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Journal articles on the topic 'Optimisation multistage'

Author: Grafiati

Published: 25 May 2024

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1

Goryachkin, E. S., V. N. Matveev, G. M. Popov, O. V. Baturin, and Yu D. Novikova. "Optimisation Method for Multistage Compressors." Herald of the Bauman Moscow State Technical University. Series Mechanical Engineering, no. 3 (138) (September 2021): 38–59. http://dx.doi.org/10.18698/0236-3941-2021-3-38-59.

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The paper presents an algorithm for seeking an optimal blade configuration for multistage axial-flow compressors. The primary tool behind the algorithm is 3D CFD simulation, augmented by commercial optimisation software. The core of the algorithm involves feeding an initial data vector to the parametric simulation module so as to form a "new" blade geometry, which is then transferred to 3D computational software. The results obtained are further processed in a program that implements the algorithm for seeking the optimum and forms a new input data vector to achieve the set goal. We present a method of parametrically simulation the blade shape, implemented in a software package, making it possible to describe the shape of the compressor blade profiles using a minimum number of variables and to automatically change the shape in the optimisation cycle. The algorithm developed allows the main parameters of compressor operation (efficiency, pressure ratio, air flow rate, etc.) to be improved by correcting the profile shape and relative position of the blades. The algorithm takes into account various possible constraints. We used the method developed to solve practical problems of optimising multistage axial compressors of gas turbine engines for various purposes, with the number of compressor stages ranging from 3 to 15. As a result, the efficiency, pressure ratio and stability margin of gas turbine engines were increased

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2

Liu, Y. Z. "Studies on process optimisation of multistage atomisation." Materials Science and Technology 18, no. 8 (August 2002): 929–34. http://dx.doi.org/10.1179/026708302225004766.

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3

Kwak, Doh-Soon, Kwang-Jae Kim, and Myeong-Soo Lee. "Multistage PRIM: patient rule induction method for optimisation of a multistage manufacturing process." International Journal of Production Research 48, no. 12 (May 14, 2009): 3461–73. http://dx.doi.org/10.1080/00207540902791827.

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4

Küttner, R., and J. Majak. "Multistage Optimisation Strategy For Solving Production Planning Problems." IFAC Proceedings Volumes 42, no. 2 (2009): 332–37. http://dx.doi.org/10.3182/20090506-3-sf-4003.00061.

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5

Vasil'ev, S. V., M. A. Kuz'mina, and V. A. Mishin. "Optimisation of a multistage pulsed dye laser system." Quantum Electronics 31, no. 6 (June 30, 2001): 505–9. http://dx.doi.org/10.1070/qe2001v031n06abeh001989.

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6

Fatemifar, Soroush, Shahrokh Asadi, Muhammad Awais, Ali Akbari, and Josef Kittler. "Face spoofing detection ensemble via multistage optimisation and pruning." Pattern Recognition Letters 158 (June 2022): 1–8. http://dx.doi.org/10.1016/j.patrec.2022.04.006.

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7

Armstrong, M., A. Galli, and R. Razanatsimba. "Using multistage stochastic optimisation to manage major production incidents." Mining Technology 121, no. 3 (September 2012): 125–31. http://dx.doi.org/10.1179/1743286312y.0000000010.

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8

Yan, Zhou, Hany Hassanin, Mahmoud Ahmed El-Sayed, Hossam Mohamed Eldessouky, JRP Djuansjah, Naser A. Alsaleh, Khamis Essa, and Mahmoud Ahmadein. "Multistage Tool Path Optimisation of Single-Point Incremental Forming Process." Materials 14, no. 22 (November 11, 2021): 6794. http://dx.doi.org/10.3390/ma14226794.

