• Structural Engineering and Mechanics
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• v.89 no.6
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• pp.571-578
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• 2024

The bistable thin cylindrical shell is developable structure with the ability to transition between its two stable configurations. This structure offers significant potential applications due to its excellent deformability. In this paper, the composite thin cylindrical shell consisting of the composite layer and the piezoelectric layer was investigated. The material and geometric parameters of the shell were found to influence its stable characteristics. The analysis model of the composite thin cylindrical shell incorporating the piezoelectric layer was developed, and the expressions for its strain energy were derived. By applying the minimum energy principle, the impact of the electric field intensity on the bi-stable behaviors of the cylindrical shell was analyzed. The results showed that the shell exhibited the bistability only under the appropriate electric field strength. And the accuracy of the theoretical prediction was verified by simulation experiments. This study provides an important reference for the application of deployable structures.

• Structural Engineering and Mechanics
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• v.65 no.5
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• pp.505-511
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• 2018

Recently, a new foundation model called "Dynamic foundation model" was proposed for the dynamic analysis of structures on the foundation. This model includes a linear elastic spring, shear layer, viscous damping and the special effects of mass density parameter of foundation during vibration. However, the relationship of foundation property parameters with the experimental parameter of the influence of foundation mass also has not been established in previous research. Hence, the purpose of the paper presents a simple experimental model in order to establish relationships between foundation properties such as stiffness, depth of foundation and experimental parameter of the influence of foundation mass. The simple experimental model is described by a steel plate connected with solid rubber layer as a single degree of freedom system including an elastic spring connected with lumped mass. Based on natural circular frequencies of the experimental models determined from FFT analysis plots of the time history of acceleration data, the experimental parameter of the influence of foundation mass is obtained and the above relationships are also discussed.

• Structural Monitoring and Maintenance
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• v.7 no.3
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• pp.261-281
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• 2020

Civil structures may experience progressive deterioration and damage under environmental and operational conditions over their service life. Finite element (FE) model updating method is one of the most important approaches for damage identification in structures due to its capabilities in structural health monitoring. Although various damage detection approaches have been investigated on structures, there are limited studies on large-sized space structures. Thus, this paper aims to investigate the applicability and efficiency of sensitivity-based FE model updating framework for damage identification in large space structures from a distinct point of view. This framework facilitates modeling and model updating in large and geometric complicated space structures. Considering sensitivity-based FE model updating and vibration measurements, the discrepancy between acceleration response data in real damaged structure and hypothetical damaged structure have been minimized through adjusting the updating parameters. The feasibility and efficiency of the above-mentioned approach for damage identification has finally been demonstrated with two numerical examples: a flat double layer grid and a double layer diamatic dome. According to the results, this method can detect, localize, and quantify damages in large-scaled space structures very accurately which is robust to noisy data. Also, requiring a remarkably small number of iterations to converge, typically less than four, demonstrates the computational efficiency of this method.

• Computers and Concrete
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• v.32 no.3
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• pp.233-246
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• 2023

Accurate prediction of concrete compressive strength can minimize the need for extensive, time-consuming, and costly mixture optimization testing and analysis. This study attempts to enhance the prediction accuracy of compressive strength using stacking ensemble machine learning (ML) with feature engineering techniques. Seven alternative ML models of increasing complexity were implemented and compared, including linear regression, SVM, decision tree, multiple layer perceptron, random forest, Xgboost and Adaboost. To further improve the prediction accuracy, a ML pipeline was proposed in which the feature engineering technique was implemented, and a two-layer stacked model was developed. The k-fold cross-validation approach was employed to optimize model parameters and train the stacked model. The stacked model showed superior performance in predicting concrete compressive strength with a correlation of determination (R²) of 0.985. Feature (i.e., variable) importance was determined to demonstrate how useful the synthetic features are in prediction and provide better interpretability of the data and the model. The methodology in this study promotes a more thorough assessment of alternative ML algorithms and rather than focusing on any single ML model type for concrete compressive strength prediction.

• Journal of the Korean Ceramic Society
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• v.39 no.3
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• pp.233-239
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• 2002

Reflection properties of $SiO_2$/ITO (Indium Tin Oxide) thin films coated for electromagnetic shielding, anti-static and anti-reflection on the front surface in CRT were studied. The behavior of reflectance as a function of thickness of $SiO_2$/ITO was investigated and applied to theoretical anti0reflection model of double layers and three layers. As the thickness of ITO layer increased, the deviation from theoretical value increased because uniformity of film deteriorated by pore. Because of the effect of mixed layer of $SiO_2$ and ITO, experimental reflectance showed better acceptance to the three layer antireflection model of $SiO_2$/$SiO_2$+ITO/ITO than the two layer model. Based on the theoretical antireflection design, the double layer whose thickness of $SiO_2$ and ITO were 90, 65 nm, respectively appear 2.5% in reflectance at standard wavelength, 550 nm. This phenomenon was similar to theoretical reflectance in visual range.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.47-54
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• 2023

For Bengali music emotion classification, deep learning models, particularly CNN and RNN are frequently used. But previous researches had the flaws of low accuracy and overfitting problem. In this research, attention-based Conv1D and BiGRU model is designed for music emotion classification and comparative experimentation shows that the proposed model is classifying emotions more accurate. We have proposed a Conv1D and Bi-GRU with the attention-based model for emotion classification of our Bengali music dataset. The model integrates attention-based. Wav preprocessing makes use of MFCCs. To reduce the dimensionality of the feature space, contextual features were extracted from two Conv1D layers. In order to solve the overfitting problems, dropouts are utilized. Two bidirectional GRUs networks are used to update previous and future emotion representation of the output from the Conv1D layers. Two BiGRU layers are conntected to an attention mechanism to give various MFCC feature vectors more attention. Moreover, the attention mechanism has increased the accuracy of the proposed classification model. The vector is finally classified into four emotion classes: Angry, Happy, Relax, Sad; using a dense, fully connected layer with softmax activation. The proposed Conv1D+BiGRU+Attention model is efficient at classifying emotions in the Bengali music dataset than baseline methods. For our Bengali music dataset, the performance of our proposed model is 95%.

