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Journal articles on the topic 'Numerical optimisation'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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1

Diouf, Serigne, Mamadou M. Diop, and Alassane Sy. "NUMERICAL IMAGING USING NONLINEAR OPTIMISATION." International Journal of Numerical Methods and Applications 20, no. 1 (January 10, 2021): 1–16. http://dx.doi.org/10.17654/nm020010001.

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2

Theodore, N. D., and K. A. Padmanabhan. "Numerical optimisation of superplastic deformation." Journal of Materials Science 25, no. 4 (April 1990): 2133–43. http://dx.doi.org/10.1007/bf01045779.

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3

Wang, Wenjun, and Hui Wang. "An improved diversity-guided particle swarm optimisation for numerical optimisation." International Journal of Computing Science and Mathematics 5, no. 1 (2014): 16. http://dx.doi.org/10.1504/ijcsm.2014.059381.

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4

Tovar, Andres, Nelson Arzola de la Peña, and Alexander Gómez Cassab. "Multidisciplinary design optimisation techniques." Ingeniería e Investigación 27, no. 1 (January 1, 2007): 84–92. http://dx.doi.org/10.15446/ing.investig.v27n1.14785.

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Design optimisation of a multidisciplinary project in engineering involves the decomposition of a system into disciplines and the subsequent association of their contributions. This work was aimed at presenting the most common decomposition and association techniques currently used in multidisciplinary design optimisation (MDO). Amongst the decomposition techniques this work includes hierarchical and non-hierarchical approaches as well as the most popular numerical procedures. The association techniques include: one-level methods (e.g. all-at-once optimisation and simultaneous analysis and design), multilevel methods (e.g. concurrent subspace optimisation and collaborative optimisation) and robust design. This work also incorporates an illustrative numerical example.

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5

Grundmann, Jens, Niels Schütze, and Franz Lennartz. "Sustainable management of a coupled groundwater–agriculture hydrosystem using multi-criteria simulation based optimisation." Water Science and Technology 67, no. 3 (February 1, 2013): 689–98. http://dx.doi.org/10.2166/wst.2012.602.

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In this paper we present a new simulation-based integrated water management tool for sustainable water resources management in arid coastal environments. This tool delivers optimised groundwater withdrawal scenarios considering saltwater intrusion as a result of agricultural and municipal water abstraction. It also yields a substantially improved water use efficiency of irrigated agriculture. To allow for a robust and fast operation we unified process modelling with artificial intelligence tools and evolutionary optimisation techniques. The aquifer behaviour is represented using an artificial neural network (ANN) which emulates a numerical density-dependent groundwater flow model. The impact of agriculture is represented by stochastic crop water production functions (SCWPF). Simulation-based optimisation techniques together with the SCWPF and ANN deliver optimal groundwater abstraction and cropping patterns. To address contradicting objectives, e.g. profit-oriented agriculture vs. sustainable abstraction scenarios, we performed multi-objective optimisations using a multi-criteria optimisation algorithm.

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Giunta, A. A., V. Balabanov, D. Haim, B. Grossman, W. H. Mason, L. T. Watson, and R. T. Haftka. "Multidisciplinary optimisation of a supersonic transport using design of experiments theory and response surface modelling." Aeronautical Journal 101, no. 1008 (October 1997): 347–56. http://dx.doi.org/10.1017/s0001924000066045.

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AbstractThe presence of numerical noise in engineering design optimisation problems inhibits the use of many gradient-based optimisation methods. This numerical noise may result in the inaccurate calculation of gradients which in turn slows or prevents convergence during optimisation, or it may promote convergence to spurious local optima. The problems created by numerical noise are particularly acute in aircraft design applications where a single aerodynamic or structural analysis of a realistic aircraft configuration may require tens of CPU hours on a supercomputer. The computational expense of the analyses coupled with the convergence difficulties created by numerical noise are significant obstacles to performing aircraft multidisciplinary design optimisation. To address these issues, a procedure has been developed to create noise-free algebraic models of subsonic and supersonic aerodynamic performance quantities, for use in the optimisation of high-speed civil transport (HSCT) aircraft configurations. This procedure employs methods from statistical design of experiments theory and response surface modelling to create the noise-free algebraic models. Results from a sample HSCT design problem involving ten variables are presented to demonstrate the utility of this method.

