• 제목/요약/키워드: Load current prediction

검색결과 124건 처리시간 0.029초

균열 콘크리트 면에서의 CIP앵커의 파괴거동 (Fracture Behavior of CIP Anchor in Cracked Concrete)

  • 김호섭;윤영수;윤영수;박성균
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 2001년도 봄 학술발표회 논문집
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    • pp.169-174
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    • 2001
  • This study concerns crack effect on concrete anchor system and prediction of tensile capacity, as governed by concrete cone failure, of single anchors located at center of concrete specimen. To Investigate crack effect three different types of crack such as crack width of 0.2mm and 0.5nm, crack depth of loom and 20cm, and crack location of center and biased point were simulated. The static tensile load was subjected to 7/8 in. CIP anchor embedded in concrete of strength 280kg/$cm^{2}$. Tested pullout capacity was compared to prediction value by each current design method (such as ACI 349-97, ACI 349 revision and CEB-FIP which is based on CC Method), In these comparison CC Method and ACI revision showed almost same value in uncracked concrete specimen, however in cracked concrete CC Method showed conservativeness. Therefore the design by ACI 349 revision is recommended for the safe and economic design.

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Hourly Steel Industry Energy Consumption Prediction Using Machine Learning Algorithms

  • Sathishkumar, VE;Lee, Myeong-Bae;Lim, Jong-Hyun;Shin, Chang-Sun;Park, Chang-Woo;Cho, Yong Yun
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2019년도 추계학술발표대회
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    • pp.585-588
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    • 2019
  • Predictions of Energy Consumption for Industries gain an important place in energy management and control system, as there are dynamic and seasonal changes in the demand and supply of energy. This paper presents and discusses the predictive models for energy consumption of the steel industry. Data used includes lagging and leading current reactive power, lagging and leading current power factor, carbon dioxide (tCO2) emission and load type. In the test set, four statistical models are trained and evaluated: (a) Linear regression (LR), (b) Support Vector Machine with radial kernel (SVM RBF), (c) Gradient Boosting Machine (GBM), (d) random forest (RF). Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) are used to measure the prediction efficiency of regression designs. When using all the predictors, the best model RF can provide RMSE value 7.33 in the test set.

비연성 RC 기둥의 하중-변형 응답 모사를 위한 모델 매개변수 제안 (Development of Model Parameter Prediction Equations for Simulating Load-deformation Response of Non-ductile RC Columns)

  • 이창석;한상환
    • 한국지진공학회논문집
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    • 제23권2호
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    • pp.119-129
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    • 2019
  • Many reinforced concrete (RC) buildings constructed prior to 1980's lack important features guaranteeing ductile response under earthquake excitation. Structural components in such buildings, especially columns, do not satisfy the reinforcement details demanded by current seismic design codes. Columns with deficient reinforcement details may suffer significant damage when subjected to cyclic lateral loads. They can also experience rapid lateral strength degradation induced by shear failure. The objective of this study is to accurately simulate the load-deformation response of RC columns experiencing shear failure. In order to do so, model parameters are calibrated to the load-deformation response of 40 RC column specimens failed in shear. Multivariate stepwise regression analyses are conducted to develop the relationship between the model parameters and physical parameters of RC column specimens. It is shown that the proposed predictive equations successfully estimated the model parameters of RC column specimens with great accuracy. The proposed equations also showed better accuracy than the existing ones.

인공신경회로망에 기초한 직류모터제어 (Control method for DC Motor based on Neural Networks)

  • 박진현;최영규;박준호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1993년도 하계학술대회 논문집 A
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    • pp.248-250
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    • 1993
  • In this paper, we assume that the dynamics of DC motor and nonlinear load are unknown. We train the inverse dynamic model of DC motor and nonlinear load using the neural network and construct speed control system based on the traind dynamic model and current control mode. Speed prediction scheme using neural network is also proposed the alleviate the time delay effect caused by the computation time of neural network. Simulation results show good performances of the control system. Finally, hardware configuration of the control system is outlined.

