Ductile fracture is the fracture initiating mechanism in steel structures subjected to both overloading and ultra-low cycle fatigue (ULCF) loading. This paper aims to characterize the statistical distribution of microvoids on the fracture surface of structural steel specimens subjected to monotonic and ULCF loading by employing advanced microscopy techniques. Furthermore, the relationship between the experimentally inferred mean microvoid size and the state of stress and strain is investigated.
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Low-yield-point steel LYP225, distinguished from the ordinary carbon structural steels by lower yield strength, preferable strain-hardening and better ductility, is widely applied in metallic dampers. Ductile fracture of these dampers after severe earthquakes were commonly observed. This paper experimentally investigates the ductile fracture of LYP225 steel under different stress states, and predicts the fracture initiation with the Hosford-Coulomb fracture model.
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While sophisticated simulation techniques are regularly applied in natural hazards engineering, they are limited in ability to capture several important failure mechanisms. A significant limitation is the capability to reliably simulate fracture in structural steel weldments. Predicting fracture in weldments is inherently challenging due to various factors. Moreover, when weldments do not have a sharp, pre-existing flaw, or are subjected to large-scale yielding or earthquake-induced Ultra Low Cycle Fatigue (ULCF – characterized by few cycles of large strain) – all of which occur frequently in modern buildings, conventional fracture and fatigue mechanics are invalidated. Given that fracture often initiates in the weld region, this represents a major obstacle to effective structural performance assessment. This is addressed this through a coordinated program of (1) physical tests and fractography on thermomechanically generated samples of various weld microstructures for discovery of fracture micromechanisms, (2) formulation of new continuum-based fracture criteria for these different microstructures, (3) numerical implementation, and (4) calibration and validation of the developed framework using laboratory testing. A key research challenge is to effectively upscale local models, considering spatial variation of microstructure and interaction between mechanisms to predict fracture at the component/structure scale, while also characterizing the uncertainty in these predictions.
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In transportation system, bridges are continuously subjected to vehiclular loads that causes accumulation of stresses in different components. The weakest region are some times prone to the development of fatigue crack, that grows leading to collapse if proper maintenance and reparing are not carried out. In this paper, a method of estimation of fatigue life of a truss girder bridge has been outlined using linear fracture mechanics approach after synthesizing the vehicle induced stress history. Von-Mises stresses which accounts for all the principal stresses at a gusset plate of a critical joint was utilized to obtain stress-cycle histogram. Number of cycles required to grow an initially detected crack of very small dimension to a threshold value has been obtained to predict the fatigue failure. The effect of the length of the bridge, vehicle speed and compound traffic growth on remaining life of the bridge has been studied
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Cracks emerging from geometrically discontinuous locations under cyclic environmental loadings are critical concerns for the safety of the existing structural components. The crack-based fatigue assessment is essential for the evolving digital twin of sustainable infrastructures, including bridges, ships, and offshore platforms, to optimize the lifetime cost of these structures. This study presents an enhanced neural network-bootstrap particle filtering algorithm to construct the complex relationship between the normalized strain relaxation indicators and the crack profiles based on the numerical simulation and experimental validation. The high-cycle fatigue bending test of the welded plate connections confirms the robustness of the proposed approach in estimating the fatigue crack initiation and propagation through both strain measurement and nondestructive testing data. To overcome the uncertainties caused by the limited strain measurement, crack measurement, and different non-destructive techniques, this study combines a bootstrap particle filtering approach with an interpolation method to update the crack prediction algorithm. As validated by the experimental results, the intelligent crack sizing approach demonstrates a potential solution for crack size forecasting through affordable strain gauges in the broad framework of digitally twinning the next-generation infrastructure.
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