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Ransing, R. S., S. Savino, and R. W. Lewis. "Numerical optimisation of tilt casting process." International Journal of Cast Metals Research 18, no. 2 (February 2005): 109–18. http://dx.doi.org/10.1179/136404605225022901.

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van der Heijden, F., W. Apperloo, and L. J. Spreeuwers. "Numerical optimisation in spot detector design." Pattern Recognition Letters 18, no. 11-13 (November 1997): 1091–97. http://dx.doi.org/10.1016/s0167-8655(97)00086-x.

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9

Krenek, Thorsten, Christopher Bacher, Günther Raidl, and Thomas Lauer. "Numerical Optimisation of Electro Hybrid Powertrains." MTZ worldwide 76, no. 3 (February 4, 2015): 46–52. http://dx.doi.org/10.1007/s38311-015-0007-9.

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10

Simić, Miloš. "Is the Bee Colony Optimisation algorithm suitable for continuous numerical optimisation?" International Journal of Metaheuristics 6, no. 4 (2017): 279. http://dx.doi.org/10.1504/ijmheur.2017.086978.

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Simić, Miloš. "Is the Bee Colony Optimisation algorithm suitable for continuous numerical optimisation?" International Journal of Metaheuristics 6, no. 4 (2017): 279. http://dx.doi.org/10.1504/ijmheur.2017.10006778.

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12

Caseiro, João F. M., Robertt Angelo Fontes Valente, António Andrade-Campos, and Renato Natal Jorge. "Optimisation of Tubular Hydroforming Processes for Wrinkling and Thinning Control." Key Engineering Materials 473 (March 2011): 159–67. http://dx.doi.org/10.4028/www.scientific.net/kem.473.159.

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This paper is focused on the development and implementation of an innovative optimisation algorithm for the wrinkling and thinning control during the hydroforming of complex metallic parts. A straightforward numerical algorithm for simultaneous tracking and evaluation of the initiation of wrinkling/thinning defects was implemented, together with a numerical simulation program based on the Finite Element Method (FEM). After undesirable wrinkling/thinning patterns are identified during FEM simulation, the developed optimisation procedure (called Hybrid Differential Evolution Particle Swarm Optimisation - HDEPSO) is responsible to automatically correct the process input parameters, in order to achieve the successful forming of the desired part. In the end, the combined procedure (optimisation methodology + FEM) proved to be able to lead to a suitable numerical simulation and design tool for industrial hydroformed metallic tubular parts.

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13

Godec, Damir, Mislav Sever, Mislav Tujmer, and Bruno Krajačić. "Numerical Optimisation of Mould and Injection Moulding Process." Tehnički glasnik 19, Si1 (May 7, 2025): 71–76. https://doi.org/10.31803/tg-20250326120249.

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The paper presents the optimisation of mould for injection moulding as well as injection moulding process parameters using numerical computer simulation in the Moldex3D software package. The optimisation process will be applied to a specific moulded part – branching terminal block – and an already manufactured mould. The paper includes evaluation of the existing mould for injection moulding designed and manufactured without application of numerical simulation of injection moulding process. According to the shortcomings found out in evaluation process, by application of numerical simulation of injection moulding process, the optimisation of the mould design was conducted in several stages to achieve as optimal as possible moulded part quality and injection moulding process parameters without dramatic changes in already manufactured mould.

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14

Susantez, Çiğdem, and Aldélio Bueno Caldeira. "Genetic Algorithm Optimisation of a TNT Solidification Model." Defence Science Journal 69, no. 6 (December 16, 2019): 545–49. http://dx.doi.org/10.14429/dsj.69.14037.

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The control of the solidification process of energetic materials is important to prevent manufacturing defects in high explosive ammunitions. The present work aims to propose an optimisation procedure to determine the value of the model parameter, avoiding the traditional trial and error approach. In this work, the solidification of TNT has been numerically modelled employing apparent heat capacity method and the model parameter was optimised using genetic algorithm. One dimensional numerical model has been solved in Comsol Multiphysics Modeling Software and the genetic algorithm code was written in Matlab. The Neumann’s analytical solution of the solidification front was used as a reference to build the fitness function, following the inverse problems concepts. The optimum model parameter has been predicted after 20 generations and among 30 candidate solutions for each generation. The numerical solution performed with the optimised model parameter has agreed with the analytical solution, indicating the feasibility of the proposed procedure. The discrepancy was 3.8 per cent when maximum difference between analytical and numerical solutions was observed.

