• 제목/요약/키워드: Construction Performance

검색결과 8,046건 처리시간 0.043초

소형 수소추진선박 기술 개발 및 실증 (The Technology Development and Substantiation of Small Hydrogen Powered Vessel)

  • 임재완;이세준;윤상진;임옥택
    • 한국수소및신에너지학회논문집
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    • 제34권6호
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    • pp.555-561
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    • 2023
  • In this study, we proposed a standard model for the design, construction and demonstration of the technology development and substantiation of small hydrogen powered vessel in order to respond to the alternative fuel-using vessel market that requires the use of low-carbon/carbon-free fuel as a greenhouse gas reduction measure. The hydrogen fuel cell-based electric propulsion system developed through this is optimized through performance and durability tests on the land-based test site (LBTS), and the electric propulsion system applied to this result is mounted on a small hydrogen propulsion vessel and operated. Simultaneously, through the digital twin technology between the LBTS and the hydrogen-propelled vessel on the sea, the technology that can predict and diagnose the problems that can occur in the electric propulsion system of the vessel is applied to carry out the empirical study of the hydrogen-propelled vessel. In addition, we propose a commercialization model by analyzing the economic feasibility of the demonstration vessel.

Multiple effects of nano-silica on the pseudo-strain-hardening behavior of fiber-reinforced cementitious composites

  • Hossein Karimpour;Moosa Mazloom
    • Advances in nano research
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    • 제15권5호
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    • pp.467-484
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    • 2023
  • Despite the significant features of fiber-reinforced cementitious composites (FRCCs), including better mechanical, fractural, and durability performance, their high content of cement has restricted their use in the construction industry. Although ground granulated blast furnace slag (GGBFS) is considered the main supplementary cementitious material, its slow pozzolanic reaction stands against its application. The addition of nano-sized mineral modifiers, including nano-silica (NS), is an alternative to address the drawbacks of using GGBFS. The main object of this empirical and numerical research is to examine the effect of NS on the strain-hardening behavior of cementitious composites; ten mixes were designed, and five levels of NS were considered. This study proposes a new method, using a four-point bending test to assess the use of nano-silica (NS) on the flexural behavior, first cracking strength, fracture energy, and micromechanical parameters including interfacial friction bond strength and maximum bridging stress. Digital image correlation (DIC) was used for monitoring the initiation and propagation of the cracks. In addition, to attain a deep comprehension of fiber/matrix interaction, scanning electron microscope (SEM) analysis was used. It was discovered that using nano-silica (NS) in cementitious materials results in an enhancement in the matrix toughness, which prevents multiple cracking and, therefore, strain-hardening. In addition, adding NS enhanced the interfacial transition zone between matrix and fiber, leading to a higher interfacial friction bond strength, which helps multiple cracking in the composite due to the hydrophobic nature of polypropylene (PP) fibers. The findings of this research provide insight into finding the optimum percent of NS in which both ductility and high tensile strength of the composites would be satisfied. As a concluding remark, a new criterion is proposed, showing that the optimum value of nano-silica is 2%. The findings and proposed method of this study can facilitate the design and utilization of green cementitious composites in structures.

MAGICal Synthesis: 반도체 패키지 이미지 생성을 위한 메모리 효율적 접근법 (MAGICal Synthesis: Memory-Efficient Approach for Generative Semiconductor Package Image Construction)

