• Title/Summary/Keyword: random load

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Pre-Filtering based Post-Load Shedding Method for Improving Spatial Queries Accuracy in GeoSensor Environment (GeoSensor 환경에서 공간 질의 정확도 향상을 위한 선-필터링을 이용한 후-부하제한 기법)

  • Kim, Ho;Baek, Sung-Ha;Lee, Dong-Wook;Kim, Gyoung-Bae;Bae, Hae-Young
    • Journal of Korea Spatial Information System Society
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    • v.12 no.1
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    • pp.18-27
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    • 2010
  • In u-GIS environment, GeoSensor environment requires that dynamic data captured from various sensors and static information in terms of features in 2D or 3D are fused together. GeoSensors, the core of this environment, are distributed over a wide area sporadically, and are collected in any size constantly. As a result, storage space could be exceeded because of restricted memory in DSMS. To solve this kind of problems, a lot of related studies are being researched actively. There are typically 3 different methods - Random Load Shedding, Semantic Load Shedding, and Sampling. Random Load Shedding chooses and deletes data in random. Semantic Load Shedding prioritizes data, then deletes it first which has lower priority. Sampling uses statistical operation, computes sampling rate, and sheds load. However, they are not high accuracy because traditional ones do not consider spatial characteristics. In this paper 'Pre-Filtering based Post Load Shedding' are suggested to improve the accuracy of spatial query and to restrict load shedding in DSMS. This method, at first, limits unnecessarily increased loads in stream queue with 'Pre-Filtering'. And then, it processes 'Post-Load Shedding', considering data and spatial status to guarantee the accuracy of result. The suggested method effectively reduces the number of the performance of load shedding, and improves the accuracy of spatial query.

Study on a Probabilistic Load Forecasting Formula and Its Algorithm (전력부하의 확률가정적 최적예상식의 유도 및 전산프로그래밍에 관한 연구)

  • Myoung Sam Ko
    • 전기의세계
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    • v.22 no.2
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    • pp.28-32
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    • 1973
  • System modeling is applied in developing a probabilistic linear estimator for the load of an electric power system for the purpose of short term load forecasting. The model assumer that the load in given by the suns of a periodic discrete time serier with a period of 24 hour and a residual term such that the output of a discrete time dynamical linear system driven by a white random process and a deterministic input. And also we have established the main forecasting algorithms, which are essemtally the Kalman filter-predictor equations.

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Fractographic Analysis Method of Fatigue Fracture Surface under Program and Random Loading for Aluminum Alloy (알루미늄 합금의 랜덤하중 하에서 발생한 피로파면 해석 방법)

  • 김상태;최성종;양현태;이희원
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.12
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    • pp.2055-2060
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    • 2003
  • Striation is a typical pattern observed on the fatigue fracture surface and the spacing is known to correspond to a macroscopic fatigue crack growth rate, and many models for the predict in the formation of such striation have been proposed. However, these theories and methods can't be applied under random loading spectrum. In this study, the fatigue tests were carried out on aluminum alloy under random loading spectrum. The fatigue fracture surfaces were observed in the scanning electron microscope (SEM) and great quantities of SEM micrographs were synthesized and saved in computer system. The space and morphology of several large-scale striations, which are expected to from at the relatively greater load range in loading block, were observed. The crack length for each loading blocks was decided in consideration of regularity and repetition of those striations. It is shown that the applicability of fractographic methods on the fatigue fracture surface under random loading spectrum.

Analysis of structural dynamic reliability based on the probability density evolution method

  • Fang, Yongfeng;Chen, Jianjun;Tee, Kong Fah
    • Structural Engineering and Mechanics
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    • v.45 no.2
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    • pp.201-209
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    • 2013
  • A new dynamic reliability analysis of structure under repeated random loads is proposed in this paper. The proposed method is developed based on the idea that the probability density of several times random loads can be derived from the probability density of single-time random load. The reliability prediction models of structure based on time responses under several times random loads with and without strength degradation are obtained by using the stress-strength interference theory and probability density evolution method. The resulting differential equations in the prediction models can be solved by using the forward finite difference method. Then, the probability density functions of strength redundancy of the structures can be obtained. Finally, the structural dynamic reliability can be calculated using integral method. The efficiency of the proposed method is demonstrated numerically through a speed reducer. The results have shown that the proposed method is practicable, feasible and gives reasonably accurate prediction.

