Results 51 to 60 of about 1,914,780 (311)
Reduced order model for hard magnetic films
In the pursuit of rare earth-lean permanent magnets for green technologies, microstructural optimisation offers a promising strategy to enhance coercivity while minimising critical element content.
H. Moustafa +11 more
doaj +1 more source
Determining Reduced Order Models for Optimal Stochastic Reduced Order Models
The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a
Matthew Bonney, Matthew Brake
openaire +2 more sources
Approximate deconvolution reduced order modeling [PDF]
This paper proposes a large eddy simulation reduced order model(LES-ROM) framework for the numerical simulation of realistic flows. In this LES-ROM framework, the proper orthogonal decomposition(POD) is used to define the ROM basis and a POD differential filter is used to define the large ROM structures.
Xie, X. +3 more
openaire +4 more sources
Dissipativity preserving model reduction by retention of trajectories of minimal dissipation [PDF]
We present a method for model reduction based on ideas from the behavioral theory of dissipative systems, in which the reduced order model is required to reproduce a subset of the set of trajectories of minimal dissipation of the original system.
Paolo Rapisarda +12 more
core +1 more source
ABSTRACT Background Central nervous system (CNS) involvement in childhood acute lymphoblastic leukemia (ALL) is assessed by cell counting and cytomorphology from cerebrospinal fluid (CSF) and is used for treatment stratification worldwide. The ratio of “CNS2” patients in clinical trials ranges from 3% to 40%, with unclear prognostic significance ...
Laura Almási +14 more
wiley +1 more source
Evaluation of Errors in Reduced Order Modeling
The purpose of the paper is to make a comparison between the equation errors and the output errors which are used as criteria for measuring modeling errors in system identification. In many practical situations real systems have high system orders which are often unknown, and reduced order models are used for estimating the parameters of the systems ...
IKEDA, Fujio +2 more
openaire +2 more sources
Reduced order methods for laminar and turbulent flows in a finite volume setting: projection-based methods and data-driven techniques [PDF]
This dissertation presents a family of Reduced Order Models (ROMs) which is specifically designed to deal with both laminar and turbulent flows in a finite volume full order setting.
Hijazi, Saddam N Y
core
Reciprocal control of viral infection and phosphoinositide dynamics
Phosphoinositides, although scarce, regulate key cellular processes, including membrane dynamics and signaling. Viruses exploit these lipids to support their entry, replication, assembly, and egress. The central role of phosphoinositides in infection highlights phosphoinositide metabolism as a promising antiviral target.
Marie Déborah Bancilhon, Bruno Mesmin
wiley +1 more source
Reduced-Order Model Approaches for Predicting Airfoil Performance
This study delves into the construction of reduced-order models (ROMs) of a flow field over a NACA 0012 airfoil at a moderate Reynolds number and an angle of attack of 8∘. Numerical simulations were computed through the finite-volume solver OpenFOAM. The
Antonio Colanera +3 more
doaj +1 more source
Reduced-order modeling of soft robots
We present a general strategy for the modeling and simulation-based control of soft robots. Although the presented methodology is completely general, we restrict ourselves to the analysis of a model robot made of hyperelastic materials and actuated by cables or tendons. To comply with the stringent real-time constraints imposed by control algorithms, a
Chenevier, Jean +4 more
openaire +8 more sources

