Pseudo-component Model Research Articles

Heavy fuel oil pyrolysis: A family of practical kinetic reaction models supported by TGA

The intricate nature and diverse composition of heavy fuel oil (HFO) pose significant challenges in constructing chemical kinetic models for its pyrolysis, gasification, and combustion processes. This study aims to introduce a model incorporating the kinetic impact of thermal decomposition reactions on pyrolysis. A novel methodology is proposed for formulating kinetic reaction models to forecast the mass transfer dynamics during the thermal decomposition of heavy fuel oil, as observed through thermogravimetric analysis. The principal objective is to predict the influence of heat on reaction kinetics, mass transfer phenomena, and the transformation of constituents. This investigation presents three distinct kinetic models: two focused on single-component representations, four structured as lumped mass models and an encompassing multi-pseudo-component model. Each model serves specific purposes tailored to its distinct applications. The lumped mass model accurately predicts the rates of light oil, middle oil, heavy oil, coke, and gas production. Conversely, the eleven pseudo-component model achieves superior precision by adjusting constituent counts based on fuel characteristics. Validation of the most effective lump model and the eleven pseudo-components confirms their reliability and validity in predicting system behavior.

Optimized lower pressure limit for condensate underground gas storage using a dynamic pseudo-component model

In the context of gas injection in reservoirs, the dilution process of components' thermodynamic properties has not been adequately represented in traditional numerical simulation methods. This study focuses on the Dalaoba condensate underground gas storage (CUGS) in China and establishes a dynamic pseudo-component model to identify the equilibrium point for gas storage facility efficiency and the condensate oil recovery rate. Using a multi-objective particle swarm optimization approach, thermodynamic parameters are estimated as functions of the injected gas volume. This dynamic pseudo-component model is then utilized to find the optimized lower pressure limit for CUGS by assessing condensate oil production, gas flow capability, and water encroachment. Results show that the dynamic pseudo-component model can represent the process of thermodynamic property changes towards lighter components during natural gas injection. The case study demonstrates that conventional models overestimate condensate oil production, while the dynamic model achieves an accuracy rate of 92.8 % with historical data. The dynamic pseudo-component model offers valuable insights for large-scale gas injection simulation, promoting stable and efficient natural gas storage and supply in CUGS.

Shortcut design of sulfur reduction distillation system using pseudo-component description of biodiesel and the sulfur contaminants

A critical factor in environmental degradation is the coupled problem of world population growth and waste management, including wastewater management. Making biodiesel from the FOG (fat, oil and grease) in the wastewater system is an attractive path for sustainable biofuel production, waste management and public health. High sulfur content is the biggest challenge in biodiesel produced with the brown grease extracted from FOG.The purpose of this paper is to present a new method to design the sulfur reduction process based on a pseudo-component approach that greatly reduces the effort required to characterize the complex mixture of methyl esters and sulfur containing contaminants. To demonstrate this method, biodiesel was produced from decanted brown grease using several combinations of acid and base catalysts in a two-step esterification/ transesterification process. Vacuum batch distillation was applied to the crude biodiesel product to generate volatility and sulfur distribution data. An easily applied vapor/liquid equilibrium model was then developed using 7 pseudo-components, each with an assigned sulfur content. A principal result is that the pseudo-component model very accurately simulated the batch distillation data. These pseudo-components were then used in the ASPEN software to design a continuous distillation system for a FOG to biodiesel system being installed at a wastewater treatment plant. The second principal result is the ASPEN based design predicts a biodiesel product containing sulfur lower than 10 ppm, satisfying sulfur requirements worldwide. In conclusion, the pseudo-component design method is a versatile and easily applied approach to design sulfur reduction processes.

Thermogravimetric characterisation and kinetic analysis of Nannochloropsis sp. and Tetraselmis sp. microalgae for pyrolysis, combustion and oxy-combustion

This paper reports the results of a complete kinetic study, based on thermogravimetric characterisation, to compare the performance of Nannochloropsis sp. and Tetraselmis sp. microalgae during pyrolysis and combustion with air, enriched air and oxygen. The analysis has been carried out including both the single- and multi-step approach studying the effect of different model-free methods and heating rates. In addition, the study brings together the pseudo-components (obtained by peaks deconvolution) model and master plot methodology to discriminate the kinetic model followed by the different processes with the aim to determine the kinetic triplet (activation energy, reaction order and pre-exponential factor). It results that the thermal decomposition of the microalgae cannot be represented by a single reaction mechanism for the whole conversion range, but several parallel decomposition reactions have been taken into account, and the kinetics have been assessed from each decomposition kinetic of the pseudo-components. The kinetic profiles can be interpreted as the combined effects of reaction-order (F), nucleation (A), exponential nucleation (P) and geometrical contraction (R) mechanisms.

