• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.3
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• pp.266-281
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• 2017

Hydroelastic interactions of a deformable floating body with random waves are investigated in time domain. Both hydroelastic motion and structural dynamics are solved by expansion of elastic modes and Fourier transform for the random waves. A direct and efficient structural analysis in time domain is developed. In particular, an efficient way of obtaining distributive loads for the hydrodynamic integral terms including convolution integral by using Fubini theory is explained. After confirming correctness of respective loading components, calculations of full distributions of loads in random waves are expedited by reformulating all the body loading terms into distributed forms. The method is validated by extensive convergence tests and comparisons against the counterparts of the frequency-domain analysis. Characteristics of motion/deformation responses and stress resultants are investigated through a parametric study with varying bending rigidity and types of random waves. Relative contributions of componential loads are identified. The consequence of elastic-mode resonance is underscored.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2000.11a
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• pp.280-288
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• 2000

In this study, flow factors are evaluated in terms of kurtosis using random rough surface generated numerically. As h/$\sigma$become large øx, øy, øfp approach to 1 and øs, øfs to 0 asymptotically regardless of kurtosis. øx, øy, øfp increase with increasing kurtosis in the mixed lubrication regime. øs, øfs is associated with an additional flow transport due to the combined effect of sliding and roughness. As h/$\sigma$ decreases øs, øfs increase up to a certain point, and then decrease toward zero. This behavior can be attributed to the increasing number of contacts in the mixed lubrication regime. øx in the presence of elastic deformation on the surface is larger than øx in the absence of it because local film thickness( h$\_$T/) increases by elastic deformation.

• Advances in aircraft and spacecraft science
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• v.4 no.5
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• pp.585-611
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• 2017

This article covenants with the post buckling witticism of carbon nanotube reinforced composite (CNTRC) beam supported with an elastic foundation in thermal atmospheres with arbitrary assumed random system properties. The arbitrary assumed random system properties are be modeled as uncorrelated Gaussian random input variables. Unvaryingly distributed (UD) and functionally graded (FG) distributions of the carbon nanotube are deliberated. The material belongings of CNTRC beam are presumed to be graded in the beam depth way and appraised through a micromechanical exemplary. The basic equations of a CNTRC beam are imitative constructed on a higher order shear deformation beam (HSDT) theory with von-Karman type nonlinearity. The beam is supported by two parameters Pasternak elastic foundation with Winkler cubic nonlinearity. The thermal dominance is involved in the material properties of CNTRC beam is foreseen to be temperature dependent (TD). The first and second order perturbation method (SOPT) and Monte Carlo sampling (MCS) by way of CO nonlinear finite element method (FEM) through direct iterative way are offered to observe the mean, coefficient of variation (COV) and probability distribution function (PDF) of critical post buckling load. Archetypal outcomes are presented for the volume fraction of CNTRC, slenderness ratios, boundary conditions, underpinning parameters, amplitude ratios, temperature reliant and sovereign random material properties with arbitrary system properties. The present defined tactic is corroborated with the results available in the literature and by employing MCS.

• Structural Engineering and Mechanics
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• v.27 no.2
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• pp.199-222
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• 2007

Composite laminated structures supported on elastic foundations are being increasingly used in a great variety of engineering applications. Composites exhibit larger dispersion in their material properties compared to the conventional materials due to large number of parameters associated with their manufacturing and fabrication processes. And also the dispersion in elastic foundation stiffness parameter is inherent due to inaccurate modeling and determination of elastic foundation properties in practice. For a better modeling of the material properties and foundation, these are treated as random variables. This paper deals with effects of randomness in material properties and foundation stiffness parameters on the free vibration response of laminated composite plate resting on an elastic foundation. A $C^0$ finite element method has been used for arriving at an eigen value problem. Higher order shear deformation theory has been used to model the displacement field. A mean centered first order perturbation technique has been employed to handle randomness in system properties for obtaining the stochastic characteristic of frequency response. It is observed that small amount of variations in random material properties and foundation stiffness parameters significantly affect the free vibration response of the laminated composite plate. The results have been compared with those available in the literature and an independent Monte Carlo simulation.

• Advances in aircraft and spacecraft science
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• v.3 no.4
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• pp.471-502
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• 2016

This paper presents the dynamic instability analysis of un-damped elastically supported piezoelectric functionally graded (FG) beams subjected to in-plane static and dynamic periodic thermomechanical loadings with uncertain system properties. The elastic foundation model is assumed as one parameter Pasternak foundation with Winkler cubic nonlinearity. The piezoelectric FG beam is subjected to non-uniform temperature distribution with temperature dependent material properties. The Young's modulus and Poison's ratio of ceramic, metal and piezoelectric, density of respective ceramic and metal, volume fraction exponent and foundation parameters are taken as uncertain system properties. The basic nonlinear formulation of the beam is based on higher order shear deformation theory (HSDT) with von-Karman strain kinematics. The governing deterministic static and dynamic random instability equation and regions is solved by Bolotin's approach with Newmark's time integration method combined with first order perturbation technique (FOPT). Typical numerical results in terms of the mean and standard deviation of dynamic instability analysis are presented to examine the effect of slenderness ratios, volume fraction exponents, foundation parameters, amplitude ratios, temperature increments and position of piezoelectric layers by changing the random system properties. The correctness of the present stochastic model is examined by comparing the results with direct Monte Caro simulation (MCS).