  • 창윤빈;최원용;한기준
    • 마이크로전자및패키징학회지
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    • 제30권4호
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    • pp.69-78
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    • 2023
  • 산업 인공지능의 발달과 함께 반도체의 수요가 크게 증가하고 있다. 시장 수요에 대응하기 위해 패키징 공정에서 자동 결함 검출의 중요성 역시 증가하고 있다. 이에 따라, 패키지의 자동 불량 검사를 위한 딥러닝 기반의 방법론들의 연구가 활발히 이루어 지고 있다. 딥러닝 기반의 모델은 학습을 위해서 대량의 고해상도 데이터를 필요로 하나, 보안이 중요한 반도체 분야의 특성상 관련 데이터의 공유 및 레이블링이 쉽지 않아 모델의 학습이 어려운 한계를 지니고 있다. 또한 고해상도 이미지를 생성하기 위해 상당한 컴퓨팅 자원이 요구되는데, 본 연구에서는 분할정복 접근법을 통해 적은 컴퓨팅 자원으로 딥러닝 모델 학습을 위한 충분한 양의 데이터를 확보하는 방법을 소개한다. 제안된 방법은 높은 해상도의 이미지를 분할하고 각 영역에 조건 레이블을 부여한 후, 독립적인 부분 영역과 경계를 학습시켜, 경계 손실이 일관적인 이미지를 생성하도록 유도한다. 이후, 분할된 이미지를 하나로 통합하여, 최종적으로 모델이 고해상도의 이미지를 생성하도록 구성하였다. 실험 결과, 본 연구를 통해 증강된 이미지들은 높은 효율성, 일관성, 품질 및 범용성을 보였다.

Effect of stud corrosion on stiffness in negative bending moment region of steel-concrete composite beams

  • Yulin Zhan;Wenfeng Huang;Shuoshuo Zhao;Junhu Shao;Dong Shen;Guoqiang Jin
    • Steel and Composite Structures
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    • 제48권1호
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    • pp.59-71
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    • 2023
  • Corrosion of the headed studs shear connectors is an important factor in the reduction of the durability and mechanical properties of the steel-concrete composite structure. In order to study the effect of stud corrosion on the mechanical properties in the negative moment region of steel-concrete composite beams, the corrosion of stud was carried out by accelerating corrosion method with constant current. Static monotonic loading was adopted to evaluate the cracking load, interface slip, mid-span deflection, and ultimate bearing capacity of four composite beams with varying corrosion rates of headed studs. The effect of stud corrosion on the stiffness of the composite beam's hogging moment zone during normal service stage was thoroughly examined. The results indicate that the cracking load decreased by 50% as the corrosion rate of headed studs increase to 10%. Meanwhile, due to the increase of interface slip and mid-span deflection, the bending stiffness dropped significantly with the same load. In comparison to uncorroded specimens, the secant stiffness of specimens with 0.5 times ultimate load was reduced by 25.9%. However, corrosion of shear studs had no obvious effect on ultimate bending capacity. Based on the experimental results and the theory of steel-concrete interface slip, a method was developed to calculate the bending stiffness in the negative bending moment region of composite beams during normal service stage while taking corrosion of headed studs into account. The validity of the calculation method was demonstrated by data analysis.

고위력 폭약의 화강암 내 장약공 폭발에 의한 지반진동 전파특성에 관한 연구 (Propagation Characteristics of Ground Vibration Caused by Blast Hole Explosion of High Explosives in Granite)

  • 김경규;신찬휘;김한림;양주석;배상호;윤경재;조상호
    • 화약ㆍ발파
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    • 제41권4호
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    • pp.29-40
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    • 2023
  • 암반발파는 광업, 터널공사, 지하 구조물 구축 등 다양한 분야에서 활용되고 있으며, 특히 지하공간의 활용이 증가하면서 암반발파 기술이 더 중요한 역할을 하고 있다. 암반발파 시 발파공에서 발생하는 발파공의 압력은 파쇄도, 발파진동 등에 직접적인 영향을 미치는 변수이며, 폭약의 성능 평가 및 발파 결과 예측에 있어서 가장 중요한 매개변수 중 하나이다. 이와 같은 발파공 압력은 몇몇 연구자들에 의해 연구가 수행된 바가 있지만, 폭약의 종류, 폭약량, 발파조건 등 실험조건으로 인하여 비교가 어려운 실정이다. 본 연구에서는 발파공 압력센서와 관측공 압력센서를 제작하여 단일공 발파 시 발파공과 관측공의 압력을 측정하였다. 실험결과를 바탕으로 발파공 주변 압력 전파특성과 발파진동 전파특성에 대해 고찰하였다.

