CFD Flow Solver Research Articles

Computational Study of a Swirl Stabilized Flame in a Gas Turbine Combustor

Size of recirculation zone and temperature field is examined in a swirl stabilized aero gas turbine combustor using computational fluid dynamics. A sector of 22.5° of an annular combustor is modeled for the study. Unstructured tetrahedral meshes comprising 1.2x106 elements are employed in the model where the governing equations are solved using CFD flow solver CFX. Grid sensitivity study and code validation through limited test data has also been carried out. The effect of pressure and fuel-air ratio on the size of recirculation zone and apparent size of flame zone has been studied at steady state conditions. The heat release rate due to combustion is found to affect the length of recirculation zone as well as the velocity field inside the combustion liner.

Mixed-Fidelity Design Optimization of Hull Form Using CFD and Potential Flow Solvers

The present paper proposes a new mixed-fidelity method to optimize the shape of ships using genetic algorithms (GA) and potential flow codes to evaluate the hydrodynamics of variant hull forms, enhanced by a surrogate model based on an Artificial Neural Network (ANN) to account for viscous effects. The performance of the variant hull forms generated by the GA is evaluated for calm water resistance using potential flow methods which are quite fast when they run on modern computers. However, these methods do not take into account the viscous effects which are dominant in the stern region of the ship. Solvers of the Reynolds-Averaged Navier-Stokes Equations (RANS) should be used in this respect, which, however, are too time-consuming to be used for the evaluation of some hundreds of variants within the GA search. In this study, a RANS solver is used prior to the execution of the GA to train an ANN in modeling the effect of stern design geometrical parameters only. Potential flow results, accounting for the geometrical design parameters of the rest of the hull, are combined with the aforementioned trained meta-model for the final hull form evaluation. This work concentrates on the provision of a more reliable framework for the evaluation of hull form performance in calm water without a significant increase of the computing time.

Numerical Study about Aerodynamic Interaction for Coaxial Rotor Blades

In the present study, the interaction effect by inter-rotor spacing of coaxial rotor blades in hovering and forward flight is studied by using a Reynolds-averaged Navier–Stokes CFD flow solver based on mixed meshes. The meshes were composed of unstructured near-body region and Cartesian off-body region. The flux-difference splitting scheme of Roe was used for computing inviscid fluxes on the near-body region, whereas the 7th order WENO scheme was used for the computation of the inviscid fluxes on the off-body region to capture vortex with high resolution. The predicted results of the baseline inter-rotor spacing were compared with the reference results of other researchers for validation. The computed results of three different inter-rotor spacings were compared in terms of the thrust and torque coefficients for each flight condition. The cause of the different interaction effect by inter-rotor spacing between hovering and forward flight was also investigated.

Computational grid adaptation for the sonic boom near field modeling

This paper discusses the numerical simulation of the 69-Degree Delta Wing Body for computing the sonic boom signature in the near field. For flow field calculation, the commercial CFD flow solver ANSYS Fluent is employed. The computational mesh in the perturbed flow regions was refined two times using the automatic gradient adaptation. The results are in agreement with the results obtained by other researchers.

Performance improvement of horizontal axis wind turbines by aerodynamic shape optimization including aeroealstic deformation

Aerodynamic shape optimization of horizontal axis wind turbines was performed to minimize the cost of energy. The optimum blade was obtained by modifying the blade section contours at selected blade radial stations. For the optimization, the design variables were defined as the coordinates of the blade section contours perpendicular to the chord. An aerodynamic performance database was constructed for those blade configurations defined by random combinations of design variables selected within a given range by Latin-Hypercube sampling. An artificial neural network was applied to derive the approximate functions between the design variables and the aerodynamic performance of the database. By utilizing the approximate functions, a genetic algorithm was adopted to search for an optimized blade. To construct the database, a CFD flow solver based on unstructured meshes was utilized. To consider the effects of aeroelastic deformation of the structurally flexible blades, a coupled CFD-CSD method was also adopted. The applications were made for the NREL phase VI and NREL 5 MW reference wind turbine rotor blades. After optimization, the cost of energy was reduced by 0.82% for the NREL phase VI rotor blade and one percent for the NREL 5 MW reference wind turbine blade, respectively.