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Single-point incremental forming (SPIF) is a flexible technology that can form a wide range of sheet metal products without the need for using punch and die sets. As a relatively cheap and die-less process, this technology is preferable for small and medium customised production. However, the SPIF technology has drawbacks, such as the geometrical inaccuracy and the thickness uniformity of the shaped part. This research aims to optimise the formed part geometric accuracy and reduce the processing time of a two-stage forming strategy of SPIF. Finite element analysis (FEA) was initially used and validated using experimental literature data. Furthermore, the design of experiments (DoE) statistical approach was used to optimise the proposed two-stage SPIF technique. The mass scaling technique was applied during the finite element analysis to minimise the computational time. The results showed that the step size during forming stage two significantly affected the geometrical accuracy of the part, whereas the forming depth during stage one was insignificant to the part quality. It was also revealed that the geometrical improvement had taken place along the base and the wall regions. However, the areas near the clamp system showed minor improvements. The optimised two-stage strategy successfully decreased both the geometrical inaccuracy and processing time. After optimisation, the average values of the geometrical deviation and forming time were reduced by 25% and 55.56%, respectively.

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9

Loveday, B. K., and A. L. Hemphill. "Optimisation of a multistage flotation plant using plant survey data." Minerals Engineering 19, no. 6-8 (May 2006): 627–32. http://dx.doi.org/10.1016/j.mineng.2005.09.014.

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10

Söylemez, Mehmet Sait. "On the thermo-economic optimisation of multistage flash evaporation desalination plants." International Journal of Nuclear Governance, Economy and Ecology 4, no. 2 (2014): 153. http://dx.doi.org/10.1504/ijngee.2014.065935.

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11

Rocha, Paula, and Daniel Kuhn. "Multistage stochastic portfolio optimisation in deregulated electricity markets using linear decision rules." European Journal of Operational Research 216, no. 2 (January 2012): 397–408. http://dx.doi.org/10.1016/j.ejor.2011.08.001.

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12

Cong, Cong, Shiyu Xuan, Sidong Liu, Shiliang Zhang, Maurice Pagnucco, and Yang Song. "Decoupled Optimisation for Long-Tailed Visual Recognition." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 2 (March 24, 2024): 1380–88. http://dx.doi.org/10.1609/aaai.v38i2.27902.

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When training on a long-tailed dataset, conventional learning algorithms tend to exhibit a bias towards classes with a larger sample size. Our investigation has revealed that this biased learning tendency originates from the model parameters, which are trained to disproportionately contribute to the classes characterised by their sample size (e.g., many, medium, and few classes). To balance the overall parameter contribution across all classes, we investigate the importance of each model parameter to the learning of different class groups, and propose a multistage parameter Decouple and Optimisation (DO) framework that decouples parameters into different groups with each group learning a specific portion of classes. To optimise the parameter learning, we apply different training objectives with a collaborative optimisation step to learn complementary information about each class group. Extensive experiments on long-tailed datasets, including CIFAR100, Places-LT, ImageNet-LT, and iNaturaList 2018, show that our framework achieves competitive performance compared to the state-of-the-art.

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13

Bruno, Giuseppe, Gianpaolo Ghiani, Gennaro Improta, and Emanuele Manni. "A taboo search heuristic for the optimisation of a multistage component placement system." Journal of Discrete Mathematical Sciences and Cryptography 8, no. 2 (January 2005): 271–85. http://dx.doi.org/10.1080/09720529.2005.10698038.

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14

Volsem, Sofie Van. "Joint optimisation of all inspection parameters for multistage processes: evolutionary algorithm and simulation." International Journal of Innovative Computing and Applications 2, no. 3 (2010): 170. http://dx.doi.org/10.1504/ijica.2010.033648.

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15

Mazurkiewicz, Łukasz A., Jakub Bukała, Jerzy Małachowski, Michał Tomaszewski, and Piotr P. Buszman. "BVS stent optimisation based on a parametric model with a multistage validation process." Materials & Design 198 (January 2021): 109363. http://dx.doi.org/10.1016/j.matdes.2020.109363.

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16

Lusa, Amaia, Albert Corominas, and Norberto Muñoz. "A multistage scenario optimisation procedure to plan annualised working hours under demand uncertainty." International Journal of Production Economics 113, no. 2 (June 2008): 957–68. http://dx.doi.org/10.1016/j.ijpe.2007.11.009.

