Open Access
Issue
MATEC Web Conf.
Volume 357, 2022
25th Polish-Slovak Scientific Conference on Machine Modelling and Simulations (MMS 2020)
Article Number 02023
Number of page(s) 8
Section Modelling and Simulation, Structural Optimization
DOI https://doi.org/10.1051/matecconf/202235702023
Published online 22 June 2022
  1. Census of World Casting Production: A Modern Casting Staff Report. Modern Casting, December (2019). [Google Scholar]
  2. P. Popielarski, Z. Ignasza: Effective modelling of phenomena in over-moisture zone existing in porous sand mould subjected to thermal shock. In: Delgado, J., Barbosa de Lima, A. (eds.) Drying and Energy Technologies, Advanced Structured Materials, vol. 63, pp.181–206, Springer, Cham (2016). [CrossRef] [Google Scholar]
  3. D. Hoefert: Quantify Casting Quality Through Filling Conditions. Metalcasting Industry Research. Inter Metalcast 14, 589–598 (2020). [Google Scholar]
  4. R.I. Stephens, A. Fatemi et al.: Metal Fatigue in Engineering. J. Willey & Sons, Inc, (2001). [Google Scholar]
  5. Z. Ignaszak, P. Popielarski, J. Hajkowski, J.B. Prunier: Problem of Acceptability of Internal Porosity in Semi-Finished Cast Product as New Trend - “Tolerance of Damage” Present in Modern Design Office. Defect and Diffusion Forum, 326-328, 612–619 (2012). [CrossRef] [Google Scholar]
  6. F. Herold, K. Bavendiek, R.R. Grigat: A new analysis and classification method for automatic defect recognition in x-ray images of castings. 8th ECNDT Proceedings, The eJournal of Nondestructive Testing Issue, 7, 10 (2002). [Google Scholar]
  7. K. Gawdzińska, J. Grabian, W. Przetakiewicz: Use of X-Ray radiography in finding defects in metal-matrix composite casts. Metalurgija, 47, 3, 199–201 (2008). [Google Scholar]
  8. M. Macko, A. Mroziński, J. Flizikowski: Design and Utility of Specialist Comminution Set-Up for Plastics and Organic Materials. 10.1115/IMECE2011-64155 (2011). [Google Scholar]
  9. Z. Ignaszak, J. Hajkowski Contribution to the identification of porosity type in AlSiCu high-pressure-die-castings by experimental and virtual way. Archives of Foundry Engineering, 15, 1, 143–151 (2015). [CrossRef] [Google Scholar]
  10. M. Macko, A. Mroziński: Computer Aided Design of Wood Pellet Machines. In: Rusiński, E., Pietrusiak, D. (eds) Proceedings of the 14th International Scientific Conference: Computer Aided Engineering. CAE 2018. Lecture Notes in Mechanical Engineering. Springer, Cham (2019). [Google Scholar]
  11. B. Ravi Computer-aided Casting Design and Simulation. STTP, V.N.I.T. Nagpur, July 21 (2009). [Google Scholar]
  12. J.-D. Braun 1990/1998, huitannées de simulation de procédésenfonderie. Hommes et Fonderie, 282 (1998). [Google Scholar]
  13. M. Jolly Casting simulation: How well do reality and virtual casting match? State of art. Review. Int. J. Cast Metals Res., 14, 303–313 (2002). [CrossRef] [Google Scholar]
  14. B. Ravi Casting Simulation - Best Practices. Transactions of 58th IFC, Ahmedabad (2010). [Google Scholar]
  15. D.M. Stefanescu Methodologies for modelling of solidification microstructure and their capabilities. ISIJ, 35, 6, 637–650 (1995). [CrossRef] [Google Scholar]
  16. M. Rappaz Modelling of solidification at various length scales: From the processes to the microstructure and defects. EUROPAM, Mainz, October 16–17 (2003). [Google Scholar]
  17. J.A. Dantzig Solidification Processes: From Dentrites to Design; Continuum Scale Simulation of Engineering Materials Fundamentals - Microstructures - Process Applications, Wiley-VCH (2004). [Google Scholar]
  18. A.A. Burbelko, D. Gurgul, W. Kapturkiewicz, M. Górny Modelling of Eutectic Saturation Influence on Microstructure in Thin Wall Ductile Iron Casting Using Cellular Automata. Archives of Foundry Engineering, 12, 4, 11–16 (2012). [CrossRef] [Google Scholar]
  19. Q. Du, A. Jacot A two-dimensional microsegregation model for the description of microstructure formation during solidification in multicomponent alloys: Formulation and behavior of the model. Acta Materialia, 53, 3479–3493 (2005). [CrossRef] [Google Scholar]
  20. D. Czarnecka-Komorowska, T. Sterzynski, M. Dutkiewicz Polyoxymeth-ylene/Polyhedral Oligomeric Silsesquioxane Composites: Processing, Crystallization, Morphology and Thermo-Mechanical Behavior. International Polymer Processing, 31, 5, 598–606 (2016). [CrossRef] [Google Scholar]
  21. Z. Ignaszak, P. Popielarski, T. Strek Estimation of coupled thermo-physical and thermo-mechanical properties of porous thermolabile ceramic material using Hot Distortion Plus® test. Defect and Diffusion Forum, 312-315, 764–769 (2011). [CrossRef] [Google Scholar]
  22. A. Goldsmith, T. Waterma, H.J. Hirschbaum Handbook of thermophysical properties of solid materials. ARMOUR Research Foundation (1961). [Google Scholar]
  23. K.D. Maglie, A. Cezairhyan, V.L. Peletsky Compendium of Thermophysical Property Measurement Methods, Volume 2: Recommended Measurement Techniques and Practices. Plenum Press, London, New York (1992). [Google Scholar]
  24. R. Sika, J. Hajkowski Synergy of modelling processes in the area of soft and hard modelling, MATEC Web of Conferences, 121, 4009 (2017). [Google Scholar]
  25. P.K. Krajewski, J.S. Suchy, G. Piwowarski, W.K. Krajewski High Temperature Thermal Properties of Bentonite Foundry Sand. Archives of Foundry Engineering, 15, 2, 47–50 (2015). [CrossRef] [Google Scholar]
  26. K. Gawdzinska, L. Chybowski, W. Przetakiewicz Study of Thermal Properties of Cast Metal-Ceramic Composite Foams. Archives of Foundry Engineering, 17, 4, 47–50 (2017). [CrossRef] [Google Scholar]
  27. K. Grzeskowiak, D. Czarnecka-Komorowska, K. Sytek, M. Wojciechowski Influence of waxes remelting used in investment casting on their thermal properties and linear shrinkage. Metalurgija, 54, 2, 350–352 (2015). [Google Scholar]
  28. D. Czarnecka-Komorowska, K. Grześkowiak, P. Popielarski, M. Barczewski, K. Gawdzińska, M. Popławski Polyethylene Wax Modified by Organoclay Bentonite Used in the Lost-Wax Casting Process: Processing-Structure-Property Relationships. Materials, 13, 2255 (2020). [CrossRef] [Google Scholar]

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