On the effects of turbulence modelling in design optimisation for high-lift devices

Aerodynamic shape optimisation is being increasingly utilised as a design tool in the aerospace industry. In order to provide accurate results, design optimisation methods rely on the accuracy of the underlying CFD methods applied to obtain aerodynamic forces for a given configuration. Previous studies of the authors have highlighted that the variation of the order of accuracy of the CFD solver with a fixed turbulence model affects the resulting optimised airfoil shape for a single element airfoil. The accuracy of the underlying CFD model is even more relevant in the context of high-lift configurations where an accurate prediction of flow is challenging due to the complex flow physics involving transition and flow separation phenomena. This paper explores the effect of the fidelity of CFD results for a range of turbulence models within the context of the computational design of aircraft configurations. The NLR7301 multi-element airfoil (main wing and flap) is selected as the baseline configuration, because of the wealth of experimental an computational results available for this configuration. An initial validation study is conducted in order to establish optimal mesh parameters. A bi-objective shape optimisation problem is then formulated, by trying to reveal the trade-off between lift and drag coefficients at high angles of attack. Optimisation of the airfoil shape is performed with Spalart-Allmaras, k - ω SST and k - o realisable models. The results indicate that there is consistent and complementary impact to the optimum level achieved from all the three different turbulence models considered in the presented case study. Without identifying particular superiority of any of the turbu- lence models, we can say though that each of them expressed favourable influence towards different optimality routes. These observations lead to the exploration of new avenues for future research. © 2012 AIAA.

On the effects of turbulence modelling in design optimisation for high-lift devices

Aerodynamic shape optimisation is being increasingly utilised as a design tool in the aerospace industry. In order to provide accurate results, design optimisation methods rely on the accuracy of the underlying CFD methods applied to obtain aerodynamic forces for a given configuration. Previous studies of the authors have highlighted that the variation of the order of accuracy of the CFD solver with a fixed turbulence model affects the resulting optimised airfoil shape for a single element airfoil. The accuracy of the underlying CFD model is even more relevant in the context of high-lift configurations where an accurate prediction of flow is challenging due to the complex flow physics involving transition and flow separation phenomena. This paper explores the effect of the fidelity of CFD results for a range of turbulence models within the context of the computational design of aircraft configurations. The NLR7301 multi-element airfoil (main wing and flap) is selected as the baseline configuration, because of the wealth of experimental an computational results available for this configuration. An initial validation study is conducted in order to establish optimal mesh parameters. A bi-objective shape optimisation problem is then formulated, by trying to reveal the trade-off between lift and drag coefficients at high angles of attack. Optimisation of the airfoil shape is performed with Spalart-Allmaras, k - ω SST and k - ε realisable models. The results indicate that there is consistent and complementary impact to the optimum level achieved from all the three different turbulence models considered in the presented case study. Without identifying particular superiority of any of the turbu- lence models, we can say though that each of them expressed favourable influence towards different optimality routes. These observations lead to the exploration of new avenues for future research. © 2012 by the authors.

Numerical modelling of chirality-Induced bi-Directional swimming of artificial flagella

Biomimetic micro-swimmers can be used for various medical applications, such as targeted drug delivery and micro-object (e.g. biological cells) manipulation, in lab-on-a-chip devices. Bacteria swim using a bundle of flagella (flexible hair-like structures) that form a rotating cork-screw of chiral shape. To mimic bacterial swimming, we employ a computational approach to design a bacterial (chirality-induced) swimmer whose chiral shape and rotational velocity can be controlled by an external magnetic field. In our model, we numerically solve the coupled governing equations that describe the system dynamics (i.e. solid mechanics, fluid dynamics and magnetostatics). We explore the swimming response as a function of the characteristic dimensionless parameters and put special emphasis on controlling the swimming direction. Our results provide fundamental physical insight on the chirality-induced propulsion, and it provides guidelines for the design of magnetic bi-directional micro-swimmers. © 2013 The Author(s) Published by the Royal Society. All rights reserved.

