The pore structure of biomass particles is a key property governing their reaction behavior in thermochemical conversion processes. This study aims to assess the applicability of different physisorption measurement protocols and analytical approaches in pore structure analysis. Therefore, three samples produced in different conversion processes are investigated. The physisorption of N2, O2, and H2 is measured at 77 K and CO2 at 273 K using a commercial volumetric sorption instrument. The four probe gases exhibit distinct adsorption behavior on the investigated chars due to their physicochemical properties under the respective adsorption conditions. This study highlights the suitability of probe gases for investigating complex pore structures in biomass chars. The applied and compared analytical methods involve the BET theory, the Dubinin-Astakhov (DA) theory, and different non-local density functional theory (NLDFT)-based models. For microporous biomass chars, the applicability of the BET theory is limited by both the feasibility of reliable N2 adsorption measurements and the inadequacy of the BET assumptions for adsorption in microporous carbons. The DA theory, based on CO2 isotherms, provides a simple and straightforward basis for micropore analysis. The most comprehensive characterization is obtained from two-dimensional (2D)-NLDFT analysis resolving the pore size distribution (PSD) of the samples. Provided that a reliable adsorption isotherm is available, 2D-NLDFT analysis is considered the most robust method for determining pore properties compared to BET and DA. Dual-gas 2D-NLDFT analysis expands the analyzable pore width range. However, this study highlights the sensitivity of correlated models when adsorption data are affected by pore blocking or diffusion limitations.

For large particles, gas-phase reactions within the boundary layer determine whether O2 or CO2 acts as the primary oxidizer at the surface of char particles. Such large particles (in the multi centimetre range) are particularly relevant for applications such as municipal solid waste (MSW) incineration. This study presents a simplified model to investigate the dominant heterogeneous surface reactions and their kinetics during char conversion of a single spherical particle. Two heterogeneous reactions—direct oxidation (C + 12O2 → CO), and the Boudouard reaction (C + CO2 → 2 CO), are incorporated alongside the homogeneous oxidation of CO (CO + 12O2 → CO2) within the gas-phase. The governing conservation equations are solved numerically in spherical coordinates using Arrhenius-type kinetics over a broad range of particle sizes and temperatures under oxidizing conditions. The simulations reveal clear transitions between kinetically controlled and diffusion-controlled regimes. For particle sizes larger than 0.1 m and temperatures exceeding 1200 K, the Boudouard reaction dominates carbon conversion, while oxygen is consumed within the boundary layer and does not reach the particle surface. The basic model has been further simplified to allow for integration into an unresolved Discrete Element Method − Computational Fluid Dynamics (DEM-CFD) framework in the form of a correlation with reasonable computational cost.

The combustion behaviour of spherical and cubical char particles in static and agitated fuel beds is experimentally examined. Beech wood spheres and cubes (10 mm initial size) were pyrolyzed at 1173.15 K to prepare biochar particles. Bulk samples of these char particles with a constant initial fuel bed height are burned in a batch-operated reactor (BORA) at four primary air flow rates (2.16 to 11.85 g/s), with the air flowing upward through the bed. The bed can be agitated by vertically moving grate elements. Bed mass is measured continuously during conversion using a balance. The results from fixed beds were compared with those from agitated beds. Mass loss rates, flue gas composition (O2, CO, CO2), and temperatures were continuously monitored to evaluate conversion rates. The mass loss rate during combustion increases with higher mass flow of air, regardless of whether the bed is static or agitated. For spherical particles, agitation reduces the mass loss rate by 17 % to 26 % compared to the static bed. The effect is less pronounced for cubical particles, where the mass loss rate decreases by only 2 % to 13 % under agitated conditions. The lower mass loss rate observed for cubical particles could be attributed to their reduced mobility compared with spherical particles. It is suggested that the lower reaction rate observed in agitated beds arises from a shift from mass-transfer-limited conversion in static beds to a more kinetically controlled conversion in agitated beds.

