• 제목/요약/키워드: stochastic analysis

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다중하중에 따른 경사제 피복재의 추계학적 신뢰성 해석 (Stochastic Reliability Analysis of Armor Units of Rubble-Mound Breakwaters Subject to Multiple Loads)

  • 이철응
    • 한국해안·해양공학회논문집
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    • 제24권2호
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    • pp.138-148
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    • 2012
  • 경사제에 불규칙하게 작용하는 임의 크기의 다중하중으로 인해 피복재의 안정성에 대한 성능이 시간에 따라 어떻게 달라지는지를 해석할 수 있는 추계학적 신뢰성 해석 모형이 개발되었다. Hudson의 공식과 Melby 공식을 이용하여 재현기간에 따른 파고의 함수로 경사제 피복재의 초기 저항력 크기와 피해율을 확률적으로 산정할 수 있는 새로운 방법이 제시되었다. 생애기간에 대한 신뢰성 분석을 실시하여 시간에 따른 다중하중의 작용과 사용한계나 극한한계 등 한계상태에 따른 구조물의 성능을 올바로 해석할 수 있었다. 마지막으로 보수보강 목표확률을 시간에 따른 누적파괴확률의 결과와 조합하여 구조물 유지관리에서 가장 중요한 변수인 보수보강 시점을 정량적으로 산정할 수 있는 방법이 제시되었다.

Monte Carlo analysis of earthquake resistant R-C 3D shear wall-frame structures

  • Taskin, Beyza;Hasgur, Zeki
    • Structural Engineering and Mechanics
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    • 제22권3호
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    • pp.371-399
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    • 2006
  • The theoretical background and capabilities of the developed program, SAR-CWF, for stochastic analysis of 3D reinforced-concrete shear wall-frame structures subject to seismic excitations is presented. Incremental stiffness and strength properties of system members are modeled by extended Roufaiel-Meyer hysteretic relation for bending while shear deformations for walls by Origin-Oriented hysteretic model. For the critical height of shear-walls, division to sub-elements is performed. Different yield capacities with respect to positive and negative bending, finite extensions of plastic hinges and P-${\delta}$ effects are considered while strength deterioration is controlled by accumulated hysteretic energy. Simulated strong motions are obtained from a Gaussian white-noise filtered through Kanai-Tajimi filter. Dynamic equations of motion for the system are formed according to constitutive and compatibility relations and then inserted into equivalent It$\hat{o}$-Stratonovich stochastic differential equations. A system reduction scheme based on the series expansion of eigen-modes of the undamaged structure is implemented. Time histories of seismic response statistics are obtained by utilizing the computer programs developed for different types of structures.

Performance Analysis of Cellular Networks with D2D communication Based on Queuing Theory Model

  • Xin, Jianfang;Zhu, Qi;Liang, Guangjun;Zhang, Tiaojiao;Zhao, Su
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권6호
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    • pp.2450-2469
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    • 2018
  • In this paper, we develop a spatiotemporal model to analysis of cellular user in underlay D2D communication by using stochastic geometry and queuing theory. Firstly, by exploring stochastic geometry to model the user locations, we derive the probability that the SINR of cellular user in a predefined interval, which constrains the corresponding transmission rate of cellular user. Secondly, in contrast to the previous studies with full traffic models, we employ queueing theory to evaluate the performance parameters of dynamic traffic model and formulate the cellular user transmission mechanism as a M/G/1 queuing model. In the derivation, Embedded Markov chain is introduced to depict the stationary distribution of cellular user queue status. Thirdly, the expressions of performance metrics in terms of mean queue length, mean throughput, mean delay and mean dropping probability are obtained, respectively. Simulation results show the validity and rationality of the theoretical analysis under different channel conditions.

