the-art experimental techniques. The in-house experiments, together with extensive literature research, guided the formulation of five pseudo-components for the definition of a fuel surrogate. The atomic ratios of the surrogate molecules were defined to be able to replicate the elemental composition of all the data with their linear combination. This approach makes the model flexible and readily applicable to any resin sample just by knowing its elemental composition. The kinetics mechanism was developed by coupling each pseudo-component with a decomposition reaction pathway. The choice of the kinetics parameters was driven by the experimental information available. The model presented a satisfactory agreement with experimental data used for the validation. The kinetic model represents a step of a more comprehensive project aimed at reconstructing the chemical kinetics of heavy and residual oils as a combination of their saturate, aromatic, resin, and asphaltene (SARA) fractions

Unraveling the complexity of pyrolysates from residual fuels by Py-GCxGC-FID/SCD/TOF-MS with an innovative data processing method

Residual fuels, often called 'bottom-of-the-barrel' are expected to play an important role in the transition towards a purely renewable energy market. Processes are required to upgrade such fuels and convert them into energy more cleanly and sustainably. To this goal, researchers aim to improve the understanding of their structure and reactivity. Given their complex nature and different chemical compositions, comprehensive two-dimensional gas chromatography (GCxGC) is well suited to provide a detailed characterization of the volatiles released during the pyrolysis of the residual fuels. This study reports a detailed characterization of pyrolysates released during the pyrolysis of two oil samples analyzed using a Py-GCxGC-FID/SCD/TOF-MS. The mass spectra generated with the electron impact ionization TOF-MS detection were used for species identification. An algorithm was developed and described here for the screening and post-processing of the detected peaks. Following algorithm postprocessing, the species identification confirms that this workflow is suitable for unraveling the complex nature of the complex mixture released during the pyrolysis of the oil samples. The algorithm results were verified using information from a flame ionization detector (FID) and a sulfur chemiluminescence detector (SCD), and the extraction of fragmentation patterns based on the literature. The chemical structure of pyrolysis products is described and classified into 26 molecular classes. The methodology presented in this work can be extended to other complex mixtures, such as bio-oils, plastics, and biomasses

Numerical model of an ultrasonically induced cavitation reactor and application to heavy oil processing

This study describes a numerical approach to model ultrasonically induced cavitation (UIC) reactors. UIC forms vapour-filled cavities in a liquid medium due to an applied acoustic field and their eventual collapse. UIC reactors are characterized by the presence of a vibrating probe that generates pressure waves by high-frequency oscillations (>20 kHz), which control the formation, dynamics, and eventual collapse of the vapour cavities. Those vapour cavities eventually enhance mixing and favour the occurrence of gas-liquid reactions. The zones of high mixing and reactivity coincide with the presence of the bubble cloud, which depends on the shape of the vessel and sonotrode. The development of advanced computational fluid dynamics (CFD) models is crucial to optimizing UIC processes’ geometry and operation parameters. A new algorithm for modelling UIC has been implemented within the OpenFOAM framework in the present study. The volume-of-fluid (VoF) method employs a diffuse interface approach for the volume fraction transport equation. The bubble dynamics are solved with sub-grid models, and the coupling between the main flow field and the sub-grid scales is performed through source terms in the transport equations. The source terms are de-coupled from convective and diffusive components of the volume fraction equation. The history of the bubbles is considered to consist of nucleation, oscillations, and collapse. The oscillations are resolved via the Rayleigh–Plesset equation. The concluding part of the work demonstrates the application of the algorithm to simulate the operation of an UIC reactor, which was designed to desulfurize fuels using the oxidative (ODS) process

Important Aspects of Nutrition in Children with Cancer1

Adequate nutrition during cancer plays a decisive role in several clinical outcome measures, such as treatment response, quality of life, and cost of care. However, the importance of nutrition in children and young adults with malignancies is still an underestimated topic within pediatric oncology. The importance of our work is to reinforce and indicate that malnutrition in children with cancer should not be accepted at any stage of the disease or tolerated as an inevitable process. Unique to our manuscript is the close collaboration, the exchange of knowledge and expertise between pediatric oncologists and a nutritional specialist, as well as the comprehension of the mechanisms during cancer cachexia and malnutrition. We provide a critical review of the current state of research and new knowledge related to nutritional management in childhood cancer