• Coupled systems mechanics
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• v.8 no.2
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• pp.99-109
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• 2019

This work investigates the accuracy and performance of a $FE^2$ multi-scale implementation used to predict the behavior of composite materials. The equations are formulated assuming the small deformations solid mechanics approach in non-linear material models with hardening plasticity. The uniform strain boundary conditions are applied for the macro-to-micro transitions. A parallel algorithm was implemented in order to solve large engineering problems. The scheme proposed takes advantage of the domain decomposition method at the macro-scale and the coupling between each subdomain with a micro-scale model. The precision of the method is validated with a composite material problem and scalability tests are performed for showing the efficiency.

• Smart Structures and Systems
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• v.24 no.5
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• pp.597-606
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• 2019

Damage detection based on dynamic characteristics of a structure is one of important roles in structural damage identification. It is difficult to detect local structural damage using traditional dynamic experimental methods due to a limited number of sensors used in an experiment. In this work, a non-contact test stand of fan blades is established, and a full-field noncontact test method, combined with three-dimensional digital image correlation, Bayesian operational modal analysis, and damage indices, is used to detect local damage of a fan blade under ambient excitation without use of baseline information before structural damage. The methodology is applied to detect invisible local damage on the fan blade. Such a method has a seemingly high potential as an alternative to detect local damage of blades with complex high-precision surfaces under extreme working conditions because it is a noncontact test method and can be used under ambient excitation without human participation.

• Smart Structures and Systems
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• v.29 no.6
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• pp.799-805
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• 2022

Permanent magnet synchronous motors (PMSMs) are widely used in systems requiring high control precision, efficiency, and reliability. Predicting the remaining useful life (RUL) with health monitoring of PMSMs prevents catastrophic failure and ensures reliable operation of system. In this study, a model-based method for predicting the RUL of PMSMs using phase current and vibration signals is proposed. The proposed method includes feature selection and RUL prediction based on a particle filter with a degradation model. The Paris-Erdogan model describing micro fatigue crack propagation is used as the degradation model. An experimental set-up to conduct accelerated life test, capable of monitoring various signals was designed in this study. Phase current and vibration data obtained from an accelerated life test of the PMSMs were used to verify the proposed approach. Features extracted from the data were clustered based on monotonicity and correlation clustering, respectively. The results identify the effectiveness of using the current data in predicting the RUL of PMSMs.

• Geomechanics and Engineering
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• v.29 no.3
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• pp.369-376
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• 2022

Accurately evaluating and predicting the performance of facilities is a key task in establishing a maintenance strategy for facilities. The importance of performance evaluation is becoming more pronounced, especially when the aging of facilities requires a huge budget. In this study, performance assessment models were developed for road and railway tunnels. Delphi analysis was performed to identify sub-elements necessary to evaluate the performance of a tunnel. The relative importance of the evaluation factors was derived from the AHP analysis. The correlation analysis was performed between each assessment factor and the final result to verify the significance of the model. For the correlation analysis, the survey data measured through precision safety diagnosis in tunnels in use was applied. The cost effectiveness analysis was also conducted according to the scenarios with different composition of performance factors in order to improve the practical applicability of the evaluation model developed in this study.

• Structural Engineering and Mechanics
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• v.82 no.6
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• pp.701-711
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• 2022

The nonlocal elasticity as well as Mindlin's first-order shear deformation plate theory are proposed to investigate thermal vibrational of a nanoplate placing on a three-factor foundation. The Winkler-Pasternak elastic foundation is connected with the viscous damping to obtain the present three-parameter viscoelastic model. Differential equations of motion are derived and resolved for simply-supported nanoplates to get their natural frequencies. The influences of the nonlocal index, viscous damping index, and temperature changes are investigated. A comparison example is dictated to validate the precision of present results. Effects of other factors such as aspect ratio, mode numbers, and foundation parameters are discussed carefully for the vibration problem. Additional thermal vibration results of nanoplates resting on the viscoelastic foundation are presented for comparisons with future investigations.