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Application of Lagrangian approach to generate P-I diagrams for RC columns exposed to extreme dynamic loading

  • Zhang, Chunwei;Abedini, Masoud
    • Advances in concrete construction
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    • 제14권3호
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    • pp.153-167
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    • 2022
  • The interaction between blast load and structures, as well as the interaction among structural members may well affect the structural response and damages. Therefore, it is necessary to analyse more realistic reinforced concrete structures in order to gain an extensive knowledge on the possible structural response under blast load effect. Among all the civilian structures, columns are considered to be the most vulnerable to terrorist threat and hence detailed investigation in the dynamic response of these structures is essential. Therefore, current research examines the effect of blast loads on the reinforced concrete columns via development of Pressure- Impulse (P-I) diagrams. In the finite element analysis, the level of damage on each of the aforementioned RC column will be assessed and the response of the RC columns when subjected to explosive loads will also be identified. Numerical models carried out using LS-DYNA were compared with experimental results. It was shown that the model yields a reliable prediction of damage on all RC columns. Validation study is conducted based on the experimental test to investigate the accuracy of finite element models to represent the behaviour of the models. The blast load application in the current research is determined based on the Lagrangian approach. To develop the designated P-I curves, damage assessment criteria are used based on the residual capacity of column. Intensive investigations are implemented to assess the effect of column dimension, concrete and steel properties and reinforcement ratio on the P-I diagram of RC columns. The produced P-I models can be applied by designers to predict the damage of new columns and to assess existing columns subjected to different blast load conditions.

Experimental and Analytical Study on the Bus Duct System for the Prediction of Temperature Variations Due To the Fluctuation of Load

  • Thirumurugaveerakumar, S.;Sakthivel, M.;Valarmathi, S.
    • Journal of Electrical Engineering and Technology
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    • 제9권6호
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    • pp.2036-2041
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    • 2014
  • In this paper, a thermal model is developed for the bus bar system to predict the temperature variation during the transient time period and to calculate both the steady-state and transient electrical current carrying capacity (ampacity) of bus bar. The bus bar system installed in the power house of Kumaraguru College of Technology, Coimbatore has been considered. Temperature variation predicted in the modelling is validated by observing the current and steady state temperatures in different feeders of the bus bar. Magnetic field of the extreme phases R and B induces more current in the middle phase Y. Hence, the steady state temperature in the phase Y is greater than other two phases. The transient capabilities of the bus bar are illustrated by calculating the variations in the bus bar temperature when it is subjected to a step change in current during the peak hours due to increase in hostel utilities and facilities (5.30 pm to 10.30 pm). The physical and geometrical properties of the bus bar and temperature variation in the bus bar are used to estimate the thermal time constants for common bus bar cross-sections. An analytical expression for the time constant of the bus bar is derived.

수명예측 방법에 따른 마이크로스위치의 수명분석 및 신뢰도 예측 (Life Analysis and Reliability Prediction of Micro Switches based on Life Prediction Method)

  • 지정건;신건영;이덕규;손영진;이희성
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2011년도 정기총회 및 추계학술대회 논문집
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    • pp.14-21
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    • 2011
  • Reliability means that a product maintains its initial quality and performance at certain period of time(time, distance, cycle etc) under given condition without failure. Given conditions include both environmental condition and operating condition. Environmental condition means common natural environment such as temperature, humidity, vibration, and working condition means artificial environment such as voltage, current load, install place, hours of use, which occurs during using the product. In the field of railway vehicles, although components of railway vehicles with reliability are the trend of mandatory as persisting period of railway vehicles is extended, using components of railway vehicles is insufficient for the practical reliability assessment. but the meaning of the first railway operating agnecy to acquire the parts in the field, the data suggest the reliability of products if you can and can show the reliability of modular units and modular units can provide the reliability of if you can present reliability of the entire system is thought to be here. In this study, lifespan of micro-switch for master controller is analyzed and prediction is performed based on its field data considering the special circumstances of railway vehicles operating agency, such as a large number of trains operates on the same line.

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수명예측 방법에 따른 마이크로스위치의 수명분석 및 신뢰도 예측 (Life Analysis and Reliability Prediction of Micro-Switches based on Life Prediction Method)

  • 지정건;신건영;이덕규;이희성
    • 시스템엔지니어링학술지
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    • 제7권1호
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    • pp.57-69
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    • 2011
  • Reliability means that a product maintains its initial quality and performance at certain period of time(time, distance, cycle etc) under given condition without failure. Given conditions include both environmental condition and operating condition. Environmental condition means common natural environment such as temperature, humidity, vibration, and working condition means artificial environment such as voltage, current load, install place, hours of use, which occurs during using the product. In the field of railway vehicles, although components of railway vehicles with reliability are the trend of mandatory as persisting period of railway vehicles is extended, using components of railway vehicles is insufficient for the practical reliability assessment. but the meaning of the first railway operating agency to acquire the parts in the field, the data suggest the reliability of products if you can and can show the reliability of modular units and modular units can provide the reliability of if you can present reliability of the entire system is thought to be here In this study, lifespan of micro-switch for master controller is analyzed and prediction is performed based on its field data considering the special circumstances of railway vehicles operating agency, such as a large number of trains operates on the same line.

