Abstract for presentation (Poster or Podium) with a Paper in the Conference Proceedings
Infrastructure Systems
Arman Ali Mohammadi, PhD
Graduate Teacher Assistant
University of Nevada, Las Vegas
Las Vegas, NV, United States
Arman Ali Mohammadi, PhD
Graduate Teacher Assistant
University of Nevada, Las Vegas
Las Vegas, NV, United States
Arman Ali Mohammadi
University of Nevada, Las Vegas
Las Vegas, Nevada, United States
Rails' surfaces are often subjected to continuous loading, leading to inevitable wear and tear. Consequently, repairs are crucial to ensure optimal performance in a railroad network. Traditional repair methods are both time-consuming and costly, prompting the exploration of innovative approaches. One such approach involves on-site overlay arc welding as an alternative to replacing the entire rail section. This study presents the development of a finite element (FE) model to simulate a submerged arc welding (SAW) process, which serves as an additive manufacturing technique for the repair of 136-lb/yd (136RE) rails, commonly employed in heavy freight and passenger rail systems throughout the United States.
To validate the developed FE model, experimental lab investigations were conducted. A worn section of the 136RE rail was selected for the study. After milling and flattening the rail's surface, a submerged arc welding process was applied to rebuild the rail, utilizing a 1/8-inch Lincore 40-S depositing wire. This reconstructed rail sample underwent experimental tests, including tensile testing, which provided mechanical properties necessary to validate the simulation process.
The FE model encompasses all possible interactions, including thermal, mechanical, and phase transformations. This simulation is executed through an element-birth-and-kill method, and it examines the thermal distribution within the sample across different sections. By considering the thermal history and phase change relations, the model predicts the mechanical properties of the repaired rail. The validated model demonstrates significant potential in investigating and predicting mechanical properties and thermal distribution during the SAW process for heavy rail repair.