Numerical Simulation and Microstructure Examination of a Low-Alloy Structural Steel for Laser Transformation Hardening Treatment

The surface treated by laser phase transformation hardening exhibits superior hardness, enhanced wear resistance, and refined grain structure. In this study, both single-track and two-track laser phase transformation hardening processes were numerically simulated, with the simulation accuracy being verified experimentally. Furthermore, the optimal overlap rate for laser two-track overlay was predicted based on the simulation results. An S355J2G3 metal block specimen was used as a case, numerical simulations of the phase transformation coupled with the temperature field on the specimen’s surface under laser irradiation were carried out using SYSWELD2019 software. The surface temperature distribution and the evolution of phase volume fractions were analyzed. Additionally, the changes in the temperature field within the softening zone and the distribution of tempering structures resulting from two-track laser overlay were examined. The discrepancy between experimental and simulated results for the hardening layer width was approximately 10%, while the error rates for the hardening layer depth and the tempering softening zone were below 5% and 10%, respectively. Based on simulations conducted with varying overlap rates, the flatness metric produces the best results at 50% overlap under these laser processing parameters.

Authors

Publication Details

Journal
Photonics
Published
2025-10-08
DOI
https://doi.org/10.3390/photonics12100992
Primary Topic
High Entropy Alloys Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Numerical Simulation and Microstructure Examination of a Low-Alloy Structural Steel for Laser Transformation Hardening Treatment

Liming Qian, Jiali Ren, Yun Wang, Peiyu He
Photonics
High Entropy Alloys Studies
article

Numerical Simulation and Microstructure Examination of a Low-Alloy Structural Steel for Laser Transformation Hardening Treatment

Liming Qian, Jiali Ren, Yun Wang, Peiyu He
article en

Abstract

The surface treated by laser phase transformation hardening exhibits superior hardness, enhanced wear resistance, and refined grain structure. In this study, both single-track and two-track laser phase transformation hardening processes were numerically simulated, with the simulation accuracy being verified experimentally. Furthermore, the optimal overlap rate for laser two-track overlay was predicted based on the simulation results. An S355J2G3 metal block specimen was used as a case, numerical simulations of the phase transformation coupled with the temperature field on the specimen’s surface under laser irradiation were carried out using SYSWELD2019 software. The surface temperature distribution and the evolution of phase volume fractions were analyzed. Additionally, the changes in the temperature field within the softening zone and the distribution of tempering structures resulting from two-track laser overlay were examined. The discrepancy between experimental and simulated results for the hardening layer width was approximately 10%, while the error rates for the hardening layer depth and the tempering softening zone were below 5% and 10%, respectively. Based on simulations conducted with varying overlap rates, the flatness metric produces the best results at 50% overlap under these laser processing parameters.

PhotonicsVol. 12(10)
National Natural Science Foundation of China, Government of Jiangsu Province
Openalex Percentile: Top 71%
High Entropy Alloys Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.