scholarly journals Design Optimization With an Uncertain Vibroacoustic Model

2008 ◽  
Vol 130 (2) ◽  
Author(s):  
E. Capiez-Lernout ◽  
C. Soize
Keyword(s):  
Numerical Model ◽  
Design Optimization ◽  
Optimization Problem ◽  
Acoustic Pressure ◽  
Design Parameters ◽  
Internal Cavity ◽  
Admissible Set ◽  
Acoustic Source ◽  
Model Uncertainties ◽  
Numerical Application

This paper deals with the design optimization problem of a structural-acoustic system in the presence of uncertainties. The uncertain vibroacoustic numerical model is constructed by using a recent nonparametric probabilistic model, which takes into account model uncertainties and data uncertainties. The formulation of the design optimization problem includes the effect of uncertainties and consists in minimizing a cost function with respect to an admissible set of design parameters. The numerical application consists in designing an uncertain master structure in order to minimize the acoustic pressure in a coupled internal cavity, which is assumed to be deterministic and excited by an acoustic source. The results of the design optimization problem, solved with and without the uncertain numerical model, show significant differences.

scholarly journals Robust Design Optimization in Computational Mechanics

2008 ◽  
Vol 75 (2) ◽  
Author(s):  
E. Capiez-Lernout ◽  
C. Soize
Keyword(s):  
Cost Function ◽  
Design Optimization ◽  
Robust Design ◽  
Stochastic System ◽  
Optimization Problem ◽  
Probabilistic Approach ◽  
Robust Design Optimization ◽  
Design Parameters ◽  
Random Response ◽  
Numerical Application

The motivation of this paper is to propose a methodology for analyzing the robust design optimization problem of complex dynamical systems excited by deterministic loads but taking into account model uncertainties and data uncertainties with an adapted nonparametric probabilistic approach, whereas only data uncertainties are generally considered in the literature by using a parametric probabilistic approach. The possible designs are represented by a numerical finite element model whose design parameters are deterministic and belong to an admissible set. The optimization problem is formulated for the stochastic system as the minimization of a cost function associated with the random response of the stochastic system including the variability of the stochastic system induced by uncertainties and the bias corresponding to the distance of the mean random response to a given target. The gradient and the Hessian of the cost function with respect to the design parameters are explicitly calculated. The complete theory and a numerical application are presented.

scholarly journals Structural optimization considering the probabilistic system response

2004 ◽  
Vol 31 (3-4) ◽  
pp. 361-394 ◽  
Author(s):  
M. Papadrakakis ◽  
N.D. Lagaros ◽  
V. Plevris
Keyword(s):  
Structural Optimization ◽  
Design Optimization ◽  
Robust Design ◽  
Large Scale ◽  
Optimization Problem ◽  
Structural Parameters ◽  
Dominant Role ◽  
Robust Design Optimization ◽  
Design Parameters ◽  
System Response

In engineering problems, the randomness and uncertainties are inherent and the scatter of structural parameters from their nominal ideal values is unavoidable. In Reliability Based Design Optimization (RBDO) and Robust Design Optimization (RDO) the uncertainties play a dominant role in the formulation of the structural optimization problem. In an RBDO problem additional non deterministic constraint functions are considered while an RDO formulation leads to designs with a state of robustness, so that their performance is the least sensitive to the variability of the uncertain variables. In the first part of this study a metamodel assisted RBDO methodology is examined for large scale structural systems. In the second part an RDO structural problem is considered. The task of robust design optimization of structures is formulated as a multi-criteria optimization problem, in which the design variables of the optimization problem, together with other design parameters such as the modulus of elasticity and the yield stress are considered as random variables with a mean value equal to their nominal value. .

