Employing MCNP to optimize experimental design for compressed sensing neutron source imaging
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© 2018 Elsevier B.V. Compressed sensing theory has been applied in the signal processing stage of many existing imaging systems. This research attempts to incorporate compressed sensing principles in conjunction with the collimator design. Monte Carlo N-Particle Transport Code (MCNP) was used to design a proof-of-concept experimental apparatus. This was accomplished by running simulations to determine: the height of water required to stop thermal neutrons from a 252 Cf source; collimator array dimensions; the collimator material; and the collimator size for the experiment. The simulations were run using a cylindrical water tank and a 2 × 2 array of channels acting as collimator. Three different materials were simulated to determine the best collimator composition for the experiment. An array configuration was defined as a random combination of air-filled and water-filled channels. Neutron counts were tallied using MCNP for each configuration with a total of 300 configurations for a 23 × 23 array and 100 for an 11 × 11 array. The image of the source corresponding to the different collimator array size was constructed using non-negative least squares with MATLAB. Another MCNP model with a rectangular tank was created with an 11 × 11 collimator array. Several images as a function of the number of measurements, K, were produced to observe the minimum K that would result in accurate image quality. These simulations have resulted in the decision to proceed with the assembly of an imaging system made of a water-filled 250-gallon tank with an array of 0.5-inch 11 × 11 polyvinyl chloride (PVC) pipes. The K required for a conventional raster scan method would be the total pixels, which is [Formula presented] in the 11 × 11 case. It was found that the source shape and location can be obtained with K that is 50% of the total pixels.
author list (cited authors)
Anuar, N., Marianno, C., & McClarren, R. G.