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Parallel computing in automation of decoupled fluid-thermostructural simulation approach

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Języki publikacji
EN
Abstrakty
EN
Decoupling approach presents a novel solution/alternative to the highly time-consuming fluid-thermal-structural simulation procedures when thermal effects and resultant displacements on machine tools are analyzed. Using high dimensional Characteristic Diagrams (CDs) along with a Clustering Algorithm that immensely reduces the data needed for training, a limited number of CFD simulations can suffice in effectively decoupling fluid and thermal-structural simulations. This approach becomes highly significant when complex geometries or dynamic components are considered. However, there is still scope for improvement in the reduction of time needed to train CDs. Parallel computation can be effectively utilized in decoupling approach in simultaneous execution of (i) CFD simulations and data export, and (ii) Clustering technique involving Genetic Algorithm and Radial Basis Function interpolation, which clusters and optimizes the training data for CDs. Parallelization reduces the entire computation duration from several days to a few hours and thereby, improving the efficiency and ease-of-use of decoupling simulation approach.
Rocznik
Strony
39--52
Opis fizyczny
Bibliogr. 17 poz., rys., tab.
Twórcy
  • Fraunhofer Institute for Machine Tools and Forming Technology IWU, Chemnitz, Germany
  • Dresden University of Technology, Institute of Scientific Computing, Dresden, Germany
  • Fraunhofer Institute for Machine Tools and Forming Technology IWU, Chemnitz, Germany
Bibliografia
  • [1] GLÄNZEL J., IHLENFELDT S., NAUMANN C., PUTZ M., 2018, Efficient Quantification of Free and Forced Convection Via the Decoupling Of Thermo-Mechanical and Thermo-Fluidic Simulations of Machine Tools, Journal of Machine Engineering, 18/2, 41–53.
  • [2] PRIBER U., 2003, Smoothed Grid Regression, Proceedings Workshop Fuzzy Systems, 13, Dortmund, Germany, 159–172.
  • [3] NAUMANN C., RIEDEL I., IHLENFELDT S., PRIBER U., 2016, Characteristic Diagram Based Correction Algorithms for the Thermo-Elastic Deformation of Machine Tools, Procedia CIRP, 41, 801–805.
  • [4] GLÄNZEL J., IHLENFELDT S., NAUMANN C.C., PUTZ M., 2017, Decoupling of Fluid and Thermo-Elastic Simulations on Machine Tools Using Characteristic Diagrams, Procedia CIRP, 62, 340–345.
  • [5] GLÄNZEL J., KUMAR T.S., NAUMANN C., PUTZ M., 2019, Parameterization of Environmental Influences by Automated Characteristic Diagrams for the Decoupled Fluid and Structural-Mechanical Simulations, Journal of Machine Engineering, 19/1, 98–113.
  • [6] SCHALLER R.R., 1997, Moore’s Law: Past, Present and Future, IEEE Spectrum, 34/6, 52–59.
  • [7] MARKIDIS S., LAURE E., 2015, Solving Software Challenges for Exascale, Springer.
  • [8] TANENBAUM A.S., AUSTIN T., 2014, Rechnerarchitektur: von der digitalen Logik zum Parallelrechner, Pearson Deutschland GmbH.
  • [9] KOZA J.R., 1995, Survey of Genetic Algorithms and Genetic Programming, Proceedings of the Wescon 95 – Conference Record.
  • [10] KOENIG A.C., 2002, A Study of Mutation Methods for Evolutionary Algorithms, CS 447 – Advanced Topics in Artificial Intelligence, University of Missouri-Rolla.
  • [11] GLÄNZEL J., UNGER R., IHLENFELDT I., 2018, Clustering by Optimal Subsets to Describe Environment Interdependencies, 1st Conference on Thermal Issues in Machine Tools, Dresden, Proceedings, 143–157.
  • [12] PUTZ M., IHLENFELDT S., KAUSCHINGER B., NAUMANN C., THIEM X., RIEDEL M., 2016, Implementation and Demonstration of Characteristic Diagram as Well as Structure Model Based Correction of Thermo-Elastic Tool Center Point Displacements, Journal of Machine Engineering, 16/3, 88–101.
  • [13] JOHNSON D.S., 1984, The NP-Completeness Column: An Ongoing Guide, Journal of Algorithms, 8/3, 438–448.
  • [14] BAKER B.S., 1985, A New Proof for the First-Fit Decreasing Bin-Packing Algorithm, Journal of Algorithms, 6/1, 49–70.
  • [15] ANSYS ACT, https://www.ansys.com/products/structures/ansys-act.
  • [16] ZIH HPC Compendium, https://tu-dresden.de/zih/hochleistungsrechnen
  • [17] Slurm Manual, https://slurm.schedmd.com/
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-afa3ad0e-4b3d-47c7-a6e5-ae8f165c4723
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