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Langrangian finite element and finite difference methods for poisson problems [PDF]
, 1974 The use of Lagrangian finite element methods for solving a Poisson problem produces systems of linear equations, the global stiffness equations. The components of the vectors which are the solutions of these systems are approximations to the exact ...
Whiteman, J R
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Differential Equations and Nonlinear Mechanics, 2007 The stochastic finite element method (SFEM) is employed for solving stochastic one-dimension time-dependent differential equations with random coefficients. SFEM is used to have a fixed form of linear algebraic equations for polynomial chaos coefficients
M. M. Saleh, I. L. El-Kalla, M. M. Ehab
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Foundations, 2023 We investigate the application of the Galerkin finite element method to approximate a stochastic semilinear space–time fractional wave equation. The equation is driven by integrated additive noise, and the time fractional order α∈(1,2).
Bernard A. Egwu, Yubin Yan
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Fuzzy finite element analysis based on the transformation between fuzzy and random variables
Vietnam Journal of Science, Technology and Engineering, 2022 In this paper, a fuzzy finite element method (FFEM) for determining the responses of structures is proposed by using the transformation between fuzzy and random variables.
Tuan Hung Nguyen, Huynh Xuan Le
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Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
International Journal of Adaptive Control and Signal Processing, EarlyView.This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
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Advances in Mechanical Engineering, 2017 This article presents the development of a finite element model, which considers stochastic tow waviness using a Markov Chain algorithm and non-linear material properties using Binary Model, to predict the stress–strain and fracture behaviour of plain ...
Mingming Chen +3 more
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dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
A Stochastic Wavelet Finite Element Method for 1D and 2D Structures Analysis
Shock and Vibration, 2014 A stochastic finite element method based on B-spline wavelet on the interval (BSWI-SFEM) is presented for static analysis of 1D and 2D structures in this paper. Instead of conventional polynomial interpolation, the scaling functions of BSWI are employed
Xingwu Zhang +4 more
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Solving the stochastic growth model with a finite element method [PDF]
Journal of Economic Dynamics and Control, 1993 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source