전산유체/전산구조 연계 방법을 이용한 후퇴각이 있는 수평축 풍력터빈 로터 블레이드의 공탄성 특성 예측

The aeroelastic characteristics for the backward swept blade of a horizontal axis wind turbine were examined by using a coupled CFD/CSD method as the fundamental research for a bend-twist coupled (BTC) blade. The aerodynamic loads were obtained from the three-dimensional, incompressible, Navier-Stokes CFD flow solver based on unstructured meshes. The elastic behavior of the blade was calculated by using an FEM-based CSD solver utilizing a nonlinear coupled flap-lag-torsion beam theory. The calculations were made for the blade of the NREL 5MW wind turbine with backward swept angle. Compared to the straight rotor blade, flapwise deflection toward the tower and edgewise deflection toward the leading edge of the backward swept blade were decreased; otherwise, its torsional deflection in nose-down direction was significantly increased. Due to the blade deformations that decreased its effective angle-of-attack, the aerodynamic loads applied to the swept blades were remarkably reduced compared to the straight rotor blade. In addition, the root bending moments were also influenced by the swept-back configuration of the blade. Due to the aerodynamic loads reduction of the backward swept blade, the root bending moments in the edgewise and flapwise directions were decreased, although the torsional bending moments were significantly increased.

A model for solid propellant burning fluctuations using mesoscale simulations

The combustion of composite solid propellants shows velocity fluctuations which are expected to have marked effects on turbulence or aeroacoustic instabilities. In this work, we propose a specific propellant boundary condition that models such fluctuations using a spectral synthetic turbulence approach. In order to feed this model with reliable input data, we consider mesoscale direct simulations of propellant combustion. This new propellant boundary condition is implemented in a CFD flow solver and applied to a real lab-scale motor. Simulations show that burning fluctuations can trigger aeroacoustic instabilities, in better agreement with experiments.

Aeroelastic Study for HART II Rotor Using Unstructured Mixed Meshes

In the present study, aeroelastic response of HART II rotor blade has been numerically investigated using a coupled CFD/CSD method. Aerodynamic forces were calculated from a Navier–Stokes CFD flow solver based on unstructured mixed meshes. In the mixed meshes methodology, body-fitted prismatic/tetrahedral mesh was used in the near-body flow region to handle complex geometries easily. Cartesian mesh was used in the off-body flow region and high-order accurate weighted essentially non-oscillatory scheme was employed to implement high-order spatial accuracy. In the FEM-based CSD solver, an elastic deformation of the rotor blade was obtained on the basis of nonlinear Euler–Bernoulli beam theory. The coupling between the CFD and CSD solver was performed in a loosely coupled manner by exchanging the aerodynamic loads and elastic deformation of the rotor blade. An overset mesh technique was adopted to simulate rotating motion of the rotor blade and to exchange flow information between two different meshes. In addition, spring analogy was used to implement elastic deformation of the rotor blade. Coupled CFD/CSD method was applied to the HART II rotor in forward flight to examine aerodynamic performance and aeroelastic effect of the rotor. Aerodynamic loads and elastic deformation of the rotor blade were calculated and compared with experimental results and other research efforts. Overall, the present results were in good agreement with the experimental data. In addition, adaptive fine mesh was used to capture tip vortex trajectory and BVI (blade–vortex interaction) phenomenon more accurately.

