Self-adaptive coupling frequency for unsteady coupled conjugate heat transfer simulations

Abstract Tackling transient conjugate heat transfer with high-fidelity methods such as large-eddy simulation (LES) requires to couple the LES solver with a heat transfer solver in the solid parts of the computational domain. Challenges include performance scalability, numerical stability and accuracy. In such unsteady simulations, both solvers integrate their respective set of equations in time independently for the sake of computational efficiency, and during a physical time corresponding to a coupling period to be specified. During the separate temporal integrations, the thermal state at the wall interface is typically set as a Dirichlet condition in the flow solver while a Neumann condition is imposed in the heat transfer solver to enhance numerical stability. When carefully validated, the chosen value of the coupling period which optimal value is initially unknown can be compared a posteriori with a refined solution. However, this optimal value of the coupling period (neither too large to remain accurate nor too short not to penalize the computational cost) is case-dependent. In this study, an approach to automatically adapt the coupling period is presented. It relies on a describing the temporal evolution of the boundary temperature in hybrid cells composed of the neighboring fluid and solid mesh cells. Then, between coupling iterations, each solver advances separately with the same Dirichlet boundary condition on the computed interface temperature. Yielding a first order Ordinary Differential Equation (ODE) for the boundary temperature, the method allows using automatic adaptation of the step size to control the numerical integration error based on a prescribed tolerance by using controllers. The coupling method is studied on 1D unsteady configurations where the results demonstrate that this energy conserving method is able to determine the coupling period automatically and efficiently for different configurations. The impact of excitation frequency and prescribed tolerance enables to select a specific PID controller which remains robust in spite of not carrying out step rejections for the sake of computational performance in the context of an LES application.

[1]  Donald Estep,et al.  A posteriori error analysis for a transient conjugate heat transfer problem , 2009 .

[2]  L. He,et al.  Fourier spectral modelling for multi-scale aero-thermal analysis , 2013 .

[3]  William D. Henshaw,et al.  A composite grid solver for conjugate heat transfer in fluid-structure systems , 2009, J. Comput. Phys..

[4]  K. Gustafsson,et al.  API stepsize control for the numerical solution of ordinary differential equations , 1988 .

[5]  R. Dickinson Convergence Rate and Stability of Ocean-Atmosphere Coupling Schemes with a Zero-Dimensional Climate Model , 1981 .

[6]  Gustaf Söderlind,et al.  Digital filters in adaptive time-stepping , 2003, TOMS.

[7]  Barry F. Smith,et al.  Domain Decomposition: Parallel Multilevel Methods for Elliptic Partial Differential Equations , 1996 .

[8]  Gabriel Staffelbach,et al.  On the sensitivity of a helicopter combustor wall temperature to convective and radiative thermal loads , 2016 .

[9]  Abram Dorfman,et al.  Conjugate Problems in Convective Heat Transfer: Review , 2009 .

[10]  E. Hairer,et al.  Solving Ordinary Differential Equations II , 2010 .

[11]  J. M. Duboué,et al.  Conjugate Heat Transfer Analysis of an Engine Internal Cavity , 2000 .

[12]  Patrick Knupp,et al.  Code Verification by the Method of Manufactured Solutions , 2000 .

[13]  Florent Duchaine,et al.  Analysis of high performance conjugate heat transfer with the OpenPALM coupler , 2015 .

[14]  Florent Duchaine,et al.  Massively parallel conjugate heat transfer methods relying on large eddy simulation applied to an aeronautical combustor , 2013 .

[15]  R. Sausen,et al.  Climate simulations with the global coupled atmosphere-ocean model ECHAM2/OPYC Part I: present-day climate and ENSO events , 1996 .

[16]  Franck Nicoud,et al.  Development and assessment of a coupled strategy for conjugate heat transfer with Large Eddy Simulation: Application to a cooled turbine blade , 2009 .

[17]  J. Gressier,et al.  Methodology of numerical coupling for transient conjugate heat transfer , 2014 .

[18]  Horst-Michael Prasser,et al.  Computational study of conjugate heat transfer in T-junctions , 2010 .

[19]  Kjell Gustafsson,et al.  Control-theoretic techniques for stepsize selection in implicit Runge-Kutta methods , 1991, TOMS.

[20]  Alfio Quarteroni,et al.  Domain Decomposition Methods for Partial Differential Equations , 1999 .

[21]  Robert Sausen,et al.  Time-dependent greenhouse warming computations with a coupled ocean-atmosphere model , 1992 .

[22]  Francois-Xavier Roux,et al.  Domain Decomposition Methodology with Robin Interface Matching Conditions for Solving Strongly Coupled Fluid-Structure Problems , 2009 .

[23]  Leon Cizelj,et al.  Double-sided cooling of heated slab: Conjugate heat transfer DNS , 2013 .

[24]  Stéphane Moreau,et al.  Large-Eddy Simulation and Conjugate Heat Transfer Around a Low-Mach Turbine Blade , 2013 .

[25]  B. Cuenot,et al.  Effect of pressure on Hydrogen/Oxygen coupled flame-wall interaction , 2016 .

[26]  R. Sausen,et al.  Techniques for asynchronous and periodically synchronous coupling of atmosphere and ocean models , 1996 .

[27]  P. Roache Code Verification by the Method of Manufactured Solutions , 2002 .

[28]  W. R. Van Dalsem,et al.  Thermal interaction between an impinging hot jet and a conducting solid surface , 1990 .

[29]  Michael B. Giles,et al.  Stability analysis of numerical interface conditions in fluid-structure thermal analysis , 1997 .

[30]  Marc-Paul Errera,et al.  Optimal solutions of numerical interface conditions in fluid-structure thermal analysis , 2013, J. Comput. Phys..

[31]  T. Lieuwen Unsteady Combustor Physics , 2012 .

[32]  Li He,et al.  Unsteady Conjugate Heat Transfer Modeling , 2011 .