• Journal of Auto-vehicle Safety Association
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• v.15 no.1
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• pp.55-62
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• 2023

In this study, a chest deflection is predicted by introducing a deep learning technique with the results of the frontal impact of the USNCAP conducted for 110 car models from MY2018 to MY2020. The 120 data are divided into training data and test data, and the training data is divided into training data and validation data to determine the hyperparameters. In this process, the deceleration data of each vehicle is averaged in units of 10 ms from crash pulses measured up to 100 ms. The performance of the deep learning model is measured by the indices of the mean squared error and the mean absolute error on the test data. A DNN (Deep Neural Network) model can give different predictions for the same hyperparameter values at every run. Considering this, the mean and standard deviation of the MSE (Mean Squared Error) and the MAE (Mean Absolute Error) are calculated. In addition, the deep learning model performance according to the inclusion of CVW (Curb Vehicle Weight) is also reviewed.

• Structural Engineering and Mechanics
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• v.73 no.6
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• pp.715-724
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• 2020

The influence on flexural strength of Glass/Epoxy laminated composite curved panels of different geometries (cylindrical, spherical, elliptical, hyperboloid and flat) due to inclusion of nano cenosphere filler examined in this research article. The deflection responses of the hybrid structure are evaluated numerically using the isoparametric finite element technique and modelled mathematically via higher-order displacement structural kinematics. To predict the deflection values, a customised in-house computer code in MATLAB environment is prepared using the higher-order isoparametric formulation. Subsequently, the numerical model validity has been established by comparing with those of available benchmark solution including the convergence characteristics of the finite element solution. Further, a few cenosphere filled hybrid composite are prepared for different volume fractions for the experimental purpose, to review the propose model accuracy. The experimental deflection values are compared with the finite element solutions, where the experimental elastic properties are adopted for the computation. Finally, the effect of different variable design dependent parameter and the percentages of nano cenosphere including the geometrical shapes obtained via a set of numerical experimentation.

• Computers and Concrete
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• v.19 no.6
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• pp.631-639
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• 2017

This study experimentally investigated the flexural capacity of a concrete beam reinforced with a newly developed GFRP bar that overcomes the lower modulus of elasticity and bond strength compared to a steel bar. The GFRP bar was fabricated by thermosetting a braided pultrusion process to form the outer fiber ribs. The mechanical properties of the modulus of elasticity and bond strength were enhanced compared with those of commercial GFRP bars. In the four-point bending test results, all specimens failed according to the intended failure mode due to flexural design in compliance with ACI 440.1R-15. The effects of the reinforcement ratio and concrete compressive strength were investigated. Equations from the code were used to predict the deflection, and they overestimated the deflection compared with the experimental results. A modified model using two coefficients was developed to provide much better predictive ability, even when the effective moment of inertia was less than the theoretical $I_{cr}$. The deformability of the test beams satisfied the specified value of 4.0 in compliance with CSA S6-10. A modified effective moment of inertia with two correction factors was proposed and it could provide much better predictability in prediction even at the effective moment of inertia less than that of theoretical cracked moment of inertia.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.4
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• pp.694-704
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• 1988

A recursive parameter estimation scheme utilizing the variance perturbation method is applied to the workpiece deflection model during CNC turning process, in order to improve the cylindricity of slender workpiece. It features that it is based on exponentially weighted recursive least squares method with post-process measurement of finish surfaces at two locations and it does not require a priori knowledge on the time varying deflection model parameter. The measurements of finish surfaces by using two proximity sensors mounted face to face enable one to identify the straightness, guide-way, run-out eccentricity errors. Preliminary cutting tests show that the straightness error of the finish surface due to workpiece deflection during cutting is most dominant. Identifying the errors and recursive updating the parameter, the off-line control is carried out to compensate the workpiece deflection error, through single pass cutting. Experimental results show that the proposed method is superior to the conventional multi-pass cutting and the direct compensation control in cutting accuracy and efficiency.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.119-124
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• 1996

End milling operation is very important in machining precision components. Deterioration of surface roughness and surface geometry will cause more process for surface finishing. According to the feed rate and the cutting edge geometry, the cusp which is geometrically uncut surface is determined. To reduce the cost for dinishing operation after end milling, the cusp must be remaianed in small size as possible. Due to the cylindrical type of the end mill, tool deflection is one of the main problems in surface generation. The cutting resistance and the rigidity of the end mill will determine the size of tool deflection. One more important factor which deteriorate surface quality comes from the error in manufacturing end mills. Run-out of end mill which is the difference of the radius of each cutting edges will produce the difference of the cusp size in every rotation of end mill. These three major factors to the surface quality will be analized and the result will be compared with experimental ressult.

