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
Human Factors, Instrumentation & Controls
Improving task performance, system reliability, system and personnel safety, efficiency, and effectiveness are the division's main objectives. Its major areas of interest include task design, procedures, training, instrument and control layout and placement, stress control, anthropometrics, psychological input, and motivation.
Meeting Spotlight
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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
Jul 2024
Jan 2024
Latest Journal Issues
Nuclear Science and Engineering
September 2024
Nuclear Technology
August 2024
Fusion Science and Technology
Latest News
Taking shape: Fusion energy ecosystems built with public-private partnerships
It’s possible to describe fusion in simple terms: heat and squeeze small atoms to get abundant clean energy. But there’s nothing simple about getting fusion ready for the grid.
Private developers, national lab and university researchers, suppliers, and end users working toward that goal are developing a range of complex technologies to reach fusion temperatures and pressures, confounded by science and technology gaps linked to plasma behavior; materials, diagnostics, and electronics for extreme environments; fuel cycle sustainability; and economics.
Dingkang Zhang, Farzad Rahnema
Nuclear Science and Engineering | Volume 182 | Number 3 | March 2016 | Pages 369-376
Technical Paper | doi.org/10.13182/NSE15-15
Articles are hosted by Taylor and Francis Online.
The coupled stochastic deterministic COarse MEsh radiation Transport (COMET) method requires a library of incident flux response expansion coefficients for its whole-core calculations. These coefficients are calculated using a stochastic method because of its high accuracy and robustness in modeling geometric complexity. However, the stochastic uncertainty inherent in response coefficients is unavoidably propagated into the whole-core calculations, and consequently, its effects must be quantitatively evaluated. The current method in COMET based on the error propagation significantly overpredicts uncertainty since the correlations among response coefficients are ignored. In this paper, a new adjoint-based method is developed to take into account the uncertainty and correlations of response coefficients. In this approach, forward calculations are first performed to obtain whole-core solutions such as the core eigenvalue and forward partial currents crossing mesh surfaces. Low-order adjoint calculations are then performed to determine the sensitivity of response coefficients. The core eigenvalue uncertainty is finally computed by taking into account the variances of surface-to-surface response coefficients, response fission production, and absorption rates as well as their correlations. The eigenvalue uncertainty predicated by the new method agrees very well with the reference solution, with a discrepancy <3 pcm, while the original error propagation method significantly overestimates the uncertainty. It is also found that the new method’s computational efficiency is comparable to that of the current error propagation method in COMET since the computation time spent on the adjoint calculations is negligible. As an additional benefit, since the covariances among response coefficients are absorbed into the variance of the response net gain rates and the variance of the effective leakage terms, no extra computer memory is needed to store these covariances.