Articles de revues : « Optimisation Topologie »

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Raj Kumar S, Solomon, et P. Nallasamy. « Topology Optimisation of Passive Constrained Layer Damping - A Comprehensive Review ». International Journal of Scientific Engineering and Research 11, n^o 5 (27 mai 2023) : 78–84. https://doi.org/10.70729/se23516171228.

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Chiu, Louis N. S., Daniel Stojanov, Bernard Rolfe et Wen Yi Yan. « Effect of Optimisation Parameters in Topology Optimisation ». Key Engineering Materials 725 (décembre 2016) : 529–34. http://dx.doi.org/10.4028/www.scientific.net/kem.725.529.

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The Bi-directional Evolutionary Structural Optimisation (BESO) method had been used by many authors for the optimisation of structures. This work sets out to investigate the effect of key optimisation parameters utilized in the BESO method, the evolution rate and the filter radius, on the outcome of the optimisation. An understanding of the interaction of these factors in the optimisation process enables a more efficient way to produce optimised components that can fully capitalise on the capabilities of additive manufacturing.

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Dongre, Prof Ganesh, Parag Kshirsagar, Shruti Kulat, Bhargav Kulkarni, Vedant Kulkarni et Sanket More. « Topology Optimisation of Piston ». International Journal for Research in Applied Science and Engineering Technology 11, n^o 5 (31 mai 2023) : 2978–83. http://dx.doi.org/10.22214/ijraset.2023.51449.

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Abstract: This research paper presents a comprehensive study on the topology optimization of a piston component manufactured through 3D printing technology. The study employs a combination of SolidWorks and ANSYS software to model and simulate the piston's structural behavior under different loading conditions. The optimized piston design is produced using PLA material through Ultimaker Cura software. The topology optimization process involves defining the design constraints and objectives, which are optimized to produce an optimal design with reduced weight while maintaining the required structural integrity. The paper investigates the effects of different loading conditions on the piston's structural performance and shows how the optimized design can enhance the piston's mechanical properties. The results show that the topology optimization process results in a piston design that reduces weight while maintaining the required strength and performance, thereby enhancing the efficiency of the 3D printing process. The study contributes to the growing body of research on the use of topology optimization in additive manufacturing and provides insights into the practical implementation of this approach in piston design.

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Ait Ouchaoui, A., M. Nassraoui et B. Radi. « Numerical investigation of the effect of topology optimisation methods parameters in the topology quality, the strength, and the computational cost ». Archives of Materials Science and Engineering 123, n^o 2 (1 octobre 2023) : 55–71. http://dx.doi.org/10.5604/01.3001.0054.2492.

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The literature abounds with many distinct topology optimisation methods, many of which share common parameter configurations. This study demonstrates that alternative parameter configurations may produce better results than common parameters. Additionally, we try to answer two fundamental questions: identifying the most effective topology optimisation method and determining the optimal parameter selection within this optimisation method. In order to respond to these questions, we conducted a comparative and objective analysis of topology optimisation methods.This paper evaluates four prominent topology optimisation methodologies, SIMP, RAMP, BESO, and LSM, based on three essential criteria: structural strength, topology quality, and computational cost. We conducted an in-depth examination of 12,500 topology optimisation results spanning a broad range of critical parameter values. These outcomes were generated using MATLAB codes. In the meantime, we comprehensively compared our findings with the existing literature on this subject.As predicted, our chosen parameters had a substantial effect on the topology quality, structural strength, and computational cost of the topology optimisation outcomes. Across the 12,500 results, many parameter combinations appeared to produce favourable results compared to conventional parameters commonly found in the existing literature.This study focuses exclusively on four specific topology optimisation methods; however, its findings may be extrapolated to apply to other methodologies. Additionally, while it extensively examines the effects of parameters on topology quality, strength, and computational cost, it does not encompass an exploration of these parameters' impacts on other performance criteria.Novel parameter configurations for topology optimisation have been identified, yielding enhanced outcomes in terms of topology quality, structural strength, and computational efficiency.

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Ribeiro, Tiago P., Luís F. A. Bernardo et Jorge M. A. Andrade. « Topology Optimisation in Structural Steel Design for Additive Manufacturing ». Applied Sciences 11, n^o 5 (27 février 2021) : 2112. http://dx.doi.org/10.3390/app11052112.

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Topology Optimisation is a broad concept deemed to encapsulate different processes for computationally determining structural materials optimal layouts. Among such techniques, Discrete Optimisation has a consistent record in Civil and Structural Engineering. In contrast, the Optimisation of Continua recently emerged as a critical asset for fostering the employment of Additive Manufacturing, as one can observe in several other industrial fields. With the purpose of filling the need for a systematic review both on the Topology Optimisation recent applications in structural steel design and on its emerging advances that can be brought from other industrial fields, this article critically analyses scientific publications from the year 2015 to 2020. Over six hundred documents, including Research, Review and Conference articles, added to Research Projects and Patents, attained from different sources were found significant after eligibility verifications and therefore, herein depicted. The discussion focused on Topology Optimisation recent approaches, methods, and fields of application and deepened the analysis of structural steel design and design for Additive Manufacturing. Significant findings can be found in summarising the state-of-the-art in profuse tables, identifying the recent developments and research trends, as well as discussing the path for disseminating Topology Optimisation in steel construction.