Non-isothermal kinetic study of fodder radish seed cake pyrolysis: performance of model-free and model-fitting methods

The scientific community has shown concern about the suitable application of different methods (model-free/model-fitting) for the determination of kinetic parameters. The application of an unsuitable method may lead to unreliable kinetic parameters. In this study, the performance of five methods for the determination of the kinetic parameters of fodder radish seed cake (FRSC) pyrolysis was evaluated. This is the first detailed study of the pyrolysis kinetics of FRSC. The characterization was performed through thermogravimetric analysis at different heating rates (5, 10, and 25 K/min) and temperatures ranged from 298 to 1073 K. Four model-free isoconversional methods (Friedman, Kissinger, Kissinger–Akahira–Sunose and Flynn–Wall–Ozawa) were used to determine the activation energy. A model-fitting (five pseudo-components model—FPCM) method was used to obtain the kinetic parameters of fodder radish seed cake pyrolysis. A detailed evaluation of the performance of these methods to estimate the kinetic parameters of fodder radish seed cake pyrolysis was performed. The Criado method was applied to verify reaction mechanisms that governed the pyrolysis process. The activation energies (Ea) ranged from 127.70 to 991.53 kJ/mol from the four model-free methods, which presented themselves as unreliable. The FPCM presented a better performance, with higher R2 values. At low conversions, pyrolysis was controlled by diffusion mechanisms, while at higher conversions, a third-order reaction became the governing pyrolysis mechanism.

Fast determination of lignocellulosic composition of poplar biomass by thermogravimetry

The evaluation of the amount of lignocellulosic polymeric components of woody biomass is fundamental to assess its adequacy to produce energy or chemicals. Classic techniques for quantification of these components are slow and laborious, and modern expeditious techniques such as thermogravimetry (TG) have allowed for new and accurate measurement methodologies. TG was used to analyze woody biomass and lignocellulosic composition was assessed through deconvolution of rate of mass loss curves with a pseudo-component model. The quantification of hemicelluloses, cellulose and lignin was performed for nine different poplar genotypes grown as a short rotation coppice (SRC) in Portugal and Belgium. The average composition was (% mass, dry basis) 23% hemicelluloses, 49% cellulose and 27% lignin, with the remaining 1% ash. The classic determination of lignin (Klason) allowed to comparable content (29%). Moreover, TG results agree with published data obtained by conventional wet techniques for poplar wood. The usefulness of the application of TG for lignocellulosic content determination was verified, allowing useful and simple characterization of biomass for thermochemical conversion processes. SRCs are envisaged as an auspicious renewable source of woody biomass, and TG can be a valuable tool to improve the knowledge of factors related to the influence of genetic and environmental conditions on biomass quality.

Critical analysis of non-isothermal kinetics of poultry litter pyrolysis

Poultry litter is a waste from poultry industry that has been used for bioenergy generation and has high potential as feedstock for thermochemical processes, as pyrolysis. Kinetic parameters of poultry litter pyrolysis are paramount for techno-economic analysis of commercial scale processes. Scientific community has shown concern about the suitable application of different methods (model-free/model-fitting) for the determination of kinetic parameters. The application of an unsuitable method may lead to unreliable kinetic parameters. In this study, the performance of model-free methods for the determination of the kinetic parameters of poultry litter pyrolysis was evaluated. The characterization was performed through thermogravimetric analysis. Were applied the methods of Kissinger–Akahira–Sunose, Flynn–Wall–Ozawa and Vyazovkin. The model-free methods were not adequate to describe the kinetics of poultry litter pyrolysis throughout the whole reaction. Therefore, a model-based (five pseudo-components model) method was applied to obtain the kinetic parameters of poultry litter pyrolysis. Such model provided an adequate fit to the experimental data.

