Sfoglia per Soggetto "Structural dynamics"
Items 1-20 di 67
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Bayesian damage characterization based on probabilistic model of scattering coefficients and hybrid wave finite element model scheme
(2019)Ultrasonic Guided Wave(GW) has been proven to be sensitive to small damage. Motivated by the fact that the quantitative relationship between wave scattering and damage intensity can be described by scattering properties, ... -
Bayesian finite element model updating
(2019)In this chapter, the implementation of the reduced-order models within Bayesian finite element model updating is explored. The Bayesian framework for model parameter estimation, model selection, and robust predictions of ... -
A bayesian framework for optimal experimental design in structural dynamics
(2016)A Bayesian framework for optimal experimental design in structural dynamics is presented. The optimal design is based on an expected utility function that measures the value of the information arising from alternative ... -
Bayesian Hierarchical Models for Uncertainty Quantification in Structural Dynamics
(2014)The Bayesian framework for hierarchical modeling is applied to quantify uncertainties, arising mainly due to manufacturing variability, for a group of identical structural components. Parameterized Gaussian models of ... -
Bayesian optimal experimental design for parameter estimation and response predictions in complex dynamical systems
(2017)A Bayesian optimal experimental design (OED) framework is revisited and applied to a number of structural dynamics problems. The objective is to optimize the design of the experiment such that the most informative data are ... -
Bayesian optimal experimental design using asymptotic approximations
(2017)Bayesian optimal experimental design (OED) tools for model parameter estimation and response predictions in structural dynamics include sampling (Huan and Marzouk, J. Comput. Phys., 232:288–317, 2013) and asymptotic ... -
Bayesian uncertainty quantification and propagation in nonlinear structural dynamics
(2013)A Bayesian uncertainty quantification and propagation (UQ&P) framework is presented for identifying nonlinear models of dynamic systems using vibration measurements of their components. The measurements are taken to be ... -
Bayesian uncertainty quantification and propagation in nonlinear structural dynamics
(2009)Nonlinear modelling and parametric identification of an experimental vehicle model, are employed in this paper. The composite structure of the vehicle model is split into a frame substructure and to four support substructures. ... -
A combined numerical/experimental prediction method for urban railway vibration
(2017)Railway-induced ground vibrations can cause negative effects to people/structures located in urban areas. One of the main sources of these vibrations is from the large vehicle forces generated when train wheels impact local ... -
Computational Framework for Online Estimation of Fatigue Damage using Vibration Measurements from a Limited Number of Sensors
(2017)This study proposes a computational framework for the online estimation of fatigue damage using operational vibration measurements from a limited number of sensors. To infer the stress response time histories required for ... -
Computationally efficient hierarchical Bayesian modeling framework for learning embedded model uncertainties
(2020)A hierarchical Bayesian modeling (HBM) framework has recently been developed for estimating the uncertainties in the parameters of physics-based models of systems, as well as propagating these uncertainties to estimate the ... -
Damage detection in flexible plates through reduced-order modeling and hybrid particle-Kalman filtering
(2016)Health monitoring of lightweight structures, like thin flexible plates, is of interest in several engineering fields. In this paper, a recursive Bayesian procedure is proposed to monitor the health of such structures through ... -
Data features-based likelihood-informed Bayesian finite element model updating
(2019)A new formulation for likelihood-informed Bayesian inference is proposed in this work based on probability models introduced for the features between the measurements and model predictions. The formulation applies to both ... -
Data-driven uncertainty quantification and propagation in structural dynamics through a hierarchical Bayesian framework
(2020)In the presence of modeling errors, the mainstream Bayesian methods seldom give a realistic account of uncertainties as they commonly underestimate the inherent variability of parameters. This problem is not due to any ... -
Design and assessment of steel and steel-concrete composite structures: Efficacy of EN1998 design procedure
(2013)Design codes for seismic constructions allow the realization of structures able to dissipate energy through cyclic plastic deformations localized in specific zones, selected to involve the largest number of structural ... -
Efficient techniques for bayesian inverse modeling of large-order computational models
(2013)Bayesian tools for inverse modeling are based on asymptotic approximations and Stochastic Simulation Algorithms (SSA). Such tools require a number of moderate to large number of system re-analyses. For large-order numerical ... -
Experimental and numerical study of the behaviour of high dissipation metallic devices for the strengthening of existing structures
(2011)The use of steel bracing systems for the strengthening of existing reinforced concrete (RC) frames may lead to increase of both strength and stiffness. However, in most of the cases the main target is the increase of the ... -
Experimental investigation of jet pulse control on flexible vibrating structures
(2016)The feasibility of applying on-line fluid jet pulses to actively control the vibrations of flexible structures subjected to harmonic and earthquake-like base excitations provided by a shake table is explored. The operating ... -
Experimental validation of the dual kalman filter for online and real-time state and input estimation
(2015)In this study, a novel dual implementation of the Kalman filter is proposed for simultaneous estimation of the states and input of structures via acceleration measurements. In practice, the uncertainties stemming from the ... -
Fast Bayesian updating of large-scale finite element models using CMS technique and surrogate models
(2012)A Bayesian probabilistic framework for parameter estimation is applied for updating large-order finite element models of structures using response measurements. Fast and accurate component mode synthesis (CMS) techniques ...