PARALLEL SOLUTION OF THERMOMECHANICAL INVERSE PROBLEMS FOR LASER DIELESS DRAWING OF ULTRA-THIN WIRE
Andrij MILENIN
milenin@agh.edu.plAGH University of Science and Technology, Faculty of Metals Engineering and Industrial Computer Science, Department of Applied Computer Science and Modelling, Krakow, (Poland)
Abstract
The paper discusses the solving of inverse thermomechanical problems requiring a large number of FEM tasks with various boundary conditions. The study examined the case when all tasks have the same number of nodes, finite elements, and nodal connections. In this study, the speedup of the solution of the inverse problem is achieved in two ways: 1. The solution of all FEM tasks in parallel mode. 2. The use by all FEM tasks a common matrix with addresses of nonzero elements in the stiffness matrices. These algorithms are implemented in the own FEM code, designed to solve inverse problems of the hot metal forming. The calculations showed that developed code in parallel mode is effective for the number of tasks late than 0,7-0,9 of the number of available processors. Thus, at some point, it becomes effective to use a sequential solution to all tasks and to use a common matrix of addresses of nonzero elements in the stiffness matrix. The achieved acceleration at the optimal choice of the algorithm is 2–10 times compared with the classical multivariate calculations in the FEM. The paper provides an example of the practical application of the developed code for calculating the allowable processing maps for laser dieless drawing of ultra-thin wire from copper alloy by solving the thermomechanical inverse problem. The achieved acceleration made it possible to use the developed parallel code in the control software of the laboratory setup for laser dieless drawing.
Keywords:
FEM, parallel computing, dieless drawing, thin wireReferences
Chandra, R., Dagum, L., Kohr, D., Menon, R., Maydan, D., & McDonald, J. (2001). Parallel Programming in OpenMP. Elsevier Science.
Google Scholar
Chenot, J., Massoni, E., & Fourment, J. L. (1996). Inverse problems in finite element simulation of metal forming processes. Engineering Computations, 13(2/3/4), 190–225. https://doi.org/10.1108/02644409610114530
DOI: https://doi.org/10.1108/02644409610114530
Google Scholar
Furushima, T., & Manabe, K. (2007). Experimental and numerical study on deformation behavior in dieless drawing process of superplastic microtubes. Journal of Materials Processing Technology, 191(1), 59–63. https://doi.org/https://doi.org/10.1016/j.jmatprotec.2007.03.084
DOI: https://doi.org/10.1016/j.jmatprotec.2007.03.084
Google Scholar
Hensel, A. & Spittel, T. (1978). Kraft- und Arbeitsbedarf bildsamer Formgebungsverfahren. VEB Deutscher Verlag fur Grundstoffindustrie.
Google Scholar
Jaluria, Y. (2021). Strategies for solving inverse problems in thermal processes and systems. International Journal of Numerical Methods for Heat & Fluid Flow, 31(10), 3073–3088. https://doi.org/10.1108/HFF12-2019-0926
DOI: https://doi.org/10.1108/HFF-12-2019-0926
Google Scholar
Kraft, F. B. (1980). Three fine wire drawing systems – in economic comparison. Wire Journal International, 19, 103–105.
Google Scholar
Kubo, S. (1988). Inverse Problems Related to the Mechanics and Fracture of Solids and Structures. JSME International Journal. Ser. 1, Solid Mechanics, Strength of Materials, 31(2), 157–166. https://doi.org/10.1299/jsmea1988.31.2_157
DOI: https://doi.org/10.1299/jsmea1988.31.2_157
Google Scholar
Lesnic, D. (2021). Inverse Problems with Applications in Science and Engineering. Chapman and Hall/CRC.
DOI: https://doi.org/10.1201/9780429400629
Google Scholar
Li, Y., Quick, N. R., & Kar, A. (2002). Dieless laser drawing of fine metal wires. Journal of Materials Processing Tech., 123(3), 451–458.
DOI: https://doi.org/10.1016/S0924-0136(02)00110-3
Google Scholar
Milenin, A. (2017). Parallel FEM code for simulation of laser dieless drawing process of tubes. Computer Methods in Materials Science, 17(4), 178–185.
Google Scholar
Milenin, A., Kustra, P., Furushima, T., Du, P., & Němeček, J. (2018). Design of the laser dieless drawing process of tubes from magnesium alloy using FEM model. Journal of Materials Processing Technology, 262, 65–74. https://doi.org/https://doi.org/10.1016/j.jmatprotec.2018.06.018
DOI: https://doi.org/10.1016/j.jmatprotec.2018.06.018
Google Scholar
Milenin, A., Wróbel, M., & Kustra, P. (2021). Investigation of the workability and surface roughness of thin brass wires in various dieless drawing technologies. Archives of Civil and Mechanical Engineering, 22(1), 10. https://doi.org/10.1007/s43452-021-00331-2
DOI: https://doi.org/10.1007/s43452-021-00331-2
Google Scholar
Pokorska, I. (2007). Direct and inverse problems in metal forming of rigid-poroplastic materials. Journal of Materials Processing Technology, 184(1), 146–156. https://doi.org/https://doi.org/10.1016/j.jmatprotec.2006.11.015
DOI: https://doi.org/10.1016/j.jmatprotec.2006.11.015
Google Scholar
Schenk, O., & Gärtner, K. (2004). Solving unsymmetric sparse systems of linear equations with PARDISO. Future Generation Computer Systems, 20(3), 475–487. https://doi.org/https://doi.org/10.1016/j.future.2003.07.011
DOI: https://doi.org/10.1016/j.future.2003.07.011
Google Scholar
Szeliga, D., Gawąd, J., & Pietrzyk, M. (2004). Parameters Identification of Material Models Based on the Inverse Analysis. International Journal of Applied Mathematics and Computer Science, 14, 549–556.