Numerical Simulation of Horizontal Axis Wind Turbines with Vortex Generators

In the present study, a simulation about the effects of vortex generators on horizontal axis wind turbine rotor blade was numerically conducted using a static coupled CFD–CSD method. A Navier–Stokes CFD flow solver based on unstructured meshes was used to obtain the blade aerodynamic loads. A FEM-based CSD solver employing a nonlinear coupled flap-lag-torsion beam theory was utilized to calculate the blade elastic deformation. The coupling of the CFD and CSD solvers was accomplished in a loosely coupled manner by exchanging the information between the two solvers at infrequent intervals. The static coupled CFD–CSD method was applied to the NREL 5 MW reference wind turbine rotor under steady axial flow conditions. Triangular counter-rotating vortex generators were adopted to control flow separation and radial flow in the inboard section of the NREL 5 MW reference rotor blades. They were installed on the inboard part of the blade from 0.2 to 0.4 R. As a result of the flow analysis considering the counter-rotating vortex generators, strong vortices were generated by counter-rotating vortex generators. It can be seen that the regions where flow separation and radial flow occur in the inboard sections were reduced compared to the baseline wind turbine. For this reason, the maximum power improvement due to counter-rotating vortex generators was 1.04% at the rated wind speed.

Structure modification and numerical study of the moisture-separation performance of special crossunder pipe separators for nuclear power steam turbines

The present paper investigated the enhancement of moisture-separation efficiency for ordinary special crossunder pipe separators (SCRUPSs) and proposed three structure-modified separators (combined separator, Z-shaped SCRUPSs, and spiral-type SCRUPSs). Deposition mechanisms for droplets with different sizes were considered using commercial CFD flow solver. Results show that three-structure modified separators can increase droplet deposition rate to varying degrees. Regarding flow losses, spiral-type SCRUPSs cause the highest increase, with a total pressure loss coefficient of 231%, although it has the best deposition rate improvement. Among the three structure-modified separators, "Z" shape separator has the best separation performance because of its higher moisture-separation efficiency and lower total pressure loss efficiency. Results could provide theoretical basis for research on and development of this new type of moisture separator.

Predicting wind turbine blade loads and aeroelastic response using a coupled CFD–CSD method

The aeroelastic response and the airloads of horizontal-axis wind turbine rotor blades were numerically investigated using a coupled CFD–CSD method. The blade aerodynamic loads were obtained from a Navier–Stokes CFD flow solver based on unstructured meshes. The blade elastic deformation was calculated using a FEM-based CSD solver which employs a nonlinear coupled flap-lag-torsion beam theory. The coupling of the CFD and CSD solvers was accomplished in a loosely coupled manner by exchanging the information between the two solvers at infrequent intervals. At first, the present coupled CFD–CSD method was applied to the NREL 5MW reference wind turbine rotor under steady axial flow conditions, and the mean rotor loads and the static blade deformation were compared with other predicted results. Then, the unsteady blade aerodynamic loads and the dynamic blade response due to rotor shaft tilt and tower interference were investigated, along with the influence of the gravitational force. It was found that due to the aeroelastic blade deformation, the blade aerodynamic loads are significantly reduced, and the unsteady dynamic load behaviors are also changed, particularly by the torsional deformation. From the observation of the tower interference, it was also found that the aerodynamic loads are abruptly reduced as the blades pass by the tower, resulting in oscillatory blade deformation and vibratory loads, particularly in the flapwise direction.

Two Mesh Deformation Methods Coupled with a Changing-connectivity Moving Mesh Method for CFD Applications

Three-dimensional real-life simulations are generally unsteady and involve moving geometries. Industry is currently very far from performing such body-fitted simulations on a daily basis, mainly due to the robustness of the moving mesh algorithm and their extensive computational cost. A moving mesh algorithm coupled to local mesh optimizations has proved its efficiency in dealing with large deformation of the mesh without re-meshing. In this paper, the coupling of this algorithm with two mesh deformation techniques is studied: an elasticity PDE-based one and an explicit Inverse Distance Weighted interpolation one, and both techniques are compared. The efficiency of this method is demonstrated on challenging test cases, involving large body deformations, boundary layers and large displacements with shearing. Finally, the moving mesh algorithm is coupled to a CFD flow solver.

