Pyrolysis Model Research Articles

Numerical investigation on pyrolysis and ignition of ammonia/coal blends during co-firing

Co-firing ammonia with coal is a promising and feasible technology for reducing coal-related carbon emissions. Pyrolysis and ignition of ammonia-coal blended fuels are the key steps for flame stability and boiler operation safety throughout the conversion process but remain unclear. In this work, an extended Euler–Lagrange framework coupled to detailed solid-phase pyrolysis kinetics and gas-phase reactions mechanism is introduced and validated against experimental results for ammonia-coal co-firing in a two-stage flat flame burner. First, the CRECK-S coal pyrolysis model was validated with TGA experiments and the CPD model at different heating rates to determine parameters for a competing two-step model for CFD simulations. Second, a detailed gas-phase mechanism with 116 species and 1513 elementary reactions was derived from the volatile and ammonia reaction mechanisms. Thirdly, the co-firing simulations were validated for the ignition delay time for various ammonia co-firing ratios. The results show that increasing the co-firing ratios from 0.0 to 1.0 results in gradually increasing ignition delay times in a low-oxygen atmosphere. Further analysis demonstrates that adding ammonia accelerates the coal particle heating rate due to the reduced coal particle number density and ammonia reaction induced gas-phase temperature increase, and thus the coal devolatilization rate is increased. The latter plays a dominant role. Hydrogen produced from ammonia pyrolysis is negligible, so ammonia predominantly participates in the ignition. Time scale analysis shows that homogeneous ignition is dominant during the ignition process. The presence of ammonia inhibits the inward oxygen diffusion and causes the reaction zone to move away from the pulverized coal particle flow. The oxygen diffusion inhibition and low reactivity of ammonia compared to volatiles lead to an increase in ignition delay time for ammonia co-firing, even though pulverized coal devolatilization is accelerated.

Thermogravimetric analysis and pyrolysis characterization of expanded–polystyrene and polyurethane–foam insulation materials

Expanded polystyrene (EPS) and polyurethane foam (PUF) are commonly used as building insulation material for energy savings; however, the fire risk is high because insulation material ignites easily and combusts upon exposure to external heat sources. Insulation materials are regarded as solid fuels, which undergo pyrolysis before combustion. Therefore, elucidating insulation material pyrolysis is an important aspect of efforts to predict combustion and fire phenomenon in these materials. Thermogravimetric analysis (TGA) was conducted to investigate the pyrolysis behavior of EPS and PUF in a nitrogen atmosphere using four heating rates. The results showed that the pyrolysis of EPS and PUF in nitrogen occurred through one- and two-weight loss reactions, respectively. Based on the pyrolysis temperatures obtained via TGA, the effective activation energies were determined using multiple model-free methods. The pre-exponential factors were calculated by applying the kinetic compensation effect from the reaction mechanism established using the model-fitting method. Additionally, the material activation energies and pre-exponential factors determined from experiments could be used as pyrolysis properties for numerical predictions of fire using the Fire Dynamics Simulator (FDS). Numerical simulations were conducted to validate the material activation energies and pre-exponential factors determined from experiments based on the FDS pyrolysis model.

Process modelling of waste tyre pyrolysis for gas production using response surface methodology

The search for cleaner and renewable energy sources coupled with the need for environmental protection has necessitated the conversion of municipal solid wastes to energy sources. In this study, the pyrolysis of waste tyres in a fixed-bed reactor was carried out in a bid to generate non-condensable gases. The influence of process variables such as sample weight, reaction temperature, and reaction time were modelled and optimized using the central composite design of the response surface methodology. Based on the central composite design of the response surface methodology, the R2, adjusted R2 and predicted R2 values of 0.968, 0.941 and 0.750 respectively, indicated that the model properly fitted the experimental data. This implied the accuracy of the model prediction. The maximum predicted gas yield of 10.212 wt% was estimated under optimal conditions with desirability of 0.697, a dimensionless value indicating the closeness of the combination of input variables to the desired values for the response variables. The gases obtained upon pyrolysis of waste tyres can serve as a source of hydrocarbon gases in the petroleum and petrochemical industry.

