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2026 Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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Latest News
Mike Kramer: Navigating power deals in the new data economy
Mike Kramer has a background in finance, not engineering, but a combined 20 years at Exelon and Constellation and a key role in the deals that have Meta and Microsoft buying power from Constellation’s Clinton and Crane sites have made him something of a nuclear expert.
Kramer spoke with Nuclear News staff writer Susan Gallier in late August, just after a visit to Clinton in central Illinois to celebrate a power purchase agreement (PPA) with Meta that closed in June. As Constellation’s vice president for data economy strategy, Kramer was part of the deal-making—not just the celebration.
Dylan S. Hoagland, Raffi A. Yessayan, Yousry Y. Azmy
Nuclear Science and Engineering | Volume 195 | Number 10 | October 2021 | Pages 1036-1064
Technical Paper | doi.org/10.1080/00295639.2021.1898309
Articles are hosted by Taylor and Francis Online.
The Parallel Block Jacobi (PBJ) spatial domain decomposition is well suited for implementation on massively parallel computers to solve the neutron transport equation on unstructured grids due to the simple scheduling policy that arises from the PBJ’s iterative asynchronicity. The Parallel Block Jacobi-Integral Transport Matrix Method (PBJ-ITMM) is an iterative method that utilizes the PBJ decomposition and resolves local within-group scattering in a single iteration, but requires a matrix-vector iterative solution. This work details the development, implementation, and testing of the novel Green’s Function ITMM Construction (GFIC) algorithm. The GFIC constructs the matrices required for the PBJ-ITMM’s iterative solution on unstructured grids, utilizing the physical interpretation of these matrices as discretized response functions to create a local problem with a Green’s Function–like source. Conducting a set of mesh sweeps over all angles on this local problem yields the ITMM matrix elements. On unstructured grids, this approach utilizes the kernel calculation and fundamental solution algorithm present in an existing transport code, thus avoiding reimplementation of code functionality. Using the GFIC, the PBJ-ITMM is implemented in THOR, a tetrahedral mesh transport code, along with the Inexact Parallel Block Jacobi (IPBJ) method for performance comparison. This comparison involves strong and weak scaling studies of the Godiva and C5G7 benchmark problems using up to 32 768 processors. These studies establish that the PBJ-ITMM executes faster than the IPBJ when the number of cells per subdomain falls below a problem-dependent threshold, ~128 cells for Godiva, >256 cells for C5G7. The largest problem tested, comprising more than 6.8 billion unknowns, solves in <30 min with the IPBJ and <20 min with the PBJ-ITMM, using 32 768 processors. These results demonstrate the PBJ-ITMM as a viable approach for solving neutron transport problems on unstructured grids using massively parallel computers. Additionally, this study illustrates the range of number of cells per subdomain over which this method is favorable.
