• 한국도로학회:학술대회논문집
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• 2008.10a
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• pp.93-102
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• 2008

An energy based crack growth model is developed in this study to simulate the propagation of top-down cracking in asphalt pavements. A viscoelastic fracture mechanics approach, generalized J integral, is employed to model the crack growth of asphalt concrete. Laboratory fatigue crack propagation tests for three different asphalt mixtures are performed at various load levels, frequencies and temperatures. Disk-shaped specimens with a proper loading fixture and crack growth monitoring system are selected for the tests. It is observed from the tests that the crack propagation model based on the generalized J integral is independent of load levels and frequencies, while the traditional Paris' law model based on stress intensity factor is dependent of loading frequencies. However, both models are unable to take care of the temperature dependence of the mixtures. The fatigue crack propagation model proposed in this study has a good agreement between experimental and predicted crack growth lives, which implies that the energy based J integral could be a better parameter to describe fatigue crack propagation of viscoelastic materials such as asphalt mixtures.

• Smart Structures and Systems
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• v.15 no.2
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• pp.355-373
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• 2015

An optimal sensor placement (OSP) method based on structural subsection technique (SST) and model reduction technique was proposed for modal identification of truss structures, which was conducted using genetic algorithm (GA). The constraints of GA variables were determined by SST in advance. Subsequently, according to model reduction technique, the optimal group of master degrees of freedom and the optimal objective function value were obtained using GA in a case of the given number of sensors. Correspondingly, the optimal number of sensors was determined according to optimal objective function values in cases of the different number of sensors. The proposed method was applied on a scaled jacket offshore platform to get its optimal number of sensors and the corresponding optimal sensor layout. Then modal kinetic energy and modal assurance criterion were adopted to evaluate vibration energy and mode independence property. The experiment was also conducted to verify the effectiveness of the selected optimal sensor layout. The results showed that experimental modes agreed reasonably well with numerical results. Moreover the influence of the proposed method using different optimal algorithms and model reduction technique on optimal results was also compared. The results showed that the influence was very little.

• Geomechanics and Engineering
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• v.7 no.4
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• pp.335-353
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• 2014

The softening hyperelastic model based on the strain energy limitation is of clear concepts and simple forms to describe the failure of materials. In this study, a linear and a nonlinear softening hyperelastic model are proposed to characterize the deformation and the failure in granular materials by introducing a softening function into the shear part of the strain energy. A method to determine material parameters introduced in the models is suggested. Based on the proposed models the numerical examples focus on bearing capacity and strain localization of granular materials. Compared with Volokh softening hyperelasticity and classical Mohr-Coulomb plasticity, our proposed models are able to capture the typical characters of granular materials such as the strain softening and the critical state. In addition, the issue of mesh dependency of the proposed models is investigated.

• Structural Engineering and Mechanics
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• v.75 no.4
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• pp.477-485
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• 2020

Finite element (FE) model based structural damage detection (SDD) methods play vital roles in effectively locating and quantifying structural damages. Among these methods, structural model updating should be conducted before SDD to obtain benchmark models of real structures. However, the characteristics of updating parameters are not reasonably considered in existing studies. Inspired by the l_∞ norm regularization, a novel anti-sparse representation method is proposed for structural model updating in this study. Based on sensitivity analysis, both frequencies and mode shapes are used to define an objective function at first. Then, by adding l_∞ norm penalty, an optimization problem is established for structural model updating. As a result, the optimization problem can be solved by the fast iterative shrinkage thresholding algorithm (FISTA). Moreover, comparative studies with classical regularization strategy, i.e. the l₂ norm regularization method, are conducted as well. To intuitively illustrate the effectiveness of the proposed method, a 2-DOF spring-mass model is taken as an example in numerical simulations. The updating results show that the proposed method has a good robustness to measurement noises. Finally, to further verify the applicability of the proposed method, a six-storey aluminum alloy frame is designed and fabricated in laboratory. The added mass on each storey is taken as updating parameter. The updating results provide a good agreement with the true values, which indicates that the proposed method can effectively update the model parameters with a high accuracy.

• Structural Engineering and Mechanics
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• v.63 no.2
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• pp.251-257
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• 2017

A local damage identification method using measured structural static displacement is proposed in this study. Based on the residual force vector deduced from the static equilibrium equation, residual strain energy (RSE) is introduced, which can localize the damage in the element level. In the case of all the nodal displacements are used, the RSE can localize the true location of damage, while incomplete displacement measurements are used, some suspicious damaged elements can be found. A model updating method based on static displacement response sensitivity analysis is further utilized for accurate identification of damage location and extent. The proposed method is verified by two numerical examples. The results indicate that the proposed method is efficient for damage identification. The advantage of the proposed method is that only limited static displacement measurements are needed in the identification, thus it is easy for engineering application.

