An Overview of Numerical Optimization Applications for Friction Stir Welding

• Autorzy: Tutum C. , Hattel J. C.

Warianty tytułu

PL

Przegląd aplikacji optymalizacji procesu spawania tarciowego wykorzystujących modelowanie numeryczne

• Języki publikacji: EN

Abstrakty

EN

Recent advances in the computational power, and at the same time, the software that is capable of taking advantage of the new hardware architecture promote numerical modelling activities for the Friction Stir Welding (FSW) process as in parallel with other engineering applications. All these developments provide a stronger basis for understanding of the FSW process by enabling inclusion of more detailed multi-physics phenomena, i.e. complex interaction among material behaviour, microstructure evolution, material flow, heat generation, etc. A source of motivation behind all these efforts is the increasing demand for the FSW process mainly in aerospace and automotive industries. However the list of unknowns for the success of the process (e.g. defect free welds) is not yet cleared up. Tool design and process parameter optimization studies are in general limited by design of experiments and those rarely supported by the statistical analysis tools. One of the main reasons for the lack of the autonomous optimization studies, in which the numerical FSW simulations are used for response evaluations, is still the high computational cost. Here in this review paper, a brief overview of remarkable achievements together with the discussion of the limitations in the numerical FSW optimization studies are laid on the table.

PL

Rozwój komputerów i oprogramowania, które wykorzystuje nową architekturę sprzętową umożliwia obecnie modelownie numeryczne procesu spawania tarciowego (ang.: Friction Stir Welding - FSW). Modelowanie zjawisk zachodzących w trakcie spawania prowadzi do lepszego zrozumienia procesu FSW poprzez wprowadzenie do modelowania złożonych zależności pomiędzy zachowaniem się materiałów, zmian mikrostruktury, płynięcia materiału, generowania ciepła. Motywacją do tych badań jest coraz szerzej stosowany proces FSW głównie w przemyśle samochodowym i lotniczym. Modelowanie tego procesu jest skomplikowane, a liczba niewiadomych decydujących o własnościach spawu (np. spawy wolne od defektów) nie jest do końca znana. Możliwości optymalizacji projektowania narzędzi oraz parametrów procesu FSW są ograniczone, ponieważ nie stosuje się metod projektowania doświadczenia i analizy statystycznej ze względu na wciąż wysokie koszty obliczeniowe numerycznej symulacji tego procesu. W niniejszym artykule przedstawiono krótki przegląd najważniejszych osiągnięć wraz z dyskusją o ograniczeniach w optymalizacji procesu FSW wykorzystującej numeryczne modelowanie.

Słowa kluczowe

EN

friction stir welding; process optimization; tool design; evolutionary computation; metamodelling

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Methods in Materials Science
• Rocznik: 2013
• Tom: Vol. 13, No. 1
• Strony: 153--159
• Opis fizyczny: Bibliogr. 26 poz., rys.

Twórcy

autor

Tutum C.

• Technical University of Denmark (DTU), Department of Mechanical Engineering, Kgs. Lyngby, 2800 Denmark

autor

Hattel J. C.

• Technical University of Denmark (DTU), Department of Mechanical Engineering, Kgs. Lyngby, 2800 Denmark

