Advanced Computational Methods for Simulating and Optimizing Stochastic Fracture: A Systematic Literature Review
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Abstract
Stochastic fracture processes, pervasive in diverse natural and engineered systems, pose intricate challenges for accurate simulation and optimization. This systematic literature review surveys the landscape of advanced computational methodologies to unravel and optimize stochastic fracture phenomena. Grounded in multidisciplinary perspectives spanning engineering, physics, and applied mathematics, the review navigates through the intricacies of simulation techniques and optimizations methods. From Finite Element Method (FEM) to Molecular Dynamics (MD) simulations, the review delineates the evolution and application of computational frameworks. It scrutinizes optimization strategies ranging from evolutionary algorithms to surrogate-assisted techniques, illuminating their efficacy in optimizing fracture properties amidst stochasticity. Drawing from applications in geological formations, engineered materials, and biomechanics, the review elucidates the diverse realms where advanced computational methods find resonance. Despite strides in computational prowess, challenges loom large, including computational complexity, validation dilemmas, and interdisciplinary communication barriers. Looking ahead, the review prognosticates on the integration of machine learning, novel algorithmic developments, and standardization endeavor’s to propel the frontier of stochastic fracture simulations towards unprecedented realms of understanding and optimization. Through synthesis and critique, this review engenders a roadmap for future research and underscores the transformative potential of advanced computational methods in deciphering stochastic fracture phenomena.
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Bleyer, J., Alessi, R., & Besson, J. (2017). Phase field modeling of ductile fracture in heterogeneous systems. Procedia Structural Integrity, 3, 159-166.
Abdelaziz, R., & Hamouda, A. M. (2010). Finite element modeling of crack propagation in composites using cohesive zone model. Engineering Fracture Mechanics, 77(3), 397-406.
Belytschko, T., Chen, H., Xu, J., & Zi, G. (2011). Dynamic crack propagation based on loss of hyperbolicity and a new discontinuous enrichment. International Journal for Numerical Methods in Engineering, 76(4), 518-548.
Karihaloo, B. L., & Xiao, Q. Z. (2012). Modelling of stationary and growing cracks in FE framework without remeshing: a state-of-the-art review. Computers & Structures, 90-91, 3-12.
Miehe, C., Welschinger, F., & Hofacker, M. (2010). Thermodynamically consistent phase-field models of fracture: Variational principles and multi-field FE implementations. International Journal for Numerical Methods in Engineering, 83(10), 1273-1311. https://doi.org/10.1002/nme.2861
Nguyen, T. T., Li, X., & Bordas, S. P. (2014). Isogeometric crack propagation: Variationally consistent and geometrically flexible simulations. Computer Methods in Applied Mechanics and Engineering, 284, 265-302.
Wang, M. Y., & Wang, X. (2014). A level set method for structural topology optimization. Computer Methods in Applied Mechanics and Engineering, 276, 379-394.
Moës, N., & Belytschko, T. (2011). Extended finite element method for cohesive crack growth. Engineering Fracture Mechanics, 78(3), 309-325.
Rabczuk, T., & Belytschko, T. (2011). Adaptivity for structured meshfree particle methods in 2D and 3D. International Journal for Numerical Methods in Engineering, 92(3), 360-395.
Song, J. H., & Belytschko, T. (2012). Cracking node method for dynamic fracture with finite elements. International Journal for Numerical Methods in Engineering, 89(8), 991-1008.
Sukumar, N., & Prévost, J. H. (2013). Extended finite element method for three-dimensional crack modeling. International Journal for Numerical Methods in Engineering, 92(8), 740-758.
