• 대한기계학회논문집A
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• 제35권10호
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• pp.1145-1153
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• 2011

본 연구의 목적은 극저온 열처리를 통해 Al6061 의 열처리 잔류응력을 제거하는 것이다. 이를 위해 유한요소해석을 이용하여 열처리 잔류응력을 예측하였으며, 열처리 조건에 따른 각 단계별 대류 열전달계수를 T6 와 극저온 열처리 실험을 수행하여 결정하였다. 예측된 잔류응력 결과는 X 선회절법(XRD)으로 측정된 잔류응력 결과와 비교하여 유한요소해석 결과의 타당성을 확인하였다. 또한 T6 와 극저온 열처리에 대해 각각 전기 전도도와 경도를 측정하여 기계적 특성을 평가하고 TEM 관찰과 XRD 회절 분석을 통해 석출물의 크기 및 성분을 파악하였다. 이를 통해 Al6061 의 T6 열처리와 비교하여 극저온 열처리를 적용함에 따른 잔류응력, 기계적 특성 및 미세조직변화를 조사하였다.

• Composites Research
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• 제36권6호
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• pp.441-447
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• 2023

최근 경량 소재에 대한 수요 증가로 기존 금속과 복합재간 접합 관심이 지대하다. 리벳팅과 같은 볼트 체결인 기계적 결합의 경우 응력 집중, 균열 및 박리가 발생함에 따라 접착제를 사용한 화학적 결합이 주목받고 있다. 본 논문에서는 접착제의 접합강도 향상을 위해 레이저 및 플라즈마 표면처리를 진행하였으며, 이에 대한 접착특성을 평가하고자 한다. 접합강도 실험을 위해 흔히 자동차용 소재로 사용되는 탄소섬유강화플라스틱(CFRP), CR340(Steel)과 Al6061(Aluminum)을 실험 소재로 선정해 레이저 및 플라즈마 표면처리를 진행 후 단축전단강도를 측정하였다. 플라즈마 표면처리 후 CFRP-CR340 및 CFRP-Al6061 이종소재 시편에서 각각 접합강도가 7.3% 및 39.2% 향상되었다. CR340-Al6061 시편은 레이저 표면처리에서 기준 시편대비 56.2% 증가하였다. 플라즈마 표면처리 후 표면자유에너지(SFE)가 향상되었는데 이는 화학반응 메커니즘을 통해 손상을 최소화해 접합강도 향상을 나타낸 것으로 사료된다. 레이저 표면처리는 물리적 표면처리로 거친 접합 표면 생성으로 인해 mechanical interlocking 효과로 인해 접착 강도가 향상된 것으로 사료된다. 본 연구를 토대로 실제 구조물 파손의 대표적인 원인인 피로파손을 예방하기 위해 장기 피로시험을 진행 할 예정이다.

• 한국재료학회지
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• 제29권6호
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• pp.392-397
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• 2019

A cold roll-bonding process is applied to fabricate an AA6061/AA5052/AA6061 three-layer clad sheet. Two AA6061 and one AA5052 sheets of 2 mm thickness, 40 mm width, and 300 mm length are stacked, with the AA5052 sheet located in the center. After surface treatment such as degreasing and wire brushing, sample is reduced to a thickness of 1.5 mm by multi-pass cold rolling. The rolling is performed at ambient temperature without lubricant using a 2-high mill with a roll diameter of 400 mm at rolling speed of 6.0 m/sec. The roll bonded AA6061/AA5052/AA6061 complex sheet is then hardened by natural aging(T4) and artificial aging(T6) treatments. The microstructures of the as-roll bonded and age-hardened Al complex sheets are revealed by optical microscopy; the mechanical properties are investigated by tensile testing and hardness testing. After rolling, the roll-bonded AA6061/AA5052/AA6061 sheets show a typical deformation structure in which grains are elongated in the rolling direction. However, after T4 and T6 aging treatment, there is a recrystallization structure consisting of coarse equiaxed grains in both AA5052 and AA6061 sheets. The as roll-bonded specimen shows a sandwich structure in which an AA5052 sheet is inserted into two AA6061 sheets with higher hardness. However, after T4 and T6 aging treatment, there is a different sandwich structure in which the hardness of the upper and lower layers of the AA6061 sheets is higher than that of the center of the AA5052 sheet. The strength values of the T4 and T6 age-treated specimens are found to increase by 1.3 and 1.4 times, respectively, compared to that value of the starting material.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2009년도 추계학술대회 논문집
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• pp.447-448
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• 2009

• 한국분말재료학회지
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• 제16권3호
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• pp.209-216
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• 2009

A composite of rapidly solidified Al-6061 alloy powder with graphite particle reinforcements was prepared by ball milling and subsequent hot extrusion. The microstructure and mechanical properties of these composites were investigated as a function of milling time. With increasing milling time, the gas atomized initially and spherical powders became elongated with a maximum aspect ratio after milling for 30 h. Then, refinement and spheroidization were achieved by further milling to 70 h with a homogeneous and fine dispersion of graphite particles forming between the matrix alloy layers. The best compression and wear properties were obtained in the powder milled for 70 h, associated with the increased fine and homogeneous distribution of graphite particles in the aluminum alloy matrix.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 2010년도 춘계학술발표대회 초록집
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• pp.42-42
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• 2010

