The development of a hybridized particle swarm for kriging hyperparameter tuning

Journal of Engineering for Gas Turbines and Power

Keane

et al. 2015

The prometheus combustor design system aims to reduce the complexity of evaluating combustor designs by automatically defining preprocessing, simulation, and postprocessing tasks based on the automatic identification of combustor features within the computer-aided design (CAD) environment. This system enables best practice to be codified and topological changes to a combustor's design to be more easily considered within an automated design process. The following paper presents the prometheus combustor design system and its application to the multiobjective isothermal optimization of a combustor prediffuser and the multifidelity isothermal optimization of a fuel injector feed arm in combination with a surrogate modeling strategy accelerated via a high-performance graphical processing unit (GPU).

Section: Gpu Accelerated Surrogate Model Constructionmentioning

confidence: 99%

“…In the following paper the hybrid particle swarm algorithm of Toal et al [19,20] which utilizes an adjoint of the likelihood function within a local search is employed.…”

Section: Krigingmentioning

confidence: 99%

Isothermal Combustor Prediffuser and Fuel Injector Feed Arm Design Optimization Using the prometheus Design System

Zhang

Journal of Engineering for Gas Turbines and Power

Keane

et al. 2015

“…In both the single and multi-fidelity Kriging models used here the hyperparameters are optimized using a hybridized particle swarm algorithm similar to that of Toal et al [23].…”

Section: Single and Multi-fidelity Krigingmentioning

confidence: 99%

Some considerations regarding the use of multi-fidelity Kriging in the construction of surrogate models

2014

Struct Multidisc Optim

109

Surrogate models or metamodels are commonly used to exploit expensive computational simulations within a design optimization framework. The application of multi-fidelity surrogate modeling approaches has recently been gaining ground due to the potential for further reductions in simulation effort over single fidelity approaches. However, given a black box problem when exactly should a designer select a multi-fidelity approach over a single fidelity approach and vice versa? Using a series of analytical test functions and engineering design examples from the literature, the following paper illustrates the potential pitfalls of choosing one technique over the other without a careful consideration of the optimization problem at hand. These examples are then used to define and validate a set of guidelines for the creation of a multi-fidelity Kriging model. The resulting guidelines state that the different fidelity functions should be well correlated, that the amount of low fidelity data in the model should be greater than the amount of high fidelity data and that more than 10% and less than 80% of the total simulation budget should be spent on low fidelity simulations in order for the resulting multi-fidelity model to perform better than the equivalent costing high fidelity model.

“…The SFC resulting from each successful simulation was then used to create a Kriging model using the toolbox provided with OPTIMATv2 where the Kriging hyperparameters are optimized using a hybridized particle swarm exploiting an adjoint of the likelihood function. More details on this process can be found in [31].…”

Section: Simulation Of Sfc Based On a Detailed Mechanical Modelmentioning

confidence: 99%

Bi-objective optimization of pylon-engine-nacelle assembly: weight vs. tip clearance criterion

Bettebghor¹,

Blondeau²,

et al. 2013

Struct Multidisc Optim

A realistic application of advanced structural and multi-objective optimization for the design of a fully assembled aircraft powerplant installation is presented. As opposed to the classical design process of powerplant installation that does not consider the influence of pylon sizing over engine efficiency, we develop in the present a fully integrated approach where both pylon and compressor intercase are designed at once. The main objective is to consider the impact of weight over tip clearance performance criterion and see how these two objectives are antagonistic. In this work, we perform in the same design session tasks traditionally devoted to the airframe manufacturer and aero-engine manufacturer. The overall weight of the assembly is minimized with respect to Specific Fuel Consumption (SFC) criterion. One interesting aspect of the process is that SFC criterion is based on highly proprietary models and its simulation and call within an optimization process is made available through the development of a webservice. One major phenomenon to consider in both pylon and engine design is Fan Blade Off (FBO) event, i.e. the sudden release of a blade. This event causes high impact loads and must be considered carefully in the design. Such a simulation is not an easy task and several nonlinear phenomena must be addressed (e.g. rotordynamics), not to mention the integration of this nonlinear dynamic response in a static structural optimization process. This article describes how the design of the full assembly is performed taking into account both objectives. Such a problem lies in multi-objective optimization field and then we describe the method we use to solve such a problem. The simulation of an FBO post-impact rotor dynamics is also described and we end up with the final results that show the influence of pylon-engine weight sizing over SFC.