Intelligent prediction of engineered cementitious composites with limestone calcined clay cement (LC3-ECC) compressive strength based on novel machine learning techniques

  • Enming Li;Ning Zhang;Bin Xi;Vivian WY Tam;Jiajia Wang;Jian Zhou
    • Computers and Concrete
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    • 제32권6호
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    • pp.577-594
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    • 2023
  • Engineered cementitious composites with calcined clay limestone cement (LC3-ECC) as a kind of green, low-carbon and high toughness concrete, has recently received significant investigation. However, the complicated relationship between potential influential factors and LC3-ECC compressive strength makes the prediction of LC3-ECC compressive strength difficult. Regarding this, the machine learning-based prediction models for the compressive strength of LC3-ECC concrete is firstly proposed and developed. Models combine three novel meta-heuristic algorithms (golden jackal optimization algorithm, butterfly optimization algorithm and whale optimization algorithm) with support vector regression (SVR) to improve the accuracy of prediction. A new dataset about LC3-ECC compressive strength was integrated based on 156 data from previous studies and used to develop the SVR-based models. Thirteen potential factors affecting the compressive strength of LC3-ECC were comprehensively considered in the model. The results show all hybrid SVR prediction models can reach the Coefficient of determination (R2) above 0.95 for the testing set and 0.97 for the training set. Radar and Taylor plots also show better overall prediction performance of the hybrid SVR models than several traditional machine learning techniques, which confirms the superiority of the three proposed methods. The successful development of this predictive model can provide scientific guidance for LC3-ECC materials and further apply to such low-carbon, sustainable cement-based materials.

사과 과원 무인 제초를 위한 작업 경로 생성 및 경로 제어 시스템 개발 (Development of the Path Generation and Control System for Unmanned Weeding Robot in Apple Orchards)

  • 전진택;장호승;양창주;권경도;홍영기;김국환
    • 드라이브 ㆍ 컨트롤
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    • 제20권4호
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    • pp.27-34
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    • 2023
  • Weeding in orchards is closely associated with productivity and quality. The customary weeding process is both labor-intensive and time-consuming. To solve the problems, there is need for automation of agricultural robots and machines in the agricultural field. On the other hand, orchards have complicated working areas due to narrow spaces between trees and amorphous terrain. Therefore, it is necessary to develop customized robot technology for unmanned weeding work within the department. This study developed a path generation and path control method for unmanned weeding according to the orchard environment. For this, the width of the weeding span, the number of operations, and the width of the weeding robot were used as input parameters for the orchard environment parameters. To generate a weeding path, a weeding robot was operated remotely to obtain GNSS-based location data along the superheated center line, and a driving performance test was performed based on the generated path. From the results of orchard field tests, the RMSE in weeding period sections was measured at 0.029 m, with a maximum error of 0.15 m. In the steering period within row and steering to the next row sections, the RMSE was 0.124 m, and 0.047 m, respectively.

모래 3체 마모시험 장비(3-body abrasion tester)를 이용한 PLA프린팅 표면의 형상별 트라이볼로지 성능 분석 (Tribology Performance Analysis by Surface Patterns of PLA Printing Samples Using 3-body Abrasion Tester)

