Numerical Study of the Pyrolysis of Ellipsoidal Low-Rank Coal

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Numerical Study of the Pyrolysis of Ellipsoidal Low-Rank Coal Briquettes Yuting Zhuo, Tianyu Wang, Changxing Li, and Yansong Shen Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.7b03224 • Publication Date (Web): 01 Jan 2018 Downloaded from http://pubs.acs.org on January 17, 2018

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Energy & Fuels

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Numerical Study of the Pyrolysis of Ellipsoidal

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Low-Rank Coal Briquettes

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Yuting Zhuo, Tianyu Wang, Changxing Li, Yansong Shen*

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School of Chemical Engineering, University of New South Wales, Sydney, NSW 2052,

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Australia

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KEYWORDS: Low-rank coal, pyrolysis, briquette, ellipsoid, CFD, DEM

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ABSTRACT

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Low-rank coal (LRC) upgrading is essential to convert LRC to a more thermal-efficient and

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environmentally friendly fuel before utilization in coal-based industries. Briquetting and

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pyrolysis is the dominant route where briquettes are usually in shape of ellipsoid through a

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two-roll briquetting process. In this work, an integrated numerical model is developed to

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predict the pyrolysis process of ellipsoidal LRC briquettes in a packed bed pyrolyzer. A

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Computational Fluid Dynamics (CFD) model is developed to describe the flow and

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thermochemical behaviours related to the pyrolysis of ellipsoidal LRC briquettes including

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dewatering, pyrolysis, and other homogeneous and heterogeneous chemical reactions. A

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Discrete Element Method (DEM) model is used to describe the packing density distribution

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of ellipsoidal briquettes. The model is validated against the measurements in a pilot-scale test

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rig in terms of temperature history and gas species yields. The typical in-furnace phenomena

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are illustrated including flow field, temperature field, and products evolution. Then the

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effects of key variables including briquettes properties and heating condition on pyrolysis

1 ACS Paragon Plus Environment

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behaviour are investigated quantitatively. The effects of key parameters including briquettes

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moisture, final pyrolysis temperature, and briquettes aspect ratio on pyrolysis are studied and

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the optimal values are identified under the given conditions. For example, more H2 and less

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CH4 are generated when the initial briquettes’ moisture content is increased in the range of 2%

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to 15%, but H2 is then decreased and CH4 is increased in the range of 15% to 20%. The

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maximum packing density is obtained when briquettes’ aspect ratio is 2.0. However, the

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highest temperature increase rate is observed when the aspect ratio is 1.7. An appropriate

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final pyrolysis temperature, 973K in this study, is suggested to balance pyrolysis rate and

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energy consumption. This model provides a cost-effective tool for optimizing the design and

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operation of pyrolyzers for ellipsoidal LRC briquettes.


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Energy & Fuels

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1

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The low-rank coals (LRCs), typically sub-bituminous and lignite, are geographically

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dispersed, abundant, and accounts for almost half of the world's coal reserves

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LRCs have some undesirable characteristics, such as high moisture content, low heat value,

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and high mineral content etc., leading to limited use in industries. The upgraded LRCs have

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been proven to improve plant efficiency, enhance safety, and reduce greenhouse gas

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emissions3,4. On the other hand, as non-renewable premium coking coal reserve decreases

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and the greater awareness of potential environmental risks of coal utilization, there is also a

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need to convert LRCs to a thermal-efficient and environmentally friendly fuel for wider and

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cleaner applications with higher economic value5. Thus, these necessitate LRCs upgrading

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before effective applications in industries in power plant and metallurgical industries.

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To date, the major LRC upgrading techniques include blending, briquetting, drying, cleaning

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(removal of minerals) and chemical upgrading6,7. Out of these techniques, briquetting-

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pyrolysis is a cost-effective and dominant route. LRC briquetting is a physical process where

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excess moisture is removed by extruding coal fines with pressure and likely temperature,

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producing briquettes in certain shapes, typically in ellipsoid shape using two-roll briquetting

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machines. It has been widely investigated in terms of products yield and physical properties

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worldwide8,9. On the other hand, pyrolysis is a thermochemical decomposition process where

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the coal particles or briquettes are heated up without oxygen present, and produce tar, gases,

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and semi-coke. Compared to raw coal combustion, pyrolysis is able to convert LRCs to more

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diverse, specifically designed and profitable fuels. Moreover, in conventional industrial fixed

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bed pyrolyzer, lump coal is usually the major material, allowing gas heat carrier and pyrolysis

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gases pass through the bed smoothly and reduce the risk of explosion when semi-coke is

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discharged after pyrolysis. Hence, fine coal cannot be directly utilized in such pyrolysis

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process in the past, limiting LRC’s application. Combining briquetting and pyrolysis

INTRODUCTION


1,2

. However,

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techniques, more fine coals can be used efficiently and the friability and emission problems

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can be mitigated at a competitive cost against the traditional fuels10. Therefore, it is important

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to understand and optimize the pyrolysis of LRC briquettes, typically in the shape of ellipsoid,

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including the packing of ellipsoidal briquettes and their pyrolysis behaviour in the packed bed

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pyrolyzer.

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The pyrolysis of LRCs has been studied by different methods, experimentally and

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numerically11. Extensive experimental studies have been conducted to investigate coal

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pyrolysis process. For example, Li et al.12 reviewed the recent experimental studies of

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pyrolysis and gasification behaviour of Victoria brown coal13,14. Due to the harsh thermal and

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chemical conditions inside the pyrolysis reactor, it is difficult to measure the detail internal

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information in a continuous operating pyrolyzer, such as temperature and gas evolution, but

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such information plays a significant role in optimizing design and operation.

