Results 31 to 40 of about 2,192 (177)

Dictionary‐based weak‐form training for noise‐robust series hybrid models with multiplicative unknowns

AIChE Journal, EarlyView.
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho, Akshay Kudva, Parth Shah, Dongheon Lee, Joseph Sang‐Il Kwon   +4 more
wiley   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Perturbed Strong Stability Preserving Time-Stepping Methods For Hyperbolic PDEs [PDF]

, 2017
A plethora of physical phenomena are modelled by hyperbolic partial differential equations, for which the exact solution is usually not known. Numerical methods are employed to approximate the solution to hyperbolic problems; however, in many cases it
Hadjimichael, Yiannis
core   +1 more source

Toward Intelligent Multimodal Holography for Real‐Time Chemical Imaging of Dynamic Ion Separation

Advanced Intelligent Discovery, EarlyView.
Intelligent multimodal holography integrates digital off‐axis holography, spectroscopic imaging, and AI‐driven reconstruction to visualize ion transport and chemical dynamics in real time. In this perspective paper, we outline how this approach enables label‐free, chemically specific monitoring of complex environments and discuss its potential to ...
Giovanna Ricchiuti, Sarah I. Allec, Maxim Ziatdinov, Venkateshkumar Prabhakaran   +3 more
wiley   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Nanostructured Deep Eutectic Systems in Healthcare: From Bioactive Solvents to Intelligent Biointerfaces, Wearables, and AI‐Driven Design

Advanced NanoBiomed Research, EarlyView.
Beyond the green solvent paradigm, this review redefines Deep Eutectic Systems (DES) as programmable supramolecular nanoassemblies. We survey their biomedical convergence: stabilizing thermolabile mRNA to enable cold chain‐free logistics, reshaping transdermal microneedle delivery, enabling long‐term wearables via eutectogels, and utilizing Generative ...
Jeesu Moon, Min Seo Kim, Jae‐Seung Lee
wiley   +1 more source

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

Stabilité Lp exponentielle d’un système d’échangeurs thermiques avec diffusion et sans diffusion [PDF]

, 2008
International audienceIn this paper we study exponential stability of a heat exchanger system with diffusion and without diffusion in the context of Banach spaces.
Li, Chen-Zhong, Li, Xiao-Dong, Gauthier Sallet, Xu, Cheng-Zhong, Abdoua Tchousso, Xiao-Dong Li, Sallet, Gauthier, Tchousso, Abdoua, Chen-Zhong Li   +8 more
core   +2 more sources

Cyclodextrins as Chiral Selectors in Capillary Electrophoresis—Recent Developments in Understanding Analyte Complexation and Applications in Pharmaceutical Analysis

ELECTROPHORESIS, EarlyView.
Cyclodextrins are the most often applied chiral selectors in CE enantioseparations. In combination with NMR spectroscopy and molecular modeling, studies for an understanding of chiral recognition underlying enantioseparations have been performed.
Gerhard K. E. Scriba
wiley   +1 more source

Reduced order models for parametric bifurcation problems in nonlinear PDEs [PDF]

, 2020
This work is concerned with the analysis and the development of efficient Reduced Order Models (ROMs) for the numerical investigation of complex bifurcating phenomena held by nonlinear parametrized Partial Differential Equations (PDEs) in many physical ...
Pichi, Federico
core