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  • Open Access

    ARTICLE

    The Applications of Order Reduction Methods in Nonlinear Dynamic Systems

    Nan Wu1,#, Kuan Lu1,2,#,*, Yulin Jin2,3,*, Haopeng Zhang1, Yushu Chen2

    Sound & Vibration, Vol.54, No.2, pp. 113-125, 2020, DOI:10.32604/sv.2020.09783 - 09 May 2020

    Abstract Two different order reduction methods of the deterministic and stochastic systems are discussed in this paper. First, the transient proper orthogonal decomposition (T-POD) method is introduced based on the high-dimensional nonlinear dynamic system. The optimal order reduction conditions of the T-POD method are provided by analyzing the rotor-bearing system with pedestal looseness fault at both ends. The efficiency of the T-POD method is verified via comparing with the results of the original system. Second, the polynomial dimensional decomposition (PDD) method is applied to the 2 DOFs spring system considering the uncertain stiffness to study the More >

  • Open Access

    ARTICLE

    Seismic Vulnerability Analysis of Single-Story Reinforced Concrete Industrial Buildings with Seismic Fortification

    Jieping Liu1, Lingxin Zhang1,*, Haohao Zhang2, Tao Liu1

    Structural Durability & Health Monitoring, Vol.13, No.2, pp. 123-142, 2019, DOI:10.32604/sdhm.2019.04486

    Abstract As there is a lack of earthquake damage data for factory buildings with seismic fortifications in China, seismic vulnerability analysis was performed by numerical simulation in this paper. The earthquake-structure analysis model was developed with considering the influence of uncertainties of the ground motion and structural model parameters. The small-size sampling was conducted based on the Latin hypercube sampling and orthogonal design methods. Using nonlinear analysis, the seismic vulnerability curves and damage probability matrix with various seismic fortification intensities (SFI) were obtained. The seismic capacity of the factory building was then evaluated. The results showed… More >

  • Open Access

    ARTICLE

    Probabilistic Performance-Based Optimum Seismic Design Framework: Illustration and Validation

    Yong Li1,*, Joel P. Conte2, Philip E. Gill3

    CMES-Computer Modeling in Engineering & Sciences, Vol.120, No.3, pp. 517-543, 2019, DOI:10.32604/cmes.2019.06269

    Abstract In the field of earthquake engineering, the advent of the performance-based design philosophy, together with the highly uncertain nature of earthquake ground excitations to structures, has brought probabilistic performance-based design to the forefront of seismic design. In order to design structures that explicitly satisfy probabilistic performance criteria, a probabilistic performance-based optimum seismic design (PPBOSD) framework is proposed in this paper by extending the state-of-the-art performance-based earthquake engineering (PBEE) methodology. PBEE is traditionally used for risk evaluation of existing or newly designed structural systems, thus referred to herein as forward PBEE analysis. In contrast, its use… More >

  • Open Access

    ARTICLE

    Uncertain Knowledge Reasoning Based on the Fuzzy Multi Entity Bayesian Networks

    Dun Li1, Hong Wu1, Jinzhu Gao2, Zhuoyun Liu1, Lun Li1, Zhiyun Zheng1,*

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 301-321, 2019, DOI:10.32604/cmc.2019.05953

    Abstract With the rapid development of the semantic web and the ever-growing size of uncertain data, representing and reasoning uncertain information has become a great challenge for the semantic web application developers. In this paper, we present a novel reasoning framework based on the representation of fuzzy PR-OWL. Firstly, the paper gives an overview of the previous research work on uncertainty knowledge representation and reasoning, incorporates Ontology into the fuzzy Multi Entity Bayesian Networks theory, and introduces fuzzy PR-OWL, an Ontology language based on OWL2. Fuzzy PR-OWL describes fuzzy semantics and uncertain relations and gives grammatical… More >

  • Open Access

    ARTICLE

    Modeling of Consumer Buying Behaviour Using Z-Number Concept

    Gunay Sadikoglu

    Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 173-178, 2018, DOI:10.1080/10798587.2017.1327159

    Abstract Consumer behaviour has always been of a great interest in marketing research. The consumer buying behaviour has become an integral part of strategic market planning and includes mental, emotional and physical activities. The consumer behaviour and decision-making process are usually subject to uncertainties related to influences of socio-cultural, psychological and personal factors. In this paper, the Z-number concept is applied for handling uncertainties in analysing the consumer buying behaviour. More >