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Fenci, Giulia Evelina, Neil G. R. Currie et Greg Hardie. « Topology Optimisation : A case study. » IABSE Symposium Report 108, n^o 1 (19 avril 2017) : 64–65. http://dx.doi.org/10.2749/222137817821232450.

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Safonov, Alexander, et Andrew Adamatzky. « Computing via material topology optimisation ». Applied Mathematics and Computation 318 (février 2018) : 109–20. http://dx.doi.org/10.1016/j.amc.2017.08.030.

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Safonov, Alexander, et Jeff Jones. « Physarum computing and topology optimisation ». International Journal of Parallel, Emergent and Distributed Systems 32, n^o 5 (16 août 2016) : 448–65. http://dx.doi.org/10.1080/17445760.2016.1221073.

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Lowe, Thomas, et Joshua Pinskier. « Tree Reconstruction Using Topology Optimisation ». Remote Sensing 15, n^o 1 (28 décembre 2022) : 172. http://dx.doi.org/10.3390/rs15010172.

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Generating accurate digital tree models from scanned environments is invaluable for forestry, agriculture, and other outdoor industries in tasks such as identifying fall hazards, estimating trees’ biomass and calculating traversability. Existing methods for tree reconstruction rely on sparse feature identification to segment a forest into individual trees and generate a branch structure graph, limiting their application to easily separable trees and uniform forests. However, the natural world is a messy place in which trees present with significant heterogeneity and are frequently encroached upon by the surrounding environment. We present a general method for extracting the branch structure of trees from point cloud data, which estimates the structure of trees by adapting the methods of structural topology optimisation to find the optimal material distribution to interpolate the input data. We present the results of this optimisation over a wide variety of scans, and discuss the benefits and drawbacks of this novel approach to tree structure reconstruction. Our method generates detailed and accurate tree structures, with a mean Surface Error (SE) of 15 cm over 13 diverse tree datasets.

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Hurtado-Pérez, A. B., A. de J. Pablo-Sotelo, F. Ramírez-López, J. J. Hernández-Gómez et M. F. Mata-Rivera. « Iterative design of satellite structures and topology optimisation methods ». Journal of Physics : Conference Series 2804, n^o 1 (1 juillet 2024) : 012001. http://dx.doi.org/10.1088/1742-6596/2804/1/012001.

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Abstract Satellite launches are critical amid increasing demands for advanced services. Rising costs urge innovation in engineering. Enhancing satellite structural integrity during launches is crucial due to intense vibrations. Topology optimisation and additive manufacturing converge as promising solutions. Topology optimisation uses mathematical techniques to iteratively improve structures by reducing mass while enhancing attributes like load capacity. This field, active for about three decades, employs continuum and discrete algorithms to optimise structures. Recent trends show optimised structures through topology optimisation and additive manufacturing promise cost-effective and high-performance solutions. This study aims to extensively review topology optimisation methods, specifically focusing on satellite structures, to shape future developments within the years to come.

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Gonzalez-Delgado, Daniel, Pablo Jaen-Sola et Erkan Oterkus. « A Generative Design Approach for the Dynamic Optimisation of Multi-MW Offshore Direct-Drive Wind Turbine Electrical Generator Supporting Structures Using Modal Analysis ». Wind 4, n^o 2 (19 juin 2024) : 172–89. http://dx.doi.org/10.3390/wind4020009.

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Generative design techniques together with the rapid development of additive manufacturing represent a revolution in the field of structural optimisation processes. In this study, a static structural and modal analysis was integrated to drive a multi-objective generative design optimisation process for a 3 MW direct-drive offshore wind turbine electrical generator rotor structure. This novel optimisation approach implements an automated fittest-for-purpose process including a static structural analysis and a modal analysis as the input for the optimisation strategy algorithm, allowing the exploration of a wide range of non-conventional topologies. If compared with the simple generator rotor disc structure, the results obtained using this innovative method achieved over 7% of weight reduction and a 39% increment in the generator operational range with the consequent growth in the wind turbine energy capture capability. Moreover, this approach generates a vast amount of structural analysis information, crucial at an early stage of the development of large-scale projects for a cost-effective scheme.

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Sato, Takahiro, Kota Watanabe et Hajime Igarashi. « A modified immune algorithm with spatial filtering for multiobjective topology optimisation of electromagnetic devices ». COMPEL : The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 33, n^o 3 (29 avril 2014) : 821–33. http://dx.doi.org/10.1108/compel-09-2012-0174.

