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.
Division Spotlight
Young Members Group
The Young Members Group works to encourage and enable all young professional members to be actively involved in the efforts and endeavors of the Society at all levels (Professional Divisions, ANS Governance, Local Sections, etc.) as they transition from the role of a student to the role of a professional. It sponsors non-technical workshops and meetings that provide professional development and networking opportunities for young professionals, collaborates with other Divisions and Groups in developing technical and non-technical content for topical and national meetings, encourages its members to participate in the activities of the Groups and Divisions that are closely related to their professional interests as well as in their local sections, introduces young members to the rules and governance structure of the Society, and nominates young professionals for awards and leadership opportunities available to members.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
Standards Program
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
Apr 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
May 2025
Nuclear Technology
April 2025
Fusion Science and Technology
Latest News
Norway’s Halden reactor takes first step toward decommissioning
The government of Norway has granted the transfer of the Halden research reactor from the Institute for Energy Technology (IFE) to the state agency Norwegian Nuclear Decommissioning (NND). The 25-MWt Halden boiling water reactor operated from 1958 to 2018 and was used in the research of nuclear fuel, reactor internals, plant procedures and monitoring, and human factors.
Gokhan Yesilyurt, William R. Martin, Forrest B. Brown
Nuclear Science and Engineering | Volume 171 | Number 3 | July 2012 | Pages 239-257
Technical Paper | doi.org/10.13182/NSE11-67
Articles are hosted by Taylor and Francis Online.
One of the primary challenges associated with the neutronic analysis of a nuclear reactor is accounting for temperature feedback due to Doppler broadening. This challenge is addressed by a new “on-the-fly” methodology that is applied during the random walk process in Monte Carlo codes with negligible impact on computational efficiency. The Monte Carlo code only needs to store 0 K cross sections for each isotope and the method will broaden the 0 K cross sections for any isotope in the library to any temperature in the range 77 to 3200 K for all incoming neutron energies up to 20 MeV. The methodology is based on a combination of Taylor series expansions and asymptotic series expansions. The type of series representation was determined by investigating the temperature dependence of 238U resonance cross sections in three regions: near the resonance peaks, midresonance, and the resonance wings. The coefficients for these series expansions were determined by a regression over the energy and temperature range of interest. Since the resonance parameters are a function of the neutron energy and the target nuclide, the ψ and χ functions in the Adler-Adler multilevel resonance model can be represented by series expansions in temperature only, allowing the least number of terms to approximate the temperature-dependent cross sections within a specified accuracy. The comparison of the broadened cross sections using this methodology with the NJOY cross sections was excellent over the entire temperature range (77 to 3200 K) and energy range. A Monte Carlo code was implemented to apply the combined regression model and used to estimate the additional computing cost, which was found to be <1%.