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17

Calvet, J. P., and L. C. Zullo. "Modelling and optimisation of a backmixed, multistage reactor for an industrial reactive system." Computers & Chemical Engineering 17 (January 1993): S129—S134. http://dx.doi.org/10.1016/0098-1354(93)80218-c.

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18

Calvet, J. "Modelling and optimisation of a backmixed, multistage reactor for an industrial reactive system." Computers & Chemical Engineering 17, no. 1 (1993): S129—S134. http://dx.doi.org/10.1016/0098-1354(93)85019-i.

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19

Li, Yu, Liang Li, Tong Zhao, and Jun Li. "Aerodynamic optimisation of a low-pressure multistage turbine using the response-surface method." Journal of Mechanical Science and Technology 27, no. 8 (August 2013): 2537–46. http://dx.doi.org/10.1007/s12206-013-0638-1.

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20

Zhang, Zhaoxia. "Improvement of Computer Adaptive Multistage Testing Algorithm Based on Adaptive Genetic Algorithm." International Journal of Intelligent Information Technologies 20, no. 1 (May 17, 2024): 1–19. http://dx.doi.org/10.4018/ijiit.344024.

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Multistage testing (MST) is a portion of computational adaptive testing that adapts assessment structure at the sublevel rather than the component level. The goal of the MST algorithm is to identify bugs in computer programming, and there is a significant cost to utilising MST due to its decreased versatility during software development and maintenance. The efficiency of most algorithms drastically reduces for adaptive MST with complex feasible regions, while some modern algorithms function well while tackling computerised MST with a basic practicable range. The study offers an automated Adaptive Multistage Testing algorithm based on Adaptive Genetic Algorithm (AMST-AGA) for optimisation and scalability problems, in which constraints are successively introduced and dealt with at various evolutionary phases. In this paper, many test cases will aid in finding bugs and meeting completeness goals. Each time test cases are created, these testing scenarios must continue to pass.

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21

Mappas, Vasileios, Vassilios S. Vassiliadis, Bogdan Dorneanu, Alexander F. Routh, and Harvey Arellano-Garcia. "Maintenance scheduling optimisation of Reverse Osmosis Networks (RONs) via a multistage Optimal Control reformulation." Desalination 543 (December 2022): 116105. http://dx.doi.org/10.1016/j.desal.2022.116105.

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22

Minoux, Michel. "Robust and stochastic multistage optimisation under Markovian uncertainty with applications to production/inventory problems." International Journal of Production Research 56, no. 1-2 (November 2017): 565–83. http://dx.doi.org/10.1080/00207543.2017.1394597.

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23

Manimaran, P., V. Selladurai, W. C. Yeh, and M. Sivakumar. "Particle Swarm Optimisation for fixed-charge transportation problem in a Multistage Supply Chain Network." International Journal of Logistics Systems and Management 9, no. 3 (2011): 328. http://dx.doi.org/10.1504/ijlsm.2011.041692.

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24

Manimaran, P., V. Selladurai, and Rajesh Ranganathan. "A simple heuristics for optimisation of unbalanced multistage supply chain logistics associated with fixed charges." International Journal of Procurement Management 4, no. 2 (2011): 203. http://dx.doi.org/10.1504/ijpm.2011.038899.

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25

Yan, Haiyang, Yaoming Wang, Liang Wu, Muhammad A. Shehzad, Chenxiao Jiang, Rongqiang Fu, Zhaoming Liu, and Tongwen Xu. "Multistage-batch electrodialysis to concentrate high-salinity solutions: Process optimisation, water transport, and energy consumption." Journal of Membrane Science 570-571 (January 2019): 245–57. http://dx.doi.org/10.1016/j.memsci.2018.10.008.

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26

Abe, Y., K. Mori, and O. Ebihara. "Optimisation of the distribution of wall thickness in the multistage sheet metal forming of wheel disks." Journal of Materials Processing Technology 125-126 (September 2002): 792–97. http://dx.doi.org/10.1016/s0924-0136(02)00394-1.