국방 R&D프로젝트의 일정-비용분석모델의 연구 (A study on a schedule-cost analysis model for defense R&D project planning)

  • 황홍석;류정철;정덕길
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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    • pp.213-216
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    • 1996
  • R'||'&'||'D project management is a process of decisions concerned with the achievement of goals of objectives. Especially, defense R'||'&'||'D project planning is the key in the successfull management of defense development. The defense project managers are constantly having to perform "what if\ulcorner" exercise, such as what if the project is extended out for an additional cost\ulcorner In this reserch, we developed a schedule-cost analysis model based upon Critical Path Method(CPM) and Venture Evaluation and Review Technique(VERT) for schedule-cost trade off analysis defense R'||'&'||'D projects. In the first step, a deterministic model is developed as a heuristic which deterministic model is developed as a heuristic which determines the schedule extension and reduction cost as a function desired schedule. In the second step, a stochastic network simulation model is developed to analyse the project risk (sucess and failure). The expected time and cost can be determined for desired schedule under the assumptions of stochastic arc data (time and cost) with a various precedence relationships. This model provides the defense R'||'&'||'D managers with an estimated and expected cost for curtailing or extending a project a given amount of time. The effectiveness and efficiency of the proposed methods, a heuristic and stochastic networks simulations, have been demonstrated through examples.

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SSA-based stochastic subspace identification of structures from output-only vibration measurements

  • Loh, Chin-Hsiung;Liu, Yi-Cheng;Ni, Yi-Qing
    • Smart Structures and Systems
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    • 제10권4_5호
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    • pp.331-351
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    • 2012
  • In this study an output-only system identification technique for civil structures under ambient vibrations is carried out, mainly focused on using the Stochastic Subspace Identification (SSI) based algorithms. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), capable to smooth a noisy signal, is adopted for preprocessing the measurement data. An SSA-based SSI algorithm with the aim of finding accurate and true modal parameters is developed through stabilization diagram which is constructed by plotting the identified system poles with increasing the size of data matrix. First, comparative study between different approaches, with and without using SSA to pre-process the data, on determining the model order and selecting the true system poles is examined in this study through numerical simulation. Finally, application of the proposed system identification task to the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.

Application of recursive SSA as data pre-processing filter for stochastic subspace identification

  • Loh, Chin-Hsiung;Liu, Yi-Cheng
    • Smart Structures and Systems
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    • 제11권1호
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    • pp.19-34
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    • 2013
  • The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using the Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approach. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis (rSSA) is presented to remove the noise contaminant measurements so as to enhance the stability of data analysis. Through the application of rSSA-SSI-COV to the vibration measurement of bridge during scouring experiment, the ability of the proposed algorithm was proved to be robust to the noise perturbations and offers a very good online tracking capability. The accuracy and robustness offered by rSSA-SSI-COV provides a key to obtain the evidence of imminent bridge settlement and a very stable modal frequency tracking which makes it possible for early warning. The peak values of the identified $1^{st}$ mode shape slope ratio has shown to be a good indicator for damage location, meanwhile, the drastic movements of the peak of $2^{nd}$ mode slope ratio could be used as another feature to indicate imminent pier settlement.

Estimating the Loss Ratio of Solar Photovoltaic Electricity Generation through Stochastic Analysis

  • Hong, Taehoon;Koo, Choongwan;Lee, Minhyun
    • Journal of Construction Engineering and Project Management
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    • 제3권3호
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    • pp.23-34
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    • 2013
  • As climate change and environmental pollution become one of the biggest global issues today, new renewable energy, especially solar photovoltaic (PV) system, is getting great attention as a sustainable energy source. However, initial investment cost of PV system is considerable, and thus, it is crucial to predict electricity generation accurately before installation of the system. This study analyzes the loss ratio of solar photovoltaic electricity generation from the actual PV system monitoring data to predict electricity generation more accurately in advance. This study is carried out with the following five steps: (i) Data collection of actual electricity generation from PV system and the related information; (ii) Calculation of simulation-based electricity generation; (iii) Comparative analysis between actual electricity generation and simulation-based electricity generation based on the seasonality; (iv) Stochastic approach by defining probability distribution of loss ratio between actual electricity generation and simulation-based electricity generation ; and (v) Case study by conducting Monte-Carlo Simulation (MCS) based on the probability distribution function of loss ratio. The results of this study could be used (i) to estimate electricity generation from PV system more accurately before installation of the system, (ii) to establish the optimal maintenance strategy for the different application fields and the different season, and (iii) to conduct feasibility study on investment at the level of life cycle.