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15

Zhang, Meng Jian, Dao Yin Long, Dan Dan Li, Xiao Wang, Tao Qin, and Jing Yang. "A novel chaotic grey wolf optimisation for high-dimensional and numerical optimisation." International Journal of Computer Applications in Technology 67, no. 2/3 (2021): 194. http://dx.doi.org/10.1504/ijcat.2021.121524.

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Yang, Jing, Xiao Wang, Tao Qin, Dao Yin Long, Dan Dan Li, and Meng Jian Zhang. "A novel chaotic grey wolf optimisation for high-dimensional and numerical optimisation." International Journal of Computer Applications in Technology 67, no. 2/3 (2021): 194. http://dx.doi.org/10.1504/ijcat.2021.10045758.

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Pinto, Mark Christhian Barrueta, and Yongbo Li. "Numerical investigation on welding process parameters optimisation using multi-objective optimisation technique." International Journal of Advanced Operations Management 12, no. 3 (2020): 195. http://dx.doi.org/10.1504/ijaom.2020.10032145.

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Pinto, Mark Christhian Barrueta, and Yongbo Li. "Numerical investigation on welding process parameters optimisation using multi-objective optimisation technique." International Journal of Advanced Operations Management 12, no. 3 (2020): 195. http://dx.doi.org/10.1504/ijaom.2020.109788.

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19

Berteau, J. Ph, J. Ph Pastre, S. Mesure, M. Pithioux, G. Bolini, and P. Chabrand. "Optimisation of brace treatment with numerical modelling." Computer Methods in Biomechanics and Biomedical Engineering 12, sup1 (August 2009): 45–46. http://dx.doi.org/10.1080/10255840903065399.

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20

Odstrcil, M., J. Mlynar, T. Odstrcil, B. Alper, and A. Murari. "Modern numerical methods for plasma tomography optimisation." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 686 (September 2012): 156–61. http://dx.doi.org/10.1016/j.nima.2012.05.063.

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21

Xiang, qin. "An improved firefly algorithm for numerical optimisation." International Journal of Computing Science and Mathematics 6, no. 2 (2015): 201. http://dx.doi.org/10.1504/ijcsm.2015.069466.

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22

Guo, Bao-Yu, Ke-Jun Dong, and Ai-Bing Yu. "Optimisation of sputnik distributor using numerical method." International Journal of Computational Fluid Dynamics 23, no. 2 (February 2009): 119–35. http://dx.doi.org/10.1080/10618560902740618.

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23

G., W., and Philippe G. Ciarlet. "Introduction to Numerical Linear Algebra and Optimisation." Mathematics of Computation 55, no. 191 (July 1990): 395. http://dx.doi.org/10.2307/2008817.

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24

Dai, Chaohua, Jiajun Ouyang, Weirong Chen, Yunfang Zhu, and Lei Ma. "Human group optimiser for global numerical optimisation." International Journal of Bio-Inspired Computation 6, no. 5 (2014): 333. http://dx.doi.org/10.1504/ijbic.2014.065586.

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25

Naar, Raphaëlle, and François Bay. "Numerical optimisation for induction heat treatment processes." Applied Mathematical Modelling 37, no. 4 (February 2013): 2074–85. http://dx.doi.org/10.1016/j.apm.2012.04.058.

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26

Guha, A. "Optimisation of aero gas turbine engines." Aeronautical Journal 105, no. 1049 (July 2001): 345–58. http://dx.doi.org/10.1017/s0001924000012264.

