The goal of this project is to improve liquefied natural gas (LNG) dispersion modeling capabilities for uncontrolled releases.
Gas Technology Institute
University of Arkansas-Fayetteville
Des Plaines, Illinois 60018
Fayetteville, Arkansas 72701
Using a specially designed wind tunnel at the Chemical Hazards Research Center (CHRC) of the University of Arkansas-Fayetteville, researchers are seeking to improve LNG dispersion prediction capabilities. The capability to predict LNG dispersion around obstacle and terrain features of realistic complexity as well as for very low wind speed and stable weather conditions will be enhanced using improved wind tunnel simulations and enhancing the turbulence closure equations.
This research will support the development of the DOE LNG/Fluent model for LNG dispersion studies by improving ability to predict the turbulent mixing of denser-than-air gases or aerosols with air. This will allow for more realistic description of dispersion problems with obstacle and terrain features of real world complexity and will be used to evaluate hazard consequence issues for accidental releases of LNG and other liquefied energy fuels.
Investigation of the effect upon numerical stability of the heat transfer model used to predict the surface-to-cloud heat transfer is completed. Effort is now being directed to describing the ground surface temperature decrease as a function of time. Questions regarding surface to cloud heat transfer were identified as being largely responsible for the model instability problems previously encountered. Simulations at the required low wind speed of 2 m/s at 10 m elevation, with both D stability and F stability conditions, with the presence of LNG vapor release, but without the presence of dike/tank obstacle features have been successfully completed. Researchers are now including the effects, under low wind speed and stable conditions, of the presence of dike and tank obstacles to the flow.
and Remaining Tasks:
This project has been completed. The project enhances several critical capabilities of the dispersion modeling, such as: