University of Cambridge
Novel integrated computational approach for designing Fe-Ni-based alloys
Abstract
dc:description.abstractA novel computational approach for designing high temperature alloys is proposed; the approach incorporates properties prediction and optimisation. As for properties prediction, microstructural parameters, such as the volume fraction and precipitate size after heat treatment (replicating the service conditions of automobile sealing parts) were thermokinetically calculated by adopting phase transformation software. The associated yield stress was then predicted using classical strengthening theories: solid solution, grain boundary and precipitation strengthenings. These calculations were integrated with a genetic algorithm (GA) for searching the optimal chemical compositions considering not only the strength after a long time heat treatment but also cost and producibility constraints. The calculation parameters for the GA, such as population size and mutation ratio, were also considered. The alloy designed by the computer-aided approach described above was produced and validated. The designed alloy (Fe-opt) whose composition is Fe-33Ni-15.5Cr-1.6Al-0.3Nb-2.8Ti-3.7W-0.9Co-0.01C are proved to have the high strength after a long time high temperature exposure due to finely dispersed precipitates, γ\prime, although the strength is not as high as expected from the calculation. The microstructure analysis suggests that W in the designed alloy has a negative influence on the mechanical properties of the alloy by forming coarse Laves phases on the grain boundaries. Therefore, the alloy sheet, with the same composition of Fe-opt but without W (Fe-opt2) was prepared and examined. Fe-opt2 has higher strength than Fe-opt and than more expensive Ni-based superalloys, such as Alloy 718Plus. The integrated approach conducted in this study has successfully provided an efficient and effective alloy design methodology. This approach can be widely adopted for use in many fields beyond high-temperature alloys by adopting suitable thermokinetic databases and strengthening modelling approaches.
Degree
thesis:*- Name dc:type.qualificationname
- Doctor of Philosophy (PhD)
- Level dc:type.qualificationlevel
- Doctoral
- Grantor dc:publisher.institution
- University of Cambridge
- Year dc:date.issued
- 2019
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Sawada, Masayoshi
- Advisor dc:contributor.advisor
-
- Rivera Diaz del Castillo, Pedro
Subjects
dc:subject × 8Rights
dc:rightsIdentifiers
dc:identifier.*- DOI dc:identifier.doi
- https://doi.org/10.17863/CAM.42268
- OAI identifier oai:identifier
- oai:www.repository.cam.ac.uk:1810/295208