Tim Craft

Bio: Tim Craft is an academic researcher from University of Manchester. The author has contributed to research in topics: Turbulence & Reynolds-averaged Navier–Stokes equations. The author has an hindex of 24, co-authored 114 publications receiving 3118 citations.

Development and application of a cubic eddy-viscosity model of turbulence

Abstract: Many quadratic stress-strain relations have been proposed in recent years to extend the applicability of linear eddy-viscosity models at modest computational cost However, comparison shows that none achieves much greater width of applicability This paper, therefore, proposes a cubic relation between the strain and vorticity tensor and the stress tensor, which does much better than a conventional eddy-viscosity scheme in capturing effects of streamline curvature over a range of flows The flows considered range from simple shear at high strain rates and pipe flow, to flows involving strong streamline curvature and stagnation

Impinging jet studies for turbulence model assessment—II. An examination of the performance of four turbulence models

Abstract: Four turbulence models are applied to the numerical prediction of the turbulent impinging jets discharged from a circular pipe measured by Cooper el al. [ Int. J. Heat Mass Transfer 36, 2675–2684 (1993)], Baughn and Shimizu [ ASME J. Heat Transfer 111, 1096–1098 (1986)] and Baughn el al. [ASME Winter Annual Meeting, November 1992]. They comprise one k-e eddy viscosity model and three second-moment closures. In the test cases selected, the jet discharge was two and six diameters above a plane surface orthogonal to the jet's axis. The Reynolds numbers were 2.3 × 10 4 and 7 × 10 4 the flow being fully developed at the discharge plane. The numerical predictions, obtained with an extended version of the finite-volume TEAM code, indicate that the k-e model and one of the Reynolds stress models lead to far too large levels of turbulence near the stagnation point. This excessive energy in turn induces much too high heat transfer coefficients and turbulent mixing with the ambient fluid. The other two second-moment closures, adopting new schemes for accounting for the wall's effect on pressure fluctuations, do much better though one of them is clearly superior in accounting for the effects of the height of the jet discharge above the plate. None of the schemes is entirely successful in predicting the effects of Reynolds number. It is our view, however, that the main cause of this failure is the two-equation eddy viscosity scheme adopted in all cases to span the near-wall sublayer rather than the outer layer models on which the present study has focused.

Progress in the generalization of wall-function treatments

Abstract: This paper describes progress in developing an analytical representation of the variation of the dynamic variables and temperature across the near-wall sublayer of a turbulent flow. The aim is to enable the effective “resistance” of the viscous sublayer to the transport of heat and momentum to be packaged in the form of a “wall function”, thus enabling CFD predictions of convective heat transfer to be made without incurring the cost of the very fine near-wall grid that would otherwise have to be adopted. While the general idea is not new, the detailed strategy contains many new features, which have led to a scheme capable of accounting for the effects of buoyancy, pressure gradient and of variations in molecular transport properties. The scheme is applied to the problem of forced and mixed convection in a vertical pipe and to the opposed wall jet with encouraging results.

A new divergence free synthetic eddy method for the reproduction of inlet flow conditions for les

Abstract: This paper describes a recent development of the Synthetic Eddy Method (SEM) proposed by Jarrin et al. (Int J Heat Fluid Flow 30(3):435–442, 2009) for generation of synthetic turbulence. The present scheme is designed to produce a divergence-free turbulence field that can reproduce almost all possible states of Reynolds stress anisotropy. This improved representation, when used to provide inlet conditions for an LES, leads to reduced near-inlet pressure fluctuations in the LES and to a reduced development length, both of which lead to lower computer resource requirements. An advantage of this method with respect to forcing approaches (which require an iterative approach) is the suitability for direct usage with embedded LES. Results for a turbulent channel flow are reported here and compared to those from the original SEM, and other direct approaches such as the VORTEX method of Sergent (2002) and the Synthesized Turbulence approach of Davidson and Billson (Int J Heat Fluid Flow 27(6):1028–1042, 2006), showing overall improved performance and a more accurate representation of turbulence structures immediately downstream of the inlet.

A Reynolds stress closure designed for complex geometries

Abstract: The paper describes steps in the development of a low Reynolds number second-moment closure for general flow geometries. This requirement means that the model cannot contain geometry-specific quantities, such as the wall-normal vector or wall distance. In their place, invariant dimensionless “gradient indicators” are introduced. New models are also devised for stress dissipation to capture the very diverse behaviour of the different components of eij in the wall's vicinity with and without shear. A novel decomposition of the fluctuating pressure terms is also proposed. Applications are shown for shear-free boundary regions, plane channel, and stagnation flows.

Reynolds averaged turbulence modelling using deep neural networks with embedded invariance

Abstract: There exists significant demand for improved Reynolds-averaged Navier–Stokes (RANS) turbulence models that are informed by and can represent a richer set of turbulence physics. This paper presents a method of using deep neural networks to learn a model for the Reynolds stress anisotropy tensor from high-fidelity simulation data. A novel neural network architecture is proposed which uses a multiplicative layer with an invariant tensor basis to embed Galilean invariance into the predicted anisotropy tensor. It is demonstrated that this neural network architecture provides improved prediction accuracy compared with a generic neural network architecture that does not embed this invariance property. The Reynolds stress anisotropy predictions of this invariant neural network are propagated through to the velocity field for two test cases. For both test cases, significant improvement versus baseline RANS linear eddy viscosity and nonlinear eddy viscosity models is demonstrated.

Introduction to Computational Fluid Dynamics

Abstract: Introduction to Computational Fluid Dynamics is a textbook for advanced undergraduate and first year graduate students in mechanical, aerospace and chemical engineering. The book emphasizes understanding CFD through physical principles and examples. The author follows a consistent philosophy of control volume formulation of the fundamental laws of fluid motion and energy transfer, and introduces a novel notion of 'smoothing pressure correction' for solution of flow equations on collocated grids within the framework of the well-known SIMPLE algorithm. The subject matter is developed by considering pure conduction/diffusion, convective transport in 2-dimensional boundary layers and in fully elliptic flow situations and phase-change problems in succession. The book includes chapters on discretization of equations for transport of mass, momentum and energy on Cartesian, structured curvilinear and unstructured meshes, solution of discretised equations, numerical grid generation and convergence enhancement. Practising engineers will find this particularly useful for reference and for continuing education.

The Scale-Adaptive Simulation Method for Unsteady Turbulent Flow Predictions. Part 1: Theory and Model Description

Abstract: The article gives an overview of the Scale-Adaptive Simulation (SAS) method developed by the authors during the last years. The motivation for the formulation of the SAS method is given and a detailed explanation of the underlying ideas is presented. The derivation of the high-Reynolds number form of the equations as well as the calibration of the constants is provided. The concept of SAS is explained using several generic examples and test cases. In a companion article, the model is applied to more complex industrial-type applications.

Review of the shear-stress transport turbulence model experience from an industrial perspective

Abstract: The present author was asked to provide an update on the status and the more recent developments around the shear-stress transport (SST) turbulence model for this special issue of the journal. The article is therefore not intended as a comprehensive overview of the status of engineering turbulence modelling in general, nor on the overall turbulence modelling strategy for ANSYS computational fluid dynamics (CFD) in particular. It is clear from many decades of turbulence modelling that no single model-nor even a single modelling approach-can solve all engineering flows. Any successful CFD code will therefore have to offer a wide range of models from simple Eddy-viscosity models through second moment closures all the way to the variety of unsteady modelling concepts currently under development. This article is solely intended to outline the role of the concepts behind the SST model in current and future CFD simulations of engineering flows.