Results 61 to 70 of about 113,247 (266)
Coarse‐grained (left) and atomistic (right) models of the shape memory polymer ESTANE ETE 75DT3 are shown schematically. The two representations bridge molecular detail and mesoscopic description. Both models capture shape memory behavior, linking segmental mobility and conformational relaxation of anisotropic chains to macroscopic recovery, and ...
Fathollah Varnik
wiley +1 more source
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi +3 more
wiley +1 more source
Generalized Regression Neural Network Based Predictive Model of Nonlinear System
Generalized Regression Neural Network (GRNN) is usually applied to the Function approximation. This paper, based on the principle of GRNN, presents a method for the predictive model of nonlinear complex system. The presented algorithm is applied to the learning and predicting process for the system modeling.
Yibin Song, Zhenbin Du
openaire +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Linear genetic programming control for strongly nonlinear dynamics with frequency crosstalk
We advance Genetic Programming Control (GPC) for turbulence flow control application building on the pioneering work of [1]. GPC is a recently proposed model-free control framework which explores and exploits strongly nonlinear dynamics in an ...
R. Li +5 more
doaj +1 more source
New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare +5 more
wiley +1 more source
Radiometric normalization is an essential preprocessing step that must be performed to detect changes in multi-temporal satellite images and, in general, relative radiometric normalization is utilized.
Dae Kyo Seo, Yang Dam Eo
doaj +1 more source
Postbuild annealing systematically modifies the phase fractions and morphology of EB‐PBF processed Mo–9Si–8B. Quantitative microstructure–property correlations reveal how controlled phase evolution enhances high‐temperature compressive strength and creep resistance.
Christopher Schmidt +5 more
wiley +1 more source
Geometry‐driven design of soft cellular metamaterials is systematically investigated by combining experiments, finite element modeling, and statistical prediction. The study quantifies how unit cell geometry and material properties govern stiffness, instability, densification, and energy absorption.
Alice Berardo +4 more
wiley +1 more source
A bio‐inspired biopolymeric implantable drug delivery platform enables localized and sustained release of 7‐ethyl‐10‐hydroxycamptothecin (SN‐38) in solid tumor treatment. The three‐dimensional (3D) structured crosslinked‐chitosan implants are fabricated via 3D‐printed molds and provide drug release over 3 months, significantly inhibiting tumor growth ...
Mercedes Lozano‐Garcia +12 more
wiley +1 more source