Random Access Channel Allocation Scheme in Multihop Cellular Networks (멀티 홉 셀룰라 망에서의 랜덤 액세스 채널 할당 방안)

  • Cho, Sung-Hyun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.4A
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    • pp.330-335
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    • 2007
  • This paper proposes a multichannel random access channel allocation scheme for multihop cellular networks to guarantee the stable throughput of a random access. The fundamental contribution is a mathematical formula for an optimal partition ratio of shared random access channels between a base station and a relay station. In addition, the proposed scheme controls the retransmission probability of random access packets under heavy load condition. Simulation results show that the proposed scheme can guarantee the required random access channel utilization and packet transmission delay even if the a random access packet arrival rate is higher than 0.1.

Probabilistic analysis of RC beams according to IS456:2000 in limit state of collapse

  • Kulkarni, Anadee M.;Dattaa, Debarati
    • Structural Engineering and Mechanics
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    • v.71 no.2
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    • pp.165-173
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    • 2019
  • This paper investigates the probability of failure of reinforced concrete beams for limit state of collapse for flexure and shear. The influence of randomness of the variables on the failure probability is also examined. The Indian standard code for plain and reinforced concrete IS456:2000 is used for the design of beams. Probabilistic models are developed for flexure and shear according to IS456:2000. The loads considered acting on the beam are live load and dead load only. Random variables associated with the limit state equation such as grade of concrete, grade of steel, live load and dead load are identified. Probability of failure is evaluated based on the limit state equation using First Order Reliability Method (FORM). Importance of the random variables on the limit state equations are observed and the variables are accordingly reduced. The effect of the reduced parameters is checked on the probability of failure. The results show the role of each parameter on the design of beam. Thus, the Indian standard guidelines for plain and reinforced concrete IS456:2000 is investigated with the probabilistic and risk-based analysis and design for a simple beam. The results obtained are also compared with the literature and accordingly some suggestions are made.

An Improved Algorithm of the Daily Peak Load Forecasting fair the Holidays (특수일의 최대 전력수요예측 알고리즘 개선)

  • Song, Gyeong-Bin;Gu, Bon-Seok;Baek, Yeong-Sik
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.3
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    • pp.109-117
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    • 2002
  • High accuracy of the load forecasting for power systems improves the security of the power system and generation cost. However, the forecasting problem is difficult to handle due to the nonlinear and the random-like behavior of system loads as well as weather conditions and variation of economical environments. So far. many studies on the problem have been made to improve the prediction accuracy using deterministic, stochastic, knowledge based and artificial neural net(ANN) method. In the conventional load forecasting method, the load forecasting maximum error occurred for the holidays on Saturday and Monday. In order to reduce the load forecasting error of the daily peak load for the holidays on Saturday and Monday, fuzzy concept and linear regression theory have been adopted into the load forecasting problem. The proposed algorithm shows its good accuracy that the average percentage errors are 2.11% in 1996 and 2.84% in 1997.

Mean Square Response Analysis of the Tall Building to Hazard Fluctuating Wind Loads (재난변동풍하중을 받는 고층건물의 평균자승응해석)

  • Oh, Jong Seop;Hwang, Eui Jin;Ryu, Ji Hyeob
    • Journal of Korean Society of Disaster and Security
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    • v.6 no.3
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    • pp.1-8
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    • 2013
  • Based on random vibration theory, a procedure for calculating the dynamic response of the tall building to time-dependent random excitation is developed. In this paper, the fluctuating along- wind load is assumed as time-dependent random process described by the time-independent random process with deterministic function during a short duration of time. By deterministic function A(t)=1-exp($-{\beta}t$), the absolute value square of oscillatory function is represented from author's studies. The time-dependent random response spectral density is represented by using the absolute value square of oscillatory function and equivalent wind load spectrum of Solari. Especially, dynamic mean square response of the tall building subjected to fluctuating wind loads was derived as analysis function by the Cauchy's Integral Formula and Residue Theorem. As analysis examples, there were compared the numerical integral analytic results with the analysis fun. results by dynamic properties of the tall uilding.

Vertical Seismic Vibration of Suspension Bridges (지진을 받는 현수교의 수직진동)

  • Choi, Jee-Hoon;Lee, Jon-Ja;Kim, Su-Bo;Lee, Yong-Jae
    • Journal of Korean Society of Steel Construction
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    • v.12 no.5 s.48
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    • pp.581-593
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    • 2000
  • In this study, vertical dynamic analyses on the suspension bridges under seismic load are developed. Time domain analysis, random vibration analysis, and spectral analysis are formulated theoretically. The random nitration analysis is checked by numerical integration and the mathematical integration with correlation coefficient which include CQC and SRSS method in the conditions of white noise and filtered white noise. Beam, truss and frame elements are used in order to model the suspension bridge. Geometric stiffness due to dead load is considered for cable and tower.

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