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@PHDTHESIS{Giang:482023,
      author       = {Giang, Ngoc Anh},
      othercontributors = {Broeckmann, Christoph and Weichert, Dieter},
      title        = {{M}ulti-scale model for fatigue in carbide rich tool steel},
      volume       = {6},
      school       = {Zugl.: Aachen, Techn. Hochsch.},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {Shaker},
      reportid     = {RWTH-2015-04575},
      isbn         = {978-3-8440-3748-7},
      series       = {Werkstoffanwendungen im Maschinenbau},
      pages        = {XVIII, 129 S. : Ill., graph. Darst.},
      year         = {2015},
      note         = {Auch veröffentlicht auf dem Publikationsserver der RWTH
                      Aachen University; Zugl.: Aachen, Techn. Hochsch., Diss.,
                      2014},
      abstract     = {Carbide-rich tool steel is most commonly used not in the
                      tooling industry, but also in engine parts, e.g. springs,
                      bearings, diesel injections, connecting rods etc..
                      Components made from this kind of material are often
                      subjected to cyclic mechanical stresses. Fatigue is
                      important as it occupies the largest cause of failure in
                      metal, aproximately estimated $90\%$ of all metallic
                      failures, tool steels are also susceptible to this type of
                      failure. Fatigue resistance of this material strongly
                      depends on the microstructural features including shapes,
                      shape ratio, volume fractions, and distributions of primary
                      and eutectic carbides. Thus, besides loading condition
                      microstructural features are considered as the main factor
                      which influences lifetime of tool components.It is known
                      that the lifetime prediction of carbide-rich tool steel in
                      alternating applied stress is not an easy task to perform.
                      Therefore, gaining knowledge about the effects of
                      microstructural features on the fatigue behavior of this
                      material is necessary. Subsequently, the main objective of
                      this research is to develop a simple model as well asa
                      computational framework to quantify the influence of these
                      microstructural features on the fatigue behavior of the
                      material in the high cycle fatigue (HCF) regime.In general,
                      fatigue crack mechanisms can be divided into 3 stages:
                      initial crack formation (crack incubation or nucleation),
                      short crack and long crack growth, which have successfully
                      been established by McDowell, in a so-called multistage
                      fatigue model (MSF). To model fatigue behavior of carbide
                      rich tool steel, McDowell’s model was modified and
                      developed at three length-scale levels, resulting in
                      amulti-scale fatigue model. For fatigue crack formation and
                      early growth, a hierarchical approach was used, and lifetime
                      of this stage was estimated based on local cyclic micro
                      plasticity within a representative volume element (RVE). The
                      short crack stage consists of microstructurally short crack
                      (MSC) and physically short crack (PSC) growth in which short
                      crack drivingforce was determined from the process zone at
                      the crack tip, so-called cyclic crack tip opening
                      displacement (CTOD). From this relation, the effects of
                      microstructural features on the cyclic short crack growth
                      were explicitly identified. For long crack growth, an
                      accumulated fatigue damage concept was implemented to
                      calculate the lifetime of this stage. Based on that
                      relation, the long crack growth rate was easily derived from
                      low cycle fatigue (LCF) properties because it is believed
                      that LCF test is easy to calibrate and it may be
                      interpolated from monotonic tensile test, which results in
                      saving time and cost for fatigue prediction.The most
                      important contributions of this study are to simulate and
                      model the influence of carbides on three different length
                      scales of fatigue crack mechanisms in tool steels. The
                      proposed model is considered as a powerful tool for lifetime
                      prediction not only in tool steels, but also in particle
                      reinforced composites and other heterogeneous materials.
                      Moreover, optimization process on microstructural features
                      can be done basedon the results of this study. Consequently,
                      the in-service life of materials may be improved.},
      cin          = {418110 / 411110},
      ddc          = {620},
      cid          = {$I:(DE-82)418110_20140620$ / $I:(DE-82)411110_20140620$},
      typ          = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
      urn          = {urn:nbn:de:hbz:82-rwth-2015-045750},
      url          = {https://publications.rwth-aachen.de/record/482023},
}