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27

Li, Liang, Changhe Du, Xiaojun Fan, and Gangyun Zhong. "Optimisation of a low-pressure multistage steam turbine towards decreasing the wetness losses and aerodynamic losses." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 230, no. 4 (February 12, 2016): 345–53. http://dx.doi.org/10.1177/0957650916630036.

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28

Szelag, Wojciech, Cezary Jedryczka, Mariusz Baranski, and Milena Kurzawa. "Design, Analysis and Experimental Verification of a Coreless Permanent Magnet Synchronous Motor." Energies 17, no. 7 (March 30, 2024): 1664. http://dx.doi.org/10.3390/en17071664.

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The paper presents a new cost-effective magnetic circuit structure of a coreless permanent magnet synchronous motor (PMSM) with 16 poles and 12 coils for a mass production fan drive unit. 2D and 3D numerical models of the coreless PMSM were developed. Optimisation calculations were carried out using the field model of the machine. Multistage calculations were performed using the professional FEM package, ANSYS Maxwell and the author’s proprietary finite element method (FEM) code. On the basis of the conducted tests and analysis of the obtained results, the “optimal” magnetic circuit structure of the PMSM motor was selected. The prototype motor was subjected to measurement to verify the developed models and the proposed design approach that takes advantage of finite element analysis (FEA).

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29

Karczewski, Artur, and Janusz Kozak. "Variant Designing in the Preliminary Small Ship Design Process." Polish Maritime Research 24, no. 2 (June 27, 2017): 77–82. http://dx.doi.org/10.1515/pomr-2017-0052.

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Abstract Ship designing is a complex process, as the ship itself is a complex, technical multi-level object which operates in the air/water boundary environment and is exposed to the action of many different external and internal factors resulting from the adopted technical solutions, type of operation, and environmental conditions. A traditional ship design process consists of a series of subsequent multistage iterations, which gradually increase the design identification level. The paper presents problems related to the design of a small untypical vessel with the aid of variant methodology making use of optimisation algorithms. The computer-aided design methodology has been developed which does not need permanent reference to already built real ships and empirical-statistical relations. Possibilities were indicated for integrating together early design stages, and parallel designing of hull shape and parameters.

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30

McMurray, Robert J., M. O’Donnell, Alan G. Leacock, and Desmond Brown. "Modelling the Effect of Pre-Strain and Inter-Stage Annealing on the Stretch Forming of a 2024 Aluminium Alloy." Key Engineering Materials 410-411 (March 2009): 421–28. http://dx.doi.org/10.4028/www.scientific.net/kem.410-411.421.

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The severe double curvatures often encountered in aerospace fuselage and nacelle skins often necessitate multistage stretch forming operations. Each stage adds value to the component and rejection, particularly at later stages, must be avoided. Therefore process optimisation using accurate modelling tools to predict the strain levels is essential. This paper presents a novel method for modelling the aforementioned stages of the process using a tailored material model based on strain history and heat treatment. The modelling process is implemented within the PAMSTAMP Finite Element code, by modifying the material properties in the input file using an Excel based algorithm. The proposed method is validated using profiled stretch formed specimens, thereby imposing a variable strain gradient in a single specimen without having to resort to the complexity of double curvature. The model results are shown to represent the observed behaviour well.

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31

Mukherjee, Indrajit, and Pradip Kumar Ray. "Quality improvement of multistage and multi-response grinding processes: an insight into two different methodologies for parameter optimisation." International Journal of Productivity and Quality Management 4, no. 5/6 (2009): 613. http://dx.doi.org/10.1504/ijpqm.2009.025188.

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32

Shopa, Roman Y., and Kamil Dulski. "Positronium imaging in J-PET with an iterative activity reconstruction and a multistage fitting algorithm." Bio-Algorithms and Med-Systems 19, no. 1 (December 31, 2023): 54–63. http://dx.doi.org/10.5604/01.3001.0054.1826.

