Variable-fidelity shape optimization of dual-rotor wind turbines

2018 ◽  
Vol 35 (7) ◽  
pp. 2514-2542
Author(s):  
Andrew Thelen ◽  
Leifur Leifsson ◽  
Anupam Sharma ◽  
Slawomir Koziel
Keyword(s):  
Design Optimization ◽  
Wind Turbines ◽  
Computational Cost ◽  
Optimization Techniques ◽  
Fast Variable ◽  
Efficient Design ◽  
Content Type ◽  
Optimization Framework ◽  
Derivative Free ◽  
Variable Fidelity

Purpose Dual-rotor wind turbines (DRWTs) are a novel type of wind turbines that can capture more power than their single-rotor counterparts. Because their surrounding flow fields are complex, evaluating a DRWT design requires accurate predictive simulations, which incur high computational costs. Currently, there does not exist a design optimization framework for DRWTs. Since the design optimization of DRWTs requires numerous model evaluations, the purpose of this paper is to identify computationally efficient design approaches. Design/methodology/approach Several algorithms are compared for the design optimization of DRWTs. The algorithms vary widely in approaches and include a direct derivative-free method, as well as three surrogate-based optimization methods, two approximation-based approaches and one variable-fidelity approach with coarse discretization low-fidelity models. Findings The proposed variable-fidelity method required significantly lower computational cost than the derivative-free and approximation-based methods. Large computational savings come from using the time-consuming high-fidelity simulations sparingly and performing the majority of the design space search using the fast variable-fidelity models. Originality/value Due the complex simulations and the large number of designable parameters, the design of DRWTs require the use of numerical optimization algorithms. This work presents a novel and efficient design optimization framework for DRWTs using computationally intensive simulations and variable-fidelity optimization techniques.

RANS-based design optimization of dual-rotor wind turbines

2018 ◽  
Vol 35 (1) ◽  
pp. 35-52 ◽  
Author(s):  
Andrew Thelen ◽  
Leifur Leifsson ◽  
Anupam Sharma ◽  
Slawomir Koziel
Keyword(s):  
Design Optimization ◽  
Wind Turbines ◽  
Optimization Algorithms ◽  
Computational Cost ◽  
Pattern Search ◽  
Optimization Techniques ◽  
Optimal Designs ◽  
Kriging Interpolation ◽  
Direct Optimization ◽  
Content Type

Purpose An improvement in the energy efficiency of wind turbines can be achieved using dual rotors. Because of complex flow physics, the design of dual-rotor wind turbines (DRWTs) requires repetitive evaluations of computationally expensive partial differential equation (PDE) simulation models. Approaches for solving design optimization of DRWTs constrained by PDE simulations are investigated. The purpose of this study is to determine design optimization algorithms which can find optimal designs at a low computational cost. Design/methodology/approach Several optimization approaches and algorithms are compared and contrasted for the design of DRWTs. More specifically, parametric sweeps, direct optimization using pattern search, surrogate-based optimization (SBO) using approximation-based models and SBO using kriging interpolation models with infill criteria are investigated for the DRWT design problem. Findings The approaches are applied to two example design cases where the DRWT fluid flow is simulated using the Reynolds-averaged Navier−Stokes (RANS) equations with a two-equation turbulence model on an axisymmetric computational grid. The main rotor geometry is kept fixed and the secondary rotor characteristics, using up to three variables, are optimized. The results show that the automated numerical optimization techniques were able to accurately find the optimal designs at a low cost. In particular, SBO algorithm with infill criteria configured for design space exploitation required the least computational cost. The widely adopted parametric sweep approach required more model evaluations than the optimization algorithms, as well as not being able to accurately find the optimal designs. Originality/value For low-dimensional PDE-constrained design of DRWTs, automated optimization algorithms are essential to find accurately and efficiently the optimal designs. More specifically, surrogate-based approaches seem to offer a computationally efficient way of solving such problems.

Design-airworthiness integration method for general aviation aircraft during early development stage

2019 ◽  
Vol 91 (7) ◽  
pp. 1067-1076
Author(s):  
Maxim Tyan ◽  
Jungwon Yoon ◽  
Nhu Van Nguyen ◽  
Jae-Woo Lee ◽  
Sangho Kim
Keyword(s):  
Design Optimization ◽  
Design Stage ◽  
Design Parameters ◽  
Design Framework ◽  
Efficient Design ◽  
Content Type ◽  
Early Design ◽  
Early Design Stage ◽  
Optimization Framework ◽  
Design Requirements