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As the development of computer technology, numerical modelling has emerged as an

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effective tool for understanding and optimizing complex reaction systems including the

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pyrolysis of LRCs15–18. Some 2D CFD models were developed for describing the

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carbonization process in coke ovens19–21. In these models, fine coal bed was treated as porous

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medium and the flow pattern and evolution of coke oven gas was investigated. Moreover,

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some multi-fluid models are developed to study the influence of operation conditions on coal

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pyrolysis and gasification processes22. For example, Zhang et al.23,24 developed a CFD model

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for municipal solid waste gasification process in an industrial scale fixed bed, and discussed

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the effects of operation conditions on energy consumption and syngas composition. In

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addition, some CFD-DEM models

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pyrolysis and gasification process at particle sale, where particles were in the shape of sphere.

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On the other hand, in the packing processes, packing density is widely used as a parameter in

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particle packing characterization. The effect of particle shape on packing density has been

25–28

were developed for investigating coal or biomass


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studied for years, for example, Zhou et al.29,30 and Li et al.31 Recently, the investigation

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regarding the packing of non-spherical particles by DEM approach is increasingly gaining

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popularity32,33. They showed that ellipsoid packing is quite different from the packing of

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spheres. To date, few studies have been found in the literature on the modelling of the

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pyrolysis or combustion of ellipsoidal briquettes34. In the present work, an integrated

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numerical model is developed for describing the pyrolysis behaviour of ellipsoidal LRC

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briquettes in a packed bed reactor. In this integrated model, a CFD model is developed for

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describing the flow and thermochemical behaviour related to pyrolysis including dewatering,

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pyrolysis, and other homogeneous and heterogeneous reactions, and a DEM model is used for

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describing the packing density distribution of ellipsoidal briquettes. The model is validated

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against the measurements in a pilot-scale test rig in terms of temperature history and gas

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yields. The typical in-furnace phenomena are illustrated including spatial distribution of flow

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field and temperature profile, and products evolutions. The effects of key variables on

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pyrolysis are then investigated quantitatively including briquettes properties and external

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heating conditions.

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2

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2.1 Experiment setup

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A pilot-scale fixed bed pyrolyzer is built at Sinosteel, China and used to investigate pyrolysis

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performance of LRC briquettes. The schematic of pilot-scale pyrolysis test system is shown

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in Figure 1. The geometry information is shown in Figure 2. Briquettes are introduced into

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the reactor at room temperature. The remaining air is purged by N2 with a rate of 2 L/min for

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10 minutes. The reactor is heated up under the control system using a predefined scheme.

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Four thermocouples are placed inside the wall for monitoring the heating wall’s practical

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temperature and feedback to the temperature control system to adjust the temperature. One

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more thermocouple is placed at the centre axis of the bed to measure the bed centre

EXPERIMENT DETAILS


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temperature during the pyrolysis process. The gas products including vapour and tar releasing

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from the reactor will outflow from the upper exit, and then are separated by the tar trapper

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and dryer for being collected and weighted. The composition of the remained gases is

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collected and analyzed by gas chromatography. 3.5kg (dry base) briquettes are used in each

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test. The geometry and operational conditions will be used as boundary condition for the

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numerical model, and the measured data will be used for model validation.

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2.2

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In this study, briquettes made from Shenmu LRCs through the two-roll briquetting process

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are used in the experiment. The average particle size of an ellipsoidal briquette is shown in

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Figure 3, where briquette’s semimajor axis length, a, is 25mm and semiminor axis length, b,

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is 14.7mm. The average weight of each briquette is 12g with bulk density being 1280 kg/m3.

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The proximate and ultimate analyses of the briquettes are shown in Table 1.

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3

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3.1

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In the present work, a CFD model is developed for describing the pyrolysis process in the

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fixed bed pyrolyzer. In this model, Euler-Euler multiphase approach is employed in the CFD

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model. The gas flow is treated as a laminar flow of ideal gas

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composition analyses in the experiment, 15 kinds of gas species are defined in this model for

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the involved homogeneous and heterogeneous chemical reactions. The solid phase is treated

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as a continuous granular flow. The flow of granular materials in the fixed bed pyrolyzer is

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treated as plastic flow35–37. The radiation heat transfer is described by the discrete ordinate

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model. On the other hand, a DEM model is used for describing the packing of the ellipsoidal

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briquettes. The model is detailed elsewhere 31. The results of the DEM model will be used as

Properties of the briquettes

MODEL DETAILS Gas-solid flow and heat transfer


21

. According to the gas

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the initial condition of the CFD model. The governing equations of continuity, momentum,

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and energy for solid and gas phases are listed in Table 2.

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The Gidaspow drag model38 is used to calculate the drag force. This paper studies ellipsoidal

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LRC briquettes rather than spherical particles. It is necessary to introduce the effect of

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particle shape on drag force and heat transfer. Nanda et al.

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describing the non-spherical particles in terms of drag force and heat transfer by modifying

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drag force coefficient and Nusselt number, respectively. That is, the drag force coefficient Cd

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for the ellipsoid particles proposed by Nanda et al.

