On the dynamics of the ultra-fast rotating cantilever orthotropic piezoelectric nanodisk based on nonlocal strain gradient theory
MSH Al-Furjan, R Dehini, M Khorami, M Habibi… - Composite …, 2021 - Elsevier
In this article, amplitude, and vibrational characteristics of a rotating orthotropic piezoelectric
nanodisk are presented. The centrifugal and Coriolis effects due to the rotation are …
nanodisk are presented. The centrifugal and Coriolis effects due to the rotation are …
Bayesian model updating of a coupled-slab system using field test data utilizing an enhanced Markov chain Monte Carlo simulation algorithm
Abstract Markov chain Monte Carlo (MCMC) simulation is applied for model updating of the
coupled-slab system of a building structure based on field test data following the Bayesian …
coupled-slab system of a building structure based on field test data following the Bayesian …
Efficiency of the slime mold algorithm for damage detection of large‐scale structures
Optimization‐based methods are increasingly being implemented for structural damage
detection problems through the minimization of the objective functions based on vibration …
detection problems through the minimization of the objective functions based on vibration …
PC-Kriging-powered parallelizing Bayesian updating for stochastic vehicle-track dynamical system with contact force measurements and Gaussian process …
High-precision vehicle-track coupled dynamical models play a vital role in assessing the
running safety of the vehicle, tracking fatigue behavior, and establishing a digital twin for …
running safety of the vehicle, tracking fatigue behavior, and establishing a digital twin for …
Probabilistic updating of building models using incomplete modal data
This paper investigates a new probabilistic strategy for Bayesian model updating using
incomplete modal data. Direct mode matching between the measured and the predicted …
incomplete modal data. Direct mode matching between the measured and the predicted …
Adaptive Markov chain Monte Carlo algorithms for Bayesian inference: recent advances and comparative study
Condition assessments of structures require prediction models such as empirical model and
numerical simulation model. Generally, these prediction models have model parameters to …
numerical simulation model. Generally, these prediction models have model parameters to …
A new Gibbs sampling based algorithm for Bayesian model updating with incomplete complex modal data
Abstract Model updating using measured system dynamic response has a wide range of
applications in system response evaluation and control, health monitoring, or reliability and …
applications in system response evaluation and control, health monitoring, or reliability and …
[HTML][HTML] Separable shadow Hamiltonian hybrid Monte Carlo for Bayesian neural network inference in wind speed forecasting
Accurate wind speed and consequently wind power forecasts form a critical enabling tool for
large scale wind energy adoption. Probabilistic machine learning models such as Bayesian …
large scale wind energy adoption. Probabilistic machine learning models such as Bayesian …
Bayesian updating using accelerated Hamiltonian Monte Carlo with gradient-enhanced Kriging model
Bayesian methods have been widely used to improve the accuracy of finite element model
in civil engineering. However, Bayesian methods generally suffer from the computational …
in civil engineering. However, Bayesian methods generally suffer from the computational …
A damage localization approach for rahmen bridge based on convolutional neural network
Damage localization is the process of detecting the location of damage using a structural
health monitoring system. However, existing damage localization methods cannot be used …
health monitoring system. However, existing damage localization methods cannot be used …