Bibliografia

• Bandaru, S., Tutum, C.C., Deb, K., Hattel, J.H., 2011, Higherlevel innovization: A case study from Friction Stir Welding process optimization, Proc. of IEEE Congress on Evolutionary Computation (CEC), 2782-2789.
• Chao, Y.J., Qi, X., 1998, Thermal and thermo-mechanical modeling of friction stir welding of aluminum alloy 6061-T6. Journal of Materials Processing Manufacturing, 7, 215-233.
• Chen, C.M., Kovacevic, R., 2006, Parametric finite element analysis of stress evolution during friction stir welding. Journal of Engineering Manufacture, 220, 1359-1371.
• Colegrove, P.A., Shercliff, H.R., 2005, 3-Dimensional CFD modelling of flow round a threaded friction stir welding tool profile, Journal of Materials Processing Technology, 169, 320-327.
• Cox, C.D., Gibson, B.T., Strauss, A.M., Cook, G.E., 2012, Effect of Pin Length and Rotation Rate on the TensileStrength of a Friction Stir Spot-Welded Al Alloy: A Contribution to Automated Production, Materials and Manufacturing Processes, 27, 472-478.
• Deb, K., Srinivasan, A., 2006, Innovization: Innovating design principles through optimization, Proc. conf. 8th Genetic and Evolutionary Computation (GECCO), 1629–1636.
• Deb, K., Agarwal, S., Pratap, A., Meyarivan, T., 2002, A fast and elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II, IEEE Transactions on Evolutionary Computation, 6, 182–197.
• Feng, Z., Wang, X., David, S.A., Sklad, P., 2007, Modeling of residual stresses and property distributions in friction stir welds of aluminum alloy 6061-T6, Science and Technology of Welding and Joining, 12, 348-356.
• Kumar, K., Kailas, S.V., Srivatsan, T.S., 2011, The Role of Tool Design in Influencing the Mechanism for the Formation of Friction Stir Welds in Aluminum Alloy 7020. Materials and Manufacturing Processes, 26, 915-921.
• Ma, Z.Y., 2001, Friction stir processing technology: a review, Metallurgical and Materials Transactions A, 39, 642–658.
• Mishra, R.S., Ma, Z.Y., 2005, Friction stir welding and processing, Material Science and Engineering R, 50, 1–78.
• Nandan, R., Lienert, T. J., DebRoy, T., 2008, Toward reliable calculations of heat and plastic flow during friction stir welding of Ti-6Al-4V alloy, International Journal of Materials Research, 99, 434–444.
• Rajakumar, S., Balasubramanian, V., 2012, Predicting Grain Size and Tensile Strength of Friction Stir Welded Joints of AA7075-T6 Aluminum Alloy, Materials and Manufacturing Processes, 27, 78-83.
• Richards, D.G., Pragnell, P.B., Williams, S.W., Withers, P.J., 2008, Global mechanical tensioning for the management of residual stresses in welds, Mater. Sci. Eng. A, 489, 351-362.
• Robson, J.D., Kamp, N., Sullivan, A., 2007, Microstructural Modelling for Friction Stir Welding of Aluminium Alloys, Materials and Manufacturing Processes, 22, 450- 456.
• Schmidt, H.N.B., Hattel, J.H., 2008, Thermal modelling of friction stir welding, Scripta Materialia, 58, 332–337.
• Schmidt, H.N.B., Hattel, J.H., 2005, Modelling heat flow around tool probe in friction stir welding, Science and Technology of Welding and Joining, 10, 176-186.
• Thomas, W.M., 1999, Friction Stir Welding of Ferrous Materials: A Feasibility Study, Proc. of 1st International Symposium on Friction Stirs Welding, Rockwell Science Centre, Thousand Oaks, CA, USA.
• Tutum, C.C., Schmidt, H., Hattel, J.H., Bendsøe, M., 2007, Estimation of the Welding Speed and Heat Input in Friction Stir Welding using Thermal Models and Optimization, Proc. of 7th World Congress on Structural and Multidisciplinary Optimization, Seoul, 2639-2646.
• Tutum, C.C., Deb, K., Hattel, J.H., 2010, Hybrid search for faster production and safer process conditions in friction stir welding, Proc. of 8th International Conference on Simulated Evolution and Learning, 603-612.
• Tutum, C.C., Hattel, J.H., 2010a, Optimisation of process parameters in friction stir welding based on residual stress analysis: a feasibility study, Science and Technology of Welding and Joining, 15, 369-377.
• Tutum, C.C., Hattel, J.H., 2010b, A multi-objective optimization application in friction stir welding: Considering thermomechanical aspects, Proc. of IEEE Congress on Evolutionary Computation (CEC), 1-8.
• Tutum, C.C., Hattel, J.H., 2011, Numerical optimisation of friction stir welding: review of future challenges, Science and Technology of Welding and Joining, 16, 318-324.
• Tutum, C.C., Hattel, J.H., 2011, State-of-the-Art Multi-objective Optimisation of Manufacturing Processes Based on Thermo-Mechanical Simulations, Multi-objective Evolutionary Optimisation for Product Design and Manufacturing, Book Chapter-3, eds, Wang, L., Ng, A.H.C., Deb, K., Springer, 71-133.
• Tutum, C.C., Deb, K., Hattel, J.H., 2012, Multi-Criteria Optimization in Friction Stir Welding Using a Thermal Model with Prescribed Material Flow, Materials and Manufacturing Processes (Special Genetic Algorithm Issue), accepted.
• Zhu, X.K., Chao, Y.J., 2004, Numerical simulation of transient temperature and residual stresses in friction stir welding of 304L stainless steel, Journal of Materials Processing Manufacturing, 146, 263-272.