Modeling and simulation of Khat waste fast pyrolysis for energy recovery

Bioenergy is now recognized to be capable of providing the vast majority of predicted future renewable energy supply. Biomass is currently considered a common and commonly used renewable energy source. This study depends upon the investigation of khat waste using Aspen Plus software, which is required for creating environmentally friendly energy sources capable of improving our access to energy and economic sustainability. The outcome of the study is to understand the characteristics of the pyrolysis process without conducting a time-consuming, expensive, and complex procedure. The results of the investigation will be useful in determining the best feedstock for the formation of biofuel. Aspen Plus software simulates several ash-free organic components, including carbon, oxygen, nitrogen, hydrogen, and sulfur, with results like 45.72 % for carbon, 5.84 % for hydrogen, 0.43 % for nitrogen, and 38.56 % for oxygen. The production of biofuel is affected by processing parameters such as temperature and total mass flow rate. During reactions with the same mass but different temperatures, the bio-oil declined from 600 °C to 800 °C, while the maximum gas emission climbed quickly and the biochar reduced. In addition, it was recovered from Khat waste and proved to have an energy efficiency of 80.75 % and a net energy capacity of 134.25 kW. In addition, the High heating value (HHV) can be obtained from Khat waste is 19.38 MJ/kg, and low heating (LHV) can be 18.12 MJ/kg. We have been able to realize it using the Institute of Gas Technology formula based on ultimate analysis. The results show that Khat produces more oil than other wastes. As a result, all Khat waste is naturally occurring and Khat waste usually contains less nitrogen and no sulfur when used as fuel, which is an air pollutant reducing and protecting the environment.

Cellulose pyrolysis kinetic model: Detailed description of volatile species

Lignocellulosic biomass is typically composed by a major fraction of cellulose. Its decomposition influences on large extent the biomass rate of pyrolysis and product distribution, affecting process behaviour in thermochemical conversion processes. Containing approximately 90 % of volatile matter, volatile products from cellulose pyrolysis are very important in the characteristics of flames and ignition properties. Recent developments in analytical methods allowed a detailed identification of these volatile products, giving valuable information to process development and better understanding of kinetics. Predictions of a previous kinetic model are compared with these new findings, revealing large space for improvements. In this work, we propose a multi-step kinetic model of cellulose pyrolysis, incorporating the most recent experimental findings into the detailed product description. The model consists of four main reactions for the decomposition of cellulose, with formation of gases, volatiles, char and metaplastic species. The release of metaplastic species is described by a set of six reactions. The formation and release of 13 oxygenated hydrocarbons is predicted by the model, including anhydrosugars, furans, aldehydes, alcohols, ketones and carboxylic acids. The model also describes the formation of levoglucosan in metaplastic state before its release, explaining high heating rate mass loss behaviour. The model is compared with a large variety of experiments from literature, and validated for mass loss rates and product distribution, achieving overall good agreement despite experimental uncertainties and the large simplifications characteristic of the model formulation. Besides effectively quantifying the yields of gaseous, condensable and solid products, the model accurately captures the distribution of volatiles in terms of functional groups and C-chain length.

Pyrolysis and kinetic modeling study of tetramethylethylenediamine: A potential green propellant

Tetramethylethylenediamine (TMEDA) is a promising green propellant that has been studied as a substitute for hydrazine. An in-depth study of the TMEDA thermal decomposition mechanism is important for future applications in engines. In this work, pyrolysis experiments of TMEDA were carried out in an atmospheric jet-stirred reactor (JSR) from 610 to 1000 K. Abundant intermediate species were analyzed and quantified by synchrotron vacuum ultraviolet photoionization mass spectrometry (SVUV-PIMS) and gas chromatography (GC). The results show that the pyrolysis of TMEDA mainly produces hydrocarbons, amines, imines, and nitriles, among which HCN and C2H5N are the main nitrogen-containing intermediates. Based on the experimental results, a detailed chemical kinetic model for describing the thermal decomposition of TMEDA was updated to improve predictions. The updated model can satisfactorily predict the consumption of TMEDA and the generation of most intermediates. Furthermore, detailed experimental measurements combined with kinetic analysis are used to clarify the decomposition reaction pathways of TMEDA. The rate of production (ROP) analysis indicates that unimolecular C-C bond dissociation is one of the leading consumption pathways of TMEDA, forming the (CH3)2NCH2 radical. In addition, the H-atom abstraction reactions involving CH3 radicals formed by the C-N bond dissociation of (CH3)2NCH2 radicals further promote the consumption of TMEDA. Sensitivity analysis highlights that the unimolecular C-C bond dissociation reaction of TMEDA and the reactions involving CH3 radicals mainly control the pyrolysis behavior of TMEDA. The detailed experimental results and kinetic analysis in this work are expected to contribute valuable references to further research on the combustion mechanism of TMEDA.

