Results 101 to 110 of about 1,491 (210)

Lie group analysis of magnetohydrodynamic tangent hyperbolic fluid flow towards a stretching sheet with slip conditions. [PDF]

Heliyon, 2017
Ullah Z, Zaman G.
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, Volume 2, Issue 4, August 2026.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Numerical investigation of forced convective MHD tangent hyperbolic nanofluid flow with heat source/sink across a permeable wedge

AIP Advances
The combined effect of wedge angle and melting energy transfer on the tangent hyperbolic magnetohydrodynamics nanofluid flow across a permeable wedge is numerically evaluated.
Taghreed A. Assiri, Muhammad Bilal, Emad E. Mahmoud, Aatif Ali, Joshua Kiddy K. Asamoah, Adnan   +5 more
doaj   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, Volume 2, Issue 4, August 2026.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

The Canadian Journal of Chemical Engineering, Volume 104, Issue 8, Page 4079-4100, August 2026.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos, Heleno Bispo, Thiago Vaz da Costa, Sérgio Mauro da Silva Neiro   +3 more
wiley   +1 more source

Individual Virtues, Social Movements, and Allyship in the Sphere of Intellectual Disability

Journal of Social Philosophy, EarlyView.
Tommy Ness
wiley   +1 more source

Impact of Iridium Crucible Aging on Cz‐YAG Crystal Quality and Process Economy: A Data‐Driven Study

Crystal Research and Technology, Volume 61, Issue 8, August 2026.
Machine learning models trained on CFD‐generated data reveal how iridium crucible aging influences key Czochralski YAG crystal growth outcomes. Interpretable analyses uncover the dominant role of iridium loss and its interactions with process variables, enabling accurate prediction of heating power, interface shape, and the ratio of growth rate to ...
Natasha Dropka, Xiao Le Ye, Kunal Meshram, Debajyoti Biswas, Martin Holena   +4 more
wiley   +1 more source

Mesenchymal stem cell‐derived exosomes for cardiac repair: Challenges, standardization gaps and a realistic path to clinical translation

Clinical and Translational Discovery, Volume 6, Issue 4, August 2026.
Mesenchymal stem cell‐derived exosomes (MSC‐sEVs) show preclinical promise for cardiac repair via anti‐inflammatory, anti‐apoptotic, pro‐angiogenic and anti‐fibrotic effects. However, translational hurdles remain, including non‐standardized isolation, unvalidated potency assays, incomplete GMP manufacturing, and lack of completed Phase II/III trials ...
Sakhavat Abolhasani, Yasin Ahmadi, Amin Jalizih   +2 more
wiley   +1 more source

Transient Conjugate MHD Flow With Variable Thermal Conductivity: A CFD to ANN Study

Engineering Reports, Volume 8, Issue 8, August 2026.
A star‐shaped obstacle inside a hexagonal cavity alters fluid flow and heat transfer under magnetic fields. Simulations and ANN predictions reveal that magnetic strength and material properties control cooling efficiency, supporting smarter designs for real‐time thermal management.
M. A. Forhad, A. K. Azad, M. Sakib Hasan, Md. Ibrahim, Aminur Rahman Khan, M. M. Billah   +5 more
wiley   +1 more source

Computational Investigation of MHD Radiative Flow of Shape‐Dependent Al2O3$$ A{l}_2{O}_3 $$ and Fe3O4$$ F{e}_3{O}_4 $$ Nanofluids in A Semi‐Porous Channel

Engineering Reports, Volume 8, Issue 8, August 2026.
A computational study of unsteady MHD radiative nanofluid flow in a semi‐porous channel reveals that nanoparticle shape, volume fraction, and magnetic effects significantly influence velocity and heat transfer. Results highlight strong coupling between geometric, electromagnetic, and thermophysical parameters in optimizing thermal system performance ...
Mahmmoud M. Syam, Sondos M. Syam, Muhammed I. Syam   +2 more
wiley   +1 more source