A Gaussian Process Modeling Approach for Fast Robust Design With Uncertain Inputs

2018 ◽  
Author(s):  
Kevin M. Ryan ◽  
Jesper Kristensen ◽  
You Ling ◽  
Sayan Ghosh ◽  
Isaac Asher ◽  
...  
Keyword(s):  
Gaussian Process ◽  
Design Optimization ◽  
Robust Design ◽  
Optimization Problem ◽  
Robust Design Optimization ◽  
Design Parameters ◽  
Input Uncertainty ◽  
Single Level ◽  
Output Uncertainty ◽  
Gp Model

Many engineering design and industrial manufacturing applications are tasked with finding optimum designs while dealing with uncertainty in the design parameters. The performance or quality of the design may be sensitive to the input variation, making it difficult to optimize. Probabilistic and robust design optimization methods are used in these scenarios to find the designs that will perform best under the presence of known input uncertainty. Robust design optimization algorithms often require a two-level optimization problem (double-loop) to find a solution. The design optimization outer-loop repeatedly calls a series of inner loops that calculate uncertainty measures of the outputs. This nested optimization problem is computationally expensive and can sometimes render the task infeasible for practical engineering robust design problems. This paper details a single-level metamodel-assisted approach for probabilistic and robust design. An enhanced Gaussian Process (GP) metamodel formulation is used to provide exact values of output uncertainty in the presence of uncertain inputs. The GP model utilizes a squared-exponential kernel function and assumes normally distributed input uncertainty. These two factors together allow for an exact calculation of the first and second moments of the marginal predictive distribution. Predictions of output uncertainty are directly calculated, creating an efficient single-level robust optimization problem. We demonstrate the effectiveness of the single-level GP-assisted robust design approach on multiple engineering example problems, including a beam vibration problem, a cantilevered beam with multiple constraints, and a robust autonomous aircraft flight controller design problem. For the optimization problems investigated in this study, the single-level framework found the robust optimum with a 99.9% savings in function evaluations over the standard two-level approach.

Probabilistic Design Optimization of Frequency Dispersion for Rotating Blades

2010 ◽  
Author(s):  
Liqiang An ◽  
G. Gary Wang ◽  
Zhangqi Wang
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Design Optimization ◽  
Optimization Problem ◽  
Frequency Dispersion ◽  
Probabilistic Constraints ◽  
Design Parameters ◽  
Probabilistic Design ◽  
Rotating Blades ◽  
Element Method

In this paper, a probabilistic design optimization method based on finite element method is proposed to calculate the variability of design parameters subject to a specified dispersion of natural frequencies of rotating blades. The element stiffness and mass matrices are derived using a two-stage finite element method and numerical integration. Based on the perturbation technology, the sensitivity of the frequencies, as well as relationship between the frequency dispersion and the coefficient of variability (CV) of the design parameters can be obtained. Such sensitivity information is then used to convert the probabilistic design optimization problem into a deterministic optimization problem. Two case studies are given to illustrate the proposed method. From the results, it is concluded that rotation of blade changes the sensitivity of CV to the design parameters considered, and using the proposed method can transform the probabilistic constraints to deterministic constraints.

A Framework of Multi-Fidelity Topology Design and its Application to Optimum Design of Flow Fields in Battery Systems

2019 ◽  
Author(s):  
Kentaro Yaji ◽  
Shintaro Yamasaki ◽  
Shohji Tsushima ◽  
Kikuo Fujita
Keyword(s):  
Topology Optimization ◽  
Design Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Flow Fields ◽  
Design Solution ◽  
Design Parameters ◽  
High Fidelity ◽  
Topology Optimization Problem ◽  
Battery Systems

Abstract We propose a novel framework based on multi-fidelity design optimization for indirectly solving computationally hard topology optimization problems. The primary concept of the proposed framework is to divide an original topology optimization problem into two subproblems, i.e., low- and high-fidelity design optimization problems. Hence, artificial design parameters, referred to as seeding parameters, are incorporated into the low-fidelity design optimization problem that is formulated on the basis of a pseudo-topology optimization problem. Meanwhile, the role of high-fidelity design optimization is to obtain a promising initial guess from a dataset comprising topology-optimized design candidates, and subsequently solve a surrogate optimization problem under a restricted design solution space. We apply the proposed framework to a topology optimization problem for the design of flow fields in battery systems, and confirm the efficacy through numerical investigations.

