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Computational intelligent optimization approach based on Particle Swarm Optimization and Extended Finite Element Method for high-cycle fatigue life extension

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Abstract

The crack growth trajectory is a significant structural issue, directly affecting its quality and stability. Specifically, a crack propagating toward a critical condition will fail the structure. On the other hand, cutouts in a structure can deviate from the crack path; hence, the position of a cutout is one of the most influential parameters in crack path deviation. It is essential to obtain the most optimal position since a cutout may be located at different positions relative to the crack. In order to determine the optimal cutout position to extend the fatigue life, the present manuscript investigated a suitable position for the center of a constant-radius circular cutout by optimizing an objective function using the Particle Swarm Optimization (PSO) algorithm. The results indicated that the vertical position of the cutout to the crack is influential in crack path deviation. Subsequently, the results obtained from a coupling between the PSO and Extended Finite Element Method (XFEM) were validated via experiments. It was concluded that numerical results are in good agreement with experimental results.

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Data availability

The datasets generated during the current study are available from the corresponding author upon reasonable request.

References

  1. Dimatteo ND, Lampman SR (1996). Fatigue and fracture, (ed) vol. 19, ASM Handbook

  2. Ghazwan Q, Al M (2017) High cycle fatigue (HCF) testing of steel for fedral aviation administration (FAA) part qualification. California State University

    Google Scholar 

  3. Chapetti Mirco D (2002) Estimation of the plain high-cycle fatigue propagation resistance in steels. Mater Res 2:101–105

    Article  Google Scholar 

  4. Sander M, Richard HA (2006) Experimental and numerical investigations on the influence of the loading direction on the fatigue crack growth. Int J Fatigue 28:583–591

    Article  MATH  Google Scholar 

  5. Ding F, Zhao T, Jiang Y, Ding F, Zhao T (2007) A study of fatigue crack growth with changing loading direction. Eng Fract Mech 74:2014–2029

    Article  Google Scholar 

  6. Seifi R, Ghadimian O, Ranjbaran M (2015) Study on life and path of fatigue cracks in multiple site damage plates. Int J Fatigue 80:449–458

    Article  Google Scholar 

  7. Liao Y, Li Y, Huang M, Wang B, Yang B, Pei S (2019) Effect of hole relative size and position on crack deflection angle of repaired structure. Theoret Appl Fract Mech 101:92–102

    Article  Google Scholar 

  8. Reis L, Li B, Freitas M (2009) Crack initiation and growth path under multiaxial fatigue loading in structural steels. Int J Fatigue 31:1660–1668

    Article  Google Scholar 

  9. Makabe C, Murdani A, Kuniyoshi K, Irei Y, Saimoto A (2009) Crack-growth arrest by redirecting crack growth by drilling stop holes and inserting pins into them. Eng Fail Anal 16:475–483

    Article  Google Scholar 

  10. Ayatollahi MR, Zakeri M (2017) An improved definition for mode I and mode II crack problems. Eng Fract Mech 175:235–246

    Article  Google Scholar 

  11. Saber A, Shariati M (2016), Taguchi statistical analysis of experiments on the effect of cutout on crack growth and fatigue life of ck45 steel. In 5th International conference on electrical, computer, mechanical and mechatronics engineering, Istanbul

  12. Hu XF, Yao WA (2013) A new enriched finite element for fatigue crack growth. Int J Fatigue 48:247–256

    Article  Google Scholar 

  13. Bashir R, Xue H, Zhang J, Guo R, Hayat R, Li G, Bi Y (2020) Effect of XFEM mesh density (mesh size) on stress intensity factors, strain gradient and stress corrosion cracking (SCC) growth rate. Structures 25:593–602

    Article  Google Scholar 

  14. Chabouk E, Shariati M, Kadkhodayan M, Masoudi Nejad R (2021) Fatigue assessment of 2024–T351 aluminum alloy under uniaxial cyclic loading. J Mater Eng Perform 30(4):2864–2875

    Article  Google Scholar 

  15. Krishnapillai K, Jones R (2009) Three-dimensional structural design optimisation based on fatigue implementing a genetic algorithm and a non-similitude crack growth law. Finite Elem Anal Des 45:132–146

    Article  Google Scholar 

  16. ASTM (2001) Standard test methods for tension testing of metallic materials, Annual book of ASTM standards, (ed), Vol E8–E99, ASTM

