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.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
Feb 2026
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
March 2026
Nuclear Technology
February 2026
Fusion Science and Technology
January 2026
Latest News
Hanford begins removing waste from 24th single-shell tank
The Department of Energy’s Office of Environmental Management said crews at the Hanford Site near Richland, Wash., have started retrieving radioactive waste from Tank A-106, a 1-million-gallon underground storage tank built in the 1950s.
Tank A-106 will be the 24th single-shell tank that crews have cleaned out at Hanford, which is home to 177 underground waste storage tanks: 149 single-shell tanks and 28 double-shell tanks. Ranging from 55,000 gallons to more than 1 million gallons in capacity, the tanks hold around 56 million gallons of chemical and radioactive waste resulting from plutonium production at the site.
Vinay Kumar, Lalit Singh, A. K. Tripathi
Nuclear Technology | Volume 197 | Number 1 | January 2017 | Pages 20-28
Technical Paper | doi.org/10.13182/NT16-89
Articles are hosted by Taylor and Francis Online.
Any risk in safety-critical or control applications may lead to catastrophic disaster; hence, safety is a primary concern for such applications. The impact of risk varies from minor inconvenience and cost to personal injury, significant economic loss, and death. Therefore, a safety assessment process should be an inherent part of the system development process to make a system safe or to ensure that the effects from failures are minimized. This paper deals with a new probabilistic approach to quantify the safety of safety-critical systems (SCSs) and control systems based on probabilistic safety assessment to deal with the shortcomings of the existing techniques. The methodology has been tested on 29 operational data sets to validate its effectiveness. This paper demonstrates the methodology on the digital feedwater controller system of a nuclear power plant. The results indicate that the method can identify possible hazards and quantify such hazards of a SCS.