Purpose Major changes of an aircraft configuration are conducted during the early design stage. It is important to include the airworthiness regulations at this stage while there is extensive freedom for designing. The purpose of this paper is to introduce an efficient design framework that integrates airworthiness guidelines and documentation at the early design stage. Design/methodology/approach A new design and optimization process is proposed that logically includes the airworthiness regulations as design parameters and constraints by constructing a certification database. The design framework comprises requirements analysis, preliminary sizing, conceptual design synthesis and loads analysis. A design certification relation table (DCRT) describes the legal regulations in terms of parameters and values suitable for use in design optimization. Findings The developed framework has been validated and demonstrated for the design of a Federal Aviation Regulations (FAR) 23 four-seater small aircraft. The validation results show an acceptable level of accuracy to be applied during the early design stage. The total mass minimization problem has been successfully solved while satisfying all the design requirements and certification constraints specified in the DCRT. Moreover, successful compliance with FAR 23 subpart C is demonstrated. The proposed method is a useful tool for design optimization and compliance verifications during the early stages of aircraft development. Practical implications The new certification database proposed in this research makes it simpler for engineers to access a large amount of legal documentation related to airworthiness regulations and provides a link between the regulation text and actual design parameters and their bounds. Originality/value The proposed design optimization framework integrates the certification database that is built of several types of legal documents such as regulations, advisory circulars and standards. The Engineering Requirements and Guide summarizes all the documents and design requirements into a single document. The DCRT is created as a summary table that indicates the design parameters affected by a given regulation(s), the design stage at which the parameter can be evaluated and its value bounds. The introduction of the certification database into the design optimization framework significantly reduces the engineer’s load related for airworthiness regulations.

Rapid design optimization of antennas using variable-fidelity EM models and adjoint sensitivities

2016 ◽  
Vol 33 (7) ◽  
pp. 2007-2018 ◽  
Author(s):  
Slawomir Koziel ◽  
Adrian Bekasiewicz
Keyword(s):  
Design Optimization ◽  
Optimization Technique ◽  
Computational Cost ◽  
Trust Region ◽  
Simulation Models ◽  
Direct Optimization ◽  
Content Type ◽  
Variable Fidelity ◽  
Em Simulation ◽  
Conventional Methods

Purpose Development of techniques for expedited design optimization of complex and numerically expensive electromagnetic (EM) simulation models of antenna structures validated both numerically and experimentally. The paper aims to discuss these issues. Design/methodology/approach The optimization task is performed using a technique that combines gradient search with adjoint sensitivities, trust region framework, as well as EM simulation models with various levels of fidelity (coarse, medium and fine). Adaptive procedure for switching between the models of increasing accuracy in the course of the optimization process is implemented. Numerical and experimental case studies are provided to validate correctness of the design approach. Findings Appropriate combination of suitable design optimization algorithm embedded in a trust region framework, as well as model selection techniques, allows for considerable reduction of the antenna optimization cost compared to conventional methods. Research limitations/implications The study demonstrates feasibility of EM-simulation-driven design optimization of antennas at low computational cost. The presented techniques reach beyond the common design approaches based on direct optimization of EM models using conventional gradient-based or derivative-free methods, particularly in terms of reliability and reduction of the computational costs of the design processes. Originality/value Simulation-driven design optimization of contemporary antenna structures is very challenging when high-fidelity EM simulations are utilized for performance utilization of structure at hand. The proposed variable-fidelity optimization technique with adjoint sensitivity and trust regions permits rapid optimization of numerically demanding antenna designs (here, dielectric resonator antenna and compact monopole), which cannot be achieved when conventional methods are of use. The design cost of proposed strategy is up to 60 percent lower than direct optimization exploiting adjoint sensitivities. Experimental validation of the results is also provided.

Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation

2019 ◽  
Vol 37 (2) ◽  
pp. 753-788
Author(s):  
Slawomir Koziel ◽  
Adrian Bekasiewicz
Keyword(s):  
Design Optimization ◽  
Design Problem ◽  
Low Cost ◽  
Computational Cost ◽  
Search Space ◽  
Population Based ◽  
Design Framework ◽  
Content Type ◽  
Multi Objective ◽  
Variable Fidelity