  17. Blazic M, Maksimovic S, Petrovic Z, Vasovic A, Turnic D (2014) Determination of fatigue crack growth trajectory and residual life under mixed modes. J Mech Eng 60:250–254

    Article  Google Scholar 

  18. Perez N (2004), (ed) Fracture mechanics. Kluwer Academic Publishers, Boston

  19. Ratnaweera A, Halgamuge S, Harry WC (2004) Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients. IEEE Trans Evol Comput 3:240–255

    Article  Google Scholar 

  20. Engelbrecht Andries P (2007) Computational intelligence, Second, Edition. Wiley, University of Pretoria South Africa

    Book  Google Scholar 

  21. Hosseini S, Hamidi S, Mansuri M, Ghoddosian A (2015) Multi objective particle swarm optimization (MOPSO) for size and shape optimization of 2D truss structures. Period Polytech Civ Eng 59:9–14

    Article  Google Scholar 

  22. Jafari M, Salajegheh E, Salajegheh J (2021) Optimal design of truss structures using a hybrid method based on particle swarm optimizer and cultural algorithm. Structures 32:391–405

    Article  Google Scholar 

  23. Keshavarzian H, Daneshjou K (2020) PSO-based online estimation of aerodynamic ground effect in the backstepping controller of quadrotor. J Braz Soc Mech Sci Eng 42:1–10

    Article  Google Scholar 

  24. Cleghorn CW, Engelbrecht AP (2018) Particle swarm stability: a theoretical extension using the non-stagnate distribution assumption. Swarm Intell 12:1–22

    Article  Google Scholar 

  25. Bonyadi M, Michalewicz Z (2016) Stability analysis of the particle swarm optimization without stagnation assumption. IEEE Trans Evol Comput 20:814–819

    Article  Google Scholar 

  26. Qunfeng L (2015) Order-2 stability analysis of particle swarm optimization. Evol Comput 23:187–216

    Article  Google Scholar 

  27. Li XL, Serra R, Olivier J (2021) An investigation of particle swarm optimization topologies in structural damage detection. Appl Sci 11(11):5144

    Article  Google Scholar 

  28. Ozgur Y (2005) Penalty function methods for constrained optimization with genetic algorithms. Math Comput Appl 10:45–56

    Google Scholar 

  29. Singh I, Mishra B, Bhattacharya S, Patil R (2012) The numerical simulation of fatigue crack growth using extended finite element method. Int J Fatigue 36:109–119

    Article  Google Scholar 

  30. Ding J, Yu T, Yang Y, Bui TQ (2020) An efficient variable-node XFEM for modeling multiple crack growth: a Matlab object-oriented implementation. Adv Eng Softw 140:102750

    Article  Google Scholar 

  31. Latifi Rostami SA, Ghoddosian A, Kolahdooz A, Zhang J (2022) Topology optimization of continuum structures under geometric uncertainty using a new extended finite element method. Eng Optim 54(10):1692–1708

    Article  MathSciNet  Google Scholar 

  32. Martínez E, Farias M, Evangelista Junior F (2019) Investigation of the notch angle in hydraulic fracturing using XFEM. J Braz Soc Mech Sci Eng 41:1–13

    Article  Google Scholar 

  33. Ayatollahi MR, Razavi SMJ, Yahya MY (2015) Mixed mode fatigue crack initiation and growth in a CT specimen repaired by stop hole technique. Eng Fract Mech 145:115–127

    Article  Google Scholar 

  34. Becker WT, Lampman S (2002) Fracture appearance and mechanisms of deformation and fracture. Mater Park, OH: ASM Int 2002:559–586

    Google Scholar 

  35. Lesiuk G, Rymsza B, Rabiega J, Correia J, Jesus A, Calcada R (2019) Influence of loading direction on the static and fatigue fracture properties of the long term operated metallic materials. Eng Fail Anal 96:409–425

    Article  Google Scholar 

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Correspondence to Ali Ghoddosian.

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Saberian, M., Ghoddosian, A. & Ghasemi-Ghalebahman, A. Computational intelligent optimization approach based on Particle Swarm Optimization and Extended Finite Element Method for high-cycle fatigue life extension. J Braz. Soc. Mech. Sci. Eng. 45, 93 (2023). https://doi.org/10.1007/s40430-022-03935-8

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