Results 71 to 80 of about 35,710 (245)

Partially integrable systems in multidimensions by a variant of the dressing method. 1

, 2006
In this paper we construct nonlinear partial differential equations in more than 3 independent variables, possessing a manifold of analytic solutions with high, but not full, dimensionality. For this reason we call them ``partially integrable''.
A I Zenchuk, Ablowitz M J, Ablowitz M J, Beals R Coifman R R, Bogdanov L V, Calogero F, Drinfeld V G, Konopelchenko B, Manakov S V Santini P M, P M Santini, Zakharov V E, Zakharov V E, Zakharov V E, Zakharov V E, Zakharov V E, Zakharov V E, Zenchuk A   +16 more
core   +1 more source

Digital Twin of Solid Oxide Electrochemical Cells: From 3D Microstructure Reconstruction to Multiphysics Modeling

Advanced Energy Materials, EarlyView.
This review outlines the implementation of digital twin frameworks for solid oxide electrochemical cells (SOCs), encompassing 3D microstructure reconstruction, quantitative morphological analysis, and microstructure‐resolved multiphysics modeling. Emphasis is placed on recent advances that position digital twins as powerful tools for microstructure ...
Seungsoo Jang, Yejin Kang, Kyung Taek Bae, Seong Hyun Park, Young Je Park, Dongyeon Kim, Hyeongmin Yu, Hyunjin Kim, Siwon Yu, Kang Taek Lee   +9 more
wiley   +1 more source

2D population balance modeling and ML‐based multi‐objective optimization for the crystallization process of resveratrol

AIChE Journal, EarlyView.
Abstract Crystallization is critical in pharmaceutical manufacturing, influencing active pharmaceutical ingredient (API) purity and processability. This study models the cooling crystallization of resveratrol in a water‐ethanol solvent using a two‐dimensional population balance model (2D‐PBM). Experimental data from Focused Beam Reflectance Measurement
Álmos Orosz, Monika Neal, Rekha Rao, Christine Roberts, Botond Szilágyi, Zoltán K. Nagy   +5 more
wiley   +1 more source

A multi-resolution, non-parametric, Bayesian framework for identification of spatially-varying model parameters

, 2008
This paper proposes a hierarchical, multi-resolution framework for the identification of model parameters and their spatially variability from noisy measurements of the response or output.
Ainsworth, Barry, Brigham, Chen, Chopin, Craig, Del Moral, Del Moral, Del Moral, Dorobantu, Dostert, Doucet, E, Emery, Engl, Fadale, Fatemi, Ferreira, Fienen, Gelman, Green, Groetsch, Hegstad, Higdon, Higdon, Higdon, Holloman, Hou, Hughes, Jefferys, Kaipio, Kennedy, Kevrekidis, Kimeldorf, Kitanidis, Koutsourelakis, Lee, Lee, Lewicki, Liu, Liu, Liu, MacEachern, P.S. Koutsourelakis, Robert, Sangali, Schmidt, Simo, Tikhonov, Tikhonov, Tipping, Torquato, Velamur Asokan, Vermaak, Wang, Wang, Wang, Weir, Wynn   +58 more
core   +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

Multidimensional inverse problems and completeness of the products of solutions to PDE

Journal of Mathematical Analysis and Applications, 1988
A method is given to prove uniqueness theorems for some multidimensional inverse problems with data given at a fixed frequency. A number of new uniqueness theorems are proved. In particular: 1) if \(A(\theta ',\theta)\) is given for all \(\theta ',\theta \in S^ 2\) at a fixed \(k>0\) then \(q(x)\) is uniquely determined. Here A(\(\theta\) ',\(\theta)\)
openaire   +3 more sources

Neural network augmented inverse problems for PDEs

, 2017
In this paper we show how to augment classical methods for inverse problems with artificial neural networks. The neural network acts as a prior for the coefficient to be estimated from noisy data. Neural networks are global, smooth function approximators and as such they do not require explicit regularization of the error functional to recover smooth ...
Berg, Jens, Nyström, Kaj
openaire   +2 more sources

Is Computing with Light All You Need? A Perspective on Codesign for Optical Artificial Intelligence and Scientific Computing

Advanced Intelligent Systems, EarlyView.
This perspective article considers what computations optical computing can and should enable. Focusing upon free‐space optical computing, it argues that a codesign approach whereby materials, devices, architectures, and algorithms are simultaneously optimized is needed.
Prasad P. Iyer, Gaurang R. Bhatt, Saaketh Desai, Elliot J. Fuller, Corinne M. Teeter, François Léonard, Craig M. Vineyard   +6 more
wiley   +1 more source

A Cut Discontinuous Galerkin Method for Coupled Bulk-Surface Problems

, 2017
We develop a cut Discontinuous Galerkin method (cutDGM) for a diffusion-reaction equation in a bulk domain which is coupled to a corresponding equation on the boundary of the bulk domain. The bulk domain is embedded into a structured, unfitted background
Massing, Andre
core   +1 more source

Robotic Needle Steering for Percutaneous Interventions: Sensing, Modeling, and Control

Advanced Intelligent Systems, EarlyView.
This review examines recent advances in robotic needle steering for percutaneous interventions, highlighting closed‐loop sensing, physics‐informed tissue‐needle interaction modeling, and real‐time trajectory planning and control. It synthesizes innovations in deep learning, fiber‐optic feedback, and adaptive control strategies, and outlines emerging ...
Fangjiao Zhao, Ruixue Xu, Wujun Zhao, Xi‐Ming Sun, Yu Sun, Changsheng Dai   +5 more
wiley   +1 more source