Design of High Performing Duct-Burners for Combined-Cycle Plants Using Progressive Optimization

2002 ◽  
Author(s):  
L. A. Catalano ◽  
A. Dadone ◽  
D. Manodoro
Keyword(s):  
Design Optimization ◽  
Flow Analysis ◽  
Combined Cycle ◽  
Inverse Design ◽  
Optimization Process ◽  
Computational Time ◽  
Optimization Strategy ◽  
High Performing ◽  
Commercial Code ◽  
Progressive Optimization

A general efficient strategy for the design optimization of duct-burners for combined-cycle plants is presented. This methodology combines a widely employed commercial code, used for the flow analysis, with a progressive optimization strategy, whose efficiency relies on the simultaneous convergence of both the flow solution and the optimization process, as well as on the use of progressively finer grid levels. The proposed strategy has been initially tested versus two inverse design examples with known solutions; then, it has been employed to flatten the outlet thermal profile of a new enhanced-mixing after-burner. The presented results show that the overall optimization process requires a computational time compared to that required by 5 ÷ 14 flow analyses.

Combustor Design Optimization Using Co-Kriging of Steady and Unsteady Turbulent Combustion

2011 ◽  
Vol 133 (12) ◽  
Author(s):  
Moresh J. Wankhede ◽  
Neil W. Bressloff ◽  
Andy J. Keane
Keyword(s):  
Design Optimization ◽  
Optimization Process ◽  
Design Stage ◽  
Reacting Flow ◽  
High Fidelity ◽  
Optimization Strategy ◽  
Function Calls ◽  
Unsteady Rans ◽  
Computational Budget ◽  
High Level

In the gas turbine industry, computational fluid dynamics (CFD) simulations are often used to predict and visualize the complex reacting flow dynamics, combustion environment and emissions performance of a combustor at the design stage. Given the complexity involved in obtaining accurate flow predictions and due to the expensive nature of simulations, conventional techniques for CFD based combustor design optimization are often ruled out, primarily due to the limits on available computing resources and time. The design optimization process normally requires a large number of analyses of the objective and constraint functions which necessitates a careful selection of fast, reliable and efficient computational methods for the CFD analysis and the optimization process. In this study, given a fixed computational budget, an assessment of a co-Kriging based optimization strategy against a standard Kriging based optimization strategy is presented for the design of a 2D combustor using steady and unsteady Reynolds-averaged Navier Stokes (RANS) formulation. Within the fixed computational budget, using a steady RANS formulation, the Kriging strategy successfully captures the underlying response; however with unsteady RANS the Kriging strategy fails to capture the underlying response due to the existence of a high level of noise. The co-Kriging strategy is then applied to two design problems, one using two levels of grid resolutions in a steady RANS formulation and the other using steady and unsteady RANS formulations on the same grid resolution. With the co-Kriging strategy, the multifidelity analysis is expected to find an optimum design in comparatively less time than that required using the high-fidelity model alone since less high-fidelity function calls should be required. However, using the applied computational setup for co-Kriging, the Kriging strategy beats the co-Kriging strategy under the steady RANS formulation whereas under the unsteady RANS formulation, the high level of noise stalls the co-Kriging optimization process.

scholarly journals Turbine cascade design via multigrid-aided finite-difference progressive optimization

2008 ◽  
pp. 199-215
Author(s):  
Luciano A. Catalano ◽  
Andrea Dadone ◽  
Vito S.E. Daloiso
Keyword(s):  
Design Optimization ◽  
Stokes Equations ◽  
Flow Analysis ◽  
Navier Stokes ◽  
Computational Time ◽  
Turbine Cascade ◽  
Navier Stokes Equations ◽  
Fine Mesh ◽  
Sensitivity Derivatives ◽  
Volume Method

This paper proposes an efficient and robust procedure for the design optimization of turbomachinery cascades in inviscid and turbulent transonic flow conditions. It employs a progressive strategy, based on the simultaneous convergence of the design process and of all iterative solutions involved (flow analysis, gradient evaluation), also including the global refinement from a coarse to a sufficiently fine mesh. Cheap, flexible and easy-to-program Multigrid-Aided Finite Differences are employed for the computation of the sensitivity derivatives. The entire approach is combined with an upwind finite-volume method for the Euler and the Navier-Stokes equations on cell-vertex unstructured (triangular) grids, and validated versus the inverse design of a turbine cascade. The methodology turns out to be robust and highly efficient, the converged design optimization being obtained in a computational time equal to that required by 15 to 20 (depending on the application) multigrid flow analyses on the finest grid.