생태계모텔에 의한 진해만의 빈산소수괴 저감예측 (Numerical Prediction for Reduction of Oxygen Deficient Water Mass by Ecological Model in Jinhae Bay)

  • 이인철;공화훈;윤석진
    • 한국해양공학회지
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    • 제22권5호
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    • pp.75-82
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    • 2008
  • As a basic study for establishing a countermeasure for an oxygen deficient water mass (ODW), we investigated the variation of ODW volume according to the enforced total pollution load management in Jinhae Bay. This study estimated the inflowing pollutant loads into Jinhae Bay and predicted the reduction in ODW by using a sediment-water ecological model (SWEM). The result obtained in this study are summarized as follows: 1) The daily average pollutant loads of COD, SS, TN, TP, DIN, and DIP inflowing into Jinhae bay in 2005 were estimated to be about 12,218 kg-COD/day, 91,884 kg-SS/day, 5,292 kg-TN/day, 182 kg-TP/day, 4,236 kg-DIN/day, and 130 kg-DIP/day. 2) The calculated results of the tidal current by the hydrodynamic model showed good agreement with the observed currents. Also, an ecological model well reproduced the spatial distribution of the water quality in the bay. 3) This study defined the ODWDI (ODW decreasing index) in order to estimate the ODW decreasing volume caused by a reduction in the inflowing pollutant loads. As a result, the ODWDI was predicted to be about 0.91 (COD 30% reduction), 0.87 (COD 50% reduction), 0.79 (COD 70% reduction), 0.85 (ALL 30% reduction), 0.66 (ALL 50% reduction), and 0.45 (ALL 70% reduction). The ODW volume was decreased 1.5 $\sim$ 2.6 times with a reduction in the COD, TN, and TP inflowing pollutant loads compared to a reduction in just the COD inflowing pollutant load. Therefore, it is necessary to enforce total pollution load management, not only for COD, but also fm TN and TP.

Shear strength prediction of concrete-encased steel beams based on compatible truss-arch model

  • Xue, Yicong;Shang, Chongxin;Yang, Yong;Yu, Yunlong;Wang, Zhanjie
    • Steel and Composite Structures
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    • 제43권6호
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    • pp.785-796
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    • 2022
  • Concrete-encased steel (CES) beam, in which structural steel is encased in a reinforced concrete (RC) section, is widely applied in high-rise buildings as transfer beams due to its high load-carrying capacity, great stiffness, and good durability. However, these CES beams are prone to shear failure because of the low shear span-to-depth ratio and the heavy load. Due to the high load-carrying capacity and the brittle failure process of the shear failure, the accurate strength prediction of CES beams significantly influences the assessment of structural safety. In current design codes, design formulas for predicting the shear strength of CES beams are based on the so-called "superposition method". This method indicates that the shear strength of CES beams can be obtained by superposing the shear strengths of the RC part and the steel shape. Nevertheless, in some cases, this method yields errors on the unsafe side because the shear strengths of these two parts cannot be achieved simultaneously. This paper clarifies the conditions at which the superposition method does not hold true, and the shear strength of CES beams is investigated using a compatible truss-arch model. Considering the deformation compatibility between the steel shape and the RC part, the method to obtain the shear strength of CES beams is proposed. Finally, the proposed model is compared with other calculation methods from codes AISC 360 (USA, North America), Eurocode 4 (Europe), YB 9082 (China, Asia), JGJ 138 (China, Asia), and AS/NZS 2327 (Australia/New Zealand, Oceania) using the available test data consisting of 45 CES beams. The results indicate that the proposed model can predict the shear strength of CES beams with sufficient accuracy and safety. Without considering the deformation compatibility, the calculation methods from the codes AISC 360, Eurocode 4, YB 9082, JGJ 138, and AS/NZS 2327 lead to excessively conservative or unsafe predictions.