수요가 재생 도착과정을 따르는 (s, S) 재고 시스템에서 시뮬레이션 민감도 분석을 이용한 최적 전략 (Optimal Policy for (s, S) Inventory System Characterized by Renewal Arrival Process of Demand through Simulation Sensitivity Analysis)

  • 권치명
    • 한국시뮬레이션학회논문지
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    • 제12권3호
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    • pp.31-40
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    • 2003
  • This paper studies an optimal policy for a certain class of (s, S) inventory control systems, where the demands are characterized by the renewal arrival process. To minimize the average cost over a simulation period, we apply a stochastic optimization algorithm which uses the gradients of parameters, s and S. We obtain the gradients of objective function with respect to ordering amount S and reorder point s via a combined perturbation method. This method uses the infinitesimal perturbation analysis and the smoothed perturbation analysis alternatively according to occurrences of ordering event changes. The optimal estimates of s and S from our simulation results are quite accurate. We consider that this may be due to the estimated gradients of little noise from the regenerative system simulation, and their effect on search procedure when we apply the stochastic optimization algorithm. The directions for future study stemming from this research pertain to extension to the more general inventory system with regard to demand distribution, backlogging policy, lead time, and inter-arrival times of demands. Another direction involves the efficiency of stochastic optimization algorithm related to searching procedure for an improving point of (s, S).

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Non-stochastic interval arithmetic-based finite element analysis for structural uncertainty response estimate

  • Lee, Dongkyu;Park, Sungsoo;Shin, Soomi
    • Structural Engineering and Mechanics
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    • 제29권5호
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    • pp.469-488
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    • 2008
  • Finite element methods have often been used for structural analyses of various mechanical problems. When finite element analyses are utilized to resolve mechanical systems, numerical uncertainties in the initial data such as structural parameters and loading conditions may result in uncertainties in the structural responses. Therefore the initial data have to be as accurate as possible in order to obtain reliable structural analysis results. The typical finite element method may not properly represent discrete systems when using uncertain data, since all input data of material properties and applied loads are defined by nominal values. An interval finite element analysis, which uses the interval arithmetic as introduced by Moore (1966) is proposed as a non-stochastic method in this study and serves a new numerical tool for evaluating the uncertainties of the initial data in structural analyses. According to this method, the element stiffness matrix includes interval terms of the lower and upper bounds of the structural parameters, and interval change functions are devised. Numerical uncertainties in the initial data are described as a tolerance error and tree graphs of uncertain data are constructed by numerical uncertainty combinations of each parameter. The structural responses calculated by all uncertainty cases can be easily estimated so that structural safety can be included in the design. Numerical applications of truss and frame structures demonstrate the efficiency of the present method with respect to numerical analyses of structural uncertainties.

McCARD/MIG stochastic sampling calculations for nuclear cross section sensitivity and uncertainty analysis

  • Ho Jin Park
    • Nuclear Engineering and Technology
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    • 제54권11호
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    • pp.4272-4279
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    • 2022
  • In this study, a cross section stochastic sampling (S.S.) capability is implemented into both the McCARD continuous energy Monte Carlo code and MIG multiple-correlated data sampling code. The ENDF/B-VII.1 covariance data based 30 group cross section sets and the SCALE6 covariance data based 44 group cross section sets are sampled by the MIG code. Through various uncertainty quantification (UQ) benchmark calculations, the McCARD/MIG results are verified to be consistent with the McCARD stand-alone sensitivity/uncertainty (S/U) results and the XSUSA S.S. results. UQ analyses for Three Mile Island Unit 1, Peach Bottom Unit 2, and Kozloduy-6 fuel pin problems are conducted to provide the uncertainties of keff and microscopic and macroscopic cross sections by the McCARD/MIG code system. Moreover, the SNU S/U formulations for uncertainty propagation in a MC depletion analysis are validated through a comparison with the McCARD/MIG S.S. results for the UAM Exercise I-1b burnup benchmark. It is therefore concluded that the SNU formulation based on the S/U method has the capability to accurately estimate the uncertainty propagation in a MC depletion analysis.