Engineering of surface microstructure transformations using high rate severe plastic deformation in machining
Engineering surface stuctures especially at the nanometer length-scales can enable fundamentally new multifunctional property combinations, including tunable physical, mechanical, electrochemical and biological responses. Emerging manufacturing paradigms involving Severe Plastic Deformation (SPD), f...
- Autores:
-
Abolghasem Ghazvini, Sepideh
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2015
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/7840
- Acceso en línea:
- http://hdl.handle.net/1992/7840
- Palabra clave:
- Materiales a altas presiones
Microestructura
Deformaciones (Mecánica)
Materiales nanoestructurados
Ingeniería
- Rights
- openAccess
- License
- https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf
| Summary: | Engineering surface stuctures especially at the nanometer length-scales can enable fundamentally new multifunctional property combinations, including tunable physical, mechanical, electrochemical and biological responses. Emerging manufacturing paradigms involving Severe Plastic Deformation (SPD), for manipulating final microstructure of the surfaces are unfotunately limited by poorly elucidated process-structure-pelfonnance linkages, which are characterized by three central variables of plasticity: strain, strain-rate and temperature that detemine the resulting Ultra fine Grained (UFG) microstructure. The challenge of UFG surface engineering, design and manufacturing can be overcome if and only if the mappings between the central variables and the final microstructure are delineated. The objective of the proposed document is to first envision a phase-space, whose axes are parameterized in terms of the central variables of SPD. Then, each point can correspond to a unique microstructure, charactefized by its location on this map. If the parametrization and the population of the datasets are accurately defined, then the mapping is bijective where: i) realizing microstructure designs can be reduced to simply one of tuning process parameters falling within the map's desired subspaces. And, inversely, ii) microstructure prediction is directly possible by merely relating the measured/calculated thennomechanics at each point in the deformation zone to the conesponding spot on the maps |
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