• 제목/요약/키워드: Laboratory model testing

검색결과 268건 처리시간 0.021초

Performance verification and improvement of the frequency analysis unit for GIS Preventive & Diagnostic Monitoring System (GIS 예방진단시스템 주파수 분석장치 성능개선 및 검증)

  • Kim, Won-Gyu;Kim, Min-Soo;Baek, Young-Sik
    • The Transactions of The Korean Institute of Electrical Engineers
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    • 제64권3호
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    • pp.485-491
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    • 2015
  • This paper shows the design improvement and test model of FAU (Frequency Analysis Unit) in PDD (Partial Discharge Diagnosis system) for 800kV GIS (Gas Insulated Switchgear). We found some problems during operation of previous FAU, such as the aging of fiber-optic converter that can cause communication error, the malfunction of signal analysis circuit etc. And then we solved those problems by design improvement and verified the performance through type test. To monitor partial discharge, the performance of UHF sensor is important but the performance of frequency analysis unit is also very important. So we solved communication error, the malfunction of signal analysis circuit and then increased the operation reliability of FAU by improving fiber-optic converter and signal analysis circuit. Accredited testing laboratory carried out the performance verification test according to performance test criteria and procedure of reliability test standards, IEC-60225, 61000 and 60068 etc. We confirmed the test results which correspond with the performance test criteria.

The discrete element method simulation and experimental study of determining the mode I stress-intensity factor

  • Shemirani, Alireza Bagher;Haeri, Hadi;Sarfarazi, Vahab;Akbarpour, Abbas;Babanouri, Nima
    • Structural Engineering and Mechanics
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    • 제66권3호
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    • pp.379-386
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    • 2018
  • The present study addresses the direct and indirect methods of determining the mode-I fracture toughness of concrete using experimental tests and particle flow code. The direct method used is compaction tensile test and the indirect methods are notched Brazilian disc test, semi-circular bend specimen test, and hollow center cracked disc. The experiments were carried out to determine which indirect method yields the fracture toughness closer to the one obtained by the direct method. In the numerical analysis, the PFC model was first calibrated with respect to the data obtained from the Brazilian laboratory test. The crack paths observed in the simulated tests were in reasonable accordance with experimental results. The discrete element simulations demonstrated that the macro fractures in the models are caused by microscopic tensile breakages on large numbers of bonded particles. The mode-I fracture toughness in the direct tensile test was smaller than the indirect testing results. The fracture toughness obtained from the SCB test was closer to the direct test results. Hence, the semi-circular bend test is recommended as a proper experiment for determination of mode-I fracture toughness of concrete in the absence of direct tests.

Detection of Incipient Faults in Induction Motors using FIS, ANN and ANFIS Techniques

  • Ballal, Makarand S.;Suryawanshi, Hiralal M.;Mishra, Mahesh K.
    • Journal of Power Electronics
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    • 제8권2호
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    • pp.181-191
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    • 2008
  • The task performed by induction motors grows increasingly complex in modern industry and hence improvements are sought in the field of fault diagnosis. It is essential to diagnose faults at their very inception, as unscheduled machine down time can upset critical dead lines and cause heavy financial losses. Artificial intelligence (AI) techniques have proved their ability in detection of incipient faults in electrical machines. This paper presents an application of AI techniques for the detection of inter-turn insulation and bearing wear faults in single-phase induction motors. The single-phase induction motor is considered a proto type model to create inter-turn insulation and bearing wear faults. The experimental data for motor intake current, rotor speed, stator winding temperature, bearing temperature and noise of the motor under running condition was generated in the laboratory. The different types of fault detectors were developed based upon three different AI techniques. The input parameters for these detectors were varied from two to five sequentially. The comparisons were made and the best fault detector was determined.

