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Languages : en
Pages : 14
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A method is presented to perform aerodynamic design optimization of turbomachinery blades. The method couples a Navier-Stokes flow solver with a grid generator and numerical optimization algorithm to seek improved designs for transonic turbine blades. A fast and efficient multigrid, finite-volume flow solver provides accurate performance evaluations of potential designs. Design variables consist of smooth perturbations to the blade surface. A unique elliptic-hyperbolic grid generation method is used to regenerate a Navier-Stokes grid after perturbations have been added to the geometry. Designs are sought which improve a design objective while remaining within specified constraints. The method is demonstrated with two transonic turbine blades with different types and numbers of design variables.
Author:
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Category :
Languages : en
Pages : 14
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Book Description
A method is presented to perform aerodynamic design optimization of turbomachinery blades. The method couples a Navier-Stokes flow solver with a grid generator and numerical optimization algorithm to seek improved designs for transonic turbine blades. A fast and efficient multigrid, finite-volume flow solver provides accurate performance evaluations of potential designs. Design variables consist of smooth perturbations to the blade surface. A unique elliptic-hyperbolic grid generation method is used to regenerate a Navier-Stokes grid after perturbations have been added to the geometry. Designs are sought which improve a design objective while remaining within specified constraints. The method is demonstrated with two transonic turbine blades with different types and numbers of design variables.
Author: K. K. Chand
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Category :
Languages : en
Pages :
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Author: S. Shahpar
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Category : Applied mathematics
Languages : en
Pages :
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Author: Temesgen Teklemariam Mengistu
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Category : Aerodynamics
Languages : en
Pages : 0
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Aerodynamic shape optimization of gas turbine blades is a very challenging task, given e.g. the flow complexity, the stringent performance requirements, the structural and manufacturing constraints, etc ... This work addresses the challenge by automating the optimization process through the development, implementation and integration of state-of-the-art shape parametrization, numerical optimization methods, Computational Fluid Dynamics (CFD) algorithms and computer architectures. The resulting scheme is successfully applied to single and multi-point aerodynamic shape optimization of several cascades involving two-dimensional transonic and subsonic, viscous and inviscid flow in compressor and turbine cascades. The optimization objective is to achieve a better aerodynamic performance, subject to aerodynamic and structural constraints, over the full operating range of gas turbine cascades by varying the blade profile. That profile is parameterized using a Non-Uniform Rational B-Splines (NURBS) representation, which is flexible accurate and capable of representing the blade profiles with a relatively small number of control points for a given tolerance. The NURBS parameters are then used as design variables in the optimization process. The optimization objective is determined from simulating the flow using an in-house CFD code that solves the two-dimensional Reynolds-Averaged Navier-Stokes (or Euler) equations using a cell-vertex finite volume method on an unstructured triangular mesh and turbulence is modeled using the Baldwin-Lomax model. To save computing time significantly, Artificial Neural Network (ANN) is used to build a low fidelity model that approximates the optimization objective and constraints. Moreover, to reduce the computing wall-clock time, the optimization scheme was parallelized on an SGI ALTIX 3700 machine using Message Passing Interface (MPI), resulting in a parallelization efficiency of almost 100%. Different numerical optimization methods (genetic algorithm, simulated annealing and sequential quadratic programming) were developed, tested and implemented for the different parts of this work. The present choice of objective function and optimization methodology results in a significant improvement in performance for all the cascades that were optimized, without violating the design constraints. The use of ANN results in a ten-fold speed-up of the design process and the scheme parallelization allows for further reduction of the wall-clock time.
Author: Kwang-Yong Kim
Publisher: John Wiley & Sons
ISBN: 1119188326
Category : Science
Languages : en
Pages : 312
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Design Optimization of Fluid Machinery: Applying Computational Fluid Dynamics and Numerical Optimization Drawing on extensive research and experience, this timely reference brings together numerical optimization methods for fluid machinery and its key industrial applications. It logically lays out the context required to understand computational fluid dynamics by introducing the basics of fluid mechanics, fluid machines and their components. Readers are then introduced to single and multi-objective optimization methods, automated optimization, surrogate models, and evolutionary algorithms. Finally, design approaches and applications in the areas of pumps, turbines, compressors, and other fluid machinery systems are clearly explained, with special emphasis on renewable energy systems. Written by an international team of leading experts in the field Brings together optimization methods using computational fluid dynamics for fluid machinery in one handy reference Features industrially important applications, with key sections on renewable energy systems Design Optimization of Fluid Machinery is an essential guide for graduate students, researchers, engineers working in fluid machinery and its optimization methods. It is a comprehensive reference text for advanced students in mechanical engineering and related fields of fluid dynamics and aerospace engineering.
