Modeling General Hysteresis Behavior and Random Vibration Application

Baber, Thomas T.; Noori, M.

doi:10.1115/1.3269364

Cited by 142 publications

(56 citation statements)

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“…where the first part of the expression is the pinching inducing function and the second part is the BBW hysteresis model [8,22]. The general shape of the hysteresis loop is determined by the selection of parameters/3, 7, A and n. The parameter/3 controls the total energy dissipation for a cycle (area inside the loop).…”

Section: Bbw Modelmentioning

confidence: 99%

“…where (10 is the maximum value of (1; P controls the development rate of (1; and A, £0 and 6~ control the evolution of (2 [8]. A typical SEP force-displacement curve is shown in Figure 2, In depth studies of this model are given by Baber and Noori [8,9].…”

Section: Bbw Modelmentioning

confidence: 99%

“…A typical SEP force-displacement curve is shown in Figure 2, In depth studies of this model are given by Baber and Noori [8,9]. As mentioned previously, the It6-based solution method is based on a stochastic differential formulation of the equation of motion.…”

Section: Bbw Modelmentioning

confidence: 99%

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Application of an It�-based approximation method to random vibration of a pinching hysteretic system

Noori

Padua²,

Davoodi

1992

Nonlinear Dyn

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In this paper, an extension of the Cumulant-Neglect closure scheme is utilized for the random vibration analysis of a single degree of freedom system with a general pinching hysteresis restoring force. The hysteresis element used in the system model can simulate commonly observed forms of stiffness, strength and pinching degradations. The second order statistics of the system response to a stationary Gaussian white noise input are derived using an It6-based approximation technique. The validity of these response statistics are then verified by comparing them to Monte Carlo simulation results. The numerical studies performed for different combinations of degradation parameters and excitation levels show that the response estimates obtained by this solution method are in good agreement with Monte Carlo simulation. These studies also indicate the applicability of this technique for response analysis of complicated forms of non-linearities.

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Section: Bbw Modelmentioning

confidence: 99%

Section: Bbw Modelmentioning

confidence: 99%

See 1 more Smart Citation

Application of an It�-based approximation method to random vibration of a pinching hysteretic system

Noori

Padua²,

Davoodi

1992

Nonlinear Dyn

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“…An extension of this solution was given by Barber and Noori [2]. Further, a solution for the classical assumption of a bilinear hysteresis, which is used to describe the behavior of steel with large plastic cycles, was found by Suzuki and Minai [3] later on.…”

Section: Introductionmentioning

confidence: 96%

A Strategy for the Prediction of the Response of Hysteretic Systems: A Base for Capacity Assessment of Buildings under Seismic Load

Cavaleri¹,

Trapani²,

Macaluso³

et al. 2014

TOBCTJ

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A statistical non linearization method is used to approximate systems modeled by the Bouc differential equation and excited by a Gaussian white noise external load. To this aim restricted potential models (RPM) are used, which are suitable for an extended number of nonlinear problems as have been proved several times. Since the solution of RPM is known by the probabilistic point of view, all statistical characteristics can be derived at once with advantages by the computational point of view. Hence, this paper discusses the possibility to determine sets of parameters characterizing potential models that are valid for describing a hysteretic behavior. In this way the characterization of the hysteretic behavior of a system can be performed with computational efforts lower than that normally requested.

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“…Further, n i , the power factor, determines the sharpness of the curve from elastic to plastic force-deflection behaviour of each storey. Finally, ) (t r i & is the velocity of storey i relative to 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 arising from deteriorating systems [19]. In this study, the classical Bouc-Wen model in conjunction with a variable structural stiffness has been used to model nonlinearities arising from both the hysteretic behaviour of the structure and degradation.…”

Section: A R T R T Z T Z T R T Z T Z T Ymentioning

confidence: 99%

LMS-based approach to structural health monitoring of nonlinear hysteretic structures

Nayyerloo

Chase

MacRae

et al. 2010

Structural Health Monitoring

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Structural health monitoring (SHM) algorithms based on adaptive least mean squares (LMS) filtering theory can directly identify time-varying changes in structural stiffness in real-time in a computationally efficient fashion. However, better metrics of seismic structural damage and future utility after an event are related to permanent and total plastic deformations. This study presents a modified LMS-based SHM method and a novel two-step structural identification technique using a baseline nonlinear Bouc—Wen structural model to directly identify changes in stiffness due to damage as well as plastic or permanent deflections. The algorithm is designed to be computationally efficient; therefore it can work in real-time. An in silico single-degree-of-freedom (SDOF) nonlinear shear-type structure is used to prove the concept. The efficiency of the proposed SHM algorithm in identifying stiffness changes and plastic/permanent deflections is assessed under different ground motions using a suite of 20 different ground acceleration records. The results show that in a realistic scenario with fixed filter tuning parameters, the proposed LMS-based SHM algorithm identifies stiffness changes to within 10% of true values within 2s. Permanent deflection is identified to within 14% of the actual as-modeled value using noise-free simulation-derived structural responses. This latter value provides important post-event information on the future serviceability, safety, and repair cost.

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Modeling General Hysteresis Behavior and Random Vibration Application

Cited by 142 publications

References 0 publications

Application of an It�-based approximation method to random vibration of a pinching hysteretic system

Application of an It�-based approximation method to random vibration of a pinching hysteretic system

A Strategy for the Prediction of the Response of Hysteretic Systems: A Base for Capacity Assessment of Buildings under Seismic Load

LMS-based approach to structural health monitoring of nonlinear hysteretic structures

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