@phdthesis{Wang,
  author    = {Wang, Jiasheng},
  title     = {Lebensdauerabsch{\"a}tzung von Bauteilen aus globularem Grauguss auf der Grundlage der lokalen gießprozessabh{\"a}ngigen Werkstoffzust{\"a}nde},
  doi       = {10.25643/bauhaus-universitaet.4554},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220111-45542},
  school      = {Bauhaus-Universit{\"a}t Weimar},
  pages     = {165},
  abstract  = {Das Ziel der Arbeit ist, eine m{\"o}gliche Verbesserung der G{\"u}te der Lebensdauervorhersage f{\"u}r Gusseisenwerkstoffe mit Kugelgraphit zu erreichen, wobei die Gießprozesse verschiedener Hersteller ber{\"u}cksichtigt werden. Im ersten Schritt wurden Probenk{\"o}rper aus GJS500 und GJS600 von mehreren Gusslieferanten gegossen und daraus Schwingproben erstellt. Insgesamt wurden Schwingfestigkeitswerte der einzelnen gegossenen Proben sowie der Proben des Bauteils von verschiedenen Gussherstellern weltweit entweder durch direkte Schwingversuche oder durch eine Sammlung von Betriebsfestigkeitsversuchen bestimmt. Dank der metallografischen Arbeit und Korrelationsanalyse konnten drei wesentliche Parameter zur Bestimmung der lokalen Dauerfestigkeit festgestellt werden: 1. statische Festigkeit, 2. Ferrit- und Perlitanteil der Mikrostrukturen und 3. Kugelgraphitanzahl pro Fl{\"a}cheneinheit. Basierend auf diesen Erkenntnissen wurde ein neues Festigkeitsverh{\"a}ltnisdiagramm (sogenanntes Sd/Rm-SG-Diagramm) entwickelt. Diese neue Methodik sollte vor allem erm{\"o}glichen, die Bauteildauerfestigkeit auf der Grundlage der gemessenen oder durch eine Gießsimulation vorhersagten lokalen Zugfestigkeitswerte sowie Mikrogef{\"u}genstrukturen besser zu prognostizieren. Mithilfe der Versuche sowie der Gießsimulation ist es gelungen, unterschiedliche Methoden der Lebensdauervorhersage unter Ber{\"u}cksichtigung der Herstellungsprozesse weiterzuentwickeln.},
  subject      = {Grauguss},
  language  = {de}
}
@inproceedings{SwaddiwudhipongThoLiu2004,
  author    = {Swaddiwudhipong, Somsak and Tho, Kee Kiat and Liu, Zishun},
  title     = {Material characterization using artificial neural network},
  doi       = {10.25643/bauhaus-universitaet.155},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20111215-1550},
  year      = {2004},
  abstract  = {Indentation experiments have been carried out over the past century to determine hardness of materials. Modern indentation machines have the capability to continuously monitor load and displacement to high precision and accuracy. In recent years, research interests have focussed on methods to extract material properties from indentation load-displacement curves. Analytical methods to interpret the indentation load-displacement curves are difficult to formulate due to material and geometric nonlinearities as well as complex contact interactions. In the present study, an artificial neural network model was constructed for interpretation of indentation load-displacement curves. Large strain-large deformation finite element analyses were first carried out to simulate indentation experiments. The data from finite element analyses were then used to train the artificial neural network model. The artificial neural network model was able to accurately determine the material properties when presented with load-displacement curves which were not used in the training process. The proposed artificial neural network model is robust and directly relates the characteristics of the indentation loaddisplacement curve to the elasto-plastic material properties.},
  subject      = {Neuronales Netz},
  language  = {en}
}
@article{MotraHildebrandDimmigOsburg,
  author    = {Motra, Hem Bahadur and Hildebrand, J{\"o}rg and Dimmig-Osburg, Andrea},
  title     = {Assessment of strain measurement techniques to characterise mechanical properties of structural steel},
  series = {Engineering Science and Technology, an International Journal},
  journal   = {Engineering Science and Technology, an International Journal},
  doi       = {10.1016/j.jestch.2014.07.006},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170425-31540},
  pages     = {260 -- 269},
  abstract  = {Strain measurement is important in mechanical testing. A wide variety of techniques exists for measuring strain in the tensile test; namely the strain gauge, extensometer, stress and strain determined by machine crosshead motion, Geometric Moire technique, optical strain measurement techniques and others. Each technique has its own advantages and disadvantages. The purpose of this study is to quantitatively compare the strain measurement techniques. To carry out the tensile test experiments for S 235, sixty samples were cut from the web of the I-profile in longitudinal and transverse directions in four different dimensions. The geometry of samples are analysed by 3D scanner and vernier caliper. In addition, the strain values were determined by using strain gauge, extensometer and machine crosshead motion. Three techniques of strain measurement are compared in quantitative manner based on the calculation of mechanical properties (modulus of elasticity, yield strength, tensile strength, percentage elongation at maximum force) of structural steel. A statistical information was used for evaluating the results. It is seen that the extensometer and strain gauge provided reliable data, however the extensometer offers several advantages over the strain gauge and crosshead motion for testing structural steel in tension. Furthermore, estimation of measurement uncertainty is presented for the basic material parameters extracted through strain measurement.},
  subject      = {Baustahl},
  language  = {en}
}