Recent studies have used numerical models to estimate the collection efficiency of solid precipitation gauges when exposed to the wind in both shielded and unshielded configurations. The models used computational fluid dynamics (CFD) simulations of the airflow pattern generated by the aerodynamic response to the gauge–shield geometry. These are used as initial conditions to perform Lagrangian tracking of solid precipitation particles. Validation of the results against field observations yielded similarities in the overall behavior, but the model output only approximately reproduced the dependence of the experimental collection efficiency on wind speed. This paper presents an improved snowflake trajectory modeling scheme due to the inclusion of a dynamically determined drag coefficient. The drag coefficient was estimated using the local Reynolds number as derived from CFD simulations within a time-independent Reynoldsaveraged Navier–Stokes approach. The proposed dynamic model greatly improves the consistency of results with the field observations recently obtained at theMarshall Field winter precipitation test bed in Boulder, Colorado.
An improved trajectory model to evaluate the collection performance of snow gauges
COLLI, MATTEO;LANZA, LUCA GIOVANNI;
2015-01-01
Abstract
Recent studies have used numerical models to estimate the collection efficiency of solid precipitation gauges when exposed to the wind in both shielded and unshielded configurations. The models used computational fluid dynamics (CFD) simulations of the airflow pattern generated by the aerodynamic response to the gauge–shield geometry. These are used as initial conditions to perform Lagrangian tracking of solid precipitation particles. Validation of the results against field observations yielded similarities in the overall behavior, but the model output only approximately reproduced the dependence of the experimental collection efficiency on wind speed. This paper presents an improved snowflake trajectory modeling scheme due to the inclusion of a dynamically determined drag coefficient. The drag coefficient was estimated using the local Reynolds number as derived from CFD simulations within a time-independent Reynoldsaveraged Navier–Stokes approach. The proposed dynamic model greatly improves the consistency of results with the field observations recently obtained at theMarshall Field winter precipitation test bed in Boulder, Colorado.File | Dimensione | Formato | |
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