The structural evolution and oxidation reactivity of partially converted mineral-free biomass-derived chars were investigated under both low and high heating rate conditions in O2 and CO2 atmospheres. Applying two-dimensional non-local density functional theory (2D-NLDFT) to CO2 and N2 physisorption data allowed for a detailed analysis of individual pore regimes as defined by IUPAC. Low heating rate experiments revealed that char conversion proceeds via kinetically controlled ultramicropore growth, followed by growth from ultramicropores to micropores and mesopores. Under kinetically controlled char conversion in O2 atmosphere, char conversion contributes to pronounced pore growth to overall surface areas three times as high as for the unconverted chars, dominated by ultramicropore formation. For gasification, both the generation of ultramicropores and their subsequent evolution into larger pores strongly dominate pore development, with an overall surface area increase by a factor of five. High heating rate treatments induced simultaneous pyrolysis and char conversion, resulting in the development of ultramicropores through devolatilization and reactions. These interdependent processes altered the distribution of reactive sites and reversed the relative reactivity trends observed under low heating rates. Structure/reactivity correlations demonstrate that oxidation reactivity is governed not only by total surface area but primarily by the distribution of pore regimes and reactive carbon sites. These findings highlight the critical role of heating rate and reaction atmosphere in determining char microstructure and performance.

View factors (VFs) are an efficient way to calculate radiative heat exchange in dense and loose packings of particles. Our present study investigates VFs in packings of cubes by means of Monte Carlo Ray Tracing (MCRT) simulations that are precise, but computationally extremely demanding. Subsequently, we use the obtained MCRT data to train and validate machine learning (ML) models to predict VFs based on a plurality of features meant to quantify shadowing. We then demonstrate that our ML models based on (i) a Multilayer Perceptron (MLP), (ii) a graph neural network (GNN), and (iii) a symbolic regressor (SR) can accurately predict VFs, drastically reducing computational cost compared to the MCRT simulations. MLPs achieve the highest accuracy, especially when using physically informed shadowing features, but require significant computation time to calculate the features. The SR relies on the same features, offers a straightforward implementation and achieves slightly lower accuracy. GNNs, using only particle positions, orientations, and direction vectors as features, offer a computationally efficient alternative with competitive performance and strong generalization. Our results show that reliable VF predictions are possible by ML-based models (i) for view factors larger than 10−3, (ii) using easily accessible features, and (iii) at a speed that is many orders of magnitude faster than MCRT. This enables integration of our ML-based models for VFs into large-scale DEM or CFD-DEM simulations of cubical particles. The performance and feature set used in our ML-based models, especially the GNNs, suggests that these approaches are also applicable to arbitrarily-shaped non-spherical particles.

Limestones release CO2 during their decomposition in shaft kilns, which is typically initiated by the combustion of natural gas. Oxy-fuel technology is one option to mitigate CO2 emissions by enabling carbon capture methodologies but induces more challenging process conditions.3D DEM/CFD simulations can compute the complex interaction of particles and gas flow but usually rely on spatial averaging of the gas-phase, which cannot capture all flow details. For a more detailed description of the processes, resolving the interstitial gas flow and the flame front inside the particle assembly is necessary. This study examines a down-scaled single-shaft lime kiln, utilizing an approach to locally resolve the gas flow in the most important region at the burner lances. The kiln has a height of 2.5 m, a diameter of 0.64 m, and contains 22,400 limestone particles of four different diameters. Two different simulation approaches are compared, the conventional unresolved method and the locally resolved approach. Results show minor differences in the average particle conversion degree. Higher differences are found in the local distribution of conversion degree and maximum particle temperatures. Unresolved simulations predict higher temperatures, leading to a deterioration of quicklime reactivity and potentially harming product quality, as details of the flow features are not captured. Consequently, the results indicate that unresolved simulations are a good approximation for the mean calcination degree of the particles but for more sensitive details, such as product quality, a higher-resolution simulation is necessary.