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Abstract A systematic methodology for the thermodynamic optimisation of civil bypass engines (turbofan or advanced propulsors) is presented, which would be useful for designing air-breathing engines based on “clean-sheet analysis”. The process starts with establishing an optimum specific thrust for the engine based on an economic analysis (installation constraints, noise regulations etc. also need to be considered). The task of the optimisation process is then to find the combination of optimum values of fan pressure ratio, overall pressure ratio, bypass ratio and turbine entry temperature concurrently that maximises overall efficiency at the fixed specific thrust. This procedure is quite different from the usual single-variable parametric performance studies which do not give proper optimum values and may involve large excursion in the value of the specific thrust unacceptable for a particular mission. Additionally, several, simple and explicit, analytical relations are derived here from fundamental principles, which perform well against numerical optimisation performed by a specialist computer program employing iterative and advanced search techniques. The analytical relations accelerate the optimisation process and offer physical insight. Present numerical computations with real gas properties have established new concepts in turbofan optimisation (for example, the existence of an optimum bypass ratio and optimum turbine entry temperature). The question of optimum jet velocity has been addressed. An analytical expression for the optimum jet velocity at a given bypass ratio has been derived which performs well against numerical optimisation results.

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27

Shariatmadar, Keivan, and Mark Versteyhe. "Numerical Linear Programming under Non-Probabilistic Uncertainty Models — Interval and Fuzzy Sets." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 28, no. 03 (May 21, 2020): 469–95. http://dx.doi.org/10.1142/s0218488520500191.

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This paper considers a linear optimisation problem under uncertainty with at least one element modelled as a non-probabilistic uncertainty. The uncertainty is expressed in the coefficient matrices of constraints and/or coefficients of goal function. Previous work converts such problems to classical (linear) optimisation problems and eliminates uncertainty by converting the linear programming under uncertainty problem to a decision problem using imprecise probability and imprecise decision theory. Our aim here is to generalise this approach numerically and present three methods to calculate the solution. We investigate what numerical results can be obtained for interval and fuzzy types of uncertainty models and compare them to classical probabilistic cases — for two different optimality criteria: maximinity and maximality. We also provide an efficient method to calculate the maximal solutions in the fuzzy set model. A numerical example is considered for illustration of the results.

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Haas, Titus, Sascha Weikert, and Konrad Wegener. "MPCC-Based Set Point Optimisation for Machine Tools." International Journal of Automation Technology 13, no. 3 (May 5, 2019): 407–18. http://dx.doi.org/10.20965/ijat.2019.p0407.

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Numerical control code is typically used for manufacturing a workpiece using machine tools. Most state-of-the-art approaches decouple the set point optimisation into two steps: the geometry and the feed rate optimisation that does not necessarily result in time-optimal set points for the desired geometry. Given the originally programmed geometry through the numerical control code, dynamic constraints of the machine tool, and maximum permissible contour error for the optimisation, a model predictive contouring control based set point optimisation approach is developed to generate time-optimal set points for machine tools globally. A suitable error definition and its linearisation are used whereby the optimisation problem can be represented by a quadratic programming problem with linear constraints. Compared to most state-of-the-art methods, a direct approach is presented and no previous geometry optimisation step is required. Depending on the demands of accuracy, different maximum contour error constraints and penalisation as well as various maximum permissible axis velocities and accelerations are presented and tested on a test bench. The method is shown to be adaptable to different demands on the set points, and the contour errors can be affected by either the constraints or penalising factors.

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Ali, Karim, Tim Stallard, and Pablo Ouro. "Evaluating wind-farm power generation using a new direct integration of axisymmetric turbine wake." Journal of Physics: Conference Series 2767, no. 9 (June 1, 2024): 092015. http://dx.doi.org/10.1088/1742-6596/2767/9/092015.

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Abstract Engineering wake models enable fast calculation of wind-farm power generation including wake-turbine interactions, which is critical for annual energy yield calculations and for farm optimisation either at the design phase or during operation. The operating point of a turbine is determined based on its rotor-averaged wind speed, which is impacted by upstream wakes. The rotor-averaged deficit is typically calculated numerically by using a set of averaging points across the rotor disk, for which a Gaussian shape function is commonly evaluated. This numerical approach can have uncertainty based on the distribution of the averaging points. Also, a large number of averaging points can increase computational cost, which is detrimental for studies that rely on many individual calculations of farm power generation, e.g. layout optimisation. To avoid these drawbacks, we present a novel analytical solution to the circular-disk integration of a two-dimensional axisymmetric Gaussian function depicting upstream wakes for an arbitrary lateral offset between the rotor and the wake source. The analytical expression is compared against numerical averaging of an upstream wake, and is applied to the Horns Rev 1 wind farm showing excellent accuracy. Wind-farm layout optimisation models, especially methods based on gradient-descent optimisation, can benefit from the presented expression significantly, as this provides an analytically differentiable formulation for the rotor-averaged wind speed.