Purpose The purpose of this paper is to investigate the strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup. Design/methodology/approach Formulation of the multi-objective design problem-oriented toward execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploits variable fidelity modeling, physics- and approximation-based representation of the structure and model correction techniques. The considered approach is suitable for handling various problems pertinent to the design of microwave and antenna structures. Numerical case studies are provided demonstrating the feasibility of the segmentation-based framework for the design of real-world structures in setups with two and three objectives. Findings Formulation of appropriate design problem enables identification of the search space region containing Pareto front, which can be further divided into a set of compartments characterized by small combined volume. Approximation model of each segment can be constructed using a small number of training samples and then optimized, at a negligible computational cost, using population-based metaheuristics. Introduction of segmentation mechanism to multi-objective design framework is important to facilitate low-cost optimization of many-parameter structures represented by numerically expensive computational models. Further reduction of the design cost can be achieved by enforcing equal-volumes of the search space segments. Research limitations/implications The study summarizes recent advances in low-cost multi-objective design of microwave and antenna structures. The investigated techniques exceed capabilities of conventional design approaches involving direct evaluation of physics-based models for determination of trade-offs between the design objectives, particularly in terms of reliability and reduction of the computational cost. Studies on the scalability of segmentation mechanism indicate that computational benefits of the approach decrease with the number of search space segments. Originality/value The proposed design framework proved useful for the rapid multi-objective design of microwave and antenna structures characterized by complex and multi-parameter topologies, which is extremely challenging when using conventional methods driven by population-based metaheuristics algorithms. To the authors knowledge, this is the first work that summarizes segmentation-based approaches to multi-objective optimization of microwave and antenna components.

Inverse surrogate modeling for low-cost geometry scaling of microwave and antenna structures

2016 ◽  
Vol 33 (4) ◽  
pp. 1095-1113 ◽  
Author(s):  
Slawomir Koziel ◽  
Adrian Bekasiewicz
Keyword(s):  
Low Cost ◽  
Computational Cost ◽  
Surrogate Modeling ◽  
High Fidelity ◽  
Modeling Framework ◽  
Simulation Accuracy ◽  
Content Type ◽  
Scaling Process ◽  
Variable Fidelity ◽  
Em Simulation

Purpose – The purpose of this paper is to investigate strategies for expedited dimension scaling of electromagnetic (EM)-simulated microwave and antenna structures, exploiting the concept of variable-fidelity inverse surrogate modeling. Design/methodology/approach – A fast inverse surrogate modeling technique is described for dimension scaling of microwave and antenna structures. The model is established using reference designs obtained for cheap underlying low-fidelity model and corrected to allow structure scaling at high accuracy level. Numerical and experimental case studies are provided demonstrating feasibility of the proposed approach. Findings – It is possible, by appropriate combination of surrogate modeling techniques, to establish an inverse model for explicit determination of geometry dimensions of the structure at hand so as to re-design it for various operating frequencies. The scaling process can be concluded at a low computational cost corresponding to just a few evaluations of the high-fidelity computational model of the structure. Research limitations/implications – The present study is a step toward development of procedures for rapid dimension scaling of microwave and antenna structures at high-fidelity EM-simulation accuracy. Originality/value – The proposed modeling framework proved useful for fast geometry scaling of microwave and antenna structures, which is very laborious when using conventional methods. To the authors’ knowledge, this is one of the first attempts to surrogate-assisted dimension scaling of microwave components at the EM-simulation level.

Multidisciplinary Design Optimization of Modular Industrial Robots

2011 ◽  
Author(s):  
Mehdi Tarkian ◽  
Johan Persson ◽  
Johan O¨lvander ◽  
Xiaolong Feng
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Structural Strength ◽  
Computational Cost ◽  
Industrial Robots ◽  
Multidisciplinary Design ◽  
Geometry Model ◽  
Optimization Framework ◽  
Speed Up ◽  
Multi Level

This paper presents a multidisciplinary design optimization framework for modular industrial robots. An automated design framework, containing physics based high fidelity models for dynamic simulation and structural strength analyses are utilized and seamlessly integrated with a geometry model. The proposed framework utilizes well-established methods such as metamodeling and multi-level optimization in order to speed up the design optimization process. The contribution of the paper is to show that by applying a merger of well-established methods, the computational cost can be cut significantly, enabling search for truly novel concepts.

scholarly journals Multi-Fidelity Optimization of a Composite Airliner Wing Subject to Structural and Aeroelastic Constraints

Aerospace ◽  
2021 ◽  
Vol 8 (12) ◽  
pp. 398
Author(s):  
Angelos Kafkas ◽  
Spyridon Kilimtzidis ◽  
Athanasios Kotzakolios ◽  
Vassilis Kostopoulos ◽  
George Lampeas
Keyword(s):  
Low Cost ◽  
Computational Cost ◽  
Design Stage ◽  
Computational Time ◽  
High Fidelity ◽  
Full Potential ◽  
Optimized Design ◽  
Structural Representation ◽  
Optimization Framework ◽  
Variable Fidelity

