Enhanced framework for solving general energy equations based on metropolis-hasting Markov chain Monte Carlo

ZY Zhu, BH Gao, ZT Niu, YT Ren, MJ He… - International Journal of …, 2024 - Elsevier
Due to the widespread presence of heat and mass transfer phenomena in industrial
applications, numerous studies have been devoted to the accurate solution of energy …

The analysis of parameter uncertainty on performance and reliability of photovoltaic cells

F Zhang, M Wu, X Hou, C Han, X Wang, Z Liu - Journal of Power Sources, 2021 - Elsevier
In engineering practice, the parameters affecting the output of a photovoltaic cell such as its
irradiation intensity, surface temperature, current temperature coefficient, series resistance …

Rational design of field-effect sensors using partial differential equations, Bayesian inversion, and artificial neural networks

A Khodadadian, M Parvizi, M Teshnehlab, C Heitzinger - Sensors, 2022 - mdpi.com
Silicon nanowire field-effect transistors are promising devices used to detect minute
amounts of different biological species. We introduce the theoretical and computational …

A multilevel Monte Carlo finite element method for the stochastic Cahn–Hilliard–Cook equation

A Khodadadian, M Parvizi, M Abbaszadeh… - Computational …, 2019 - Springer
In this paper, we employ the multilevel Monte Carlo finite element method to solve the
stochastic Cahn–Hilliard–Cook equation. The Ciarlet–Raviart mixed finite element method is …

Jacobi polynomials for the numerical solution of multi-dimensional stochastic multi-order time fractional diffusion-wave equations

MH Heydari, S Zhagharian, M Razzaghi - Computers & Mathematics with …, 2023 - Elsevier
In this paper, the one-and two-dimensional stochastic multi-order fractional diffusion-wave
equations are introduced and a collocation procedure based on the shifted Jacobi …

Unbiased multilevel Monte Carlo: Stochastic optimization, steady-state simulation, quantiles, and other applications

JH Blanchet, PW Glynn, Y Pei - arXiv preprint arXiv:1904.09929, 2019 - arxiv.org
We present general principles for the design and analysis of unbiased Monte Carlo
estimators in a wide range of settings. Our estimators posses finite work-normalized …

An adaptive multilevel Monte Carlo algorithm for the stochastic drift–diffusion–Poisson system

A Khodadadian, M Parvizi, C Heitzinger - Computer Methods in Applied …, 2020 - Elsevier
We present an adaptive multilevel Monte Carlo algorithm for solving the stochastic drift–
diffusion–Poisson system with non-zero recombination rate. The a-posteriori error is …

Bayesian inversion for nanowire field-effect sensors

A Khodadadian, B Stadlbauer, C Heitzinger - Journal of Computational …, 2020 - Springer
Nanowire field-effect sensors have recently been developed for label-free detection of
biomolecules. In this work, we introduce a computational technique based on Bayesian …

Three-dimensional optimal multi-level Monte–Carlo approximation of the stochastic drift–diffusion–Poisson system in nanoscale devices

A Khodadadian, L Taghizadeh, C Heitzinger - Journal of Computational …, 2018 - Springer
The three-dimensional stochastic drift–diffusion–Poisson system is used to model charge
transport through nanoscale devices in a random environment. Applications include …

Meshless local numerical procedure based on interpolating moving least squares approximation and exponential time differencing fourth-order Runge–Kutta …

M Abbaszadeh, M Dehghan - Engineering with Computers, 2022 - Springer
The main propose of this investigation is to develop an interpolating meshless numerical
procedure for solving the stochastic parabolic interface problems. The present numerical …