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Godi, N. Y., L. B. Zhengwuvi, and M. O. Petinrin. "Forced convection heat transfer in micro heat sinks with square and circular configuration." Nigerian Journal of Technological Development 20, no. 2 (October 10, 2023): 35–42. http://dx.doi.org/10.4314/njtd.v20i2.1272.

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This paper reports the results of three-dimensional numerical optimisation of microchannel heat exchanger with square and circular cooling channels. The objective of the optimisation is to maximise the global thermal conductance or minimise global thermal resistance. Response surface optimisation methodology (RSM) is used in the numerical optimisation. A high-density heat flux (2.5×106W/m2) is imposed at the bottom surface of the unit cell microchannel and numerical simulation carried out using ANSYS Fluent commercial software package.The elemental volume and axial length N=10mm of the microchannel were all fixed, while the width was free to morph. The cooling technique employs single-phase water which flows through the rectangular block microchannel heat sink to remove the heat at the bottom of the microchannels in a forced convection laminar flow regime. The velocity of the fluid pumped across the microchannel axial length is the range 400≤Rew≤500. Finite volume method (FVM) is used to descretised the computational domain and computational fluid dynamic (CFD) code employed to solve a series of governing equations. The effect of channel hydraulic diameter and Reynolds number of water-flow on peak wall temperature and minimised temperature are investigated and reported. The numerical results show that the microchannel with square cooling channel has the highest maximised global thermal conductance than the micro heat sink with circular configuration. The result of the numerical study agrees with what is in the open literature.

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Düğenci, Muharrem, and Mehmet Emin Aydin. "A honeybees-inspired heuristic algorithm for numerical optimisation." Neural Computing and Applications 32, no. 16 (October 16, 2019): 12311–25. http://dx.doi.org/10.1007/s00521-019-04533-x.

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Abstract Swarm intelligence is all about developing collective behaviours to solve complex, ill-structured and large-scale problems. Efficiency in collective behaviours depends on how to harmonise the individual contributors so that a complementary collective effort can be achieved to offer a useful solution. The main points in organising the harmony remain as managing the diversification and intensification actions appropriately, where the efficiency of collective behaviours depends on blending these two actions appropriately. In this paper, a hybrid bee algorithm is presented, which harmonises bee operators of two mainstream well-known swarm intelligence algorithms inspired of natural honeybee colonies. The parent algorithms have been overviewed with many respects, strengths and weaknesses are identified, first, and the hybrid version has been proposed, next. The efficiency of the hybrid algorithm is demonstrated in comparison with the parent algorithms in solving two types of numerical optimisation problems; (1) a set of well-known functional optimisation benchmark problems and (2) optimising the weights of a set of artificial neural network models trained for medical classification benchmark problems. The experimental results demonstrate the outperforming success of the proposed hybrid algorithm in comparison with two original/parent bee algorithms in solving both types of numerical optimisation benchmarks.

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Porsev, V. I., A. I. Sivkov, and E. P. Voroshilin. "Estimating angular velocities of a ballistic object using radial acceleration." Journal of «Almaz – Antey» Air and Space Defence Corporation, no. 2 (June 30, 2016): 30–35. http://dx.doi.org/10.38013/2542-0542-2016-2-30-35.

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We developed an algorithm for estimating the total velocity vector of a ballistic object based on its radial acceleration, without employing numerical optimisation methods. We supply a comparison between the efficiency of the algorithm functioning and an existing optimisation method.

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33

Khurana, M., and H. Winarto. "Development and validation of an efficient direct numerical optimisation approach for aerofoil shape design." Aeronautical Journal 114, no. 1160 (October 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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Sun, Liang, and Bing Wang. "Robust Optimisation Approach for Vehicle Routing Problems with Uncertainty." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/901583.

