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Employing MCNP to optimize experimental design for compressed sensing neutron source imaging

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dc.contributor.authorAnuar N.en_US
dc.contributor.authorMarianno C.en_US
dc.contributor.authorMcClarren R.G.en_US
dc.contributor.authorid57190939309en_US
dc.contributor.authorid6505947929en_US
dc.contributor.authorid15521383500en_US
dc.date.accessioned2023-05-29T08:11:03Z
dc.date.available2023-05-29T08:11:03Z
dc.date.issued2020
dc.descriptionChlorine compounds; Imaging systems; MATLAB; Neutron sources; Neutrons; Pixels; Polyvinyl chlorides; Water tanks; Array configurations; Compressive sensing; Experimental apparatus; Least Square; Monte carlo n particles; Polyvinyl chloride pipes; Random combination; Running simulations; Compressed sensingen_US
dc.description.abstractCompressed 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 252Cf 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 K=121 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. � 2018 Elsevier B.V.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo161446
dc.identifier.doi10.1016/j.nima.2018.10.124
dc.identifier.scopus2-s2.0-85055969164
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85055969164&doi=10.1016%2fj.nima.2018.10.124&partnerID=40&md5=2eaef7c7b3bdb33477b9deade47d68ae
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25570
dc.identifier.volume954
dc.publisherElsevier B.V.en_US
dc.sourceScopus
dc.sourcetitleNuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
dc.titleEmploying MCNP to optimize experimental design for compressed sensing neutron source imagingen_US
dc.typeReviewen_US
dspace.entity.typePublication
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