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interphase momentum exchange is as follows: r r  α sα g ρ g v s − v g 3  K sg = C D α g −2.65  ds 4 r r  ρ gα s v s − v g  α s (1 − α g ) µ g + 1.75  K sg = 150 ds α g ds2  CD =

39

39

proposed a modified model for

is used. The coefficient K sg of the

If α g ≥ 0.8

(7) If α g < 0.8

24 e 0 .4 9 (1.0 5 + 0.1 52 R e 0 .6 87 e 0 .6 7 1 ) Re

(8)

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The interphase heat exchange intensity between solid phase and gas phase is driven by the

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temperature difference, and calculated as follows: Q sg = − Q gs = k sg (T s − T g ) k sg =

(9)

6 k gα sα gNu s dS 2

(10)

Nus = 2e0.3 + Pr 0.4 (0.4 Re0.5 e0.83 + 0.06 Re2/3 e0.1 )

(11)

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Here, the modified Nusselt number modified by Nanda et al.39 is introduced for considering

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the influence of ellipsoid particle’s aspect ratio on interphase heat transfer.


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3.2

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Moisture retained in briquettes could be divided into three categories, free water, bound water

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and water vapour, which will be driven out when particles are heated up

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process involves free water evaporation, bound water desorption and evaporation as well as

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the chemical bound water separation24. In the present work, a simplified drying model is used

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to predict the moisture evolution in pyrolysis process24,40, as below.

Drying

25

. This complex

r = A v k m ( C M oi − C H 2 O )

when Ts < 373.15K

（12）

r = Q a / H evap

when Ts ≥ 373.15K

（13）

Q a = A s ( h s ' ( T s − T g ) + Q ra d

（14）

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where Av is the specific area of particles, km is the interphase mass transfer coefficient

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between solid and gas phase. Qa is a summation of heat absorbed by the solid phase.

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3.3

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The briquettes are assumed to be consist of four components, including water, volatile matter,

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fixed carbon, and ash. The homogeneous reaction rate is calculated using the finite rate model,

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and the unreacted shrinking core model

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calculation. Reactions considered in this CFD model and their reaction kinetics are given in

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Table 3. For example, many pyrolysis or devolatilization models have been proposed, such as

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one step kinetic rate model42, two competing model43 and complex models whereby DAEM44,

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FLASHCHAIN45, CPD46 and FG-DVC47. In the present model, the two steps model is used

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to balance accuracy and computational load, where the coal will thermal decompose firstly to

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primary tar, gas, and char at first and then primary tar will subsequently crack and convert to

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the secondary tar and other hydrocarbon gases. T 1 is defined as the activation temperature at

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which the first step of devolatilization is activated. It is estimated using the correlation

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modified by Gregory and Littlejohn48. The CFD model is developed based on the framework

Reaction models

41

is applied for heterogeneous reactions rate


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of a commercial software package ANSYS-Fluent v17.2. The reaction rate, modified drag

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force model, and modified heat transfer model introduced previously are written as UDF in

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Fluent.

166 167

4

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4.1

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The properties of the coals used in the base case are the same as used in the experiment

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(Table 1). The thermal properties of briquettes and operating conditions are shown in Table 4.

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The simulation geometry is set as same as the experiment (Figure 2). It should be noted that

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for evaluating the influence of final pyrolysis temperature on pyrolysis three heating schemes

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for heating wall are defined. These heating schemes are used in the experimental studies to

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make sure that the coal bed temperature can increase at a mild rate and therefore avoid crack

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when the temperature increase too fast.

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4.2

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In order to control the briquettes bed height in the experiment, dense packing is conducted for

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keeping the bed height as 0.355m in each test to guarantee the entire bed stay at the flat-

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temperature zone of the furnace. The DEM model

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process for obtaining the briquettes’ packing density distribution. The DEM code used in this

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study has been validated in several cases29-31, where the simulation results were found

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comparable with the experimental data. Based on the DEM simulation, the bed is divided into

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8 sections and each section’s average packing density is calculated, as shown in Figure 4.

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Based on this DEM simulation result, the correlation between bed height and packing density

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is obtained as Equ 15. It will be used as the initial condition of the CFD-based pyrolysis

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model.

SIMULATION CONDITIONS Materials properties, and boundary conditions for CFD model

Packing density

29–31

is applied to simulate the packing


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Pc = 0.543 + 0.874 y − 7.028 y 2 + 24.866 y3 − 32.408 y 4

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(15)

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5

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5.1 Model validation

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The model is validated against the measurements in the experiments in term of temperature

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history and gas yields. Figure 5 compares the predicted and measured temperature history at

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the monitor point. The monitored point is set to the same position with the thermal probe

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located in the experimental reactor (see Figure 2). Figure 6 illustrates the comparison of

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generated gases composition between the simulation results and experimental data. It is

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indicated in Figure 5 and Figure 6 that both the predicted temperature history and the gas

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components show good agreements with the experimental data. This confirms the validity of

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this model. This model slightly underestimates the mole fraction of CH4 and overestimates

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the H2, this can be explained by the simplified devolatilization reaction assumption.

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Generally, this deviation of predicted results is acceptable for understanding the

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characteristics pyrolysis process.

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5.2

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In this section, the key in-furnace phenomena related to the pyrolysis of ellipsoidal LRC

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briquettes are described including flow field, temperature field and gas distributions.

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Figure 7 shows the temperature profiles of the briquettes and gas phases at the selected time

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in the base case. Note that the wall temperature follows scheme 2 (see Table 4). It can be

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observed that with the wall temperature increases, the briquettes bed temperature rises up

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gradually from near wall section to the centre. With the reaction proceeds, the briquettes

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temperature at upper part rises faster than that of the lower part, due to the intensive heat

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transfer by convection between gas and solid phase. The lower temperature is found near the

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bottom due to the adiabatic setting of the wall, consistent with the practical operation. At

RESULTS AND DISCUSSION

Typical phenomena of the pyrolysis of ellipsoidal LRC briquettes


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10000s, almost all briquettes are heated up to predefined final pyrolysis temperature (973K)

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except for the bottom bed. It is indicated that the temperature history at the monitor point (see

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Figure 5) has a plateau between around 1500s and 2100s, due to the endothermal dewatering,

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then the temperature increase at a higher rate until the devolatilization reaction takes place.

