• Title/Summary/Keyword: Probabilistic Method.

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A probabilistic seismic demand model for required separation distance of adjacent structures

  • Rahimi, Sepideh;Soltani, Masoud
    • Earthquakes and Structures
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    • v.22 no.2
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    • pp.147-155
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    • 2022
  • Regarding the importance of seismic pounding, the available standards and guidelines specify minimum separation distance between adjacent buildings. However, the rules in this field are generally based on some simple assumptions, and the level of confidence is uncertain. This is attributed to the fact that the relative response of adjacent structures is strongly dependent on the frequency content of the applied records and the Eigen frequencies of the adjacent structures as well. Therefore, this research aims at investigating the separation distance of the buildings through a probabilistic-based algorithm. In order to empower the algorithm, the record-to-record uncertainties, are considered by probabilistic approaches; besides, a wide extent of material nonlinear behaviors can be introduced into the structural model by the implementation of the hysteresis Bouc-Wen model. The algorithm is then simplified by the application of the linearization concept and using the response acceleration spectrum. By implementing the proposed algorithm, the separation distance in a specific probability level can be evaluated without the essential need of performing time-consuming dynamic analyses. Accuracy of the proposed method is evaluated using nonlinear dynamic analyses of adjacent structures.

A new human-robot interaction method using semantic symbols

  • Park, Sang-Hyun;Hwang, Jung-Hoon;Kwon, Dong-Soo
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.2005-2010
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    • 2004
  • As robots become more prevalent in human daily life, situations requiring interaction between humans and robots will occur more frequently. Therefore, human-robot interaction (HRI) is becoming increasingly important. Although robotics researchers have made many technical developments in their field, intuitive and easy ways for most common users to interact with robots are still lacking. This paper introduces a new approach to enhance human-robot interaction using a semantic symbol language and proposes a method to acquire the intentions of robot users. In the proposed approach, each semantic symbol represents knowledge about either the environment or an action that a robot can perform. Users'intentions are expressed by symbolized multimodal information. To interpret a users'command, a probabilistic approach is used, which is appropriate for interpreting a freestyle user expression or insufficient input information. Therefore, a first-order Markov model is constructed as a probabilistic model, and a questionnaire is conducted to obtain state transition probabilities for this Markov model. Finally, we evaluated our model to show how well it interprets users'commands.

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A Study on Probabilistic Response-time Analysis for Real-time Control Systems (실시간 제어시스템의 확률적 응답시간 해석에 관한 연구)

  • Han, Jae-Hyun;Shin, Min-Suk;Hwang, In-Yong;SunWoo, Myoung-Ho
    • Transactions of the Korean Society of Automotive Engineers
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    • v.14 no.3
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    • pp.186-195
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    • 2006
  • In real-time control systems, the traditional timing analysis based on worst-case response-time(WCRT) is too conservative for the firm and soft real-time control systems, which permit the maximum utilization factor greater than one. We suggested a probabilistic analysis method possible to apply the firm and soft real-time control systems under considering dependency relationship between tasks. The proposed technique determines the deadline miss probability(DMP) of each task from computing the average response-time distribution under a fixed-priority scheduling policy. The method improves the predictable ability forthe average performance and the temporal behavior of real-time control systems.

Reliability-Based Shape Optimization Under the Displacement Constraints (변위 제한 조건하에서의 신뢰성 기반 형상 최적화)

  • Oh, Young-Kyu;Park, Jae-Yong;Im, Min-Gyu;Park, Jae-Yong;Han, Seog-Young
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.5
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    • pp.589-595
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    • 2010
  • This paper presents a reliability-based shape optimization (RBSO) using the evolutionary structural optimization (ESO). An actual design involves uncertain conditions such as material property, operational load, poisson's ratio and dimensional variation. The deterministic optimization (DO) is obtained without considering of uncertainties related to the uncertainty parameters. However, the RBSO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraint is satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability-based shape design optimization method is proposed by utilization the reliability index approach (RIA), performance measure approach (PMA), single-loop single-vector (SLSV), adaptive-loop (ADL) are adopted to evaluate the probabilistic constraint. In order to apply the ESO method to the RBSO, a sensitivity number is defined as the change of strain energy in the displacement constraint. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization.

Learning Similarity with Probabilistic Latent Semantic Analysis for Image Retrieval

  • Li, Xiong;Lv, Qi;Huang, Wenting
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.4
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    • pp.1424-1440
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    • 2015
  • It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

In-plane response of masonry infilled RC framed structures: A probabilistic macromodeling approach

  • De Domenico, Dario;Falsone, Giovanni;Laudani, Rossella
    • Structural Engineering and Mechanics
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    • v.68 no.4
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    • pp.423-442
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    • 2018
  • In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.

