Modeling Biomass Piles
for Pile Management
Wasim Faizal, E.I.T., M.Eng
Team

Dr. Suzanne Wetzel, NRCan, Canadian Wood
Fibre Center

Prof. Sally Krigstin, UofT, Department of Forestry

Janet Damianopoulos, NRCan

Wasim Faizal, NRCan
What is pile management?
Nobody Really Knows
Why Do We Need It?

Build up of heat within a pile
 Can
lead to localized fires

Want to understand how much CO2 a pile releases

Want to know if better storage practices can
improve quality of feed
Picture Reference: https://imgflip.com/memegenerator/Boardroom-Meeting-Suggestion
-30 C
Current Practices

Turning the piles to dissipate heat at fixed periods

Random temperature measurements

Managing pile geometry

Compost Piles: controlling oxygen levels
Why does a pile heat up?
Factors Influencing Heat build up

Biological - bacteria/living woody tissue

Chemical - oxidation reactions

Physical - evaporation / condensation of water
Can we predict temperature rise within a
pile?


Why?
 To
understand when a new pile might get too hot
 To
know when to release heat
How?
 Requires
knowledge of specific wood properties
 Requires
mathematical models
Application Heat and Mass Transfer
concepts

Mass Build up = Mass Flow in – Mass Flow out +/Reaction

Heat Build up = Heat Flow in – Heat Flow out +/Reaction

Dispersion of mass through diffusion (Fick’s Law)

Dispersion of heat through conduction (Fourier
Law of Heat Conduction)
Reactor Analogy
Mass in
Heat in
Mass
out
Heat out
Modeling Biological Growth

Biological growth = Bacteria in – Bacteria out + Rate of Growth
 𝑟𝑥
=
𝑀𝐵
𝜇𝑚
𝐾𝑏 +𝑀𝐵
𝑋 − 𝑏𝑋
𝑘𝑔
( 3)
𝑚

𝜇𝑚 -growth factor

𝑏 − 𝑑𝑒𝑎𝑡ℎ 𝑓𝑎𝑐𝑡𝑜𝑟

𝑀𝐵 − 𝑤𝑜𝑜𝑑𝑦 𝑏𝑖𝑜𝑚𝑎𝑠𝑠 𝑐𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛 (sugars)

𝐾𝑏 − 𝑏𝑖𝑜𝑚𝑎𝑠𝑠 𝑠𝑎𝑡𝑢𝑟𝑎𝑡𝑖𝑜𝑛 𝑐𝑜𝑛𝑠𝑡𝑎𝑛𝑡

𝑋-bacterial concentration
Equation Reference: F. Ferrero et al. Journal of Loss Prevention in the Process Industries 22 (2009) 439-448
Modeling Oxygen Consumption
 𝐶6 𝐻12 𝑂6

+ 6𝑂2 → 6𝐶𝑂2 + 6𝐻2 𝑂 −− −Δ𝐻𝑐.𝑟.
Heat released per mole of oxygen consumed
𝑞𝑂2 = (Δ𝐻𝑐.𝑟. /6)(1-efficiency)
Equation Reference: F. Ferrero et al. Journal of Loss Prevention in the Process Industries 22 (2009) 439-448
Modeling Oxygen Consumption (cont.)
1−𝑌
𝑀𝐵
𝜇𝑚
𝑌
𝐾𝑏 +𝑀𝐵

−𝑟𝑂2 =

Oxygen consumption is used to predict heat
released by bacteria.

𝑄 = (𝑟𝑂2 )𝑞𝑂2 (
𝑊
𝑚3
𝑋 − 𝑏(1 − 𝑓)𝑋
)
 𝑞𝑂2 -
oxycalorific coefficient (heat released per
molecule of oxygen consumed)
Equation Reference: F. Ferrero et al. Journal of Loss Prevention in the Process Industries 22 (2009) 439-448
Why use Oxygen consumption to
estimate heat?
Modeling Other Heat Sources

Model the decomposition of wood as a first order
chemical reaction

Use the rate of decomposition with the enthalpy of
decomposition to determine heat released
Temperature Modeling
𝑑𝑇
 𝜌𝐶𝑝
𝑑𝑡
= 𝐻𝑒𝑎𝑡 𝐺𝑒𝑛𝑒𝑟𝑎𝑡𝑒𝑑
Modeling

Impossible to solve analytically

Multi-dimensional problem

Use COMSOL or MATLAB to determine a
numerical solution set
Current Results
Model Improvement

Add growth limiting factors for bacteria
 Moisture
content
 Temperature
 Oxygen
limits
content
Collaboration to Monitor Data

Data Expertise:

NRCan

UofT

Equipment Expertise:

Braingrid
Monitoring Temperatures

Previous temperature monitoring failed
 Temperature

loggers caught fire
Braingrid provides a wireless sensor monitoring
tool
 Monitor
 Data
and log data to a remote server
is accessible from any location
Sentroller

The Sentroller acts as a data hub.

It is capable of capturing
information from any sensor

Relays that information to a remote
location off-site
Goals

Determine accuracy of the model (other data sets)

Work being conducted at PAMI to prepare new
biomass piles

Use model to determine best practices for various
biomass types

Develop a CSA standard for managing a pile
Summary

It is possible to model biomass conditions

Currently working on improving and verifying the
model

Enables us to determine practices to increase
efficiency and reduce cost
Questions?