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The second plateau emerges after about 11000s where the briquettes bed’s temperature levels

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off at 973K that reach the target heating temperature of the wall as the predefined scheme

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(Table 5).

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Coal pyrolysis is a complex process including gas-solid flow, heat transfer and a series of

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chemical reactions, such as drying, devolatilization, water-gas shifting, etc. Devolatilization

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is the key step in the entire pyrolysis process. Figure 8 upper part shows the remaining

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volatile matter content distribution in the bed at the selected time. The initial VM content is

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set to 32.7%. It is indicated that at the beginning stage, VM content decreases slowly. This is

222

because, the temperature of the centre part of briquettes bed is lower than that close to the

223

wall, as a result, the VM content will not change much until it reaches the activating

224

temperature. It is also observed that the remained VM content depends on the distance to the

225

wall. With increasing temperature of bed (Figure 7), the devolatilization reaction is favoured

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by higher temperature. The heat exchange in the near-wall area and the roof of bed is more

227

intensive than other parts, resulting in the faster decrease of VM. Typically, the remaining

228

amount of volatile matter is used to characterize the extent of pyrolysis. At around 11000s all

229

the volatile matter is driven out. This means the pyrolysis reaction nearly finishes. Figure 8

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middle and bottom part illustrate the evolutions of primary tar and secondary tar, respectively.

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It can be observed that the primary tar resulting from the first step reaction in the

232

devolatilization model shows a lower mass fraction along the centreline initially and near the

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bottom of reactor finally. This is because a gas flow stream exists along the centreline (Figure

234

9) driven by the temperature difference in briquettes bed. And the gas products in the second 11 ACS Paragon Plus Environment

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step of devolatilization reaction tend to go through briquette bed from high temperature area

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to low temperature area. Therefore, the primary tar mass fraction shows a lower value, while

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the secondary tar shows a higher mass fraction in these areas.

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Moreover, it is found in Figure 8 that as reaction proceeds, tar cracking becomes the

239

dominant reaction in the gas phase, and consequently, secondary tar concentration gradually

240

increases in the high-temperature area. It can be found that at the beginning stage of pyrolysis,

241

secondary tar emerges at the roof of reactor where the temperature is much higher than the

242

bed. As heating proceeds, more primary tar is converted to secondary tar in the briquettes bed.

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This is induced by the increasingly higher gas temperature as well as the primary tar

244

concentration, where the latter accelerates the tar cracking rate and subsequently convert the

245

primary tar into other light hydrocarbon gases.

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Typically, the in-furnace information of gas and moisture released from briquettes bed in an

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industrial plant are difficult to measure. In order to produce results that can be more readily

248

and useful in practice, the mass flow rate of generated pyrolysis gases is monitored at the

249

outlet, as shown in Figure 10. Two peaks can be observed during the whole process. The first

250

peak is found ranging from 0 to 2500s, resulting from the heat transfer from the wall to the

251

briquettes bed and the intensive moisture evaporation. Before the secondary peak, the

252

pyrolysis gas release as a mild rate, because the bed average temperature has not reached the

253

point where the devolatilization rate becomes faster. The secondary peak is found around

254

8000s where the mass flow approach to the highest level and then decrease dramatically as

255

the remaining VM has been completely released. To observe the pyrolysis gas species

256

distributions at the middle stage of the process, profiles of some important gas species at

257

7500s (where mass flow rate reaches the peak) are shown in Figure 11. It is indicated that the

258

vapour is nearly disappeared at this moment, whereas CH4 and H2 show a relatively higher

259

concentration within the bed and CO2 shows a higher concentration near the roof. The latter 12 ACS Paragon Plus Environment

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can be explained by the secondary tar cracking reaction takes place at that part and produce

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more CO2.

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5.3 Effects of key variables on ellipsoidal LRC pyrolysis

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Pyrolysis performance may be directly affected by many conditions including charge

264

properties and operating conditions. In this section, the effects of briquettes’ moisture content,

265

ellipsoid’s aspect ratio, and final heating temperature on pyrolysis are investigated

266

quantitatively at the bed centre. Each operating condition is varied while keeping other

267

parameters constant. The varying parameters are listed in Table 5. Case 1 is the base case

268

where boundary conditions and charge properties are set as same as the experimental

269

conditions.

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Effects of briquettes’ moisture content

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Figure 12 shows the effect of initial moisture content of the briquettes on bed temperature

272

evolution (a), gas products composition (b), VM content (c) and mass flow rate at the outlet

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(d), respectively, by means of comparing Cases 1-5. It can be found in Figure 12(a) that the

274

temperature increase rate gradually decreases in preheating stage and the dewatering time is

275

prolonged when briquettes bed has a higher initial briquettes moisture content. In particular,

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the temperature difference is significant between Case 1 and Case 5 at the time when

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dewatering is finished in Case 5, because more energy is needed for evaporating the

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increased moisture in the briquettes. Even though in the later stage, the temperature

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increasing rate in all cases becomes faster than preheating stage, yet Case 5 shows faster rate

280

than other cases, since less amount of VM remains and briquettes’ specific heat and thermal

281

conductivity are varied with the composition. Therefore, at the later stage of pyrolysis

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process, the temperature difference between different cases is not as large as the initial stage.

