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In the theory of radiative transfer, of either thermal [1] or neutron [2] radiation, a position and direction-dependent intensity function is usually sought for the description of the radiation field. 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] The method of discrete ordinates, or the Sn method, is one way to approximately solve the RTE by discretizing both the xyz-domain and the angular variables that specify the direction of radiation. The methods were developed by Subrahmanyan Chandrasekhar when he was working on radiative transfer.
In the case of time-independent monochromatic radiation in an elastically scattering medium, the RTE is [1]
where the first term on the RHS is the contribution of emission, the second term the contribution of absorption and the last term is the contribution from scattering in the medium. The variable is a unit vector that specifies the direction of radiation and the variable is a dummy integration variable for the calculation of scattering from direction to direction .
In the discrete ordinates method, the full solid angle of is divided to some number of discrete angular intervals, and the continuous direction variable is replaced by a discrete set of direction vectors . Then the scattering integral in the RTE, which makes the solution problematic, becomes a sum [1] [2]
where the numbers are weighting coefficients for the different direction vectors. With this the RTE becomes a linear system of equations for a multi-index object, the number of indices depending on the dimensionality and symmetry properties of the problem.
It is possible to solve the resulting linear system directly with Gauss–Jordan elimination, [2] but this is problematic due to the large memory requirement for storing the matrix of the linear system. Another way is to use iterative methods, where the required number of iterations for a given degree of accuracy depends on the strength of scattering. [4] [5]
The discrete ordinates method, or some variation of it, is applied for solving radiation intensities in several physics and engineering simulation programs, such as COMSOL Multiphysics [6] or the Fire Dynamics Simulator. [7]
In 3D computer graphics, radiosity is an application of the finite element method to solving the rendering equation for scenes with surfaces that reflect light diffusely. Unlike rendering methods that use Monte Carlo algorithms, which handle all types of light paths, typical radiosity only account for paths which leave a light source and are reflected diffusely some number of times before hitting the eye. Radiosity is a global illumination algorithm in the sense that the illumination arriving on a surface comes not just directly from the light sources, but also from other surfaces reflecting light. Radiosity is viewpoint independent, which increases the calculations involved, but makes them useful for all viewpoints.
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In mathematics gradient descent is a first-order iterative optimization algorithm for finding a local minimum of a differentiable function. The idea is to take repeated steps in the opposite direction of the gradient of the function at the current point, because this is the direction of steepest descent. Conversely, stepping in the direction of the gradient will lead to a local maximum of that function; the procedure is then known as gradient ascent.
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In physics, the reciprocal lattice represents the Fourier transform of another lattice. In normal usage, the initial lattice is usually a periodic spatial function in real-space and is also known as the direct lattice. While the direct lattice exists in real-space and is what one would commonly understand as a physical lattice, the reciprocal lattice exists in reciprocal space. The reciprocal lattice of a reciprocal lattice is equivalent to the original direct lattice, because the defining equations are symmetrical with respect to the vectors in real and reciprocal space. Mathematically, direct and reciprocal lattice vectors represent covariant and contravariant vectors, respectively.
Neutron transport is the study of the motions and interactions of neutrons with materials. Nuclear scientists and engineers often need to know where neutrons are in an apparatus, what direction they are going, and how quickly they are moving. It is commonly used to determine the behavior of nuclear reactor cores and experimental or industrial neutron beams. Neutron transport is a type of radiative transport.
The Gauss–Newton algorithm is used to solve non-linear least squares problems. It is a modification of Newton's method for finding a minimum of a function. Unlike Newton's method, the Gauss–Newton algorithm can only be used to minimize a sum of squared function values, but it has the advantage that second derivatives, which can be challenging to compute, are not required.
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In spectroscopy, spectral flux density is the quantity that describes the rate at which energy is transferred by electromagnetic radiation through a real or virtual surface, per unit surface area and per unit wavelength. It is a radiometric rather than a photometric measure. In SI units it is measured in W m−3, although it can be more practical to use W m−2 nm−1 or W m−2 μm−1, and respectively by W·m−2·Hz−1, Jansky or solar flux units. The terms irradiance, radiant exitance, radiant emittance, and radiosity are closely related to spectral flux density.
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