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Author: Temesgen Teklemariam Mengistu
Publisher:
ISBN:
Category : Aerodynamics
Languages : en
Pages : 0
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Book Description
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: Temesgen Teklemariam Mengistu
Publisher:
ISBN:
Category : Aerodynamics
Languages : en
Pages : 0
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Book Description
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: Naixing Chen
Publisher: John Wiley & Sons
ISBN: 0470825014
Category : Science
Languages : en
Pages : 448
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Book Description
Computational Fluid Dynamics (CFD) is now an essential and effective tool used in the design of all types of turbomachine, and this topic constitutes the main theme of this book. With over 50 years of experience in the field of aerodynamics, Professor Naixing Chen has developed a wide range of numerical methods covering almost the entire spectrum of turbomachinery applications. Moreover, he has also made significant contributions to practical experiments and real-life designs. The book focuses on rigorous mathematical derivation of the equations governing flow and detailed descriptions of the numerical methods used to solve the equations. Numerous applications of the methods to different types of turbomachine are given and, in many cases, the numerical results are compared to experimental measurements. These comparisons illustrate the strengths and weaknesses of the methods – a useful guide for readers. Lessons for the design of improved blading are also indicated after many applications. Presents real-world perspective to the past, present and future concern in turbomachinery Covers direct and inverse solutions with theoretical and practical aspects Demonstrates huge application background in China Supplementary instructional materials are available on the companion website Aerothermodynamics of Turbomachinery: Analysis and Design is ideal for senior undergraduates and graduates studying in the fields of mechanics, energy and power, and aerospace engineering; design engineers in the business of manufacturing compressors, steam and gas turbines; and research engineers and scientists working in the areas of fluid mechanics, aerodynamics, and heat transfer. Supplementary lecture materials for instructors are available at www.wiley.com/go/chenturbo
Author: Yi-Lung Yang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Yi-Lung Yang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Massachusetts Institute of Technology. Gas Turbine Laboratory
Publisher:
ISBN:
Category :
Languages : en
Pages : 65
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Author:
Publisher:
ISBN:
Category : Mechanical engineering
Languages : en
Pages : 205
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Author: Vadivel Kumaran Sivashanmugam
Publisher:
ISBN:
Category :
Languages : en
Pages : 122
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Book Description
Aero-structural optimization of gas turbine blades is a very challenging task, given e.g. three dimensional nature of the flow, stringent performance requirements, structural and manufacturing considerations, etc. The current research work addresses this challenge by development and implementation of structural shape optimization module and integrating it with an aerodynamic shape optimization module to form an automated aero-structural optimization procedure. The optimizer combines a Multi-Objective Genetic Algorithm (MOGA), with a Response Surface Approximation (RSA) of the Artificial Neural Network (ANN) type. During the optimization process, each objective function and constraint is approximated by an individual ANN, which is trained and tested using an aerodynamic as well as a structure database composed of a few high fidelity flow simulations (CFD) and structure analysis (CSD) that are obtained using ANSYS Workbench 11.0. Addition of this multiple ANN technique to the optimizer greatly improves the accuracy of the RSA, provides control over handling different design variables and disciplines. The described methodology is then applied to the aero-structural optimization of the E/TU-3 turbine blade row and stage at design conditions to improve the aerodynamic and structural performance of the turbomachinery blades by optimizing the stacking curve. The proposed methodology proved quite successful, flexible and practical with significant increase in stage efficiency and decrease in equivalent stress.
Author: Kasra Daneshkhah
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
An inverse blade design method, applicable to 2D and 3D flow in turbomachinery blading is developed and is implemented for the design of 2D cascades in compressible viscous flow. The prescribed design quantities are either the pressure distributions on the blade suction and pressure surfaces or the blade pressure loading and its thickness distribution. The design scheme is based on a wall movement approach where the blade walls are modified based on a virtual velocity distribution that would make the current and target momentum fluxes balance on the blade suction and pressure surfaces. The virtual velocity is used to drive the blade geometry towards a steady state shape corresponding to the prescribed quantities. The design method is implemented in a consistent manner into the unsteady Reynolds Averaged Navier-Stokes (RANS) equations, where an arbitrary Lagrangian-Eulerian (ALE) formulation is used and the boundaries of the computational domain can move and deform in any prescribed time-varying fashion to accommodate the blade movement. A cell vertex finite volume method is used for discretizing the governing equations in space and, at each physical time level, integration in pseudotime is performed using an explicit Runge-Kutta scheme, where local time stepping and residual smoothing are used for convergence acceleration. For design calculations, which are inherently unsteady due to blade movement, the time accuracy of the solution is achieved by means of a dual time stepping scheme. An algebraic Baldwin-Lomax model is used for turbulence closure. The flow analysis method is applied to several test cases for steady state internal flow in linear cascades and the results are compared to numerical and experimental data available in the literature. The inverse design method is first validated for three different configurations, namely a parabolic cascade, a subsonic compressor cascade and a transonic impulse turbine cascade, where different choices of the prescribed design variables are used. The usefulness, robustness, accuracy, and flexibility of this inverse method are then demonstrated on the design of an ONERA transonic compressor cascade, a NACA transonic compressor cascade, a highly cambered DFVLR subsonic turbine cascade, and a VKI transonic turbine cascade geometries, which are typical of gas turbine blades used in modern gas turbine engines.
Author: L. Griffin
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author:
Publisher:
ISBN:
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.
