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NC State celebrates 70 years of nuclear engineering education
An early picture of the research reactor building on the North Carolina State University campus. The Department of Nuclear Engineering is celebrating the 70th anniversary of its nuclear engineering curriculum in 2020–2021. Photo: North Carolina State University
The Department of Nuclear Engineering at North Carolina State University has spent the 2020–2021 academic year celebrating the 70th anniversary of its becoming the first U.S. university to establish a nuclear engineering curriculum. It started in 1950, when Clifford Beck, then of Oak Ridge, Tenn., obtained support from NC State’s dean of engineering, Harold Lampe, to build the nation’s first university nuclear reactor and, in conjunction, establish an educational curriculum dedicated to nuclear engineering.
The department, host to the 2021 ANS Virtual Student Conference, scheduled for April 8–10, now features 23 tenure/tenure-track faculty and three research faculty members. “What a journey for the first nuclear engineering curriculum in the nation,” said Kostadin Ivanov, professor and department head.
Maria Pusa, Jaakko Leppänen
Nuclear Science and Engineering | Volume 175 | Number 3 | November 2013 | Pages 250-258
Technical Paper | dx.doi.org/10.13182/NSE12-52
Articles are hosted by Taylor and Francis Online.
The Chebyshev Rational Approximation Method (CRAM) has recently been introduced by the authors to solve burnup equations, and the results have been excellent. This method has been shown to be capable of simultaneously solving an entire burnup system with thousands of nuclides both accurately and efficiently. The method was prompted by an analysis of the spectral properties of burnup matrices, and it can be characterized as the best rational approximation on the negative real axis. The coefficients of the rational approximation are fixed and have been reported for various approximation orders. In addition to these coefficients, implementing the method requires only a linear solver. This paper describes an efficient method for solving the linear systems associated with the CRAM approximation. The introduced direct method is based on sparse Gaussian elimination, where the sparsity pattern of the resulting upper triangular matrix is determined before the numerical elimination phase. The stability of the proposed Gaussian elimination method is discussed based on consideration of the numerical properties of burnup matrices. Suitable algorithms are presented for computing the symbolic factorization and numerical elimination in order to facilitate the implementation of CRAM and its adoption into routine use. The accuracy and efficiency of the described technique are demonstrated by computing the CRAM approximations for a large test case with 1606 nuclides.