modeFRONTIER™ at SAE 2008 World Congress

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modeFRONTIER™ at SAE 2008 World Congress

By clicking on the website of the world-wide biggest event in automotive engineering, the SAE World Congress and searching for modeFRONTIER™ you will find out a number of papers that directly refernce modeFRONTIER™. Out of these 10 are related to SAE2008 that will be held in Detroit on 14th-15th April 2008 making modeFRONTIER™ the most referenced optimization and process integration software during the 2008 edition of SAE.

We can report the four abstract related to papers where ESTECO personnel was directly involved but we look forward to see the results obtained by our users in the other papers. Our suspect is that modeFRONTIER™ is also behind many other published work but we cannot say this until we will see it. It will be a pleasure to listen and learn from our customers during SAE2008.

Paper Number 2008-01-0874
Self Organizing Maps (SOM) for Design Selection in Multi-Objective Optimization using modeFRONTIER™
Sumeet Parashar, Nader Fateh - ESTECO North America Inc., Livonia, MI
Valentino Pediroda, Carlo Poloni - University of Trieste, Trieste, Italy
Copyright © 2007 SAE International

ABSTRACT
Self Organizing Maps (SOM) has evolved as a very useful visualization and data analysis tool for high dimensional data. Visualization and analysis of Pareto data for multi-objective optimization problems with more than three objectives is also a challenge. This paper will investigate the application of SOM for visualization and design selection for multi-objective Pareto data. The SOM is applied to investigate the spread of Pareto front as well as to investigate trade-off between objectives. The visualization and selection strategy is applied to mathematical test problem to explain the concept. Later it is also applied to real world automotive design problem of engine optimization.

Paper Number 2008-01-1429
Efficient Stochastic Optimization using Chaos Collocation method with modeFRONTIER™
Valentino Pediroda, Lucia Parussini, Carlo Poloni - University of Trieste, Italy
Sumeet Parashar, Nader Fateh - ESTECO North America Inc, Livonia, MI
Mauro Poian - ESTECO srl, Trieste, Italy
Copyright © 2007 SAE International

ABSTRACT
Robust Design Optimization (RDO) using traditional approaches such as Monte Carlo (MC) sampling requires tremendous computational expense. Performing a RDO for problems involving time consuming CAE analysis may not even be possible within time constraints. In this paper a new stochastic modeling technique based on chaos collocation method is used to measure the mean and standard deviation (σ) for uncertain output parameters. For a given accuracy, chaos collocation method requires far less sample evaluations compared to MC. The efficient evaluation of mean and std. deviation terms using chaos collocation method makes it quite attractive to be used with RDO methods. In this work the RDO of an automotive engine design is performed employing chaos collocation method. The solution strategy is implemented in commercial Process Integration and Design Optimization (PIDO) software tool modeFRONTIER™. modeFRONTIER™ provides a very effective environment to apply multi-objective optimization algorithms to various CAE or in-house analysis and simulation tools. The engine design simulations were performed using GT-Power through modeFRONTIER™. The chaos collocation method is coded in MATLAB scripts that are also invoked through modeFRONTIER™. The rest of the paper covers an introduction describing the motivation and challenges. The chaos collocation method is described followed by a description of it's application through modeFRONTIER™. The engine design optimization problem is explained followed by a discussion of RDO results.

Paper Number 2008-01-0871
Game Theory Approach to Engine Performance Optimization
Nader Fateh, Sumeet Parashar - ESTECO North America Inc., Livonia, MI
John Silvestri - Gamma Technologies Inc., Westmont, IL
Copyright © 2007 SAE International

ABSTRACT
Genetic Algorithms have proved to be very useful as global search methods for multi-dimensional optimization problems. One drawback, however, is that they are inefficient from the point of view of the number of function evaluations. This paper presents a two phase approach to optimization, using Game Theory in an initial step which provides a family of designs which are close to the Pareto frontier. The starting population for the genetic algorithm is then selected from the non-dominated designs produced in the first phase. This ensures that the genetic algorithm starts with a population of points which are already optimized to a large degree.

Paper Number 2008-01-0886
Multi-objective Optimization of a Charge Air Cooler using modeFRONTIER™
Phil Stephenson, Yang Chen - BEHR America Inc., Troy, MI
Nader Fateh, Sumeet Parashar - ESTECO North America Inc., Livonia, MI
Mauro Poian - ESTECO srl, Trieste, Italy
Copyright © 2007 SAE International

ABSTRACT In order for an automotive charge air cooler (CAC) to function efficiently, the flow of air through the cross tubes should be as uniform as possible. The position of the inlet and outlet, as well as the shape of the header tanks, are generally the most important determinants of the flow uniformity, and therefore of the cooling performance of the system. In an attempt to achieve this goal of flow uniformity, however, the effect on pressure loss in the system must also be considered. Further, the cost of the CAC tanks, which is directly related to the amount of material, should be minimized. Finally, the physical space in which the CAC can be located is limited by other underhood components and vehicle styling features. This presents an optimization problem with four conflicting objectives: to reduce the pressure loss in the system, to increase the uniformity of flow in the tubes, to minimize the tank material and to conform to the package volume. In this work, CATIA v5 was used to define the package volume to which the optimized CAC must conform, and a commercial CFD tool was used to create the geometry and mesh, and to run the analysis; modeFRONTIER™ was used as the multi-objective optimization tool to automatically drive the process of modifying the parameters controlling the shape of the tanks, and position of the inlet and outlet, in order to achieve the above objectives.

The full list of Papers that will be presented at SAE2008 regarding modeFRONTIER™ is available at SAE 2008 World Conference website.


