Results 181 to 190 of about 2,453,874 (341)
Convergence to equilibrium in a class of interacting particle systems evolving in discrete time [PDF]
Henryk Fukś, Nino Boccara
openalex +1 more source
On stopping time directed convergence [PDF]
openaire +3 more sources
A Novel Simulation Approach for Damage Evolution during Tailored Forming
Traditional damage models are struggling to accurately and efficiently simulate large‐scale three‐dimensional models with a great number of degrees of freedoms. A new gradient‐enhanced damage model based on the extended Hamilton principle can significantly reduce the computation time while ensuring mesh‐independence which is suitable to use in tailored
Fangrui Liu+2 more
wiley +1 more source
A Design Method and Stability of Continuous-Time MRACS with Exponential Rate of Convergence
Akira Inoue+3 more
openalex +2 more sources
Uniform convergence of sample second moments of families of time series arrays [PDF]
David F. Findley+2 more
openalex +1 more source
Influence of Form and Structural Features of Open‐Cell Hybrid Foam on the Remanent Magnetic Scanning
Simulations using an equivalent model are performed to improve the understanding of remanent magnetic scanning of hybrid foam samples for coating thickness estimation. The model allows to study the influence of isolated geometrical features such as layer thickness, boundary effects, as well as effects due to the statistical nature of the foams, which ...
Bashar Ibrahim+4 more
wiley +1 more source
Global convergence for time-periodic systems with negative feedback and applications [PDF]
For the discrete-time dynamical system generated by the Poincare map T of a time-periodic closed-loop negative feedback system, we present an amenable condition which enables us to obtain the global convergence of the orbits. This yields the global convergence to the harmonic periodic solutions of the corresponding time-periodic systems with negative ...
arxiv
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi+4 more
wiley +1 more source