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Positronium imaging is a new technique complementary to positron emission tomography (PET) based on the histogramming of time delay between the emission of a de-excitation photon, and a consequent electron-positron annihilation, to estimate the mean lifetime of orthopositronium (o-Ps), which depends on the local size of the voids, concentration of oxygen and bioactive molecules. We improve the resolution and reduce noise in positronium imaging by building time-delay spectra from the PET activity reconstructed by a 3-photon time-of-flight maximum likelihood expectation maximisation. The method was tested on the data measured for four human-tissue samples injected by 22Na and put in the Jagiellonian PET “Big barrel” scanner. Due to an ill-posed problem of fitting time-delay histograms, a multistage optimisation procedure was explored along with inferential analysis of the solution space. Run in parallel for multiple sets of initial guesses, we compared the second-order LevenbergMarquardt algorithm (LMA) and the direct search Nelder-Mead simplex (NMS) method. The LMA proved to be faster and more precise, but the NMS was more stable with a higher convergence rate. The estimated mean o-Ps lifetimes in the 1.9 ns – 2.6 ns range were consistent with the reference results, while other fitting parameters allowed differentiation between the two patients who provided the tissue samples.

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33

Mupondo, Ndava Constantine. "Use of Multistage Optimisation Technique in Formulation of Strategies to Reduce Customer Churn Problem Facing Internet Operators in Zimbabwe." Science Journal of Applied Mathematics and Statistics 1, no. 2 (2013): 7. http://dx.doi.org/10.11648/j.sjams.20130102.11.

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34

Liang, Zhi-chao, Yu Yang, Qiu Xie, Jing Wang, Xue-jiao Zhang, and Bao-dong Li. "Dynamic three-sided matching model for personnel–robot-position matching problem in intelligent environments." PLOS ONE 18, no. 4 (April 7, 2023): e0282312. http://dx.doi.org/10.1371/journal.pone.0282312.

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In recent years, intelligent robots have facilitated intelligent production, and a new type of problem (personnel–robot-position matching (PRPM)) has been encountered in personnel–position matching (PPM). In this study, a dynamic three-sided matching model is proposed to solve the PRPM problem in an intelligent production line based on man–machine collaboration. The first issue considered is setting the dynamic reference point, which is addressed in the information evaluation phase by proposing a method for setting the dynamic reference point based on the prospect theory. Another important issue involves multistage preference information integration, wherein a probability density function and a value function are introduced. Considering the attenuation of preference information in a time series, the attenuation index model is introduced to calculate the satisfaction matrix. Furthermore, a dynamic three-sided matching model is established. Additionally, a multi-objective decision-making model is established to optimize the matching of multiple sides (personnel, intelligent robots, and positions). Subsequently, the model is transformed into a single objective model using the triangular balance principle, which is introduced to obtain the final optimisation results in this modelling process. A case study is presented to illustrate the practicality of the dynamic three-sided matching model in intelligent environments. The results indicate that this model can solve the PRPM problem in an intelligent production line.

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35

Al-Obaidi, M. A., J.-P. Li, S. Alsadaie, C. Kara-Zaïtri, and I. M. Mujtaba. "Modelling and optimisation of a multistage Reverse Osmosis processes with permeate reprocessing and recycling for the removal of N-nitrosodimethylamine from wastewater using Species Conserving Genetic Algorithms." Chemical Engineering Journal 350 (October 2018): 824–34. http://dx.doi.org/10.1016/j.cej.2018.06.022.

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36

Picton, H. M., S. E. Harris, W. Muruvi, and E. L. Chambers. "The in vitro growth and maturation of follicles." REPRODUCTION 136, no. 6 (December 2008): 703–15. http://dx.doi.org/10.1530/rep-08-0290.