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Figure 12(b) indicates that CH4 mole fraction shows a slight decrease as the moisture increase

284

in Cases 1, 2, and 3, while H2 mole fraction shows an opposite trend due to more vapour 13 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

285

existing in the gas phase and favouring the reactions. However, Case 4 and Case 5 show

286

lower mole fraction of H2 and higher CH4 mole fraction compared to previous cases. That is,

287

more H2 and less CH4 are generated when the initial briquettes’ moisture content is increased

288

in the range of 2% to 15%, but then H2 decreased and CH4 increased in the range of 15% to

289

20%. This is because, the relative low bed temperature is obtained when briquette moisture

290

content is high, and thus the water-gas shift reaction rate is decreased.

291

Figure 12(c) compares the evolutions of volatile matter content remaining in the briquettes

292

for the briquettes beds with different initial moisture contents. In each case, VM mass

293

fraction shows a slight decrease in the beginning, due to the vapour condensation at the centre

294

bed. Then VM mass fraction increases dramatically as the moisture begins to release from the

295

briquettes bed until the dewatering process approach to complete. A stable stage occurs due

296

to the time gap between bed reaches evaporation temperature and devolatilization reaction

297

activated temperature. Therefore, before the start of devolatilization VM mass fraction keeps

298

constant for a while. On the other hand, these cases are compared. As higher moisture content

299

extends the dewatering time and therefore the beginning of devolatilization at the centre bed

300

is deferred when the briquettes with higher moisture is used. Moreover, the temperature is

301

increased after drying in all cases, where such increase in Case 1 is earlier than Case 5 by

302

over 2000s in the early stage, whereas the two cases reach the final temperature at the similar

303

time, within 1000s. Therefore, the temperature increases in Case 5, with a higher moisture

304

content, is faster and catches up in the later stage (see Figure 12(a)). This means that the

305

temperature is the critical factor to determine pyrolysis behaviour. Figure 12(d) indicates that

306

as the increase of moisture in the briquettes, at the beginning stage the outgoing mass flow

307

dramatically rises up due to the more vapour generated during the dewatering process. On the

308

other hand, the second peak emerges is deferred compared to other cases. This is due to the

309

relatively lower VM amount as well as the lower bed temperature. Even though higher 14 ACS Paragon Plus Environment

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Energy & Fuels

310

vapour generated in Case 5, the time difference between vapour and pyrolysis gases

311

generated also results in gas-water shift reaction doesn’t become the dominate homogeneous

312

reaction. Hence, the produced H2 does not show a significant increase when briquettes

313

moisture increases at the same time (see Figure 12(b)).

314

Effects of ellipsoidal briquette’s aspect ratio

315

In order to investigate the influence of ellipsoid shape on pyrolysis performance, in this

316

section, apart from the Case 1 (aspect ratio 1.7), four more aspect ratios are investigated and

317

compared. Four more packing density distribution results are obtained through the DEM

318

simulations based on these aspect ratios, as shown in Figure 13. Overall, because of the wall

319

effects, at the roof and bottom part, the packing density shows a little bit smaller that of other

320

parts. On the other hand, in comparison, it is indicated that the packing density is varied with

321

the aspect ratio. Specifically, the case with aspect ratio being 1.0 has the lowest packing

322

density distribution, while the highest value is obtained when the aspect ratio is 2.0. That is,

323

for the equivalent volume ellipsoidal briquettes, the packing density of charge is influenced

324

by the particle shape. The fitting curves of the packing density as a function of bed height are

325

obtained and then applied to the CFD model as initial conditions. In the CFD model, the

326

practical diameter of the briquettes is used to calculate the equivalent volume diameter. When

327

changing the aspect ratio, the equivalent diameter is fixed.

328

Figure 14 shows the effect of briquettes aspect ratio on bed temperature evolution, gas

329

products composition, the remaining VM content evolution and mass flow rate at the outlet,

330

respectively, by means of comparing between Cases 1 and 8-11. It is indicated in Figure 14(a)

331

that when other operation conditions are fixed, Case 1 with aspect ratio being 1.7 gives the

332

fastest heating rate after dewatering process than other cases, followed by Case 9, Case 11,

333

Case 8, Case 10. It can be found that the temperature difference between Case 1 and Case 10

334

is about 20K at a given time. It is indicated that the heating rate is not only determined by the 15 ACS Paragon Plus Environment

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

335

packing density but also determined by the heat exchange intensity that varies with the aspect

336

ratio. That is, the appropriate aspect ratio is beneficial to heat transfer as well as packing

337

process. In addition, the VM mass fraction evolution shows the same trend as temperature

338

varies (Figure 14(c)). However, the composition of generated gases does not show much

339

difference between these cases as aspect ratio changes. Moreover, Figure 14(d) indicates that

340

Case 1 has the smallest peak value of mass flow rate. This phenomenon indicates the

341

variation of aspect ratio has impacts on internal heat transfer and subsequent mass transfer.

342

Such difference will be more prominent if the gas heating is applied to the pyrolysis process.

343

They will be reported elsewhere.

344

Effects of different final pyrolysis temperature

345

In order to investigate impacts of final pyrolysis temperature on pyrolysis performance, three

346

cases with different final temperature are examined in Figure 15, namely Case 1 (973K),

347

Case 6 (873K), Case 7 (1073K), in terms of bed temperature history (a), gas products

348

composition (b), the remaining VM content evolution (c), mass flow rate at the outlet (d). It is

349

indicated that Case 6 with a lower final pyrolysis temperature shows a much slower VM

350

decrease compared to other cases. The VM decrease rate has a similar trend, which can be

351

found in Figure 15(c). In the comparison of gas products’ outflow rate, it can be found that

352

the Case 6 with 873K shows a significant difference with other cases, that is, the peak value

353

of mass flow rate of Case 7 is 2 times larger than Case 6. This means that higher final

354

pyrolysis temperature will enhance the devolatilization rate significantly. These results

355

indicate that the lower final pyrolysis temperature dramatically extends the time needed for

356

devolatilization reaction. It is important to note that the determination of final pyrolysis

357

temperature should consider the fact that the appropriate temperature can satisfy the demand

358

of pyrolysis completion with less time and energy consumption.