Design of a Passively Morphing Ornithopter Wing Using a Novel Compliant Spine

2010 ◽  
Author(s):  
Yashwanth Tummala ◽  
Aimy Wissa ◽  
Mary Frecker ◽  
James E. Hubbard
Keyword(s):  
Drag Reduction ◽  
Design Optimization ◽  
Design Methodology ◽  
Optimization Problem ◽  
Optimization Procedure ◽  
Complete Analysis ◽  
Design Parameters ◽  
Flight Performance ◽  
Level Flight ◽  
Steady Level

A new scheme to design morphing ornithopter wings using a passive compliant spine is presented in this paper. The objective of this work is to optimize steady level flight performance of an ornithopter by passively implementing the Continuous Vortex Gait (CVG) which requires bending, twist and sweep coupling during the upstroke. An optimization problem is formulated to design a compliant spine for pre-specified bending, sweep, and twist deflections. As a first step to achieving these 3 DOF kinematics, a 1 DOF compliant spine is considered to produce a specified bending deflection during the upstroke for drag reduction while remaining stiff during the downstroke for increased lift. The effect of the relevant geometric design parameters, namely contact gap, angle, and hinge geometry, are considered and optimized to achieve the aforementioned kinematics for both single and multiple joints, which make up a compliant spine. Results presented include the spine design optimization procedure, as well as a complete analysis for a 1DOF compliant spine to illustrate the efficacy of the methodology. This compliant spine design methodology and optimization procedure will be used, in the future, to design the 3-DOF compliant spine for the passively morphing ornithopter.

CAD Based Design Optimization of Planar Parallel Manipulators

2010 ◽  
Vol 166-167 ◽  
pp. 33-38 ◽  
Author(s):  
Khaled Assad Arrouk ◽  
Belhassen Chedli Bouzgarrou ◽  
Sergiu Dan Stan ◽  
Grigore Gogu
Keyword(s):  
Design Optimization ◽  
Parallel Manipulator ◽  
Optimization Problem ◽  
Parallel Manipulators ◽  
New Method ◽  
Design Parameters ◽  
Geometrical Approach ◽  
Geometrical Design ◽  
The Relationship ◽  
Planar Parallel Manipulators

In this paper a new method for determination and optimization of the workspace of parallel manipulators is presented. The proposed method is based on a geometrical approach, and offers the possibility to generate automatically the workspace in a CAD environment. Thus, the relationship between the geometrical design parameters of the parallel manipulator and its workspace can be analyzed without difficulty. Optimization problem considered in this paper consists in determining the dimensions of a parallel manipulator having the closest workspace to a prescribed task region. Finally, numerical applications of two types of planar parallel manipulators are presented in order to illustrate the proposed approach.

Shape Optimization of Hydraulic Structures: an Example of an Optimum Design of a Fish Passage

10.29007/2k64 ◽  
2018 ◽  
Author(s):  
Pat Prodanovic ◽  
Cedric Goeury ◽  
Fabrice Zaoui ◽  
Riadh Ata ◽  
Jacques Fontaine ◽  
...  
Keyword(s):  
Numerical Model ◽  
Shape Optimization ◽  
Objective Function ◽  
Optimum Design ◽  
Optimization Problem ◽  
A Priori ◽  
Coupled System ◽  
Fish Passage ◽  
Hydraulic Structures ◽  
Design Variables

This paper presents a practical methodology developed for shape optimization studies of hydraulic structures using environmental numerical modelling codes. The methodology starts by defining the optimization problem and identifying relevant problem constraints. Design variables in shape optimization studies are configuration of structures (such as length or spacing of groins, orientation and layout of breakwaters, etc.) whose optimal orientation is not known a priori. The optimization problem is solved numerically by coupling an optimization algorithm to a numerical model. The coupled system is able to define, test and evaluate a multitude of new shapes, which are internally generated and then simulated using a numerical model. The developed methodology is tested using an example of an optimum design of a fish passage, where the design variables are the length and the position of slots. In this paper an objective function is defined where a target is specified and the numerical optimizer is asked to retrieve the target solution. Such a definition of the objective function is used to validate the developed tool chain. This work uses the numerical model TELEMAC- 2Dfrom the TELEMAC-MASCARET suite of numerical solvers for the solution of shallow water equations, coupled with various numerical optimization algorithms available in the literature.

