Results 91 to 100 of about 6,123,697 (192)

Development of a force identification method using system-level measurements with component-level reduced-order modeling

Nuclear Engineering and Technology
The accurate estimation of excitation forces is essential for maintaining the structural integrity of dynamic systems. However, direct measurement of excitation forces is often infeasible in practical scenarios.
Hyeongyeong Jin, Seunghun Baek
doaj   +1 more source

A multiparametric advection-diffusion reduced-order model for molecular transport in scaffolds for osteoinduction. [PDF]

Biomech Model Mechanobiol, 2022
Muixí A, Zlotnik S, Calvet P, Espanol M, Lodoso-Torrecilla I, Ginebra MP, Díez P, García-González A.   +7 more
europepmc   +1 more source

Reduced-Order Model of a Time-Trial Cyclist Helmet for Aerodynamic Optimization Through Mesh Morphing and Enhanced with Real-Time Interactive Visualization

Fluids
Aerodynamics is a key factor in time-trial cycling. Over the years, various aspects have been investigated, including positioning, clothing, bicycle design, and helmet shape.
E. Di Meo, A. Lopez, C. Groth, M. E. Biancolini, P. P. Valentini   +4 more
doaj   +1 more source

An improved reduced-order model for pressure drop across arterial stenoses. [PDF]

PLoS One, 2021
Lyras KG, Lee J.
europepmc   +1 more source

A reduced-order model of the spine to study pediatric scoliosis. [PDF]

Biomech Model Mechanobiol, 2021
Neelakantan S, Purohit PK, Pasha S.
europepmc   +1 more source

Koopman Reduced-Order Modeling with Confidence Bounds

SIAM Journal on Applied Dynamical Systems
This paper introduces a reduced order modeling technique based on Koopman operator theory that gives confidence bounds on the model's predictions. It is based on a data-driven spectral decomposition of the Koopman operator. The reduced order model is constructed using a finite number of Koopman eigenvalues and modes, while the rest of spectrum is ...
Mohr, Ryan, Fonoberova, Maria, Mezić, Igor   +2 more
openaire   +2 more sources

Numerical Prediction of Two-Phase Flow through a Tube Bundle Based on Reduced-Order Model and a Void Fraction Correlation. [PDF]

Entropy (Basel), 2021
Dubot C, Allery C, Melot V, Béghein C, Oulghelou M, Bonneau C.   +5 more
europepmc   +1 more source

Development of a Reduced Order Model for Turbine Blade Cooling Design

International Journal of Turbomachinery, Propulsion and Power
Rotating detonation engines (RDEs) are expected to have higher specific work and efficiency, but the high-temperature transonic flow delivered by the combustor poses relevant design and technological difficulties.
Andrea Pinardi, Noraiz Mushtaq, Paolo Gaetani   +2 more
doaj   +1 more source

A Data-Driven Space-Time-Parameter Reduced-Order Model with Manifold Learning for Coupled Problems: Application to Deformable Capsules Flowing in Microchannels. [PDF]

Entropy (Basel), 2021
Boubehziz T, Quesada-Granja C, Dupont C, Villon P, De Vuyst F, Salsac AV.   +5 more
europepmc   +1 more source

Nonintrusive reduced order models

, 2018
Le but de cette thèse est de construire des modèles réduits permettant de se substituer à des logiciels de simulation de systèmes physiques complexes. Ces modèles réduits devront être rapides à interroger et seront identifiés sur la base d’un nombre limité de calculs issus du logiciel de simulation.
openaire   +1 more source