Page 16 of 45

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Energy & Fuels

359

6

360

An integrated DEM-CFD numerical model is developed to investigate the packing and

361

pyrolysis process of ellipsoidal LRC briquettes. The model is validated against the

362

experimental measurements in a pilot scale fixed bed reactor in terms of briquettes

363

temperature history and gas products distribution. The typical in-furnace phenomena are

364

described, including packing density distribution, flow field, temperature field and gas

365

species distributions. Then the effects of some key variables on pyrolysis behaviour are

366

investigated in terms of LRC briquettes’ initial moisture content, heating condition, and

367

ellipsoid’ aspect ratio. Under the current conditions, some optimal values are found for this

368

pyrolyzer.

369

The main conclusions from the present study are summarized as follows:

370

CONCLUSIONS

•

The packing density distribution of the ellipsoidal briquettes varies with the briquettes

371

aspect ratio and then affects the heat and mass transfers in the pyrolysis process. As

372

briquette’s initial moisture content is higher, the bed temperature increase and volatile

373

release are slowed down and dewatering process is prolonged. At the latter stage of

374

pyrolysis, cases with higher initial moisture content give faster bed temperature

375

increase rates. But excessive moisture in briquettes will lead to the relative low bed

376

temperature and cause the water-gas shift reaction rate decrease, generating less H2

377

and more CH4.

378

•

Maximum packing density is obtained when briquettes’ aspect ratio is 2.0. However,

379

the highest temperature increase rate is observed when the aspect ratio is 1.70. The

380

heat transfer between bed and gas is significantly influenced by packing structure and

381

briquette aspect ratio.


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

382

•

Excessive low temperature (873K) leads to a much slower devolatilization reaction

383

rate so as to dramatically extend the reaction time. But the higher temperature (1073K)

384

does not favour the devolatilization too much. Therefore, an appropriate final

385

temperature, 973K in this study, is identified for lowering energy consumption in

386

pyrolysis process.

387

This model provides a cost-effective tool for understanding and optimizing the pyrolysis of

388

LRC ellipsoidal briquettes in a packed bed pyrolyzer.

389

NOMENCLATURE

Av

specific surface area (m-1)

As

Surface area of the briquettes (m2)

C

mass concentration (kg m-3)

CP

specific heat of briquette (J kg-1K-1)

CF

specific heat of fixed carbon (J kg-1K-1)

CV

specific heat of volatile matter (J kg-1K-1)

CA

specific heat of ash (J kg-1K-1)

CMoi

specific heat of moisture (J kg-1K-1)

d

equivalent particle diameter (m)

D

diffusion coefficient (m2 s-1)

R

universal gas constant (J mol-1 K-1)

ur g

gravitational acceleration (m s-2)

h

specific enthalpy (J kg-1)

λ

thermal conductivity (Wm-1K-1)

Heva

evaporation heat of the solid material (J kg-1)


Page 18 of 45

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Energy & Fuels

Kc

equilibrium constant

k

heat-transfer coefficient (W m-2 K-1)

km

mass-transfer coefficient (m s-1)

kri

kinetics rate of heterogeneous reaction I (m s-1)

K

interphase momentum exchange coefficient (kg m-3 s-1)

•

m

mass-transfer rate (kg m-3 s-1)

Nu

Nusselt number

Mi

molar weight (kg kmol-1)

WV

volatile mass fraction of briquette

p

pressure (Pa)

q

heat flux (W m-2)

Q

intensity of heat exchange (W m-3)

ri

reaction rate (kmol m-3 s-1)

rmi

heterogeneous reaction rate (kmol m-3 s-1)

rki

kinetic rate of heterogeneous reaction i (m s-1)

R

universal gas constant (J mol-1 K-1)

S

source term

Sh

Sherwood number

Pr

Prandtl number

e

aspect ratio

t

time (s)

T

temperature(K)

r v

velocity (m/s)


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

CD

drag force coefficient

vi

stoichiometric coefficient of reactant i

Yi

mass fraction of the ith species

Pc

packing density

y

bed height (m)

Greek Symbols α

volume fraction

ρ

density (kg m-3)

µ

dynamic viscosity (Pa s)

φ

angle of internal friction

λ

thermal conductivity (W m-1 K-1)

τ

stress tensor (Pa)

Subscripts

C

fixed carbon

CO

carbon monoxide

CH4

methane

CO2

carbon dioxide

volatile

volatile matter

primary tar

primary tar

g

gas phase

ra d

radiation

H2

hydrogen

H2O

vapour


Page 20 of 45

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Energy & Fuels

Moi

moisture

s

solid phase

Vi

mass fraction of solid species

390

ACKNOWLEDGEMENTS

391

The authors wish to thank Australian Research Council (LP150100112) and Coal Energy

392

Australia for the financial support of this project. Sino Steel is acknowledged for providing

393

the experimental data used in the model validation.

394

REFERENCES

395

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396

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Kobayashi, H.; Howard, J. B.; Sarofim, A. F. Symposium (International) on Combustion 1977, 16 (1), 411–425.

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478 479 480 481 482 483 484


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

485 486

Figure 1. Schematic of the pilot-scale pyrolysis test system.

