LÓPEZ-MARTÍNEZ, Edgar ;VERGARA-HERNÁNDEZ, Héctor Javier;SERNA, Sergio ;CAMPILLO, Bernardo . Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 61, n.12, p. 741-750, june 2018. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/artificial-neural-networks-to-estimate-the-thermal-properties-of-an-experimental-micro-alloyed-steel-and-their-application-to-the-welding-thermal-analysis/>. Date accessed: 20 dec. 2024. doi:http://dx.doi.org/10.5545/sv-jme.2015.2610.
López-Martínez, E., Vergara-Hernández, H., Serna, S., & Campillo, B. (2015). Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis. Strojniški vestnik - Journal of Mechanical Engineering, 61(12), 741-750. doi:http://dx.doi.org/10.5545/sv-jme.2015.2610
@article{sv-jmesv-jme.2015.2610,
author = {Edgar López-Martínez and Héctor Javier Vergara-Hernández and Sergio Serna and Bernardo Campillo},
title = {Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {61},
number = {12},
year = {2015},
keywords = {heat capacity; thermal conductivity; micro-alloyed steel; heat-affected zone; artificial neural network},
abstract = {The effect of welding thermal cycles on the micro-structure and micro-hardness of the heat-affected zone (HAZ) of an experimental micro-alloyed steel was studied. Due to the experimental difficulties involved in acquiring the thermal cycles, these were determined by applying the solutions of Rosenthal’s equations for thick and thin plates. However, to perform this thermal analysis, it requires knowledge of the thermal properties of the micro-alloyed steel; therefore, the implementation of two artificial neural networks (ANNs) was proposed as tools to estimate the thermal conductivity and the heat capacity as a function of the chemical composition and temperature. The ANNs were trained with information obtained from the literature review and then tested with steels that were not used for the training step, but with thermal known properties. A good approximation between the actual and the estimated properties was observed. It was determined that the microstructural characteristics of the welding zone are a function of the thermal cycles, although there is no great difference in micro-hardness. Martensite was not observed in the welding zone; therefore, the welds of this steel, under these welding conditions, could not be susceptible to hydrogen induced cracking (HIC).},
issn = {0039-2480}, pages = {741-750}, doi = {10.5545/sv-jme.2015.2610},
url = {https://www.sv-jme.eu/article/artificial-neural-networks-to-estimate-the-thermal-properties-of-an-experimental-micro-alloyed-steel-and-their-application-to-the-welding-thermal-analysis/}
}
López-Martínez, E.,Vergara-Hernández, H.,Serna, S.,Campillo, B. 2015 June 61. Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 61:12
%A López-Martínez, Edgar %A Vergara-Hernández, Héctor Javier %A Serna, Sergio %A Campillo, Bernardo %D 2015 %T Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis %B 2015 %9 heat capacity; thermal conductivity; micro-alloyed steel; heat-affected zone; artificial neural network %! Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis %K heat capacity; thermal conductivity; micro-alloyed steel; heat-affected zone; artificial neural network %X The effect of welding thermal cycles on the micro-structure and micro-hardness of the heat-affected zone (HAZ) of an experimental micro-alloyed steel was studied. Due to the experimental difficulties involved in acquiring the thermal cycles, these were determined by applying the solutions of Rosenthal’s equations for thick and thin plates. However, to perform this thermal analysis, it requires knowledge of the thermal properties of the micro-alloyed steel; therefore, the implementation of two artificial neural networks (ANNs) was proposed as tools to estimate the thermal conductivity and the heat capacity as a function of the chemical composition and temperature. The ANNs were trained with information obtained from the literature review and then tested with steels that were not used for the training step, but with thermal known properties. A good approximation between the actual and the estimated properties was observed. It was determined that the microstructural characteristics of the welding zone are a function of the thermal cycles, although there is no great difference in micro-hardness. Martensite was not observed in the welding zone; therefore, the welds of this steel, under these welding conditions, could not be susceptible to hydrogen induced cracking (HIC). %U https://www.sv-jme.eu/article/artificial-neural-networks-to-estimate-the-thermal-properties-of-an-experimental-micro-alloyed-steel-and-their-application-to-the-welding-thermal-analysis/ %0 Journal Article %R 10.5545/sv-jme.2015.2610 %& 741 %P 10 %J Strojniški vestnik - Journal of Mechanical Engineering %V 61 %N 12 %@ 0039-2480 %8 2018-06-27 %7 2018-06-27
López-Martínez, Edgar, Héctor Javier Vergara-Hernández, Sergio Serna, & Bernardo Campillo. "Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis." Strojniški vestnik - Journal of Mechanical Engineering [Online], 61.12 (2015): 741-750. Web. 20 Dec. 2024
