SUMMARY Conjugate heat‐transfer problems are typically solved using partitioned methods where fluid and solid subdomains are evaluated separately by dedicated solvers coupled through a common boundary. Strongly coupled schemes for transient analysis require fluid and solid problems to be solved many times each time step until convergence to a steady state. In many practical situations, a fairly simple and frequently employed fixed‐point iteration process is rather ineffective; it leads to a large number of iterations per time step and consequently to long simulation times. In this article, Anderson mixing is proposed as a fixed‐point convergence acceleration technique to reduce computational cost of thermal coupled fluid–solid problems. A number of other recently published methods with applications to similar fluid–structure interaction problems are also reviewed and analyzed. Numerical experiments are presented to illustrate relative performance of these methods on a test problem of rotating pre‐swirl cavity air flow interacting with a turbine disk. It is observed that performance of Anderson mixing method is superior to that of other algorithms in terms of total iteration counts. Additional computational savings are demonstrated by reusing information from previously solved time steps. Copyright © All rights reserved 2012 Rolls‐Royce plc.

This paper presents the transient aero-thermal analysis of a gas turbine internal air system through an engine flight cycle featuring multiple fluid cavities that surround a HP turbine disk and the adjacent structures. Strongly1 γ least-squares problem solution ∆ difference δ wall temperature perturbation factor θ time discretization control parameter Superscripts () n n-th time step INTRODUCTIONAccurate prediction of aerodynamic, aero-mechanical and thermo-mechanical phenomena attracts an increasing interest from the gas turbine industry. Efficient and robust analysis procedures able to properly describe the thermal and flow environment within a secondary air system may lead to substantial gains in overall engine performance, weight and components reliability by offering improved means of optimizing designs [1].Typically, in thermal modeling, the internal air system is modeled with user-specified boundary conditions, while more accurate CFD predictions, if available, are applied only on some portions of the system. The user-specified boundary conditions rely heavily on correlations, they require a significant effort from an end-user to correctly represent the complex physical phenomena over a wide range of operating conditions. As the geometries of modern air systems grow in complexity, current models with correlations become painful to build and increasingly obsolete.A general trend in computational modeling of modern turbo-machinery systems is to move towards the "virtual" or "whole" engine simulation [2]. As far as modeling of the internal air systems is concerned, a natural and incremental advance in both the complexity and the accuracy of current modeling is to include and interconnect multiple CFD domains within a single simulation. Among the advantages it may offer are a lower level of human intervention and time required to set up the models, and more importantly, automatic generation of the boundary conditions for the downstream components. However, this comes at a price of a considerably higher computational effort required to run a simulation through an engine transient flight cycle leading to long analysis times.Many studies in recent years sought to improve the predictive capabilities of thermo-mechanical analysis codes by coupling FE solvers to detailed CFD models of individual components to more accurately evaluate wall temperature distribution in turbine cavities, see, for example, [3,4,5,6,7]. While these studies were able to obtain only a general agreement with the experimental data, they did demonstrate many of the fundamental features outlined in earlier investigations. Subsequent efforts attempted to further improve the agreement by including some of both fluid and solid domains 3D geometrical features in the analysis [8] or the effects of solid domain thermo-mechanical distortion on flow dynamics [9]. Still, accurate and automatic predictions of heat transfer in the internal air systems remain a difficult challenge.The main goal of this paper is to provide a snapshot of the state-...

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This paper describes a coupling framework for parallel execution of different solvers for multi-physics and multi-domain simulations with an arbitrary number of adjacent zones connected by different physical or overlapping interfaces. The coupling architecture is based on the execution of several instances of the same coupling code and relies on the use of smart edges (i.e., separate processes) dedicated to managing the exchange of information between two adjacent regions. The collection of solvers and coupling sessions forms a flexible and modular system, where the data exchange is handled by independent servers that are dedicated to a single interface connecting two solvers’ sessions. Accuracy and performance of the strategy is considered for turbomachinery applications involving Conjugate Heat Transfer (CHT) analysis and Sliding Plane (SP) interfaces.

This paper presents the transient aero-thermal analysis of a gas turbine internal air system through an engine flight cycle featuring multiple fluid cavities that surround a HP turbine disk and the adjacent structures. Strongly1 γ least-squares problem solution ∆ difference δ wall temperature perturbation factor θ time discretization control parameter Superscripts () n n-th time step INTRODUCTIONAccurate prediction of aerodynamic, aero-mechanical and thermo-mechanical phenomena attracts an increasing interest from the gas turbine industry. Efficient and robust analysis procedures able to properly describe the thermal and flow environment within a secondary air system may lead to substantial gains in overall engine performance, weight and components reliability by offering improved means of optimizing designs [1].Typically, in thermal modeling, the internal air system is modeled with user-specified boundary conditions, while more accurate CFD predictions, if available, are applied only on some portions of the system. The user-specified boundary conditions rely heavily on correlations, they require a significant effort from an end-user to correctly represent the complex physical phenomena over a wide range of operating conditions. As the geometries of modern air systems grow in complexity, current models with correlations become painful to build and increasingly obsolete.A general trend in computational modeling of modern turbo-machinery systems is to move towards the "virtual" or "whole" engine simulation [2]. As far as modeling of the internal air systems is concerned, a natural and incremental advance in both the complexity and the accuracy of current modeling is to include and interconnect multiple CFD domains within a single simulation. Among the advantages it may offer are a lower level of human intervention and time required to set up the models, and more importantly, automatic generation of the boundary conditions for the downstream components. However, this comes at a price of a considerably higher computational effort required to run a simulation through an engine transient flight cycle leading to long analysis times.Many studies in recent years sought to improve the predictive capabilities of thermo-mechanical analysis codes by coupling FE solvers to detailed CFD models of individual components to more accurately evaluate wall temperature distribution in turbine cavities, see, for example, [3,4,5,6,7]. While these studies were able to obtain only a general agreement with the experimental data, they did demonstrate many of the fundamental features outlined in earlier investigations. Subsequent efforts attempted to further improve the agreement by including some of both fluid and solid domains 3D geometrical features in the analysis [8] or the effects of solid domain thermo-mechanical distortion on flow dynamics [9]. Still, accurate and automatic predictions of heat transfer in the internal air systems remain a difficult challenge.The main goal of this paper is to provide a snapshot of the state-...