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Purpose – In the development of electromagnetic devices, multiobjective topology optimisation is effective to obtain diverse design candidates for production models. However, multiobjective topology optimisation has not widely been performed because it is difficult to obtain resultant shapes for engineering realisation due to large search spaces. The purpose of this paper is to present a new multiobjective topology optimisation method. Design/methodology/approach – This paper presents a new multiobjective topology optimisation method in which the Immune Algorithm is modified for multiobjecrive optimisation and a shape modification process based on spatial filtering is employed. Findings – The present method shows that better Pareto solutions can be found in comparison with the conventional methods. Originality/value – A new effective multiobjective topology optimisation is presented. This method enables to diverse design candidates for production models.

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Eigel, Martin, Marvin Haase et Johannes Neumann. « Topology Optimisation under Uncertainties with Neural Networks ». Algorithms 15, n^o 7 (12 juillet 2022) : 241. http://dx.doi.org/10.3390/a15070241.

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Topology optimisation is a mathematical approach relevant to different engineering problems where the distribution of material in a defined domain is distributed in some optimal way, subject to a predefined cost function representing desired (e.g., mechanical) properties and constraints. The computation of such an optimal distribution depends on the numerical solution of some physical model (in our case linear elasticity) and robustness is achieved by introducing uncertainties into the model data, namely the forces acting on the structure and variations of the material stiffness, rendering the task high-dimensional and computationally expensive. To alleviate this computational burden, we develop two neural network architectures (NN) that are capable of predicting the gradient step of the optimisation procedure. Since state-of-the-art methods use adaptive mesh refinement, the neural networks are designed to use a sufficiently fine reference mesh such that only one training phase of the neural network suffices. As a first architecture, a convolutional neural network is adapted to the task. To include sequential information of the optimisation process, a recurrent neural network is constructed as a second architecture. A common 2D bridge benchmark is used to illustrate the performance of the proposed architectures. It is observed that the NN prediction of the gradient step clearly outperforms the classical optimisation method, in particular since larger iteration steps become viable.

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Zhou, Xin, Chenglin Tao, Xi Liang, Zeliang Liu et Huijian Li. « Design and Mechanical Properties of Maximum Bulk Modulus Microstructures Based on a Smooth Topology with Grid Point Density ». Aerospace 11, n^o 2 (9 février 2024) : 145. http://dx.doi.org/10.3390/aerospace11020145.

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The aim of topology optimisation is to determine the optimal distribution of material phases within the periodic cells of a microstructure. In this paper, the density of grid points under element volume fraction is constructed to replace the finite elements in the traditional SIMP framework, avoiding jagged and blurry boundaries in the computational process due to grid dependence. This is then combined with homogenisation theory, a microstructure topology optimisation algorithm with maximum bulk modulus under prescribed volume constraints is proposed, which can obtain 2D and 3D topologies with smooth boundaries. In addition, a closed form expression for the two-dimensional topological concave edge structure (taking the most typical topology as an example) was derived, and a compression experiment was conducted on the topological microstructure based on 3D metal printing technology. Scanning electron microscopy showed that the powder bonded on the surface of the printed structure was not completely melted and the step effect caused the finite element analysis results to be higher than the experimental results. Overall, the finite element simulation and experimental results of the concave surface structure have good consistency, with high strength and energy absorption effects. Topologies based on grid point density obtain microstructures with smooth boundaries, and the introduction of the Heaviside smoothing function and multiple filtering steps within this algorithm leads to more robust optimisation, facilitating 3D or 4D printing of microstructures that meet specific design requirements and confirming the feasibility of the proposed topology for lightweighting studies.

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Otomori, M., T. Yamada, K. Izui et S. Nishiwaki. « Level set-based topology optimisation of a compliant mechanism design using mathematical programming ». Mechanical Sciences 2, n^o 1 (10 mai 2011) : 91–98. http://dx.doi.org/10.5194/ms-2-91-2011.

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Abstract. We propose a structural optimisation method, based on the level set method and using mathematical programming such as the method of moving asymptotes (MMA), which we apply to the design of compliant mechanisms. A compliant mechanism is a monolithic joint-free mechanism designed to be flexible to obtain a specified motion. In the design of compliant mechanisms, several requirements such as the direction of the deformation and stress concentrations must be considered to obtain the specified mechanical function. Topology optimisation, the most flexible type of structural optimisation, has been successfully used as a design optimisation method for compliant mechanisms, but the utility of topology optimisation results is often spoiled by a plethora of impractical designs such as structures containing grayscale areas. Level set-based topology optimisation methods are immune to the problem of grayscales since the boundaries of the optimal configuration are implicitly represented using the level set function. The proposed method updates the level set function using mathematical programming to facilitate the treatment of constraint functionals. To verify its capability, we apply our method to compliant mechanism design problems that include displacement constraints and stress constraints.

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Gilmore, Nicholas, Victoria Timchenko et Chris Menictas. « Manifold microchannel heat sink topology optimisation ». International Journal of Heat and Mass Transfer 170 (mai 2021) : 121025. http://dx.doi.org/10.1016/j.ijheatmasstransfer.2021.121025.

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Kuczek, Tomasz, et Bartosz Szachniewicz. « Topology optimisation of railcar composite structure ». International Journal of Heavy Vehicle Systems 22, n^o 4 (2015) : 375. http://dx.doi.org/10.1504/ijhvs.2015.073206.

