The effect of particle size distribution on the bulk thermal conductivity of biomass pellets

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Delft University of Technology

Gilvari, Hamid; Eijssen, Dirk; IJzermans, Kasper; Stolk, Maarten; Homsma, Thom; de Jong, Wiebren; Schott, Dingena

Publication date 2018

Document Version Final published version

Citation (APA)

Gilvari, H., Eijssen, D., IJzermans, K., Stolk, M., Homsma, T., de Jong, W., & Schott, D. (2018). The effect of particle size distribution on the bulk thermal conductivity of biomass pellets. Poster session presented at TU Delft Process Technology Institute (DPTI) annual meeting 2018, Rotterdam, Netherlands.

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The effect of particle size distribution on the bulk thermal conductivity

of biomass pellets

H. Gilvari *

a

, D.J. Eijssen

b

, K.F. Ijzermans

b

, M.J. Stolk

b

, T.A. Homsma

b

, W. de Jong

c

, D. L. Schott

a

a_{Section of Transport Engineering & Logistics, Department of Maritime & Transport Technology, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology}

b _{Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology}

c_{Section of Large Scale Energy Storage, Department of Process & Energy, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology}

Table 1. Definition of the terms used in the calculations

Objective

 The thermal conductivity highly depends on the bulk density, however, it does not show a high correlation with the mean particle length  Increasing the particle size distribution does not necessarily lead to higher bulk densities

Conclusions

This work was carried out as a part of the BioForce project co-financed by KIC InnoEnergy (Project Agreement Ref 24_2014_IP102_Bioforce).

Acknowledgment

*Corresponding author: Hamid Gilvari Email: H.Gilvari@tudelft.nl

The large-scale storage of biomass pellets is challenging due to health issues, material loss, and the risk of fire and explosions. The thermal conductivity is a material property which plays a key role in determining the self-heating properties of biomass.

Meanwhile, understanding the thermal conductivity and the affecting factors help to better understand and

reduce the risk of self-heating and fire explosions.

Introduction

The thermal conductivity was measured based on:

𝑘𝑘_𝑠𝑠 = _𝐴𝐴𝐿𝐿𝑆𝑆𝑄𝑄𝑠𝑠 𝑐𝑐𝑠𝑠∆𝑇𝑇𝑠𝑠 Where ∆𝑇𝑇_𝑠𝑠= 𝑇𝑇₂ − _𝐴𝐴𝐿𝐿𝑜𝑜𝑄𝑄1 𝑐𝑐𝑐𝑐𝑘𝑘𝑎𝑎𝑎𝑎 − (𝑇𝑇3 + 𝐿𝐿_𝑜𝑜𝑄𝑄₂ 𝐴𝐴_{𝑐𝑐𝑐𝑐}𝑘𝑘_{𝑎𝑎𝑎𝑎}), and 𝑄𝑄𝑠𝑠 = 𝑄𝑄₁+𝑄𝑄₂ 2 𝑄𝑄₁ = 𝑘𝑘𝑎𝑎𝑎𝑎𝐴𝐴𝑐𝑐𝑠𝑠_𝐿𝐿(𝑇𝑇1 − 𝑇𝑇2) 𝑡𝑡𝑐𝑐 − 2𝜋𝜋𝑘𝑘_{𝑖𝑖𝑖𝑖𝑠𝑠}𝐿𝐿_{𝑡𝑡𝑐𝑐}((𝑇𝑇1 + 𝑇𝑇₂ 2) − 𝑇𝑇_{𝑎𝑎𝑎𝑎𝑎𝑎}) ln(𝑟𝑟_𝑟𝑟2 1) 𝑄𝑄₂ = 𝑘𝑘𝑎𝑎𝑎𝑎𝐴𝐴𝑐𝑐𝑠𝑠_𝐿𝐿(𝑇𝑇3 − 𝑇𝑇4) 𝑡𝑡𝑐𝑐 − 2𝜋𝜋𝑘𝑘_{𝑖𝑖𝑖𝑖𝑠𝑠}𝐿𝐿_{𝑡𝑡𝑐𝑐}((𝑇𝑇3 + 𝑇𝑇₂ 4) − 𝑇𝑇_{𝑎𝑎𝑎𝑎𝑎𝑎}) ln(𝑟𝑟_𝑟𝑟2 1)

Calculations

Figure 2. Setup configuration

Biomass pellets with 6 mm diameter made of sawdust were

used in this study. Ten batches of pellets with different particle size distributions were selected for the experiments as shown in

figure 1.

