scholarly journals GPU-accelerated CFD Simulations for Turbomachinery Design Optimization

2018 ◽  
Author(s):  
Mohamed Hassanine Aissa
Keyword(s):  
Design Optimization ◽  
Cfd Simulations ◽  
Turbomachinery Design

A Kriging-Simulated Annealing Meta-Algorithm for Optimization of Convective Heat Transfer in a Grooved Channel

2011 ◽  
Author(s):  
Sertac Cadirci ◽  
Alpay Akguc ◽  
Hasan Gunes
Keyword(s):  
Heat Transfer ◽  
Simulated Annealing ◽  
Design Optimization ◽  
Convective Heat Transfer ◽  
Convective Heat ◽  
Transfer Problem ◽  
Geometry Optimization ◽  
Constant Heat Flux ◽  
Design Tool ◽  
Cfd Simulations

As computational fluid dynamics (CFD) simulations still take a lot of time in industry for design optimization analyses, we propose to reduce the number of required CFD simulations considerably using a new meta-algorithm. The algorithm consists of employing kriging in conjunction with simulated annealing (SA) as a design tool. The method enables effective and fast design optimization for complex fluid flow systems. In this paper, it is applied to a convective heat transfer problem in a channel with periodic heat sources with constant heat flux. We show that the geometry optimization of two dimensional thermo-fluids problems in complex geometries is made more effective and faster using kriging-simulated annealing meta-algorithm.

Towards Orthogonal Turbomachinery Design

2006 ◽  
Author(s):  
Jerome P. Jarrett ◽  
Theo A. Bell ◽  
P. John Clarkson
Keyword(s):  
Design Optimization ◽  
Orthogonal Design ◽  
Pressure Rise ◽  
Global Optimum ◽  
Aviation Industry ◽  
Design Problems ◽  
Surge Margin ◽  
Design Changes ◽  
Engine Compressor ◽  
Turbomachinery Design

The aviation industry is under significant commercial and environmental pressure to produce a revolution in design. However, despite the significant advances in automatic design optimization made over the last 30 years, the industry is still largely conducting design by evolution. The complexity of a modern aeroengine encourages the separation of its conceptual from its detailed design: this limits the utility of powerful design optimization tools solving the “classical” optimization problem (of design space search for the global optimum) to the detailed designer who is more usually tasked with reaching a specification. One of the principal difficulties of modifying the design to reach a particular specified goal is that, though the desired improvement might be achieved, it often comes at unacceptable detriment to other performance indicators. We present results of our orthogonal design technique (that assists the designer in producing improvements in specific attributes of the design without penalty in other aspects) applied to the redesign of a generic core engine compressor for two “real-world” design problems: reducing the part count without aerodynamic penalty and increasing the efficiency without reduction in surge margin, pressure rise or mass flow. The two resulting designs, while meeting their constraints, exhibit a reduction in blading equivalent to two rotor rows and an increase in adiabatic efficiency of 1.0 percentage point respectively. The design changes which produce these improvements, together with how these compare with design rationale, are discussed.

Advances of Turbomachinery Design Optimization

2015 ◽  
Author(s):  
James H. Page ◽  
Rob Watson ◽  
Zaib Ali ◽  
Paul Hield ◽  
Paul G. Tucker
Keyword(s):  
Design Optimization ◽  
Turbomachinery Design

Truck Trailer Aerodynamic Design Optimization Through CFD Simulations

2020 ◽  
Author(s):  
Filipe Fabian Buscariolo ◽  
Felipe Magazoni ◽  
Leonardo José Della Volpe ◽  
Flavio Koiti Maruyama ◽  
Julio Cesar Lelis Alves
Keyword(s):  
Design Optimization ◽  
Aerodynamic Design ◽  
Cfd Simulations ◽  
Aerodynamic Design Optimization

scholarly journals Design Optimization of a Novel Receiving Cavity for Concentrated Solar Power Applications by Means of 3D CFD Simulations

2015 ◽  
Vol 69 ◽  
pp. 379-387 ◽  
Author(s):  
A. Gaetano ◽  
S.A. Zavattoni ◽  
M.C. Barbato ◽  
P. Good ◽  
G. Ambrosetti ◽  
...  
Keyword(s):  
Design Optimization ◽  
Solar Power ◽  
Concentrated Solar Power ◽  
Cfd Simulations

Turbomachinery Design Optimization Using Automatic Differentiated Adjoint Code

2007 ◽  
Author(s):  
Mihai C. Duta ◽  
Shahrokh Shahpar ◽  
Michael B. Giles
Keyword(s):  
Design Optimization ◽  
Adjoint Method ◽  
Automatic Differentiation ◽  
Nonlinear Flow ◽  
Flow Solver ◽  
Current State ◽  
Discrete Adjoint ◽  
Gradient Based ◽  
Turbomachinery Design ◽  
Objective Functional

The last decade has established the adjoint method as an effective way in Computational Fluid Dynamics of calculating the gradients of an objective functional in a large dimensional design space. This paper addresses the concerns that code developers face when creating a discrete adjoint computer program for design optimization, starting from a nonlinear flow solver and using Automatic Differentiation. Adjoint code development benefits greatly from using Automatic Differentiation but at its current state of maturity, this technology is best applied selectively rather than on entire codes. The paper discusses the practical aspects of using Automatic Differentiation on a large industrial turbomachinery flow solver with the objective of deriving efficient adjoint code. The use of the adjoint gradients is illustrated in an optimization exercise using gradient based methods on the NASA Rotor 37 public testcase.