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Thike, Aye Min, Sergey Lupin, Roustiam Chakirov et Yuriy Vagapov. « Topology Optimisation of Wireless Sensor Networks ». MATEC Web of Conferences 82 (2016) : 01010. http://dx.doi.org/10.1051/matecconf/20168201010.

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Peeters, Daniël, Daniel van Baalen et Mostafa Abdallah. « Combining topology and lamination parameter optimisation ». Structural and Multidisciplinary Optimization 52, n^o 1 (18 janvier 2015) : 105–20. http://dx.doi.org/10.1007/s00158-014-1223-7.

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., P. S. Burli. « TOPOLOGY OPTIMISATION OF HYDRAULIC PRESS STRUCTURE ». International Journal of Research in Engineering and Technology 04, n^o 07 (25 juillet 2015) : 369–73. http://dx.doi.org/10.15623/ijret.2015.0407059.

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Fredricson, Harald. « Structural topology optimisation : an application review ». International Journal of Vehicle Design 37, n^o 1 (2005) : 67. http://dx.doi.org/10.1504/ijvd.2005.006089.

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Alexandersen, Joe, Niels Aage, Casper Schousboe Andreasen et Ole Sigmund. « Topology optimisation for natural convection problems ». International Journal for Numerical Methods in Fluids 76, n^o 10 (17 septembre 2014) : 699–721. http://dx.doi.org/10.1002/fld.3954.

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Zhang, Li, Jin gui Lu, Lei Chen et Jian de Zhang. « Particle swarm optimisation algorithm for radio frequency identification network topology optimisation ». International Journal of Computational Science and Engineering 6, n^o 1/2 (2011) : 16. http://dx.doi.org/10.1504/ijcse.2011.041208.

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Fliegner, Felix Jakob. « Offshore grid topology optimisation with a geographical information system ». Journal of Physics : Conference Series 2362, n^o 1 (1 novembre 2022) : 012012. http://dx.doi.org/10.1088/1742-6596/2362/1/012012.

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A novel methodology is investigated to identify and optimise large scale offshore grid topologies connecting multiple wind farms and countries with each other. A Geographical Information System (GIS) is setup to cluster wind farms and create a permissive graph topology. Its purpose is to propose grid layouts with potential hub locations and landing points bottom-up in a fully analytical toolchain, while avoiding manual scenario building. A coupled market model performs the investment optimisation into new lines on the GIS created graph. This two-step procedure is demonstrated at the example of the Baltic Sea Region for the target year 2040. It can be found, that future offshore topologies benefit from bundled transmission paths and many clustered wind farms. A sensitivity analysis reveals that the topology results are sensitive for wind farm location assumptions and pre-defined interconnectors or hubs. Not least, the capability of the onshore grid to integrate the influx of offshore wind power and the level of detail it is modelled in, directly reflects on the topology results for the offshore grid. It is concluded that optimising the future offshore grid is a quest of pan-European scale which benefits heavily from geo data based pre-processing in a GIS.

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Khurana, M., et H. Winarto. « Development and validation of an efficient direct numerical optimisation approach for aerofoil shape design ». Aeronautical Journal 114, n^o 1160 (octobre 2010) : 611–28. http://dx.doi.org/10.1017/s0001924000004097.

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Abstract Intelligent shape optimisation architecture is developed, validated and applied in the design of high-altitude long endurance aerofoil (HALE). The direct numeric optimisation (DNO) approach integrating a geometrical shape parameterisation model coupled to a validated flow solver and a population based search algorithm are applied in the design process. The merit of the DNO methodology is measured by computational time efficiency and feasibility of the optimal solution. Gradient based optimisers are not suitable for multi-modal solution topologies. Thus, a novel particle swarm optimiser with adaptive mutation (AM-PSO) is developed. The effect of applying the PARSEC and a modified variant of the original function, as a shape parameterisation model on the global optimal is verified. Optimisation efficiency is addressed by mapping the solution topology for HALE aerofoil designs and by computing the sensitivity of aerofoil shape variables on the objective function. Variables with minimal influence are identified and eliminated from shape optimisation simulations. Variable elimination has a negligible effect on the aerodynamics of the global optima, with a significant reduction in design iterations to convergence. A novel data-mining technique is further applied to verify the accuracy of the AM-PSO solutions. The post-processing analysis, to swarm optimisation solutions, indicates a hybrid optimisation methodology with the integration of global and local gradient based search methods, yields a true optima. The findings are consistent for single and multi-point designs.

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Othaganont, Pongpun, Francis Assadian et Daniel J. Auger. « Multi-objective optimisation for battery electric vehicle powertrain topologies ». Proceedings of the Institution of Mechanical Engineers, Part D : Journal of Automobile Engineering 231, n^o 8 (6 octobre 2016) : 1046–65. http://dx.doi.org/10.1177/0954407016671275.

