• Geomechanics and Engineering
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• 제15권1호
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• pp.631-643
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• 2018

The estimation of the strength and other mechanical parameters characterizing the tensile behavior of granites can play an important role in civil engineering tasks such as design, construction, rehabilitation and repair of existing structures. The purpose of this paper is to apply data mining techniques, such as multiple regression (MR), artificial neural networks (ANN) and support vector machines (SVM) to estimate the mechanical properties of granites. In a first phase, the mechanical parameters defining the complete tensile behavior are estimated based on the tensile strength. In a second phase, the estimation of the mechanical properties is carried out from different combination of the physical properties (ultrasonic pulse velocity, porosity and density). It was observed that the estimation of the mechanical properties can be optimized by combining different physical properties. Besides, it was seen that artificial neural networks and support vector machines performed better than multiple regression model.

• Computers and Concrete
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• 제32권6호
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• pp.595-606
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• 2023

Dune sand (DS) has been widely used as a partial replacement for regular sand in concrete construction. Therefore, investigating its mechanical properties is critical for the analysis and design of structural elements using DS as a construction material. This paper presents a comprehensive investigation of the mechanical properties of DS concrete, considering different replacement ratios and strength grades. Regression analysis is utilized to develop strength prediction models for different mechanical properties of DS concrete. The proposed models exhibit high calculation accuracy, with R² values of 0.996, 0.991, 0.982, and 0.989 for cube compressive strength, axial compressive strength, splitting tensile strength, and elastic modulus, respectively, and an error within ±20%. Furthermore, a stress-strain relationship specific to DS concrete is established, showing good agreement with experimental results. Additionally, nonlinear finite element analysis is performed on concrete-filled steel tube columns incorporating DS concrete, utilizing the established stress-strain relationship. The analytical and experimental results exhibit good agreement, confirming the validity of the proposed stress-strain relationship for DS concrete. Therefore, the findings presented in this paper provide valuable references for the design and analysis of structures utilizing DS concrete as a construction material.

• 대한기계학회논문집
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• 제10권4호
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• pp.519-528
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• 1986

본 연구에서는 우선 1차적으로 한국중공업에서 제조한 실제의 터어빈 회전자 축에서 시편을 채취하여 화력발전소 터어빈의 작동 온도에서의 크리이프 거동을 실험 하고, Larson-Miller 법 및 Orr-sherby-Dorn 법에 의하여 수명을 예상하엿으며 열처리 조건의 변화에 따른 크리이프 특성 변화를 고찰하였다.

• 대한가정학회지
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• 제39권11호
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• pp.223-232
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• 2001

This study, by explaining the relationship between mechanical properties and clothing formability, aims to propose functional data for tailoring performance of fabrics of good tailorability. The KES-FB system was used to measure factors of mechanical properties and also the technique of stepwise-block-regression method was applied to investigate relationship between functional properties and mechanical properties of men's shirks. As results of vasual inspection of men's shirts, it showed that good fabrics had higher value in the LT, bending properties, shear properties and RC than poor fabrics in Total Appearance Value(TAV). And finally, A formula was obtained for calculating the VIA of men's shirts from functional properties which were calculated from the mechanical properties.

• Structural Engineering and Mechanics
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• 제57권2호
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• pp.265-280
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• 2016

A NLFE model was proposed to investigate the mechanical behavior of short columns, cast using plain or fibrous lightweight aggregate concrete (LWAC), and subjected to elevated temperatures of up to $700^{\circ}C$. The model was validated, before its predictions were extended to study the effect of other variables, not studied experimentally. The three-dimensional NLFE model was developed using ANSYS software and involved rational simulation of thermal mechanical behavior of plain and fibrous LWAC as well as longitudinal and lateral steel reinforcement. The prediction from the NLFE model of columns' mechanical behavior, as represented by the stress-strain diagram and its characteristics, compared well with the experimental results. The predictions of the proposed models, considering wide range of lateral reinforcement ratios, confirmed the behaviors observed experimentally and stipulated the importance of steel confinement in preserving post-heating mechanical properties of plain and fibrous LWAC columns, being subjected to high temperature.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 추계학술대회 논문집
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• pp.146-151
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• 2003