Laminar flamelet modeling of a turbulent CH 4/H 2/N 2 jet diffusion flame using artificial neural networks

The laminar flamelet concept is used in the prediction of mean reactive scalars in a non-premixed turbulent CH 4/H 2/N 2 flame. First, a databank for temperature and species concentrations is developed from the solutions of counter-flow diffusion flames. The effects of flow field on flamelets are considered by using mixture fraction and scalar dissipation rate. Turbulence–chemistry interactions are taken into account by integrating different quantities based on a presumed probability density function (PDF), to calculate the Favre-averaged values of scalars. Flamelet library is then generated. To interpolate in the generated library, one artificial neural network (ANN) is trained where the mean and variance of mixture fraction and the scalar dissipation rate are used as inputs, and species mean mass fractions and temperature are selected as outputs. The weights and biases of this ANN are implemented in a CFD flow solver code, to estimate mean values of the scalars. Results reveal that ANN yields good predictions and the computational time has decreased as compared to numerical integration for the estimation of mean thermo-chemical variables in the CFD code. Predicted thermo-chemical quantities are close to those from experimental measurements but some discrepancies exist, which are mainly due to the assumption of non-unity Lewis number in the calculations.

Adaptive closed‐loop control of cavity flows

Results from a combined experimental and computational study are presented on the development of an adaptive feedback controller for the suppression of cavity pressure loads. The experiments are performed in a variable‐sized cavity in a high‐speed wind tunnel, while the computations are performed using the CRAFT CFD flow solver. The adaptive control system incorporates recursive algorithms for system identification with disturbance rejection algorithms for feedback control. Results are presented using unsteady surface pressure sensors on the cavity walls and an array of zero‐net mass‐flux (ZNMF) actuators at the leading edge. The experimental data are used to compare with and validate the computations. These novel simulations form a virtual experiment testbed that is used to assess, for example, actuator type, placement, and requirements and also candidate identification and control algorithms.

Performance of a new CFD flow solver using a hybrid programming paradigm

This paper presents several algorithmic innovations and a hybrid programming style that lead to highly scalable performance using shared memory for a new computational fluid dynamics flow solver. This hybrid model is then converted to a strict message-passing implementation, and performance results for the two are compared. Results show that using this hybrid approach our OpenMP implementation is actually marginally faster than the MPI version, with parallel speedups of up to 599 out of 640 using OpenMP and 486 with MPI.

Probability-density function model of turbulent hydrogen flames

Hydrogen combustion attracted much attention recently because of the need for clean alternative energy. For the theoretical/numerical study of hydrogen combustion, there is a need for modeling capabilities for turbulent hydrogen flames. The present work examines the applicability of probability density function (pdf) turbulence models. For the purpose of accurate prediction of turbulent combustion, an algorithm that combines a conventional CFD flow solver with the Monte Carlo simulation of the pdf evolution equation, has been developed. The algorithm is validated using experimental data for a heated turbulent plane jet. A study of H 2–F 2 diffusion flames has been carried out using this algorithm. Numerical results show that the pdf method is capable of correctly simulating turbulence effects in hydrogen combustion.

Probability density function method for turbulent hydrogen flames

Hydrogen combustion attracted much attention recently because of the need for a clean alternative energy. For the theoretical/numerical study of hydrogen combustion, there is a need for modeling capabilities for turbulent hydrogen flames. The present work examines the applicability of probability density function (pdf) turbulence models. For the purpose of accurate prediction of turbulent combustion, an algorithm that combines a conventional CFD flow solver with the Monte Carlo simulation of the pdf evolution equation has been developed. The algorithm is validated using experimental data for a heated turbulent plane jet. A study of H 2–F 2 diffusion flames has been carried out using this algorithm. Numerical results show that the pdf method is capable of correctly simulating turbulence effects on hydrogen combustion. © 1999 International Association for Hydrogen Energy. Published by Elsevier Science Ltd. All rights reserved.

