Applications of Crystal Plasticity in Forming Technologies

• Format: eBook
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2022
• Subjects: Industrial chemistry and chemical engineering; Technology: general issues; alternative error method; aluminum wires; bending crystal; characteristics; complex variable function method; crack; creep; crystal plasticity; crystallographic misorientation; cubic quasicrystal piezoelectric materials; damage mechanics; DAMASK; defect and grain structure evolution; densitometry; density; detwinning; digital image correlation; discrete dislocation dynamics; dislocation; dual-phase steel; ductility; dynamic recrystallization; EBSD; elastoplastic properties; electron microscopy; fatigue; finite element method; grain boundary; grain shape and grain size; high-pressure; in situ tensile test; L-Leucinium hydrogen maleate; lead-free; least square method; local deformation behavior; low temperature; Magnesium; magnesium alloy; multilevel models; multiscale model; n/a; near-surface layer; non-metallic inclusions; numerical simulation; overhead power transmission lines; plastic crystals; plasticity; Raman spectroscopy; reliability; representative volume element; screw dislocation; SEM-DIC; size effects; slip transfer; solder joints; twinning; VEDDAC; X-ray diffraction; XRD
• Online Access: Open Access: DOAB: description of the publication; Open Access: DOAB, download the publication
• Physical Description: 1 online resource (242 p.)
• ISBN: 9783036557335; 9783036557342; books978-3-0365-5734-2
• Access: Open Access

In this Special Issue, we have gathered work on simulations of polycrystalline metals and alloys at various length scales to model multiscale localization phenomena such as slip bands, cracks, and twins. The series highlights innovative techniques that combine simulation and experiments to capture material production and guide the development of forming theories. The published work helps to understand the effect of microstructure characteristics on deformation and damage behavior under multiaxial load conditions. Furthermore, these models and the studies can be used with machine learning technologies to optimize microstructure functions for materials application and process paths.