Spatial recondensation using the Discrete Generalized Multigroup method

Everson, Matthew S.; Forget, Benoit

doi:10.1016/j.anucene.2013.06.027

Cited by 2 publications

(2 citation statements)

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“…A l,g, B l,g , and C l,g , are referred to as transport coefficients and are defined using the coarse group total cross section. [10] The definitions of the transport coefficients are dependent on the spatial method used to solve the transport equation. In the case of 1D step characteristics, the coarse group transport coefficients are defined according to Equation (2.10).…”

Section: Exact Recondensationmentioning

confidence: 99%

“…[6] [7][8] [9] One of the main problems with generalized multigroup and recondensation is that the nonlinear iteration is not consistent with the fine group problem when using high order spatial methods, meaning the nonlinear iteration does not converge to the fine group solution. [10] [11] Previous work modifying the generalized multigroup equations produced full consistency with the fine group problem but came with a substantial increase in memory requirements. To overcome this limitation, this paper proposes a new nonlinear acceleration method as the primary means of producing high fidelity solutions in an efficient manner for high energy and angular dimensionality problems.…”

Section: Introductionmentioning

confidence: 99%

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The Source Equivalence Acceleration Method

Everson

Forget

2015

Annals of Nuclear Energy

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Fine-group whole-core reactor analysis remains one of the long sought goals of the reactor physics community. Such a detailed analysis is typically too computationally expensive to be realized on anything except the largest of supercomputers. Recondensation using the Discrete Generalized Multigroup (DGM) method, though, offers a relatively cheap alternative to solving the fine group transport problem. DGM, however, suffered from inconsistencies when applied to high-order spatial methods. While an exact spatial recondensation method was developed and provided full spatial consistency with the fine group problem, this approach substantially increased memory requirements for realistic problems. The method described in this paper, called the Source Equivalence Acceleration Method (SEAM), forms a coarse-group problem which preserves the fine-group problem even when using higher order spatial methods. SEAM allows recondensation to converge to the fine-group solution with minimal memory requirements and little additional overhead. This method also provides for consistency when using different spatial methods and angular quadratures between the coarse group and fine group problems. SEAM was implemented in OpenMOC, a 2D MOC code developed at MIT, and its performance tested against Coarse Mesh Finite Difference (CMFD) acceleration on the C5G7 benchmark problem and on a 361 group version of the problem. For extremely expensive transport calculations, SEAM was able to outperform CMFD, resulting in speed-ups of 20-45 relative to the normal power iteration calculation.

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Section: Exact Recondensationmentioning

confidence: 99%