A PDE Sensitivity Equation Method for Optimal Aerodynamic Design

The use of gradient-based optimization algorithms in inverse design is well established as a practical approach to aerodynamic design. A typical procedure uses a simulation scheme to evaluate the objective function (from the approximate states) and its gradient, then passes this information to an optimization algorithm. Once the simulation scheme (CFD flow solver) has been selected and used to provide approximate function evaluations, there are several possible approaches to the problem of computing gradients. One popular method is to differentiate the simulation scheme and compute design sensitivities that are then used to obtain gradients. Although this black-box approach has many advantages in shape optimization problems, one must compute mesh sensitivities in order to compute the design sensitivity. In this paper, we present an alternative approach using the PDE sensitivity equation to develop algorithms for computing gradients. This approach has the advantage that mesh sensitivities need not be computed. Moreover, when it is possible to use the CFD scheme for both the forward problem and the sensitivity equation, then there are computational advantages. An apparent disadvantage of this approach is that it does not always produce consistent derivatives. However, for a proper combination of discretization schemes, one can showasymptotic consistencyunder mesh refinement, which is often sufficient to guarantee convergence of the optimal design algorithm. In particular, we show that when asymptotically consistent schemes are combined with a trust-region optimization algorithm, the resulting optimal design method converges. We denote this approach as thesensitivity equation method.The sensitivity equation method is presented, convergence results are given, and the approach is illustrated on two optimal design problems involving shocks.

96/01845 The influence of hydrodynamics on the performance of an interconnected fluidized bed system for regenerative desulfurization

The laminar flamelet concept is used in the prediction of mean reactive scalars in a non-premixed turbulent CH4/H2/N2 flame. First, a databank for temperature and species concentrations is developed from the solutions of counter-flow diffusion flames. The effects of flow field on flamelets are considered by using mixture fraction and scalar dissipation rate. Turbulence–chemistry interactions are taken into account by integrating different quantities based on a presumed probability density function (PDF), to calculate the Favre-averaged values of scalars. Flamelet library is then generated. To interpolate in the generated library, one artificial neural network (ANN) is trained where the mean and variance of mixture fraction and the scalar dissipation rate are used as inputs, and species mean mass fractions and temperature are selected as outputs. The weights and biases of this ANN are implemented in a CFD flow solver code, to estimate mean values of the scalars. Results reveal that ANN yields good predictions and the computational time has decreased as compared to numerical integration for the estimation of mean thermo-chemical variables in the CFD code. Predicted thermo-chemical quantities are close to those from experimental measurements but some discrepancies exist, which are mainly due to the assumption of non-unity Lewis number in the calculations.

95/03941 Palladium-catalyzed combustion of methane: Simulated gas turbine combustion at atmospheric pressure

The laminar flamelet concept is used in the prediction of mean reactive scalars in a non-premixed turbulent CH4/H2/N2 flame. First, a databank for temperature and species concentrations is developed from the solutions of counter-flow diffusion flames. The effects of flow field on flamelets are considered by using mixture fraction and scalar dissipation rate. Turbulence–chemistry interactions are taken into account by integrating different quantities based on a presumed probability density function (PDF), to calculate the Favre-averaged values of scalars. Flamelet library is then generated. To interpolate in the generated library, one artificial neural network (ANN) is trained where the mean and variance of mixture fraction and the scalar dissipation rate are used as inputs, and species mean mass fractions and temperature are selected as outputs. The weights and biases of this ANN are implemented in a CFD flow solver code, to estimate mean values of the scalars. Results reveal that ANN yields good predictions and the computational time has decreased as compared to numerical integration for the estimation of mean thermo-chemical variables in the CFD code. Predicted thermo-chemical quantities are close to those from experimental measurements but some discrepancies exist, which are mainly due to the assumption of non-unity Lewis number in the calculations.