A hierarchically coupled cellular automata (CA) model, crystal plasticity finite element method (CPFEM), and thermal finite element (FE) model is developed to predict the softening kinetics of the ...bulged steel tube during non-isothermal annealing. Through the developed model, the kinetics of softening mechanisms including static recovery (SRV) and static recrystallization (SRX), as well as the recrystallization texture are predicted. Later, the Johnson-Mehl-Avrami-Kohnogorov (JMAK) model based on the predicted SRX data is developed to interpret the recrystallization behavior of the material. To perform this study, diverse experimental tests including tube hydroforming (THF), annealing, uniaxial tensile test, hardness test, as well as microstructure observations through optical microscopy and Electron Backscatter Diffraction (EBSD) tests on steel tube are performed. The obtained experimental data are utilized to calibrate and verify the implemented CPFEM model for simulation of THF process, thermal FE model for prediction of the local temperature over annealing time, and CA algorithm for modeling of the softening kinetics and texture evolution throughout the annealing process. The study shows that the predicted deformation characteristics, softening kinetics, recrystallization texture and temperature profile during non-isothermal annealing are in good agreement with experimental data. During the annealing process, a total of four stages for the kinetics of softening mechanisms is observed: No softening; SRV only; SRV dominant; and SRX dominant. During the progress of SRX, the behavior of recrystallization is abruptly changed, confirming that two different mechanisms are controlling the kinetics of transformation.
The aim of the present study is to propose an innovative type of gusset plate damper, which can be employed to protect structures against severe earthquakes and improve the seismic behavior of ...concentrically cross-braced frames. The proposed device comprises of a gusset plate which is grooved such that it yields in time at several places and prevents any plastic action or buckling in the braces. It is called a grooved gusset plate damper (GGPD). The GGPD can be used as an energy dissipater when installed in cross-braced frames as it dissipates input energy through inelastic deformations at its steel strips. To predict the yield and ultimate capacity and elastic stiffness of the GGPD, theoretical derivations are conducted resulting in analytical equations of the system. Afterwards, finite element models of the system are analyzed using ABAQUS and its hysteretic behavior is investigated under cyclic loading. Effects of the length, width and thickness of the strips and arrangement of stiffeners, on the cyclic performance and energy dissipation of the GGPD are studied. It is concluded that the analytical formulas are in very good agreement with the numerical results. Moreover, the hysteretic curves of the system are full and stable and have a similar behavior in tension and compression without pinching. In addition, the proposed system is able to significantly dissipate the seismic energy and tolerate more than 4% story drift.
•A slit gusset plate is proposed as a seismic energy dissipation device in a X-braced frame.•The analytical equations of the elastic stiffness and ultimate strength are derived.•A comprehensive parametrical study is carried out on the yielding steel damper.•Results of the developed analytical equations are in excellent agreement with those of the nonlinear finite element analysis.•Hysteresis curves of the damper are well-shaped with no pinching and stiffness/strength degradation up to large drifts.
Mechanical behavior of highly porous alumina catalytic supports is investigated through a non-conventional approach consisting in a multi-point crushing of individual cylindrical extrudates. A ...ductile behavior characterized by irreversible deformation and fragmentation phenomena is observed and pointed out by experimental load-displacement curves. SEM fractographies of the fragments collected after the tests confirm the presence of dense micro-cracking and of local deformations under contact zones. A Finite Element analysis of the test shows that a Drucker-Prager strength criterion associated with a perfectly plastic flow rule mimics the global damageable behavior of the specimen under the multi-point crushing test. A correlation is proposed between the evolution of the mass of fine fragments and the plastic energy dissipation.
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•The multi-point crushing test reveals the damageable behavior of highly porous alumina used as catalyst supports.•Plastic deformation, micro-cracking and fragmentation are observed under multi-point crushing tests.•The ductile damage of mesoporous γ-alumina can be represented by a Drucker-Prager plastic criterion.