A Method to Forecast the Combustion Characteristics of Biomass Waste: Based on a Custom-Designed Macro-TGA

The combustion characteristics of five model biomass components (cellulose, hemicellulose, lignin, pectin and starch) and four real biomass waste (poplar stem, Chinese cabbage, orange peel and ginkgo leaf) were evaluated in a custom-designed macro-TGA at three different heating rates. With the increase in the heating rates, the peaks of the various samples in DTG curves shifted to the high temperature region. All main peaks temperature of 20 °C/min were 40–55 °C higher than that of 10 °C/min and 30–40 °C lower than that of 30 °C/min in the combustion on macro-TGA, except for lignin. Furthermore, the pseudo-component model based on the macro-TG curves simulation was analyzed and three/five components simulating results were compared. The overlap ratios between actual macro-TG curves and fitting curves by different methods and heating rates were all higher than 0.979 to suggest that biomass waste combustion characteristics could be well simulated by its components, and the three and five components fitting effects differed for the specific material because of its composition. The TG curves of real biomasses at one heating rate were used to gain the fitting TG curves of other heating rates and forecast their combustion characteristics. The forecast method showed good results but they varied among the biomasses. It might be due to their composition and the interactions among the biomass model components. The pseudo-component model provides a potential method to forecast the combustion characteristics of biomass waste in the MSW incineration.

Pyrolysis and gasification of typical components in wastes with macro-TGA

The pyrolysis and gasification of typical components of solid waste, cellulose, hemicellulose, lignin, pectin, starch, polyethylene (PE), polystyrene (PS), polyvinyl chloride (PVC) and poly(ethylene terephthalate) (PET) were performed and compared in a macro thermogravimetric analyzer (macro-TGA). Three model biomasses, poplar stem, orange peel and Chinese cabbage, were applied to pyrolysis and gasification simulation by their components based on TG curves. Compared to those from TGA, peaks temperature of the differential thermogravimetric (DTG) curves of each samples pyrolysis on macro-TGA delayed 30–55°C due to heat transferring effect. CO2 promoted the thermal decomposition of hemicellulose, lignin, starch, pectin and model biomasses significantly by Boudouard reaction, and enhanced slightly the decomposition of PET. The activation energy (AE) of biomass components pyrolysis on macro-TGA was 167–197kJ/mol, while that of plastic samples was 185–235kJ/mol. The activation energy of 351–377kJ/mol was corresponding to the Boudouard reaction in CO2 gasification. All overlap ratios in pseudo-components simulation were higher than 0.98 to indicate that pseudo-components model could be applied to both pyrolysis and CO2 gasification, and the mass fractions of components derived from pyrolysis and gasification were slightly different but not brought in obvious difference in simulating curves when they were applied across.

Pyrolysis of microalgae residues – A kinetic study

Pyrolysis of residues from the oil extraction process of two types of microalgae, Chlamydomonas (C. sp. JSC4) and Chlorella sorokiniana (C. Sorokiniana CY1) was studied by means of a thermogravimetric analyzer. Five pseudo-components (hemicellulose, cellulose, lignin, lipid and protein) model with n=1 or n#1 was assumed for a kinetic analysis of the collected pyrolysis data. The model with n#1 resulted in a slightly better fit quality and reasonable kinetic parameters. The calculated activation energy of hemicellulose, cellulose, lignin, lipid, protein was 115.12–117.12kJ/mol, 181.67–198.30kJ/mol, 61.74–62.75kJ/mol, 104.93–114.14kJ/mol and 90.75–99.31kJ/mol, respectively, for C. sp. JSC4; and 113.12–117.12kJ/mol, 218.73–28.79kJ/mol, 64.77–66.39kJ/mol, 131.97–143.63kJ/mol and 108.03–118.13kJ/mol, respectively, for C. Sorokiniana CY1.

