Results 91 to 100 of about 1,345 (197)
Ghost effect from Boltzmann theory
Communications on Pure and Applied Mathematics, Volume 79, Issue 3, Page 558-675, March 2026.Abstract Taking place naturally in a gas subject to a given wall temperature distribution, the “ghost effect” exhibits a rare kinetic effect beyond the prediction of classical fluid theory and Fourier law in such a classical problem in physics. As the Knudsen number ε$\varepsilon$ goes to zero, the finite variation of temperature in the bulk is ...
Raffaele Esposito +3 more
wiley +1 more source
Engineering Reports, Volume 8, Issue 3, March 2026.Implementation of deterministic and probabilistic regression algorithms on an additive manufacturing dataset for prediction of dimensional accuracy—difference from target (DFT), which is the dimensional deviation of a manufactured part from a reference computer‐aided design geometry.
Dipayan Sanpui +4 more
wiley +1 more source
Engineering Reports, Volume 8, Issue 3, March 2026.Agricultural intensification and the increasing use of fertilizers and irrigation have significantly improved crop productivity but have also led to growing concerns over groundwater contamination and inefficient water usage. When solutes like nitrates and pesticides seep past the root zone, they not only deplete soil fertility but also endanger the ...
Wubale Demis Alamirew, Ephrem Yetbarek
wiley +1 more source
A Mathematical Model for Two‐Phase Flow in Confined Environments: Numerical Solution and Validation
International Journal for Numerical Methods in Fluids, Volume 98, Issue 3, Page 306-320, March 2026.We present a numerical framework based on the Cahn‐Hilliard‐Navier‐Stokes (CHNS) model to simulate biphasic flow in confined environments. After deriving the mathematical model, we develop the weak form of the system of PDEs using a pedagogical approach to enable its implementation in FEniCS.
Giuseppe Sciumè +3 more
wiley +1 more source
Optimal Control Applications and Methods, Volume 47, Issue 2, Page 570-588, March/April 2026.Implicit third‐order Peer two‐step methods that are superconvergent for variable stepsizes have the potential to significantly improve the efficiency of solving large‐scale ODE‐constrained optimal control problems. These include real‐world applications in medical treatment planning for prostate cancer, such as the design of effective three‐dose drug ...
Jens Lang, Bernhard A. Schmitt
wiley +1 more source
Numerical and Analytical Study of Elastic Parameters in Linearized Micropolar Elasticity
Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 1, March 2026.ABSTRACT The effect of elastic parameters in the linearized theory of micropolar elasticity on observable deformation is analyzed analytically and numerically. Specifically, a shear deformation boundary value problem is studied to explore the physical implications of a micropolar formulation. Our new analytical solution for the two‐dimensional shearing
Lucca Schek, Wolfgang H. Müller
wiley +1 more source
BiLO: Bilevel Local Operator Learning for PDE Inverse Problems. Part I: PDE-Constrained Optimization
We propose a new neural network based method for solving inverse problems for partial differential equations (PDEs) by formulating the PDE inverse problem as a bilevel optimization problem. At the upper level, we minimize the data loss with respect to the PDE parameters.
Zhang, Ray Zirui +3 more
openaire +2 more sources
Latent Neural Operator for Solving Forward and Inverse PDE Problems
Advances in Neural Information Processing Systems 37Neural operators effectively solve PDE problems from data without knowing the explicit equations, which learn the map from the input sequences of observed samples to the predicted values. Most existing works build the model in the original geometric space, leading to high computational costs when the number of sample points is large.
Wang, Tian, Wang, Chuang
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A Generalization Error Bound of Physics‐Informed Neural Networks for Ecological Diffusion Models
Stat, Volume 15, Issue 1, March 2026.ABSTRACT Ecological diffusion equations (EDEs) are partial differential equations (PDEs) that model spatiotemporal dynamics, often applied to wildlife diseases. Derived from ecological mechanisms, EDEs are useful for forecasting, inference, and decision‐making, such as guiding surveillance strategies for wildlife diseases.
Juan Francisco Mandujano Reyes +4 more
wiley +1 more source
Inverse problems for infinite-dimensional transport PDEs on Wasserstein space
We develop a foundational framework for inverse problems governed by evolutionary partial differential equations (PDEs) on the Wasserstein space of probability measures. While the forward problems for such transport-type PDEs have been extensively and intensively studied, their corresponding inverse problems--which aim to reconstruct unknown operators,
Liu, Hongyu +2 more
openaire +2 more sources