Exploring flow reactor pyrolysis of branched OMEs: Insights into multi-sidechain effects on pyrolysis chemistry of CH3OCH3-n(OCH3)n (n = 1–3)

Oxymethylene ethers (OMEs) have received great attention due to their carbon-neutral nature and advantageous properties as alternative transportation fuels or fuel additives. Previous studies focused on the combustion of linear OMEs with the chemical formula of CH3O(CH2O)mCH3 (m ≥ 0), while a deep understanding of the combustion of branched OMEs with the chemical formula of CH3OCH3-n(OCH3)n (0 ≤ n ≤ 3) is still absent. In this work, the flow reactor pyrolysis of dimethoxymethane (DMM, n = 1), trimethoxymethane (TMM, n = 2), and tetramethoxymethane (TeMM, n = 3) is investigated using gas chromatography, with special attention given to the multi-sidechain effects on the pyrolysis chemistry. A pyrolysis model of branched OMEs is developed and validated against the new pyrolysis data. Modeling analysis is performed to provide insights into the pyrolysis chemistry of the three branched OMEs and the multi-sidechain effects. Unimolecular decomposition and H-abstraction reactions are found to be two major types of fuel decomposition pathways, with the former dominating TMM decomposition, the latter dominating DMM decomposition, and both contributing almost equally to TeMM decomposition. Sensitivity analysis shows that CO bond dissociation is the most sensitive reaction to fuel decomposition in DMM pyrolysis, while methanol elimination is the most sensitive reaction in TMM and TeMM pyrolysis. Among the three fuels, DMM has the lowest pyrolysis reactivity and produces the least abundant methanol. In contrast, TMM is observed with the highest pyrolysis reactivity and produces the most abundant methanol. Theoretical calculations reveal that TMM and DMM have the lowest and highest energy barriers of methanol elimination reactions, which determines the order of their pyrolysis reactivities and methanol formation trends. As a result, DMM pyrolysis occurs at higher temperature regions where the CO bond dissociation and H-abstraction reactions are preferred, while TMM pyrolysis occurs at lower temperature region where methanol elimination dominates.

The relative position of pyrolysis onset and flame front location for downward flame spread

The interaction of solid and gas phase phenomena in downward flame spread is studied under buoyant conditions. Phosphor thermometry (PT) was used to determine the spatiotemporally resolved surface temperatures both ahead and beneath the flame while CH* chemiluminescence allowed for the quantification of the flame location relative to the fuel surface. The combination of these measurements allowed for the superposition of the flame front location and the surface temperature distribution. The standoff distance (∼1.1 mm) and preheated distance along the surface (∼3.5 mm) were quantified. The application of PT allowed for the continued measurement of surface temperatures in the pyrolyzing region beneath the flame, where the surface temperature was found to remain relatively constant between 300 and 350 °C. The combination of measurements allowed for the calculation of the gas-phase heat flux distribution ahead of the flame front using a point-source approximation, which compared well with previous studies. PT and CH* measurements were used to expand previous work to quantify the thermal gradients through the solid both ahead of and behind the flame front. Surface temperature measurements were coupled with thermogravimetric analysis (TGA) and a simple pyrolysis model to determine that the onset of pyrolysis occurs approximately 1 mm ahead of the flame front. This approach was also used to illustrate that pyrolysis gases were generated in sufficient volume to result in a flammable mixture at the leading edge of the flame. This study highlights the benefit of optical diagnostic techniques in exploring the controlling mechanisms of flame spread, and provides insight into the interaction of solid and gas-phase phenomena in downward flame spread.

Modeling of wood crib fires using a detailed pyrolysis model

Wood is a widely used energy source but is dangerous in the case of fires. In this study, a detailed pyrolysis model was used to analyze wood fires. Cellulose, active cellulose, hemicellulose, lignin, char, ash, moisture, and air were the wood components that were considered in this study. Seven flammable gaseous species (cellulose gas, hemicellulose gas, lignin gas, propane, char gas, oxidized product 1, and oxidized product 2) were considered in the detailed pyrolysis model. The wood fire model, using a detailed pyrolysis model, predicted the heat release rate and mass loss rate of the wood close to those of a cone calorimetry experiment, particularly for high external heat fluxes (35, 50, and 65 kW/m2). The wood crib fire was analyzed with a detailed pyrolysis model and the heat release rate (HRR)-based model, and the simulation results were compared with experimental results. The HRR-based fire model could not capture the experimentally measured HRR curves. The wood fire model based on the detailed pyrolysis model was able to predict the flaming stage of the wood crib fire. However, the total heat release was predicted to be lower than that in the experiment, and the fire could not be sustained at the stage where heat release due to char oxidation occurred.

