• Title, Summary, Keyword: optimisation

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A novel method for the vibration optimisation of structures subjected to dynamic loading

  • Munk, David J.;Vio, Gareth A.;Steven, Grant P.
    • Advances in aircraft and spacecraft science
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    • v.4 no.2
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    • pp.169-184
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    • 2017
  • The optimum design of structures with frequency constraints is of great importance in the aeronautical industry. In order to avoid severe vibration, it is necessary to shift the fundamental frequency of the structure away from the frequency range of the dynamic loading. This paper develops a novel topology optimisation method for optimising the fundamental frequencies of structures. The finite element dynamic eigenvalue problem is solved to derive the sensitivity function used for the optimisation criteria. An alternative material interpolation scheme is developed and applied to the optimisation problem. A novel level-set criteria and updating routine for the weighting factors is presented to determine the optimal topology. The optimisation algorithm is applied to a simple two-dimensional plane stress plate to verify the method. Optimisation for maximising a chosen frequency and maximising the gap between two frequencies are presented. This has the application of stiffness maximisation and flutter suppression. The results of the optimisation algorithm are compared with the state of the art in frequency topology optimisation. Test cases have shown that the algorithm produces similar topologies to the state of the art, verifying that the novel technique is suitable for frequency optimisation.

Parameters Influencing the Performance of Ant Algorithms Applied to Optimisation of Buffer Size in Manufacturing

  • Becker, Matthias;Szczerbicka, Helena
    • Industrial Engineering and Management Systems
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    • v.4 no.2
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    • pp.184-191
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    • 2005
  • In this article we study the feasibility of the Ant Colony Optimisation (ACO) algorithm for finding optimal Kanban allocations in Kanban systems represented by Stochastic Petri Net (SPN) models. Like other optimisation algorithms inspired by nature, such as Simulated Annealing/Genetic Algorithms, the ACO algorithm contains a large number of adjustable parameters. Thus we study the influence of the parameters on performance of ACO on the Kanban allocation problem, and identify the most important parameters.

Sensitivity and optimisation procedures for truss structures under large displacement

  • Bothma, A.S.;Ronda, J.;Kleiber, M.
    • Structural Engineering and Mechanics
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    • v.7 no.1
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    • pp.111-126
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    • 1999
  • The work presented here focuses on the development of suitable discretised formulations, for large-displacement shape and non-shape design sensitivity analysis (DSA), which enable the straightforward incorporation of structural optimisation into established finite element analysis (FEA) codes. For the generalised displacement-based functional the design sensitivity vector has been expressed in terms of displacement sensitivity. The Total Lagrangian formulation is utilised for modelling of large deformation of truss structures. The variational formulation of the sensitivity analysis procedure is discretised by using "pseudo" - finite elements, Results are presented for the sensitivity analysis and optimisation of standard truss structures. For the purposes of this work, the analysis and optimisation procedures outlined below are incorporated into the FEA code ABAQUS.

Optimal stacking sequence design of laminate composite structures using tabu embedded simulated annealing

  • Rama Mohan Rao, A.;Arvind, N.
    • Structural Engineering and Mechanics
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    • v.25 no.2
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    • pp.239-268
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    • 2007
  • This paper deals with optimal stacking sequence design of laminate composite structures. The stacking sequence optimisation of laminate composites is formulated as a combinatorial problem and is solved using Simulated Annealing (SA), an algorithm devised based on inspiration of physical process of annealing of solids. The combinatorial constraints are handled using a correction strategy. The SA algorithm is strengthened by embedding Tabu search in order to prevent recycling of recently visited solutions and the resulting algorithm is referred to as tabu embedded simulated Annealing (TSA) algorithm. Computational performance of the proposed TSA algorithm is enhanced through cache-fetch implementation. Numerical experiments have been conducted by considering rectangular composite panels and composite cylindrical shell with different ply numbers and orientations. Numerical studies indicate that the TSA algorithm is quite effective in providing practical designs for lay-up sequence optimisation of laminate composites. The effect of various neighbourhood search algorithms on the convergence characteristics of TSA algorithm is investigated. The sensitiveness of the proposed optimisation algorithm for various parameter settings in simulated annealing is explored through parametric studies. Later, the TSA algorithm is employed for multi-criteria optimisation of hybrid composite cylinders for simultaneously optimising cost as well as weight with constraint on buckling load. The two objectives are initially considered individually and later collectively to solve as a multi-criteria optimisation problem. Finally, the computational efficiency of the TSA based stacking sequence optimisation algorithm has been compared with the genetic algorithm and found to be superior in performance.

Optimum Design of Sandwich Panel Using Hybrid Metaheuristics Approach

  • Kim, Yun-Young;Cho, Min-Cheol;Park, Je-Woong;Gotoh, Koji;Toyosada, Masahiro
    • Journal of Ocean Engineering and Technology
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    • v.17 no.6
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    • pp.38-46
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    • 2003
  • Aim of this article is to propose Micro-Genetic Simulated Annealing (${\mu}GSA$) as a hybrid metaheuristics approach to find the global optimum of nonlinear optimisation problems. This approach combines the features of modern metaheuristics such as micro-genetic algorithm (${\mu}GAs$) and simulated annealing (SA) with the general robustness of parallel exploration and asymptotic convergence, respectively. Therefore, ${\mu}GSA$ approach can help in avoiding the premature convergence and can search for better global solution, because of its wide spread applicability, global perspective and inherent parallelism. For the superior performance of the ${\mu}GSA$, the five well-know benchmark test functions that were tested and compared with the two global optimisation approaches: scatter search (SS) and hybrid scatter genetic tabu (HSGT) approach. A practical application to structural sandwich panel is also examined by optimism the weight function. From the simulation results, it has been concluded that the proposed ${\mu}GSA$ approach is an effective optimisation tool for soloing continuous nonlinear global optimisation problems in suitable computational time frame.

