Computational Mathematics (CM)http://hdl.handle.net/20.500.11824/52024-02-28T18:28:58Z2024-02-28T18:28:58ZExploring the link between coffee matrix microstructure and flow properties using combined X‐ray microtomography and smoothed particle hydrodynamics simulationsSuggi Liverani, FMo, C.Johnston, R.Navarini, L.Ellero, M.http://hdl.handle.net/20.500.11824/17802024-02-27T23:20:00Z2022-09-29T00:00:00ZExploring the link between coffee matrix microstructure and flow properties using combined X‐ray microtomography and smoothed particle hydrodynamics simulations
Suggi Liverani, F; Mo, C.; Johnston, R.; Navarini, L.; Ellero, M.
Coffee extraction involves many complex physical and transport processes extremely difficult to model. Among the many factors that will affect the final quality of coffee, the microstructure of the coffee matrix is one of the most critical ones. In this article, we use X-ray micro-computed (microCT) technique to capture the microscopic details of coffee matrices at particle-level and perform fluid dynamics simulation based on the smoothed particle hydrodynamics method (SPH) with the 3D reconstructured data. Information like flow permeability and tortuosity of the matrices can be therefore obtained from our simulation. We found that inertial effects can be quite significant at the normal pressure gradient conditions typical for espresso brewing, and can provide an explanation for the inconsistency of permeability measurements seen in the literature. Several types of coffee powder are further examined, revealing their distinct microscopic details and resulting flow features. By comparing the microCT images of pre- and post-extraction coffee matrices, it is found that a decreasing porosity profile (from the bottom-outlet to the top-inlet) always develops after extraction. This counterintuitive phenomenon can be explained using a pressure-dependent erosion model proposed in our prior work. Our results reveal not only some important hydrodynamic mechanisms of coffee extraction, but also show that microCT scan can provide useful microscopic details for coffee extraction modelling. MicroCT scan establishes the basis for a data-driven numerical framework to explore the link between coffee powder microstructure and extraction dynamics, which is the prerequisite to study the time evolution of both volatile and non-volatile organic compounds and then the flavour profile of coffee brews.
2022-09-29T00:00:00ZShape Optimization for Temperature Regulation in Extrusion Dies Using MicrostructuresZwar, J.Elber, G.Elgeti, S.http://hdl.handle.net/20.500.11824/17732024-02-22T23:19:53Z2023-01-01T00:00:00ZShape Optimization for Temperature Regulation in Extrusion Dies Using Microstructures
Zwar, J.; Elber, G.; Elgeti, S.
Plastic profile extrusion—a manufacturing process for continuous profiles with fixed cross section—requires a complex and iterative design process to prevent deformations and residual stresses in the final product. The central task is to ensure a uniform material velocity at the outlet. To this end, not only the geometry of the flow decisively influences the quality of the outflow but also the temperature profile along the flow channel wall. It is exactly here that this work contributes by presenting a novel design approach for extrusion dies that will allow for optimal temperature profiles. The core of this approach is the composition of the extrusion die through microstructures. The optimal shape and distribution of these microstructures is determined via shape optimization. The corresponding optimization procedure is the main topic of this article. Special emphasis is placed on the definition of a suitable, low-dimensional shape parameterization. The proposed design-framework is then applied to two numerical test cases with varying complexity.
2023-01-01T00:00:00ZMONITORING MOORING (MONIMOOR) LINES OF FLOATING STRUCTURES USING DEEP LEARNING-BASED APPROACHESSharma, S.Nava, V.Gorostidi, N.http://hdl.handle.net/20.500.11824/17702024-02-20T23:20:25Z2023-01-01T00:00:00ZMONITORING MOORING (MONIMOOR) LINES OF FLOATING STRUCTURES USING DEEP LEARNING-BASED APPROACHES
Sharma, S.; Nava, V.; Gorostidi, N.
2023-01-01T00:00:00ZEfficient Minimum Distance Computation for Solids of RevolutionElber, G.Kim, M.Yoon, S.Son, S.http://hdl.handle.net/20.500.11824/17612024-02-20T23:20:19Z2020-01-01T00:00:00ZEfficient Minimum Distance Computation for Solids of Revolution
Elber, G.; Kim, M.; Yoon, S.; Son, S.
We present a highly efficient algorithm for computing the minimum distance between two solids of revolution, each of which is
defined by a planar cross-section region and a rotation axis. The boundary profile curve for the cross-section is first approx-
imated by a bounding volume hierarchy (BVH) of fat arcs. By rotating the fat arcs around the axis, we generate the BVH of
fat tori that bounds the surface of revolution. The minimum distance between two solids of revolution is then computed very
efficiently using the distance between fat tori, which can be boiled down to the minimum distance computation for circles in the
three-dimensional space. Our circle-based approach to the solids of revolution has distinctive features of geometric simplifica-
tion. The main advantage is in the effectiveness of our approach in handling the complex cases where the minimum distance is
obtained in non-convex regions of the solids under consideration. Though we are dealing with a geometric problem for solids,
the algorithm actually works in a computational style similar to that of handling planar curves. Compared with conventional
BVH-based methods, our algorithm demonstrates outperformance in computing speed, often 10–100 times faster. Moreover,
the minimum distance can be computed very efficiently for the solids of revolution under deformation, where the dynamic
reconstruction of fat arcs dominates the overall computation time and takes a few milliseconds.
2020-01-01T00:00:00Z