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.
Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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
Finland in Front: The World’s Likely First Spent Fuel Repository Moves Toward Licensing
The year 2024 is shaping up to be a historic one for Posiva, the waste management organization owned by Finland’s two nuclear power plant utilities, Fortum and Teollisuuden Voima. The company is looking to receive regulatory approval of its operating license for the Onkalo deep geological repository for high-level radioactive waste by the end of the year.
Xiong Gao, Jamie B. Coble, A. C. Hines, Belle R. Upadhyaya, J. Wesley Hines
Nuclear Technology | Volume 207 | Number 11 | November 2021 | Pages 1725-1745
Regular Technical Paper | doi.org/10.1080/00295450.2020.1831873
Articles are hosted by Taylor and Francis Online.
Nuclear power plants (NPPs) require accurate measurement of mass flow rates. Advanced flowmeters have been widely applied in several current industries; however, the operating environment in NPPs is especially harsh because of high temperature, high radiation, and extremely corrosive conditions. Several of the advanced reactor designs, such as liquid sodium pool reactors and integral small modular reactors, do not have conventional primary piping systems. These designs require an alternative method to accurately measure primary flow. Cross-correlation function (CCF) flow estimation can estimate the flow velocity indirectly without any specific instruments for flow measurement. The target flow rate is derived by the delay time between two sensors located near each other along the flow direction. Temperature sensors are a common choice for this function because they are reliable, economical, and widely used in various industries. The delay time is inferred by applying the CCF to the signals collected from two or more sensors. CCF flow estimation can be performed in any structure of the flow region, not limited to pipes. One challenge for the CCF flow estimation is that the accuracy of the flow measurement is mainly determined by the inherent local process variation, which is small compared to the uncorrelated noise. To differentiate the process variations from the uncorrelated noise, this paper demonstrates periodic fluid injection of a different temperature before the sensors to amplify common process variation. The feasibility and accuracy of this method have been investigated through a physical flow loop experiment designed to verify the CCF flow estimation using fluid injection. Several parameters must be selected when designing the fluid injection CCF measurement system, such as the distance between the fluid injection site and the sensors, the injection period, and the injection flow rate. A series of tests was conducted to investigate whether these parameters were related to the accuracy of the CCF flow estimation and to identify appropriate values for these parameters for different flow regimes. The results show that the fluid injection method improves the flow measurement performance, and the appropriate design of flow injection and measurement geometry produces better flow characterization performance over a range of flow rates.