Wetness loss prediction for a low pressure steam turbine using computational fluid dynamics

Two-phase computational fluid dynamics modelling is used to investigate the magnitude of different contributions to the wet steam losses in a three-stage model low pressure steam turbine. The thermodynamic losses (due to irreversible heat transfer across a finite temperature difference) and the kinematic relaxation losses (due to the frictional drag of the drops) are evaluated directly from the computational fluid dynamics simulation using a concept based on entropy production rates. The braking losses (due to the impact of large drops on the rotor) are investigated by a separate numerical prediction. The simulations show that in the present case, the dominant effect is the thermodynamic loss that accounts for over 90% of the wetness losses and that both the thermodynamic and the kinematic relaxation losses depend on the droplet diameter. The numerical results are brought into context with the well-known Baumann correlation, and a comparison with available measurement data in the literature is given. The ability of the numerical approach to predict the main wetness losses is confirmed, which permits the use of computational fluid dynamics for further studies on wetness loss correlations. © IMechE 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

On Directional Selectivity in Vertebrate Retina: An Experimental and Computational Study

This thesis describes an investigation of retinal directional selectivity. We show intracellular (whole-cell patch) recordings in turtle retina which indicate that this computation occurs prior to the ganglion cell, and we describe a pre-ganglionic circuit model to account for this and other findings which places the non-linear spatio-temporal filter at individual, oriented amacrine cell dendrites. The key non-linearity is provided by interactions between excitatory and inhibitory synaptic inputs onto the dendrites, and their distal tips provide directionally selective excitatory outputs onto ganglion cells. Detailed simulations of putative cells support this model, given reasonable parameter constraints. The performance of the model also suggests that this computational substructure may be relevant within the dendritic trees of CNS neurons in general.

Subsethood-based fuzzy modelling and classification

K. Rasmani and Q. Shen. Subsethood-based fuzzy modelling and classification. Proceedings of the 2004 UK Workshop on Computational Intelligence, pages 181-188.

Adaptive Mixture Modelling Metropolis Methods for Bayesian Analysis of Non-linear State-Space Models.

We describe a strategy for Markov chain Monte Carlo analysis of non-linear, non-Gaussian state-space models involving batch analysis for inference on dynamic, latent state variables and fixed model parameters. The key innovation is a Metropolis-Hastings method for the time series of state variables based on sequential approximation of filtering and smoothing densities using normal mixtures. These mixtures are propagated through the non-linearities using an accurate, local mixture approximation method, and we use a regenerating procedure to deal with potential degeneracy of mixture components. This provides accurate, direct approximations to sequential filtering and retrospective smoothing distributions, and hence a useful construction of global Metropolis proposal distributions for simulation of posteriors for the set of states. This analysis is embedded within a Gibbs sampler to include uncertain fixed parameters. We give an example motivated by an application in systems biology. Supplemental materials provide an example based on a stochastic volatility model as well as MATLAB code.

Fire field modelling using the SMARTFIRE automated dynamic solution control environment

SMARTFIRE is a fire field model based on an open architecture integrated CFD code and knowledge-based system. It makes use of the expert system to assist the user in setting up the problem specification and new computational techniques such as Group Solvers to reduce the computational effort involved in solving the equations. This paper concentrates on recent research into the use of artificial intelligence techniques to assist in dynamic solution control of fire scenarios being simulated using fire field modelling techniques. This is designed to improve the convergence capabilities of the software while further decreasing the computational overheads. The technique automatically controls solver relaxations using an integrated production rule engine with a blackboard to monitor and implement the required control changes during solution processing. Initial results for a two-dimensional fire simulation are presented that demonstrate the potential for considerable savings in simulation run-times when compared with control sets from various sources. Furthermore, the results demonstrate enhanced solution reliability due to obtaining acceptable convergence within each time step unlike some of the comparison simulations.

Modelling meso-scale diffusion processes in stochastic fluid bio-membranes

The space–time dynamics of rigid inhomogeneities (inclusions) free to move in a randomly fluctuating fluid bio-membrane is derived and numerically simulated as a function of the membrane shape changes. Both vertically placed (embedded) inclusions and horizontally placed (surface) inclusions are considered. The energetics of the membrane, as a two-dimensional (2D) meso-scale continuum sheet, is described by the Canham–Helfrich Hamiltonian, with the membrane height function treated as a stochastic process. The diffusion parameter of this process acts as the link coupling the membrane shape fluctuations to the kinematics of the inclusions. The latter is described via Ito stochastic differential equation. In addition to stochastic forces, the inclusions also experience membrane-induced deterministic forces. Our aim is to simulate the diffusion-driven aggregation of inclusions and show how the external inclusions arrive at the sites of the embedded inclusions. The model has potential use in such emerging fields as designing a targeted drug delivery system.

Multiphysics modelling of the metals casting process

Metals casting is a process governed by the interaction of a range of physical phenomena. Most computational models of this process address only what are conventionally regarded as the primary phenomena-heat conduction and solidification. However, to predict the formation of porosity (a factor of key importance in cast quality) requires the modelling of the interaction of the fluid flow, heat transfer, solidification and the development of stress-deformation in the solidified part of a component. In this paper, a model of the casting process is described which addresses all the main continuum phenomena involved in a coupled manner. The model is solved numerically using novel finite volume unstructured mesh techniques, and then applied to both the prediction of shape deformation (plus the subsequent formation of a gap at the metal-mould interface and its impact on the heat transfer behaviour) and porosity formation in solidifying metal components. Although the porosity prediction model is phenomenologically simplistic it is based on the interaction of the continuum phenomena and yields good comparisons with available experimental results. This work represents the first of the next generation of casting simulation tools to predict aspects of the structure of cast components.

