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Sökning: WFRF:(Labbe C) > Chalmers tekniska högskola

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1.
  • Berg, Frenk van den, et al. (författare)
  • Results of the European collaborative project "Product Uniformity Control" to improve the inline sensing of mechanical properties and microstructure of automotive steels
  • 2018
  • Ingår i: e-Journal of Nondestructive Testing (eJNDT). - 1435-4934. ; 23:8
  • Tidskriftsartikel (refereegranskat)abstract
    • A European consortium consisting of four major steel manufacturers and ten academic technology institutes has conducted a research and development project, called “Product Uniformity Control“ (PUC) in the period 2013 to 2017. This project aimed to develop and improve non-destructive (inline) measurement techniques to characterise the (uniformity of the) microstructure of steel strip products. In this project, a multitude of strip steel samples from various stages of production have been collected from the four participating steel manufacturers. The samples have been characterised in various ways, namely on their (1) non-destructive measurement parameters using different techniques suited for inline evaluation, (2) fundamental ultrasonic and electromagnetic properties (wave speed, ultrasonic attenuation, magnetisation loops, coercive field), (3) tensile properties (stress-strain curves) and (4) microstructure (by optical micrographs and EBSD images). The correlations between these different characterisations will be addressed. Besides the experimental characterisation, a strong accent has been on modelling activities: during the project, fundamental models have been developed to describe, starting from 2D and 3D microstructures, the ultrasonic and magnetic properties, which are next used as input to sensor models that predict the output of the inline measurement systems. This contribution presents the recent results of experimental work, which underlines the importance of associated modelling studies for the interpretation of the measurement data for the benefit of inline characterisation of the mechanical properties complementary to traditional destructive tensile testing.
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2.
  • Van Den Berg, F. D., et al. (författare)
  • Product uniformity control - A research collaboration of european steel industries to non-destructive evaluation of microstructure and mechanical properties
  • 2018
  • Ingår i: Stud. Appl. Electromagn. Mech.. - : IOS Press. - 9781614998358 ; 43, s. 120-129
  • Konferensbidrag (refereegranskat)abstract
    • In steel manufacturing, the conventional method to determine the mechanical properties and microstructure is by offline, destructive (lab-)characterisation of sample material that is typically taken from the head or the tail of the coil. Since coils can be up to 7 km long, the samples are not always representative for the main coil body. Also, the time delay (typically a few days) between the actual production and the availability of the characterisation results implies that these results cannot be exploited for real-time adaptation of the process settings. Information about the microstructure and material properties can also be obtained from electromagnetic (EM) and ultrasonic (US) parameters, which can be measured in real-time, non-destructively, and over the full length of the steel strip product. With the aim to improve the consistency in product quality by use of inline EM and US measurements, a European project called "Product Uniformity Control" (PUC) has been set up as a broad collaboration between 4 major European Steel Manufacturers and 10 Universities / Research institutes. Using both numerical simulations and experimental characterisations, we study the inline measured EM and US parameters in regard of the microstructural and mechanical properties. In this way, we aim to establish an improved understanding of their mutual relationships, and to apply this knowledge in existing and new nondestructive evaluation techniques. In this paper, the concerted approach of modelling and experimental validation will be addressed, and results of this work will be shown in combination with inline measured data.
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