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Electric vehicles are becoming more popular in the market. To be competitive, manufacturers need to produce vehicles with a low energy consumption, a good range and an acceptable driving performance. These are dependent on the choice of components and the topology in which they are used. In a conventional gasoline vehicle, the powertrain topology is constrained to a few well-understood layouts; these typically consist of a single engine driving one axle or both axles through a multi-ratio gearbox. With electric vehicles, there is more flexibility, and the design space is relatively unexplored. In this paper, we evaluate several different topologies as follows: a traditional topology using a single electric motor driving a single axle with a fixed gear ratio; a topology using separate motors for the front axle and the rear axle, each with its own fixed gear ratio; a topology using in-wheel motors on a single axle; a four-wheel-drive topology using in-wheel motors on both axes. Multi-objective optimisation techniques are used to find the optimal component sizing for a given requirement set and to investigate the trade-offs between the energy consumption, the powertrain cost and the acceleration performance. The paper concludes with a discussion of the relative merits of the different topologies and their applicability to real-world passenger cars.

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Messager, Tanguy, Mariusz Pyrz et Jérôme Coloos. « Optimisation topologique de plaques par algorithme génétique ». Revue Européenne des Éléments Finis 7, n^o 7 (janvier 1998) : 793–810. http://dx.doi.org/10.1080/12506559.1998.10511341.

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Botteghi, N., A. Kamilaris, L. Sinai et B. Sirmacek. « MULTI-AGENT PATH PLANNING OF ROBOTIC SWARMS IN AGRICULTURAL FIELDS ». ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2020 (3 août 2020) : 361–68. http://dx.doi.org/10.5194/isprs-annals-v-1-2020-361-2020.

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Abstract. Collaborative swarms of robots/UAVs constitute a promising solution for precision agriculture and for automatizing agricultural processes. Since agricultural fields have complex topologies and different constraints, the problem of optimized path routing of these swarms is important to be tackled. Hence, this paper deals with the problem of optimizing path routing for a swarm of ground robots and UAVs in different popular topologies of agricultural fields. Four algorithms (Nearest Neighbour based on K-means clustering, Christofides, Ant Colony Optimisation and Bellman-Held-Karp) are applied on various farm types commonly found around Europe. The results indicate that the problem of path planning and the corresponding algorithm to use, are sensitive to the field topology and to the number of agents in the swarm.

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THAMINNI RAMAMOORTHY, Vivek, et Francois-Xavier BECOT. « Towards topology optimisation of poroelastic materials using field-based heuristics ». INTER-NOISE and NOISE-CON Congress and Conference Proceedings 270, n^o 2 (4 octobre 2024) : 9490–501. http://dx.doi.org/10.3397/in_2024_4257.

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In passive noise control, it is well known that the shapes of acoustic porous material absorbers can be modified to achieve favourable resonances resulting in high sound absorption. However, finding the optimised shapes for a given sound field environment is challenging as it involves solving an inverse problem. Recently, the use of topology optimisation for designing the shapes of acoustic porous material absorbers has gained interest. Previous studies suggest that conventional gradient methods can often result in local optimal results that may be poorer in overall absorption than what can be achieved by using heuristic optimisation techniques. In this study, the use of field variables such as acoustic pressures and velocities in developing better heuristic optimisation methods are explored with the aim of avoiding cumbersome gradient computations. The acoustic shapes produced by the field-based heuristics are compared with traditional approaches to develop insights as to what patterns in the shape designs contribute to improved sound absorption in various target frequencies.

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Dawson, Rach, Carolyn O’Dwyer, Edward Irwin, Marcin S. Mrozowski, Dominic Hunter, Stuart Ingleby, Erling Riis et Paul F. Griffin. « Automated Machine Learning Strategies for Multi-Parameter Optimisation of a Caesium-Based Portable Zero-Field Magnetometer ». Sensors 23, n^o 8 (15 avril 2023) : 4007. http://dx.doi.org/10.3390/s23084007.

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Machine learning (ML) is an effective tool to interrogate complex systems to find optimal parameters more efficiently than through manual methods. This efficiency is particularly important for systems with complex dynamics between multiple parameters and a subsequent high number of parameter configurations, where an exhaustive optimisation search would be impractical. Here we present a number of automated machine learning strategies utilised for optimisation of a single-beam caesium (Cs) spin exchange relaxation free (SERF) optically pumped magnetometer (OPM). The sensitivity of the OPM (T/Hz), is optimised through direct measurement of the noise floor, and indirectly through measurement of the on-resonance demodulated gradient (mV/nT) of the zero-field resonance. Both methods provide a viable strategy for the optimisation of sensitivity through effective control of the OPM’s operational parameters. Ultimately, this machine learning approach increased the optimal sensitivity from 500 fT/Hz to <109fT/Hz. The flexibility and efficiency of the ML approaches can be utilised to benchmark SERF OPM sensor hardware improvements, such as cell geometry, alkali species and sensor topologies.

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Jiao, Yuhang. « A Critical Review of Structural Topology Optimization Algorithms ». E3S Web of Conferences 606 (2025) : 04005. https://doi.org/10.1051/e3sconf/202560604005.

