Sophie Grape

Comparison of prediction models for Cherenkov light emissions from nuclear fuel assemblies

The Digital Cherenkov Viewing Device (DCVD) [1] is a tool used by nuclear safeguards inspectors to verify irradiated nuclear fuel assemblies in wet storage based on the Cherenkov light produced by the assembly. Verifying that no rods have been substituted in the fuel, so-called partial-defect verification, is done by comparing the intensity measured with a DCVD with a predicted intensity, based on operator fuel declaration. The prediction model currently used by inspectors is based on simulations of Cherenkov light production in a BWR 8x8 geometry. This work investigates prediction models based on simulated Cherenkov light production in a BWR 8x8 and a PWR 17x17 assembly, as well as a simplified model based on a single rod in water. Cherenkov light caused by both fission product gamma and beta decays was considered. The simulations reveal that there are systematic differences between the model used by safeguards inspectors and the models described in this publication, most noticeably with respect to the fuel assembly cooling time. Consequently, if the intensity predictions are based on another fuel type than the fuel type being measured, a systematic bias in intensity with respect to burnup and cooling time is introduced. While a simplified model may be accurate enough for a set of fuel assemblies with nearly identical cooling times, the prediction models may differ systematically by up to 18 % for fuels with more varied cooling times. Accordingly, these investigations indicate that the currently used model may need to be exchanged with a set of more detailed, fuel-type specific models, in order minimize the model dependent systematic deviations.

Experimental study of background subtraction in Digital Cherenkov Viewing Device measurements

The Digital Cherenkov Viewing Device (DCVD) is an imaging tool used by authority inspectors for partial defect verification of nuclear fuel assemblies in wet storage, i.e. to verify that part of an ...

Experimental evaluation of models for predicting Cherenkov light intensities from short-cooled nuclear fuel assemblies

The Digital Cherenkov Viewing Device (DCVD) is a tool used by nuclear safeguards inspectors to verify irradiated nuclear fuel assemblies in wet storage based on the recording of Cherenkov light pro ...

Nonproliferation and safeguards aspects of the MSR fuel cycle

In this chapter the reader is introduced to the concepts of nonproliferation: safeguards and security. The identified threats to the peaceful nuclear fuel cycle as well as possible targets, and the existing nuclear safeguards system are discussed. The advantages and disadvantages of the molten salt reactor (MSR) fuel cycle in terms of nonproliferation are discussed and it is compared to that of the light-water reactor fuel cycle, which is widely implemented today.

On Cherenkov light production by irradiated nuclear fuel rods

Safeguards verification of irradiated nuclear fuel assemblies in wet storage is frequently done by measuring the Cherenkov light in the surrounding water produced due to radioactive decays of fissi ...

Partial Defect Evaluation Methodology for Nuclear Safeguards Inspections of Used Nuclear Fuel Using the Digital Cherenkov Viewing Device

Abstract This paper describes possible ways of analyzing and interpreting data obtained using the digital Cherenkov viewing device on spent nuclear fuel assemblies for the identification of partial defects in the fuel. According to the terminology of the International Atomic Energy Agency, partial defects refer to items, for instance, fuel assemblies, that are manipulated to the extent that a fraction of the fuel material is diverted or substituted. Analysis can be performed either by using a measure of the total light intensity or by identifying the light distribution pattern emanating from the spent nuclear fuel, the goal of either type of analysis being a quantitative measure that can be used in the data interpretation step. Two possible data interpretation alternatives are presented here: the threshold method and the hypothesis testing method. This paper summarizes some of the simulation studies and results that have been obtained, related to the two analysis and data interpretation methodologies.