Performance Analysis of Electricity Demand Forecasting by Detail Level of Building Energy Models Based on the Measured Submetering Electricity Data (서브미터링 전력데이터 기반 건물에너지모델의 입력수준별 전력수요 예측 성능분석)

  • Shin, Sang-Yong;Seo, Dong-Hyun
    • Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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    • 제12권6호
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    • pp.627-640
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    • 2018
  • Submetering electricity consumption data enables more detail input of end use components, such as lighting, plug, HVAC, and occupancy in building energy modeling. However, such an modeling efforts and results are rarely tried and published in terms of the estimation accuracy of electricity demand. In this research, actual submetering data obtained from a university building is analyzed and provided for building energy modeling practice. As alternative modeling cases, conventional modeling method (Case-1), using reference schedule per building usage, and main metering data based modeling method (Case-2) are established. Detail efforts are added to derive prototypical schedules from the metered data by introducing variability index. The simulation results revealed that Case-1 showed the largest error as we can expect. And Case-2 showed comparative error relative to Case-3 in terms of total electricity estimation. But Case-2 showed about two times larger error in CV (RMSE) in lighting energy demand due to lack of End Use consumption information.

Laboratory evaluation of roller compacted concrete containing RAP

  • Ahmadi, Amin;Gogheri, Mohammad K.;Adresi, Mostafa;Amoosoltani, Ershad
    • Advances in concrete construction
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    • 제10권6호
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    • pp.489-498
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    • 2020
  • This paper investigates mechanical properties of roller compacted concrete (RCC) involving reclaimed asphalt pavement (RAP). In this way, a set of 276 cylindrical RCC specimens were prepared with different RAP sizes (i.e., fine, coarse & total) at various ratios (i.e., 10%, 20%, and 40%). Results reveal that incorporation of RAP decreases unconfined compressive strength (UCS), modulus of elasticity (E), and indirect tensile (IDT) strength of RCC. For each RAP size, a regression model was used to maximize RAP content while satisfying the UCS lower limit (27.6 Mpa) mentioned by ACI as a minimum requirement for RCC used in pavement construction. Moreover, UCS of RAP incorporated mixes, dissimilar to that of control mixes, was found to be sensitive and insensitive to the testing temperature and curing time after 7 days, respectively. The results also demonstrate that the higher amounts of RAP, the more flexibility in RCC is. This issue was also proved by the results of modulus of elasticity test. In addition, the toughness index (TI) shows that increase in RAP content leads to up to 43% increase in energy absorbance capacity of RCC.

Evaluation of the Degradation Trend of the Polyurethane Resilient Pad in the Rail Fastening System by Multi-stress Accelerated Degradation Test (복합가속열화시험을 통한 레일체결장치 폴리우레탄 탄성패드의 열화 경향 분석)

  • Sung, Deok-Yong;Park, Kwang-Hwa
    • Journal of the Korean Society for Railway
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    • 제16권6호
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    • pp.466-472
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    • 2013
  • The use of a concrete track is gradually growing in urban and high-speed railways in many part of the world. The resilient pad, which is essentially when concrete tracks are used, plays the important role of relieving the impact caused by train loads. The simple fatigue test[1] to estimate the variable stiffness of resilient pads is usually performed, but it differs depending on the practical conditions of different railways. In this study, the static stiffness levels of used resilient pads according to passing tonnages levels were measured in laboratory tests. Also, the simple fatigue test and the multi-stress accelerated degradation test for new resilient pads were performed in a laboratory. The static stiffness of the used pad was compared with the results of tests of usage times and cycles. The results of the comparison showed that the variable static stiffness levels of the used pad were similar to results of the multi-stress accelerated degradation test considering the fatigue and heat load. With a T-NT equation related to the degree of the multi-stress accelerated degradation, a model of multi-stress accelerated degradation for a resilient pad was devised. It was found through this effort that the total acceleration factor was approximately 2.62. Finally, this study proposes an equation for a multi-stress accelerated degradation model for polyurethane resilient pads.

Measurement of Pile Load Transfer Using Fiber Bragg Grating Sensor (광섬유 격자소자에 의한 말뚝의 하중전이 측정)

  • 오정호;이원제;이상배;이우진
    • Journal of the Korean Geotechnical Society
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    • 제16권4호
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    • pp.201-208
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    • 2000
  • Axial load distribution in model piles was measured by fiber Bragg Grating(FBG) sensor to investigate a possibility of analyzing the load transfer mechanism by Fiber Optic sensor system. Since FBGs of different wave lengths can be multiplexed in an optical fiber, the installation of sensor system and the measurement of strains are relatively simple, compared with consisting strain gages. In this study, FBG sensors and electric strain gages were embedded in the same piles and the distributions of load transfer by two sensor systems were measured. It was observed from the test results that the variations of axial load by both systems showed insignificant difference and that the measurements by FBG were smoother than those by strain gage. Under the environments of laboratory testing, survival rate of embedded FBG system was higher than that of strain gage. Therefore, it was concluded that the use of FBG sensor has a great potential for the measurement of load transfer for pile foundation.

