2015
DOI: 10.1007/s00707-015-1419-y
|View full text |Cite
|
Sign up to set email alerts
|

Complex variable step method for sensitivity analysis of effective properties in multi-field micromechanics

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
8
0

Year Published

2017
2017
2025
2025

Publication Types

Select...
7
2

Relationship

2
7

Authors

Journals

citations
Cited by 12 publications
(8 citation statements)
references
References 46 publications
0
8
0
Order By: Relevance
“…17. Gradients are routinely computed numerically using forward finite difference (FFD) [86], backward finite difference (BFD) [86], central finite differences (CFD) [87]- [89], and complex-step methods [89]. The FFD and BFD methods require one additional simulation for each design parameter, whereas the more accurate CFD requires two extra simulations for each design parameter.…”
Section: ) Objective Gradient Calculation Methodsmentioning
confidence: 99%
“…17. Gradients are routinely computed numerically using forward finite difference (FFD) [86], backward finite difference (BFD) [86], central finite differences (CFD) [87]- [89], and complex-step methods [89]. The FFD and BFD methods require one additional simulation for each design parameter, whereas the more accurate CFD requires two extra simulations for each design parameter.…”
Section: ) Objective Gradient Calculation Methodsmentioning
confidence: 99%
“…The linear constitutive equations of the magnetoelectroelastic continuum can be expressed as [1,3,8]:…”
Section: Magnetoelectroelastic Linear Constitutive Modelmentioning
confidence: 99%
“…where q v is the volume charge density; for the static case the electromagnetic field is irrotational, therefore the static potentials can be introduced on the base of the Maxwell equations [1,3,8]:…”
Section: Magnetoelectroelastic Linear Constitutive Modelmentioning
confidence: 99%
“…Finite Element Method (FEM) is used in the following paper for building the numerical representation for its great advantages like versatility [4,5], adaptivity, stability and flexibility (possibility to model inhomogeneity, complex geometries and complex boundary conditions) [6].…”
Section: Fig 1 General Algorithm Of Hybrid Simulationmentioning
confidence: 99%