Artificial Neural Networks to Estimate the Thermal Properties of an Experimental Micro-Alloyed Steel and Their Application to the Welding Thermal Analysis

1478 Ogledov
1125 Prenosov
Izvoz citacije: ABNT
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/sl/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: 17 sep. 2021. 
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/sl/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/sl/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.  17 Sep. 2021
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/sl/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/sl/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/sl/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)

Avtorji

Inštitucije

  • National Autonomous University of Mexico, Faculty of Chemistry, Mexico 1
  • Morelia Institute of Technology, Metallurgy Science Postgraduate Programme, Mexico 2
  • State Autonomous University of Morelos, Research Center in Engineering and Applied Sciences, Mexico 3
  • National Autonomous University of Mexico, Institute of Physical Sciences, Mexico 4

Informacije o papirju

Strojniški vestnik - Journal of Mechanical Engineering 61(2015)12, 741-750

https://doi.org/10.5545/sv-jme.2015.2610

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).

heat capacity; thermal conductivity; micro-alloyed steel; heat-affected zone; artificial neural network