알루미늄 합금은 질량 대비 강도가 우수하고 내식성 및 저온 특성이 양호하여 구조재로서 널리 사용되고 있다. 또한 그 사용 추세가 점점 증가 하고 있으며 알루미늄 합금의 용접을 위해 현재까지 다양한 용접 공정이 적용되었다. 일반적으로 GMAW, GTAW 등의 아크 용접과 박판의 경우 저항 점용접, 그 외의 $CO_2$ laser, Nd:YAG laser와 같은 고밀도 에너지 용접 공정에 의한 연구 결과들이 많이 발표 되었다. 하지만 알루미늄 합금의 특성 상 용접부에 기공과 균열과 같은 결함들이 각 공정에서 많이 발생하며 이러한 결함을 감소시키기 위한 용접기술에 관해 많은 연구가 진행되고 있다. 본 연구에서는 GMAW, Plasma-GMAW 공정을 적용하여 알루미늄 합금의 용접특성을 비교하였다. 알루미늄 합금 Al 5052, Al 6061 4mm 두께 모재에 대해 BOP(Bead On Plate) 용접실험을 실시하였으며 생산성 측면에서 각 공정에 따라 완전 용입 시 최대 용접 속도를 측정하여 비교하였다. 용접 품질 측면에서는 비드 표면 및 단면을 검사하고 인장시험을 수행하였으며, 용접 기공과 균열을 X-ray 촬영을 통해 비교하였다. 또한 고속카메라 촬영을 통해 용접 중 플라즈마로 인한 산화막 제거 효과를 확인하고 각 공정별 용접 시작부의 아크 안정성을 평가하였다. 인장시험 결과 모든 모드에서 모재에서 파단됨을 확인 하였고, Plasma-GMAW 공정의 경우 플라즈마의 예열효과로 인하여 GMAW 보다 완전용입 기준 용접속도가 빨랐으며, 청정작용도 우수한 것으로 확인되었다.

• 한국생산제조학회지
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• 제25권6호
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• pp.401-409
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• 2016

The formation of micro-burrs in micro-milling processes causes several problems related to productivity and surface integrity. It should be minimized and suppressed by effective monitoring of the cutting conditions. This paper presents the correlation between the micro-burr length and cutting signals in the micro-milling process of an Al alloy (Al6061-T6). The acoustic emission (AE) signals and cutting force signals are acquired during the experiments. The characteristics of the cutting signals are obtained by analyzing the AE root mean square value and resultant cutting force. In addition, the micro-burr length is measured according to the cutting conditions by analyzing a scanning electron microscopy image of the machined surface. The results of this study can be used to enhance the surface quality of micro parts.

• 소성∙가공
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• 제31권4호
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• pp.229-239
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• 2022

Convolution Neural Network(CNN) is a class of deep learning algorithms and can be used for image analysis. In particular, it has excellent performance in finding the pattern of images. Therefore, CNN is commonly applied for recognizing, learning and classifying images. In this study, the surface defect classification performance of Al 6061 extruded material using CNN-based algorithms were compared and evaluated. First, the data collection criteria were suggested and a total of 2,024 datasets were prepared. And they were randomly classified into 1,417 learning data and 607 evaluation data. After that, the size and quality of the training data set were improved using data augmentation techniques to increase the performance of deep learning. The CNN-based algorithms used in this study were VGGNet-16, VGGNet-19, ResNet-50 and DenseNet-121. The evaluation of the defect classification performance was made by comparing the accuracy, loss, and learning speed using verification data. The DenseNet-121 algorithm showed better performance than other algorithms with an accuracy of 99.13% and a loss value of 0.037. This was due to the structural characteristics of the DenseNet model, and the information loss was reduced by acquiring information from all previous layers for image identification in this algorithm. Based on the above results, the possibility of machine vision application of CNN-based model for the surface defect classification of Al extruded materials was also discussed.

• Corrosion Science and Technology
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• 제9권1호
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• pp.48-55
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• 2010

The many vessels are built with FRP(Fiber-Reinforced Plastic) material for small boats and medium vessels. However, FRP is impossible to be used for recyclable material owing to environmental problems and causes large proportion of collision accidents because radar reflection wave is so weak that large vessels could not detect FRP ships during the sailing. Hence, Al alloy comes into the spotlight to solve these kinds of problems as a new-material for next generation instead of FRP. Al alloy ships are getting widely introduced for fish and leisure boats to save fuel consumption due to lightweight. In this study, it was selected 6061-T6 Al alloy which are mainly used for Al-ships and carried out various electrochemical experiment such as potential, anodic/cathodic polarization, Tafel analysis, potentiostatic experiment and surface morphologies observation after potentiostatic experiment for 1200 sec by using the SEM equipment to evaluate optimum corrosion protection potential in sea water. It is concluded that the optimum corrosion protection potential range is -1.4 V ~ -0.7 V(Ag/AgCl) for 6061-T6 Al alloy, in the case of application of ICCP(Impressed current cathodic protection), which was shown the lowest current density at the electrochemical experiment and good specimen surface morphologies after potentiostatic experiment for Al-Mg-Si(6061-T6) Al alloy in seawater environment.

• Journal of Welding and Joining
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• 제20권4호
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• pp.534-537
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• 2002

In the various industry such as shipbuilding and automobile, etc., Al-alloys are used to reduce weight and improve economical efficiency, and they are mainly utilized in the process of Friction Stir Welding (FSW). A number of studies have been carried out on the metallurgical characteristics of friction stir welding In Al-alloys. However, research on the thermal behavior of FSW by using numerical analysis is not sufficient in the domestic and abroad. In this paper, therefore, numerical simulation was used to find out thermal behaviour of FSW by finite element method. We considered heat source that occurred by friction between tool shoulder including pin and base metal. To confirm the result of simulation, macrostructure is examined and compared after welding. The result of numerical simulation shows that Al-alloy is welded under a melting point of Al around pin by FSW.