Novel Optimization Methodology for Welding Process/Consumable Integration
Advanced materials are being developed to improve the energy efficiency of many industries of future including steel, mining, and chemical, as well as, US infrastructures including bridges, pipelines and buildings. Effective deployment of these materials is highly dependent upon the development of arc welding technology. Traditional welding technology development is slow and often involves expensive and time-consuming trial and error experimentation. The reason for this is the lack of useful predictive tools that enable welding technology development to keep pace with the deployment of new materials in various industrial sectors. Literature reviews showed two kinds of modeling activities. Academic and national laboratory efforts focus on developing integrated weld process models by employing the detailed scientific methodologies. However, these models are cumbersome and not easy to use. Therefore, these scientific models have limited application in real-world industrial conditions. On the other hand, industrial users have relied on simple predictive models based on analytical and empirical equations to drive their product development. The scopes of these simple models are limited. In this research, attempts were made to bridge this gap and provide the industry with a computational tool that combines the advantages of both approaches. This research resulted in the development of predictive tools which facilitate the development of optimized welding processes and consumables. The work demonstrated that it is possible to develop hybrid integrated models for relating the weld metal composition and process parameters to the performance of welds. In addition, these tools can be deployed for industrial users through user friendly graphical interface. In principle, the welding industry users can use these modular tools to guide their welding process parameter and consumable composition selection. It is hypothesized that by expanding these tools throughout welding industry, substantial energy savings can be made. Savings are expected to be even greater in the case of new steels, which will require extensive mapping over large experimental ranges of parameters such as voltage, current, speed, heat input and pre-heat.
- Research Organization:
- The Lincoln Electric Company
- Sponsoring Organization:
- USDOE Office of Industrial Technologies (OIT) - (EE-20)
- DOE Contract Number:
- FC36-01ID14204
- OSTI ID:
- 862404
- Report Number(s):
- DOE-ID14204-F1; TRN: US200712%%88
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
36 MATERIALS SCIENCE
ARC WELDING
ENERGY EFFICIENCY
INDUSTRY
MINING
OPTIMIZATION
PERFORMANCE
PIPELINES
SIMULATION
STEELS
VELOCITY
WELDING
arc welding
enabling technology
energy savings
process and consumable optimization
heat transfer
fluid flow
weld pool shape
weld cooling rate
artificial neural network model
numerical model
analytical model
paraequilibrium thermodynamic model
kinetic model
steel phase transformation
Weld Metal Properties