Results 101 to 110 of about 107,267 (309)
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
The
In this paper, we introduce a new generalized inverse called m-CCE inverse which presents a generalization of the CCE inverse in Minkowski space by using the m-core-EP decomposition and the Minkowski inverse.
Xin Tan, Xiaoji Liu
doaj +1 more source
Generalized Inversion of Nonlinear Operators
AbstractInversion of operators is a fundamental concept in data processing. Inversion of linear operators is well studied, supported by established theory. When an inverse either does not exist or is not unique, generalized inverses are used. Most notable is the Moore–Penrose inverse, widely used in physics, statistics, and various fields of ...
Eyal Gofer, Guy Gilboa
openaire +2 more sources
A Predictor-Corrector Methods for Mixed Inverse Variational Inequalities
In this paper, a class of mixed inverse variational inequalities is introduced and studied. We prove the existence of the solution of the auxiliary problem for mixed inverse variational inequalities, suggest a predictor-corrector method for solving the ...
Shi, Chaofeng
core
A two‐dimensional multiscale finite element analysis framework was established for the first‐generation MoSiBTiC alloy, and the mechanical and fracture‐related parameters of the constituent phases were calibrated through experiments and simulations. The framework provides a basis for analyzing crack propagation behavior in its complex microstructure ...
Junfeng Du +4 more
wiley +1 more source
Applications of recurrent neural networks in batch reactors. Part II: Nonlinear inverse and predictive control of the heat transfer fluid temperature [PDF]
Although nonlinear inverse and predictive control techniques based on artificial neural networks have been extensively applied to nonlinear systems, their use in real time applications is generally limited.
Zaldívar, J.M., Galván, Inés M.
core +1 more source
In Situ Micromechanical Study of Bimodal γ′–γ″ Precipitate Assemblies in Ni–Cr–Al–Nb Superalloy
A Ni–Cr–Al–Nb superalloy with a bimodal γ′–γ″ precipitate distribution is developed. Composite precipitate assemblies form through heterogeneous nucleation, effectively impeding dislocation motion. Micropillar compression reveals high strength at room and elevated temperatures, governed by precipitate shearing, with coupled faulting mechanisms ...
Ujjval Bansal +4 more
wiley +1 more source
Some Characteristics of the MN-LS aggregated modela of MA pro- cesa.
Se estudian algunas propiedades de los modelos agregados de mínimos cuadrados y mínima norma de procesos MA. Dichos agregados MC-MN se obtienen mediante una metodología matricial desarrollada por el autor, que es aquí brevemente esbozada.
Carrión García, Andrés
core +1 more source
Knowledge‐based atomistic workflows are presented for mechanical and thermodynamic properties. By coupling modular simulations with ontology‐aligned metadata and provenance, Fe case studies on elastic behavior, defects, thermal properties, and Hall–Petch strengthening reveal how FAIR, queryable, and reusable simulation data can be generated. Mechanical
Abril Azócar Guzmán +5 more
wiley +1 more source
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran +6 more
wiley +1 more source

