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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.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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!
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Latest News
X-energy receives federal tax credit for TRISO fuel facility
Advanced reactor company X-energy has been awarded $148.5 million in tax credits under the Inflation Reduction Act for construction of its TRISO-X fuel fabrication facility in Oak Ridge, Tenn.
Tracy E. Stover, Paul J. Turinsky
Nuclear Technology | Volume 180 | Number 2 | November 2012 | Pages 216-230
Technical Paper | Radiation Measurements and General Instrumentation | doi.org/10.13182/NT12-A14635
Articles are hosted by Taylor and Francis Online.
The safe and economical design of new, innovative nuclear reactors will require uncertainty reduction in basic nuclear data that are input to simulations used during reactor design. These data uncertainties propagate to uncertainties in design responses, which in turn require the reactor designer to incorporate additional safety margins into the design, often increasing the cost of the reactor. Therefore, basic nuclear data need to be improved, and this is accomplished through experimentation, which is often done using cold critical experiments. Considering the high cost of nuclear experiments, it is desired to have an optimized experiment that will provide the experimental data needed for maximum uncertainty reduction in the design responses. However, the optimization of the experiment is coupled to the reactor design itself because with reduced uncertainty in the design responses the reactor design can be re-optimized. It is thus desired to find the experiment design that gives the most optimized reactor design. Solution of this nested optimization problem is made possible by the use of the simulated annealing algorithm. Cost values for experiment design specifications and reactor design specifications are estimated and used to compute a total savings by comparing the a posteriori reactor cost to the a priori cost accounting for the offsetting cost of the experiment. This was done for the Argonne National Laboratory-developed Advanced Burner Test Reactor design concept employing a modified Zero Power Physics Reactor as the experimental facility.