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We formulated a solution procedure for vehicle routing problems with uncertainty (VRPU for short) with regard to future demand and transportation cost. Unlike E-SDROA (expectation semideviation robust optimisation approach) for solving the proposed problem, the formulation focuses on robust optimisation considering situations possibly related to bidding and capital budgets. Besides, numerical experiments showed significant increments in the robustness of the solutions without much loss in solution quality. The differences and similarities of the robust optimisation model and existing robust optimisation approaches were also compared.

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Banks, Robert J., Dan E. Browne, and P. A. Warburton. "Rapid quantum approaches for combinatorial optimisation inspired by optimal state-transfer." Quantum 8 (February 13, 2024): 1253. http://dx.doi.org/10.22331/q-2024-02-13-1253.

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We propose a new design heuristic to tackle combinatorial optimisation problems, inspired by Hamiltonians for optimal state-transfer. The result is a rapid approximate optimisation algorithm. We provide numerical evidence of the success of this new design heuristic. We find this approach results in a better approximation ratio than the Quantum Approximate Optimisation Algorithm at lowest depth for the majority of problem instances considered, while utilising comparable resources. This opens the door to investigating new approaches for tackling combinatorial optimisation problems, distinct from adiabatic-influenced approaches.

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Ramakrishna, Varanasi, Shinadam Rama Krishna, and PVS Ganesh Kumar. "Experimental and Numerical Investigation of Engine Foundation for Vibration Reduction." Defence Science Journal 68, no. 6 (October 31, 2018): 604. http://dx.doi.org/10.14429/dsj.68.12705.

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<p>The purpose of this study is to minimise frequency response of engine foundation using topology optimisation. The study involves vibration response estimation of an existing marine engine foundation, validation of estimations with measurements and estimation of reduction in vibration response after optimisation. Initially, solid model of baseline model is generated using dimensions of the existing foundation measured by a laser line probe coordinate measuring machine. Harmonic analysis is used to find the vibration response of the foundation. These results are experimentally validated by the measurements on the foundation using the vibration testing. Frequency response topology optimisation is then carried out on the baseline model to reduce vibration response with specified constraints and objective function. Subsequently, harmonic analysis is performed on the topology optimised design to verify the reduction in vibration response. From these results, it is observed that considerable frequency response is reduced with modified design compared to baseline model.</p>

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Merklein, Marion, Maren Johannes, M. Biasutti, and Michael Lechner. "Numerical Optimisation of a Shear Specimen Geometry According to ASTM." Key Engineering Materials 549 (April 2013): 317–24. http://dx.doi.org/10.4028/www.scientific.net/kem.549.317.

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Complex material models used for the numerical representation of forming processes need in addition to tension and compression tests also shear tests to completely analyse the behaviour of the material under different loading conditions. There are two concepts of shear test one uses symmetrical specimens with two shear zones (according to Miyauchi) the other one specimens with a single shear zone. In both cases, a homogeneous distribution of the strain in the shear zone is essential for the validity of the shear test. Therefore, the length and width of the shear zone in a single shear specimen made from high strength steel according to the ASTM standard geometry were varied. Analysing the resulting strain distribution numerically an optimised sample geometry with a more uniform strain distribution than the ASTM standard was achieved. The numerical results were also validated with experimental shear tests.

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Kijanski, Wojciech, and Franz-Joseph Barthold. "Two-scale shape optimisation based on numerical homogenisation techniques and variational sensitivity analysis." Computational Mechanics 67, no. 4 (March 6, 2021): 1021–40. http://dx.doi.org/10.1007/s00466-020-01955-6.

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AbstractThis contribution presents a theoretical and computational framework for two-scale shape optimisation of nonlinear elastic structures. Particularly, minimum compliance optimisation problems with composite (matrix-inclusion) microstructures subjected to static loads and volume-type design constraints are focused. A homogenisation-based FE$$^2$$ 2 scheme is extended by an enhanced formulation of variational (shape) sensitivity analysis based on Noll’s intrinsic, frame-free formulation of continuum mechanics. The obtained overall two-scale sensitivity information couples shape variations across micro- and macroscopic scales. A numerical example demonstrates the capabilities of the proposed variational sensitivity analysis and the (shape) optimisation framework. The investigations involve a mesh morphing scheme for the design parametrisation at both macro- and microscopic scales.