• Fire Science and Engineering
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• v.13 no.4
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• pp.20-29
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• 1999

This paper describes the smoke filling process of a fire field model based on a self-developed SMEP(Smoke Movement Estimating Program) code to the simulation of fire induced flows in the two types of atrium space containing a ceiling heat flux. The SMEP using PISO algorithm solves conservation equations for mass, momentum, energy and species, together with those for the modified k- epsilon turbulence model with buoyancy term. Compressibility is assumed and the perfect gas law is used. The results of the calculated upper-layer average temperature and smoke layer interface height has shown reasonable agreement compared with the zone models. The zone models used are the CFAST developed at the Building and Fire Research Laboratory NIST U.S.A. and the NBTC one-room of FIRECALC developed at CSIRO, Australia. The smoke layer interface heights that are important in fire safety were not as sensitive as the smoke layer temperature to the nature of ceiling heat flux condition.

• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.131-139
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• 2002

This study introduces a developed artificial neural networks(ANN) model as a more efficient and reliable prediction model in operating speed Prediction with the 85th percentile horizontal curve of two-way rural highway in the aspect of evaluating highway design consistency. On the assumption that the speed is decided by highway geometry features, total 30 survey sites were selected. Data include currie radius, curve length, intersection angle, sight distance, lane width, and lane of those sites and were used as input layer data of the ANN. The optimized model structure was drawn by number of unit of hidden layer, learning coefficient, momentum coefficient, and change in learning frequency in multi-layer a ANN model. To verify learning Performance of ANN, 30 survey sites were selected while data in obtained from the 20 cites were used as learning data and those from the remaining 10 sites were used as predictive data. As a result of statistical verification, the model D of 4 types of ANN was evaluated as the most similar model to the actual operating speed value: R2 was 85% and %RMSE was 0.0204.

• Wind and Structures
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• v.32 no.5
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• pp.471-485
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• 2021

Onshore wind turbines may experience substantially different wind loads depending on their working conditions, i.e. rotation velocity of rotor blades, incoming freestream wind velocity, pitch angle of rotor blades, and yaw angle of the wind-turbine tower. In the present study, aerodynamic loads acting on a horizontal axis wind turbine were accordingly quantified for the high tip speed ratio (TSR) at high yaw angles because these conditions have previously not been adequately addressed. This was analyzed experimentally on a small-scale wind-turbine model in a boundary layer wind tunnel. The wind-tunnel simulation of the neutrally stratified atmospheric boundary layer (ABL) developing above a flat terrain was generated using the Counihan approach. The ABL was simulated to achieve the conditions of a wind-turbine model operating in similar inflow conditions to those of a prototype wind turbine situated in the lower atmosphere, which is another important aspect of the present work. The ABL and wind-turbine simulation length scale factors were the same (S=300) in order to satisfy the Jensen similarity criterion. Aerodynamic loads experienced by the wind-turbine model subjected to the ABL simulation were studied based on the high frequency force balance (HFFB) measurements. Emphasis was put on the thrust force and the bending moment because these two load components have previously proven to be dominant compared to other load components. The results indicate several important findings. The loads were substantially higher for TSR=10 compared to TSR=5.6. In these conditions, a considerable load reduction was achieved by pitching the rotor blades. For the blade pitch angle at 90°, the loads were ten times lower than the loads of the rotating wind-turbine model. For the blade pitch angle at 12°, the loads were at 50% of the rotating wind-turbine model. The loads were reduced by up to 40% through the yawing of the wind-turbine model, which was observed both for the rotating and the parked wind-turbine model.

• Progress in Medical Physics
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• v.29 no.4
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• pp.101-105
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• 2018

In this paper, a neutron moderation system for boron neutron capture therapy (BNCT) based on a $^{252}Cf$ neutron source is proposed. Different materials have been studied in order to produce a high percentage of epithermal neutrons. A moderator with a construction mixture of $AlF_3$ and Al, three reflectors of $Al_2O_3$, BeO, graphite, and seven filters (Bi, Cu, Fe, Pb, Ti, a two-layer filter of Ti+Bi, and a two-layer filter of Ti+Pb) is considered. The MCNPX simulation code has been used to calculate the neutron and gamma flux at the output window of the neutronic system. The results show that the epithermal neutron flux is relatively high for four filters: Ti+Pb, Ti+Bi, Bi, and Ti. However, a layer of Ti cannot reduce the contribution of ${\gamma}$-rays at the output window. Although the neutron spectra filtered by the Ti+Bi and Ti+Pb overlap, a large fraction of neutrons (74.95%) has epithermal energy when the Ti+Pb is used as a filter. However, the percentages of the fast and thermal neutrons are 25% and 0.5%, respectively. The Bi layer provides a relatively low epithermal neutron flux. Moreover, an assembly configuration of 30% $AlF_3+70%$ Al moderator/$Al_2O_3$ reflector/a two-layer filter of Ti+Pb reduces the fast neutron flux at the output port much more than other assembly combinations. In comparison with a recent model suggested by Ghassoun et al., the proposed neutron moderation system provides a higher epithermal flux with a relatively low contamination of gamma rays.