Facile preparation of ladder-like polyphenyl silsesquioxanes-sodium benzenesulfonate micro-nano compound with novel pyrolysis model and high flame retardancy for epoxy resin

To reduce the fire hazard of epoxy resin and expand its application scenarios, a novel micro-nano compound of ladder-like polyhedral oligomeric silsesquioxane (PPSQ) and sodium benzenesulfonate (BSNa) was successfully developed. Due to the addition of BSNa, the thermal decomposition behaviour of ladder-like PPSQ was completely changed, making it an effective additive to improve the flame retardancy of epoxy resin. Compared with neat epoxy resin, at 3wt% addition, the peak of heat release rate(p-HRR), the peak of carbonic oxide production rate(p-COP), the peak of smoke production rate(p-SPR) and the peak of carbon dioxide production rate(p-CO2P) were reduced significantly. In addition, the mechanism of the negative influence of PPSQ-BSNa on the flame retardancy of epoxy resin at excessive addition was detailed and analyzed in this work. Finally, this work provides a new prospect and strategy of synthesis metal containing POSS to reduce the fire hazards of epoxy resin.

Modeling pyrolysis kinetics of extracted biomass components with the bio-chemical percolation devolatilization model

Within the pyrolysis modeling of biomass, the solid is typically interpreted as a mixture of cellulose, hemicellulose, and lignin, where the components react independently before the products are linearly superimposed. This assumption applies to the bio-chemical percolation devolatilization model (Bio-CPD), which, as a network model, represents the physicochemical processes very realistically. A literature review regarding available structural and kinetic parameters for the Bio-CPD model revealed four hits. To investigate and evaluate the model predictivity, experiments from extracted lignocellulosic biomass components pyrolyzed separately in a fluidized bed reactor are used as reference data. Using single-component data simplifies the reaction chemistry by minimizing interactions between the components and best approximates the model assumptions. The comparison between experimentally obtained total volatile release rates and model predictions revealed the parameter set from Vizzini et al. (2008) for cellulose and the one from Sheng and Azevedo (2002) for hemicellulose as best-suitable candidates to predict the pyrolysis behavior for the boundary conditions of the fluidized bed reactor. For lignin, instead, the Genetti correlation (Genetti, Fletcher, and Pugmire, 1999) to estimate structural parameters based on the ultimate and proximate analysis led to better results than all other sets. Further, the analysis of light gas and tar fractions showed a high relevance to model secondary tar cracking reactions in the fluidized bed reactor system.

The effect of uncertainty in calibration data on burning rate predictions

Comprehensive pyrolysis models describe solid phase reaction rates with respect to the material temperature and the concentrations of components. In theory, this aspect of comprehensive pyrolysis models allows for true predictive capabilities for pyrolysis models and, more generally, fire models. To utilize these capabilities, the reaction kinetics must be defined for the material of interest and there is a lack of publicly available data from which these kinetic parameters may be determined. There is also a lack of guidance for quality and repeatability for thermal analysis experiments, which complicates the use of mean thermal analysis data found in the literature to estimate the thermal degradation kinetics. This study details a numerical investigation on the effect of repeatability of thermogravimetric analysis data on the kinetics calibrated from the data. The uncertainty in the kinetic parameters that corresponded to target repeatability values imposed on synthetic calibration data was determined through a latin hypercube sampling procedure. The generalized polynomial chaos expansions method allowed propagation of the uncertainty of the kinetic parameters through a one-dimensional model of a bench-scale experiment. The relationship between uncertainty in calibration data and uncertainty in bench-scale model predictions was linear.

