PSI - Issue 38

Adrian Loghin et al. / Procedia Structural Integrity 38 (2022) 331–341 A. Loghin et al. / Structural Integrity Procedia 00 (2021) 000–000

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Fig. 1: Overall nominal model dimensions following Leser et al. (2017).

In order to make use of more accurate deterministic solutions, runtime e ffi cient routines are needed in probabilistic fatigue crack growth studies and Airframe Digital Twin development (Kobryn (2019), Millwater et al. (2019)). A component level surrogate model development is a more accurate representation of the fatigue crack growth conditions (local geometry and stress gradient that acts on the crack plane) than a reduced order model. A machine learning based surrogate model calibrated on accurate 3D FEA simulations can satisfy both conflicting requirements, high accuracy and low runtime cost, at a higher standard than current methodologies. Also, since well established FEA solvers are employed, surrogate modeling as presented in this study can benefit from decades of finite element modeling development. A practical implementation is also desired from a cost perspective. The integrated CAD to FEA modeling process along with remeshing capabilities for simulating fatigue crack growth at component level (Loghin (2018)), allows en gineers to easily employ models developed in the design and analysis process. Machine learning modeling capabilities available to the public in SciPy (Virtanen et al. (2020)) were utilized in this study without any additional functional development. SimModeler Crack as well as batch mode capabilities for modeling crack growth were employed to perform all the 3D FEM based simulations presented in this study. Component level CAD geometries as well as meshes with no underlying geometry can be used to initiate the modeling process. A geometry-mesh compatibility allows continuous and automatic assignment of pre-processing items to the geometric entities and transferred to mesh entities for each 3D model generated in the explicit crack propagation simulation process. More details of the development are provided in Loghin (2018) along with several verification and validation examples (Loghin and Ismonov (2020b)). The experimental procedure presented by Leser et al. (2017) is modeled using a nominal geometry of test specimen and finite element representations that capture loading conditions and crack surface advancement. Three-dimensional nominal geometry used in the numerical assessment is presented in Figure 1. Location of the initial crack relative to the hole feature in the panel specimen is identified through the ” Y 1 ” parameter. A cyclic uniform remote tensile loading with a of maximum value of 41 MPa and a stress ratio R = 0 ( ∆ K I = K Imax , K Imin = 0) was used. Fatigue crack growth simulation is performed via SimModeler Crack using classical Paris-Erdogan relationship and fatigue crack growth rate data for 2024-T62 reported in Farahmand et al. (1997): C = 2.97e-12, n = 3.2, corresponding to ∆ K I [MPa*mm 0 . 5 ] 2. Modeling Procedure 2.1. 3D FEA Procedure - Nominal Configuration