| Description |
The need to understand and predict the behavior of fires and explosions is important considering the amount of property damage and the loss of life that can result. In the case of transportation pool fires (fires resulting from liquid fuel spills), predictive science is an especially valuable tool considering that experiments with large pools fires are costly and often lead to damaged or destroyed instrumentation. In the development of fire codes as well as in other areas of computational science, the need for fidelity in computational results has become a prominent issue. The various sources of error in computation, such as discretization error, machine round-off error, iterative convergence error, programmer error, and model error, must be accounted for and, if possible, quantified if computational results are to be considered legitimate. The current study seeks to remedy an important source of error in pool fire simulations. The error stems from the application of a simplistic fuel inlet boundary condition. Traditionally this type of boundary condition assumes that the liquid pool vaporizes fuel to feed the flame at a constant rate. Additionally the vaporization rate is assumed to be uniform over the pool surface. In reality there is a complex feedback mechanism between the pool surface and the flame. Pool vaporization rate changes with time as the pool is heated, and thermal flux to the pool will be nonuniform over the surface. The responsive Boundary model utilizes energy and mass conservation principles to model the thermal behavior of the fuel pool and to predict the vaporization rate given thermal input from the flame. Verification tests such as the Method of Manufactured Solutions and grid convergence and validation methods such as model input sensitivity analysis and consistency analysis are applied to the Responsive Boundary model on its own and linked with the gas-phase fire code (ARCHES). The tests verify that the code solves the continuum model that is the basis of the boundary model with acceptable error. A region of consistency is also found between the steady vaporization fluxes predicted from the model and experimental data for a small heptane pool fire. Consistency analysis is also applied to data obtained from ARCHES simulations of a small helium plume and data taken from holographic interferometric images. |
