  We evaluate Beer-Lambert (BL) ray-tracing and Monte Carlo N-Particle (MCNP)
photon tracking simulations for prediction and comparison of X-ray imaging
system performance. These simulation tools can aid the methodical design of
laboratory-scale X-ray particle image velocimetry (XPIV) experiments and tracer
particles by predicting image quality. Particle image signal-to-noise ratio
(SNR) is used as the metric of system performance. Simulated and experiment
data of hollow, silver-coated, glass sphere tracer particles (AGSF-33) are
compared. As predicted by the simulations, the AGSF-33 particles are visible
with a SNR greater than unity in 100~ms exposure time images, demonstrating
their potential as X-ray PIV or particle tracking velocimetry (XPTV) tracers.
The BL approach predicts the image contrast, is computationally inexpensive,
and enables the exploration of a vast parameter space for system design. MCNP
simulations, on the other hand, predict experiment images slightly more
accurately, but are more than an order of magnitude more computationally
expensive than BL simulations. For most practical XPIV system design
applications, the higher computational expense of MCNP is likely not justified
by the modest accuracy improvement compared to BL.