• International Journal of Highway Engineering
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• v.15 no.1
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• pp.95-102
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• 2013

PURPOSES: The existing method evaluating the existence of the hollows in concrete pavement does not consider the stiffness of pavement. In addition, the method uses unreasonable logic judging the hollow existence by the deflection caused by zero loading. In this study, the deflection of slab corner due to heavy weight deflectometer (HWD) was measured in concrete pavement sections where underground structures are located causing the hollows around them. METHODS: The modulus of subgrade reaction obtained by comparing the actual deflection of slab to the result of finite element analysis was calibrated into the composite modulus of subgrade reaction. The radius of relative stiffness was calculated, and the relationship between the ratio of HWD load to the radius of relative stiffness and the slab deflection was expressed as the curve of secondary degree. RESULTS: The trends of the model coefficients showing width and maximum value of the curve of secondary degree were analyzed by categorizing the pavement sections into three groups : hollows exist, additional investigation is necessary, and hollows do not exist. CONCLUSIONS: The results analyzed by the method developed in this study was compared to the results analyzed by existing method. The model developed in this study will be verified by analyzing the data obtained in other sections with different pavement structure and materials.

• Steel and Composite Structures
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• v.39 no.1
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• pp.21-33
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• 2021

This paper aims to improve the current state-of-the-art in long-term deflection prediction in steel-concrete composite beams. The efficiency of a time-dependent finite element model based on linear creep theory is verified with available experimental data. A parametric numerical study is then carried out, which focuses on the effects of concrete creep and/or shrinkage, ultimate shrinkage strain and reinforcing bars in the slab. The study shows that the long-term deformations in composite beams are dominated by concrete shrinkage and that a higher area of reinforcing bars leads to lower long-term deformations and steel stresses. The AISC model appears to overestimate the shrinkage-induced deflection. A modified ACI equation is proposed to quantify time-dependent deflections in composite beams. In particular, a modified reduction factor reflecting the influence of reinforcing bars and a coefficient reflecting the influence of ultimate shrinkage are introduced in the proposed equation. The long-term deflections predicted by this equation and the results of extensive numerical analyses are found to be in good agreement.

• Steel and Composite Structures
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• v.48 no.6
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• pp.625-639
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• 2023

In this paper, a Taguchi-based finite element method (FEM) has been proposed and implemented to assess optimal design parameters for minimum static deflection in laminated composite plate. An orthodox mathematical model (based on higher-order shear deformation plate theory and Green-Lagrange geometrical nonlinearity) has been used to compute the nonlinear central deflection values of laminated composite plates according to Taguchi design of experiment via a self-developed MATLAB computer code. The lay-up scheme, aspect ratio, thickness ratio and the support conditions of the laminated composite plate structure were designated as the governable design parameters. Analysis of variance (ANOVA) is used to investigate the effect of diverse control factors on the nonlinear static responses. Moreover, regression model is developed for predicting the desired responses. The ANOVA revealed that the lay-up scheme alongside the support condition plays vital role in minimizing the central deflection values of laminated composite plate under uniformly distributed load. The conformity test results of Taguchi analysis are also in good agreement with the numerical experimentation results.

• Steel and Composite Structures
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• v.48 no.4
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• pp.419-428
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• 2023

In this paper, dynamic and static bending of ball modelled by nanocomposite microbeam by nanoparticles seeing agglomeration is presented. The structural damping is considered by Kelvin-Voigt model. The agglomeration effects are assumed using Mori-Tanaka model. The football ball is modeled by third order shear deformation theory (TSDT). The motion equations are derived by principle of Hamilton's and energy method assuming size effects on the basis of Eringen theory. Using differential quadrature method (DQM) and Newmark method, the static and dynamic deflections of the structure are obtained. The effects of agglomeration and CNTs volume percent, damping of structure, nonlocal parameter, length and thickness of micro-beam are presented on the static and dynamic deflections of the nanocomposite structure. Results show that with increasing CNTs volume percent, the maximum dimensionless dynamic deflection is reduced about 17%. In addition, assuming CNTs agglomeration increases the dimensionless dynamic deflection about 14%. It is also found that with increasing the CNTs volume percent from 0 to 0.15, the static deflection is decreased about 3 times due to the enhance in the stiffness of the structure. In addition, with enhancing the nonlocal parameters, the dynamic deflection is increased about 3.1 times.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.143-152
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• 1997

The deflection of an end mill is very important in machining process and cutting simulation because it affects directly workpiece accuracy, cutting force, and chattering. In this study, the deflection of the end mill was studied both experimentally and by using finite element analysis. And the moment of inertia of cross sections of the helical end mill is calculated for the determination of the relation between geometry of radial cross section and rigidity of the tools. Using the Bernoulli-Euler beam theory and the concept of equivalent diameter, a deflection model is established, which includes most influences from tool geomety parameters. It was found that helix angle attenuates the rigidity of the end mill by the finite element analysis. As a result, the equivalent diameter is determined by tooth number, inscribed diameter ratio, cross sectional geometry and helix angle. Because the relation betweem equivalent diameter and each factor is nonlinear, neural network is used to decide the equivalent diameter. Input patterns and desired outputs for the neural network are obtained by FEM analysis in several case of end milling operations.