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The development of technologies to grow oocytes from the most abundant primordial follicles to maturity in vitro holds many attractions for clinical practice, animal production technology and research. The production of fertile oocytes and live offspring has been achieved in mice following the long-term culture of oocytes in primordial follicles from both fresh and cryopreserved ovarian tissue. In contrast, in non-rodent species advances in follicle culture are centred on the growth of isolated preantral follicles. As a functional unit, mammalian preantral follicles are well-suited to culture but primordial and primary follicles do not grow well after isolation from the ovarian stroma. The current challenges for follicle culture are numerous and include: optimisation of culture media and the tailoring of culture environments to match the physiological needs of the cell in vivo; the maintenance of cell–cell communication and signalling during culture; and the evaluation of the epigenetic status, genetic health and fertility of in vitro derived mature oocytes. In large animals and humans, the complete in vitro growth and maturation of oocytes is only likely to be achieved following the development of a multistage strategy that closely mimics the ovary in vivo. In this approach, primordial follicle growth will be initiated in situ by the culture of ovarian cortex. Isolated preantral follicles will then be grown to antral stages before steroidogenic function is induced in the somatic cells. Finally, cytoplasmic and nuclear maturation will be induced in the in vitro derived oocytes with the production of fertile metaphase II gametes.

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37

Krska, R., A. Malachova, F. Berthiller, and H. P. van Egmond. "Determination of T-2 and HT-2 toxins in food and feed: an update." World Mycotoxin Journal 7, no. 2 (January 1, 2014): 131–42. http://dx.doi.org/10.3920/wmj2013.1605.

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Based on the recent scientific opinion of the European Food Safety Authority (EFSA) Panel on Contaminants in the Food Chain on the risks to human and animal health related to the presence of T-2 and HT-2 toxins in food and feed that was published by EFSA in the EFSA Journal, this article provides an update on the determination of these Fusarium mycotoxins. After a brief introduction into the chemistry of these toxins, both chromatographic and immuno-analytical methods are discussed for the determination of these type A trichothecenes. During the last decade, liquid chromatography with (tandem) mass spectrometry has become the most frequently used method for the determination of T-2 and HT-2 toxins, often within a multi-analyte approach. However, complex matrices and the resulting signal suppression effects, as observed particularly in electrospray-mass spectrometry methods owing to matrix effects, may require careful optimisation of clean-up, usage of matrix matched standards, or e.g. the use of internal standards. For specific purposes where extremely low limits of quantification are needed, e.g. for the analysis of duplicate diets, a dedicated gas chromatography method with multistage mass spectrometry has become available. Other novel analytical approaches to determine T-2 and HT-2 toxins in food and feed include biosensor-based methods in surface plasmon resonance and electrochemical formats, as well as DNA microchip assays. For rapid screening, several immunochemical methods (mostly ELISAs) have become available and some are sold as commercial test kits. Whereas these methods work fast, cross-reactivities with other trichothecenes can have an undesired effect on their accuracy. While proficiency tests including T-2 and HT-2 toxins have been carried out, none of the chromatographic or immunochemical methods have been formally validated in interlaboratory validation studies. There are no certified reference materials available for T-2 and HT-2 toxins.

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38

Cau, T. D. H., and R. J. Kaye. "Evolutionary optimisation method for multistorage hydrothermal scheduling." IEE Proceedings - Generation, Transmission and Distribution 149, no. 2 (2002): 152. http://dx.doi.org/10.1049/ip-gtd:20020120.

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39

Huang, Chao-Hui, Chun-Ho Wang, and Guan-Liang Chen. "Multiobjective Multistate System Preventive Maintenance Model with Human Reliability." International Journal of Aerospace Engineering 2021 (July 14, 2021): 1–16. http://dx.doi.org/10.1155/2021/6623810.

