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The goal of the work is to determine unknown parameters of reactor heating in the process of biomass solar pyrolysis. The lab-scale reactor is heated by a xenon lamp, but the fraction of heat absorbed by the reactor is unknown, as well as the heat transfer coefficient from the reactor walls to the nitrogen flowing through internal reactor channels, and the overall heat transfer coefficient through the external reactor walls to the surroundings. The missing parameters are impossible to measure, therefore they need to be determined by solving the inverse problem. As the problem is strongly ill-conditioned, since the quantities are directly dependent on each other, two different inverse algorithms were used to retrieve them, namely, the Levenberg-Marquardt method and the Metropolis-Hastings method. The effectiveness of both approaches was assessed and then they were applied to the real data. The inverse problem was implemented in the MatLab software, while validation of the mathematical model and optimisation procedure was carried out with a CFD model built in Ansys Fluent 19.2. Calculations showed that 14.4% of the lamp power penetrates inside the reactor and heat transfer coefficients to the flowing nitrogen equal 8.74 W/m2K and 0.965 W/m2K to the surroundings. • Two inverse algorithms were used: Levenberg-Marquardt and Metropolis-Hastings. • The validation was carried out with a 3D CFD model. • Calculations showed that only 14.4% of the lamp power penetrates inside the reactor. [ABSTRACT FROM AUTHOR]

The article presents a review of works on mathematical modelling of biomass pyrolysis process. Models types, number of dimensions, captured phenomena, type and dimensions of the reactors and biomass particles as well as models validation methods were analysed. Particular attention was paid to descriptions of chemical reactions, which are the essence of biomass thermal decomposition simulation. The article briefly describes the most important issues related to biomass pyrolysis and provides a review of commonly used methods of modelling this process with emphasis on solutions "ready to employ" in CFD modelling. A summary of other review papers on this topic is also provided. The problem of mathematical modelling in the context of "model - an engineering tool" was also discussed. Mathematical model for an engineering applications must be prepared with consideration of necessary consensus between the calculations accuracy, calculation time, preparation efforts and analysis requirements. Therefore, in pyrolysis modelling context, the inclusion of chemical reactions and changes of heat transport conditions were considered as priority, while taking into account moisture evaporation and bed shrinkage should be conditioned by their actual contribution in the calculations accuracy and by their influence on the calculations time. • A review of research on mathematical modelling of biomass pyrolysis is presented. • Captured phenomena, kinetic models, properties change, reactor types are summarized. • Compromise between model precision and calculations costs is discussed. [ABSTRACT FROM AUTHOR]

The paper presents a Computational Fluid Dynamics (CFD) model of the cold alpha-type Stirling engine. The developed mathematical model comprises of Unsteady Reynolds Averaged Navier-Stokes (URANS) set of equations, i.e. continuity, momentum and energy equations. Moreover, the developed mathematical model comprises a non-equilibrium description of the regenerator, by the introduction of the energy conservation equation for the regenerator matrix. It was implemented in the framework of commercial CFD software ANSYS Fluent. The work presents an in-depth analysis of the influence of the numerical mesh and applied turbulence model on the obtained results. The model was used to analyse the influence of the regenerator on the performance of the cold Stirling engine at different operating conditions. It appeared that on an average application of the regenerator increased the engine specific work by 10 J/kg and this increase is significantly higher at a high rotational speed of the engine. At the same time, the engine efficiency averagely was increased by 10 percent points and again this increase was significantly higher at higher rotational speeds of the engine. Especially, the influence of the heat source and sink temperatures on the engine operation were analysed. It appears that the lower are temperatures of a heat source and sink the more pronounced is the presence of the regenerator in the engine. Finally, the influence of the elementary parameters: particle diameter and porosity of the solid matrix which constitute the regenerator filling was investigated. It was shown that for the analysed engine the optimal value of the regenerator packing porosity equals about 0.72 it results in the specific area of the regenerator equal around 1675 m2/m3. Obtained results can be used to analyse the possibility of application of Stirling engines to recover low-temperature exergy of regasified Liquified Natural Gas (LNG), which for small regasification units can be alternative for commonly utilised Ambient Air Vaporizers (AAV) and it aside for regasification of LNG it could produce electric energy. [ABSTRACT FROM AUTHOR]

This paper deals with the Bayesian estimation of flow parameters in a porous material based on the measurements of local temperature at selected points inside the packed-bed. The unknown probability distribution function of estimated parameters was sampled using a Markov Chain Monte Carlo (MCMC) method. The MCMC method is efficient in sampling unknown distributions, but it is extremely time-consuming. The Proper Orthogonal Decomposition was used to construct off-line, low order approximation of the porous media flow problem. This model was further incorporated into the Metropolis-Hastings algorithm to retrieve the posterior distribution of the unknown parameters. This approach allowed us to decrease the computational time necessary to generate an ergodic Markov Chain. The efficiency of the proposed approach was tested on the simulated data generated with commercial CFD tools, and finally, it was applied to the real data acquired on the dedicated experimental stand. • Research highlight are summarized as follows: • Development of the mathematical model of biomass drying process. • Development of the coupled POD-MCMC inverse methodology estimate unknown parameters of the model. • Analysis of the accuracy of the developed approach. • Application of the inverse method to estimate model parameters for a real measurement data. [ABSTRACT FROM AUTHOR]