ECS System Simulation - Architecture and Performance Optimization from the Early Phases of the System Design
This case study from Alenia Aermacchi’s Environmental Control System (ECS) department shows how the different design disciplines involved are handled effectively through process integration and automation, enabling the optimization of the overall performance from the early stages of system design.
Multi-objective ship hull form optimization using a free surface RANSE solver
In this work a multi-objective optimization procedure for resistance based on a free surface RANSE code is presented. This procedure is made practical by the use of a specific hull shape modeler and numerical restart methods, the effectiveness of the procedure has been demonstrated on an example supported by model test results.
A strategy for optimization problems involving complex CFD simulations
In this presentation significant reduction on the processing time was observed for the test case presented. With the new optimization tool there is less need for advanced computational resources that can be used during the optimization phase. Addictive corrections improve accuracy, in an adaptive way. As correction functions are updated, all low fidelity results remain valid (just need to use the new correction value).
Automatic optimization of the Sulzer CompaX™ mixer as part of the design process
The proceeding presents the automatic optimization of the Sulzer CompaX™ mixer as part of the design process
Design of a Low Shear Hydrofoil through the use of Computational Fluid Dynamics and Multi-Objective Design Optimization
The presentation focuses on the design of a low shear hydrofoil through the use of computational fluid dynamics and multi-objective design optimization
Multi Objective Optimization of an industrial oven's fan with CAD-CAO methodology
The study deal with Multi-Disciplinary integration and Multi Objective Optimization of a industrial oven fan, in particular CATIA V5 has been used for the parametrization of the model, ANSYS ICEM CFD and CFX 5.6 has been used respectively for the mesh generation and for the fluid dynamic solution. Finally modeFrontier is used to link each others all the programs and to get the optimal solutions.
Game Theory Optimisation with CAD in the loop for CFD application
In the following presentation a parametric model of a 3D wing has been prepared using Catia v5, here a modular program links and steers Catia, mesh generator, flow solver and the optimization algorithm in an automated way. Furthermore, different multi-objective algorithms have been tested (and 3D case), in particular algorithms based on Game Theory and EA.
Optimization methodologies applied to the design of a gas turbine cooling system
The multi-objective optimization techniques were applied to a three-dimensional CFD model for the design of the cooling system of a gas turbine blade tip.A parametric CFD model of a high pressure rotor blade was developed in order to study the cooling efficiency in the tip area.
Optimisation techniques applied to the design of a gas turbine cooling system
In this proceeding a novel methodology was used to design the layout of the tip cooling nozzles of a high pressure rotor blade turbine. The methodology used is a complete CAE approach, by means of a parametric CFD model which was run many times for the exploration of several designs by an optimizer.The final design of the tip cooling geometry found by the optimizer proved to be better than the base design (which used mean values of all input parameters) and also better than the design proposed by an experienced heat transfer AVIO engineer, who used standard best practice methods.
Numerical Prediction of the Cavitating Flow Around Model Scale Propellers by CFD and Advanced Model Calibration
Cavitating flows, which can occur in a variety of practical applications, can be modelled using a wide range of methods. One strategy consists of using the RANS (Reynolds Averaged Navier Stokes) approach along with an additional transport equation for the liquid volume fraction, where mass transfer rate due to cavitation is modelled by a mass transfer model.