Author: Stephane Pierret
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ISBN:
Category :
Languages : en
Pages : 0
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Presented at the International Gas Turbine & Aeroengine Congress & Exhibition, Stockholm, Sweden, June 2 - June 5, 1998.
Author: Seyyed Arash Mousavi
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Category :
Languages : en
Pages :
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"This research work presents an adjoint approach to optimize the aero-thermalproperties of gas turbine blades. The flow solver is a Reynolds-Averaged Navier-Stokes code applicable to structured grids. The flow governing equations are discretizedusing a second-order finite-volume scheme and for artificial dissipation, theJameson-Schmidt-Turkel (JST) scheme is applied in order to accurately capture theflow discontinuities. The code uses a five-stage modified Runge-Kutta explicit temporaldiscretisation and utilizes the multigrid method, residual smoothing and thelocal time stepping for convergence acceleration.A loosely coupled conjugate heat transfer (CHT) method is applied to considerthe effect of the internal convective cooling and obtain the fluid-solid interface temperatureat the blade surface. A finite-element solver is developed to solve the energyequation in the solid domain and the governing equation is solved by implementingthe weak-Galerkin finite-element discretization scheme where an unstructured lineartriangular mesh is adopted for the solution domain. The temperature at the solid andfluid interface is computed through an iterative exchange of the boundary conditionsacross the interface using the Flux Forward Temperature Back (FFTB) method. Forexternally cooled blades, a source term injection model is implemented to model theeffect of external cooling on the blade surface heat transfer.The optimization procedure is gradient-based and the blade shape optimizationis accomplished through SNOPT, a sequential-quadratic programming package thatis capable of automatically handling the linear and/or non-linear flow and geometric constraints. To efficiently calculate the gradients, a continuous adjoint method isemployed and in order to be consistent with the flow boundary condition, a characteristicbased approach is utilized in developing the adjoint boundary conditions.The flow solver is validated for several benchmark turbomachinery cascades.The optimization procedure is applied to several inviscid and viscous turbine andcompressor blades to enhance the aerodynamic and/or thermal performance. Thedeveloped optimization algorithm is demonstrated to be efficient in terms of computationaltime and accuracy for the optimization of two-dimensional turbomachinerycases where it provides promising results in reducing the desired objective functionswhile respecting the imposed flow and geometric constraints." --
Author: Kwang-Yong Kim
Publisher: John Wiley & Sons
ISBN: 1119188296
Category : Science
Languages : en
Pages : 305
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Book Description
Design Optimization of Fluid Machinery: Applying Computational Fluid Dynamics and Numerical Optimization Drawing on extensive research and experience, this timely reference brings together numerical optimization methods for fluid machinery and its key industrial applications. It logically lays out the context required to understand computational fluid dynamics by introducing the basics of fluid mechanics, fluid machines and their components. Readers are then introduced to single and multi-objective optimization methods, automated optimization, surrogate models, and evolutionary algorithms. Finally, design approaches and applications in the areas of pumps, turbines, compressors, and other fluid machinery systems are clearly explained, with special emphasis on renewable energy systems. Written by an international team of leading experts in the field Brings together optimization methods using computational fluid dynamics for fluid machinery in one handy reference Features industrially important applications, with key sections on renewable energy systems Design Optimization of Fluid Machinery is an essential guide for graduate students, researchers, engineers working in fluid machinery and its optimization methods. It is a comprehensive reference text for advanced students in mechanical engineering and related fields of fluid dynamics and aerospace engineering.