TY - JOUR AU - López-Martínez, Edgar AU - Vergara-Hernández, Héctor Javier AU - Serna, Sergio AU - Campillo, Bernardo PY - 2015 TI - Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis JF - Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2015.2610 KW - heat capacity; thermal conductivity; micro-alloyed steel; heat-affected zone; artificial neural network N2 - The effect of welding thermal cycles on the micro-structure and micro-hardness of the heat-affected zone (HAZ) of an experimental micro-alloyed steel was studied. Due to the experimental difficulties involved in acquiring the thermal cycles, these were determined by applying the solutions of Rosenthal’s equations for thick and thin plates. However, to perform this thermal analysis, it requires knowledge of the thermal properties of the micro-alloyed steel; therefore, the implementation of two artificial neural networks (ANNs) was proposed as tools to estimate the thermal conductivity and the heat capacity as a function of the chemical composition and temperature. The ANNs were trained with information obtained from the literature review and then tested with steels that were not used for the training step, but with thermal known properties. A good approximation between the actual and the estimated properties was observed. It was determined that the microstructural characteristics of the welding zone are a function of the thermal cycles, although there is no great difference in micro-hardness. Martensite was not observed in the welding zone; therefore, the welds of this steel, under these welding conditions, could not be susceptible to hydrogen induced cracking (HIC). UR - https://www.sv-jme.eu/article/artificial-neural-networks-to-estimate-the-thermal-properties-of-an-experimental-micro-alloyed-steel-and-their-application-to-the-welding-thermal-analysis/
@article{{sv-jme}{sv-jme.2015.2610},
author = {López-Martínez, E., Vergara-Hernández, H., Serna, S., Campillo, B.},
title = {Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {61},
number = {12},
year = {2015},
doi = {10.5545/sv-jme.2015.2610},
url = {https://www.sv-jme.eu/article/artificial-neural-networks-to-estimate-the-thermal-properties-of-an-experimental-micro-alloyed-steel-and-their-application-to-the-welding-thermal-analysis/}
}
TY - JOUR AU - López-Martínez, Edgar AU - Vergara-Hernández, Héctor Javier AU - Serna, Sergio AU - Campillo, Bernardo PY - 2018/06/27 TI - Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 61, No 12 (2015): Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2015.2610 KW - heat capacity, thermal conductivity, micro-alloyed steel, heat-affected zone, artificial neural network N2 - The effect of welding thermal cycles on the micro-structure and micro-hardness of the heat-affected zone (HAZ) of an experimental micro-alloyed steel was studied. Due to the experimental difficulties involved in acquiring the thermal cycles, these were determined by applying the solutions of Rosenthal’s equations for thick and thin plates. However, to perform this thermal analysis, it requires knowledge of the thermal properties of the micro-alloyed steel; therefore, the implementation of two artificial neural networks (ANNs) was proposed as tools to estimate the thermal conductivity and the heat capacity as a function of the chemical composition and temperature. The ANNs were trained with information obtained from the literature review and then tested with steels that were not used for the training step, but with thermal known properties. A good approximation between the actual and the estimated properties was observed. It was determined that the microstructural characteristics of the welding zone are a function of the thermal cycles, although there is no great difference in micro-hardness. Martensite was not observed in the welding zone; therefore, the welds of this steel, under these welding conditions, could not be susceptible to hydrogen induced cracking (HIC). UR - https://www.sv-jme.eu/article/artificial-neural-networks-to-estimate-the-thermal-properties-of-an-experimental-micro-alloyed-steel-and-their-application-to-the-welding-thermal-analysis/
López-Martínez, Edgar, Vergara-Hernández, Héctor, Serna, Sergio, AND Campillo, Bernardo. "Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 61 Number 12 (27 June 2018)
Strojniški vestnik - Journal of Mechanical Engineering 61(2015)12, 741-750
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
The effect of welding thermal cycles on the micro-structure and micro-hardness of the heat-affected zone (HAZ) of an experimental micro-alloyed steel was studied. Due to the experimental difficulties involved in acquiring the thermal cycles, these were determined by applying the solutions of Rosenthal’s equations for thick and thin plates. However, to perform this thermal analysis, it requires knowledge of the thermal properties of the micro-alloyed steel; therefore, the implementation of two artificial neural networks (ANNs) was proposed as tools to estimate the thermal conductivity and the heat capacity as a function of the chemical composition and temperature. The ANNs were trained with information obtained from the literature review and then tested with steels that were not used for the training step, but with thermal known properties. A good approximation between the actual and the estimated properties was observed. It was determined that the microstructural characteristics of the welding zone are a function of the thermal cycles, although there is no great difference in micro-hardness. Martensite was not observed in the welding zone; therefore, the welds of this steel, under these welding conditions, could not be susceptible to hydrogen induced cracking (HIC).