Computational Mathematics (CM)http://hdl.handle.net/20.500.11824/52019-06-08T06:20:47Z2019-06-08T06:20:47ZMesoscopic modelling and simulation of espresso coffee extractionEllero M.Navarini L.http://hdl.handle.net/20.500.11824/9812019-06-07T01:00:10Z2019-01-01T00:00:00ZMesoscopic modelling and simulation of espresso coffee extraction
Ellero M.; Navarini L.
A mesoscopic model for the simulation of espresso extraction based on the Smoothed Particle Hydrodynamics method is presented. The model incorporates some essential features such as bimodal granulometry (fines-coarses) of the coffee bed, double (liquid/intra-granular) molecular diffusion and solid-liquid release mechanism. The porous structures ('coarses') are modelled as stationary solid regions whereas the migration of cellular fragments ('fines') is described by single-particles advected by the flow. The boundary filter is modelled as a buffer region where fines are immobilized while entering it, therefore providing a transient flow impedance. The model captures well the transient permeability of the coffee bed under direct-inverse discharge observed in experiments, showing the importance of fines migration on the hydrodynamics of the extraction. The concentration kinetics for different molecular compounds (i.e caffeine, trigonelline and chlorogenic acid) are compared to experimental data for a traditional espresso extraction, showing excellent results. The present work lays down the basis for the virtual analysis of coffee flavors by monitoring the hydrodynamic and microstructural effects on the balance of extracted key-odorant or taste-actives compounds in the beverage.
2019-01-01T00:00:00ZReducing variability in the cost of energy of ocean energy arraysTopper M.B.RNava V.Collin A. J.Bould D.Ferri F.Olson S. S.Dallmann A. R.Roberts J. D.Ruiz-Minguela P.Jeffrey H. F.http://hdl.handle.net/20.500.11824/9802019-06-04T01:00:11Z2019-09-01T00:00:00ZReducing variability in the cost of energy of ocean energy arrays
Topper M.B.R; Nava V.; Collin A. J.; Bould D.; Ferri F.; Olson S. S.; Dallmann A. R.; Roberts J. D.; Ruiz-Minguela P.; Jeffrey H. F.
Variability in the predicted cost of energy of an ocean energy converter array is more substantial than for other forms of energy generation, due to the combined stochastic action of weather conditions and failures. If the variability is great enough, then this may influence future financial decisions. This paper provides the unique contribution of quantifying variability in the predicted cost of energy and introduces a framework for investigating reduction of variability through investment in components. Following review of existing methodologies for parametric analysis of ocean energy array design, the development of the DTOcean software tool is presented. DTOcean can quantify variability by simulating the design, deployment and operation of arrays with higher complexity than previous models, designing sub-systems at component level. A case study of a theoretical floating wave energy converter array is used to demonstrate that the variability in levelised cost of energy (LCOE) can be greatest for the smallest arrays and that investment in improved component reliability can reduce both the variability and most likely value of LCOE. A hypothetical study of improved electrical cables and connectors shows reductions in LCOE up to 2.51% and reductions in the variability of LCOE of over 50%; these minima occur for different combinations of components.
2019-09-01T00:00:00ZForward-in-Time Goal-Oriented AdaptivityMuñoz-Matute J.Pardo D.Calo V.M.Alberdi E.http://hdl.handle.net/20.500.11824/9742019-05-03T01:00:10Z2019-03-01T00:00:00ZForward-in-Time Goal-Oriented Adaptivity
Muñoz-Matute J.; Pardo D.; Calo V.M.; Alberdi E.
In goal-oriented adaptive algorithms for partial differential equations, we adapt the finite element mesh in order to reduce the error of the solution in some quantity of interest. In time-dependent problems, this adaptive algorithm involves solving a dual problem that runs backward in time. This process is, in general, computationally expensive in terms of memory storage. In this work, we define a pseudo-dual problem that runs forward in time. We also describe a forward-in-time adaptive algorithm that works for some specific problems. Although it is not possible to define a general dual problem running forwards in time that provides information about future states, we provide numerical evidence via one-dimensional problems in space to illustrate the efficiency of our algorithm as well as its limitations. Finally, we propose a hybrid algorithm that employs the classical backward-in-time dual problem once and then performs the adaptive process forwards in time.
2019-03-01T00:00:00ZAccessibility for Line-Cutting in Freeform Surfacesvan Sosin B.Bartoň M.Elber G.http://hdl.handle.net/20.500.11824/9682019-04-27T01:00:10Z2019-04-26T00:00:00ZAccessibility for Line-Cutting in Freeform Surfaces
van Sosin B.; Bartoň M.; Elber G.
Manufacturing techniques such as hot-wire cutting, wire-EDM, wire-saw cutting, and flank CNC machining all belong to a class of processes called line-cutting where the cutting tool moves tangentially along the reference geometry. From a geometric point of view, line-cutting brings a unique set of challenges in guaranteeing that the process is collision-free. In this work, given a set of cut-paths on a freeform geometry as the input, we propose a conservative algorithm for finding collision-free tangential cutting directions. These directions, if they exist, are guaranteed to be globally accessible for fabricating the geometry by line-cutting. We then demonstrate how this information can be used to generate globally collision-free cut-paths. We apply our algorithm to freeform models of varying complexity.
2019-04-26T00:00:00Z