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Thermal Hydraulics
The division provides a forum for focused technical dialogue on thermal hydraulic technology in the nuclear industry. Specifically, this will include heat transfer and fluid mechanics involved in the utilization of nuclear energy. It is intended to attract the highest quality of theoretical and experimental work to ANS, including research on basic phenomena and application to nuclear system design.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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!
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Glass strategy: Hanford’s enhanced waste glass program
The mission of the Department of Energy’s Office of River Protection (ORP) is to complete the safe cleanup of waste resulting from decades of nuclear weapons development. One of the most technologically challenging responsibilities is the safe disposition of approximately 56 million gallons of radioactive waste historically stored in 177 tanks at the Hanford Site in Washington state.
ORP has a clear incentive to reduce the overall mission duration and cost. One pathway is to develop and deploy innovative technical solutions that can advance baseline flow sheets toward higher efficiency operations while reducing identified risks without compromising safety. Vitrification is the baseline process that will convert both high-level and low-level radioactive waste at Hanford into a stable glass waste form for long-term storage and disposal.
Although vitrification is a mature technology, there are key areas where technology can further reduce operational risks, advance baseline processes to maximize waste throughput, and provide the underpinning to enhance operational flexibility; all steps in reducing mission duration and cost.
Dan Gabriel Cacuci
Nuclear Science and Engineering | Volume 186 | Number 3 | June 2017 | Pages 199-223
Technical Paper | doi.org/10.1080/00295639.2017.1305244
Articles are hosted by Taylor and Francis Online.
Using the problem of inverse prediction from detector responses in the presence of counting uncertainties of the thickness of a homogeneous slab of material containing uniformly distributed gamma-emitting sources, this work investigates the possible reasons for the apparent failure of the traditional inverse-problem methods based on the minimization of chi-square-type functionals to predict accurate results for optically thick slabs. This work also compares the results produced by such methods with the results produced by applying the Predictive Modeling of Coupled Multi-Physics Systems (PM-CMPS) methodology for optically thin and thick slabs. For optically thin slabs, this work shows that both the traditional chi-square-minimization method and the PM-CMPS methodology predict the slab’s thickness accurately. However, the PM-CMPS methodology is considerably more efficient computationally, and a single application of the PM-CMPS methodology predicts the thin slab’s thickness at least as precisely as the traditional chi-square-minimization method, even though the measurements used in the PM-CMPS methodology were ten times less accurate than the ones used for the traditional chi-square-minimization method. For optically thick slabs, the results obtained in this work show that: (1) the traditional inverse-problem methods based on the minimization of chi-square-type functionals fail to predict the slab’s thickness; (2) the PM-CMPS methodology underpredicts the slab’s actual physical thickness when imprecise experimental results are assimilated, even though the predicted responses agree within the imposed error criterion with the experimental results; (3) the PM-CMPS methodology correctly predicts the slab’s actual physical thickness when precise experimental results are assimilated, while also predicting the physically correct response within the selected precision criterion; and (4) the PM-CMPS methodology is computational vastly more efficient while yielding significantly more accurate results than the traditional chi-square-minimization methodology.