Parameter study and optimization design of a hat oblique tunnel portal

2021 ◽  
pp. 095440972110140
Author(s):  
Zijian Guo ◽  
Tanghong Liu ◽  
Wenhui Li ◽  
Yutao Xia
Keyword(s):  
High Speed ◽  
Optimization Design ◽  
Pareto Front ◽  
Optimization Problem ◽  
Optimization Method ◽  
Design Parameters ◽  
Parameter Study ◽  
Buffer Structure ◽  
Tunnel Entrance ◽  
The Ideal

The present work focuses on the aerodynamic problems resulting from a high-speed train (HST) passing through a tunnel. Numerical simulations were employed to obtain the numerical results, and they were verified by a moving-model test. Two responses, [Formula: see text] (coefficient of the peak-to-peak pressure of a single fluctuation) and[Formula: see text] (pressure value of micro-pressure wave), were studied with regard to the three building parameters of the portal-hat buffer structure of the tunnel entrance and exit. The MOPSO (multi-objective particle swarm optimization) method was employed to solve the optimization problem in order to find the minimum [Formula: see text] and[Formula: see text]. Results showed that the effects of the three design parameters on [Formula: see text] were not monotonous, and the influences of[Formula: see text] (the oblique angle of the portal) and [Formula: see text] (the height of the hat structure) were more significant than that of[Formula: see text] (the angle between the vertical line of the portal and the hat). Monotonically decreasing responses were found in [Formula: see text] for [Formula: see text] and[Formula: see text]. The Pareto front of [Formula: see text] and[Formula: see text]was obtained. The ideal single-objective optimums for each response located at the ends of the Pareto front had values of 1.0560 for [Formula: see text] and 101.8 Pa for[Formula: see text].

Workspace, dexterity and dimensional optimization of microhexapod

2015 ◽  
Vol 35 (4) ◽  
pp. 341-347 ◽  
Author(s):  
E. Rouhani ◽  
M. J. Nategh
Keyword(s):  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Screw Theory ◽  
Design Parameters ◽  
Dimensional Synthesis ◽  
Content Type ◽  
Workspace Analysis ◽  
The Difference ◽  
Flexure Joints ◽  
6 Degrees Of Freedom

Purpose – The purpose of this paper is to study the workspace and dexterity of a microhexapod which is a 6-degrees of freedom (DOF) parallel compliant manipulator, and also to investigate its dimensional synthesis to maximize the workspace and the global dexterity index at the same time. Microassembly is so essential in the current industry for manufacturing complicated structures. Most of the micromanipulators suffer from their restricted workspace because of using flexure joints compared to the conventional ones. In addition, the controllability of micromanipulators inside the whole workspace is very vital. Thus, it is very important to select the design parameters in a way that not only maximize the workspace but also its global dexterity index. Design/methodology/approach – Microassembly is so essential in the current industry for manufacturing complicated structures. Most of the micromanipulators suffer from their restricted workspace because of using flexure joints compared to the conventional ones. In addition, the controllability of micromanipulators inside the whole workspace is very vital. Thus, it is very important to select the design parameters in a way that not only maximize the workspace but also its global dexterity index. Findings – It has been shown that the proposed procedure for the workspace calculation can considerably speed the required calculations. The optimization results show that a converged-diverged configuration of pods and an increase in the difference between the moving and the stationary platforms’ radii cause the global dexterity index to increase and the workspace to decrease. Originality/value – The proposed algorithm for the workspace analysis is very important, especially when it is an objective function of an optimization problem based on the search method. In addition, using screw theory can simply construct the homogeneous Jacobian matrix. The proposed methodology can be used for any other micromanipulator.

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