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In the past 30 years , the field of structural topology optimization has developed rapidly, and many representative algorithms such as homogenization algorithm, solid isotropic material with penalization algorithms and evolutionary structural optimization algorithms have emerged. In this paper, the above three representative algorithms’ principles and development history are briefly introduced. Secondly, with the classic example of long cantilever beams, the three methods are compared in all aspects of the optimisation process, and their similarities and differences in terms of optimisation objectives, constraints, and characteristics of the results are analysed. Finally, the above algorithms are summarized, and their advantages, disadvantages and applicable scenarios are listed, which will provide reference for future designers to a certain extent.

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Ortigosa, R., J. Martínez-Frutos, D. Ruiz, A. Donoso et J. C. Bellido. « Density-based topology optimisation considering nonlinear electromechanics ». Structural and Multidisciplinary Optimization 64, n^o 1 (10 avril 2021) : 257–80. http://dx.doi.org/10.1007/s00158-021-02886-3.

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Cannoodt, Robrecht, Joeri Ruyssinck, Jan Ramon, Katleen De Preter et Yvan Saeys. « IncGraph : Incremental graphlet counting for topology optimisation ». PLOS ONE 13, n^o 4 (26 avril 2018) : e0195997. http://dx.doi.org/10.1371/journal.pone.0195997.

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Wang, Jinlong, et Junlong Chen. « Topology optimisation design of mechanical tee backsheet ». International Journal of Reliability and Safety 13, n^o 1/2 (2019) : 5. http://dx.doi.org/10.1504/ijrs.2019.097010.

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Wang, Jinlong, et Junlong Chen. « Topology optimisation design of mechanical tee backsheet ». International Journal of Reliability and Safety 13, n^o 1/2 (2019) : 5. http://dx.doi.org/10.1504/ijrs.2019.10017888.

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Cai, Kun, Qing H. Qin, Zhen Luo et Ai J. Zhang. « Robust topology optimisation of bi-modulus structures ». Computer-Aided Design 45, n^o 10 (octobre 2013) : 1159–69. http://dx.doi.org/10.1016/j.cad.2013.05.002.

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Chen, Jahau Lewis, et Hsiang-Tang Chang. « Topology optimisation on frames of electric motorcycles ». International Journal of Vehicle Design 34, n^o 2 (2004) : 191. http://dx.doi.org/10.1504/ijvd.2004.003902.

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Gavali, S. L., Y. P. Reddy et K. N. Vijayakumar. « A genetic algorithm-based structural topology optimisation ». International Journal of Design Engineering 11, n^o 1 (2022) : 27. http://dx.doi.org/10.1504/ijde.2022.127072.

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Vasista, Srinivas, et Li Yong Tong. « Topology Optimisation of 3D Structures Using the Moving Iso-Surface Threshold Method ». Applied Mechanics and Materials 553 (mai 2014) : 801–6. http://dx.doi.org/10.4028/www.scientific.net/amm.553.801.

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This paper describes developments to the moving iso-surface threshold (MIST) topology optimisation method for 3D cases. With these developments, optimisation can be conducted in design domains featuring complex 3D geometry and meshed with tetrahedral and/or hexahedral finite elements. Benchmark examples demonstrate the functionality of the method and an example of an airliner seat leg structure shows how MIST can be used in an industrial application.

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Grekavicius, Lukas, Jack Antony Hughes, Konstantinos Daniel Tsavdaridis et Evangelos Efthymiou. « Novel Morphologies of Aluminium Cross-Sections through Structural Topology Optimization Techniques ». Key Engineering Materials 710 (septembre 2016) : 321–26. http://dx.doi.org/10.4028/www.scientific.net/kem.710.321.

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In the last decades, the deployment of aluminium and its alloys in civil engineering fields has been increased significantly, due to the material’s special features accompanied by supportive technological and industrial development. However, the extent of aluminium structural applications in building activities is still rather limited and barriers related to strength and stability issues prevent its wider use. In the context of the extrusion characteristic, appropriate design in aluminium cross-sections can overcome inherent deficiencies, such as the material’s low elastic modulus.This paper investigates a new breed of cross-sectional design for aluminium members employing pioneering structural topology optimisation techniques. Topology optimisation problems utilise the firmest mathematical basis, to account for improved weight-to-stiffness ratio and perceived aesthetic appeal of specific structural forms. The current study investigates the application of structural topology optimisation to the design of aluminium beam and column cross-sections. Through a combination of 2D and 3D approaches, with a focus on post-processing and manufacturability, ten unique cross-sectional profiles are proposed. Additionally, the variation of cross-section along the member is also investigated in order to identify correlation between 2D and 3D topology optimisation results. Conclusions attempt to highlight the advantageous characteristics of aluminium use as well as the potential benefits to the more widespread implementation of topology optimization within the utilization of aluminium in civil/structural engineering.

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Caivano, R., A. Tridello, D. Paolino et G. Chiandussi. « Topology and fibre orientation simultaneous optimisation : A design methodology for fibre-reinforced composite components ». Proceedings of the Institution of Mechanical Engineers, Part L : Journal of Materials : Design and Applications 234, n^o 9 (18 juin 2020) : 1267–79. http://dx.doi.org/10.1177/1464420720934142.

