Indirect Prediction of Welding Fume Diffusion inside a Room Using Computational Fluid Dynamics

Welding is an important and widely used process in the manufacturing and maintenance of various works involving metals and alloys. While welding has broad applications, the welding fume generated during the process has impacts on workers’ health, which needs to be addressed. One of the major steps that can be undertaken to take care of this issue is the use of ventilation, which requires knowledge of characteristics and dispersion of the welding fume in the workers’ breathing zone. It is difficult to assess welding fume dispersion from manual measurement due to numerous welding processes and sufficient data requirement. Numerical prediction of welding fume is dubious due to several errors. This paper considers the use of numerically predicted CO2 concentrations to indirectly predict welding fume distribution in workshops. This is based on the assumption that if the particles are sufficiently small size, they follow the diffusion pattern of gases. Experiments are carried out in a room with an opening and a welding fume generation system for measurement of CO2 and fume diffusion. The results show high possibility of predicting welding fume concentration based on Computational Fluid Dynamics (CFD) simulated CO2 concentration with a correlation coefficient of 0.74

Indirect Prediction of Welding Fume Diffusion inside a Room Using Computational Fluid Dynamics

Welding is an important and widely used process in the manufacturing and maintenance of various works involving metals and alloys. While welding has broad applications, the welding fume generated during the process has impacts on workers’ health, which needs to be addressed. One of the major steps that can be undertaken to take care of this issue is the use of ventilation, which requires knowledge of characteristics and dispersion of the welding fume in the workers’ breathing zone. It is difficult to assess welding fume dispersion from manual measurement due to numerous welding processes and sufficient data requirement. Numerical prediction of welding fume is dubious due to several errors. This paper considers the use of numerically predicted CO2 concentrations to indirectly predict welding fume distribution in workshops. This is based on the assumption that if the particles are sufficiently small size, they follow the diffusion pattern of gases. Experiments are carried out in a room with an opening and a welding fume generation system for measurement of CO2 and fume diffusion. The results show high possibility of predicting welding fume concentration based on Computational Fluid Dynamics (CFD) simulated CO2 concentration with a correlation coefficient of 0.74