• Structural Engineering and Mechanics
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• v.69 no.2
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• pp.155-162
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• 2019

It is very common to find an empirical formulation in an earthquake design code to calculate fundamental vibration period of a structural system. Fundamental vibration period or frequency is a key parameter to provide adequate information pertinent to dynamic characteristics and performance assessment of a structure. This parameter enables to assess seismic demand of a structure. It is possible to find an empirical formulation related to reinforced concrete structures, masonry towers and slender masonry structures. Calculated natural vibration frequencies suggested by empirical formulation in the literatures has not suits in a high accuracy to the case of rest of the historical masonry bridges due to different construction techniques and wide variety of material properties. For the listed reasons, estimation of fundamental frequency gets harder. This paper aims to present an empirical formulation through Mean Square Error study to find ambient vibration frequency of historical masonry bridges by using a non-linear regression model. For this purpose, a series of data collected from literature especially focused on the finite element models of historical masonry bridges modelled in a full scale to get first global natural frequency, unit weight and elasticity modulus of used dominant material based on homogenization approach, length, height and width of the masonry bridge and main span length were considered to predict natural vibration frequency. An empirical formulation is proposed with 81% accuracy. Also, this study draw attention that this accuracy decreases to 35%, if the modulus of elasticity and unit weight are ignored.

• Journal of Fashion Business
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• v.24 no.6
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• pp.1-17
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• 2020

This study investigated the perceptions, attitudes, and behaviors of potential consumers toward using 3D printers to create their personal clothes. An online survey and a series of Welch's t-tests and ANOVA were conducted to investigate the differences in demographic characteristics, prior experiences in 3D printing, and levels of need for uniqueness among the sub-groups. A multiple linear regression analysis was performed to test the relationships among variables of the modified Unified Theory of Acceptance and Use of Technology (UTAUT). There were significant differences in gender and prior experiences regarding the UTAUT of personal 3D printing. The need for uniqueness has a positive effect on consumers' intention to use 3D printing technology for designing personal clothes and perception of the price of the 3D printer used to create individual clothes is important. Positive relationships were found between UTAUT variables as well as the use and purchase intentions. This study analyzed the potential for popularization of 3D printing technology to create fashion items and explore consumer willingness to embrace and use personal fashion designs. The results of this study are expected to assist consumers, designers, retailers and marketers, and experts in 3D printing technology by providing insight into consumer awareness and acceptance of personalized 3D-printed fashion and products.

• Atmosphere
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• v.31 no.2
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• pp.171-183
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• 2021

The sensitivity of the extratropical jet to the stratospheric mean state is investigated by conducting a series of idealized numerical experiments using a dynamic-core general circulation model. When the polar stratosphere is forced to be cold, the extratropical jet, defined by the 850-hPa zonal wind, tends to shift poleward without much change in its intensity. The opposite is also true when the polar stratosphere becomes warm. This jet response, however, is not exactly linear. A poleward jet shift under a cold vortex is much weaker than an equatorward jet shift under a warm vortex. The jet intensity change is also larger under a warm vortex. This result indicates that the stratosphere-troposphere downward coupling is more efficient for the warm and weak polar vortex. This finding is consistent with a stronger downward coupling during stratospheric sudden warming than vortex intensification events in the Northern Hemisphere winter, possibly providing a clue to better understand the observed stratosphere-troposphere downward coupling.

• Bulletin of the Korean Chemical Society
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• v.12 no.2
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• pp.193-196
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• 1991

The $^{13}C-NMR$ shifts of a series of para-substituted $8-aryl-tricyclo[3.2.1.0^{2,7}]oct-8-yl$ and $9-aryl-tricyclo[3.3.1.0^{2,8}]-non-9-yl$ cations were measured in $FSO_3H/SO_2ClF\ at\-90^{\circ}$ in order to examine whether the ${\rho}^{C^+}$ values can be used as a measure of the geometric influence on the charge delocalization resulting from ${\rho}$ conjugation in rigid tricyclopropylcarbinyl cations. Plot of the ${\Delta}{\delta}^{C+} shifts against the ${\sigma}^{C+}$ constants revealed excellent linear correlation. The 8-aryl tricyclooctyl systems yielded a ${\rho}^{C+}$ value of -5.00 with r = 0.9962. Previous investigation of the 9-aryl-tricyclononyl systems gave a correlation coefficient of r = 0.9948 with a slope of ${\rho}^{C+}$ = -4.95. A fair parallelism exists between the results of $^{19}F-NMR $ studies and the change of ${\rho}^{C+}$ value in these cations. Consequently, it is established that the ${\rho}^{C+}$ value can be used to explain the mechanism of charge stabilization of the rigid cyclopropylcarbinyl cation such as tricyclo $[3.2.1.0^{2,7}]oct-8-yl$ cation.

• Bulletin of the Korean Chemical Society
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• v.6 no.6
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• pp.344-347
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• 1985

Perovskite type oxides of $SrTiO_3,SrZrO_3,and\;SrTi_{1-x}Zr_xO_3$ have been systematically synthesized at $1250^{\circ}C$and $1550^{\circ}C$ with specimens containing additions of up to x=0.9 of zirconium by solid state reactions and characterized by X-ray diffraction. X-ray diffraction studies showed that the compound $SrTi_{1-x}Zr_xO_3$ has cubic structure. The lattice paramters of $SrTi_{1-x}Zr_xO_3$ solid solutions obey the Vegard's law and fairly large increase in volume can acompany the formation of this solution with increasing Zr content(X). Assuming the lattice constants of perovskite type compounds $A(B_{1-x}B'_x)O_3$where $B_{1-x}B'_x$ is $Ti_{1-x}Zr_x$, to be a linear function of the ionic radii of B and B' ions, the disordered ion pair of $Ti^{4+}$and $Zr^{4+}$ was verified from the lattice constants of a series compounds varying x=0,0.05, 0.25, 0.5, 0.75, 0.9, and 1.0 with known isovalent pairs.