Determination of kinetic parameters of Phlomis bovei de Noé using thermogravimetric analysis

This paper reports the pyrolysis study of Phlomis bovei biomass by thermogravimetric experiments in order to determine the thermal degradation behavior and kinetic parameters. The weight losses were found to occur in three stages. In the DTG thermograms, an increase of the heating rate tended to delay thermal degradation processes towards higher temperatures. The average values of activation energy and pre-exponential factor calculated from Ozawa–Flynn–Wall, Kissinger–Akahira–Sunose and Kissinger methods are 134.83, 134.06, 223.31kJ/mol and 4.161013, 1.181010, 2.811011/s, respectively. The three-pseudo-component method shows that the activation energy increases with increasing the heating rate for hemicellulose and cellulose while the activation energy of the lignin decreased with an increase of the heating rate. Predicted results and experimental data exhibit similar tendencies and the three pseudo-components model with n different from unity 1 is recommended as the most suitable for prediction of kinetic behavior of Phlomis bovei de Noé.

Pyrolysis and simulation of typical components in wastes with macro-TGA

Abstract The pyrolysis of typical components of biomass waste, cellulose, hemicellulose, lignin, pectin and starch was performed and compared in a continuous-weighting fixed bed reactor acting as a macro thermogravimetric analyzer (TGA), namely macro-TGA. The mass loss and mass loss rate with time derived from macro-TGA looks similar to TG curve and differential thermogravimetric (DTG) curve from TGA. Compared to those from TGA, the DTG peak of every sample pyrolysis on macro-TGA delayed, and only one main peak appeared on hemicellulose with macro-TGA. The residue of different samples was in decreasing sequence as lignin > pectin > hemicellulose > starch > cellulose. Furthermore, the pseudo-components model based on the TG/macro-TG curves simulation was analyzed and compared. The overlap ratios between raw TG/macro-TG curves and simulation curves through different methods were all higher than 0.977 at the heating rate of 10 °C/min to suggest that biomass waste pyrolysis characteristics could be well simulated by its components.

Non-isothermal pyrolysis of torrefied stump – A comparative kinetic evaluation

The pyrolysis of native and torrefied stump materials was studied in the kinetic regime by means of a thermogravimetric analyzer operated in the non-isothermal fashion. Three different kinetic models applicable to biomass pyrolysis were evaluated for the collected data, which include a single-reaction model, two three pseudo-components models, and a distributed activation energy model (DAEM). It was shown that the single-reaction model was not suitable to simulating stump biomass pyrolysis. The other models including the three pseudo-components model with n=1 and n≠1, and the DAEM demonstrated very good fits between simulated and experimental curves. However, the three pseudo-components model with n≠1 is recommended as the most suitable for simulation and prediction of kinetic behaviour of slow pyrolysis for both untreated and torrefied stump, considering that it offers the best fits to the experimental data and that the generated reaction orders are realistic, being slightly higher than unity. It appears that the torrefied stump has higher activation energy than its native material. The activation energy predicted for the native stump pyrolysis is in the range of 105.2–108.9kJ/mol, 183.5–183.6kJ/mol, and 40.3–48.01kJ/mol for hemicelluloses, celluloses, and lignin, respectively. That for pyrolysis of the stump torrefied at 200°C is 105.13–111.19kJ/mol, 183.68–185.79kJ/mol, and 40.49–50.70kJ/mol, respectively.

Mathematical Modeling of Thermal Conversion of Athabasca Bitumen. Part I: Reaction Pathways and Experimental Method