487


Page 26 of 45

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Energy & Fuels

488 489

Figure 2. Dimensions of the pyrolyzer chamber (unit: mm) and position of the monitor point

490

in the middle of the chamber (red dot).

491 492


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

493 494

Figure 3. Particle size of an ellipsoidal briquette.

495 496 497 498 499


Page 28 of 45

Page 29 of 45

0.60 Packing density Polynomial Fit of "Packing Density"

0.59

Packing density

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

0.58 0.57 0.56 0.55 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40

500 501

Bed height (m)

Figure 4. Packing density distribution of the ellipsoids packed bed in the pyrolyzer.

502 503 504 505 506 507 508 509


Energy & Fuels

Experimental data Predict data

1000 900

Temperature (K)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 30 of 45

800 700 600 500 400 300 0

2000

4000

6000

8000

10000 12000

Time (s)

510 511

Figure 5. Comparison of temperature history between simulation results and experiment

512

measurements.

513 514 515 516 517 518 519


Page 31 of 45

35

2.1 % moisture Experimental data

35.2 32 29.6 27.6

30

15

25 20

10

18.5 16.6

15.915.1

15

5

10 5

2.9

1.1 1.5

4

0

0 CH4

CO2

H2

NH3

1.9

CO

C2H6

Remaining VM mass fraction %

20

40

2.1 % moisture

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

0

VM

Experiment

520 521

Figure 6. Comparison of gas yields between simulation results and experiment measurements.

522 523 524 525 526 527 528 529 530


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(a)

(b)

Page 32 of 45

(c)

(d)

531 532

Figure 7. Temperature profiles of the briquettes (upper row) and gas phase (bottom row) at

533

selected time in the base case: (a) t=2500s; (b) t=5000s; (c) t=7500s; (d) t=10000s.

534 535 536 537 538


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Energy & Fuels

(a)

(b)

(c)

(d)

539 540

Figure 8. Evolution of briquettes’ remaining volatile matte, primary tar, and secondary tar in

541

the base case: (a) t=2500s; (b) t=5000s; (c) t=7500s; (d) t=10000s.

542


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 34 of 45

543 544

(a)

(b)

(c)

(d)

545

Figure 9. Evolution of gas flow field in the base case: (a) t=2500s; (b) t=5000s; (c) t=7500s;

546

(d) t=10000s.

547 548


Page 35 of 45

2.5x10

Mass flow rate (kg/s)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

-3

2.0x10-3 1.5x10-3 1.0x10-3 5.0x10-4

0.0 0

2500

5000

7500

10000

12500

15000

Time (s)

549 550

Figure 10. Mass flow rate versus time at the outlet in the base case.

551 552 553 554 555 556 557 558 559 560


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

561 562

Page 36 of 45

(a)

(b)

(c)

(d)

Figure 11. Profiles of some gas species at 7500s in the base case: (a), CH4; (b), CO2 ; (c), H2 and (d), H2O.

563 564 565


Page 37 of 45

1100

35

1000

30

900 800

Mole fraction (% )

Tem perature (k)

566

Case 1 Case 2 Case 3 Case 4 Case 5

700 600 500

CH4 CO2 H2 NH3 CO C2H6

25 20 15 10 5

400

0

300 0

2000 4000 6000 8000 10000 12000 14000

Case 1

Case 2

Case 3

Case 4

Case 5

Time (s)

(b)

(a)

3.0x10-3

0.30 0.25



0.35

VM m ass fraction

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

0.20 0.15 0.10


2.0x10-3

-3

1.0x10

0.05 0.00 0

2000 4000 6000 8000 10000 12000 14000

0.0

Time (s)

0

2000 4000 6000 8000 10000 12000 14000 Time (s)

(d)

(c) 567 568 569

Figure 12. Comparison of Cases 1-5 with different initial moisture contents of the briquettes, in terms of (a), temperature history, (b), gas products composition, (c), remaining volatile matter in briquettes, and (d), mass flow rate at the outlet.

570 571


Energy & Fuels

0.60 Case 1 Case 8 Case 9 Case 10 Case 11

0.59

Packing density

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 38 of 45

0.58 0.57 0.56 0.55 0.54 0.53 0.00

572 573

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

Bed height (m)

Figure 13. Packing density distribution for briquettes with different aspect ratio.

574 575 576 577


Page 39 of 45

1100

35

1000

30

900

Case Case Case Case Case

800 700 600

Mole fraction (%)

Temperature (K)

578

8 9 1 10 11

500


25 20 15 10 5

400 300

0 0

2000

4000

6000

Case 8 Case 9 Case 1 Case 10 Case 11 Cases with different aspect ratio

8000 10000 12000 14000

Time (s)

(a)

(b)

0.35

2.5x10

0.25 0.20

Mass flow rate (k g/s)

C ase 8 C ase 9 C ase 1 C ase 10 C ase 11

0.30

VM mass fraction

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Energy & Fuels

0.15 0.10

-3

Case Case Case Case Case

2.0x10-3

8 9 1 10 11

1.5x10-3 1.0x10-3 5.0x10-4

0.05 0.0

0.00 0

579 580 581

2000

4000

6000

0

8000 10000 12000 14000

2000 4000 6000 8000 10000 12000 14000

Time (s)

Tim e (s)

(c)

(d)

Figure 14. Comparison of Cases 1, 8-11 with different briquette aspect ratio, in terms of (a), temperature history, (b), gas products composition, (c), remaining volatile matter in briquettes, and (d), mass flow rate at the outlet.