Multi-step kinetic mechanism coupled with CFD modeling of slow pyrolysis of biomass at different heating rates

This study employed numerical modeling to investigate the reactivity and kinetics involved in the slow pyrolysis of lignocellulosic biomass. The model integrates a biomass multi-step kinetics scheme with heat, momentum, and mass transfer, and it was based on the transport of species and flow in a porous medium approach. To develop the multi-step kinetics model, two samples of biomass, avocado stone (AS) with a high hemicellulose content and α-cellulose (CEL), were subjected to TGA experiments in an inert atmosphere. Furthermore, several experimental data in the literature on the evolution of slow pyrolysis products and data obtained by TGA experiments were considered to refine and validate the proposed kinetic mechanism. The temperature range, from 25 to 700 °C, was explored using different heating rates (10, 20, and 40 °C/min). Experimental results showed that CO and CO2 are the predominant gases during primary devolatilization, whereas H2 and CH4 result from secondary reactions at temperatures above 400 °C. The proposed mechanism involves computational fluid dynamic (CFD) simulations of laboratory-scale biomass pyrolysis, comparing temperature and species concentrations with experimental data. The predicted results for individual non-condensable gas mass yields showed an average relative error of below 6.90 % and 11.59 % for CEL and AS, respectively. In the case of biochar, the error was 6.41 % and 9.74 % for AS and CEL, respectively. The developed kinetic model can be applied to simulate the slow pyrolytic degradation of biomass based on its chemical composition.

A review on thermogravimetric analysis‐based analyses of the pyrolysis kinetics of oil shale and coal

AbstractSolid fossil fuels still support the development of the energy and chemical industry. The clean and efficient utilization of solid fossil fuels can effectively alleviate the problems of energy shortage and environmental pollution. An in‐depth understanding of the kinetic process, models, and mechanism of pyrolysis of solid fossil fuels is also of great significance for the exploration and utilization technologies of petroleum resources. Thermogravimetric analysis is an effective method to study the pyrolysis process and kinetics with the advantages of high sensitivity, repeatability, and reliability for data acquisition. Researchers have conducted a lot of research on the thermogravimetric kinetics of solid fossil fuels in recent years, but there is a lack of systematic summary and comparison of kinetic methods, research progress, and trends. Therefore, a comprehensive study on pyrolysis kinetic principles, methods, and models of solid fossil fuels by thermogravimetric analysis is carried out in this paper. The influencing factors of pyrolysis kinetics of solid fossil fuels using thermogravimetry are elaborated and discussed in detail. This study also provides progress in recent years and prospects of thermogravimetric kinetics of solid fossil fuels. It is expected that this paper can provide certain technical support and theoretical guidance for the research on pyrolysis kinetics based on thermogravimetric analysis, and the exploration and development, clean, and efficient utilization of solid fossil fuels.

Advances in Computational Fluid Dynamics Modeling for Biomass Pyrolysis: A Review

Pyrolysis, a process for extracting valuable chemicals from waste materials, leverages computational fluid dynamics (CFD) to optimize reactor parameters, thereby enhancing product quality and process efficiency. This review aims to understand the application of CFD in pyrolysis. Initially, the need for pyrolysis and its role in biomass valorization are discussed, and this is followed by an elaboration of the fundamentals of CFD studies in terms of their application to the pyrolysis process. The various CFD simulations and models used to understand product formation are also explained. Pyrolysis is conducted using both conventional and microwave-assisted pyrolysis platforms. Hence, the reaction kinetics, governing model equations, and laws are discussed in the conventional pyrolysis section. In the microwave-assisted pyrolysis section, the importance of wavelength, penetration depth, and microwave conversion efficiencies on the CFD are discussed. This review provides valuable insights to academic researchers on the application of CFD in pyrolysis systems. The modeling of pyrolysis by computational fluid dynamics (CFD) is a complex process due to the implementation of multiple reaction kinetics and physics, high computational cost, and reactor design. These challenges in the modeling of the pyrolysis process are discussed in this paper. Significant solutions that have been used to overcome the challenges are also provided with potential areas of research and development in the future of CFD in pyrolysis.

Exergy Analysis and Modeling of Pilot-Scale Pyrolysis for Magnesium Oxide Preparation from Salt Lake Bischofite Industrial Waste.

