By Dr. Aminu Owonikoko, PhD
Overview
This thesis investigates a deceptively simple but industrially important question: what happens to biomass materials when they are compressed and then allowed to relax? Biomass — such as woodchips, wheat straw, leafy residues, cotton seeds, and wood pellets — is a major renewable resource used for energy production and sustainable manufacturing. However, its physical behaviour during handling, storage, and processing is poorly understood. Unlike uniform materials such as sand or grain, biomass is irregular, springy, and unpredictable. This unpredictability leads to blockages, equipment failures, and inefficient energy use in biomass processing plants.
The research provides a scientific foundation for predicting how biomass behaves under pressure by combining controlled experiments with Visco elastic modelling. The work introduces a new method for extracting key model parameters, enabling more accurate and transparent predictions of biomass relaxation behaviour.
Why Biomass Behaviour Matters
Biomass supply chains involve several mechanical steps: compaction, transport, storage, and feeding into processing equipment. During these steps, biomass is often compressed. Once the pressure is removed, the material “relaxes” — it expands, shifts, and redistributes internal stresses. This relaxation affects:
• how much biomass can be stored
• how reliably it flows through hoppers and conveyors
• how much energy is required to process it
• the likelihood of blockages or equipment downtime
Understanding this behaviour is essential for designing efficient, reliable, and cost effective biomass systems.
Research Aim
The central aim of the thesis is to characterise the stress relaxation behaviour of five biomass feedstocks and to develop robust Visco elastic models that can predict this behaviour under different loading conditions.
Experimental Approach
Five biomass materials were selected due to their relevance in renewable energy and agricultural supply chains:
• Fuzzy cotton seeds
• Leafy biomass
• Wheat straw
• Woodchips
• Wood pellets
Each material was compressed using a Shimadzu MTS testing machine. After reaching a target stress level, the load was held constant while the material’s stress decay was recorded over time (typically 60, 120, and 180 seconds). These measurements captured both fast relaxation (immediate stress drop) and slow relaxation (longer term settling).
The experimental data revealed that each biomass type behaves differently, reflecting differences in structure, moisture content, particle shape, and internal bonding.
Modelling Approach
To interpret the experimental results, the thesis applies Visco elastic models — mathematical tools traditionally used to describe materials that behave partly like solids and partly like fluids. Two models were central:
1. Zener Model
– Captures both elastic and viscous behaviour
– Useful for materials with a clear fast relaxation component
2. Two Maxwell Elements Model
– Represents two relaxation processes simultaneously
– Ideal for materials with both fast and slow relaxation phases
A key contribution of the thesis is the development of a numerical and graphical method for estimating model parameters (such as relaxation time constants) without relying heavily on curve fitting software like MATLAB or OriginPro. This method improves transparency, reduces error, and makes the modelling approach more accessible to engineers.
Key Findings
1. Biomass Has Distinct Relaxation “Signatures”
Each biomass type exhibits a unique pattern of stress decay. For example:
• Wood pellets relax quickly and predictably.
• Leafy biomass relaxes slowly and irregularly.
• Wheat straw shows intermediate behaviour.
These signatures can be used to classify materials and predict their handling performance.
2. Fast and Slow Relaxation Are Mechanically Meaningful
The two Maxwell elements model successfully separates fast and slow relaxation processes. This distinction helps engineers understand how biomass responds immediately after compression versus how it settles over time.
3. New Parameter Extraction Method Improves Accuracy
The thesis introduces a novel approach for estimating relaxation time constants and stress components. This reduces dependence on automated curve fitting tools and provides more reliable model predictions.
4. Models Predict Real Behaviour Well
When applied to experimental data, both the Zener and two Maxwell models accurately reproduce the relaxation curves. This confirms that Visco elastic modelling is a powerful tool for biomass characterisation.
Practical Implications
The findings have direct relevance for industries that handle biomass:
• Improved equipment design: Better predictions of relaxation behaviour reduce blockages and mechanical failures.
• Optimised storage: Understanding how biomass settles helps determine safe and efficient storage densities.
• Reduced energy use: More predictable flow reduces the energy required for conveying and processing.
• Enhanced process reliability: Plants can operate more consistently with fewer interruptions.
Conclusion
This thesis provides a comprehensive experimental and theoretical framework for understanding biomass relaxation behaviour. By combining detailed measurements with improved Visco elastic modelling, it offers new insights into how biomass responds under pressure — insights that are essential for scaling up renewable energy and sustainable manufacturing.
The work advances both scientific understanding and practical engineering, contributing to the development of cleaner, more efficient biomass systems.
