Applying the neutron scatter camera to treaty verification and warhead monitoring
ABSTRACT The neutron scatter camera was originally developed for a range of SNM detection applications. We are now exploring the feasibility of applications in treaty verification and warhead monitoring using experimentation, maximum likelihood estimation method(MLEM), detector optimization, and MCNP-PoliMi simulations.
Conference Proceeding: Results with a 32-element dual mode imager[show abstract] [hide abstract]
ABSTRACT: We present advances with a 32 element scalable, segmented dual mode imager. Scaling up the number of cells results in a 1.4 increase in efficiency over a system we deployed last year. Variable plane separation has been incorporated which further improves the efficiency of the detector. By using 20 cm diameter cells we demonstrate that we could increase sensitivity by a factor of 6. We further demonstrate gamma ray imaging in from Compton scattering. This feature allows for powerful dual mode imaging. Selected results are presented that demonstrate these new capabilities.Nuclear Science Symposium Conference Record (NSS/MIC), 2010 IEEE; 12/2010
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ABSTRACT: The Monte-Carlo simulation of correlation measurements that rely on the detection of fast neutrons and photons from fission requires that particle interactions in each history be described as closely as possible. The MCNP-PoliMi11PoliMi stands for Politecnico di Milano. code has been developed from the standard MCNP code to simulate each neutron–nucleus interaction as closely as possible. In particular, neutron interaction and photon production are made correlated and correct neutron and photon fission multiplicities have been implemented. The code output consists in relevant information about each collision, for example the type of collision, the collision target, the energy deposited, and the position of the interaction. A post-processing code has also been developed and can be tailored to model specific detector characteristics. These features make MCNP-PoliMi a versatile tool to simulate particle interactions and detection processes. The application of the MCNP-PoliMi code to simulate neutron and gamma ray detection in a plastic scintillator is presented.Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment - NUCL INSTRUM METH PHYS RES A. 01/2003; 513(3):550-558.
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ABSTRACT: Previous models for emission tomography (ET) do not distinguish the physics of ET from that of transmission tomography. We give a more accurate general mathematical model for ET where an unknown emission density lambda = lambda(x, y, z) generates, and is to be reconstructed from, the number of counts n(*)(d) in each of D detector units d. Within the model, we give an algorithm for determining an estimate lambdainsertion mark of lambda which maximizes the probability p(n(*)|lambda) of observing the actual detector count data n(*) over all possible densities lambda. Let independent Poisson variables n(b) with unknown means lambda(b), b = 1, ..., B represent the number of unobserved emissions in each of B boxes (pixels) partitioning an object containing an emitter. Suppose each emission in box b is detected in detector unit d with probability p(b, d), d = 1, ..., D with p(b,d) a one-step transition matrix, assumed known. We observe the total number n(*) = n(*)(d) of emissions in each detector unit d and want to estimate the unknown lambda = lambda(b), b = 1, ..., B. For each lambda, the observed data n(*) has probability or likelihood p(n(*)|lambda). The EM algorithm of mathematical statistics starts with an initial estimate lambda(0) and gives the following simple iterative procedure for obtaining a new estimate lambdainsertion mark(new), from an old estimate lambdainsertion mark(old), to obtain lambdainsertion mark(k), k = 1, 2, ..., lambdainsertion mark(new)(b)= lambdainsertion mark(old)(b)Sum of (n(*)p(b,d) from d=1 to D/Sum of lambdainsertion mark()old(b('))p(b('),d) from b(')=1 to B), b=1,...B.IEEE Transactions on Medical Imaging 02/1982; 1(2):113-22. · 4.03 Impact Factor