Efficient optimization is a prerequisite to realize the full potential of an aeronautical structure. The success of an optimization framework is predominately influenced by the ability to capture all relevant physics. Furthermore, high computational efficiency allows a greater number of runs during the design optimization process to support decision-making. The efficiency can be improved by the selection of highly optimized algorithms and by reducing the dimensionality of the optimization problem by formulating it using a finite number of significant parameters. A plethora of variable-fidelity tools, dictated by each design stage, are commonly used, ranging from costly high-fidelity to low-cost, low-fidelity methods. Unfortunately, despite rapid solution times, an optimization framework utilizing low-fidelity tools does not necessarily capture the physical problem accurately. At the same time, high-fidelity solution methods incur a very high computational cost. Aiming to bridge the gap and combine the best of both worlds, a multi-fidelity optimization framework was constructed in this research paper. In our approach, the low-fidelity modules and especially the equivalent-plate methodology structural representation, capable of drastically reducing the associated computational time, form the backbone of the optimization framework and a MIDACO optimizer is tasked with providing an initial optimized design. The higher fidelity modules are then employed to explore possible further gains in performance. The developed framework was applied to a benchmark airliner wing. As demonstrated, reasonable mass reduction was obtained for a current state of the art configuration.

Aerodynamic preliminary design optimization of a centrifugal compressor turbocharger based on one-dimensional mean-line model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lakhdar Bourabia ◽  
Cheikh Brahim Abed ◽  
Mahfoudh Cerdoun ◽  
Smail Khalfallah ◽  
Michaël Deligant ◽  
...  
Keyword(s):  
Design Optimization ◽  
Centrifugal Compressor ◽  
Optimization Design ◽  
Optimization Techniques ◽  
Solution Phase ◽  
Geometrical Parameters ◽  
Preliminary Design ◽  
Line Model ◽  
Content Type ◽  
One Dimensional

Purpose The purpose of this paper is the development of a new turbocharger compressor is a challenging task particularly when both wider operating range and higher efficiency are required. However, the cumbersome design effort and the inherent calculus burden can be significantly reduced by using appropriate design optimization approaches as an alternative to conventional design techniques. Design/methodology/approach This paper presents an optimization-based preliminary-design (OPD) approach based on a judicious coupling between evolutionary optimization techniques and a modified one-dimensional mean-line model. Two optimization strategies are considered. The first one is mono-objective and is solved using genetic algorithms. The second one is multi-objective and it is handled using the non-dominated sorting genetic algorithm-II. The proposed approach constitutes an automatic search process to select the geometrical parameters of the compressor, ensuring the most common requirements of the preliminary-design phase, with a minimum involvement of the designer. Findings The obtained numerical results demonstrate that the proposed tool can rapidly produce nearly optimal designs as an excellent basis for further refinement in the phase by using more complex analysis methods such as computational fluid dynamics and meta-modeling. Originality/value This paper outlines a new fast OBPD approach for centrifugal compressor turbochargers. The proposal adopts an inverse design method and consists of two main phases: a formulation phase and a solution phase. The complexity of the formulated problem is reduced by using a sensitivity analysis. The solution phase requires to link, in an automatic way, three processes, namely, optimization, design and analysis.

A modified BLISCO method and its combination with variable fidelity metamodel for engineering design

2016 ◽  
Vol 33 (5) ◽  
pp. 1353-1377 ◽  
Author(s):  
Ping Jiang ◽  
Qi Zhou ◽  
Xinyu Shao ◽  
Ren Long ◽  
Hui Zhou
Keyword(s):  
Multidisciplinary Design Optimization ◽  
Design Methodology ◽  
Mathematical Problem ◽  
Integrated System ◽  
Collaborative Optimization ◽  
Efficient Design ◽  
Content Type ◽  
Computational Costs ◽  
Variable Fidelity ◽  
Practical Implications

Purpose – The purpose of this paper is to present a modified bi-level integrated system collaborative optimization (BLISCO) to avoid the non-separability of the original BLISCO. Besides, to mitigate the computational burden caused by expensive simulation codes and employ both efficiently simplified and expensively detailed information in multidisciplinary design optimization (MDO), an effective framework combining variable fidelity metamodels (VFM) and modified BLISCO (MBLISCO) (VFM-MBLISCO) is proposed. Design/methodology/approach – The concept of the quasi-separable MDO problems is introduced to limit range of applicability about the BLISCO method and then based on the quasi-separable MDO form, the modification of BLISCO method without any derivatives is presented to solve the problems of BLISCO. Besides, an effective framework combining VFM-MBLISCO is presented. Findings – One mathematical problem conforms to the quasi-separable MDO form is tested and the overall results illustrate the feasibility and robustness of the MBLISCO. The design of a Small Waterplane Area Twin Hull catamaran demonstrates that the proposed VFM-MBLISCO framework is a feasible and efficient design methodology in support of design of engineering products. Practical implications – The proposed approach exhibits great capability for MDO problems with tremendous computational costs. Originality/value – A MBLISCO is proposed which can avoid the non-separability of the original BLISCO and an effective framework combining VFM-MBLISCO is presented to efficiently integrate the different fidelities information in MDO.

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