Probabilistic seismic hazard assessment of Sanandaj, Iran

  • Ghodrati Amiri, Gholamreza;Andisheh, Kaveh;Razavian Amrei, Seyed Ali
    • Structural Engineering and Mechanics
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    • v.32 no.4
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    • pp.563-581
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    • 2009
  • In this paper, the peak horizontal ground acceleration over the bedrock (PGA) is calculated by a probabilistic seismic hazard assessment (PSHA). For this reason, at first, all the occurred earthquakes in a radius of 200 km of Sanandaj city have been gathered. After elimination of the aftershocks and foreshocks, the main earthquakes were taken into consideration to calculate the seismic parameters (SP) by Kijko (2000) method. The seismotectonic model of the considered region and the seismic sources of the region have been modeled. In this research, Sanandaj and its vicinity has been meshed as an 8 (vertical lines) * 10 (horizontal lines) and the PGA is calculated for each point of the mesh using the logic tree method and the five attenuation relationships (AR) with different weighted coefficient. These calculations have been performed by the Poisson distribution of four hazard levels. Then by using it, four regional maps of the seismic hazard regions have been provided for Sanandaj and its vicinity. The results show that the maximum and minimum value of PGA for the return periods of 75, 225, 475, 2475 years are (0.114, 0.074) (0.157, 0.101), (0.189, 0.121) and (0.266, 0.170), respectively.

A Method for Operational Safety Assessment of a Deep Geological Repository for Spent Fuels

  • Jeong, Jongtae;Cho, Dong-Keun
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.18 no.spc
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    • pp.63-74
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    • 2020
  • The operational safety assessment is an important part of a safety case for the deep geological repository of spent fuels. It consists of different stages such as the identification of initiating events, event tree analysis, fault tree analysis, and evaluation of exposure doses to the public and radiation workers. This study develops a probabilistic safety assessment method for the operational safety assessment and establishes an assessment framework. For the event and fault tree analyses, we propose the advanced information management system for probabilistic safety assessment (AIMS-PSA Manager). In addition, we propose the Radiological Safety Analysis Computer (RSAC) program to evaluate exposure doses to the public and radiation workers. Furthermore, we check the applicability of the assessment framework with respect to drop accidents of a spent fuel assembly arising out of crane failure, at the surface facility of the KRS+ (KAERI Reference disposal System for SNFs). The methods and tools established through this study can be used for the development of a safety case for the KRS+ system as well as for the design modification and the operational safety assessment of the KRS+ system.

An Optimal Installation Strategy for Allocating Energy Storage Systems and Probabilistic-Based Distributed Generation in Active Distribution Networks

  • Sattarpour, Tohid;Tousi, Behrouz
    • Transactions on Electrical and Electronic Materials
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    • v.18 no.6
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    • pp.350-358
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    • 2017
  • Recently, owing to increased interest in low-carbon energy supplies, renewable energy sources such as photovoltaics and wind turbines in distribution networks have received considerable attention for generating clean and unlimited energy. The presence of energy storage systems (ESSs) in the promising field of active distribution networks (ADNs) would have direct impact on power system problems such as encountered in probabilistic distributed generation (DG) model studies. Hence, the optimal procedure is offered herein, in which the simultaneous placement of an ESS, photovoltaic-based DG, and wind turbine-based DG in an ADN is taken into account. The main goal of this paper is to maximize the net present value of the loss reduction benefit by considering the price of electricity for each load state. The proposed framework consists of a scenario tree method for covering the existing uncertainties in the distribution network's load demand as well as DG. The collected results verify the considerable effect of concurrent installation of probabilistic DG models and an ESS in defining the optimum site of DG and the ESS and they demonstrate that the optimum operation of an ESS in the ADN is consequently related to the highest value of the loss reduction benefit in long-term planning as well. The results obtained are encouraging.

A Study on the Decision of Optimum Installed Reserve Rate by Loss of Load Expectation (공급지장기대치에 의한 적정설비예비율 결정에 관한 연구)

  • Park, Jeong-Je;Liang, Wu;Choi, Jae-Seok;Cha, Jun-Min;Yun, Yong-Bum
    • Proceedings of the KIEE Conference
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    • 2008.07a
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    • pp.103-104
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    • 2008
  • This paper proposes an alternative methodology for deciding an optimum deterministic reliability level (IRR; Installed Reserve Rate) by using probabilistic reliability criterion (LOLE; Loss of Load Expectation). Additionally, case studies using the proposed method induce the characteristics of relationship between the probabilistic reliability index (LOLE) and deterministic reliability index (IRR) for 2008 year in Korea power system. The case study presents a possibility that an optimum IRR level in Korea can be assessed using the proposed method. Korea power system has been using the LOLE criterion to determine the adequacy of installed capacity (ICAP) requirement. The criterion in Korea is that the loss of load expectation shall not exceed the available capacity more than five day in ten years (=0.5[days/year]). The probabilistic reliability evaluation and production cost simulation program which is called PRASim is used in order to evaluate the relationship and optimum IRR in this paper.

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