Google Scholar
Szeliga, D., & Pietrzyk, M. (2007). Testing of the inverse software for identification of rheological models of materials subjected to plastic deformation. Archives of Civil and Mechanical Engineering, 7(1), 35–52. https://doi.org/https://doi.org/10.1016/S1644-9665(12)60003-X
DOI: https://doi.org/10.1016/S1644-9665(12)60003-X
Google Scholar
Thomas, A. E., Abbes, B., Li, Y. M., Abbes, F., Guo, Y.-Q., & Duval, J.-L. (2017). A coupled thermo-mechanical pseudo inverse approach for preform design in forging. AIP Conference Proceedings, 1896, 170004. https://doi.org/10.1063/1.5008202
DOI: https://doi.org/10.1063/1.5008202
Google Scholar
Tiernan, P., & Hillery, M. T. (2004). Dieless wire drawing—an experimental and numerical analysis. Journal of Materials Processing Tech., 155–156(Complete), 1178–1183. https://doi.org/10.1016/j.jmatprotec.2004.04.175
DOI: https://doi.org/10.1016/j.jmatprotec.2004.04.175
Google Scholar
Tiernan, P., & Hillery, M. T. (2008). Technical paper. Journal of Manufacturing Processes, 10(1), 12–20. https://doi.org/10.1016/j.manpro.2008.05.001
DOI: https://doi.org/10.1016/j.manpro.2008.05.001
Google Scholar
Authors
Andrij MILENINmilenin@agh.edu.pl
AGH University of Science and Technology, Faculty of Metals Engineering and Industrial Computer Science, Department of Applied Computer Science and Modelling, Krakow, Poland
Statistics
Abstract views: 104PDF downloads: 96
License
All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.
Similar Articles
- Wulan Dewi, Wiranto Herry Utomo, PLANT CLASSIFICATION BASED ON LEAF EDGES AND LEAF MORPHOLOGICAL VEINS USING WAVELET CONVOLUTIONAL NEURAL NETWORK , Applied Computer Science: Vol. 17 No. 1 (2021)
- Rafał KLIZA, Karol ŚCISŁOWSKI, Ksenia SIADKOWSKA, Jacek PADYJASEK, Mirosław WENDEKER, STRENGTH ANALYSIS OF A PROTOTYPE COMPOSITE HELICOPTER ROTOR BLADE SPAR , Applied Computer Science: Vol. 18 No. 1 (2022)
- K. Raju, Niranjan N Chiplunkar, PERFORMANCE ENHANCEMENT OF CUDA APPLICATIONS BY OVERLAPPING DATA TRANSFER AND KERNEL EXECUTION , Applied Computer Science: Vol. 17 No. 3 (2021)
- Kevin Joy DSOUZA, Zahid Ahmed ANSARI, HISTOPATHOLOGY IMAGE CLASSIFICATION USING HYBRID PARALLEL STRUCTURED DEEP-CNN MODELS , Applied Computer Science: Vol. 18 No. 1 (2022)
- Ihor PYSMENNYI, Anatolii PETRENKO, Roman KYSLYI, GRAPH-BASED FOG COMPUTING NETWORK MODEL , Applied Computer Science: Vol. 16 No. 4 (2020)
- Xianlei GE, Vladimir MARIANO, RETRACTED PAPER: Enhancing 3D human pose estimation through multi-feature fusion , Applied Computer Science: Vol. 19 No. 3 (2023)
- Lucian LUPŞA-TĂTARU, IMPLEMENTING THE FADE-IN AUDIO EFFECT FOR REAL-TIME COMPUTING , Applied Computer Science: Vol. 15 No. 2 (2019)
- Irena NOWOTYŃSKA, Stanisław KUT, COMPARATIVE ANALYSIS OF THE IMPACT OF DIE DESIGN ON ITS LOAD AND DISTRIBUTION OF STRESS DURING EXTRUSION , Applied Computer Science: Vol. 14 No. 4 (2018)
- Lucian LUPŞA-TĂTARU, CUSTOMIZING AUDIO FADES WITH A VIEW TO REAL-TIME PROCESSING , Applied Computer Science: Vol. 15 No. 4 (2019)
- Anitha Rani PALAKAYALA, Kuppusamy P, A QUALITATIVE AND QUANTITATIVE APPROACH USING MACHINE LEARNING AND NON-MOTOR SYMPTOMS FOR PARKINSON’S DISEASE CLASSIFICATION. A HIERARCHICAL STUDY , Applied Computer Science: Vol. 20 No. 3 (2024)
You may also start an advanced similarity search for this article.