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Computational fluid dynamics (CFD) modelling has made significant contributions to the analysis and treatment of obstructive sleep apnoea (OSA). While several investigations have considered the flow field within the airway and its effect on airway collapse, the effect of breathing on the pharynx region is still poorly understood. We address this gap via a combined experimental and numerical study of the flow field within the pharynx and its impacts upon airway collapse. Two 3D experimental models of the upper airway were constructed based upon computerised tomography scans of a specific patient diagnosed with severe OSA; (i) a transparent, rigid model for flow visualisation, and (ii) a semi-flexible model for understanding the effect of flow on pharynx collapse. Validated simulation results for this geometry indicate that during inhalation, negative pressure (with respect to atmospheric pressure) caused by vortices drives significant narrowing of the pharynx. This narrowing is strongly dependent upon whether inhalation occurs through the nostrils. Thus, the methodology presented here can be used to improve OSA treatment by improving the design methodology for personalised, mandibular advancement splints (MAS) that minimise OSA during sleep.

At present, most multiscale simulation approaches to model the temperature evolution of the molten pool, and the resulting microstructure evolution for selective laser melting, assume an equilibrium freezing range and steady state solidification conditions. This is despite the solidification conditions being observed to be highly unsteady and non-equilibrium. These two assumptions lead to inaccurate predictions of the temperature evolution of the molten pool and thus microstructure predictions. To demonstrate this, an approach to scale-bridging computational models of the laser additive manufacturing process is presented, in which the temperature history is passed from a macroscale molten pool simulation to a microscale phase-field simulation. This linkage is achieved by volume mapping of the temperature field from the grid of the molten pool simulation to the grid of the microstructure simulation. To describe the system evolution at the scale of the molten pool, a computational fluid dynamics (CFD) method that captures the laser–metal interaction, vapour production, gas recoil pressure, fluid flow, surface tension, Marangoni flow, and heat conduction, convection, and radiation is applied. To capture the chemical kinetics of the phase-transition, a non-equilibrium CALPHAD-integrated phase-field (PF) model is applied. The discrepancy between the predictions of the solid front isotherm is quantified as ⩾ 100 K for an Al-10Si alloy under the large observed cooling rate. This leads to a spatial discrepancy in the solidification front between the CFD model, which assumes equilibrium freezing behaviour, and the PF model, which does not, of approximately 10 µm over 50 µs in the present case. Under these conditions, present formulations of multiphase CFD cannot accurately predict the solidification behaviour because of the assumption of equilibrium at the solid–liquid interface. Strategies for reconciling this discrepancy for materials that exhibit rapid solidification under large thermal undercooling will need to be developed for multiscale simulation of additive manufacturing to advance.

Enhanced natural gas recovery (EGR) with supercritical (sc)CO2 sequestration offers the prospect of increased natural gas recovery. High-fidelity reservoir simulations offer a method to quantify the risk of contamination of produced gas by the injected scCO2. Simulations of scCO2 mixing with the reservoir gas have been reported; however the effects of connate water on EGR have not been effectively explored. We extend a prior EGR simulation tool (Patel, May and Johns, 2016; Ref. [1]) to incorporate connate water accounting for its effect on dispersivity and permeability; chemical equilibrium is modelled using a novel, computationally efficient Lagrange multiplier-based approach. The code is applied to a ‘quarter five-spot’ benchmark scenario. The inclusion of connate water generally resulted in a reduction in breakthrough time and a decrease in methane recovery. The connate water's largest effect was to change the scCO2 flow field, which sank towards the reservoir floor, flooded the lowermost accessible layers and entered the production well via a high throughput channel (‘coning’). The magnitude of these effects were, however, sensitive to well perforation depth, the influence of which was subsequently studied systematically. Well perforation depth was found to determine the duration of these sinking and coning events in a non-linear manner.

