Cellular neural networks (CNN) simulation for the TN approximation of the time dependent neutron transport equation in slab geometry

Cellular non-linear network model of microbial fuel cell

“…There are several studies published on CNN/CA or hybrid models of reaction-diffusion [6,7,8,9,10,11,12,13,14,15] and prototyping of chemical computers [16,17,18,19,20,21] and molecular computers [22], spatial dynamics of bacterial colonies [23,24,25,26,27]. Other approaches relevant to CNN modelling of MFCs are CA models of fuel loading patterns in nuclear reactors [28], dynamics of nuclear reactors [29,30,31,32], neutron transport [33], waste water treatment by aerobic granules [34], sequencing batch reactor [35], fluid flow in a porous medium [36].…”

Analog Computing for a New Nuclear Reactor Dynamic Model Based on a Time-Dependent Second Order Form of the Neutron Transport Equation

“…We call the cell on the i th row and j th column cell (i, j) and denote it as C(i, j). The cell architecture has been discussed thoroughly in previous studies [12], [20]. However we now modify the equivalent electrical circuit of each cell to model the second order form of the time-dependent neutron transport equation using CNN.…”