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.
Materials Science & Technology
The objectives of MSTD are: promote the advancement of materials science in Nuclear Science Technology; support the multidisciplines which constitute it; encourage research by providing a forum for the presentation, exchange, and documentation of relevant information; promote the interaction and communication among its members; and recognize and reward its members for significant contributions to the field of materials science in nuclear technology.
Nuclear and Emerging Technologies for Space (NETS 2023)
May 7–11, 2023
Idaho Falls, ID|Snake River Event Center
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
The blossoming of cooperation between the U.S. and Canada
The United States and Canadian nuclear industries used to be an example of how two independent teams of engineers facing an identical problem—making electricity from uranium—could come up with completely different answers. In the 1950s, Canada began designing a reactor with tubes, heavy water, and natural uranium, while in the U.S. it was big pots of light water and enriched uranium.
But 80 years later, there is a remarkable convergence. The North American push for a new generation of nuclear reactors, mostly small modular reactors (SMRs), is becoming binational, with U.S. and Canadian companies seeking markets and regulatory certification on both sides of the border and in many cases sourcing key components in the other country.
Joshua M. Hykes, Yousry Y. Azmy
Nuclear Science and Engineering | Volume 179 | Number 4 | April 2015 | Pages 364-380
Technical Paper | doi.org/10.13182/NSE13-91
Articles are hosted by Taylor and Francis Online.
We present a method to map the spectral and spatial distributions of radioactive sources using a limited number of detectors. Locating and identifying radioactive materials is important for border monitoring, in accounting for special nuclear material in processing facilities, and in cleanup operations following a radioactive material spill. Most methods to analyze these types of problems make restrictive assumptions about the distribution of the source. In contrast, the source mapping method presented here allows an arbitrary three-dimensional distribution in space and a gamma peak distribution in energy. To apply the method, the problem is cast as an inverse problem where the system’s geometry and material composition are known and fixed, while the radiation source distribution is sought. A probabilistic Bayesian approach is used to solve the resulting inverse problem since the system of equations is ill-posed. The posterior is maximized with a Newton optimization method. The probabilistic approach also provides estimates of the confidence in the final source map prediction. A set of adjoint, discrete ordinates flux solutions, obtained in this work by the Denovo code, is required to efficiently compute detector responses from a candidate source distribution. These adjoint fluxes form the linear mapping from the state space to the response space. The test of the method’s success is simultaneously locating a set of 137Cs and 60Co gamma sources in a room. This test problem is solved using experimental measurements that we collected for this purpose. Because of the weak sources available for use in the experiment, some of the expected photopeaks were not distinguishable from the Compton continuum. However, by supplanting 14 flawed measurements (out of a total of 69) with synthetic responses computed by MCNP, the proof-of-principle source mapping was successful. The locations of the sources were predicted within 25 cm for two of the sources and 90 cm for the third, in a room with an ~4- × 4-m floor plan. The predicted source intensities were within a factor of ten of their true value.