• Smart Structures and Systems
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• v.30 no.2
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• pp.209-219
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• 2022

The determination for bearing capacity of precast nodular piles is conventionally time-consuming and high-cost by using numerous experiments and empirical methods. This study proposes an intelligent method to evaluate the bearing capacity and shaft resistance of the nodular piles with high efficiency based on long short-term memory (LSTM) approach. A series of field tests are first designed to measure the axial force, shaft resistance and displacement of the combined nodular piles under different loadings, in comparison with the single pre-stressed high-strength concrete piles. The test results confirm that the combined nodular piles could provide larger ultimate bearing capacity (more than 100%) than the single pre-stressed high-strength concrete piles. Both the LSTM-based method and empirical methods are used to calculate the shift resistance of the combined nodular piles. The results show that the LSTM-based method has a high-precision estimation on shaft resistance, not only for the ultimate load but also for the working load.

• Steel and Composite Structures
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• v.48 no.5
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• pp.583-597
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• 2023

This paper introduces a novel approach to multi-material topology optimization (MTO) targeting in-plane bi-directional functionally graded (IBFG) non-uniform thickness Reissner-Mindlin plates, employing an alternative active phase approach. The mathematical formulation integrates a first shear deformation theory (FSDT) to address compliance minimization as the objective function. Through an alternating active-phase algorithm in conjunction with the block Gauss-Seidel method, the study transforms a multi-phase topology optimization challenge with multi-volume fraction constraints into multiple binary phase sub-problems, each with a single volume fraction constraint. The investigation focuses on IBFG materials that incorporate adequate local bulk and shear moduli to enhance the precision of material interactions. Furthermore, the well-established mixed interpolation of tensorial components 4-node elements (MITC4) is harnessed to tackle shear-locking issues inherent in thin plate models. The study meticulously presents detailed mathematical formulations for IBFG plates in the MTO framework, underscored by numerous numerical examples demonstrating the method's efficiency and reliability.

• Smart Structures and Systems
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• v.32 no.4
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• pp.219-233
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• 2023

Crack width is an important indicator to evaluate the health condition of the concrete structure. The crack width is measured by manual using crack width gauge commonly, which is time-consuming and laborious. In this paper, we have proposed a fast and simplified crack width quantification method via deep Q learning and geometric calculation. Firstly, the crack edge is extracted by using U-Net network and edge detection operator. Then, the intelligent decision of is made by the deep Q learning model. Further, the geometric calculation method based on endpoint and curvature extreme point detection is proposed. Finally, a case study is carried out to demonstrate the effectiveness of the proposed method, achieving high precision in the real crack width quantification.

• Computers and Concrete
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• v.32 no.6
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• pp.607-613
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• 2023

The objective of this work is to determine the compressive strength of geopolymer concrete utilizing four distinct machine learning approaches. These techniques are known as gradient boosting machine (GBM), generalized linear model (GLM), extremely randomized trees (XRT), and deep learning (DL). Experimentation is performed to collect the data that is then utilized for training the models. Compressive strength is the response variable, whereas curing days, curing temperature, silica fume, and nanosilica concentration are the different input parameters that are taken into consideration. Several kinds of errors, including root mean square error (RMSE), coefficient of correlation (CC), variance account for (VAF), RMSE to observation's standard deviation ratio (RSR), and Nash-Sutcliffe effectiveness (NSE), were computed to determine the effectiveness of each algorithm. It was observed that, among all the models that were investigated, the GBM is the surrogate model that can predict the compressive strength of the geopolymer concrete with the highest degree of precision.

• Steel and Composite Structures
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• v.50 no.2
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• pp.135-148
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• 2024

This paper analytically investigates the free vibration analysis of functionally graded-carbon nanotube reinforced composite (FG-CNTRC) plates by dynamic stiffness method (DSM). The properties of CNTRC are determined with the extended rule of mixture. The governing differential equations of motion based on the first-order shear deformation theory of CNTRC plate are derived using Hamilton's principle. The FG-CNTRC plates are studied for a uniform and two different distributions of carbon nanotubes (CNTs). The accuracy and performance of the DSM are compared with the results obtained from closed closed-form and semi-analytical solution methods in previous studies. In this study, the effects of boundary condition, distribution type of CNTs, plate aspect ratio, plate length to thickness ratio, and different values of CNTs volume fraction on the natural frequencies of the FG-CNTRC plates are investigated. Finally, various natural frequencies of the plates in different conditions are provided as a benchmark for comparing the accuracy and precision of the other analytical and numerical methods.