Shape-design optimization of hull structures considering thermal deformation

2013 ◽  
Vol 228 (13) ◽  
pp. 2266-2277
Author(s):  
Myung-Jin Choi ◽  
Min-Geun Kim ◽  
Seonho Cho
Keyword(s):  
Optimal Design ◽  
Design Optimization ◽  
Thermal Deformation ◽  
Parametric Design ◽  
Optimization Method ◽  
Optimization Process ◽  
Design Parameters ◽  
Shape Design ◽  
Shape Design Optimization ◽  
Modified Method

We developed a shape-design optimization method for the thermo-elastoplasticity problems that are applicable to the welding or thermal deformation of hull structures. The point is to determine the shape-design parameters such that the deformed shape after welding fits very well to a desired design. The geometric parameters of curved surfaces are selected as the design parameters. The shell finite elements, forward finite difference sensitivity, modified method of feasible direction algorithm and a programming language ANSYS Parametric Design Language in the established code ANSYS are employed in the shape optimization. The objective function is the weighted summation of differences between the deformed and the target geometries. The proposed method is effective even though new design variables are added to the design space during the optimization process since the multiple steps of design optimization are used during the whole optimization process. To obtain the better optimal design, the weights are determined for the next design optimization, based on the previous optimal results. Numerical examples demonstrate that the localized severe deviations from the target design are effectively prevented in the optimal design.

Design Optimization of Cryogenic Pump Inducer Considering Suction Performance and Cavitation Instability

2011 ◽  
Author(s):  
Hiroyoshi Watanabe ◽  
Hiroshi Tsukamoto
Keyword(s):  
Pressure Distribution ◽  
Design Optimization ◽  
Surface Pressure ◽  
Design Approach ◽  
Inverse Design ◽  
Blade Surface ◽  
Free Vortex ◽  
Surface Pressure Distribution ◽  
Cavitation Instability ◽  
Suction Performance

This paper presents the result of design optimization for three-bladed pump inducer using a three-dimensional (3-D) inverse design approach, Computational Fluid Dynamics (CFD) and DoE (Design of Experiments) taking suction performance and cavitation instability into consideration. The parameters to control streamwise blade loading distribution and spanwise work (free vortex or non-free vortex) for inducer were chosen as design optimization variables for the inverse design approach. Cavitating and non-cavitating performances for inducers designed using the design variables arranged in the DoE table were analyzed by steady CFD. Objective functions for non-cavitating operating conditions were the head and efficiency of inducers at a design flow (Qd), 80% Qd and 120% Qd. The volume of the inducer cavity region with a void ratio above 50% was selected as the objective function for inducer suction performance. In order to evaluate cavitation instability by steady CFD, the dispersion of the blade surface pressure distribution on each blade was selected as the evaluation parameter. This dispersion of the blade surface pressure distribution was caused by non-uniformity in the cavitation length that was developed on each inducer blade and increased when the cavitation number was reduced. The effective design parameters on suction performance and cavitation instability were confirmed by sensitivity analysis during the design optimization process. Inducers with specific characteristics (stable, unstable) designed using the effective parameters were evaluated through experiments.

scholarly journals Multidisciplinary design optimization of hard rock tunnel boring machine using collaborative optimization

2018 ◽  
Vol 10 (1) ◽  
pp. 168781401875472 ◽  
Author(s):  
Wei Sun ◽  
Xiaobang Wang ◽  
Maolin Shi ◽  
Zhuqing Wang ◽  
Xueguan Song
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Hard Rock ◽  
Tunnel Boring Machine ◽  
Collaborative Optimization ◽  
Optimization Process ◽  
Multidisciplinary Design ◽  
Tunnel Boring ◽  
Geological Conditions ◽  
Rock Tunnel

A multidisciplinary design optimization model is developed in this article to optimize the performance of the hard rock tunnel boring machine using the collaborative optimization architecture. Tunnel boring machine is a complex engineering equipment with many subsystems coupled. In the established multidisciplinary design optimization process of this article, four subsystems are taken into account, which belong to different sub-disciplines/subsytems: the cutterhead system, the thrust system, the cutterhead driving system, and the economic model. The technology models of tunnel boring machine’s subsystems are build and the optimization objective of the multidisciplinary design optimization is to minimize the construction period from the system level of the hard rock tunnel boring machine. To further analyze the established multidisciplinary design optimization, the correlation between the design variables and the tunnel boring machine’s performance is also explored. Results indicate that the multidisciplinary design optimization process has significantly improved the performance of the tunnel boring machine. Based on the optimization results, another two excavating processes under different geological conditions are also optimized complementally using the collaborative optimization architecture, and the corresponding optimum performance of the hard rock tunnel boring machine, such as the cost and energy consumption, is compared and analysed. Results demonstrate that the proposed multidisciplinary design optimization method for tunnel boring machine is reliable and flexible while dealing with different geological conditions in practical engineering.

scholarly journals Comparison of Solvers Performance for Load Flow Analysis

2019 ◽  
Vol 3 (1) ◽  
pp. 26 ◽  
Author(s):  
Vishnu Sidaarth Suresh
Keyword(s):  
Steady State ◽  
Power System ◽  
Reactive Power ◽  
Flow Analysis ◽  
Steady State Solution ◽  
Load Flow ◽  
State Solution ◽  
Computational Time ◽  
Load Flow Analysis ◽  
Active And Reactive Power

Load flow studies are carried out in order to find a steady state solution of a power system network. It is done to continuously monitor the system and decide upon future expansion of the system. The parameters of the system monitored are voltage magnitude, voltage angle, active and reactive power. This paper presents techniques used in order to obtain such parameters for a standard IEEE – 30 bus and IEEE-57 bus network and makes a comparison into the differences with regard to computational time and effectiveness of each solver

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