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The neutron transport equation is a balance statement that conserves neutrons. Each term represents a gain or a loss of a neutron, and the balance, in essence, claims that neutrons gained equals neutrons lost. It is formulated as follows: [1]
In 1947, John von Neumann sent a letter to Robert Richtmyer proposing the use of a statistical method to solve neutron diffusion and multiplication problems in fission devices. [5] His letter contained an 81-step pseudo code and was the first formulation of a Monte Carlo computation for an electronic computing machine.
The intensity field can in principle be solved from the integrodifferential radiative transfer equation (RTE), but an exact solution is usually impossible and even in the case of geometrically simple systems can contain unusual special functions such as the Chandrasekhar's H-function and Chandrasekhar's X- and Y-functions. [3]
Download as PDF; Printable version; In other projects ... m n = neutron rest ... These equations need to be refined such that the notation is defined as has been done ...
Continuity equations are a stronger, local form of conservation laws. For example, a weak version of the law of conservation of energy states that energy can neither be created nor destroyed—i.e., the total amount of energy in the universe is fixed. This statement does not rule out the possibility that a quantity of energy could disappear ...
If k = 1, the chain reaction is critical and the neutron population will remain constant. In an infinite medium, neutrons cannot leak out of the system and the multiplication factor becomes the infinite multiplication factor, k = k ∞ {\displaystyle k=k_{\infty }} , which is approximated by the four-factor formula.
The current stable version Serpent 2.2.0 was released in May 2022. [4] Serpent was originally developed to be a simplified neutron transport code for reactor physics applications. Its main focus was on group constant generation with two-dimensional lattice calculations. Burnup calculation capability was included early on.
This involves computing exact or approximate solutions of the transport equation, and there are various forms of the transport equation that have been studied. Common varieties include steady-state vs time-dependent, scalar vs vector (the latter including polarization), and monoenergetic vs multi-energy (multi-group).