Free vibration of basalt fiber reinforced polymer (FRP) laminated variable thickness plates with intermediate elastic support using finite strip transition matrix (FSTM) method

Altabey, Wael A.

doi:10.21595/jve.2017.18154

Cited by 20 publications

(14 citation statements)

References 22 publications

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“…Bayesian optimization is a powerful tool for optimizing objective functions which are very costly or slow to evaluate [48][49][50][51][52][53]. In particular, we consider problems where the maximum is sought for an objective function f:…”

Section: In Summary Interconnected Computational Nodes Perform Lineamentioning

confidence: 99%

Applying Neural Networks for Tire Pressure Monitoring Systems

Kost¹,

Altabey²,

Noori³

et al. 2019

Structural Durability &Amp; Health Monitoring

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A proof-of-concept indirect tire-pressure monitoring system is developed using artificial neural networks to identify the tire pressure of a vehicle tire. A quarter-car model was developed with MATLAB and Simulink to generate simulated accelerometer output data. Simulation data are used to train and evaluate a recurrent neural network with long short-term memory blocks (RNN-LSTM) and a convolutional neural network (CNN) developed in Python with Tensorflow. Bayesian Optimization via SigOpt was used to optimize training and model parameters. The predictive accuracy and training speed of the two models with various parameters are compared. Finally, future work and improvements are discussed.

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Section: In Summary Interconnected Computational Nodes Perform Lineamentioning

confidence: 99%

Applying Neural Networks for Tire Pressure Monitoring Systems

Kost¹,

Altabey²,

Noori³

et al. 2019

Structural Durability &Amp; Health Monitoring

View full text Add to dashboard Cite

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“…The normalized partial differential equation governing the vibration of symmetrically, angleply laminated, variable thickness, rectangular plates under the assumption of the classical deformation theory in terms of the plate deflection ( , , ) using the non-Dimensional variables and is given by [1,2]:…”

Section: Governing Equationsmentioning

confidence: 99%

“…FSTM is one of a semi-analytical methods are welcomed in the many literatures as an alternative to the exact solution. In our previous paper by Altabey [1], a semi-analytical method, the FSTM approach has been used to investigate the free vibration of basalt FRP laminated variable thickness rectangular plates with IES. Since all of the coefficients in the FSTM method can be obtained, a lot of calculations with large number of iterations must be performed to obtain a frequency parameters, i.e.…”

Section: Introductionmentioning

confidence: 99%

Prediction of natural frequency of basalt fiber reinforced polymer (FRP) laminated variable thickness plates with intermediate elastic support using artificial neural networks (ANNs) method

Altabey¹

2017

J. vibroeng.

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The paper is focused on the application of artificial neural networks (ANNs) in predicting the natural frequency of basalt fiber reinforced polymer (FRP) laminated, variable thickness plates. The author has found that the finite strip transition matrix (FSTM) approach is very effective to study the changes of plate natural frequencies due to intermediate elastic support (IES), but the method difficulty in terms of, a lot of calculations with large number of iterations is the main drawback of the method. For training and testing of the ANN model, a number of FSTM results for different classical boundary conditions (CBCs) with different values of elastic restraint coefficients () for IES have been carried out to training and testing an ANN model. The ANN model has been developed using multilayer perceptron (MLP) Feed-forward neural networks (FFNN). The adequacy of the developed model is verified by the regression coefficient () and Mean Square error (MSE) It was found that the R2 and MSE values are 0.986 and 0.0134 for train and 0.9966 and 0.0122 for test data respectively. The results showed that, the training algorithm of FFNN was sufficient enough in predicting the natural frequency in basalt FRP laminated, variable thickness plates with IES. To judge the ability and efficiency of the developed ANN model, MSE has been used. The results predicted by ANN are in very good agreement with the FSTM results. Consequently, the ANN is show to be effective in predicting the natural frequency of laminated composite plates.

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“…These disturbances are dealt with innovative technologies to enhance structural functionality and safety in various stages of research and development (Spencer, 2003;Altabey, 2017a). Several types of structures that employ control strategies for different application scopes can be found in Constantinou et al (1998), Soong and Spencer (2002), and Altabey (2014Altabey ( , 2017b; Altabey (2018). Proper modeling of inherent non-linearity in vast majority of structural systems plays an important role in understanding structural response under hazardous loadings.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Three Different Methods for the Identification of Hysterically Degrading Structures Using BWBN Model

Zhao

Noori

Altabey

et al. 2019

Front. Built Environ.

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Structural control and health monitoring scheme play key roles not only in enhancing the safety and reliability of infrastructure systems when they are subjected to natural disasters, such as earthquakes, high winds, and sea waves, but it also optimally minimize the life cycle cost and maximize the whole performance through the full life cycle design. In this scheme, system identification is regarded as a major technique to identify system states and related parameter variables, thus preventing degradation of structural or mechanical systems when unexpected disturbances occur. In this paper, three different strategies are proposed to identify general hysteretic behavior of a typical shear structure subjected to external excitations. Different case studies are presented to analyze the dynamic responses of a time varying shear structural system with the early version of Bouc-Wen-Baber-Noori (BWBN) hysteresis model. By incorporating a "Gray Box" strategy utilizing an Intelligent Parameter Varying (IPV) and Artificial Neural Network (ANN) approach, a Genetic algorithm (GA), and a Transitional Markov Chain Monte Carlo (TMCMC) based Bayesian Updating framework system identification schemes are developed to identify the hysteretic behavior of the structural system. Hysteresis characteristics, computational accuracy, and algorithm efficiency are further discussed by evaluating the system identification results. Results show that IPV performs superior computational efficiency and system identification accuracy over GA and TMCMC approaches.

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Free vibration of basalt fiber reinforced polymer (FRP) laminated variable thickness plates with intermediate elastic support using finite strip transition matrix (FSTM) method

Cited by 20 publications

References 22 publications

Applying Neural Networks for Tire Pressure Monitoring Systems

Applying Neural Networks for Tire Pressure Monitoring Systems

Prediction of natural frequency of basalt fiber reinforced polymer (FRP) laminated variable thickness plates with intermediate elastic support using artificial neural networks (ANNs) method

A Comparison of Three Different Methods for the Identification of Hysterically Degrading Structures Using BWBN Model

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