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Effect of suprascapular nerve injury on muscle and regenerated enthesis in a rat rotator cuff tear model

  • Kenichiro Eshima;Hiroki Ohzono;Masafumi Gotoh;Hisao Shimokobe;Koji Tanaka;Hidehiro Nakamura;Tomonoshin Kanazawa;Takahiro Okawa;Naoto Shiba
    • Clinics in Shoulder and Elbow
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    • 제26권2호
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    • pp.131-139
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    • 2023
  • Background: Massive rotator cuff tears (RCTs) are complicated by muscle atrophy, fibrosis, and intramuscular fatty degeneration, which are associated with postoperative tendon-to-bone healing failure and poor clinical outcomes. We evaluated muscle and enthesis changes in large tears with or without suprascapular nerve (SN) injury in a rat model. Methods: Sixty-two adult Sprague-Dawley rats were divided into SN injury (+) and SN injury (-) groups (n=31 each), comprising tendon (supraspinatus [SSP]/infraspinatus [ISP]) and nerve resection and tendon resection only cases, respectively. Muscle weight measurement, histological evaluation, and biomechanical testing were performed 4, 8, and 12 weeks postoperatively. Ultrastructural analysis with block face imaging was performed 8 weeks postoperatively. Results: SSP/ISP muscles in the SN injury (+) group appeared atrophic, with increased fatty tissue and decreased muscle weight, compared to those in the control and SN injury (-) groups. Immunoreactivity was only positive in the SN injury (+) group. Myofibril arrangement irregularity and mitochondrial swelling severity, along with number of fatty cells, were higher in the SN injury (+) group than in the SN injury (-) group. The bone-tendon junction enthesis was firm in the SN injury (-) group; this was atrophic and thinner in the SN injury (+) group, with decreased cell density and immature fibrocartilage. Mechanically, the tendon-bone insertion was significantly weaker in the SN injury (+) group than in the control and SN injury (+) groups. Conclusions: In clinical settings, SN injury may cause severe fatty changes and inhibition of postoperative tendon healing in large RCTs. Level of evidence: Level Basic research, controlled laboratory study.

Predicting concrete's compressive strength through three hybrid swarm intelligent methods

  • Zhang Chengquan;Hamidreza Aghajanirefah;Kseniya I. Zykova;Hossein Moayedi;Binh Nguyen Le
    • Computers and Concrete
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    • 제32권2호
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    • pp.149-163
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    • 2023
  • One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R2). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R2=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.

Machine Learning Framework for Predicting Voids in the Mineral Aggregation in Asphalt Mixtures (아스팔트 혼합물의 골재 간극률 예측을 위한 기계학습 프레임워크)

  • Hyemin Park;Ilho Na;Hyunhwan Kim;Bongjun Ji
    • Journal of the Korean Geosynthetics Society
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    • 제23권1호
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    • pp.17-25
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    • 2024
  • The Voids in the Mineral Aggregate (VMA) within asphalt mixtures play a crucial role in defining the mixture's structural integrity, durability, and resistance to environmental factors. Accurate prediction and optimization of VMA are essential for enhancing the performance and longevity of asphalt pavements, particularly in varying climatic and environmental conditions. This study introduces a novel machine learning framework leveraging ensemble machine learning model for predicting VMA in asphalt mixtures. By analyzing a comprehensive set of variables, including aggregate size distribution, binder content, and compaction levels, our framework offers a more precise prediction of VMA than traditional single-model approaches. The use of advanced machine learning techniques not only surpasses the accuracy of conventional empirical methods but also significantly reduces the reliance on extensive laboratory testing. Our findings highlight the effectiveness of a data-driven approach in the field of asphalt mixture design, showcasing a path toward more efficient and sustainable pavement engineering practices. This research contributes to the advancement of predictive modeling in construction materials, offering valuable insights for the design and optimization of asphalt mixtures with optimal void characteristics.