A detailed one-dimensional model of combustion of a woody biomass particle

Haseli, Yousef; Oijen, van Ja Jeroen; Goey, de Lph Philip

doi:10.1016/j.biortech.2011.07.075

Cited by 88 publications

(54 citation statements)

References 30 publications

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“…While this compared favourably to experimental data presented for a single particle burning in entrained gas flow, a more robust validation would require more extensive experimentally derived data to be produced, covering the range of particle sizes. Other useful single particle modelling approaches have been set out by Haseli et al [9] and Saastamoinen et al [10].…”

Section: Introductionmentioning

confidence: 99%

Single particle flame-combustion studies on solid biomass fuels

Mason

Darvell

Jones

et al. 2015

Fuel

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Combustion of solid biomass in large scale power generation has been recognized as a key technology for the transition to a decarbonized electricity sector in the UK by 2050. Much of the near-term forecast capacity is likely to be by the conversion of existing coal-fired pulverized fuel plant [1]. In such applications, it will be necessary to ensure that the combustion behaviour of the solid biomass fuels is engineered to match, as far as practical, that of the original plant design. While biomass feedstock characteristics vary considerably, one controllable variable for pulverized fuel is the size of the particles.Useful modelling for adaptation and design of boiler plant can be improved with more detailed measurement of the real behaviour of individual particles of the varying fuels. Typical power plant biomass fuels including pine, eucalyptus and willow with particle sizes ranging from up to 3mm [2] and with differing moisture content and aspect ratios were selected for study. Single particles were supported in a water-cooled cover and then exposed above a flame, simulating biomass combustion in a furnace.Measurements of ignition delay, volatile burning time and char burn-out time were undertaken using high speed image capture. Temperatures of the surrounding environment and near to the particle surface were measured with thermocouples and thermometric imaging. Thermo-gravimetric measurements on 2 separate samples complement the single particle measurements as a means of verifying the demarcation between the different stages of combustion and providing kinetic data.Analysis of the data identified correlations between the biomass fundamental characteristics, particle size, and the observed combustion profiles. Empirical expressions for the duration of each combustion stage have been derived. These have been validated with basic modelling including the predicted devolatilisation stage calculated by the FG-Biomass model [3].

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Section: Introductionmentioning

confidence: 99%

Single particle flame-combustion studies on solid biomass fuels

Mason

Darvell

Jones

et al. 2015

Fuel

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“…Already, the effect of particle size on quantitative differential thermal analysis is generally considered in organic materials [8,9,26,27] and biomass sample, Pinus radiata [28]. Depending on various parameters such as particle size and density, surrounding temperature, oxygen concentration in the surrounding flow, the combustion of biomass particle may take place sequentially or simultaneously [29]. Thermal analyses are conducted, by definition, by the samples being brought into a thermal disequilibrium, so it can be readily accepted that the recorded temperature of transformation depends on the reaction rate, which is influenced by the particle size distribution [10].…”

Section: Discussionmentioning

confidence: 99%

Thermal analysis of green algae for comparing relationship between particle size and heat evolved

Kang

Yoon

2014

Biomass Conv. Bioref.

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The thermal properties affected by particle size of microbial cell were investigated by the simultaneous thermogravimetry (TG) and differential thermal analysis (DTA). The particle size, which could affect the heat evolved, occurred from the combustion of the microbial cells. The model microorganism used in this study is Nostoc, a genus of flamentous, heterocystous, and cyanobacteria, known as a freshwater microalga, which can accumulate a large amount of lipid in the cell. As a result, the marked difference in heat energy between the different particle sizes of microbial sample was detected in the temperature range from 310 to 351°C. So, the two-step linear temperature program is used for resolving the overlapping exothermic peaks in the DTA curves in the temperature range from 310 to 315°C. The heat evolved from 45 μm-sized particle sample in this temperature range was 3.78±0.19 kJ/g which was 1.1-to 1.4-fold greater than those from the other particle size samples. The heat evolved occurred in 310-351°C was inversely proportional to the particle size of dried microbial cells. In conclusion, exothermic heat per dry sample mass (kJ/g) in the temperature range from 310 to 351°C is highly dependent on the particle size of dried microbial cell.

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“…A detailed modeling of the physical and chemical processes tends to become quite involved [12]. In this article we aim at a simple effective model which still yields a reasonable qualitative description of the key processes.…”

Section: A Ca Model For Log Wood Combustionmentioning

confidence: 99%

Towards a Stochastic Cellular Automata Model of Log Wood Combustion

Lichtenegger

Schappacher

Hebenstreit

et al. 2014

J. Phys.: Conf. Ser.

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Abstract. Describing the combustion of log wood and others solid fuels with complex geometry, considerable water content and often heterogenous struture is a nontrivial task. Stochastic Cellular Automata models offer a promising approach for modelling such processes. Combustion models of this type exhibit several similarities to the well-known forest fire models, but there are also significant differences between those two types of models. These differences call for a detailed analysis and the development of supplementary modeling approaches. In this article we define a qualitative two-dimensional model of burning log wood, discuss the most important differences to classical forest fire models and present some preliminary results. Keywords: cellular automata, stochastic modeling, combustion Introduction: The Role of Log WoodBiomass is an important source of renewable energy; the efficient use of biomass will be essential to achieve the transition to a lifestyle based on renewable resources. In order to reach the European 20-20-20 goals [1], about half of the demand for renewable energy will have to be covered by biomass. More than half of this amount will presumably be used in domestic smallscale combustion systems.While pellet technology -promising better control and lower emissions than traditional wood combustions -is on the rise, log wood is still an important fuel and will presumably remain to be so for decades to come. A main advantage of log wood is an economic one: Since less processing is required, log wood has a lower price than pellets. Also stoves tend to be cheaper. At the same time, less volume is needed for storing wood logs than for storing wood chips, an even cheaper renewable fuel. Also the handling of wood logs is easier than that of wood chips.The combustion of wood logs, however, is a complex process which involves transport processes, chemical reactions and heat transfer processes within complex geometry. There has been put quite some effort in the development of models for combustion of woody particles, in particular shrinking-core and reacting-core models [2,3,4,5] and CFD-related approaches based on partial differential equations [6,7]. These models grasp some important aspects of wood combustion, but they cannot (yet) incorporate the often complex geometry of wood logs. Complementary modeling approches, as the one presented in this article, may help to improve this situation.

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A detailed one-dimensional model of combustion of a woody biomass particle

Cited by 88 publications

References 30 publications

Single particle flame-combustion studies on solid biomass fuels

Single particle flame-combustion studies on solid biomass fuels

Thermal analysis of green algae for comparing relationship between particle size and heat evolved

Towards a Stochastic Cellular Automata Model of Log Wood Combustion

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