Geotechnical observational method (OM) that aims to improve predictions of geotechnical structure responses (e.g., embankment settlement) based on the monitoring data can be rigorously formulated ...under a Bayesian updating framework. However, Bayesian analysis often faces a computational challenge when sophisticated numerical models (e.g., finite element model, FEM) are involved due to a significant number of model evaluations. Although response surface models (RSMs) provide cost-efficient alternatives to alleviate the computational burden, they are criticized for the problem-dependent accuracy. First, RSM is frequently established using the prior distribution, and its applicability in posterior space might degenerate, leading to inconsistent posterior predictions. Second, RSM-based Bayesian analysis can only provide updated responses for which RSMs are constructed. The updated information of other responses, for which the corresponding RSMs are not constructed, is missed. This paper presents an auxiliary Bayesian approach that combines a simple RSM (e.g., lower order polynomials) and FEM to update the embankment settlement based on monitoring data. The proposed approach improves the consistency of RSM-based Bayesian updating at the expense of FEM evaluations with acceptable computational costs. It avoids the blind confidence in applicability of RSMs constructed using prior samples to different posterior space, and provides information on updated predictions of responses without RSMs constructed using prior samples. An embankment example is investigated to illustrate the proposed approach and to explore its performance of the proposed approach.
•An auxiliary Bayesian approach for updating embankment settlement is proposed.•Response surface model (RSM) and FEM are systematically and effectively combined.•Consistency of RSM-based Bayesian updating method is improved.•Updated geotechnical responses without RSMs are obtained from posterior analysis.
•Multiresponse parameter estimation was used for simultaneous stiffness and mass estimations.•Monte Carlo analysis was performed to identify error sensitive parameters.•NDT data quality analysis was ...implemented to reduce measurement errors.•A set of most observable and error tolerant parameters were estimated.•Two separate commercial software packages were used for real-time FE model updating.
Structural Health Monitoring (SHM) using nondestructive test data has become promising for finite element (FE) model updating, model verification, structural evaluation and damage assessment. This research presents a multiresponse structural parameter estimation method for the automated FE model updating using data obtained from a set of nondestructive tests conducted on a laboratory bridge model. Both stiffness and mass parameters are updated at the element level, simultaneously. Having measurement and modeling errors is an inevitable part of data acquisition systems and finite element models. The presence of these errors can affect the accuracy of the estimated parameters. Therefore, an error sensitivity analysis using Monte Carlo simulation was used to study the input–output error behavior of each parameter based on the load cases and measurement locations of the nondestructive tests. Given the measured experimental responses, the goal was to select the unknown parameters of the FE model with high observability that leads to creating a well-conditioned system with the least sensitivity to measurement errors. A data quality study was performed to assess the accuracy and reliability of the measured data. Based on this study, a subset of the most reliable measured data was selected for the FE model updating. The selected subset of higher quality measurements and the observable unknown parameters were used for FE model updating. Three static and dynamic error functions were used for structural parameter estimation using the selected measured static strains, displacements, and slopes as well as dynamic natural frequencies and associated mode shapes. The measured data sets were used separately and also together for multiresponse FE model updating to match the predicted analytical response with the measured data. The FE model was successfully calibrated using multiresponse data. Two separate commercially available software packages were used with real-time data communications utilizing Application Program Interface (API) scripts. This approach was efficient in utilizing these software packages for automated and systematic FE model updating. The usefulness of the proposed method for automated finite element model updating at the element level is shown by being able to lead to simultaneous estimation of the stiffness and mass parameters using experimental data.
In order to promote sustainable steel-concrete composite structures, special shear connectors that can facilitate deconstruction are needed. A lockbolt demountable shear connector (LB-DSC), including ...a grout-filled steel tube embedded in the concrete slab and fastened to a geometrically compatible partial-thread bolt, which is bolted on the steel section’s top flange of a composite beam, was proposed. The main drawback of previous similar demountable bolts is the sudden slip of the bolt inside its hole. This bolt has a locked conical seat lug that is secured inside a predrilled compatible counter-sunk hole in the steel section’s flange to provide a non-slip bolt-flange connection. Deconstruction is achieved by demounting the tube from the top of the slab by unfastening using a simple modified wrench. The mechanical behaviour of the proposed connector is assessed by four pushout tests that were conducted per Eurocode 4 recommendations. The tests showed high shear resistance, and high stiffness as compared to other DSCs, while the slip capacity results classified the LB-DSC as a ductile shear connector according to Eurocode 4. A refined nonlinear finite element model (FEM) was validated through the tests and reliably reproduced the experimental behaviour. Consequently, the calibrated FEM model was applied to carry out extensive parametric analyses to investigate the strength and geometry effects of concrete slab, infilled grout, tube, and bolt on the structural behaviour of the LB-DSC. On the basis of numerical and experimental results, a design equation is derived to predict the shear resistance of the LB-DSC.
