ICME 2023: Linkages: Deformation III
Program Organizers: Charles Ward, AFRL/RXM; Heather Murdoch, U.S. Army Research Laboratory
Thursday 11:10 AM
May 25, 2023
Room: Caribbean VI & VII
Location: Caribe Royale
11:10 AM
Parametrically-upscaled Crack Nucleation Model(PUCNM) for Fatigue Nucleation in Ti Alloys Containing Micro-texture Regions: Somnath Ghosh1; 1Johns Hopkins University
Micro-texture regions (MTRs), characterized as the clusters of grains with similar crystallographic orientations in the polycrystalline microstructure, play a significant role in fatigue crack nucleation and life of structures of Ti alloys. This paper develops a parametrically upscaled constitutive and crack nucleation modeling (PUCM/PUCNM) platform for predicting structural-scale fatigue crack nucleation in α/β Ti-6Al-4V alloys, whose polycrystalline microstructures contain MTRs. The PUCM/PUCNM platform bridges micro and macro scales through thermodynamically-consistent incorporation of representative aggregated microstructural parameters (RAMPs) in macroscopic constitutive relations. A RAMP that captures both the MTR size and contrast in the overall texture is proposed to represent MTR intensity in the microstructure. A functional form is derived using the genetic programming-based symbolic regression. The PUCM/PUCNM tool is used to simulate an engine blade under dwell loading conditions. The results exhibit the reduction of nucleation life with a higher level of MTR intensity, despite the same overall textures.
11:30 AM
Designing Fatigue Resistance of Metallic Alloys with a Hybrid of Deep Learning and Micromechanics: Anssi Laukkanen1; matti lindroos1; tom andersson1; napat vajragupta1; tatu pinomaa1; sicong ren1; abhishek biswas1; tomi suhonen1; 1VTT Technical Research Center of Finland
Fatigue remains a critical failure mechanism both of industrial and scientific interest. Fatigue testing is commonly a costly and time consuming exercise, which makes it difficult to establish microstructure to fatigue performance relationships. This is seen as an area where ICME driven "virtual fatigue testing" hybrid workflows consisting of physics- and data-driven modeling elements can support. We present a full field micromechanical approach to capture the effects of defects to fatigue performance of metallic alloys and steels. We utilize a high-throughput framework to derive a recurrent deep learning based surrogate to evaluate and act as a design tool for microstructural features improving resistance to fatigue. We demonstrate the approach on high strength steels and high entropy alloys using Bayesian workflows.
11:50 AM
A Phenomenological Model for the Relationship Between Fatigue Life and Mechanical Properties: Emiel Amsterdam1; Borit Zwerink1; 1NLR
We present a phenomenological model that accurately describes the influence of the initial discontinuity distribution, the applied stress range and the main mechanical properties, such as the ultimate tensile strength and the Young’s modulus, on the fatigue life of an alloy. The phenomenological model for fatigue life is constructed from a physics based fracture mechanics model that includes the effect that small cracks have on the fatigue crack growth rate. It is shown that the model is able to relate the fatigue life to i) the “effect of defect” for porosity in additively manufactured AlSi10Mg and Ti-6Al-4V, ii) the anisotropy in additively manufactured Inconel 718 and iii) the UTS of conventionally processed AA7075 with different heat treatments. The results allow for accurate screening of alloy composition and processing for the prediction of fatigue resistant alloys that can be used for optimized design of high performance engineering structures.
12:10 PM Cancelled
Evaluation of Stochastic Safe Life of a DP Steel Component Subjected to Fatigue Using a Micromechanics Based Approach: Srimannarayana P1; Harisankar K.R.1; Akash Gupta1; K.V. Vamsi1; Gerald Tennyson1; B.P. Gautham1; 1Tata Consultancy Services Limited
Fatigue life being an extreme value property is dictated by the local microstructure. A finite element based micromechanics approach is employed to capture the influence of microstructural features in predicting the cyclic stress-strain response of ferrite-pearlite/martensite steels. The material response is modelled through Chaboche non-linear kinematic hardening and continuum damage mechanics models. A 10% drop in peak stress is used as a criterion for estimating the number of cycles for crack initiation (safe life). The developed micromechanics model is used to evaluate the effect of microstructural parameters like grain size, phase fraction, interlamellar spacing on fatigue response. The safe life prediction model is utilized in a stochastic framework to account for variability in microstructure and phase properties. The details of the micromechanics model, safe life design methodology, stochastic framework and the effect of microstructure on fatigue response will be presented.