Acoustical and Optical Determination of Mechanical Properties of Inorganically-Bound Foundry Core Materials

Inorganically-bound sand cores are used in many light-metal foundries to form cavities in the cast part, which cannot be realised by the mould itself. To enable FEM simulations with core materials, their mechanical properties have to be measured. In this article, we adapt methods to determine the Young’s and shear modulus, the Poisson ratio and the fracture strain of sand cores. This allows us to fully parametrise an ideal brittle FEM model. We found that the Young’s and shear modulus can be obtained acoustically via the impulse excitation technique. The fracture strain was measured with a high-speed camera and a digital image correlation algorithm.

[1]  W. Volk,et al.  Fracture Statistics for Inorganically-Bound Core Materials , 2018, Materials.

[2]  Jue Wang,et al.  Implementation and evaluation of optical flow methods for two-dimensional deformation measurement in comparison to digital image correlation , 2018, Optics and Lasers in Engineering.

[3]  F. Yoshida Description of non-linear unloading curve and closure of cyclic stress-strain loop based on Y-U model , 2018, Journal of Physics: Conference Series.

[4]  M. Schneider,et al.  Modelling the microstructure and computing effective elastic properties of sand core materials , 2018, International Journal of Solids and Structures.

[5]  P. Schumacher,et al.  De-agglomeration rate of silicate bonded sand cores during core removal , 2018 .

[6]  P. Schumacher,et al.  Foundry sand core property assessment by 3-point bending test evaluation , 2016 .

[7]  W. Volk,et al.  Optical Measurement Techniques Determine Young’s Modulus of Sand Core Materials , 2016, International Journal of Metalcasting.

[8]  Primož Podržaj,et al.  AN ADVANCED COARSE-FINE SEARCH APPROACH FOR DIGITAL IMAGE CORRELATION APPLICATIONS , 2016 .

[9]  Wei Tong,et al.  Fast, Robust and Accurate Digital Image Correlation Calculation Without Redundant Computations , 2013, Experimental Mechanics.

[10]  Alberto Somoza,et al.  Measurement of the Young's modulus in particulate epoxy composites using the impulse excitation technique , 2010 .

[11]  Xiaoyong Liu,et al.  Subpixel In-Plane Displacement Measurement Using Digital Image Correlation and Artificial Neural Networks , 2010, 2010 Symposium on Photonics and Optoelectronics.

[12]  Damien Garcia Computational Statistics and Data Analysis Robust Smoothing of Gridded Data in One and Higher Dimensions with Missing Values , 2022 .

[13]  Anand Asundi,et al.  Two-dimensional digital image correlation for in-plane displacement and strain measurement: a review , 2009 .

[14]  Assen Shulev,et al.  Study of the deformation characteristics of window security film by digital image correlation techniques , 2009 .

[15]  S. Roux,et al.  “Finite-Element” Displacement Fields Analysis from Digital Images: Application to Portevin–Le Châtelier Bands , 2006 .

[16]  Ajay Mahajan,et al.  Measurement of Whole-Field Surface Displacements and Strain Using a Genetic Algorithm Based Intelligent Image Correlation Method , 2004 .

[17]  K. S. Ravichandran,et al.  Elastic properties of in-situ processed Ti–TiB composites measured by impulse excitation of vibration , 1999 .

[18]  B. Bollen,et al.  Impulse excitation apparatus to measure resonant frequencies, elastic moduli, and internal friction at room and high temperature , 1997 .

[19]  A. Balinski,et al.  New generation of ecological silicate binders , 2011 .

[20]  H. Hiller In: Ullmann''''s Encyclopedia of Industrial Chemistry , 1989 .