Development of geometry-driven quantitative prediction for shrinkage porosity in T-junction of steel sand castings

Kamar Mazloum; Amit Sata

Makale detayları

Development of geometry-driven quantitative prediction for shrinkage porosity in T-junction of steel sand castings

Yazarlar:

Kamar Mazloum | Amit Sata

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Experimental Methods in Fluid Flow | Heat and Mass Transfer | Computational Methods in Fluid Flow | Heat and Mass Transfer (Incl. Computational Fluid Dynamics)

Dergi:

Turkish Journal of Engineering Vol.8 Issue 4, pp.640-646

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001329389

pISSN:

2587-1366

Anahtar kelimeler:

Özet:

 Shrinkage porosity poses a significant challenge in metal casting processes, impacting both productivity and energy efficiency, especially when dealing with components that are not accepted or reprocessed. Addressing this issue requires proactive measures, and predictive techniques play a crucial role in minimizing its occurrence. Among these methods, the Criterion Function stands out as a valuable empirical model extensively explored in the literature. By intricately linking solidification processes to the development of shrinkage porosity, the Criterion Function leverages key process parameters, including thermal gradient, molten metal velocity during solidification, and cooling rate, to offer predictive insights into the location and presence of porosity. However, a criterion function is needed that also considers the effect of geometric variations as well as the size of the defect shrinkage porosity. In this study, a casting with three T-joints was taken as a benchmark shape to develop a geometry-based quantitative prediction model for plain carbon steel castings. Real experimental results were combined with solidification simulation results to produce reliable data, which were then used to extrapolate the results. The developed quantitative prediction model, which includes the effect of geometric changes, has been validated and proven effective in predicting shrinkage porosity.

 Shrinkage porosity poses a significant challenge in metal casting processes, impacting both productivity and energy efficiency, especially when dealing with components that are not accepted or reprocessed. Addressing this issue requires proactive measures, and predictive techniques play a crucial role in minimizing its occurrence. Among these methods, the Criterion Function stands out as a valuable empirical model extensively explored in the literature. By intricately linking solidification processes to the development of shrinkage porosity, the Criterion Function leverages key process parameters, including thermal gradient, molten metal velocity during solidification, and cooling rate, to offer predictive insights into the location and presence of porosity. However, a criterion function is needed that also considers the effect of geometric variations as well as the size of the defect shrinkage porosity. In this study, a casting with three T-joints was taken as a benchmark shape to develop a geometry-based quantitative prediction model for plain carbon steel castings. Real experimental results were combined with solidification simulation results to produce reliable data, which were then used to extrapolate the results. The developed quantitative prediction model, which includes the effect of geometric changes, has been validated and proven effective in predicting shrinkage porosity.

 Shrinkage porosity poses a significant challenge in metal casting processes, impacting both productivity and energy efficiency, especially when dealing with components that are not accepted or reprocessed. Addressing this issue requires proactive measures, and predictive techniques play a crucial role in minimizing its occurrence. Among these methods, the Criterion Function stands out as a valuable empirical model extensively explored in the literature. By intricately linking solidification processes to the development of shrinkage porosity, the Criterion Function leverages key process parameters, including thermal gradient, molten metal velocity during solidification, and cooling rate, to offer predictive insights into the location and presence of porosity. However, a criterion function is needed that also considers the effect of geometric variations as well as the size of the defect shrinkage porosity. In this study, a casting with three T-joints was taken as a benchmark shape to develop a geometry-based quantitative prediction model for plain carbon steel castings. Real experimental results were combined with solidification simulation results to produce reliable data, which were then used to extrapolate the results. The developed quantitative prediction model, which includes the effect of geometric changes, has been validated and proven effective in predicting shrinkage porosity.

 Shrinkage porosity poses a significant challenge in metal casting processes, impacting both productivity and energy efficiency, especially when dealing with components that are not accepted or reprocessed. Addressing this issue requires proactive measures, and predictive techniques play a crucial role in minimizing its occurrence. Among these methods, the Criterion Function stands out as a valuable empirical model extensively explored in the literature. By intricately linking solidification processes to the development of shrinkage porosity, the Criterion Function leverages key process parameters, including thermal gradient, molten metal velocity during solidification, and cooling rate, to offer predictive insights into the location and presence of porosity. However, a criterion function is needed that also considers the effect of geometric variations as well as the size of the defect shrinkage porosity. In this study, a casting with three T-joints was taken as a benchmark shape to develop a geometry-based quantitative prediction model for plain carbon steel castings. Real experimental results were combined with solidification simulation results to produce reliable data, which were then used to extrapolate the results. The developed quantitative prediction model, which includes the effect of geometric changes, has been validated and proven effective in predicting shrinkage porosity.

Makale detayları

Development of geometry-driven quantitative prediction for shrinkage porosity in T-junction of steel sand castings

Yazarlar:

Kamar Mazloum | Amit Sata

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Experimental Methods in Fluid Flow | Heat and Mass Transfer | Computational Methods in Fluid Flow | Heat and Mass Transfer (Incl. Computational Fluid Dynamics)

Dergi:

Turkish Journal of Engineering Vol.8 Issue 4, pp.640-646

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001329389

pISSN:

2587-1366

Shrinkage porosity

Plain carbon steel

Casting simulation

Sand casting

Criterion function

Sayı

Makale detayları

Development of geometry-driven quantitative prediction for shrinkage porosity in T-junction of steel sand castings

Yazarlar: Kamar Mazloum | Amit Sata

Yayıncı: Murat YAKAR

Ana Başlıklar: Experimental Methods in Fluid Flow | Heat and Mass Transfer | Computational Methods in Fluid Flow | Heat and Mass Transfer (Incl. Computational Fluid Dynamics)

Dergi: Turkish Journal of Engineering Vol.8 Issue 4, pp.640-646

Belge Tipi: Makale

Yayın Tarihi: 10/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001329389

pISSN: 2587-1366

Shrinkage porosity

Plain carbon steel

Casting simulation

Sand casting

Criterion function

Sayı

Yazarlar:

Kamar Mazloum | Amit Sata

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Experimental Methods in Fluid Flow | Heat and Mass Transfer | Computational Methods in Fluid Flow | Heat and Mass Transfer (Incl. Computational Fluid Dynamics)

Dergi:

Turkish Journal of Engineering Vol.8 Issue 4, pp.640-646

Belge Tipi:

Makale

Yayın Tarihi:

10/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001329389

pISSN:

2587-1366