Results 111 to 120 of about 32,160 (207)
A Hybrid Semi‐Inverse Variational and Machine Learning Approach for the Schrödinger Equation
A hybrid semi‐inverse variational and machine‐learning framework is presented for solving the Schrödinger equation with complex quantum potentials. Physics‐based variational solutions generate high‐quality training data, enabling Random Forest and Neural Network models to deliver near‐perfect energy predictions.
Khalid Reggab +5 more
wiley +1 more source
In this paper, the mixed-type linear and Euler-Lagrange-Rassias functional equations introduced by J. M. Rassias is generalized to the following n-dimensional functional equation: f(∑i=1nxi)+(n−2)∑i=1nf(xi)=∑1≤i2.
Paisan Nakmahachalasint
doaj +1 more source
Design of Two‐Segment Constant‐Force Compliant Mechanisms via Stiffness‐Matched Parallel Integration
This work presents a novel design for two‐segment constant‐force compliant mechanisms that achieve dual‐stage zero‐stiffness via stiffness‐matched parallel integration. Experimental results demonstrate constant forces of 4 N and 20 N with less than 5% variation, enabling extended operational ranges for precision applications such as robotic ...
Junfeng Hu, Xiwei Jiang
wiley +1 more source
From Euler-Lagrange equations to canonical nonlinear connections [PDF]
summary:The aim of this paper is to construct a canonical nonlinear connection $\Gamma =(M_{(\alpha )\beta }^{(i)}, N_{(\alpha )j}^{(i)})$ on the 1-jet space $J^{1}(T,M)$ from the Euler-Lagrange equations of the quadratic multi-time Lagrangian function \[
Neagu, Mircea
core
Elastoplasticity Informed Kolmogorov–Arnold Networks Using Chebyshev Polynomials
ABSTRACT Multilayer perceptron (MLP) networks are predominantly used to develop data‐driven constitutive models for granular materials. They offer a compelling alternative to traditional physics‐based constitutive models in predicting non‐linear responses of these materials, for example, elastoplasticity, under various loading conditions. To attain the
Farinaz Mostajeran, Salah A. Faroughi
wiley +1 more source
Mass‐Exchange Processes in a Biphasic TPM‐Phase‐Field Model
ABSTRACT The modelling of hydraulic fracturing processes in porous media gained significant interest in the past. Therefore, several approaches, such as the Biot theory or the Theory of Porous Media (TPM), were used as their modelling basis. In combination with the phase‐field method for a diffuse fracture description, especially the TPM has turned out
Yann Rivas +2 more
wiley +1 more source
On MAP Estimates and Source Conditions for Drift Identification in SDEs
ABSTRACT We consider the inverse problem of identifying the drift in an stochastic differential equation (SDE) from n$n$ observations of its solution at M+1$M+1$ distinct time points. We derive a corresponding maximum a posteriori (MAP) estimate, we prove differentiability properties as well as a so‐called tangential cone condition for the forward ...
Daniel Tenbrinck +3 more
wiley +1 more source
Fractional Euler–Lagrange Equations of Motion in Fractional Space
: Fractional variational principles have gained considerable importance during the last decade due to their various applications in several areas of science and engineering.
Dumitru Baleanu, Sami I. Muslih
core
This study presents a comprehensive analysis and modeling framework that integrates Mandelbrot's fractal scaling with fractional variational principles to advance the understanding of parameterization-invariant theories for mechanical systems.
Yazen M. Alawaideh +5 more
doaj +1 more source
On Cahn–Hilliard Type Viscoelastoplastic Two‐Phase Flows
ABSTRACT This contribution deals with a model for viscoelastoplastic two‐phase flows of Cahn–Hilliard type. We present the modeling framework for the flow, the notion of a generalized solution, namely the so‐called dissipative solution, and the key ideas of the existence proof.
Fan Cheng +2 more
wiley +1 more source

