Results 51 to 60 of about 3,082 (261)
We present a linear backward Euler fully discrete finite volume method for the initial-boundary-value problem of purely longitudinal motion of a homogeneous bar and an give optimal order error estimates in L2 and H1 norms.
Ziwen Jiang, Deren Xie
doaj +1 more source
Stability analysis for a class of discrete schistosomiasis models with general incidence
In this paper, we propose to study a class of discrete schistosomiasis models with general incidence function. This model is derived from a continuous schistosomiasis model (in Appl. Math.
Aboudramane Guiro +2 more
doaj +1 more source
Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning +3 more
wiley +1 more source
A Review of Failure Modes and Safety Strategies of Lithium‐Ion Batteries from Materials to Systems
A cascade‐aware framework is presented for lithium‐ion battery safety, linking thermal runaway initiation, acceleration, runaway reaction, and propagation with material‐, cell/pack‐, and system‐level interventions. By integrating failure mechanisms, quantitative safety indicators, and staged interception strategies, this review highlights how safer ...
Jin Hyeok Yang +8 more
wiley +1 more source
An Adaptive Time Filtered Backward Euler Method for Reduced-Order Models of Incompressible Flows
This paper studies a reduced-order model based on proper orthogonal decomposition (POD) for the incompressible Navier-Stokes equations. The difficulties resulting from nonlinearity are eliminated using the variational multiscale (VMS) method. The time filter is added as a separate post-processing step to the standard VMS-POD approximation.
openaire +3 more sources
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho +4 more
wiley +1 more source
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Error estimates of finite element methods for fractional stochastic Navier–Stokes equations
Based on the Itô’s isometry and the properties of the solution operator defined by the Mittag-Leffler function, this paper gives a detailed numerical analysis of the finite element method for fractional stochastic Navier–Stokes equations driven by white ...
Xiaocui Li, Xiaoyuan Yang
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It is a fact that slippage causes tracking errors in both longitudinal and lateral directions which results to have less travel distance in tracking a reference trajectory. Less travel distance means having energy loss of the battery and carrying loads less than planned.
Gokhan Bayar +2 more
wiley +1 more source
Herein, a patient‐mounted neuro optical coherence tomography system that integrates a 5 degrees‐of‐freedom skull‐mounted robot (Skullbot) with a 0.6 mm neuroendoscope for targeted, minimally invasive deep brain imaging, is developed. The system offers high‐resolution imaging with precise deployment, demonstrated through successful tumor imaging in a ...
Chao Xu +7 more
wiley +1 more source