Optimisation of a novel trailing edge concept for a high lift device

  • Botha, Jason D.M.;Dala, Laurent;Schaber, S.
    • Advances in aircraft and spacecraft science
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    • v.2 no.3
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    • pp.329-343
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    • 2015
  • This study aimed to observe the effect of a novel concept (referred to as the flap extension) implemented on the leading edge of the flap of a three element high lift device. The high lift device, consisting of a flap, main element and slat is designed around an Airbus research profile for sufficient take off and landing performance of a large commercial aircraft. The concept is realised on the profile and numerically optimised to achieve an optimum geometry. Two different optimisation approaches based on Genetic Algorithm optimisations are used: a zero order approach which makes simplifying assumptions to achieve an optimised solution: as well as a direct approach which employs an optimisation in ANSYS DesignXplorer using RANS calculations. Both methods converge to different optimised solutions due to simplifying assumptions. The solution to the zero order optimisation showed a decreased stall angle and decreased maximum lift coefficient against angle of attack due to early stall onset at the flap. The DesignXplorer optimised solution matched that of the baseline solution very closely. The concept was seen to increase lift locally at the flap for both optimisation methods.

Comparative numerical analysis for cost and embodied carbon optimisation of steel building structures

  • Eleftheriadis, Stathis;Dunant, Cyrille F.;Drewniok, Michal P.;Rogers-Tizard, William;Kyprianou, Constantinos
    • Advances in Computational Design
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    • v.3 no.4
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    • pp.385-404
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    • 2018
  • The study investigated an area of sustainable structural design that is often overlooked in practical engineering applications. Specifically, a novel method to simultaneously optimise the cost and embodied carbon performance of steel building structures was explored in this paper. To achieve this, a parametric design model was developed to analyse code compliant structural configurations based on project specific constraints and rigorous testing of various steel beam sections, floor construction typologies (precast or composite) and column layouts that could not be performed manually by engineering practitioners. Detailed objective functions were embedded in the model to compute the cost and life cycle carbon emissions of the different material types used in the structure. Results from a comparative numerical analysis of a real case study illustrated that the proposed optimisation approach could guide structural engineers towards areas of the solution space with realistic design configurations, enabling them to effectively evaluate trade-offs between cost and carbon performance. This significant contribution implied that the optimisation model could reduce the time required for the design and analysis of multiple structural configurations especially during the early stages of a project. Overall, the paper suggested that the deployment of automated design procedures can enhance the quality as well as the efficiency of the optimisation analysis.

Computer Simulation: A Hybrid Model for Traffic Signal Optimisation

  • Jbira, Mohamed Kamal;Ahmed, Munir
    • Journal of Information Processing Systems
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    • v.7 no.1
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    • pp.1-16
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    • 2011
  • With the increasing number of vehicles in use in our daily life and the rise of traffic congestion problems, many methods and models have been developed for real time optimisation of traffic lights. Nevertheless, most methods which consider real time physical queue sizes of vehicles waiting for green lights overestimate the optimal cycle length for such real traffic control. This paper deals with the development of a generic hybrid model describing both physical traffic flows and control of signalised intersections. The firing times assigned to the transitions of the control part are considered dynamic and are calculated by a simplified optimisation method. This method is based on splitting green times proportionally to the predicted queue sizes through input links for each new cycle time. The proposed model can be easily translated into a control code for implementation in a real time control system.

Optimisation of an inductive power transfer structure

  • Besuchet, Romain;Auvigne, Christophe;Shi, Dan;Winter, Christophe;Civet, Yoan;Perriard, Yves
    • Journal of international Conference on Electrical Machines and Systems
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    • v.2 no.3
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    • pp.349-355
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    • 2013
  • This paper presents the multi-objective optimisation of an Inductive Coupled Power Transfer (ICPT) device. A setup as complicated as the one at hand in this paper is extremely hard to model analytically. To acquire some knowledge about the influence of the geometric factors, a sensitivity analysis is first performed using design of experiment (DoE) and finite-element modelling (FEM). It allows validating that the choice of the free factors is relevant. This being done, the optimisation itself is performed using a genetic algorithm (GA), with two objectives and a strict functioning constraint.

Structural health monitoring through meta-heuristics - comparative performance study

  • Pholdee, Nantiwat;Bureerat, Sujin
    • Advances in Computational Design
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    • v.1 no.4
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    • pp.315-327
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    • 2016
  • Damage detection and localisation in structures is essential since it can be a means for preventive maintenance of those structures under service conditions. The use of structural modal data for detecting the damage is one of the most efficient methods. This paper presents comparative performance of various state-of-the-art meta-heuristics for use in structural damage detection based on changes in modal data. The metaheuristics include differential evolution (DE), artificial bee colony algorithm (ABC), real-code ant colony optimisation (ACOR), charged system search (ChSS), league championship algorithm (LCA), simulated annealing (SA), particle swarm optimisation (PSO), evolution strategies (ES), teaching-learning-based optimisation (TLBO), adaptive differential evolution (JADE), evolution strategy with covariance matrix adaptation (CMAES), success-history based adaptive differential evolution (SHADE) and SHADE with linear population size reduction (L-SHADE). Three truss structures are used to pose several test problems for structural damage detection. The meta-heuristics are then used to solve the test problems treated as optimisation problems. Comparative performance is carried out where the statistically best algorithms are identified.