  • 최용석;박경렬;강성민;김운성;정경은;박영진;이경준
    • Tribology and Lubricants
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    • 제39권6호
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    • pp.250-255
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    • 2023
  • This study applies various surface patterns to minimize material loss in construction equipment that is subject to severe wear due to sand, such as the wear-resistant steel plates of dump trucks or the teeth of excavators. The relationship between surface morphology and wear behavior is investigated using PLA+ polymer to observe the effect of the surface pattern. Five types of samples - smooth, concave, convex, wavy concave, and wavy convex designs - are created using a 3D printer. A wear experiment is conducted for a duration of 3 h using 6.5 kg of abrasive particles. The mass loss of the samples after the experiment is measured to assess the extent of wear. Additionally, the surface morphology of the samples before and after the experiment is analyzed using SEM and confocal microscopy. The study results reveal that the smooth design exhibits the highest wear loss, whereas the concave and wavy concave designs show relatively lower wear loss. The convex and wavy convex designs exhibit varying contact areas with the abrasive particles depending on the surface pattern, resulting in different levels of wear. Furthermore, a comparison between the experimental results and DEM simulations confirms the observed wear trends. This study reveals the relationship between wear damage according to surface pattern shape and is expected to be of substantial help in the analysis of wear and tear on agricultural and heavy equipment.

인공지능 기반 객체 인식을 위한 최적 학습모델 구축 방안에 관한 연구 (A Study on How to Build an Optimal Learning Model for Artificial Intelligence-based Object Recognition)

  • 양환석
    • 융합보안논문지
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    • 제23권5호
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    • pp.3-8
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    • 2023
  • 4차 산업혁명으로 많은 산업 분야에 커다란 변화가 일어나고 있으며, 그중에서도 인공지능을 활용한 융합기술에 활발한 연구가 진행되고 있다. 그중에서도 인공지능을 활용한 객체 인식과 인식 결과를 활용한 디지털 전환(Digital Transformation) 분야에서 그 요구가 나날이 증가하고 있다. 본 논문에서는 이미지내에 글자, 심볼, 선을 정확하게 인식하고 인식 결과를 시뮬레이션에 활용할 수 있도록 표준화 포맷의 파일로 저장하기 위해 최적의 학습모델 구축 방법을 제안하였다. 이미지내 글자, 심볼, 선을 인식하기 위하여 인식 대상별 특성을 분석한 후 최적의 인식 기법을 선택하였다. 그다음으로 인식 대상별 인식률을 향상시키기 위하여 최적의 학습 모델 구축 방안을 제안하였다. 글자, 심볼, 선 인식의 순서와 가중치를 다르게 설정하여 인식 결과를 확인하였으며, 인식 후처리에 대한 방안도 마련하였다. 최종적인 인식 결과는 시뮬레이션 등 다양한 처리에 활용될 수 있는 표준화 포맷으로 저장하였다. 본 논문에서 제안한 최적의 학습 모델 구축에 대한 우수한 성능은 실험을 통해 확인할 수 있었다.

Development and verification of an underground crop harvester simulation model for potato harvesting

  • Md. Abu Ayub Siddique;Hyeon-Ho Jeon;Seok-Pyo Moon;Sang-Hee Lee;Jang-Young Choi;Yong-Joo Kim
    • 드라이브 ㆍ 컨트롤
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    • 제21권1호
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    • pp.38-45
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    • 2024
  • The power delivery is crucial to designing agricultural machinery. Therefore, the tractor-mounted potato harvester was used in this study to conduct the field experiment and analyze the power delivery for each step. This study was focused on an analysis of power delivery from the engine to the hydraulic components for the tractor-mounted harvester during potato harvesting. Finally, the simulation model of a self-propelled potato harvester was developed and validated using the experimental dataset of the tractor-mounted potato harvester. The power delivery analysis showed that approximately 90.22% of the engine power was used as traction power to drive the tractor-mounted harvester, and only 5.10% of the engine power was used for the entire hydraulic system of the tractor and operated the harvester. The statistical analysis of the simulation and experimental results showed that the coefficient of determinations (R2) ranged from 0.80 to 0.96, which indicates that the simulation model was performed with an accuracy of over 80%. The regression models were correlated linearly with the simulation and experimental results. Therefore, we believe that this study could contribute to the design methodology and performance test procedure of agricultural machinery. This basic study would be helpful in the design of a self-propelled potato harvester.