Nanoscopic modelling of the adhesion, indentation and fracture characteristics of metallic systems via molecular dynamics simulations

Large-scale molecular dynamics simulations have been performed on canonical ensembles to model the adhesion and indentation characteristics of 3-D metallic nano-scale junctions in tip-substrate geometries, and the crack propagation in 2-D metallic lattices. It is shown that irreversible flows in nano-volumes of materials control the behaviour of the 3-D nano-contacts, and that local diffusional flow constitutes the atomistic mechanism underlying these plastic flows. These simulations show that the force of adhesion in metallic nano-contacts is reduced when adsorbate monolayers are present at the metal—metal junctions. Our results are in agreement with the conclusions of very accurate point-contact experiments carried out in this field. Our fracture simulations reveal that at low temperatures cleavage fractures can occur in both an elemental metal and an alloy. At elevated temperatures, the nucleation of dislocations is shown to cause a brittle-to-ductile transition. Limiting crack propagation velocities are computed for different strain rates and a dynamic instability is shown to control the crack movement beyond this limiting velocity, in line with the recent experimental results.

A non-Newtonian computational fluid dynamics study of the stencil printing process

This paper describes the application of computational fluid dynamics (CFD) to simulate the macroscopic bulk motion of solder paste ahead of a moving squeegee blade in the stencil printing process during the manufacture of electronic components. The successful outcome of the stencil printing process is dependent on the interaction of numerous process parameters. A better understanding of these parameters is required to determine their relation to print quality and improve guidelines for process optimization. Various modelling techniques have arisen to analyse the flow behaviour of solder paste, including macroscopic studies of the whole mass of paste as well as microstructural analyses of the motion of individual solder particles suspended in the carrier fluid. This work builds on the knowledge gained to date from earlier analytical models and CFD investigations by considering the important non-Newtonian rheological properties of solder pastes which have been neglected in previous macroscopic studies. Pressure and velocity distributions are obtained from both Newtonian and non-Newtonian CFD simulations and evaluated against each other as well as existing established analytical models. Significant differences between the results are observed, which demonstrate the importance of modelling non-Newtonian properties for realistic representation of the flow behaviour of solder paste.

A case based reasoning system capturing fire modelling expertise

This paper describes the architecture of the case based reasoning (CBR) component of Smartfire, a fire field modelling tool for use by members of the Fire Safety Engineering community who are not expert in modelling techniques. The CBR system captures the qualitative reasoning of an experienced modeller in the assessment of room geometries so as to set up the important initial parameters of the problem. The system relies on two important reasoning principles obtained from the expert: 1) there is a natural hierarchical retrieval mechanism which may be employed; and 2) much of the reasoning on a qualitative level is linear in nature, although the computational solution of the problem is non-linear. The paper describes the qualitative representation of geometric room information on which the system is based, and the principles on which the CBR system operates.

The Shared Memory Parallelisation of an Ocean Modelling Code using an Interactive Parallelisation Toolkit

This paper briefly describes an interactive parallelisation toolkit that can be used to generate parallel code suitable for either a distributed memory system (using message passing) or a shared memory system (using OpenMP). This study focuses on how the toolkit is used to parallelise a complex heterogeneous ocean modelling code within a few hours for use on a shared memory parallel system. The generated parallel code is essentially the serial code with OpenMP directives added to express the parallelism. The results show that substantial gains in performance can be achieved over the single thread version with very little effort.

Modelling the fluid dynamics and coupled phenomena in arc weld pools

A 3D model of melt pool created by a moving arc type heat sources has been developed. The model solves the equations of turbulent fluid flow, heat transfer and electromagnetic field to demonstrate the flow behaviour phase-change in the pool. The coupled effects of buoyancy, capillary (Marangoni) and electromagnetic (Lorentz) forces are included within an unstructured finite volume mesh environment. The movement of the welding arc along the workpiece is accomplished via a moving co-ordinator system. Additionally a method enabling movement of the weld pool surface by fluid convection is presented whereby the mesh in the liquid region is allowed to move through a free surface. The surface grid lines move to restore equilibrium at the end of each computational time step and interior grid points then adjust following the solution of a Laplace equation.