Journal ArticleDOI
Structural Optimization of Rotating Disk Using Response Surface Equation and Genetic Algorithm
Sunil Mohan,Dipak Kumar Maiti +1 more
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TLDR
In this article, the structural optimization of an axial flow compressor rotating disk in a more simplistic way has been studied, where FEA is completely avoided during the optimization runs with the help of response equations.Abstract:
This study is focused on the structural optimization of an axial flow compressor rotating disk in a more simplistic way. Since optimization involves several runs, performing Finite Element Analysis (FEA) for a disk model in each run increases computational cost. Alternative response surface design models have been developed using the design of experiment (DOE) method to represent the FE disk model. These response equations are validated and used in optimization runs. A constraint nonlinear optimization procedure based on genetic algorithms has been used. FEA is completely avoided during the optimization runs with the help of response equations, resulting in less computational time and cost.read more
Citations
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Large scale variable fidelity surrogate modeling
TL;DR: Two approaches to circumvent computational burden of the Gaussian process regression framework are proposed, one based on the Nyström approximation of sample covariance matrices and another based on an intelligent usage of a blackbox that can evaluate a low fidelity function on the fly at any point of a design space.
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Multi-objective optimization design of a connection frame in macro-micro motion platform
TL;DR: Multi-objective optimization and design for the connection frame is constructed and discussed comprehensively by the effects of thermal-mechanical deformation and the natural frequency of the system.
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Conformal and Probabilistic Prediction and Applications
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Parametric design-based multi-objective optimisation for high-pressure turbine disc
TL;DR: Experimental results show that the proposed data-driven framework reduces the engineering difficulty of multi-objective optimisation, and it has high popularisation value for optimisation of other complex products.
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Intrinsic physical relationships between rotor modal shapes and instantaneous vibrational energy flow transmission characteristics: Theoretical and numerical analysis and application
TL;DR: In this paper, the authors derived the intrinsic physical relationship between rotor modal shapes and instantaneous vibrational energy flow transmission characteristics from the general equation of motion base on the structural intensity method and established a dual-rotor support-casing coupling model subjected to the rotor unbalanced forces by the finite element method.
References
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Book
Theory of elasticity
TL;DR: The theory of the slipline field is used in this article to solve the problem of stable and non-stressed problems in plane strains in a plane-strain scenario.
Journal ArticleDOI
Theory of Elasticity (3rd ed.)
The Response Surface Methodology
TL;DR: In this paper, the three types of Response Surface Methodology, the first-order, second-order and three-level fractional factorial, are explained and analyzed in depth, and examples of application of each model by numerically and graphically using computer software.
Journal ArticleDOI
Optimal design of aeroengine turbine disc based on kriging surrogate models
TL;DR: A design optimization method based on kriging surrogate models is proposed and applied to the shape optimization of an aeroengine turbine disc to improve the accuracy of surrogate models without significantly increasing computational cost.
Journal ArticleDOI
Sensitivity analysis in shape optimization of continuum structures
TL;DR: In this article, a finite element analysis code is adapted to the purposes of the method and numerical examples are performed and comparisons made with sensitivity analysis based on forward finite differences, where the authors use a finite number of master nodes to characterize the surfaces of a set of isoparametric finite elements and the adoption of their coordinates as design variables of the shape optimization.