• Tribology and Lubricants
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• v.17 no.3
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• pp.236-243
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• 2001

In this study, flow factors are evaluated in terms of kurtosis using random rough surface generated numerically. As h/$\sigma$become large ø$\sub$x/, ø$\sub$y/, ø$\sub$fp/, approach to 1 and ø$\sub$s/, ø$\sub$fs/ to 0 asymptotically regardless of kurtosis. ø$\sub$x/, ø$\sub$y/, ø$\sub$fp/ increase with increasing kurtosis in the mixed lubrication regime. ø$\sub$s/, ø$\sub$fs/ is associated with an additional flow transport due to the combined effect of sliding and roughness. As h/$\sigma$ decreases ø$\sub$s/, ø$\sub$fs/ increase up to a certain point, and then decrease toward zero. This behavior can be attributed to the increasing number of contacts in the mixed lubrication regime. ø$\sub$x/ in the presence of elastic deformation on the surface is larger than ø$\sub$x/ in the absence of it because local film thickness(h$\sub$T/) increases by elastic deformation.

• Smart Structures and Systems
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• v.29 no.1
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• pp.1-16
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• 2022

Despite recent breakthroughs in deep learning and computer vision fields, the pixel-wise identification of tiny objects in high-resolution images with complex disturbances remains challenging. This study proposes a modified U-net for tiny crack segmentation in real-world steel-box-girder bridges. The modified U-net adopts the common U-net framework and a novel Self-Attention-Self-Adaption (SASA) neuron as the fundamental computing element. The Self-Attention module applies softmax and gate operations to obtain the attention vector. It enables the neuron to focus on the most significant receptive fields when processing large-scale feature maps. The Self-Adaption module consists of a multiplayer perceptron subnet and achieves deeper feature extraction inside a single neuron. For data augmentation, a grid-based crack random elastic deformation (CRED) algorithm is designed to enrich the diversities and irregular shapes of distributed cracks. Grid-based uniform control nodes are first set on both input images and binary labels, random offsets are then employed on these control nodes, and bilinear interpolation is performed for the rest pixels. The proposed SASA neuron and CRED algorithm are simultaneously deployed to train the modified U-net. 200 raw images with a high resolution of 4928 × 3264 are collected, 160 for training and the rest 40 for the test. 512 × 512 patches are generated from the original images by a sliding window with an overlap of 256 as inputs. Results show that the average IoU between the recognized and ground-truth cracks reaches 0.409, which is 29.8% higher than the regular U-net. A five-fold cross-validation study is performed to verify that the proposed method is robust to different training and test images. Ablation experiments further demonstrate the effectiveness of the proposed SASA neuron and CRED algorithm. Promotions of the average IoU individually utilizing the SASA and CRED module add up to the final promotion of the full model, indicating that the SASA and CRED modules contribute to the different stages of model and data in the training process.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.1
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• pp.41-51
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• 2004

FRP re-bar in concrete structures could be used as a substitute of steel re-bars for that cases in which aggressive environment produce high steel corrosion, or lightweight is an important design factor, or transportation cost increase significantly with the weight of the materials. But FRP fibers have only linearly elastic stress-strain behavior; whereas, steel re-bar has linear elastic behavior up to the yield point followed by large plastic deformation and strain hardening. Thus, the current FRP re-bars are not suitable concrete reinforcement where a large amount of plastic deformation prior to collapse is required. The main objectives of this study in to evaluate the tensile behavior and the fracture mode of hybrid FRP re-bar. Fracture mode of hybrid FRP re-bar is unique. The only feature common to the failure of the hybrid FRP re-bars and the composite is the random fiber fracture and multilevel fracture of sleeve fibers, and the resin laceration behavior in both the sleeve and the core areas. Also, the result of the tensile and interlaminar shear stress test results of hybrid FRP re-bar can provide its excellent tensile strength-strain and interlaminar stress-strain behavior.

• Structural Engineering and Mechanics
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• v.84 no.5
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• pp.605-618
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• 2022

Glass fiber reinforced polymer (GFRP) elastic gridshells consist of long continuous GFRP tubes that form elastic deformations. In this paper, a method for the form-finding of gridshell structures is presented based on the interpretable machine learning (ML) approaches. A comparative study is conducted on several ML algorithms, including support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), AdaBoost, XGBoost, category boosting (CatBoost), and light gradient boosting machine (LightGBM). A numerical example is presented using a standard double-hump gridshell considering two characteristics of deformation as objective functions. The combination of the grid search approach and k-fold cross-validation (CV) is implemented for fine-tuning the parameters of ML models. The results of the comparative study indicate that the LightGBM model presents the highest prediction accuracy. Finally, interpretable ML approaches, including Shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions of the ML model since it is essential to understand the effect of various values of input parameters on objective functions. As a result of interpretability approaches, an optimum gridshell structure is obtained and new opportunities are verified for form-finding investigation of GFRP elastic gridshells during lifting construction.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.10
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• pp.784-789
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• 2011

A linear spring model, where the interactions among atoms are assumed to be isotropic and elastic, is employed for the study of non-polar optical phonon scattering in the valence band of alloy semiconductors. The force equations of n atoms are used in the spring model for the consideration of the random distribution of constituent atoms in an alloy semiconductor. When the number of atoms in a unit cell is assumed to be two based on the experimental result, the optical deformation potent is valid for compound semiconductors as well as alloy semiconductors.