• Journal of the Korea Society of Computer and Information
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• v.25 no.11
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• pp.27-40
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• 2020

In this paper, we investigate the correlation between the amount of English sentences that Korean English learners (L2ers) are exposed to and their sentence processing patterns by examining what Long Short-Term Memory (LSTM) language models (LMs) can learn about implicit syntactic relationship: that is, the filler-gap dependency. The filler-gap dependency refers to a relationship between a (wh-)filler, which is a wh-phrase like 'what' or 'who' overtly in clause-peripheral position, and its gap in clause-internal position, which is an invisible, empty syntactic position to be filled by the (wh-)filler for proper interpretation. Here to implement L2ers' English learning, we build LSTM LMs that in turn learn a subset of the known restrictions on the filler-gap dependency from English sentences in the L2 corpus that L2ers can potentially encounter in their English learning. Examining LSTM LMs' behaviors on controlled sentences designed with the filler-gap dependency, we show the characteristics of L2ers' sentence processing using the information-theoretic metric of surprisal that quantifies violations of the filler-gap dependency or wh-licensing interaction effects. Furthermore, comparing L2ers' LMs with native speakers' LM in light of processing the filler-gap dependency, we not only note that in their sentence processing both L2ers' LM and native speakers' LM can track abstract syntactic structures involved in the filler-gap dependency, but also show using linear mixed-effects regression models that there exist significant differences between them in processing such a dependency.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.370-376
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• 2001

When an adhesive joint is exposed to high environmental temperature, the tensile load capability of the adhesive joint decreases because the elastic modulus and failure strength of structural adhesive decrease. The thermo-mechanical properties of structural adhesive can be improved by addition of fillers to the adhesive. In this paper, the elastic modulus and failure strength of adhesives as well as the tensile load capability of tubular single lap adhesive joints were experimentally and theoretically investigated with respect to the volume fraction of filler (alumina) and the environmental temperature. Also the tensile modulus of the fille containing epoxy adhesive was predicted using a new equation which considers filler shape, filler content and environmental temperature. The tensile load capability of the adhesive joint was predicted by using the effective strain obtained from the finite element analysis and a new failure model, from which the relation between the bonding length and the crack length was developed with respect to the volume fraction of filler.

• Advances in Computational Design
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• v.3 no.3
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• pp.289-302
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• 2018

The use of optimum content of supplementary cementing materials (SCMs) such as limestone filler (LF) to blend with Portland cement has been resulted in many environmental and technical advantages, such as increase in physical properties, enhancement of sustainability in concrete industry and reducing $CO_2$ emission are well known. Artificial neural networks (ANNs) have been already applied in civil engineering to solve a wide variety of problems such as the prediction of concrete compressive strength. The feed forward back propagation (FFBP) algorithm and Tan-sigmoid transfer function were used for the ANNs training in this study. The training, testing and validation of data during the backpropagation training process yielded good correlations exceeding 97%. A parametric study was conducted to study the sensitivity of the developed model to certain essential parameters affecting the compressive strength of concrete. The effects and benefits of limestone filler on hardened properties of the concrete such as compressive strength were well established endorsing previous results in the literature. The results of this study revealed that the proposed ANNs model showed a high performance as a feasible and highly efficient tool for simulating the LF concrete compressive strength prediction.

• Design & Manufacturing
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• v.16 no.2
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• pp.46-52
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• 2022

As the consumer market in the eco-friendly vehicle industry grows, the demand for water pump in a electric car parts market. This study intend to propose a mathematical model that can verify the effect of improving thermal properties when a non-conductive cooling filler liquid is introduced into an electric vehicle water pump. Also, the pros and cons of the immersion cooling method and future development way were suggested by analyzing the cooling characteristics using on the derived analysis solution. Thermal characteristics analysis of electric water pump applied with non-conductive filler liquid was carried out, and the diffusion boundary condition in the motor body and the boundary condition the inside pump were expressed as a geometric model. As a result of analyzing the temperature change for the heat source of the natural convection method and the heat conduction method, the natural convection method has difficulty in dissipating heat because no decrease in temperature due to heat release was found even after 300 sec. Also, it can be seen that the heat dissipation effect was obtained even though the non-conductive filling liquid was applied at the 120 sec and 180 sec in the heat conduction method. It has proposed to minimize thermal embrittlement and lower motor torque by injecting a non-conductive filler liquid into the motor body and designing a partition wall thickness of 2.5 mm or less.

• Steel and Composite Structures
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• v.26 no.2
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• pp.139-150
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• 2018

In this paper, two kinds of buckling restrained braces (BRBs) are designed to improve the mechanical properties and fatigue life, the reserved gap and viscoelastic filler with high energy dissipation capacity are employed as the sliding element, respectively. The fatigue life of BRBs considering the effect of sliding element is predicted based on Manson-Coffin model. The property tests under different displacement amplitudes are carried out to evaluate the mechanical properties and fatigue life of BRBs. At last, the finite element analysis is performed to study the effects of the gap and viscoelastic filler on mechanical properties BRBs. Experimental and simulation results indicate that BRB employed with viscoelastic filler has a higher fatigue life and more stable mechanical property compared to BRB employed with gap, and the smaller reserved gap can more effectively improve the energy dissipation capacity of BRB.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2001.05a
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• pp.205-210
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• 2001

In this work, virtual material characterization of 3D orthogonal woven composites is performed to predict the elastic properties by a full scale FEA. To model the complex geometry of 3D orthogonal woven composites, an accurate unit structure is first prepared. The unit structure includes warp yarns, filler yarns, stuffer yams and resin regions and reveals the geometrical characteristics. For this virtual experiments by using finite element analysis, parallel multifrontal solver is utilized and the computed elastic properties are compared to available experimental results and the other analytical results. It is founded that a good agreement between material properties obtained from virtual characterization and experimental results. Using the method of this virtual material characterization, the effects of inconsistent filler yarn distribution on the in-plane shear modulus and filler yarn waviness on the transverse Young's modulus are investigated. Especially, the stiffness knockdown of 3D woven composite structures is simulated by virtual characterization. Considering these results, the virtual material characterization of composite materials can be used for designing the 3D complex composite structures and may supplement the actual experiments.

