More Like this

1. SIMULATION OF DUCTILE FRACTURE PROPAGATION IN STRUCTURAL STEEL SUBJECTED TO ULTRA-LOW CYCLE FATIGUE

   Pericoli, V.S.; Lao, X; Terashima, M; Ziccarelli, A; Deierlein, G; Kanvinde, A.M. (January 2018, Eleventh U.S. National Conference on Earthquake Engineering)

   While considerable progress has been made in simulating the overall seismic response of steel structures using nonlinear response history (dynamic) analysis, techniques to simulate fracture propagation under large scale inelastic cyclic loading are not as well developed. This is despite the fact that fracture is often a critical limit state that can precipitate structural failure and collapse. To address this, a new ductile damage-based cohesive zone model is presented. The proposed model is an extension of the established continuum-based local or micromechanical ductile fracture models for evaluating ultra-low cycle fatigue in structural steels. This model is implemented in the finite element program WARP3D, and evaluated against tests of notched bars that fail by ductile crack propagation. The preliminary results indicate that the model is an effective tool for predicting ductile fracture initiation and propagation in structural steels subjected to monotonic and cyclic large scale inelastic loading. Implications of this for characterizing the post-fracture response of structural steel components are discussed, along with limitations of the research. 

   more » « less
2. SIMULATION OF DUCTILE FRACTURE PROPAGATION IN STRUCTURAL STEEL SUBJECTED TO ULTRA-LOW CYCLE FATIGUE

   Pericoli, V.S. and (July 2018, Proceedings of the U.S. National Conference on Earthquake Engineering)

   While considerable progress has been made in simulating the overall seismic response of steel structures using nonlinear response history (dynamic) analysis, techniques to simulate fracture propagation under large scale inelastic cyclic loading are not as well developed. This is despite the fact that fracture is often a critical limit state that can precipitate structural failure and collapse. To address this, a new ductile damage-based cohesive zone model is presented. The proposed model is an extension of the established continuum-based local or micromechanical ductile fracture models for evaluating ultra-low cycle fatigue in structural steels. This model is implemented in the finite element program WARP3D, and evaluated against tests of notched bars that fail by ductile crack propagation. The preliminary results indicate that the model is an effective tool for predicting ductile fracture initiation and propagation in structural steels subjected to monotonic and cyclic large scale inelastic loading. Implications of this for characterizing the post-fracture response of structural steel components are discussed, along with limitations of the research. 

   more » « less
3. COMPUTATIONAL SIMULATION OF DUCTILE FRACTURE IN BUCKLING RESTRAINED BRACES

   Terashima, M. Deierlein (July 2018, Proceedings of the U.S. National Conference on Earthquake Engineering)

   Since their first use in Japan about thirty years ago, Buckling Restrained Braces (BRBs) have been widely implemented in steel-framed buildings throughout the world. To date, most of the development and validation of BRB ductility has relied extensively on testing of full-scale braces under cyclic loading since no fracture evaluation method based on underlying micromechanics is currently available. Therefore, research is currently being undertaken to develop, validate and apply detailed finite element models to computationally simulate ductile fracture initiation and propagation in BRBs. As a part of this research, this paper presents an evaluation methodology of ductile fracture initiation using an Ultra-Low Cyclic Fatigue criterion, referred to as the Stress Weighted Damage Model (SWDM), along with detailed finite element analysis of BRBs. 

   more » « less
4. Microstructure-Based Modeling of the Effect of Inclusion on the Bendability of Advanced High Strength Dual-Phase Steels

   https://doi.org/10.3390/met11030431  

   Liu, Yu; Fan, Dongwei; Arróyave, Raymundo; Srivastava, Ankit (March 2021, Metals)

   null (Ed.)

   Advanced high strength dual-phase steels are one of the most widely sought-after structural materials for automotive applications. These high strength steels, however, are prone to fracture under bending-dominated manufacturing processes. Experimental observations suggest that the bendability of these steels is sensitive to the presence of subsurface non-metallic inclusions and the inclusions exhibit a rather discrete size effect on the bendability of these steels. Following this, we have carried out a series of microstructure-based finite element calculations of ductile fracture in an advanced high strength dual-phase steel under bending. In the calculations, both the dual-phase microstructure and inclusion are discretely modeled. To gain additional insight, we have also analyzed the effect of an inclusion on the bendability of a single-phase material. In line with the experimental observations, strong inclusion size effect on the bendability of the dual-phase steel naturally emerge in the calculations. Furthermore, supervised machine learning is used to quantify the effects of the multivariable input space associated with the dual-phase microstructure and inclusion on the bendability of the steel. The results of the supervised machine learning are then used to identify the contributions of individual features and isolate critical features that control the bendability of dual-phase steels. 

   more » « less
5. A data-driven geometry-specific surrogate model for forecasting the load–displacement behavior until ductile fracture

   https://doi.org/10.1007/s10704-025-00839-1  

   Dey, Surajit; Kiran, Ravi (May 2025, International Journal of Fracture)

   Krishnaswamy, RaviChandar (Ed.)

   The present study aims to configure and train a data-driven geometry-specific surrogate model (DD GSM) to simulate the load–displacement behavior until fracture in cylindrical notched specimens subjected to uniaxial monotonic tension tests. Plastic strain hardening that governs the load–displacement behavior and ductile fracture in metals are history-dependent phenomena. With this, the load–displacement response until ductile fracture in metals is hypothesized as time sequence data. To test our hypothesis, a long short-term memory (LSTM) based deep neural network was configured and trained. LSTM is a type of neural network that takes sequential data as input and forecasts the future based on the learned past sequential trend. In this study, the trained LSTM network is referred to as DD GSM as it is used to forecast the load–displacement behavior until ductile fracture for the cylindrical notched specimens. The DD GSM is trained using the load–displacement data until fracture, extracted from the finite element analyses of notched cylindrical test specimens made of ASTM A992 steel. The damage leading to fracture was captured using the Gurson–Tvergaard–Needleman (GTN) model. Finally, the trained DD GSM is validated by predicting the overall load–displacement behavior, fracture displacement, and peak load-carrying capacity of cylindrical notched ASTM A992 structural steel specimens available in the literature that are not used for training purposes. The DD GSM was able to forecast some portions of the load–displacement curve and predict the fracture displacement and peak load-carrying capacity of the notched specimens. Furthermore, the geometric sensitivity of the trained DD GSM was demonstrated by simulating the load–displacement response of an ASTM A992 steel bar with a central hole. 

   more » « less