Abstract Modeling of a thermal cracking process involves establishing a set of kinetic reactions that transform the feed into products. In a typical feed, there exist a large number of real components. Thus, an exact feed composition is not known. The most common method to overcome this difficulty is to define pseudo-components based on physical properties such as boiling point or molecular weight. In this work, we propose a set of model thermal cracking reactions based on nuclear magnetic resonance (NMR) data. NMR carbon type analysis improves the characterization of the feed and products by providing the contents of different carbon species (carbon bonds). This additional information enables a more descriptive and fundamental set of reactions to be developed for the model. The reactions chosen describe the types of carbon bonds that break and form in the feedstock under visbreaking conditions. The set of reactions is the centre of the pseudo-component model. Introduction Visbreaking is a thermal cracking process that has existed for many decades. It is a relatively mild process used primarily to reduce the viscosity of the heavy ends of crude oil feedstocks that results in low conversion of heavy-end material. For example, typically there is < 30 wt% conversion of residue with boiling points (BP) > 524 °C to lower-boiling components. Visbreaking is widely used in Europe and Asia due to the properties of available feedstocks and demand for heavier products such as fuel oil. In Alberta, an increasing proportion of the oil produced is extra heavy (i.e. Athabasca bitumen). Consequently, higher severity processes such as coking and residue hydrocracking are needed to convert 60 wt% or more of the residue to lighter products suitable for transportation fuels. However, there has been some interest in visbreaking as a field upgrading process to reduce the need for diluents to meet pipeline specifications for bitumen and heavy oil transportation. Despite visbreaking being a relatively simple process, modeling of the thermal cracking reactions that result in product formation poses many challenges. The greatest difficulty is to find a suitable method to describe the feedstock and product molecules. For the lightest components of crude oils (i.e. naphtha, BP <204 °C), there are over a thousand molecular species that can be identified and quantified. However, for fractions with boiling points > 204 °C, virtually every molecule is different. Thus, the challenge is to lump the molecules into a manageable number of groups, yet be able to retain enough chemical sensitivity so as to be able to develop fundamental correlations. The most common method to characterize a feedstock is to define pseudo-component lumps based on physical properties like molecular weight or boiling point. However, as these properties provide no specific information of the relative chemical reactivity of the lumps, the kinetic parameters determined are empirical and need to be adjusted for each different feedstock. Recently, nuclear magnetic resonance (NMR) spectroscopy has been used for structural analyses of petroleum fractions. Ali et al.(1) used NMR data to estimate average molecular structures of Kuwaiti vacuum gas oil.

The effect of different feed flow patterns on the conversion of bubble column reactors

Abstract The main objective of this work is to improve the conversion inside bubble column reactors by varying the way in which feed is input inside these systems. Bubble column reactors are usually cylindrical in shape, and the reactor feed is at the bottom. The whole idea lies on the fact that the fluid dynamic fields inside the reactor affect its yield. Since the flow pattern in these reactors depend on the radial feed velocities profiles and radial feed holdup profiles at the bottom, several radial feed profiles for these variables were tested in order to analyze how they affect the reactor conversion. The mass flow input for both phases is the same in all situations. This in-house model uses an Eulerian–Eulerian approach to simulate a set of idealized radial profiles feed input situations, that will produce different fluid dynamic fields inside the reactor, and their effect on reactor conversion. The fluid dynamics and concentrations fields, for each phase, is estimated using mass and momentum conservation equations. Turbulence is taken into account using the k – ɛ model. The petroleum thermal hydrocraking is modeled using a pseudo-component model.

KINETIC PARAMETERS OF HYDROPROCESSING REACTIONS IN A FLOW REACTOR

ABSTRACT The change in distillation properties of a blend of light and heavy distillates over a commercial hydrotreating catalyst was studied using a small packed bed reactor. The results were interpreted assuming a pseudo-component model that took into account the physical and chemical complexity of the system. A first order series-parallel reaction mechanism was found to be valid for the operating conditions involved. Pore diffusion effects were also taken into consideration.

Pseudocomponent model for prediction of molecular weight distribution of pyrolysis liquids generated at slow and rapid heating rate reactors

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTPseudocomponent model for prediction of molecular weight distribution of pyrolysis liquids generated at slow and rapid heating rate reactorsM. Rashid Khan and K. Hemanth KumarCite this: Energy Fuels 1989, 3, 3, 312–315Publication Date (Print):May 1, 1989Publication History Published online1 May 2002Published inissue 1 May 1989https://doi.org/10.1021/ef00015a009RIGHTS & PERMISSIONSArticle Views118Altmetric-Citations3LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (434 KB) Get e-Alerts Get e-Alerts

Inverse Lumping: Estimating Compositional Data From Lumped Information

Summary Many methods of characterizing reservoir fluids thermodynamically yield equation-of-state (EOS) models with a large number of components. For simulation studies, this detailed compositional model is subsequently replaced by a simplified model in which compositions are described with a limited number of groups or pseudocomponents. This paper discusses methods of translating group (pseudocomponent) compositions into detailed component compositions, a procedure that will be referred to as "inverse lumping." Inverse lumping can be used to calculate phase properties in the group (pseudocomponent) model. This eliminates the need to construct ad-hoc property correlations. Another application would be to inverse lump the well streams as predicted by the simulator so that the results can be used in a fully compositional separator-system simulator.