• Smart Structures and Systems
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• v.18 no.3
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• pp.471-484
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• 2016

Optical fiber sensors have been proven that they have the potential to detect high-frequency ultrasonic signals, in structural health monitoring field which generally refers to acoustic emission signals from active structural damages and guided waves excited by ultrasonic actuators and propagating in waveguide. In this work, the sensing properties of optical fiber sensors based on Mach-Zehnder interferometer were investigated in the metal plate. Analytical formulas were conducted first to explore the parameters affecting its sensing performances. Due to the simple and definable frequency component, the Lamb wave excited by the piezoelectric wafer was employed to study the sensitivity of the proposed optical fiber sensors with respect to the frequency, rather than the acoustic emission signals. In the experiments, according to above investigations, spiral shape optical fiber sensors with different size were selected to increase their sensitivity. Lamb waves were excited by a circular piezoelectric wafer, while another piezoelectric wafer was used to compare their voltage responses. Furthermore, by changing the excitation frequency, the tuning frequency characteristic of the proposed optical fiber sensor was also investigated experimentally.

• Smart Structures and Systems
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• v.24 no.1
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• pp.1-14
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• 2019

Transmission tower-line system is one of most critical lifeline systems to cities. However, it is found that the transmission tower-line system is prone to be damaged by earthquakes in past decades. To mitigate seismic demands, this study introduces a tuned-mass damper (TMD) using superelastic shape memory alloy (SMA) spring for the system. In addition, considering the dynamic characteristics of both tower-line system and SMA are affected by temperature change. Particular attention is paid on the effect of temperature variation on seismic behavior. In doing so, the SMA-TMD is installed into the system, and its properties are optimized through parametric analyses. The considered temperature range is from -40 to $40^{\circ}C$. The seismic control effect of using SMA-TMD is investigated under the considered temperatures. Interested seismic performance indices include peak displacement and peak acceleration at the tower top and the height-wise deformation. Parametric analyses on seismic intensity and frequency ratio were carried out as well. This study indicates that the nonlinear behavior of SMA-TMD is critical to the control effect, and proper tuning before application is advisable. Seismic demand mitigation is always achieved in this wide temperature range, and the control effect is increased at high temperatures.

• Earthquakes and Structures
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• v.17 no.1
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• pp.49-61
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• 2019

A novel asymmetrical resistance friction damper (ARFD) was proposed in this study to be applied on a rocking column base. The damper comprises multiple steel plates and was fastened using high-strength bolts. The sliding surfaces can be switched into one another and can cause strength to be higher in the loading direction than in the unloading direction. By combining the asymmetrical resistance with the restoring resistance that is generated due to an axial load on the column, the rocking column base can develop a self-centering behavior and achieve high connection strength. Cyclic tests on the ARFD proved that the damper performs a stable asymmetrical hysteretic loop. The desired hysteretic behavior was achieved by tuning the bolt pretension force and the diameter of the round bolt hole. In this study, full-scale, flexural tests were conducted to evaluate the performance of the column base and to verify the analytical model. The results indicated that the column base exhibits a stable self-centering behavior up to a drift angle of 4%. The decompression moment and maximum strength reached 42% and 88% of the full plastic moment of the section, respectively, under a column axial force ratio of approximately 0.2. The strengths and self-centering capacity can be obtained by determining the bolt pretension force. The analytical model results revealed good agreement with the experimental results.

• Transactions of Materials Processing
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• v.32 no.2
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• pp.74-80
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• 2023

A deformation behavior of commercially pure titanium (CP-Ti) is highly dependent on material and processing parameters, such as deformation temperature, deformation direction, and strain rate. This study aims to predict the multivariable and nonlinear tensile behavior of CP-Ti using machine learning based on three algorithms: artificial neural network (ANN), light gradient boosting machine (LGBM), and long short-term memory (LSTM). The predictivity for tensile behaviors at the cryogenic temperature was lower than those in the room temperature due to the larger data scattering in the train dataset used in the machine learning. Although LGBM showed the lowest value of root mean squared error, it was not the best strategy owing to the overfitting and step-function morphology different from the actual data. LSTM performed the best as it effectively learned the continuous characteristics of a flow curve as well as it spent the reduced time for machine learning, even without sufficient database and hyperparameter tuning.

• Earthquakes and Structures
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• v.15 no.3
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• pp.335-350
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• 2018

This paper presents numerical modelling, modal testing, finite element model updating, linear and nonlinear earthquake behavior of a reinforced concrete building model. A 1/2 geometrically scale, two-storey, reinforced concrete frame model with raft base were constructed, tested and analyzed. Modal testing on the model using ambient vibrations is performed to illustrate the dynamic characteristics experimentally. Finite element model of the structure is developed by ANSYS software and dynamic characteristics such as natural frequencies, mode shapes and damping ratios are calculated numerically. The enhanced frequency domain decomposition method and the stochastic subspace identification method are used for identifying dynamic characteristics experimentally and such values are used to update the finite element models. Different parameters of the model are calibrated using manual tuning process to minimize the differences between the numerically calculated and experimentally measured dynamic characteristics. The maximum difference between the measured and numerically calculated frequencies is reduced from 28.47% to 4.75% with the model updating. To determine the effects of the finite element model updating on the earthquake behavior, linear and nonlinear earthquake analyses are performed using 1992 Erzincan earthquake record, before and after model updating. After model updating, the maximum differences in the displacements and stresses were obtained as 29% and 25% for the linear earthquake analysis and 28% and 47% for the nonlinear earthquake analysis compared with that obtained from initial earthquake results before model updating. These differences state that finite element model updating provides a significant influence on linear and especially nonlinear earthquake behavior of buildings.

