We present a consistent and efficient approach to the formulation of geometric nonlinear finite elements for isogeometric analysis (IGA) and isogeometric B-Rep analysis (IBRA) based on the adjoint method. IGA elements are computationally expensive, especially for high polynomial degrees. Using the method presented here enables us to reduce this disadvantage and develop a methodical framework for the efficient implementation of IGA elements. The elements are consistently derived from energy functionals. The load vector and stiffness matrix are obtained from the first and second order derivatives of the energy. Starting from the functional, we apply the concept of algorithmic or automatic differentiation to compute the precise derivatives. Here, we compare the direct (forward) and adjoint (reversed) methods. Analysis of the computational graph allows us to optimize the computation and identify recurring modules. It turns out that using the adjoint method leads to a core-congruential formulation, which enables a clean separation between the mechanical behavior and the geometric description. This is particularly useful in CAD-integrated analysis, where mechanical properties are applied to different geometry types. The adjoint method produces the same results but requires significantly fewer operations and fewer intermediate results. Moreover, the number of intermediate results is no longer dependent on the polynomial degree of the NURBS. This is important for implementation efficiency and computation speed. The procedure can be applied to arbitrary element formulations and coupling conditions based on energy functionals. For demonstration purposes, we present the proposed approach specifically for use with geometrically nonlinear trusses, beams, membranes, shells, and coupling conditions based on the penalty method.
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We present a consistent and efficient approach to the formulation of geometric nonlinear finite elements for isogeometric analysis (IGA) and isogeometric B-Rep analysis (IBRA) based on the adjoint method. IGA elements are computationally expensive, especially for high polynomial degrees. Using the method presented here enables us to reduce this disadvantage and develop a methodical framework for the efficient implementation of IGA elements. The elements are consistently derived from energy funct...
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