ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Decommissioning & Environmental Sciences
The mission of the Decommissioning and Environmental Sciences (DES) Division is to promote the development and use of those skills and technologies associated with the use of nuclear energy and the optimal management and stewardship of the environment, sustainable development, decommissioning, remediation, reutilization, and long-term surveillance and maintenance of nuclear-related installations, and sites. The target audience for this effort is the membership of the Division, the Society, and the public at large.
2021 Student Conference
April 8–10, 2021
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
Latest Magazine Issues
Latest Journal Issues
Nuclear Science and Engineering
Fusion Science and Technology
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.
Y. F. Chen, R. J. Sheu, S. H. Jiang, J. N. Wang, U. T. Lin
Nuclear Technology | Volume 175 | Number 1 | July 2011 | Pages 343-350
Technical Paper | Special Issue on the 16th Biennial Topical Meeting of the Radiation Protection and Shielding Division / Radiation Transport and Protection | dx.doi.org/10.13182/NT11-A12306
Articles are hosted by Taylor and Francis Online.
Based on the Consistent Adjoint Driven Importance Sampling (CADIS) methodology, MAVRIC is a new computational sequence in the SCALE6 code package that is designed to perform efficient Monte Carlo simulation for a complicated and difficult shielding problem. This study aimed to evaluate the performance of MAVRIC with the latest cross-section library in calculating the surface dose rates of a realistic spent-fuel storage cask. Detailed dose rate profiles over the cask side and top surfaces were calculated, and the results were compared with our previous work using SAS4 and MCNP. In order to duplicate the same source model, the MAVRIC code has been modified to accommodate a user-defined axial source distribution. The comparison among the three codes was evaluated in terms of their accuracies and computational efficiencies. For the gamma-ray sources, the MAVRIC-calculated results are more accurate than SAS4 and consistent with those predicted by the continuous-energy MCNP calculations. Meanwhile, its computational efficiencies are comparable to the performance of the TORT-coupled MCNP calculations. For the fuel neutron source, the MAVRIC calculation with broad-group cross sections cannot give satisfactory result, and its computational performance is also a factor of [approximately]10 less efficient than that of TORT-coupled MCNP. With a fine-group cross-section library, MAVRIC can provide a better prediction but still underestimates the surface dose rates of the cask by 15 to 30%.