582


Energy & Fuels

1100

35

1000

30

900

Mole fraction (%)

Temperature (k)

583

800 700

Case 6 Case 1 Case 7

600 500


25 20 15 10 5

400

0

300 0

2000

4000

6000

Case 6

8000 10000 12000 14000

Case 1

Case 7

Time (s)

(b)

(a)

0.35

3.0x10-3


0.30


Mass fraction of VM

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 40 of 45

0.25 0.20 0.15 0.10

2.5x10


-3

2.0x10-3

1.5x10

-3

1.0x10-3 5.0x10-4

0.05 0.00

0.0

0

2000 4000 6000 8000 10000 12000 14000

0

Time (s)

4000

6000

8000

10000

12000

14000

Time (s)

(c)

584 585 586

2000

(d)

Figure 15. Comparison of Cases 1, 6, 7 with different final pyrolysis temperature, in terms of (a), temperature history, (b), gas products composition, (c), remaining volatile matter in briquettes, and (d), mass flow rate at the outlet.

587 588 589


Page 41 of 45 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

590

Energy & Fuels

Table 1. Properties of the briquette investigated. Proximate Analysis (on a Dry Basis, except Moisture)

Moisture (%)

2.1

Fixed carbon (%)

61.2

Volatile (%)

32.7

Ash (%)

6.1 Ultimate Analysis (on a Dry basis)

Carbon (%)

81.1

Hydrogen (%)

4.7

Oxygen (%)

7.2

Nitrogen (%)

0.7

Sulphur (%)

0.2

591 592 593 594


Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

595

Page 42 of 45

Table 2. Governing equations of gas-solid flows in the CFD model. Gas phase: r ∂ (α g ρ g Yi ) + ∇ (α g ρ g Yi v g ) = m& i + Si ∂t

(1)

r r r ur r r r ∂ (α g ρ g v g ) + ∇ (α g ρ g v g v g ) = −α g ∇p + ∇τ g + α g ρ g g + K sg (v s − v g ) − m& sg v sg ∂t

(2)

r r r ∂ ∂p (α g ρ g hg ) + ∇ (α g ρ g v g hg ) = −α g + τ g : ∇ v g − ∇ q g + S g + Qsg + m& sg hsg ∂t ∂t

(3)

Solid phase: r ∂ (α s ρ sY j ) + ∇ (α s ρ sY j v s ) = m& j + S j ∂t

(4)

r r r ur r ∂ (α s ρ s v s ) + ∇ (α s ρ s v s v s ) = −α s ∇ p − ∇ps + ∇τ s + α s ρ s g − m& sg v sg ∂t

(5)

r r r ∂ ∂p (α s ρ s hs ) + ∇ (α s ρ s v s hs ) = −α s + τ s : ∇ v s − ∇ q s + S s + Qgs − m& sg hsg ∂t ∂t

(6)

596 597 598 599 600 601 602 603


Page 43 of 45 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

604

Energy & Fuels

Table 3. Reactions considered in this CFD model and their reaction kinetics.

Reaction

Reaction rate expression and kinetics

Coal → αPrimary tar +

r1 = 3.2 × 10 5 (1 − α g ) exp(

Reference 48,49

− 1.6 × 10 4 ) ρ volatile Ts

βGas + γChar T1=

2 6 7 .4 + 2 7 3 .1 5 W v 0 .25 5 5 50

Primary tar → Secondary tar + gas

r2 = 9.55 × 10 4 α g exp(

r3 = α g 0.03exp( r3 CO + H 2 O ← → CO 2 + H 2

4 C H 4 + H 2 O  r → CO + 3 H 2

1.12 × 10 4 ) ρ prim ary tar Tg

−6.03 × 10 4 CCO C H 2O ) − RTg M CO M H 2O

α 0.03exp( g

Kc

51,52

M CO2 M H 2

 1 91500  (11321 − 31.08Tg + 3Tg ln Tg 2.8 ×10−4 Tg 2 − ) Kc = exp  Tg   RTg

r4 = 3.0 × 108 × α gTg exp( −15083 / T g )CCH 4 C H 2O

km =

53

54

 1  Avρ i rmi =    v iM i  1 + 1 k m rki m1 C + H 2 O  r → CO + H 2

−6.03 × 10 4 ) CCO 2 C H 2 RTg

ShD ds

rk1 = 5.714T s exp( − 15600 / T s ) m2 C + CO 2  r→ 2CO

rk2 = 5.89 × 10 2 Ts exp( −26800 / Ts )

605 606 607


55

Energy & Fuels 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

608

Page 44 of 45

Table 4. Boundary and operating conditions used in this model. Property

value

Thermal conductivity of

if Ts ≤ 673 λ = 0.23  −5 1.8 λ = 0.23 + 2.24 × 10 × (Ts − 673) if Ts > 673

briquettes

 C P = V1 C F + V 2 C V + V 3 C A + V 4 C M o i  2 −3 −6  C F = − 0.281 + 3.8 07 × 1 0 T s − 1.758 × 1 0 T s  −3  C V = 0.728 + 3.39 1 × 10 T s  −4  C A = 0.594 + 5.8 6 × 10 T s 3 C  M oi = 4.2 × 10

Specific heat of briquettes

Mass weighted

ds = 3.5cm

Equal volume briquette diameter

Wall temperature scheme 1



Twall = 873.15  Twall = 873.15 − 0.055 × ( t − 1800 )  Twall = 773.15 + 0.055 × (t − 3600) Twall = 873 

if t < 1800s

if 1800s ≤ t ≤ 3600s if 3600s

Numerical Study of the Pyrolysis of Ellipsoidal Low-Rank Coal

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