Modified Shape of Dynamic Master Curves due to Adiabatic Effects

AbstractWithin a joint project of IWM/Freiburg and MPA/Stuttgart the fracture toughness of a 22 NiMoCr 3 7 steel (A 508 Cl.2) was characterized at IWM with SE(B)10/10- und SE(B)40/20-specimens at -20 °C and high crack loading rates in the range of 103 to 106 MPa√m s-1, see Böhme et al. (2012 and 2013). The single temperature Master Curve evaluation according to ASTM E1921 and Wallin (2011) resulted in part in 5%-lower-bound fracture toughness versus temperature curves below the deterministic ASME lower bound KIR-reference-curve. At a first glance, this seems to violate the ASME KIR-concept, however, possibly this just indicates, that the conventional MC-evaluation has to be modified for elevated loading rates. Adiabatic heating in the vicinity of the crack tip could be one reason for that, as already argued in Schindler (2013 and 2015).Therefore, additional SE(B)-tests at temperatures of -20 °C, 0 °C and +20 °C were performed at IWM within the current follow-up joint IWM-MPA project. The new IWM-results show in agreement with previous investigations by Viehrig et al. (2010) and Schindler et al. (2013 and 2015) that the Master Curves at elevated loading rates are steeper than at quasistatic loading, probably due to local adiabatic heating in the vicinity of the crack tip. Therefore, the temperature field around the crack tip has been measured with a high speed infrared camera and has been compared to results of a numerical simulation. Up to crack initiation, a local adiabatic rise in temperature of the order of magnitude of about 60 K was measured and calculated in the vicinity of the crack tip at a crack loading rate of about 106 MPa√m s-1. In order to take into account this adiabatic effect, the dynamic master curves were evaluated by applying an adjusted MC shape parameter. This finally leads to more plausible results for the dynamic Master Curves. Thus, the choice of a rate dependent shape parameter p should be considered for future modifications of the elevated loading rate appendix of ASTM E1921

Untersuchung und Modellierung von sprödem Versagen und lokalem Rissarrest bei ferritischen Stählen unter dynamischer Beanspruchung

The main objective of this study is to obtain a better understanding of the micro mechanisms that lead to cleavage fracture of ferritic-bainitic steels under dynamic loading conditions. Also, the new-found knowledge was used to improve local cleavage fracture models. Initially, an extensive data base of dynamic fracture toughness experiments was provided. A combined fractographic and mostly numerical approach with the finite element method was chosen to identify and quantify the relevant micro mechanisms, whereas the finite element method was also used to calculate the probability of failure, and perform the model modification. It was shown that adiabatic heating is a highly complex phenomenon which controls cleavage fracture initiation collectively with the increase in local strain rate. The macroscopic fracture behavior, as well as the origin of fracture, is significantly impacted by this interaction. Also, local crack arrest is highly relevant under dynamic conditions, and detectable in form of so-called cleavage fracture islands on the fracture surface. Thereupon, macroscopic fracture behavior is fundamentally changed. The mechanical field variables at the origin of cleavage fracture initiation are identical with those witnessed under quasi-static conditions. The initiation mechanism can therefore solely be described by the use of adequate temperature- and strain rate dependent material properties in combination with the consideration of heat generation and heat conduction. However, the application of established local cleavage fracture concepts under dynamic conditions showed that it is not possible to predict fracture behavior correctly. The discrepancy strongly correlates with the observed amount of local crack arrest incidences. Finally, a micro-mechanistically motivated model modification in the shape of a local arrest condition is proposed. It considerably improves the analysis accuracy and applicability of local cleavage fracture models subjected to dynamic loading conditions

MaterialDigital

The MaterialDigital or BWMD dataset is an RDF data repository generated by the Use Case Metals within the framework of the MaterialDigital project. It showcases the digitalization of the aluminum permanent mold casting process, followed by a two-stage heat treatment, involving solution annealing and artificial aging by means of ontology based semantic data structures. For the purposes of the study, the casting alloy AlSi10Mg was used. In two casting campaigns, project-specific databases were established using test bars, which were subjected to mechanical and analytical material characterization. A demonstrator casting was also cast, and subjected to static bending stress on a laboratory test rig. For both casting campaigns, variations in chemical composition of the AlSi10Mg alloy were introduced with respect to the silicon and magnesium content. Accompanying the casting campaigns were casting simulations to refine model parameters through temperature measurements in the test bar mold. There were two primary objectives of the project. The first aim was to leverage the digital workflow to structure the data from the test bar characterization campaign. Individual data sets from each process step were linked together to create a comprehensive and coherent knowledge graph of the process chain, which was then transferred to a graph database. The development of a domain ontology for the process chain allowed the extraction of expert knowledge on the impact of chemical composition and heat treatment parameters on various mechanical properties from the material data space. Beyond querying metadata, the heterogeneous raw data sets could also be accessed by machines, as evidenced by tensile tests. This technology is thus transformative in its ability to capture material- and process-specific expert knowledge, serving as the basis for further data-based analyses. In practical terms, this can guide decision-making regarding the ideal heat treatment parameters given the chemical composition that will ensure the attainment of specific material strength.Fördermittelgeber: Ministerium für Wirtschaft, Arbeit und Wohnungsbau Baden-Württemberg -WM BW-In order to work with this dataset download and unzip the folder BWMD_Dataset.zip. The dataset includes the BWMD Ontology file (BWMD_Ontologie_2020-08-12.owl) in non modularized version (as legacy of the MaterialDigital project), which can be opened e.g. with the free software Protégé (https://protege.stanford.edu/about.php). The process semantic data model or generic process graph template (Graph-ProcessTemplate-bwmd-2020-05-15.kdb) is included as well and can be visualized and edited with the Inforapid KnowledgeBase Builder software (https://www.inforapid.com/en-us/). However, the main feature of the uploaded dataset is the complete BWMD RDF graph database (BWMD_full_DB_Anonymized.ttl) generated based on the generic graph template pattern for all the semantically modeled processes. Note that this file contains as well the BWMD Ontology and all the inferred generated statements with the reasoner OWL2-2RL (Optimized) from the Graph DB Free Software. To work with the BWMD RDF graph database import the file BWMD_full_DB_Anonymized.ttl in a graph instance (e.g. Graph DB Free). Once the RDF graph is imported in a local repository it is possible to further work with it and to run SPARQL queries to extract information. To facilitate the user the knowledge extraction process, two Jupyter Notebooks are included (query_mdbw.ipynb and plot_tensile_tests.ipynb) with integrated SPARQL queries. To run these Jupyter Notebooks locally, please keep in mind to download the necessary Python packages and to update the SPARQL endpoint with your own one a the name of the repository you created to import the RDF BWMD database (BWMD_full_DB_Anonymized.ttl)