• Korean Journal of Metals and Materials
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• v.47 no.1
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• pp.7-12
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• 2009

The detailed quantitative microstructural data on the cracking of coarse constituent particles in 7075 (T651) series wrought Al-alloys have been studied using the utility of a novel digital image processing technique, where the particle cracks are generated due to monotonic loading. The microstructural parameters such as number density, volume fraction, size distribution, first nearest neighbor distribution, and two-point correlation function have been quantitatively characterized using the developed technique and such data are very useful to verify and study the theoretical models for the damage evolution and fracture of Al-alloys. The data suggests useful relationships for damage modeling such as a linear relationship between particle cracking and strain exists for the uniaxial tensile loading condition, where the larger particles crack preferentially.

• Korean Journal of Metals and Materials
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• v.47 no.10
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• pp.613-620
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• 2009

The Kachanov-Rabotnov (K-R) creep model was proposed to accurately model the long-term creep curves above $10^5$ hours of Alloy 617. To this end, a series of creep data was obtained from creep tests conducted under different stress levels at $950^{\circ}C$. Using these data, the creep constants used in the K-R model and the modified K-R model were determined by a nonlinear least square fitting (NLSF) method, respectively. The K-R model yielded poor correspondence with the experimental curves, but the modified K-R model provided good agreement with the curves. Log-log plots of ${\varepsilon}^{\ast}$-stress and ${\varepsilon}^{\ast}$-time to rupture showed good linear relationships. Constants in the modified K-R model were obtained as ${\lambda}$=2.78, and $k=1.24$, and they showed behavior close to stress independency. Using these constants, long-term creep curves above $10^5$ hours obtained from short-term creep data can be modeled by implementing the modified K-R model.

• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.295-317
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• 2020

Investigation of the stability of arch dam abutments is one of the most important aspects in the analysis of this type of dams. To this end, the Bakhtiari dam, a doubly curved arch dam having six wedges at each of its abutments, is selected. The seismic safety of dam abutments is studied through time history analysis using the design-based earthquake (DBE) and maximum credible earthquake (MCE) hazard levels. Londe limit equilibrium method is used to calculate the stability of wedges in abutments. The thrust forces are obtained using ABAQUS, and stability of wedges is calculated using the code written within MATLAB. Effects of foundation flexibility, grout curtain performance, vertical component of earthquake, nonlinear behavior of materials, and geometrical nonlinearity on the safety factor of the abutments are scrutinized. The results show that the grout curtain performance is the main affecting factor on the stability of the abutments, while nonlinear behavior of the materials is the least affecting factor amongst others. Also, it is resulted that increasing number of the contraction joints can improve the seismic stability of dam. A cap is observed on the number of joints, above which the safety factor does not change incredibly.

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.617-635
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• 2020

The purpose of this study is to discuss how to improve the maneuverability of lifting and diving for underwater vehicle's vertical motion. Therefore, to solve these problems, applied the 3-D numerical simulation, Taguchi's Design of Experiment (DOE), and intelligent parameter design methods, etc. We planned four steps as follows: firstly, we applied the 2-D flow simulation with NACA series, and then through the Taguchi's dynamic method to analyze the sensitivity (β). Secondly, take the data of pitching torque and total resistance from the Taguchi orthogonal array (L9), the ignal-to-noise ratio (SNR), and analysis each factorial contribution by ANOVA. Thirdly, used Radial Basis Function Network (RBFN) method to train the non-linear meta-modeling and found out the best factorial combination by Particle Swarm Optimization (PSO) and Weighted Percentage Reduction of Quality Loss (WPRQL). Finally, the application of the above methods gives the global optimum for multi-quality characteristics and the robust design configuration, including L/D is 9.4:1, the foreplane on the hull (Bow-2), and position of the sail is 0.25 Ls from the bow. The result shows that the total quality is improved by 86.03% in comparison with the original design.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.301-307
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• 2022

Energy consumption has grown alongside dramatic population increases. Statistics show that buildings in particular utilize a significant amount of energy, worldwide. Because of this, building energy prediction is crucial to best optimize utilities' energy plans and also create a predictive model for consumers. To improve energy prediction performance, this paper proposes a ResNet-LSTM model that combines residual networks (ResNets) and long short-term memory (LSTM) for energy consumption prediction. ResNets are utilized to extract complex and rich features, while LSTM has the ability to learn temporal correlation; the dense layer is used as a regression to forecast energy consumption. To make our model more robust, we employed Huber loss during the optimization process. Huber loss obtains high efficiency by handling minor errors quadratically. It also takes the absolute error for large errors to increase robustness. This makes our model less sensitive to outlier data. Our proposed system was trained on historical data to forecast energy consumption for different time series. To evaluate our proposed model, we compared our model's performance with several popular machine learning and deep learning methods such as linear regression, neural networks, decision tree, and convolutional neural networks, etc. The results show that our proposed model predicted energy consumption most accurately.