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Additive manufacturing for fibre-reinforced composite structures is rapidly diffusing, since it enables the production of lightweight structural parts characterized by complex geometries and tailored fibre orientations. Therefore, the development of design methodologies capable to simultaneously optimize the shape of the fibre-reinforced composite part and the fibre orientation in the additive manufacturing process is, at present, of utmost interest among industries and research centres. In this paper, a novel simultaneous optimisation method capable to optimise the topology and the local fibre orientation is proposed. The method is computationally cheap, fast convergent and permits to avoid stress peaks, working efficiently on 2D and on 3D models. The analytical formulation of the problem and the optimisation algorithm are at first described. The optimisation criteria are based on the uniform strain energy density distribution and the fibre alignement along the principal stress direction. The proposed method is then verified with several benchmarks from the literature and with a 3D illustrative example, confirming that it can be effectively and efficiently employed for the optimisation of composite components to be produced through additive manufacturing.

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Steven, Grant, Osvaldo Querin et Mike Xie. « Evolutionary structural optimisation (ESO) for combined topology and size optimisation of discrete structures ». Computer Methods in Applied Mechanics and Engineering 188, n^o 4 (août 2000) : 743–54. http://dx.doi.org/10.1016/s0045-7825(99)00359-x.

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Moss, A., T. Macquart, A. Panesar, M. Forrest, P. Greaves et A. Pirrera. « Structural Design of Wind Turbine Blades with an Additively Manufactured Graded Lattice Core using Topology Optimisation ». Journal of Physics : Conference Series 2265, n^o 3 (1 mai 2022) : 032004. http://dx.doi.org/10.1088/1742-6596/2265/3/032004.

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Abstract Conventional wind turbine blade manufacture relies on large, expensive moulds. Instead, using additive manufacturing to print the internal structure of blades, upon which it would be possible to lay composite plies, could significantly reduce manufacturing costs and, as one could “3D print” topologically optimal designs, improve structural efficiency. In general, topology optimisation integrates well with additive manufacturing. There are, however, two main challenges associated with the adoption of topology optimisation in wind blade design, i.e. accounting for: (i) the aeroelastic response of blades; and (ii) the variety of different materials that would be employed, in the composite laminates as well as the printed structure. To address these challenges, the present paper proposes a new multi-step design and optimisation framework relying on the combination of three software. First, a conventional aero-servo-elastic model is used to evaluate blade loads and displacements. Next, a topology optimisation software is used to optimise the blade laminates and core structure. Third, a lattice generator is used to convert the topological optimised “grey” design into an equivalent cellular design that can be printed using additive manufacturing. The full methodology of this design framework and an initial proof-of-concept topology optimisation solution are presented in this paper.

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Mohamodhosen, Bilquis Bibi Safoorah, Frederic Gillon, Mounaim Tounzi et Loïc Chevallier. « Topology optimisation using nonlinear behaviour of ferromagnetic materials ». COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 37, n^o 6 (5 novembre 2018) : 2211–23. http://dx.doi.org/10.1108/compel-12-2017-0522.

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Purpose The purpose of this paper is to propose a methodology to seek the optimal topology of electromagnetic devices using the density method while taking into account the non-linear behaviour of ferromagnetic materials. The tools and methods used are detailed and applied to a three-dimensional (3D) electromagnet for analysis and validation. Resulting topologies with and without the non-linear behaviour are investigated. Design/methodology/approach The polynomial mapping is used with the density method for material distribution in the optimisation domain. To consider the non-linear behaviour of the materials, an analytical approximation based on the Marrocco equation is used and combined with the polynomial mapping to solve the problem. Furthermore, to prevent the occurrence of intermediate materials, a weighted sum of objectives is used in the optimisation problem to eliminate these undesired materials. Findings Taking into account the non-linear materials behaviour and 3D model during topology optimisation (TO) is important, as it produces more physically feasible and coherent results. Moreover, the use of a weighted sum of objectives to eliminate intermediate materials increases the number of evaluations to reach the final solution, but it is efficient. Practical implications Considering non-linear materials behaviour yields results closer to reality, and physical feasibility of structures is more obvious in absence of intermediate materials. Originality/value This work tackles an obstacle of TO in electromagnetism which is often overlooked in literature, that is, non-linear behaviour of ferromagnetic materials by proposing a methodology.

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Wang, Teng, Wantao Li, Roberto Quaglia et Pere L. Gilabert. « Machine-Learning Assisted Optimisation of Free-Parameters of a Dual-Input Power Amplifier for Wideband Applications ». Sensors 21, n^o 8 (17 avril 2021) : 2831. http://dx.doi.org/10.3390/s21082831.