Preliminary Aerodynamic Design of a S-CO2 Axial Turbine

2021 ◽  
Author(s):  
R. Senthil Kumaran ◽  
Dilipkumar B. Alone ◽  
Abdul Nassar ◽  
Pramod Kumar
Keyword(s):  
Mass Flow ◽  
Brayton Cycle ◽  
Cfd Simulations ◽  
Fluid Medium ◽  
Axial Turbine ◽  
Real Gas ◽  
Axial Turbines ◽  
Turbine Design ◽  
Turbomachinery Design ◽  
Line Design

Abstract Axial turbines are gaining prominence in supercritical carbon-di-oxide (S-CO2) Brayton cycle power blocks. S-CO2 Brayton cycle power systems designed for 10 MW and upwards will need axial turbines for efficient energy conversion and compact construction. The real gas behavior of S-CO2 and its rapid property variations with temperature presents a strong challenge for turbomachinery design. Applying gas and steam turbine philosophies directly to S-CO2 turbine could lead to erroneous designs. Very little information is available in the open literature on the design of S-CO2 axial turbines. In this paper, design of a 10 MW axial turbine for a simple recuperated Brayton cycle waste heat recovery system is presented. Three repeating stages with nominal stage loading coefficient of 2.3 and flow coefficient of 0.37 were designed. An axial turbine mean-line design method tuned to S-CO2 real gas fluid medium is discussed. 3D blade design was made suing commercial turbomachinery design software AxSTREAM. The turbine was designed for inlet temperature of 818.15 K, pressure ratio of 2.2, rotational speed of 12000 rpm and mass flow rate of 104.5 kg/s. 3D CFD simulations were carried out using the commercial RANS solver ANSYS CFX 2020 R2 with SST turbulence model for closure. S-CO2 was modelled as real gas with Refrigerant Gas Property tables generated over the appropriate pressure and temperature ranges using NIST Refprop database. CFD studies were carried out over a range of mass flow rates and speeds, covering the design and several off-design conditions. The performance maps generated using 3D CFD simulations of the turbine are presented. The geometrical parameters obtained with the mean-line design matched well with that of the 3D turbine design arrived using AxSTREAM. It was observed that the turbine produced 10 MW power at the design condition while passing the required mass flow. CFD studies also showed that the preliminary turbine design achieved a moderate total-to-total efficiency of 80 % at the design condition. The design has potential for further optimization to obtain improved efficiency and for reducing the number of stages from three to two.

On Noise Control in Turbomachinery Using an Automated Multidisciplinary Design Optimization System

2005 ◽  
Author(s):  
Uyigue Idahosa ◽  
Vladimir Golubev
Keyword(s):  
Design Optimization ◽  
High Speed ◽  
High Efficiency ◽  
Optimization Procedure ◽  
General Aviation ◽  
Response Analysis ◽  
Efficiency Performance ◽  
Gradient Based ◽  
Geometry Parameterization ◽  
Turbomachinery Design

In this work, we review our recent efforts to develop and apply an expanding database of aerodynamic and aeroacoustic prediction technologies for exploring new conceptual designs of propulsion system turbomachinery components optimized for high-efficiency performance with minimum noise radiation. In this context, we first discuss construction of our automated, distributed, industry-like multi-disciplinary design optimization (MDO) environment used in all the studies. The system was developed on the basis of commercially available optimization modules, and involves a user-friendly interface that provides an easy link to user-supplied response analysis modules. We address various issues in the automated optimization procedure with focus on turbomachinery design, including proper geometry parameterization, algorithms selection, and transparent interconnections between different elements of the optimization process. In a benchmark study testing the performance of the system in application to aero/acoustic optimization, we consider a problem of optimal blade design to minimize fan noise, a dominant source of sound radiation both in high-speed fan applications (such as high-bypass-ratio turbofans, propellers of turboprop and IC engines in general aviation, and helicopter rotors) and low-speed ones (including applications in automotive, computer, air-conditioning and other industries). Two approaches are investigated, with the first relying on commercial CFD software coupled with an unstructured mesh generator, and the second employing a panel-based aerodynamic code integrated with an integral acoustic solver. Success of various optimization algorithms (including gradient-based and evolutionary) in finding global minima of the objective function for a noise metric in both unconstrained and constrained optimization processes is examined.

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