• Advances in nano research
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• v.7 no.6
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• pp.419-429
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• 2019

The effect of an increasing percentage of nanofiller (glass cenosphere) with Glass/Epoxy hybrid composite curved panels modeled mathematically using the multiscale concept and subsequent numerical eigenvalues of different geometrical configurations (cylindrical, spherical, elliptical, hyperboloid and flat) predicted in this research article. The numerical model of Glass/Epoxy/Cenosphere is derived using the higher-order polynomial type of kinematic theory in association with isoparametric finite element technique. The multiscale mathematical model utilized for the customized computer code for the evaluation of the frequency data. The numerical model validation and consistency verified with experimental frequency data and convergence test including the experimental elastic properties. The experimental frequencies of the multiscale nano filler-reinforced composite are recorded through the impact hammer frequency test rig including CDAQ-9178 (National Instruments) and LABVIEW virtual programming. Finally, the nano cenosphere filler percentage and different design associated geometrical parameters on the natural frequency data of hybrid composite structural configurations are illustrated through a series of numerical examples.

• Elastomers and Composites
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• v.55 no.4
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• pp.306-313
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• 2020

To investigate the reinforcing effects of functional fillers in nitrile rubber (NBR) materials, high-structure carbon black (HS45), coated calcium carbonate (C-CaCO3), silica (200MP), and multi-walled carbon nanotubes (MWCNTs) were used as functional filler, and carbon black (SRF) as a common filler were used for oil-resistant rubber. The curing and mechanical properties of HS45-, 200MP-, and MWCNT-filled NBR compounds were improved compared to those of the SRF-filled NBR compound. The reinforcing effect also increased with a decrease in the particle size of the fillers. The C-CaCO3-filled NBR compound exhibited no reinforcing effect with increasing filler concentration because of their large primary particle size (2 ㎛). The reinforcing behavior based on 100% modulus of the functional filler based NBR compounds was compared by using several predictive equation models. The reinforcing behavior of the C-CaCO3-filled NBR compound was in accordance with the Smallwood-Einstein equation whereas the 200MP- and MWCNT-filled NBR compounds fitted well with the modified Guth-Gold (m-Guth-Gold) equation. The SRF- and HS45-filled NBR compounds exhibited reinforcing behavior in accordance with the Guth-Gold and m-Guth-Gold equations, respectively, at a low filler content. However, the values of reinforcement parameter (100Mf/100Mu) of the SRF- and HS45-filled NBR compounds were higher than those determined by the predictive equation model at a high filler content. Because the chains of SRF composed of spherical filler particles are similarly changed to rod-like filler particles embedded in a rubber matrix and the reinforcement parameter rapidly increased with a high content of HS45, the higher-structured filler. The reinforcing effectiveness of the functional fillers was numerically evaluated on the basis of the effectiveness index (��SRF/��f) determined by the ratio of the volume fraction of the functional filler (��f) to that of the SRF filler (��SRF) at three unit of reinforcing parameter (100Mf/100Mu). On the basis of their effectiveness index, MWCNT-, 200MP-, and HS45-filled compounds showed higher reinforcing effectiveness of 420%, 70%, and 20% than that of SRF-filled compound, respectively whereas C-CaCO3-filled compound exhibited lower reinforcing effectiveness of -50% than that of SRF-filled compound.

• Journal of Welding and Joining
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• v.24 no.5
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• pp.67-73
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• 2006

Laser welding is suitable for welding to the aluminum alloy sheet. In order to apply the aluminum laser welding to production line, parameters should be optimized. In this study, the optimal welding condition was searched through the genetic algorithm in laser welding of AA5182 sheet with AA5356 filler wire. Second-order polynomial regression model to estimate the tensile strength model was developed using the laser power, welding speed and wire feed rate. Fitness function for showing the performance index was defined using the tensile strength, wire feed rate and welding speed which represent the weldability, product cost and productivity, respectively. The genetic algorithm searched the optimal welding condition that the wire feed rate was 2.7 m/min, the laser power was 4 kW and the welding speed was 7.95 m/min. At this welding condition, fitness function value was 137.1 and the estimated tensile strength was 282.2 $N/mm^2$.

• Carbon letters
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• v.11 no.4
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• pp.325-331
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• 2010

This study investigates the effect of filler content (wt%), presence of interphase and agglomerates on the effective Young's modulus of polypropylene (PP) based nanocomposites reinforced with exfoliated graphite nanoplatelets ($xGnP^{TM}$) and carbon nanotubes (CNTs). The Young's modulus of the composites is determined using tensile testing based on ASTM D638. The reinforcement/polymer interphase is characterized in terms of width and mechanical properties using atomic force microscopy which is also used to investigate the presence and size of agglomerates. It is found that the interphase has an average width of ~30 nm and modulus in the range of 5 to 12 GPa. The Halpin-Tsai micromechanical model is modified to account for the effect of interphase and filler agglomerates and the model predictions for the effective modulus of the composites are compared to the experimental data. The presented results highlight the need of considering various experimentally observed filler characteristics such as agglomerate size and aspect ratio and presence and properties of interphase in the micromechanical models in order to develop better design tools to fabricate multifunctional polymer nanocomposites with engineered properties.