Results 21 to 30 of about 25,964 (155)
Advanced Intelligent Discovery, EarlyView.We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang +4 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez +4 more
wiley +1 more source
Asia-Pacific Journal of Chemical Engineering, EarlyView.ABSTRACT This paper presents a comprehensive numerical analysis of magnetohydrodynamic (MHD) Casson nanofluid movement over a permeable, linearly stretching sheet, integrating the contributions of non‐uniform heat generation or absorption and chemical interaction.
Manoj Kumar Sahoo +3 more
wiley +1 more source
Computing Solution Operators of Boundary-value Problems for Some Linear Hyperbolic Systems of PDEs
, 2017 We discuss possibilities of application of Numerical Analysis methods to proving computability, in the sense of the TTE approach, of solution operators of boundary-value problems for systems of PDEs.
Selivanov, Victor, Selivanova, Svetlana
core +1 more source
Asia-Pacific Journal of Chemical Engineering, EarlyView.ABSTRACT The paper establishes an advanced computing algorithm to investigate the thermosolutal dynamics of an electrically conductive Brinkman‐type nanofluid that moves in a porous channel, and the fluid is acted on by an inclined magnetic field exerted externally.
Urwa Shehbaz +4 more
wiley +1 more source
Rigorous results in space-periodic two-dimensional turbulence
, 2017 We survey the recent advance in the rigorous qualitative theory of the 2d stochastic Navier-Stokes system that are relevant to the description of turbulence in two-dimensional fluids.
Kuksin, Sergei, Shirikyan, Armen
core +2 more sources
Biotechnology and Bioengineering, EarlyView.ABSTRACT The growing demand for biopharmaceutical products reflects their effectiveness in medical treatments. However, developing new biopharmaceuticals remains a major bottleneck, often taking up to a decade before market approval. Machine learning (ML) models have the potential to accelerate this process, but their success depends on access to large
Mohammad Golzarijalal +2 more
wiley +1 more source
The Canadian Journal of Chemical Engineering, EarlyView.Abstract We develop a delay‐aware estimation and control framework for a non‐isothermal axial dispersion tubular reactor modelled as a coupled parabolic‐hyperbolic PDE system with recycle‐induced state delay. The infinite‐dimensional dynamics are preserved without spatial discretization by representing the delay as a transport PDE and adopting a late ...
Behrad Moadeli, Stevan Dubljevic
wiley +1 more source
Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic
Communications on Pure and Applied Mathematics, EarlyView.ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley +1 more source
Compressive Space-Time Galerkin Discretizations of Parabolic Partial Differential Equations [PDF]
, 2015 We study linear parabolic initial-value problems in a space-time variational formulation based on fractional calculus. This formulation uses "time derivatives of order one half" on the bi-infinite time axis.
Larsson, Stig, Schwab, Christoph
core +1 more source