• Wind and Structures
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• v.7 no.4
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• pp.251-264
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• 2004

The effects of a class of nonlinear Tuned Mass Dampers on the aeroelastic behavior of SDOF systems are investigated. Unlike classical linear TMDs, nonlinear constitutive laws of the internal damping acting between the primary oscillator and the TMD are considered, while the elastic properties are keept linear. The perturbative Multiple Scale Method is applied to derive a set of bifurcation equations in the amplitude and phase and a parametric analysis is performed to describe the postcritical scenario of the system. Both cubic- and van der Pol-type dampings are considered and the dependence of the limit-cycle amplitudes on the system parameters is studied. These new results, compared with the previously obtained bifurcation scenario of a SDOF aeroelastic oscillator equipped with a linear TMD, show a detrimental effect on the maximum limit-cycle amplitude reduction of the nonlinear TMD. However, the analyses evidence that in the parameter region away from the perfect tuning condition the nonlinear connection can be used to tune the system with an enhancement of the limit-cycle amplitude reduction.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.482-489
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• 2015

CSTR (Continuous Stirred Tank Reactor) which plays a key role in the chemical plants exhibits highly nonlinear behavior as well as time-varying behavior during operation. The control of CSTRs in the whole operating range has been a challenging problem to control engineers. So, a variety of feedback control forms and their tuning methods have been implemented to guarantee the satisfactory performance. This paper presents a scheme of designing a nonlinear PID controller incorporating with a GA (Genetic Algorithm) for the temperature control of a CSTR. The gains of the NPID controller are composed of easily implementable nonlinear functions based on the error and/or the error rate and its parameters are tuned using a GA by minimizing the ITAE (Integral of Absolute Error). Simulation works for reference tracking and disturbance rejecting performances and robustness to parameter changes show the feasibility of the proposed method.

• Journal of Mechanical Science and Technology
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• v.16 no.4
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• pp.476-484
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• 2002

The aim of this study is to investigate the ductile fracture behavior under mixed mode (I/II) loading using SA533B pressure vessel steel. Anti-symmetric 4-point (AS4P) bending tests were performed to obtain the J-R curves under two different mixed mode (I/II) loadings. In addition, finite element analysis using Rousselier Ductile Damage Theory was carried out to predict the J-R curves under mixed mode (I/II) loadings. In conclusions, the J-R curves under. Mixed Mode (I/II) loading were located between those of Mode I and Mode II loading. When the mixity of mixed mode (I/II) loading was high, the J-R curve of mixed mode (I/II) loading approached that of pure mode I loading after some amount of crack propagation. In contrast with the above fact, if the mixity was low, the J-R curve took after that of pure mode II loading. Finally, it was found that the predicted J-R curves made a good agreement with the test data through the tuning procedures of $\beta$ values at the different mixed mode (I/II) loading.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.755-778
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• 2024

In recent years, the number of devices being connected to the internet has grown enormously, as has the intrusive behavior in the network. Thus, it is important for intrusion detection systems to report all intrusive behavior. Using deep learning and machine learning algorithms, intrusion detection systems are able to perform well in identifying attacks. However, the concern with these deep learning algorithms is their inability to identify a suitable network based on traffic volume, which requires manual changing of hyperparameters, which consumes a lot of time and effort. So, to address this, this paper offers a solution using the extended compact genetic algorithm for the automatic tuning of the hyperparameters. The novelty in this work comes in the form of modeling the problem of identifying attacks as a multi-objective optimization problem and the usage of linkage learning for solving the optimization problem. The solution is obtained using the feature map-based Convolutional Neural Network that gets encoded into genes, and using the extended compact genetic algorithm the model is optimized for the detection accuracy and latency. The CIC-IDS-2017 and 2018 datasets are used to verify the hypothesis, and the most recent analysis yielded a substantial F1 score of 99.23%. Response time, CPU, and memory consumption evaluations are done to demonstrate the suitability of this model in a fog environment.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.5
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• pp.635-644
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• 2012

In order to design a wave energy generating system, a 6-DOF analysis technique is applied to the three-Dimensional CFD analysis on of a floating body and the behavior is interpreted according to the nature of the incoming wave. A wave period of 5.5s & amplitude of 0.57m from Marado is chosen. 12 case of natural pitching period from 1.25 to 2.8s has been modeled. The relation between tuning factor & pitch angle for the waves generated is compared to analyze the effects of energy absorption variables, namely mass moment of inertia, angular velocity and angular acceleration. From the results obtained, we conclude that model L is the maximum power absorbed, 6kW approximately. A maximum pitch angle of 1.91 degree was attained by Model F, and the maximum displacement of nearly 0.7m was attained by Model L among models D, F and L.