Currently, the traditional magnesium oxide production process is facing exceptional challenges arising from carbon emission restrictions and environmental protection. Waste bischofite pyrolysis has attracted much attention as a promising technology to address these challenges. Nonetheless, this process has primarily been demonstrated on a laboratory scale, with limited studies on an industrial scale. A comprehensive exergy analysis was conducted for the entire process and individual subunits within the pyrolysis process to identify potential areas for process enhancement. A FORTRAN subroutine based on empirical correlations of pyrolysis product yields was developed considering the impact of decomposition reactions on the simulation. Furthermore, the optimization of energy and exergy efficiency of the system was discussed in terms of the carbon dioxide emission factor, equivalence ratio, and pyrolysis temperature. The results show that the primary energy bottleneck lies in the combustion phase. In addition, the optimal energy and exergy efficiency conditions are a carbon dioxide emission factor of 5.3, an equivalent ratio of 1.15, and a pyrolysis temperature of 1100 °C. In comparison to the pilot-scale conditions, the energy efficiency and exergy efficiency increase by 2.55 and 3.61%, respectively. At this time, the MgO yield is 100%, and the HCl concentration is above 9.33%.

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.

Intrusive and non-intrusive uncertainty quantification methodologies for pyrolysis modeling

In this work we discuss and compare multiple uncertainty analysis methodologies for pyrolysis modeling. Using Arrhenius equation as the pyrolysis model and kinetic parameters for PMMA material as uncertain variables, different approaches for stochastic uncertainty quantification and their computational effort are analyzed. First non-intrusive (NI) methods are compared through convergence analysis where the deterministic model can be used as is to ascertain the statistical moments, followed by an intrusive polynomial chaos (IPC) approach which requires reformulation of the deterministic model, but solution of the model only once. The applied NI methods include Monte Carlo based simulations, regression and projection based non-intrusive polynomial chaos (NIPC) methods. The uncertainty analysis and convergence comparison is performed for three materials including the effects of overlapping reactions and dependent parameters. In general for different uncertain parameters and materials, IPC gave accurate statistical information in a single model run compared to NIPC projection requiring runs ranging from tens to hundreds and NIPC regression requiring runs in range of thousands to generate converged statistics. However, in case of only a few uncertain parameters, presence of non-polynomial functions in the model and small-scale simulations, projection based NIPC outshines IPC in terms of simplicity and applicability.

Computational fluid dynamics modeling of rapid pyrolysis of solid waste magnesium nitrate hydrate under different injection methods

This study developed a numerical model to efficiently treat solid waste magnesium nitrate hydrate through multi-step chemical reactions. The model simulates two-phase flow, heat, and mass transfer processes in a pyrolysis furnace to improve the decomposition rate of magnesium nitrate. The performance of multi-nozzle and single-nozzle injection methods was evaluated, and the effects of primary and secondary nozzle flow ratios, velocity ratios, and secondary nozzle inclination angles on the decomposition rate were investigated. Results indicate that multi-nozzle injection has a higher conversion efficiency and decomposition rate than single-nozzle injection, with a 10.3% higher conversion rate under the design parameters. The decomposition rate is primarily dependent on the average residence time of particles, which can be increased by decreasing flow rate and velocity ratios and increasing the inclination angle of secondary nozzles. The optimal parameters are injection flow ratio of 40%, injection velocity ratio of 0.6 and secondary nozzle inclination of 30 degrees corresponding to the maximum decomposition rate of 99.33%.

Solar thermal reactor model for pyrolysis of waste plastic

ABSTRACT The ability to convert waste plastic into combustible liquids and gases using solar energy could help transform the problem of disposal of non-recyclable plastic into a valuable and environmentally responsible source of fuel. The purpose of this study is to propose a practical model for a compound parabolic trough solar thermal reactor for pyrolysis of waste plastic. The model integrates predictions of energy available from solar radiation (at a given location, time of day and time of year) with parabolic trough collector orientation and efficiency, a transient energy balance for an evacuated tube reactor and pyrolysis kinetics of waste plastic. The experimental setup used to test the model includes a pyranometer, a commercial solar collector consisting of a 60 cm long evacuated tube with a compound parabolic reflector and multi-channel data loggers to collect temperature, humidity and radiation data. The solar radiation sub-model was found to be in excellent agreement with clear-sky irradiance data collected using the pyranometer. Predictions of reactor temperature and reaction rate were found to be sensitive to the concentrator aperture area, solar irradiance, type of plastic (Arrhenius kinetics) and radiation properties of the evacuated tube reactor but relatively insensitive to humidity, wind velocity and terrestrial irradiance. The model shows that even on a small scale, favourable conditions for pyrolysis of waste plastic can be achieved within a solar reactor.