A data driven approach to process & product simulations of coffee roasting

Al-Shemmeri, Mark ORCID: 0000-0002-9787-8201 (2024). A data driven approach to process & product simulations of coffee roasting. University of Birmingham. Eng.D.

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Abstract

Coffee roasting is an intersection of engineering, physics, chemistry, sensory, discipline and creativity. To truly master the artistry, the fundamentals must be learned. This thesis provides an engineer's perspective of the art of roasting, whereby the architecture of a data-driven approach to simulations of heat and mass transfer is presented, with the intention of developing a coffee roaster's digital twin.

Process equipment and applied roasting conditions were appropriately characterised to convert arbitrary set-points to values that enable cross-comparison of roasters and their viable process conditions. The effect of thermocouple diameter on temperature measurement was defined both from a first-principles approach and a convenient, rapid analysis of the thermocouple's response time, demonstrating that the thermocouple response coefficient can be coupled with the later described heat transfer simulations to predict the bean's actual temperature and further support cross-comparison of process conditions across roaster design and scale.

Measurement techniques that characterise coffee's relevant physicochemical properties were developed in the context of heat and mass transfer. These measurements facilitate quantification of coffee's transformation during roasting, thus revealing the effect of process conditions on coffee's physicochemical development. The effect of different constant inlet air temperatures, as well as different batch sizes and airflows on a Kenyan Arabica coffee was captured, with a focus on the novel use of x-ray Micro-Computed Tomography (MicroCT) to enumerate coffee's porous development during roasting. The effect of thermocouple diameter on in-situ measurement of coffee's temperature response was analysed experimentally and aligned with the first-principles approach.

Studies of particle motion in different roasters was mapped using Positron Emission Particle Tracking (PEPT) and revealed the impact of process parameters and product properties on the system's particle dynamics. In both the spouted bed and rotating drum roasters, the emergence of two distinct regions of occupancy and velocity was found. These regional differences in particle motion have a profound effect on the heat transfer rates and so extracted velocities and residence times were used to instruct dynamic boundary conditions in the later described heat and mass transfer simulations.

The physicochemical development of coffee during roasting was modelled using a chemical reaction analogy. In this way, the complex confluence of physics and chemistry was lumped into simplified Arrhenius-type kinetics. The evolution of mass, moisture, density, volume and porosity were effectively modelled using n\(^{th}\) order reaction kinetics, with the models of mass and moisture used as subroutines in the later described simulations of heat and mass transfer.

A batch-scale, zero-dimensional simulation of heat and mass transfer in a spouted bed roaster was formulated via energy balance. The simulation was rigorously calibrated using empirically derived process and product data, kinetic models of mass and moisture and a global heat transfer coefficient. A bean-scale, three-dimensional simulation of heat and mass transfer in a spouted bed roaster was also formulated via energy balance. In addition to being calibrated with empirically derived process and product data, the coffee's real particle motion (velocity and residence time) was used to estimate the regional heat transfer coefficients and instructed the time-step of the simulation. Both the batch-scale and bean-scale simulations of coffee roasting time-temperature profiles and corresponding physicochemical were effective and enable the development of a digital model of a coffee roaster with real-system accuracy.

Type of Work:

Thesis (Doctorates > Eng.D.)

Award Type:

Doctorates > Eng.D.

Supervisor(s):