Author: Xiaomin Chen (Mechanical engineer)
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages : 164
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Shape optimization is widely used in the design of wind turbine blades. In this dissertation, a numerical optimization method called Genetic Algorithm (GA) is applied to address the shape optimization of wind turbine airfoils and blades. In recent years, the airfoil sections with blunt trailing edge (called flatback airfoils) have been proposed for the inboard regions of large wind-turbine blades because they provide several structural and aerodynamic performance advantages. The FX, DU and NACA 64 series airfoils are thick airfoils widely used for wind turbine blade application. They have several advantages in meeting the intrinsic requirements for wind turbines in terms of design point, off-design capabilities and structural properties. This research employ both single- and multi-objective genetic algorithms (SOGA and MOGA) for shape optimization of Flatback, FX, DU and NACA 64 series airfoils to achieve maximum lift and/or maximum lift to drag ratio. The commercially available software FLUENT is employed for calculation of the flow field using the Reynolds-Averaged Navier-Stokes (RANS) equations in conjunction with a two-equation Shear Stress Transport (SST) turbulence model and a three equation k-kl-[omega] turbulence model. The optimization methodology is validated by an optimization study of subsonic and transonic airfoils (NACA0012 and RAE 2822 airfoils). All the optimization results have demonstrated that the GA technique can be employed efficiently and accurately to produce globally optimal airfoils with excellent aerodynamic properties using a desired objective value (minimum Cd and/or maximum Cl /Cd). It is also shown that the multi-objective genetic algorithm based optimization can generate superior airfoils compared to those obtained by using the single objective genetic algorithm. The applications of thick airfoils are extended to the assessment of wind turbine performance. It is well established that the power generated by a Horizontal-Axis Wind Turbine (HAWT) is a function of the number of blades B, the tip speed ratio [lambda] (blade tip speed/wind free stream velocity) and the lift to drag ratio (Cl /Cd) of the airfoil sections of the blade. The airfoil sections used in HAWT are generally thick airfoils such as the S, DU, FX, Flat-back and NACA 6-series of airfoils. These airfoils vary in (Cl /Cd) for a given B and [lambda], and therefore the power generated by HAWT for different blade airfoil sections will vary. Another goal of this study is to evaluate the effect of different airfoil sections on HAWT performance using the Blade Element Momentum (BEM) theory. In this dissertation, we employ DU 91-W2-250, FX 66-S196-V1, NACA 64421, and Flat-back series of airfoils (FB-3500-0050, FB-3500-0875, and FB-3500-1750) and compare their performance with S809 airfoil used in NREL Phase II and III wind turbines; the lift and drag coefficient data for these airfoils sections are available. The output power of the turbine is calculated using these airfoil section blades for a given B and [lambda] and is compared with the original NREL Phase II and Phase III turbines using S809 airfoil section. It is shown that by a suitable choice of airfoil section of HAWT blade, the power generated by the turbine can be significantly increased. Parametric studies are also conducted by varying the turbine diameter. In addition, a simplified dynamic inflow model is integrated into the BEM theory. It is shown that the improved BEM theory has superior performance in capturing the instantaneous behavior of wind turbines due to the existence of wind turbine wake or temporal variations in wind velocity. The dissertation also considers the Wind Farm layout optimization problem using a genetic algorithm. Both the Horizontal -Axis Wind Turbines (HAWT) and Vertical-Axis Wind Turbines (VAWT) are considered. The goal of the optimization problem is to optimally position the turbines within the wind farm such that the wake effects are minimized and the power production is maximized. The reasonably accurate modeling of the turbine wake is critical in determination of the optimal layout of the turbines and the power generated. For HAWT, two wake models are considered; both are found to give similar answers. For VAWT, a very simple wake model is employed. Finally, some preliminary investigation of shape optimization of 3D wind turbine blades at low Reynolds numbers is conducted. The optimization employs a 3D straight untapered wind turbine blade with cross section of NACA 0012 airfoils as the geometry of baseline blade. The optimization objective is to achieve maximum Cl /Cd as well as maximum Cl. The multi-objective genetic algorithm is employed together with the commercially available software FLUENT for calculation of the flow field using the Reynolds-Averaged Navier-Stokes (RANS) equations in conjunction with a one-equation Sparlart-Allmaras turbulence model. The results show excellent performance of the optimized wind turbine blade and indicate the feasibility of optimization on real wind turbine blades with more complex shapes in the future.
Author: S. Pierret
Publisher:
ISBN:
Category :
Languages : en
Pages : 10
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