• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Journal of Korean Society of Steel Construction
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• v.14 no.5 s.60
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• pp.613-625
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• 2002

This paper aimed to investigate the damage process of steel parts experiencing failure under strong repeated loading. Likewise, a damage index using various factors related to the damage was proposed. An analysis method for evaluating the damage state was also developed. The damage assessment method focused on the local strain history at the cross-section of the heaviest concentration of deformation. Cantilever-type steel parts were analyzed under uniaxial load combined with a constant axial load, considering horizontal displacement history, Loading patterns and steel types were considered as the main parameters in analyzing the models. The effects of the parameters on the failure modes, deformation capacity, and damage process as seen from the analysis results were also discussed. Each failure process was compared as steel types. In addition, the failure of steel parts under strong repeated loading was determined according to loading. Results revealed that the state of the failure is closely related to the local plastic strain.

• Interaction and multiscale mechanics
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• v.1 no.2
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• pp.279-301
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• 2008

This paper develops a 3D homogenization based continuum damage mechanics (HCDM) model for fiber reinforced composites undergoing micromechanical damage under monotonic and cyclic loading. Micromechanical damage in a representative volume element (RVE) of the material occurs by fiber-matrix interfacial debonding, which is incorporated in the model through a hysteretic bilinear cohesive zone model. The proposed model expresses a damage evolution surface in the strain space in the principal damage coordinate system or PDCS. PDCS enables the model to account for the effect of non-proportional load history. The loading/unloading criterion during cyclic loading is based on the scalar product of the strain increment and the normal to the damage surface in strain space. The material constitutive law involves a fourth order orthotropic tensor with stiffness characterized as a macroscopic internal variable. Three dimensional damage in composites is accounted for through functional forms of the fourth order damage tensor in terms of components of macroscopic strain and elastic stiffness tensors. The HCDM model parameters are calibrated from homogenization of micromechanical solutions of the RVE for a few representative strain histories. The proposed model is validated by comparing results of the HCDM model with pure micromechanical analysis results followed by homogenization. Finally, the potential of HCDM model as a design tool is demonstrated through macro-micro analysis of monotonic and cyclic damage progression in composite structures.

• Steel and Composite Structures
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• v.15 no.4
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• pp.357-377
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• 2013

In order to study the degradation and damage behaviors of steel frame welded connections, two series of tests in references with different connection constructions were carried out subjected to various cyclic loading patterns. Hysteretic curves, degradation and damage behaviours and fatigue properties of specimens were firstly studied. Typical failure modes and probable damage reasons were discussed. Then, various damage index models with variables of dissipative energy, cumulative displacement and combined energy and displacement were summarized and applied for all experimental specimens. The damage developing curves of ten damage index models for each connection were obtained. Finally, the predicted and evaluated capacities of damage index models were compared in order to describe the degraded performance and failure modes. The characteristics of each damage index model were discussed in depth, and then their distributive laws were summarized. The tests and analysis results showed that the loading histories significantly affected the distributive shapes of damage index models. Different models had their own ranges of application. The selected parameters of damage index models had great effect on the developing trends of damage curves. The model with only displacement variable was recommended because of a more simple form and no integral calculation, which was easier to be formulated and embedded in application programs.

• Structural Engineering and Mechanics
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• v.44 no.5
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• pp.585-600
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• 2012

This paper presents a Modified Tikhonov Regularization (MTR) method in model updating for damage identification with model errors and measurement noise influences consideration. The identification equation based on sensitivity approach from the dynamic responses is ill-conditioned and is usually solved with regularization method. When the structural system contains model errors and measurement noise, the identified results from Tikhonov Regularization (TR) method often diverge after several iterations. In the MTR method, new side conditions with limits on the identification of physical parameters allow for the presence of model errors and ensure the physical meanings of the identified parameters. Chebyshev polynomial is applied to approximate the acceleration response for moderation of measurement noise. The identified physical parameter can converge to a relative correct direction. A three-dimensional unsymmetrical frame structure with different scenarios is studied to illustrate the proposed method. Results revealed show that the proposed method has superior performance than TR Method when there are both model errors and measurement noise in the structure system.

