BIŽAL, Ana ;KLEMENC, Jernej ;FAJDIGA, Matija . Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 60, n.6, p. 407-416, june 2018. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/evaluating-the-statistical-significance-of-a-fatigue-life-reduction-due-to-macro-porosity/>. Date accessed: 19 apr. 2024. doi:http://dx.doi.org/10.5545/sv-jme.2013.1453.
Bižal, A., Klemenc, J., & Fajdiga, M. (2014). Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity. Strojniški vestnik - Journal of Mechanical Engineering, 60(6), 407-416. doi:http://dx.doi.org/10.5545/sv-jme.2013.1453
@article{sv-jmesv-jme.2013.1453,
author = {Ana Bižal and Jernej Klemenc and Matija Fajdiga},
title = {Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {60},
number = {6},
year = {2014},
keywords = {AlSi9Cu3 alloy; porosity; fatigue-life; ANOVA; MANOVA; linear regression with dummy variables},
abstract = {This study focuses on an evaluation of the significance of the fatigue-life reduction due to macro-porosity present in pressure-die-casted aluminium specimens. Three statistical models, i.e., univariate analysis of variance, multivariate analysis of variance and linear regression with dummy variables, were applied to test the statistical significance of the fatigue-life reduction. The three statistical models were applied for the case of experimentally determined fatigue-life data for an AlSi9Cu3 alloy with different levels of macro-porosity. Cylindrical specimens according to ASTM E606 were manufactured by pressure die casting using different manufacturing parameters (die pressure, die temperature) to artificially introduce detectable macro-pores into the specimens. The manufactured specimens were classified into three groups, representing their levels of porosity, which were identified based on x-ray images of the specimens. For each group, strain-controlled fatigue tests were performed at different strain levels. Of these approaches, linear regression with dummy variables proved to be the most appropriate, due to its ability to robustly identify the differences between the fatigue lives for different porosity levels.},
issn = {0039-2480}, pages = {407-416}, doi = {10.5545/sv-jme.2013.1453},
url = {https://www.sv-jme.eu/article/evaluating-the-statistical-significance-of-a-fatigue-life-reduction-due-to-macro-porosity/}
}
Bižal, A.,Klemenc, J.,Fajdiga, M. 2014 June 60. Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 60:6
%A Bižal, Ana %A Klemenc, Jernej %A Fajdiga, Matija %D 2014 %T Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity %B 2014 %9 AlSi9Cu3 alloy; porosity; fatigue-life; ANOVA; MANOVA; linear regression with dummy variables %! Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity %K AlSi9Cu3 alloy; porosity; fatigue-life; ANOVA; MANOVA; linear regression with dummy variables %X This study focuses on an evaluation of the significance of the fatigue-life reduction due to macro-porosity present in pressure-die-casted aluminium specimens. Three statistical models, i.e., univariate analysis of variance, multivariate analysis of variance and linear regression with dummy variables, were applied to test the statistical significance of the fatigue-life reduction. The three statistical models were applied for the case of experimentally determined fatigue-life data for an AlSi9Cu3 alloy with different levels of macro-porosity. Cylindrical specimens according to ASTM E606 were manufactured by pressure die casting using different manufacturing parameters (die pressure, die temperature) to artificially introduce detectable macro-pores into the specimens. The manufactured specimens were classified into three groups, representing their levels of porosity, which were identified based on x-ray images of the specimens. For each group, strain-controlled fatigue tests were performed at different strain levels. Of these approaches, linear regression with dummy variables proved to be the most appropriate, due to its ability to robustly identify the differences between the fatigue lives for different porosity levels. %U https://www.sv-jme.eu/article/evaluating-the-statistical-significance-of-a-fatigue-life-reduction-due-to-macro-porosity/ %0 Journal Article %R 10.5545/sv-jme.2013.1453 %& 407 %P 10 %J Strojniški vestnik - Journal of Mechanical Engineering %V 60 %N 6 %@ 0039-2480 %8 2018-06-28 %7 2018-06-28
Bižal, Ana, Jernej Klemenc, & Matija Fajdiga. "Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity." Strojniški vestnik - Journal of Mechanical Engineering [Online], 60.6 (2014): 407-416. Web. 19 Apr. 2024
