Signal recovery from sparse measurements by using compressed sensing techniques for reactor core flux mapping

In large size nuclear reactors an online flux mapping system is needed to continuously monitor neutron flux distribution and display to the operator. Flux mapping system employs a suitable algorithm to estimate the core flux distribution from the measurements of few in-core detectors. Most of the algorithms available today employ the Flux Synthesis method, estimation method based on Kalman filtering technique and the method based on simultaneous least squares solutions of neutron diffusion and detector response equations. Limitation of these methods is the assumption that the neutron flux profile in the reactor is independent of time, hence may not be adequate to span 2D/3D reactor core space. The paper presents a compressed sensing (CS) based signal recovery method from sparse measurements and its application to core flux mapping in Advance Heavy Water Reactor (AHWR). The CS technique relies on two principles of sparsity and incoherence. The problem of core flux mapping also falls under this category as we need to estimate core flux at more number of channel points with less number of sparse detector measurements. To start with, Fourier basis function has been used in proposed CS based technique. The method is validated on vertical In Core Detector Housing locations (1-D) and horizontal mesh locations (2-D) of AHWR core for different operating conditions. Overall accuracy in the estimation using the proposed CS based methodology has been good for in core detector housing (1-D) and mesh's locations (2-D). Subsequently the method will be extended to all the 3-D reactor core flux locations.