Australia is a major exporter of wheat to South East (SE) Asia. Much of this wheat is low protein, fails in standard bake tests and is not traded as bread wheat. Some SE Asian bakeries observed that these doughs spread too significantly to be usable on current bread manufacturing lines. However, high-spread doughs are suited to sheeting lines and can produce high quality products. For confirmation, a pilot-scale dough sheeting line was constructed consisting of four roll-stands and a folder/lapper. Rollers were fitted with sensors to measure roll forces and dough sheet thicknesses. The first roll stand was also used to test flours for dough rheology. The sensors captured flour effects on dough flow quality during sheeting (‘sheetability’). The offline dough rheology data correlated with ‘online’ dough sheetability. The Australian flour doughs flowed more steadily through the roll stands than conventional bread doughs and also produced high quality sandwich breads.

EGR (Enhanced natural gas recovery) with CO2 sequestration offers the prospect of significant environmental and economic benefits by increasing gas recovery while simultaneously sequestering the greenhouse gas. Field-scale deployment is currently limited as the risks of contamination of the produced gas by injected CO2 are poorly understood. Reservoir simulations offer a method to quantify the risk but only if sufficiently accurate. For the first time, finite element simulations are presented for several EGR scenarios that incorporate the most accurate models available for fluid mixture and rock properties. Specifically, the GERG-2008 EOS (equation of state) is utilised to describe the supercritical fluid mixture's density, as are reference correlations linked to the most accurate experimental data available for diffusivity and viscosity. Realistic values for rock dispersivity and tortuosity determined from high-accuracy core-flooding and NMR (nuclear magnetic resonance) experiments were also integrated. The relative impacts of these properties were investigated for a benchmark layered reservoir with a quarter 5-spot well pattern. Recovery efficiency at different CO2 injection rates was also investigated and was determined to be the dominant consideration: a 100-fold rate increase improved recovery from 53% to 69% while CO2 breakthrough time decreased by less than expected. Collectively, these results emphasise the importance of accurate reservoir simulations for EGR.

Dough extension tests are used in industry to rate flours for dough processability. The results impact flour selection for product use. Previously, it was shown that dough extension data correlated poorly with dough sheetability irrespective of whether doughs were tested fresh or rested. It was noted that sample shapes varied between specimens of flours. To understand how sample shape affects extensigraph tests, a finite element (FE) simulation-based approach was taken. Real extensigraph samples were drawn on a computer equipped with the commercial FE package ABAQUS and using the anisotropic Bergstrom Boyce model with Mullins damage (ABBM) constitutive model to describe the dough's rheology. Results show that the force-extension traces were affected by sample shape, and that thinning occurs more from the sides than the bulk for slumped samples. The FE predictions for sample shape effects on hook force were validated against real tests. Similar dependencies on sample shape are also predicted for the alveograph and Kieffer micro-extensigraph tests.

Extrusion of solid-liquid particulate pastes is a well-established process in industry for continuously forming products of defined cross-sectional shape. At low extrusion velocities, the solids and liquid phases can separate due to drainage of liquid through the interparticle pores, termed liquid phase migration (LPM). The effect of wall friction, die shape and extrusion speed on LPM in a cylindrically axisymmetric ram extruder is investigated using a two-dimensional finite element model of paste extrusion based on soil mechanics principles (modified Cam-Clay). This extends the smooth walled model reported by Patel et al. (2007) to incorporate a simplified Tresca wall friction condition. Three die entry angles (90°, 60° and 45°) and two extrusion speeds are considered. The extrusion pressure is predicted to increase with the Tresca friction factor and the extent of LPM is predicted to increase with decreasing ram speed (both as expected). The effects of wall friction on LPM are shown to be dictated by the die shape and ram displacement: there are few general rules relating extruder design and operating conditions to extent of LPM, so that finite element-based simulation is likely to be needed to predict the onset of LPM accurately., PowdermatriX Faraday Programme under EPSRC project GR/S/70340

The precise coordination of Directional Overcurrent Relays (DOCRs) is required to identify fault timely, effectively and isolate them from the network to avoid possible outages in a power system. The DOCRs coordination is an optimization problem including highly nonlinear constraints. In this paper, Cuckoo Search Algorithm (CSA) is implemented to solve coordination problem of DOCRs on two different case studies. The parameters of CSA are effectively tuned to obtain global best solution for the DOCRs coordination problem. The obtained results using the proposed method are compared with Genetic Algorithm (GA) and hybrid GA-Nonlinear programming (GA-NLP) methods. The result shows that the effective modification of CSA parameters can obtain feasible and superior solution for this complex problem.