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Ait Ouchaoui, A., M. Nassraoui, and 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, no. 2 (October 1, 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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Lógó, J., and E. Pintér. "Numerical Methods in Probabilistic Topology Optimisation: A Review." Computational Technology Reviews 5 (September 4, 2012): 79–108. http://dx.doi.org/10.4203/ctr.5.3.

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41

Colloud, Floren. "Advanced modelling of human movements using numerical optimisation." Movement & Sport Sciences 90, no. 4 (2015): 1. http://dx.doi.org/10.3917/sm.090.0001.

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Colloud, Floren. "Advanced modelling of human movements using numerical optimisation." Movement & Sport Sciences - Science & Motricité, no. 90 (2015): 1–6. http://dx.doi.org/10.1051/sm/2016001.

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Roshanaei, M. M., C. Lucas, and A. R. Mehrabian. "Adaptive beamforming using a novel numerical optimisation algorithm." IET Microwaves, Antennas & Propagation 3, no. 5 (2009): 765. http://dx.doi.org/10.1049/iet-map.2008.0188.

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Hiltcher, Yann, Michèle Guingand, and Jean Pierre de Vaujany. "Numerical simulation and optimisation of worm gear cutting." Mechanism and Machine Theory 41, no. 9 (September 2006): 1090–110. http://dx.doi.org/10.1016/j.mechmachtheory.2005.10.016.

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Xue, Gang, Wenbin Song, Simon J. Cox, and Andy Keane. "Numerical Optimisation as Grid Services for Engineering Design." Journal of Grid Computing 2, no. 3 (September 2004): 223–38. http://dx.doi.org/10.1007/s10723-004-6742-9.

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Boudinar, M. Ben, W. T. Hanbury, and S. Avlonitis. "Numerical simulation and optimisation of spiral-wound modules." Desalination 86, no. 3 (August 1992): 273–90. http://dx.doi.org/10.1016/0011-9164(92)80038-b.

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Draa, Amer, Samira Bouzoubia, and Imene Boukhalfa. "A sinusoidal differential evolution algorithm for numerical optimisation." Applied Soft Computing 27 (February 2015): 99–126. http://dx.doi.org/10.1016/j.asoc.2014.11.003.

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Herty, Michael, and Veronika Schleper. "Time discretizations for numerical optimisation of hyperbolic problems." Applied Mathematics and Computation 218, no. 1 (September 2011): 183–94. http://dx.doi.org/10.1016/j.amc.2011.05.116.

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Fischer, M., and X. Jiang. "Numerical optimisation for model evaluation in combustion kinetics." Applied Energy 156 (October 2015): 793–803. http://dx.doi.org/10.1016/j.apenergy.2015.05.002.

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Colomer, Maria Prat, Luke Mortimer, Irénée Frérot, Máté Farkas, and Antonio Acín. "Three numerical approaches to find mutually unbiased bases using Bell inequalities." Quantum 6 (August 17, 2022): 778. http://dx.doi.org/10.22331/q-2022-08-17-778.

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Abstract:

Mutually unbiased bases correspond to highly useful pairs of measurements in quantum information theory. In the smallest composite dimension, six, it is known that between three and seven mutually unbiased bases exist, with a decades-old conjecture, known as Zauner's conjecture, stating that there exist at most three. Here we tackle Zauner's conjecture numerically through the construction of Bell inequalities for every pair of integers n,d&#x2265;2 that can be maximally violated in dimension d if and only if n MUBs exist in that dimension. Hence we turn Zauner's conjecture into an optimisation problem, which we address by means of three numerical methods: see-saw optimisation, non-linear semidefinite programming and Monte Carlo techniques. All three methods correctly identify the known cases in low dimensions and all suggest that there do not exist four mutually unbiased bases in dimension six, with all finding the same bases that numerically optimise the corresponding Bell inequality. Moreover, these numerical optimisers appear to coincide with the ``four most distant bases'' in dimension six, found through numerically optimising a distance measure in [P. Raynal, X. Lü, B.-G. Englert, {Phys. Rev. A}, { 83} 062303 (2011)]. Finally, the Monte Carlo results suggest that at most three MUBs exist in dimension ten.

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