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	Home modeFRONTIER™ at SAE 2008 World Congress By clicking on the website of the world-wide biggest event in automotive engineering, the SAE World Congress and searching for modeFRONTIER™ you will find out a number of papers that directly refernce modeFRONTIER™. Out of these 10 are related to SAE2008 that will be held in Detroit on 14th-15th April 2008 making modeFRONTIER™ the most referenced optimization and process integration software during the 2008 edition of SAE. We can report the four abstract related to papers where ESTECO personnel was directly involved but we look forward to see the results obtained by our users in the other papers. Our suspect is that modeFRONTIER™ is also behind many other published work but we cannot say this until we will see it. It will be a pleasure to listen and learn from our customers during SAE2008. Paper Number 2008-01-0874 Self Organizing Maps (SOM) for Design Selection in Multi-Objective Optimization using modeFRONTIER™ Sumeet Parashar, Nader Fateh - ESTECO North America Inc., Livonia, MI Valentino Pediroda, Carlo Poloni - University of Trieste, Trieste, Italy Copyright © 2007 SAE International ABSTRACT Self Organizing Maps (SOM) has evolved as a very useful visualization and data analysis tool for high dimensional data. Visualization and analysis of Pareto data for multi-objective optimization problems with more than three objectives is also a challenge. This paper will investigate the application of SOM for visualization and design selection for multi-objective Pareto data. The SOM is applied to investigate the spread of Pareto front as well as to investigate trade-off between objectives. The visualization and selection strategy is applied to mathematical test problem to explain the concept. Later it is also applied to real world automotive design problem of engine optimization. Paper Number 2008-01-1429 Efficient Stochastic Optimization using Chaos Collocation method with modeFRONTIER™ Valentino Pediroda, Lucia Parussini, Carlo Poloni - University of Trieste, Italy Sumeet Parashar, Nader Fateh - ESTECO North America Inc, Livonia, MI Mauro Poian - ESTECO srl, Trieste, Italy Copyright © 2007 SAE International ABSTRACT Robust Design Optimization (RDO) using traditional approaches such as Monte Carlo (MC) sampling requires tremendous computational expense. Performing a RDO for problems involving time consuming CAE analysis may not even be possible within time constraints. In this paper a new stochastic modeling technique based on chaos collocation method is used to measure the mean and standard deviation (σ) for uncertain output parameters. For a given accuracy, chaos collocation method requires far less sample evaluations compared to MC. The efficient evaluation of mean and std. deviation terms using chaos collocation method makes it quite attractive to be used with RDO methods. In this work the RDO of an automotive engine design is performed employing chaos collocation method. The solution strategy is implemented in commercial Process Integration and Design Optimization (PIDO) software tool modeFRONTIER™. modeFRONTIER™ provides a very effective environment to apply multi-objective optimization algorithms to various CAE or in-house analysis and simulation tools. The engine design simulations were performed using GT-Power through modeFRONTIER™. The chaos collocation method is coded in MATLAB scripts that are also invoked through modeFRONTIER™. The rest of the paper covers an introduction describing the motivation and challenges. The chaos collocation method is described followed by a description of it's application through modeFRONTIER™. The engine design optimization problem is explained followed by a discussion of RDO results. Paper Number 2008-01-0871 Game Theory Approach to Engine Performance Optimization Nader Fateh, Sumeet Parashar - ESTECO North America Inc., Livonia, MI John Silvestri - Gamma Technologies Inc., Westmont, IL Copyright © 2007 SAE International ABSTRACT Genetic Algorithms have proved to be very useful as global search methods for multi-dimensional optimization problems. One drawback, however, is that they are inefficient from the point of view of the number of function evaluations. This paper presents a two phase approach to optimization, using Game Theory in an initial step which provides a family of designs which are close to the Pareto frontier. The starting population for the genetic algorithm is then selected from the non-dominated designs produced in the first phase. This ensures that the genetic algorithm starts with a population of points which are already optimized to a large degree. Paper Number 2008-01-0886 Multi-objective Optimization of a Charge Air Cooler using modeFRONTIER™ Phil Stephenson, Yang Chen - BEHR America Inc., Troy, MI Nader Fateh, Sumeet Parashar - ESTECO North America Inc., Livonia, MI Mauro Poian - ESTECO srl, Trieste, Italy Copyright © 2007 SAE International ABSTRACT In order for an automotive charge air cooler (CAC) to function efficiently, the flow of air through the cross tubes should be as uniform as possible. The position of the inlet and outlet, as well as the shape of the header tanks, are generally the most important determinants of the flow uniformity, and therefore of the cooling performance of the system. In an attempt to achieve this goal of flow uniformity, however, the effect on pressure loss in the system must also be considered. Further, the cost of the CAC tanks, which is directly related to the amount of material, should be minimized. Finally, the physical space in which the CAC can be located is limited by other underhood components and vehicle styling features. This presents an optimization problem with four conflicting objectives: to reduce the pressure loss in the system, to increase the uniformity of flow in the tubes, to minimize the tank material and to conform to the package volume. In this work, CATIA v5 was used to define the package volume to which the optimized CAC must conform, and a commercial CFD tool was used to create the geometry and mesh, and to run the analysis; modeFRONTIER™ was used as the multi-objective optimization tool to automatically drive the process of modifying the parameters controlling the shape of the tanks, and position of the inlet and outlet, in order to achieve the above objectives. The full list of Papers that will be presented at SAE2008 regarding modeFRONTIER™ is available at SAE 2008 World Conference website. \| Home \| Products \| Applications \| Support \| News \| About us \| Login \| Register \| Copyright © 2008 ESTECO s.r.l. All rights reserved - P.IVA 01635250226