  • Open Access

    ARTICLE

    Uncertainty Analysis Method of Casing Extrusion Load for Ultra-Deep Wells

    Meng Li1, Kanhua Su1, Zijian Li2, Dongjie Li3, Lifu Wan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.4, pp. 475-495, 2017, DOI:10.3970/cmes.2017.113.475

    Abstract With the consideration of the randomness of complex geologic parameters for ultra-deep wells, an uncertainty analysis method is presented for the extrusion load on casing in ultra-deep wells through complex formation at a certain confidence level. Based on the extrusion load model for casing in ultra-deep wells and the prerequisite of integrity of formation-cement ring-casing, the probability and statistics theory is introduced and the sensitivity analysis on the uncertainty of extrusion load on casing is conducted. The distribution types of each formation parameters are determined statistically. The distribution type and distribution function of the extrusion… More >

  • Open Access

    ARTICLE

    A Dimension-Reduction Interval Analysis Method for Uncertain Problems

    J.C. Tang1, C.M. Fu1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.3, pp. 239-259, 2017, DOI:10.3970/cmes.2017.113.249

    Abstract In this paper, an efficient interval analysis method called dimension-reduction interval analysis (DRIA) method is proposed to calculate the bounds of response functions with interval variables, which provides a kind of solution method for uncertainty analysis problems of complex structures and systems. First, multi-dimensional function is transformed into multiple one-dimensional functions by extending dimension reduction method to the interval analysis problem. Second, all the one-dimensional functions are transformed to standard quadratic form by second order Taylor expansion method. As a result, the multi-dimensional function is approximately represented by the functions that each interval variable occurs More >

  • Open Access

    ARTICLE

    Reliability Analysis for Complex Systems based on Dynamic Evidential Network Considering Epistemic Uncertainty

    Rongxing Duan1, Yanni Lin1, Longfei Hu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.1, pp. 17-34, 2017, DOI:10.3970/cmes.2017.113.015

    Abstract Fault tolerant technology has greatly improved the reliability of modern systems on one hand and makes their failure mechanisms more complex on the other. The characteristics of dynamics of failure, diversity of distribution and epistemic uncertainty always exist in these systems, which increase the challenges in the reliability assessment of these systems significantly. This paper presents a novel reliability analysis framework for complex systems within which the failure rates of components are expressed in interval numbers. Specifically, it uses a dynamic fault tree (DFT) to model the dynamic fault behaviors and copes with the epistemic More >

  • Open Access

    ARTICLE

    Solution of Liouville's Equation for Uncertainty Characterization of the Main Problem in Satellite Theory

    Ryan Weisman3, Manoranjan Majji4, Kyle T. Alfriend5

    CMES-Computer Modeling in Engineering & Sciences, Vol.111, No.3, pp. 269-304, 2016, DOI:10.3970/cmes.2016.111.269

    Abstract This paper presents a closed form solution to Liouville's equation governing the evolution of the probability density function associated with the motion of a body in a central force field and subject to J2. It is shown that the application of transformation of variables formula for mapping uncertainties is equivalent to the method of characteristics for computing the time evolution of the probability density function that forms the solution of the Liouville's partial differential equation. The insights derived from the nature of the solution to Liouville's equation are used to reduce the dimensionality of uncertainties More >

  • Open Access

    ARTICLE

    Multidirectional Gaussian Mixture Models for Nonlinear Uncertainty Propagation

    V. Vittaldev1, R. P. Russell2

    CMES-Computer Modeling in Engineering & Sciences, Vol.111, No.1, pp. 83-117, 2016, DOI:10.3970/cmes.2016.111.083

    Abstract Monte Carlo simulations are an accurate but computationally expensive procedure for approximating the resultant non-Gaussian probability density function (PDF) after propagation of an initial Gaussian PDF through a nonlinear function. Univariate splitting libraries for Gaussian Mixture Models (GMMs) exist with up to five elements in the literature. The number of splits are extended in the present work by generating three homoscedastic univariate splitting libraries with up to 39 elements. Mulitvariate GMMs are typically handled with splits along a single direction. Instead, we generate a regular multidirectional grid over the initial multivariate Gaussian distribution by recursively… More >

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