A radiation model based on the discrete ordinates method (DOM) is integrated into a discrete element method (DEM)-computational fluid dynamics (CFD) framework to simulate limestone calcination in a moving particle bed with gas flow. Local porosity of the particle bed is incorporated into the model to compute the effective radiative heat transfer for different packing densities. The endothermic calcination reaction converts CaCO3 into CaO. The article evaluates radiation penetration, temperature distributions, calcination degree, and CO2 mass fraction in the system. Convective, radiative, and particle-particle conductive heat transfer are considered for dilute, moderate, and dense packing densities. Results show that packing density strongly influences both radiation and calcination. The study shows that the calcination degree decreases with increasing packing density. The simulation results yield average calcination degrees of 98%, 80%, and 60% for particles at outlet in the dilute, moderate, and dense configurations, respectively.

ABSTRACT The present study focuses on the gas flow through an experiment‐scale modular packed‐bed reactor consisting of square bars arranged in layers. Each layer is rotated by 30°, resulting in a complex shape of the void spaces. Particle image velocimetry measurement results inside and above the bed are presented for Reynolds numbers of 100 and 200 and used as validation data for two sets of particle‐resolved numerical simulations, using a boundary‐conforming meshing strategy and treating the solid boundaries via the blocked‐off method. The flow inside the bed is largely independent of the Reynolds number and determined by the void space geometry. The flow in the freeboard is dominated by the presence of slowly dissipating jets downstream of the bed. The numerical results are in good agreement with the measurements, both inside and above the bed; however, stronger deviations can be observed in the freeboard and can be traced to numerical properties of the current simulation approaches.

In oxy-fuel combustion, pyrolysis is crucial for solid fuel conversion. This chapter presents experimental data on pyrolysis products from various biomasses (including minority species), forming one of the most comprehensive biomass pyrolysis data sets. Multiple setups (TG, fluidised bed, drop tube, heated strip reactors) cover a wide range of conditions, with design optimisations and discussions of advantages (e.g. reduced secondary reactions) and limitations (kinetics vs. transport). Since biomass is often modeled as cellulose, hemicellulose, and lignin, single first-order kinetics for these components under flash pyrolysis complement TG data. With walnut shells, superposition works only at slow heating rates, while higher rates demand extended modelling. Temperature strongly influences primary gas products, and residence time affects secondary distribution. The data also support more sophisticated kinetic schemes that describe the devolatilisation of biomass on the basis of its detailed chemical structure.

Char conversion is a highly complex process. Primarily composed of solid carbon, char has a very low vapour pressure, which prevents it from evaporating and undergoing gas-phase oxidation. Instead, char reacts directly at its surface throughout oxygen, carbon dioxide, hydrogen, and water vapour. These surface reactions generate carbon monoxide (CO), which then escapes the solid phase and oxidises into $$\text {CO}_2$$ CO 2 in the surrounding gas. Key factors that affect char conversion include the temperature of the surrounding gas, the composition of the atmosphere near the surface, ambient pressure, and characteristics like fuel composition, particle size, and shape. To capture the entire temperature range relevant in practical applications and to study the full span of char burnout—from the initial phase to the late stage over extended residence times—two experimental setups are employed: a fluidised bed reactor and a laminar plug flow reactor. These two test rigs also allow to study all char conversion regimes: regime I (kinetically controlled), regime II (pore-diffusion controlled) and regime III (film-diffusion controlled). Therefore char conversion is studied across a variety of fossil and biogenic solid fuels, with a broad range of temperatures and oxy-fuel gas atmospheres applied.

The conversion of biomass is significantly influenced by the presence and chemical behaviour of catalytically active minerals within the solid fuel. This chapter discusses the role of impregnated minerals during biomass conversion using extensive characterisation techniques. Iron oxides, alkali and alkaline earth metal sulphates undergo complex transformations during heating that significantly affect their catalytic activity. Kinetic analysis showed reduced activation energies for doped fuels in gasification and oxidation following an overall reactivity sequence of K > Na > Fe > Ca > Mg. Fast-heating pyrolysis experiments revealed mineral effects on the formation of all three pyrolysis products influencing tar distribution, light gas formation, and char evolution. Additionally, combustion studies in a flat flame burner demonstrated earlier ignition and varied impacts on the combustion temperature depending on the type of doping. Overall, the results demonstrated a significant influence of minerals on biomass conversion and highlight the importance of mineral characterisation in optimising biomass-based energy production.