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Modern equipment is designed to operate under deteriorating performance conditions resulting from internal ageing and/or external environmental impacts influencing downstream maintenance. This study focuses on the development of a multistate system (MSS) that considers a human reliability factor associated with maintenance personnel—a condition-based multiobjective MSS preventive maintenance model (MSSPMM). The study assumes that no more than one maintenance activity is performed to achieve the most appropriate preventive maintenance (PM) strategy and easy implementation and to reduce maintenance error due to human reliability. The MSS performance based on mean system unavailability and total maintenance cost is evaluated using a stochastic model approach, and then, the MSSPMM is used for optimisation. A customised version of the nondominated sorting genetic algorithm III is employed to ensure efficient solution of the PM model with human reliability—which is considered a constrained multiobjective combinatorial optimisation problem. The optimised solutions are determined from the nondominated Pareto frontier comprising the diversified PM alternatives. A helicopter power transmission system is used as an example to illustrate the efficacy and applicability of the proposed approach through sensitivity analyses with relevant parameters.

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40

Kajal, Sanjay, and P. C. Tewari. "Performance optimisation of a multistate operating system with hot redundancy." International Journal of Intelligent Enterprise 2, no. 4 (2014): 294. http://dx.doi.org/10.1504/ijie.2014.069069.

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41

Hufenbach, W., and M. Gude. "Analysis and optimisation of multistable composites under residual stresses." Composite Structures 55, no. 3 (February 2002): 319–27. http://dx.doi.org/10.1016/s0263-8223(01)00153-2.

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42

Betrò, Bruno, and Fabio Schoen. "Sequential stopping rules for the multistart algorithm in global optimisation." Mathematical Programming 38, no. 3 (October 1987): 271–86. http://dx.doi.org/10.1007/bf02592015.

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43

Shterenlikht, Anton, Mohammad M. Kashani, Nicholas A. Alexander, Gethin Williams, and Adam J. Crewe. "Autotuning of Isotropic Hardening Constitutive Models on Real Steel Buckling Data with Finite Element Based Multistart Global Optimisation on Parallel Computers." Modelling and Simulation in Engineering 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/6132106.

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An automatic framework for tuning plastic constitutive models is proposed. It is based on multistart global optimisation method, where the objective function is provided by the results of multiple elastoplastic finite element analyses, executed concurrently. Wrapper scripts were developed for fully automatic preprocessing, including model and mesh generation, analysis, and postprocessing. The framework is applied to an isotropic power hardening plasticity using real load/displacement data from multiple steel buckling tests. M. J. D. Powell’s BOBYQA constrained optimisation package was used for local optimisation. It is shown that using the real data presents multiple problems to the optimisation process because (1) the objective function can be discontinuous, yet (2) relatively flat around multiple local minima, with (3) similar values of the objective function for different local minima. As a consequence the estimate of the global minimum is sensitive to the amount of experimental data and experimental noise. The framework includes the verification step, where the estimate of the global minimum is verified on a different geometry and loading. A tensile test was used for verification in this work. The speed of the method critically depends on the ability to effectively parallelise the finite element solver. Three levels of parallelisation were exploited in this work. The ultimate limitation was the availability of the finite element commercial solver license tokens.

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44

Zhang, Lei, Yifan Zhou, and Chuanhui Huang. "An approximate hybrid approach to maintenance optimisation for a system with multistate components." International Journal of System Assurance Engineering and Management 8, no. 1 (December 22, 2016): 189–96. http://dx.doi.org/10.1007/s13198-016-0560-x.

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Brahim, Elhacen, Sofiane Guessasma, Abdellatif Imad, and Noureddine Benseddiq. "Identification of the mechanical behaviour of biopolymer composites using multistart optimisation technique." Materials & Design 51 (October 2013): 391–97. http://dx.doi.org/10.1016/j.matdes.2013.04.005.

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Zhou, Yifan, Libo Liu, and Hao Li. "Reliability estimation and optimisation of multistate flow networks using a conditional Monte Carlo method." Reliability Engineering & System Safety 221 (May 2022): 108382. http://dx.doi.org/10.1016/j.ress.2022.108382.

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Yusuf, Noor, and Tareq Al-Ansari. "Current and Future Role of Natural Gas Supply Chains in the Transition to a Low-Carbon Hydrogen Economy: A Comprehensive Review on Integrated Natural Gas Supply Chain Optimisation Models." Energies 16, no. 22 (November 20, 2023): 7672. http://dx.doi.org/10.3390/en16227672.