• International Journal of Aerospace System Engineering
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• v.2 no.2
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• pp.44-49
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• 2015

A gust response analyses method based on Reduced Order Models (ROMs) was developed in the paper. Firstly, taken random signal as the input signal and adopt Single Input-Multi-Output (SIMO) training fashion, a ROM based on Auto-Regressive and Moving Average model (ARMA) was established and validated with the comparison of CFD/CSD and experiment. Then, by introducing control surface deflection and control laws, flutter active suppress was studied. Lastly, through filtering and transferring function, the gust temporal signal is obtained based on Dryden gust model, and gust response and suppress were simulated.

• Structural Engineering and Mechanics
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• v.84 no.2
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• pp.285-293
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• 2022

Lumped damage mechanics (LDM) is a recent nonlinear theory with several applications to civil engineering structures, such as reinforced concrete and steel buildings. LDM apply key concepts of classic fracture and damage mechanics on plastic hinges. Therefore, the lumped damage models are quite successful in reproduce actual structural behaviour using concepts well-known by engineers in practice, such as ultimate moment and first cracking moment of reinforced concrete elements. So far, lumped damage models are based in the strain energy equivalence hypothesis, which is one of the fictitious states where the intact material behaviour depends on a damage variable. However, there are other possibilities, such as the energy equivalence hypothesis. Such possibilities should be explored, in order to pursue unique advantages as well as extend the LDM framework. Therewith, a lumped damage model based on the energy equivalence hypothesis is proposed in this paper. The proposed model was idealised for reinforced concrete structures, where a damage variable accounts for concrete cracking and the plastic rotation represents reinforcement yielding. The obtained results show that the proposed model is quite accurate compared to experimental responses.

• Structural Engineering and Mechanics
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• v.83 no.3
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• pp.293-304
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• 2022

In this work, a novel reliability approach for combined high and low cycle fatigue (CCF) estimation is developed by combining active learning strategy with least squares support vector machines (LS-SVM) (named as ALS-SVM) surrogate model to address the multi-resources uncertainties, including working loads, material properties and model itself. Initially, a new active learner function combining LS-SVM approach with Monte Carlo simulation (MCS) is presented to improve computational efficiency with fewer calls to the performance function. To consider the uncertainty of surrogate model at candidate sample points, the learning function employs k-fold cross validation method and introduces the predicted variance to sequentially select sampling. Following that, low cycle fatigue (LCF) loads and high cycle fatigue (HCF) loads are firstly estimated based on the training samples extracted from finite element (FE) simulations, and their simulated responses together with the sample points of model parameters in Coffin-Manson formula are selected as the MC samples to establish ALS-SVM model. In this analysis, the MC samples are substituted to predict the CCF reliability of turbine blades by using the built ALS-SVM model. Through the comparison of the two approaches, it is indicated that the reliability model by linear cumulative damage rule provides a non-conservative result compared with that by the proposed one. In addition, the results demonstrate that ALS-SVM is an effective analysis method holding high computational efficiency with small training samples to gain accurate fatigue reliability.

• Structural Engineering and Mechanics
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• v.18 no.5
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• pp.691-707
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• 2004

This paper presents the micro-mechanical modeling for predicting concrete behavior under compressive loading. The model is able to represent the heterogeneities in the microstructure up to three phases, i.e., aggregate particles, matrix and interfaces. The smeared crack concept based on non-linear fracture mechanics is implemented in order to formulate the constitutive relation for each component. The splitting tensile strength is considered as a fracture criterion for cracking in micro-level. The finite element method is employed to simulate the model based on plane stress condition by using quadratic triangular elements. The validation of the model is verified by comparing with the experimental results. The influence of tensile strength from both aggregate and matrix phases on the concrete compressive strength is demonstrated. In addition, a guideline on selecting appropriate tensile strength for each phase to obtain specified concrete compressive strength is also presented.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.352-361
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• 2003

A fatigue damage accumulation model based on the continuum damage mechanics theory was develope(1 where modules decay ratios in tension and shear on used as indicators for damage variables D . In the model, the damage variables are considered to be second-order tensors. Then the maximum principal damage variable, $D^*$ is introduced According to the similarity to the Principal stress, $D^*$ is obtained as the maximum eigen value of damage tensor [D']. Under proportional tension and torsion loadings, fatigue lives were satisfactorily predicted at any combined stress ratios using the present model in which the fatigue characteristics only under uniaxial tension and pure torsion loadings on needed. Fatigue life prediction under uniaxial tension and pure torsion loadings, was performed based on the damage mechanics using boundary element method.