# Modelling Meteoroid Streams

Accurate simulations of meteoroid streams permit the prediction of stream interaction with Earth, and provide a measure of risk to Earth satellites and interplanetary spacecraft. Current cometary ejecta and meteoroid stream models have been somewhat successful in predicting some stream observations, but have required significant assumptions and simplifications. Extending on the approach of Vaubaillon et al. (2005)[1], I model dust ejection from the cometary nucleus, and generate sample particles representing bins of distinct dynamical evolution-regulating characteristics (size, density, direction, albedo). Ephemerides of the sample particles are integrated and recorded for later assignment of weights based on model parameter changes. To assist in model analysis I am developing interactive software to permit the "turning of knobs" of model parameters, allowing for near-real-time 3D visualization of resulting stream structure. Using the tool, I will revisit prior assumptions made, and will observe the impact of introducing non-uniform cometary surface attributes and temporal activity.The software uses a single model definition throughout model verification, sample particle bin generation and integration, and analysis. The tool supports adjustment with feedback of both dependent and independent model values, with the intent of supporting multivariate analysis. Propagations of measurement uncertainties are tracked rigorously throughout. I maintain a separation of the model itself from the operations of model definition, parameter manipulation, and real-time analysis and visualization. Therefore I am able to quickly adapt to fundamental model changes.

The process of modelling begins with the definition of a model and selection of initial parameters (Fig. 1). I then generate a large cloud of frequency-unweighted particles varying in size, density and albedo, emitted at various velocities from the nucleus in a uniform distribution (Fig. 2). Multiple perihelion passages are modeled. The ejection position/velocity vectors, sun-angle, size and density of each particle is stored for later frequency manipulation. Each particle is integrated over hundreds of years, with ephemerides stored at sufficiently small time intervals as to permit accurate interpolation of positions at arbitrary epochs. The simulated particle stream is visualized for analysis of stream dynamics (Fig. 3) and Earth orbit intersections (Fig. 4). The particle frequency weightings are manipulated, driving near-real-time visualizations of meteoroid stream structure change. The entire process may be repeated at infinitum, introducing surface dynamic model variations, cometary nucleus rotation, non-homogeneous surface characteristics, and nucleus shape models.

Fig. 1 - The Model Editor and the Dust Ejection: Model[1],[2],[3],[4]

Fig. 2 - 3D simulation of particle emission, with particle attribute-based colouration.

Fig. 3 - 3D representation of particle ephemerides, updated near-real-time based on model parameter changes.[5]

Fig. 4 - 3D representation of particle ecliptic plane intersections (Earth's orbit being the diagonal line), updated near-real-time based on model parameter changes.[5]

**References**

[1] Vaubaillon, J.; Colas, F.; Jorda, L. (2005) A new method to predict meteor showers. I. Description of the model. A&A, 439, Issue 2, 751-760.

[2] Vaubaillon, J.; Colas, F.; Jorda, L. (2005) A new method to predict meteor showers. II. Application to the Leonids. A&A, 439, Issue 2, 751-760.

[3] Crifo, J. F.; Rodionov, A. V. (1997) The Dependence of the Circumnuclear Coma Structure on the Properties of the Nucleus. Icarus, 129, 1, 72-93.

[4] Jorda, L.; Crovisier, Jacques; Green, D. W. E. (1992) The correlation between water production rates and visual magnitudes in comets. In Lunar and Planetary Inst., ACM, 1991, 285-288 (SEE N93-19113 06-90).

[5] From Leonid meteoroid stream simulation data provided by Peter Brown (2003).