Results 71 to 80 of about 37,100 (232)

Solving inverse source problems for linear PDEs using sparse sensor measurements

open access: yes2016 50th Asilomar Conference on Signals, Systems and Computers, 2016
Many physical phenomena across several applications can be described by partial differential equations (PDEs). In these applications, sensors collect sparse samples of the resulting phenomena with the aim of detecting its cause/source, using some intelligent data analysis tools on the samples.
Murray-Bruce, J, Dragotti, PL
openaire   +2 more sources

Impact of Uncertain Parameters on Navier–Stokes Equations With Heat Transfer via Polynomial Chaos Expansion

open access: yesInternational Journal for Numerical Methods in Fluids, EarlyView.
This study investigates the impact of uncertain parameters on Navier–Stokes equations coupled with heat transfer using the Intrusive Polynomial Chaos Method (IPCM). Sensitivity equations are formulated for key input parameters, such as viscosity and thermal diffusivity, and solved numerically using the Finite Element‐Volume method.
N. Nouaime   +3 more
wiley   +1 more source

Direct Numerical Simulation of Magnetohydrodynamic Slip‐Flow Past a Stretching Surface Using Physics‐Informed Neural Network

open access: yesHeat Transfer, EarlyView.
ABSTRACT Traditional numerical methods, such as finite difference methods (FDM), finite element methods (FEM), and spectral methods, often face meshing challenges and high computational cost for solving nonlinear coupled differential equations. Machine learning techniques, specifically Physics‐informed machine learning, address these obstacles by ...
Ahmad, Feroz Soomro, Husna Zafar
wiley   +1 more source

Application of the inverse Laplace transform techniques to solve the generalized Bagley–Torvik equation including Caputo’s fractional derivative

open access: yesPartial Differential Equations in Applied Mathematics
This article employs the Laplace transform approach to solve the Bagley–Torvik equation including Caputo’s fractional derivative. Laplace transform is a powerful method for enabling solving integer and non-integer order ODEs and PDEs in engineering and ...
Dania Santina   +4 more
doaj   +1 more source

A General Method for the Solution of Inverse Problems in Transport Phenomena

open access: yesChemical Engineering Transactions, 2015
The typical inverse problems in transport phenomena are given by partial differential equations with unknown boundary conditions, which are to be estimated from measurements corresponding to solutions of the PDEs or of their gradients.
M. Vocciante, A. Reverberi, V. Dovi
doaj   +1 more source

On inverse problems for several coupled PDE systems arising in mathematical biology

open access: yesJournal of Mathematical Biology, 2023
In this paper, we propose and study several inverse problems of identifying/determining unknown coefficients for a class of coupled PDE systems by measuring the average flux data on part of the underlying boundary. In these coupled systems, we mainly consider the non-negative solutions of the coupled equations, which are consistent with realistic ...
Ming-Hui Ding   +2 more
openaire   +3 more sources

Using physics‐informed neural networks to quantify submarine groundwater discharge under high‐frequency tidal dynamics using heat as a tracer

open access: yesLimnology and Oceanography: Methods, EarlyView.
Abstract Estimating exchange rates of submarine groundwater discharge (SGD) at high temporal resolution over extended periods remains challenging, particularly when using heat as a tracer in highly dynamic environments such as tidal systems. Currently available heat transport models struggle to accurately quantify SGD exchange rates in these settings ...
S. Frei   +3 more
wiley   +1 more source

Numerical differentiation of fractional order derivatives based on inverse source problems of hyperbolic equations

open access: yesMathematical Modelling and Analysis
In this paper, we mainly study the numerical differentiation problem of computing the fractional order derivatives from noise data of a single variable function.
Zewen Wang   +3 more
doaj   +1 more source

CUQIpy: II. Computational uncertainty quantification for PDE-based inverse problems in Python [PDF]

open access: hybridInverse Problems
Abstract Inverse problems, particularly those governed by Partial Differential Equations (PDEs), are prevalent in various scientific and engineering applications, and uncertainty quantification (UQ) of solutions to these problems is essential for informed decision-making.
Amal Alghamdi   +6 more
openalex   +5 more sources

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