The experimental investigation of radiation in large combustion chambers is challenging due to the harsh environment and various radiation effects. This chapter presents experimental findings from several laboratory-scale studies that examined these effects separately. One goal was to determine the emissivity of the solid fuels and of ash utilising two setups: (1) observing a particle streak in a laminar flow reactor (LFR) and (2) studying laser-ignited fuel particles. The emissivity of both investigated solid fuels (Colombian bituminous coal and walnut shells) decreased with increasing temperature and progressing conversion, where mineral content has also an influence. For particles at higher levels of conversion, a final increase in emissivity was noticed. A spectroscopic experiment examined the emissivity of typical ash components and their mixtures. Carbonates and sulphates exhibited characteristic temperature- and wavelength-dependent emission trends, with specific emission bands attributed to CO $$_3$$ 3 and S–O functional groups. Another goal was to determine the index of refraction of the solid fuels experimentally. It was measured at room temperature and for burning particles applying inverse Mie-theory.

Pyrolysed biomass char particles may have different morphologies, as various types of biomass are prone to shrinking/swelling, spheroidisation and thermal annealing during pyrolysis in flow reactors. These features have important implications on burning mode, conversion rate and combustion efficiency. However, addressing these effects is difficult due to the inherent complexity of biomass structure. In fact, both thermal annealing and changes in particle morphology during heat treatment have often been neglected and underestimated. In this work, experiments were carried out to measure the effects of biomass lignocellulosic compositions on char reactivity and morphology. Torrefaction converts raw biomass into a solid fuel with reduced moisture and increased calorific value, mainly by degrading hemicellulose. Natural biomasses with different lignocellulosic compositions and pre-torrefied samples are compared. The experimental campaign included experiments in a drop tube reactor and a heated strip reactor, with fast heating rates of 103 degrees C/s, maximum temperatures up to 1800 degrees C, and residence times ranging from 0.2 s to 2 s. Combustion reactivity, particle shape and size are analysed to discuss the role of holocellulose/lignin in the propensity of biomass to undergo thermal annealing and plastic deformation. Hemicellulose appears to play a significant role, limiting the effects of heat treatment in terms of thermal annealing and the tendency to particle shrinkage and spheroidisation. This is attributed to its capacity to link with other structural parts of the biomass, such as lignin, making the biomass structure more rigid and to the formation of a plastic melt, which hinders free rearrangement of the biomass structural units.

Intraparticle models are crucial in the Discrete Element Method when particles are thermally thick. Accurately solving the intraparticle conservation equations using the finite volume method requires high spatial and temporal resolution, which significantly increases computational cost. This study presents a model that relies on tabulation to describe intraparticle heat conduction inside complex-shaped particles. This cost-effective method replaces the computationally expensive finite volume method without compromising the accuracy. The method has been applied to different particle shapes: a cylinder with two different aspect ratios, a cube, a square thin plate, a sphere and an irregular shape. Materials with very different thermal conductivities - glass, limestone, and wood - have also been examined. For wood particles, anisotropic heat conduction is considered as wood possesses directional thermal properties. The particles exchange heat with the surrounding gas by convection, where the gas-phase temperature varies over time between 350 K and 950 K as a superposition of four harmonic functions with different frequencies. The response of the particle surface temperature, core temperature, and internal temperature distributions is compared with results obtained from the finite volume method. The tabulated model accurately reproduced the temperatures of the finite volume method, with maximum rootmean-square deviations of 10 K. A speed-up factor of at least 100 was achieved using the tabulation method compared to the finite volume method, increasing further with higher mesh resolution.