Head injury models are notoriously time consuming and resource demanding in simulations, which prevents routine application. Here, we extend a convolutional neural network (CNN) to instantly estimate ...element-wise distribution of peak maximum principal strain (MPS) of the entire brain (>36 k speedup accomplished on a low-end computing platform). To achieve this, head impact rotational velocity and acceleration temporal profiles are combined into two-dimensional images to serve as CNN input for training and prediction of MPS. Compared with the directly simulated counterparts, the CNN-estimated responses (magnitude and distribution) are sufficiently accurate for 92.1% of the cases
10-fold cross-validation using impacts drawn from the real world (
= 5661; range of peak rotational velocity in augmented data extended to 2-40 rad/sec). The success rate further improves to 97.1% for "in-range" impacts (
= 4298). When using the same CNN architecture to train (
= 3064) and test on an independent, reconstructed National Football League (NFL) impact dataset (
= 53; 20 concussions and 33 non-injuries), 51 out of 53, or 96.2% of the cases, are sufficiently accurate. The estimated responses also achieve virtually identical concussion prediction performances relative to the directly simulated counterparts, and they often outperform peak MPS of the whole brain (e.g., accuracy of 0.83 vs. 0.77
leave-one-out cross-validation). These findings support the use of CNN for accurate and efficient estimation of spatially detailed brain strains across the vast majority of head impacts in contact sports. Our technique may hold the potential to transform traumatic brain injury (TBI) research and the design and testing standards of head protective gears by facilitating the transition from acceleration-based approximation to strain-based design and analysis. This would have broad implications in the TBI biomechanics field to accelerate new scientific discoveries. The pre-trained CNN is freely available online at https://github.com/Jilab-biomechanics/CNN-brain-strains.
•Water diffusivity of GFRP was obtained from a FE model with consideration of defects.•The penetrated water in GFRP resulted in fiber degradation at the local position.•The retained GFRP strength was ...derived from integration of fibers at each location.•A diffusion-degradation framework was developed and validated with experimental data.•The framework can rapidly predict long-term GFRP strength under a moist condition.
The durability performance of glass fiber reinforced polymer (GFRP) has attracted wide attention, but conventional experimental methods for durability prediction are time-consuming, labor-intensive and not applicable to members with different sizes or geometries. To address this issue, a new modeling approach is developed in this study to simulate the diffusion-degradation process of GFRP composite in a moist environment. Taking a GFRP rebar as an example, the water diffusivity of composite is firstly obtained from a finite element model with the assumption of hexagonal fiber arrangement. With test results on the degradation of single coated fibers in the wet environment, and the simulated water front from the diffusion analysis, the strength retention at each location over the rebar section can be derived. The time-dependent degradation of tensile strength can hence be obtained from integration. To account for the defects (including matrix cracking, fiber erosion and fiber/matrix debonding) which can affect the water diffusivity, a refined diffusion model was also performed with increased water diffusivity (from 4.0 × 10-6 mm2/s to 4.5 × 10-6 mm2/s) and presence of interfacial crevices in the corroded region. While the refined model can lead to faster water diffusion and tensile strength degradation, the difference with the original model is within 10%. More importantly, both models are able to correctly predict the GFRP tensile strength degradation measured in the laboratory over a 12-month period. As the diffusion-degradation framework proposed in this study is applicable to any member size and geometry, it supplies engineers with an evaluation method to quickly predict the long-term tensile performance of GFRP structures.
