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DC Field | Value | Language |
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dc.contributor.advisor | Ng, Eu-Gene | - |
dc.contributor.author | Tanu Halim, Silvie Maria | - |
dc.date.accessioned | 2024-10-03T13:59:46Z | - |
dc.date.available | 2024-10-03T13:59:46Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://hdl.handle.net/11375/30324 | - |
dc.description.abstract | The advancement of Finite Element micromechanical modeling in simulating the effects of microstructure has been rapid, with efficient solvers, solid research in identifying boundary conditions, and powerful computer abilities. The goal is to use the individual phase behavior to predict the overall behavior of the inhomogeneous material. However, a persistent challenge remains, specifying the parameters for the material constants to describe the behavior of individual phase properties within an inhomogeneous material. This thesis presents a different approach to research in FE micromechanical modeling. Instead of using the micromechanical model to predict the behavior of inhomogeneous material, the model will be used together with experimental data of the overall inhomogeneous material behavior to predict the behavior of the individual phase stress-flow curves. This is made possible by using the newly developed numerical technique: Micromechanical Adaptive Iteration Algorithm. The key to this newly developed iteration algorithm is that it includes the effect of strain partitioning behavior between the soft and hard phases at every strain increment. The technique is efficient; by the second iteration, the modeled stress-flow curves contained 2-3% error compared to experimental data. The advantage of this technique is that it reduces the need for detailed characterization of the material, which can be expensive, complex, and challenging. In addition to the development of MAIA, this thesis focuses on the proper fundamental techniques to carry out micromechanical modeling. By using the appropriate techniques, results could explain, in terms of solid mechanics, the behavior of hardening and softening of in-situ ferrite and martensite phases in DP steel compared to its bulk behavior. This also provide a corrected perspective to ‘constant stress’ behavior in a microstructure configuration, contrasting with the conventional definitions used for the past decades. | en_US |
dc.language.iso | en | en_US |
dc.subject | Finite Element Micromechanical Models | en_US |
dc.subject | Dual Phase Steel | en_US |
dc.subject | Ferrite | en_US |
dc.subject | Martensite | en_US |
dc.subject | Stress flow curves | en_US |
dc.subject | Micromechanical Adaptive Iteration Algorithm | en_US |
dc.title | Determination of Phase Material Stress Flow Curves Through FE Micromechanical Modelling and the Newly Developed Algorithm | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Mechanical Engineering | en_US |
dc.description.degreetype | Dissertation | en_US |
dc.description.degree | Doctor of Philosophy (PhD) | en_US |
dc.description.layabstract | Finite Element micromechanical modeling has rapidly advanced in simulating microstructure effects using powerful computer abilities and efficient solvers. This research aims to predict overall material behavior by understanding individual phase properties within complex materials. However, a persistent challenge lies in accurately specifying material parameters. This thesis proposes a novel approach: using experimental data alongside micromechanical models to predict individual phase stress-flow curves. This is facilitated by a new numerical technique called Micromechanical Adaptive Iteration Algorithm. By considering strain partitioning between soft and hard phases, this algorithm efficiently predicts stress-flow curves, with just 2-3% error by the second iteration. This approach reduces the need for complex material characterization. Additionally, the thesis focuses on fundamental techniques for micromechanical modeling, aiming to explain the behavior of different phases in DP steel compared to bulk behavior, using solid mechanics principles. | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Tanu Halim_Silvie_Maria_Aug2024_PhD.pdf | 8.64 MB | Adobe PDF | View/Open |
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