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This paper presents an auto-tuning approach for dual-input power amplifiers using a combination of global optimisation search algorithms and adaptive linearisation in the optimisation of a multiple-input power amplifier. The objective is to exploit the extra degrees of freedom provided by dual-input topologies to enhance the power efficiency figures along wide signal bandwidths and high peak-to-average power ratio values, while being compliant with the linearity requirements. By using heuristic search global optimisation algorithms, such as the simulated annealing or the adaptive Lipschitz Optimisation, it is possible to find the best parameter configuration for PA biasing, signal calibration, and digital predistortion linearisation to help mitigating the inherent trade-off between linearity and power efficiency. Experimental results using a load-modulated balanced amplifier as device-under-test showed that after properly tuning the selected free-parameters it was possible to maximise the power efficiency when considering long-term evolution signals with different bandwidths. For example, a carrier aggregated a long-term evolution signal with up to 200 MHz instantaneous bandwidth and a peak-to-average power ratio greater than 10 dB, and was amplified with a mean output power around 33 dBm and 22.2% of mean power efficiency while meeting the in-band (error vector magnitude lower than 1%) and out-of-band (adjacent channel leakage ratio lower than −45 dBc) linearity requirements.

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Golay, Frédéric. « Optimisation topologique de forme et raffinement de maillage ». Revue Européenne des Éléments Finis 13, n^o 8 (janvier 2004) : 881–97. http://dx.doi.org/10.3166/reef.13.881-897.

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Ben-Elechi, Slim, et Hakim Naceur. « Optimisation topologique de surfaces additionnelles de tôles embouties ». European Journal of Computational Mechanics 15, n^o 7-8 (janvier 2006) : 909–43. http://dx.doi.org/10.3166/remn.15.909-943.

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Kalauni, Kishor, Ajitanshu Vedrtnam, Magdalena Wdowin et Shashikant Chaturvedi. « ZIF for CO2 Capture : Structure, Mechanism, Optimization, and Modeling ». Processes 10, n^o 12 (13 décembre 2022) : 2689. http://dx.doi.org/10.3390/pr10122689.

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The requirement to counter carbon emissions is becoming urgent. Zeolitic Imidazolate Frameworks (ZIFs) have been extensively investigated recently for storing and separating gases, especially carbon dioxide. The present review aims to summarise the state of the art of ZIFs for carbon dioxide capture focusing on the structure, mechanism, optimisation, and modelling. The methods utilised for carbon capture are briefly summarized. The morphology of ZIFs with different topologies, N2-CO2 adsorption-desorption isotherms, X-ray diffraction patterns, thermo-gravimetric analysis (TGA) results are discussed to give insights into the textural properties, structure-activity relationship and structural-thermal stability of ZIFs. Finally, the experimental optimisation techniques, modelling and simulation studies for improving CO2 capture by ZIFs are discussed. This review should provide a comprehensive and quick understanding of this research area. It is timely to summarize and review ongoing developments in this growing field to accelerate the research in the right direction.

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Du, Xu Ran, Mike Xie, Xiao Ying Yang et Zhi Hao Zuo. « Topology Optimisation of Composites Containing Base Materials of Distinct Poisson’s Ratios ». Applied Mechanics and Materials 553 (mai 2014) : 813–17. http://dx.doi.org/10.4028/www.scientific.net/amm.553.813.

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From recent studies on natural composites such as nacre and bone, it has shown that the mechanical properties of the composite are significantly affected by the Poisson’s ratio of each constituent phase. In some cases it is found that when the Poisson’s ratio approaches the incompressibility limit, the stiffness of the composite in one or more directions can increase dramatically, in some cases by two or more orders of magnitude than the softer phase. In this paper we investigate designing the composite of maximum stiffness by a topology optimisation approach. The method used is based on the bi-directional evolutionary structural optimisation (BESO). The Optimisation problem is formulated and it is solved by a searching algorithm based on the sensitivity analysis. The effect of interpolation function in the sensitivity analysis is studied. Examples of different combinations of Poisson’s ratios are presented. The stiffness is found to increase from its base value. In the case of one phase having negative Poisson’s ratio, the increase is very significant. It is concluded that the proposed method is effective in optimising the stiffness of this class of composite.

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Huang, Lufan. « Integrating Deep Learning with Generative Design and Topology Optimization for Efficient Additive Manufacturing ». Applied and Computational Engineering 100, n^o 1 (8 novembre 2024) : 55–60. http://dx.doi.org/10.54254/2755-2721/100/20251723.

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Abstract. Additive manufacturing (AM) through generative design and topology optimisation creates complex, lightweight structures with exceptional material efficiency and structural integrity. When coupled with deep learning functionality, generative design and topology optimisation can explore broader design spaces and optimise more efficiently, creating novel AM structures that utilise material more efficiently and have better strength and performance than their counterparts created through conventional AM methods. The study tackles how deep learning models such as convolutional neural networks (CNNs) can be integrated into generative design and topology optimisation and how these integration help optimise material usage, production time and performance. Case studies from the aerospace, automotive, and healthcare industries exemplify how these synergies resulted in more resilient, cost-effective designs that would not have been possible through conventional AM approaches. The study focuses on material usage efficiency, reduction in production time and performance improvement to showcase how deep learning integrations enhance the process from design conceptualisation, through iterations, to final production.

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