Reduced Activation Ferritic/Martenstic (RAFs) are leading candidates for structural materials of D-T fusion reactor. One of The RAFs, JLF-1 (9Cr-2W-V, Ta) has been developed and proved to have good resistance against high-fluency neutrino irradiation and good phase stability. Recently, in order to clarify the strengthening mechanical at high temperature, a new scheme to improve high temperature mechanical properties is desired. Therefore, the creep properties and creep life prediction by Larson-Miller Parameter method for JLF-1 to be used for fusion reactor materials or other high temperature components were presented at the elevated temperatures of $500^{\circ}C$, $550^{\circ}C$, $600^{\circ}C$, $650^{\circ}C$ and $704^{\circ}C$. It was confirmed experimentally and quantitatively that a creep life predictive e벼ation at such various high temperatures was well derived by LMP.

• 대한기계학회논문집
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• 제18권6호
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• pp.1465-1473
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• 1994

This paper describes the development strategy and contents of a fatigue life evaluation system, FLEVA. The system is composed of 4 parts; material properties, load histories, cycle counting and life prediction. The cycle counting is based on the rain-flow counting method and peak counting method, and the life prediction is performed based on the linear damage rule. Material properties(static, fatigue) are also provided as a database obtained by a computer aided test system. Case study is performed to verify the developed program.

• 한국가스학회지
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• 제25권2호
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• pp.64-71
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• 2021

수소연료전지자동차를 비롯한 자동차 분야에서 성형 가공성과 기계적 특성이 우수한 고분자 복합수지에 대한 연구는 특정 기계적 특성을 갖춘 재료의 설계지원을 위한 Computer-Aided Engineering (CAE)으로 확대되고 있다. CAE 자동화는 소재의 기계적 특성 및 거동 예측이 선행되어야 하는데, 고분자 복합수지의 기계적 물성 예측은 단일물질과 달리, 바탕재와 보강재 간의 관계로만 설명하기에는 물성 거동이 복잡하기에, 수식으로 설명하기 어렵다. 본 연구에서는 큰 소성 구간과 조성에 예민하여 예측이 어려웠던 고분자 복합수지의 조성에 따른 응력-변형률 선도를 데이터의 기계학습을 기반으로 예측하였다. 개발모델은 바탕재, 보강재 종류 및 조성간의 복잡한 상관관계를 찾아, 학습한 시험 데이터가 없는 조건에서도 전체 응력-변형률 곡선을 의미있게 예측한다. 학습하지 않은 조성과 구성에 대해서도 고분자 복합수지의 기계적 특성을 예측하는 개발 모델을 기반으로 향후 소재 설계 AI 시스템을 완성할 수 있을 것으로 기대한다.

• 반도체디스플레이기술학회지
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• 제11권1호
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• pp.49-54
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• 2012

There have been plenty of difficulties because properties of Alq3 are unable to acquire in a process of manufacture of OLED. In this paper it will predict a viscosity of Alq3 through DSMC technique and suggest the way regarding a study to estimate properties of material through the computer simulation. There could generate errors of a simulation process in a vacuum deposition process since the properties of material that is used in a high-degree vacuum environment are not secured. Therefore, we would like to propose the new methods that can not only predict properties of a molecular unit but also raise an accuracy of simulation process by forecasting properties of Alq3.

• 소성∙가공
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• 제32권6호
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• pp.367-375
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• 2023

Composite materials, known for their excellent mechanical properties and lightweight characteristics, are applied in various engineering fields. Recently, efforts have been made to develop an automotive battery protection panel using a plain-woven composite composed of glass fiber and polypropylene to reduce the weight of automobiles. However, excessive warpage occurs during the GF/PP compression molding process, which makes car assembly challenging. This study aims to develop a model that predicts the warpage during the compression molding process. Obtaining out-of-plane properties such as elastic or shear modulus, essential for predicting warpages, is tricky. Existing mechanical methods also have limitations in calculating these properties for woven composite materials. To address this issue, finite element analysis is conducted using representative volume elements (RVE) for woven composite materials. A warpage prediction model is developed based on the estimated physical properties of GF/PP composite materials obtained through representative volume elements. This model is expected to be used for reducing warpages in the compression molding process.