![]() ![]() ![]() On account of setting out such a generation scheme, we optimize the particle loss by keeping an angular acceptance that is directly dependent on the VOI geometry as well as the vertical position of the restrictive plane for a tomographic system of a finite size. In other words, we favor a momentum direction that is determined by a vector constructed between an initial point randomly chosen on a generative point/plane and a second point arbitrarily selected on a restrictive plane of the same dimensions with the basal cross section of the volume-of-interest (VOI). In this study, by attempting to resolve the difficulties related to the angular distribution during the particle generation for the muon tomography applications in the GEANT4 simulations, we exhibit an unconventional methodology that is hinged on the direction limitation via the vectorial construction from the generation location to the restriction area rather than using a certain angular distribution or interval. The muon tracking is accomplished by G4Step, and the recorded hit positions on the detector layers are post-processed by means of a Python script. ![]() Our simulation features are summarized in Table 2, and we use a 80-bin discrete muon energy spectrum extracted from the CRY generator between 0 and 8 GeV. the tiny deflection owing to the detector layers. Along with the scattering angle, we track the number of the absorbed muons within the VOI as denoted in # In−target Capture = # of muMinusCaptureAtRest in VOI (11) Last but not least, we define the particle loss entitled off-target loss as follows (12) where # Out−scattering is the number of the scattered muons from the VOI by leaking out of the tomographic device, # Decay is the negligible number of the decayed muons into electrons/positrons, # Off−target Capture is the insignificant number of the absorbed muons outside the VOI, and # Initial Deflection is the number of muons that miss the VOI only in the case of the wide beams, which occasionally occurs due to the barriers before the VOI despite the initial restricted orientation to the VOI boundary, i.e. The software library and examples can be downloaded from. We provide a function library, callable from C, C++, and Fortran, and interfaces to popular Monte Carlo transport codes (MCNP, MCNPX, COG, Geant4). The code generates individual showers of secondary particles sampling the energy, time of arrival, zenith angle, and multiplicity with basic correlations, and has user controls for latitude (geomagnetic cutoff) and solar cycle effects. Our simulation provides all particle production (muons, neutrons, protons, electrons, photons, and pions) with the proper flux within a user-specified area and altitude. Our simulation is based on precomputed input tables derived from full MCNPX simulations of primary cosmic rays on the atmosphere and benchmarked against published cosmic-ray measurements. The CRY software library generates correlated cosmic-ray particle shower distributions at one of three elevations (sea level, 2100 m, and 11300 m) for use as input to transport and detector simulation codes. ![]()
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