Material and Methods

The measurements were conducted based on the steady state split-bar method (SSM) according to the standard method of measuring the thermal conductivity of polymers (figure 2). To verify the measurement of the custom-build apparatus, the thermal conductivity of 6 batches of the sample were also measured using the transient plane source method (TPS)

Term Definition

𝑘𝑘_𝑠𝑠 Thermal conductivity of the sample 𝐿𝐿_𝑆𝑆 Sample thickness (m)

𝐿𝐿_𝑜𝑜 Thermocouples distance from the sample surface (0.005 m) 𝐿𝐿_{𝑡𝑡𝑐𝑐} Distance between the thermocouples (0.135 m)

𝐴𝐴_{𝑐𝑐𝑠𝑠} Contact area of the aluminium rod with the sample (0.0044 m2) 𝑘𝑘_{𝑎𝑎𝑎𝑎} Thermal conductivity of aluminium (188 W/mK)

𝑘𝑘_{𝑖𝑖𝑖𝑖𝑠𝑠} Thermal conductivity of the insulation (0.03 W/mK) 𝑟𝑟₁ Inner radius of the insulation ring (0.0375 m)

𝑟𝑟₂ Outer radius of the insulation ring (0.059 m) 𝑇𝑇₁, 𝑇𝑇₂, 𝑇𝑇₃, 𝑇𝑇₄ Recorded temperatures by thermocouples

𝑇𝑇_{𝑎𝑎𝑎𝑎𝑎𝑎} Ambient temperature Particle length (mm) C um ul at ive par ti cl e si ze ( % )

Figure 1. Particle size distribution of different batches of the pellets

400 450 500 550 600 650 700 750 800 0,09 0,1 0,11 0,12 0,13 0,14 0,15 0,16 0 5 10 15 20 25 B ul k D en s it y ( k g /m 3 ) T he rm al C o n du c ti v it y ( W /m K )

Mean particle length (mm)

Thermal Conductivity Bulk Density 0,08 0,09 0,1 0,11 0,12 0,13 0,14 0,15 0,16 0,17 0,18 0 5 10 15 20 25 T he rm al C o n du c ti v it y ( W /m K )

Mean particle length (mm) SSM Method TPS method Correlation Coefficient=0,938 R² = 0,9222 0,08 0,09 0,1 0,11 0,12 0,13 0,14 0,15 0,16 500 550 600 650 700 750 T he rm al C o n du c ti v it y ( W /m K ) Bulk Density (kg/m3)

Results

Thermal conductivity vs pellet mean length

and bulk density SSM method vs TPS method

Thermal conductivity vs pellet mean length _{Thermal conductivity vs bulk density}

R² = 0,83 0,08 0,09 0,1 0,11 0,12 0,13 0,14 0,15 0,16 0 5 10 15 20 25 T he rm al C o n du c ti v it y ( W /m K )

Mean particle length (mm)

The objectives are (1) to characterise the thermal conductivity of batches of bulk biomass pellets with different particle size

distributions and (2), to determine the correlations between the

b bulk thermal conductivity and the mean particle length of

t the pellets.

Variac 230 V Power supply

TC- 1 TC- 2 TC- 3 TC- 4 XPS insulation Heating element 70W Cardboard box Aluminum reference bar Ø 75 mm Sample, Ø 75 mm PVC outer shell Water inlet Watercooled bath Water outlet

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