• Energy Research

Chlorinated polyvinyl chloride (CPVC), as a new type of engineering plastic waste, has been used widely due to its good heat resistance, mechanical properties and corrosion resistance, while it has become an important part of solid waste. The pyrolysis behaviors of CPVC waste were analyzed based on thermogravimetric experiments to explore its reaction mechanism. Compared with polyvinyl chloride (PVC) pyrolysis, CPVC pyrolysis mechanism was divided into two stages and speculated to be dominated by the dehydrochlorination and cyclization/aromatization processes. A common model-free method, Flynn-Wall-Ozawa method, was applied to estimate the activation energy values at different conversion rates. Meanwhile, a typical model-fitting method, Coats-Redfern method, was used to predict the possible reaction model by the comparison of activation energy obtained from model-free method, thereby the first order reaction-order model and fourth order reaction-order model were established corresponding to these two stages. Eventually, based on the initial kinetic parameter values computed by model-free method and reaction model established by model-fitting method, kinetic parameters were optimized by Shuffled Complex Evolution algorithm and further applied to predict the CPVC pyrolysis behaviors during the whole temperature range.

Abstract The effect of azeotropic blended fuel on combustion characteristics was studied experimentally in a ceiling vented compartment. A variety of blended liquid fuels with different mixing ratios was employed to explore the thermal performances by the measurement of fuel mass loss rates, fuel and gas temperatures, etc. Results indicate that azeotropism has a significant effect during the combustion process, resulting in four typical burning stages, especially based on fuel temperature profiles: initial growth, azeotropic burning, single-component burning and decaying. Two significantly different thermal performances appear: steady burning (fuel-limited) and self-extinction (oxygen-limited). When the burning rate reaches a critical value, about 35 g m −2 s −1 , the confined space cannot entertain enough air, self-extinction followed. A parameter ( Q / A v 5/4 ) derived from energy conservation equation is applied to divide the steady burning and self-extinction in consideration of both the heat release rate and ventilation condition, and the critical value is 200 kW/m 5/2 . Moreover, the ghosting flame maybe appears during the self-extinction condition, especially when Q / A v 5/4 > 300 kW/m 5/2 . The ghosting flame is detached from the fuel pan and goes from place to place with violent oscillation, which creates a larger high-temperature region and thus increases fire hazards. Meanwhile, according to both the fuel temperature profiles and mass loss rate, azeotropism can effectively delay the bulk boiling of the remaining single fuel and the emergence of ghosting flame.

AbstractChlorinated polyvinyl chloride (CPVC) is a widely‐used material in various fields with excellent properties. However, CPVC waste is one of the most intractable solids to dispose of. With the development of pyrolysis technology, some advantages have been exhibited, for example, it is flexible to convert solid waste into clean products by pyrolysis, which can be used as energy. Therefore, pyrolysis is considered as an effective method to dispose of solid waste. Especially, kinetic parameters are significant for pyrolysis, which contributes to reactor design and waste management. To better apply the kinetic parameters of CPVC to dispose of waste, thermogravimetric experiments were conducted to obtain the kinetic parameters and establish the reaction mechanism. The Tang, distributed activation energy model, and Advanced Vyazovkin methods were used to calculate the activation energy, and the reaction order was obtained by the Coats‐Redfern method. The results showed that the reaction consisted of two stages, and the average activation energy of the corresponding stage was 153.27 and 290.55 kJ/mol, respectively. However, the abovementioned parameters by traditional methods were not enough to characterize the whole pyrolysis behaviors, then the obtained kinetic parameters were further optimized and extra parameters were computed by the Particle Swarm Optimization algorithm.

The demand for the effective traceability of hazardous chemicals is crucial for preventing and controlling chemical spills and other accidents involving hazardous chemicals. The aim of the study was to investigate the correlation between the geographical location of ethanol-producing industrial sites and the carbon, hydrogen, and oxygen stable isotope ratios of the Chinese-manufactured ethanol using statistical classification analysis to enable the traceability of the ethanol. The isotopic data of 54 ethanol samples obtained from 18 different ethanol manufacturing plants in China between 2019 and 2020. The results of the statistical analysis demonstrated that the δ18O values of the ethanol positively correlated with latitudes of the production plants but negatively correlated with the δ13C values of the ethanol. A small number of samples derived from sites that were geographically close to each other could not be visually distinguished by PCA and HCA. However, by applying and comparing the results of classification by LDA, K-NN and Ensemble, an optimal classification model was obtained. Upon application of these models, 96.3% of the ethanol samples were correctly classified based on their geographical origin, indicating that the combination of isotopic ratios and latitude data is practical and effective for measuring the traceability of ethanol.

Abstract Comparative pyrolysis behaviors of typical hardwood ( Fagus sylvatica ) and softwood ( Cunninghamia lanceolata ) were investigated based on thermogravimetric analysis over a wide heating rate range from 5 K/min to 60 K/min. The Flynn-Wall-Ozawa model-free method was applied to estimate the various activation energy values at different conversion rates, and the Coats-Redfern model-fitting method was used to predict the possible reaction mechanism. Two pyrolysis regions were established by the trend of activation energy, divided by the threshold of conversion rate (0.4 for hardwood and 0.2 for softwood) but with the same distinguished temperature at about 580 K. For the region under the conversion rate threshold, the activation energy of hardwood increased gradually while softwood decreased. Furthermore, the activation energy remained the same for both hardwood and softwood in the region over the conversion rate threshold. However, softwood behaved greater activation energy than hardwood during the whole pyrolysis process. The pyrolysis differences of hardwood and softwood could be attributed to the chemical component, molecular structure, component proportion and various extractives. The same reaction mechanism of hardwood and softwood was verified by applying the Coats-Redfern approach. By checking activation energies obtained according to different models with those obtained through the Flynn-Wall-Ozawa method, the best model was based on diffusion mechanism when the conversion rate was less than its threshold, otherwise based on reaction order (2nd to 3rd).

The bench-scale pyrolysis of lignocellulosic biomass was investigated based on effect of thickness by both the experiment and numerical simulation. A critical thickness at which the two peaks of mass loss rate start to merge and the pyrolysis process is significantly accelerated, is paid attention in the fire propagation apparatus experiment at N2 atmosphere. A new method is put forward to predict the merge thickness by coupling the Gpyro pyrolysis model with the optimized chemical reaction parameters, moisture and changed volume in OpenFOAM. Eventually, the predicted equation of merge thickness at various external heat fluxes is obtained, which is basically the same with that of thermal thickness.

Pyrolysis of pinewood (pinus sylvestris) was investigated based on thermogravimetric analysis. A new method was put forward to estimate its kinetic parameters by coupling model-free and model-fitting models. Kissinger-Kai method updated from Kissinger method was used as the representative of model-free method. Particle Swarm Optimization heuristic algorithm, as the typical model-fitting method, was coupled with three-component parallel reaction mechanism to search the optimized values, wherein its search ranges of kinetic parameters were referred to the original calculated values by Kissinger-Kai method. Furthermore, to explore the influence of separate kinetic parameter on the final predicted thermogravimetric results, global sensitivity analysis about these parameters was conducted by comparison of Spearman rank correlation coefficient based on Latin Hypercube Sampling and rank transformation. It was found that the top three parameters affecting the predicted results were activation energy of lignin, reaction order of cellulose and pre-exponential factor of lignin.