Gerasimov, T., & De Lorenzis, L. (2016). A line search assisted monolithic approach for phase-field computing of brittle fracture. Computer Methods in Applied Mechanics and Engineering, 312, 276-303. https://doi.org/10.1016/j.cma.2015.12.017
Miehe, C., Hofacker, M., & Welschinger, F. (2010). A phase field model for rate-independent crack propagation: Robust algorithmic implementation based on operator splits. Computer Methods in Applied Mechanics and Engineering, 199(45-48), 2765-2778. https://doi.org/10.1016/j.cma.2010.04.011
Borden, M. J., Hughes, T. J., Landis, C. M., Anvari, A., & Lee, I. J. (2016). A phase-field formulation for fracture in ductile materials: Finite deformation balance law derivation, plastic degradation, and stress triaxiality effects. Computer Methods in Applied Mechanics and Engineering, 312, 130-166. https://doi.org/10.1016/j.cma.2016.09.005.
Bourdin, B., Marigo, J. J., & Francfort, G. A. (2008). The variational approach to fracture. Journal of Elasticity, 91(1-3), 5-148. https://doi.org/10.1007/s10659-007-9107-3.
Ambati, M., Gerasimov, T., & De Lorenzis, L. (2015). A review on phase-field models of brittle fracture and a new fast hybrid formulation. Computational Mechanics, 55, 383-405. https://doi.org/10.1007/s00466-014-1109-y
Areias, P. M. A., & Rabczuk, T. (2017). A staggered algorithm for orthotropic phase-field models of fracture. Finite Elements in Analysis and Design, 130, 1-12.
Miehe, C., & Mauthe, S. (2016). Phase field modeling of fracture in multi-physics problems. Part III. Crack driving forces in hydro-mechanics, thermo-mechanics, and electromechanics. Computer Methods in Applied Mechanics and Engineering, 304, 619-655. https://doi.org/10.1016/j.cma.2015.09.021.
Wu, J. Y., & Nguyen, V. P. (2018). A length scale insensitive phase-field damage model for brittle fracture. Journal of the Mechanics and Physics of Solids, 119, 20-42. https://doi.org/10.1016/j.jmps.2018.06.006
Tanne, E., Li, T., Bourdin, B., Marigo, J. J., & Maurini, C. (2018). Crack nucleation in variational phase-field models of brittle fracture. Journal of the Mechanics and Physics of Solids, 110, 80-99. https://doi.org/10.1016/j.jmps.2017.09.006.
Borden, M. J., Verhoosel, C. V., Scott, M. A., Hughes, T. J., & Landis, C. M. (2012). A phase-field description of dynamic brittle fracture. Computer Methods in Applied Mechanics and Engineering, 217-220, 77-95. Top of Form https://doi.org/10.1016/j.cma.2012.01.008.
Wanjau, S. K., Wambugu, G. M., & Oirere, A. M. (2022). Network Intrusion Detection Systems: A Systematic Literature Review o f Hybrid Deep Learning Approaches. In International Journal of Emerging Science and Engineering (Vol. 10, Issue 7, pp. 1–16). Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP. https://doi.org/10.35940/ijese.f2530.0610722
Radhamani, V., & Dalin, G. (2019). Significance of Artificial Intelligence and Machine Learning Techniques in Smart Cloud Computing: A Review. In International Journal of Soft Computing and Engineering (Vol. 9, Issue 3, pp. 1–7). https://doi.org/10.35940/ijsce.c3265.099319
Banga, M., Bansal, A., & Singh, A. (2019). Estimating Performance of Intelligent Software Systems. In International Journal of Recent Technology and Engineering (IJRTE) (Vol. 8, Issue 3, pp. 1150–1156). https://doi.org/10.35940/ijrte.c4264.098319
Petrushevski, A., & Us, V. (2020). Computer Algorithm for Creation Classic Mosaic Fillings Based on the Vector Guide Lines. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 3, pp. 834–839). Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP. https://doi.org/10.35940/ijeat.c5279.029320
Lochana, A. S. R., & Arthi, K. (2019). Evaluation of Over Looped 2d Mesh Topology for Network on Chip. In International Journal of Innovative Technology and Exploring Engineering (Vol. 8, Issue 9, pp. 502–504). https://doi.org/10.35940/ijitee.i7703.078919