BEAST.jl documentation

BEAST provides a number of types modelling concepts and a number of algorithms for the efficient and simple implementation of boundary and finite element solvers. It provides full implementations of these concepts for the LU based solution of boundary integral equations for the Maxwell and Helmholtz systems.

Because Julia only compiles code at execution time, users of this library can hook into the code provided in this package at any level. In the extreme case it suffices to provide overwrites of the assemble functions. In that case, only the LU solution will be performed by the code here.

At the other end it suffices that users only supply integration kernels that act on the element-element interaction level. This package will manage all required steps for matrix assembly.

For the Helmholtz 2D and Maxwell 3D systems, complete implementations are supplied. These models will be discussed in detail to give a more concrete idea of the APIs provides and how to extend them.

Central to the solution of boundary integral equations is the assembly of the system matrix. The system matrix is fully determined by specifying a kernel G, a set of trial functions, and a set of test functions.


Sets of both trial and testing functions are implemented by models following the basis concept. The term basis is somewhat misleading as it is nowhere required nor enforced that these functions are linearly independent. Models implementing the Basis concept need to comply to the following semantics.

Reference Space

The reference space concept defines an API for working with spaces of local shape functions. The main role of objects implementing this concept is to allow specialization of the functions that depend on the precise reference space used.

The functions that depend on the type and value of arguments modeling reference space are:


A kernel is a fairly simple concept that mainly exists as part of the definition of a Discrete Operator. A kernel should obey the following semantics:

In many function definitions the kernel object is referenced by operator or something similar. This is a misleading name as an operator definition should always be accompanied by the domain and range space.

Discrete Operator

Informally speaking, a Discrete Operator is a concept that allows for the computation of an interaction matrix. It is a kernel together with a test and trial basis. A Discrete Operator can be passed to assemble and friends to compute its matrix representation.

A discrete operator is a triple (kernel, test_basis, trial_basis), where kernel is a Kernel, and test_basis and trial_basis are Bases. In addition, the following expressions should be implemented and behave according to the correct semantics:

In the context of fast methods such as the Fast Multipole Method other algorithms on Discrete Operators will typically be defined to compute matrix vector products. These algorithms do not explicitly compute and store the interaction matrix (this would lead to unacceptable computational and memory complexity).

# BEAST.elementsFunction.


Create an iterable collection of the elements stored in geo. The order in which this collection produces the elements determines the index used for lookup in the data structures returned by assemblydata and quaddata.


# BEAST.numfunctionsFunction.


Return the number of functions in a Space or RefSpace.


# CompScienceMeshes.coordtypeFunction.


Returns eltype(vertextype(mesh))



Return coordinate type used by simplex.


# BEAST.scalartypeFunction.


The scalar field over which the values of a global or local basis function, or an operator are defined. This should always be a scalar type, even if the basis or operator takes on values in a vector or tensor space. This data type is used to determine the eltype of assembled discrete operators.


# BEAST.assemblydataFunction.


Given a Basis this function returns a data structure containing the information required for matrix assemble. More precise the following expressions are valid for the returned object ad:


Here, c and r are indices in the iterable set of geometric elements and the set of local shape functions on each element. i ranges from 1 to the maximum number of basis functions local shape function r on element r contributes to.

For a triplet (c,r,i), globalindex is the index in the Basis of the i-th basis function that has a contribution from local shape function r on element r. coefficient is the coefficient of that contribution in the linear combination defining that basis function in terms of local shape function.

Note: the indices c correspond to the position of the corresponding element whilst iterating over geometry(basis).


# BEAST.geometryFunction.


Returns an iterable collection of geometric elements on which the functions in basis are defined. The order the elements are encountered needs correspond to the element indices used in the data structure returned by assemblydata.


# BEAST.refspaceFunction.


Returns the ReferenceSpace of local shape functions on which the basis is built.


# BEAST.quaddataFunction.

quaddata(operator, test_refspace, trial_refspace, test_elements, trial_elements)

Returns an object cashing data required for the computation of boundary element interactions. It is up to the client programmer to decide what (if any) data is cached. For double numberical quadrature, storing the integration points for example can significantly speed up matrix assembly.

is typically overloaded on the type of these local spaces of shape functions. (See the implementation in maxwell.jl for an example).

elements on which the finite element space are defined. These are provided to allow computation of the actual integrations points - as opposed to only their coordinates.


# BEAST.quadruleFunction.

quadrule(operator,test_refspace,trial_refspace,p,test_element,q_trial_element, qd)

Returns an object that contains all the dynamic (runtime) information that defines the integration strategy that will be used by momintegrals! to compute the interactions between the local test/trial functions defined on the specified geometric elements. The indices p and q refer to the position of the test and trial elements as encountered during iteration over the output of geometry.

The last argument qd provides access to all precomputed data required for quadrature. For example it might be desirable to precompute all the quadrature points for all possible numerical quadrature schemes that can potentially be required during matrix assembly. This makes sense, since the number of point is order N (where N is the number of faces) but these points will appear in N^2 computations. Precomputation requires some extra memory but can save a lot on computation time.


# BEAST.momintegrals!Function.

regularcellcellinteractions!(biop, tshs, bshs, tcell, bcell, interactions, strat)

Function for the computation of moment integrals using simple double quadrature.