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Abstract:

Natural gas is the most growing fossil fuel due to its environmental advantages. For the economical transportation of natural gas to distant markets, physical (i.e., liquefaction and compression) or chemical (i.e., direct and indirect) monetisation options must be considered to reduce volume and meet the demand of different markets. Planning natural gas supply chains is a complex problem in today’s turbulent markets, especially considering the uncertainties associated with final market demand and competition with emerging renewable and hydrogen energies. This review study evaluates the latest research on mathematical programming (i.e., MILP and MINLP) as a decision-making tool for designing and planning natural gas supply chains under different planning horizons. The first part of this study assesses the status of existing natural gas infrastructures by addressing readily available natural monetisation options, quantitative tools for selecting monetisation options, and single-state and multistate natural gas supply chain optimisation models. The second part investigates hydrogen as a potential energy carrier for integration with natural gas supply chains, carbon capture utilisation, and storage technologies. This integration is foreseen to decarbonise systems, diversify the product portfolio, and fill the gap between current supply chains and the future market need of cleaner energy commodities. Since natural gas markets are turbulent and hydrogen energy has the potential to replace fossil fuels in the future, addressing stochastic conditions and demand uncertainty is vital to hedge against risks through designing a responsive supply chain in the project’s early design stages. Hence, hydrogen supply chain optimisation studies and the latest works on hydrogen–natural gas supply chain optimisation were reviewed under deterministic and stochastic conditions. Only quantitative mathematical models for supply chain optimisation, including linear and nonlinear programming models, were considered in this study to evaluate the effectiveness of each proposed approach.

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Zhou, Yifan, Tian Ran Lin, Yong Sun, Yangqing Bian, and Lin Ma. "An effective approach to reducing strategy space for maintenance optimisation of multistate series–parallel systems." Reliability Engineering & System Safety 138 (June 2015): 40–53. http://dx.doi.org/10.1016/j.ress.2015.01.018.

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Peng, Huan, Yu Fan, Junliang Peng, Huifen Han, Xinping Gao, Liang Wang, Xinghao Gou, Yuelin Yin, and Yuchao Zhou. "Research and Application of a Proppant Transport Experimental Device for Complex Fractures in the Unconventional Reservoir." Geofluids 2022 (January 18, 2022): 1–10. http://dx.doi.org/10.1155/2022/8356470.

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Due to the brittleness of the shale and tight reservoir and the development of natural fractures and horizontal beddings, complex fractures will be built by shear slip and tensile failure during multistaged horizontal well fracturing. Whether proppant can enter complex fractures and form effective support in main fractures and branch fractures determines conductivity of the complex fracture and stimulation effect of multistaged horizontal well fracturing. By means of discretization of disordered complex fractures, the orthogonal three-dimensional physical model of complex fractures is obtained and the complex fracture experimental device for simulating fracture complexity is developed and a complete set of proppant transport characteristic experimental device in unconventional reservoir complex fractures is formed. Combined with field parameters and lab experiments, the influence of proppant performance parameters and discharge capacity to proppant transport characteristics in complex fractures of the unconventional reservoir is studied. And on the basis of experimental results and analysis, the sensitivity analysis method is applied to analyze the influence degree of proppant transport characteristics in complex fractures of the shale or tight sandstone reservoir. The sensitivity order of influence factors is fracture morphology, proppant performance, liquid viscosity, displacement, and proppant concentration. The experimental device and research results can provide strong experimental support for the optimisation of shale or tight sandstone fracturing materials and field parameters.

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Hou, Jie, Hao Wang, Guoqing Li, Baoli Sheng, and Qiuling Wang. "Multistage dynamic optimisation of ore flow for underground metal mines." International Journal of Mining, Reclamation and Environment, February 5, 2024, 1–17. http://dx.doi.org/10.1080/17480930.2024.2311455.

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