This chapter presents the development of models for the thermochemical conversion of coal and biomass, focusing on advances in biomass modelling. Chapter 8 introduces the characteristics of solid fuels, compares pyrolysis behaviours, and outlines the molecular structure of biomass, providing a foundation for kinetic modelling. Key models discussed include the chemical percolation devolatilisation (CPD) model, char conversion kinetics (CCK) model, and the CRECK-S model. CPD and CCK models carry an increased level of phenomenological description, ideal for benchmarking fuel conversion predictions. In contrast, CRECK-S model offers balanced complexity, predictivity and seamless coupling of pyrolysis and char reactions. The CRECK-S model is chosen to be the basis of solid fuel conversion modelling in the OxySim-129 framework, and hence is the main focus of this chapter. The outcome is a comprehensive model capable of handling diverse operating conditions that can be coupled directly or indirectly to CFD simulations. Major developments include extensions for oxy-fuel char conversion, increasing details of released products, validation for biomass feedstock samples of Oxyflame (i.e. walnut shells).

The work reports preliminary results on the morphological changes that biomass particles experience at high heating rates in a heated strip reactor (HSR) at T = 1000–1600 °C under an inert atmosphere. Samples included a natural lignocellulosic biomass (pinewood) as well as biomass components: cellulose, hemicellulose (xylan) and lignin. On top of that, reference compounds have been investigated, namely naphthalene pitch, a paraffinic wax and glucose. During the heat-up phase, the investigated biomass mainly retains the original morphology and size, while the single components exhibit different behaviors. Hemicellulose undergoes a fluid stage and eventually forms millimetric spherical char particles. Cellulose does not become fully fluid but softens and forms millimetric char aggregates of different shapes. Lignin particles hardly soften and stick together in a curved slab. Comparison with model compounds allows us to infer that the degree of melting and the viscosity of the melt are responsible for the final particle shape. In fact, naphthalene pitch and glucose appear to be more viscous during pyrolysis and lead to the formation of three-dimensional columns a few millimeters high. Wax undergoes extensive melting, but the relatively low viscosity and the absence of crosslinking reactions eventually lead only to the formation of droplets.

Refuse derived fuels (RDF), produced from municipal and industrial waste, provide an alternative to fossil fuels like coal or lignite in the cement production, thereby reducing the significant CO2 emissions typically associated with cement production. The composition of RDF is often unknown, which limits the substitution rate, since otherwise the risk of impacting cement quality would increase. In this contribution, both near-infrared spectroscopy (NIRS) and RGB images were used to analyze RDF in an at-line measurement on a conveyor belt setup. The goal was to classify individual RDF particles in one of six fractions (paper, foils, 3D plastic, rubber, foams, textiles), since the fractions differ in combustion and flight behavior and therefore influence cement quality. For this, training, validation, and test data were obtained from 11,526 manually sorted RDF particles, sampled from various German cement plants and processed using an at-line conveyor belt setup. The NIRS data were processed using a small convolutional neural network (CNN) to provide the respective fraction, yielding an accuracy of 99.5

Discrete Ordinates Method (DOM) is a model for thermal radiation exchange in opaque media. In this study, the DOM formulation is employed within the framework of the Discrete Element Method coupled with Computational Fluid Dynamics (DEM-CFD), thus including full radiative heat exchange among the phases involved. This is done by adjusting the absorption coefficient, emission coefficient, and net radiative heat flux of particles by incorporating local porosity into equations. A key objective is to represent radiation propagation for different packing densities in packed beds accurately. The model is validated by comparing the results with available data from the literature for simulations with a P1 radiation model and corresponding experiments. The validation configuration is a heated box filled with spherical particles under vacuum conditions. As an application example, the radiative heat exchange between an enclosure at high temperature and moving layers of spherical particles concurrently passed by a gas in crossflow is studied. Three packing densities (dilute, moderate, and dense) are examined to evaluate radiation penetration into the particle ensemble. Convective and contact heat transfer are also considered. The DEM-CFD coupling is a nonresolved approach, where the influence of particles on the flow field is accounted for by momentum and energy source terms together with a porosity field (Averaged Volume Method (AVM)). Effect of convective, conductive and radiative heat transfer is analysed based on the evolution of incident radiation flux, spatial distributions of particle surface and fluid temperatures, and particle temperature histograms. It becomes obvious that radiation dominates the system, and that packing density defines the penetration depth of radiation. Conduction mainly leads to a smoothening of particle temperature distribution in the system. (c) 2025 Chinese Society of Particuology and Institute of Process Engineering, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).