TY - JOUR AU - Bižal, Ana AU - Klemenc, Jernej AU - Fajdiga, Matija PY - 2014 TI - Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity JF - Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2013.1453 KW - AlSi9Cu3 alloy; porosity; fatigue-life; ANOVA; MANOVA; linear regression with dummy variables N2 - This study focuses on an evaluation of the significance of the fatigue-life reduction due to macro-porosity present in pressure-die-casted aluminium specimens. Three statistical models, i.e., univariate analysis of variance, multivariate analysis of variance and linear regression with dummy variables, were applied to test the statistical significance of the fatigue-life reduction. The three statistical models were applied for the case of experimentally determined fatigue-life data for an AlSi9Cu3 alloy with different levels of macro-porosity. Cylindrical specimens according to ASTM E606 were manufactured by pressure die casting using different manufacturing parameters (die pressure, die temperature) to artificially introduce detectable macro-pores into the specimens. The manufactured specimens were classified into three groups, representing their levels of porosity, which were identified based on x-ray images of the specimens. For each group, strain-controlled fatigue tests were performed at different strain levels. Of these approaches, linear regression with dummy variables proved to be the most appropriate, due to its ability to robustly identify the differences between the fatigue lives for different porosity levels. UR - https://www.sv-jme.eu/article/evaluating-the-statistical-significance-of-a-fatigue-life-reduction-due-to-macro-porosity/
@article{{sv-jme}{sv-jme.2013.1453},
author = {Bižal, A., Klemenc, J., Fajdiga, M.},
title = {Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {60},
number = {6},
year = {2014},
doi = {10.5545/sv-jme.2013.1453},
url = {https://www.sv-jme.eu/article/evaluating-the-statistical-significance-of-a-fatigue-life-reduction-due-to-macro-porosity/}
}
TY - JOUR AU - Bižal, Ana AU - Klemenc, Jernej AU - Fajdiga, Matija PY - 2018/06/28 TI - Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 60, No 6 (2014): Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2013.1453 KW - AlSi9Cu3 alloy, porosity, fatigue-life, ANOVA, MANOVA, linear regression with dummy variables N2 - This study focuses on an evaluation of the significance of the fatigue-life reduction due to macro-porosity present in pressure-die-casted aluminium specimens. Three statistical models, i.e., univariate analysis of variance, multivariate analysis of variance and linear regression with dummy variables, were applied to test the statistical significance of the fatigue-life reduction. The three statistical models were applied for the case of experimentally determined fatigue-life data for an AlSi9Cu3 alloy with different levels of macro-porosity. Cylindrical specimens according to ASTM E606 were manufactured by pressure die casting using different manufacturing parameters (die pressure, die temperature) to artificially introduce detectable macro-pores into the specimens. The manufactured specimens were classified into three groups, representing their levels of porosity, which were identified based on x-ray images of the specimens. For each group, strain-controlled fatigue tests were performed at different strain levels. Of these approaches, linear regression with dummy variables proved to be the most appropriate, due to its ability to robustly identify the differences between the fatigue lives for different porosity levels. UR - https://www.sv-jme.eu/article/evaluating-the-statistical-significance-of-a-fatigue-life-reduction-due-to-macro-porosity/
Bižal, Ana, Klemenc, Jernej, AND Fajdiga, Matija. "Evaluating the Statistical Significance of a Fatigue-Life Reduction Due to Macro-Porosity" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 60 Number 6 (28 June 2018)
Strojniški vestnik - Journal of Mechanical Engineering 60(2014)6, 407-416
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
This study focuses on an evaluation of the significance of the fatigue-life reduction due to macro-porosity present in pressure-die-casted aluminium specimens. Three statistical models, i.e., univariate analysis of variance, multivariate analysis of variance and linear regression with dummy variables, were applied to test the statistical significance of the fatigue-life reduction. The three statistical models were applied for the case of experimentally determined fatigue-life data for an AlSi9Cu3 alloy with different levels of macro-porosity. Cylindrical specimens according to ASTM E606 were manufactured by pressure die casting using different manufacturing parameters (die pressure, die temperature) to artificially introduce detectable macro-pores into the specimens. The manufactured specimens were classified into three groups, representing their levels of porosity, which were identified based on x-ray images of the specimens. For each group, strain-controlled fatigue tests were performed at different strain levels. Of these approaches, linear regression with dummy variables proved to be the most appropriate, due to its ability to robustly identify the differences between the fatigue lives for different porosity levels.