• Advances in Traditional Medicine
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• v.7 no.1
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• pp.74-78
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• 2007

The plants, Trianthema decandra and Glinus oppositifolius are commonly used by tribal people in India for the treatment of liver diseases. Hepatoprotective activity of methanol extracts of Glinus oppositifolius and Trianthema decandra at the dose of 250 and 500 mg/kg body weight administered orally was evaluated against paracetamol induced liver damage in rats. Biochemical parameters such as serum glutamate oxaloacetate transaminase, serum glutamate pyruvate transaminase, serum alkaline phosphatase, bilirubin, total serum protein, lipid peroxide and glutathione content of the liver were estimated to determine liver function and metabolism. From the biochemical observations, it was concluded that methanol extracts of Glinus oppositifolius and Trianthema decandra significantly restored the altered biochemical parameters towards normal condition in paracetamol induced liver damage.

• Structural Monitoring and Maintenance
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• v.4 no.4
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• pp.365-379
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• 2017

This paper presents a comparison of the black-box and the physics based derived gray-box models for subspace identification for structures subjected to support-excitation. The study compares the damage detection capabilities of both these methods for linear time invariant (LTI) systems as well as linear time-varying (LTV) systems by extending the gray-box model for time-varying systems using short-time windows. The numerically simulated IASC-ASCE Phase-I benchmark building has been used to compare the two methods for different damage scenarios. The efficacy of the two methods for the identification of stiffness parameters has been studied in the presence of different levels of sensor noise to simulate on-field conditions. The proposed extension of the gray-box model for LTV systems has been shown to outperform the black-box model in capturing the variation in stiffness parameters for the benchmark building.

• Proceedings of the Korean Reliability Society Conference
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• 2000.04a
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• pp.213-222
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• 2000

In present study, a stochastic model is developed for the low cycle fatigue life prediction and reliability assessment of 316L stainless steel under variable multiaxial loading. In the proposed model, fatigue phenomenon is considered as a Markov process, and damage vector and reliability are defined on every plane. Any low cycle fatigue damage evaluating method can be included in the proposed model. The model enables calculation of statistical reliability and crack initiation direction under variable multiaxial loading, which are generally not available. In present study, a critical plane method proposed by Kandil et al., maximum tensile strain range, and von Mises equivalent strain range are used to calculate fatigue damage. When the critical plane method is chosen, the effect of multiple critical planes is also included in the proposed model. Maximum tensile strain and von Mises strain methods are used for the demonstration of the generality of the proposed model. The material properties and the stochastic model parameters are obtained from uniaxial tests only. The stochastic model made of the parameters obtained from the uniaxial tests is applied to the life prediction and reliability assessment of 316L stainless steel under variable multiaxial loading. The predicted results show good accordance with experimental results.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.93-96
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• 2006

This study represents results of performance-based fragility analysis of reinforced concrete (RC) bridge. Monte carlo simulation is performed to study nonlinear dynamic responses of RC bridge. Two-parameter log-normal distribution function is used to represent the fragility curves. These two-parameters, referred to as fragility parameters, are estimated by the traditional maximum likelihood procedure, which. is treated each event of RC bridge pier damage as a realization of Bernoulli experiment. In order to formulate the fragility curves, five different damage states are described by two practical factors: the displacement and curvature ductility, which are mostly influencing on the seismic behavior of RC bridge piers. Five damage states are quantitatively assessed in terms of these seismic ductilities on the basis of numerous experimental results of RC bridge piers. Thereby, the performance-based fragility curves of RC bridge pier are provided in this paper.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.4
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• pp.533-546
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• 2021

Large earthquakes with (M_W > ~ 6) result in ground shaking, surface ruptures, and permanent deformation with displacement. The earthquakes would damage important facilities and infrastructure such as large industrial establishments, nuclear power plants, and waste disposal sites. In particular, earthquake ruptures associated with large earthquakes can affect geological and engineered barriers such as deep geological repositories that are used for storing hazardous radioactive wastes. Earthquake-driven faults and surface ruptures exhibit various fault zone structural characteristics such as direction of earthquake propagation and rupture and asymmetric displacement patterns. Therefore, estimating the respect distances and hazardous areas has been challenging. We propose that considering multiple parameters, such as fault types, distribution, scale, activity, linkage patterns, damage zones, and respect distances, enable accurate identification of the sites for deep geological repositories and important facilities. This information would enable earthquake hazard assessment and lower earthquake-resulted hazards in potential earthquake-prone areas.