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[en] The Digital Cherenkov Viewing Device (DCVD) is a tool used to verify irradiated nuclear fuel assemblies in wet storage by imaging the Cherenkov light produced by the radiation emitted from the assemblies. It is frequently used for partial defect verification, verifying that part of an assembly has not been removed and/or replaced. In one of the verification procedures used, the detected total Cherenkov light intensities from a set of assemblies are compared to predicted intensities, which are calculated using operator declarations for the assemblies. This work presents a new, time-efficient method to simulate DCVD images of fuel assemblies, allowing for estimations of the Cherenkov light production, transport and detection. Qualitatively, good agreement between simulated and measured images is demonstrated. Quantitatively, it is shown that relative intensity predictions based on simulated images are within 0.5% of corresponding predictions based solely on the production of Cherenkov light, neglecting light transport and detection. Consequently, in most cases it is sufficient to use predictions based on produced Cherenkov light, neglecting transport and detection, thus substantially reducing the time needed for simulations. In a verification campaign, assemblies are grouped according to their type, and the relative measured and predicted intensities are compared in a group. By determining transparency factors, describing the fraction of Cherenkov light that is blocked by the top plate of an assembly, it is possible to adjust predictions based on the production of Cherenkov light to take the effect of the top plate into account. This procedure allows assemblies of the same type bit with different top plates to be compared with increased accuracy. The effect of using predictions adjusted with transparency factors were assessed experimentally on a set of Pressurized Water Reactor 17× 17 assemblies having five different top plate designs. As a result of the adjustment, the agreement between measured and predicted relative intensities for the whole data set was enhanced, resulting in a reduction of an RMSE from 14.1% to 10.7%. It is expected that further enhancements may be achieved by introducing more detailed top-plate and spacer descriptions.