Evaluation of Hot Spot Factors for Thermal and Hydraulic Design of HTTR.

Maruyama, S.; Yamashita, Kiyonobu; Fujimoto, Nozomu; Murata, Isao; Sudo, Yukio; Murakami, Tomoyuki; Fujii, Sadao

doi:10.3327/jnst.30.1186

Cited by 4 publications

(9 citation statements)

References 5 publications

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“…1.025 [111], and 1.05 [100] respectively. The nature of this subfactor does not preclude subfactors from any of the three reactor designs from being applied to FHR reactor designs.…”

Section: Implementation Of Hot Channel Factorsmentioning

confidence: 99%

“…The FBR lists a subfactor of 1.05 for maldistribution of flux [54]. The HTTR lists subfactors for radial and axial power distributions of 1.03 and 1.04 respectively for a multiplicatively combined subfactor of 1.07 [111]. The MITR lists a subfactor of 1.10 based off a 10% uncertainty in local power [53,100].…”

Section: Implementation Of Hot Channel Factorsmentioning

confidence: 99%

“…The HTTR design coolant flow rate enthalpy rise EHCF is 1.01 where the flow rate is controlled to maintain the rated reactor outlet temperature [111]. and within subassemblies is 1.15 [54].…”

Section: Implementation Of Hot Channel Factorsmentioning

confidence: 99%

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Fluoride-Salt-Cooled High-Temperature Test Reactor Thermal-Hydraulic Licensing and Uncertainty Propagation Analysis

2019

Nuclear Technology

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An important Fluoride-salt-cooled High-temperature Reactor (FHR) development step is to design, build, and operate a test reactor. Through a literature review, liquid-salt coolant thermophysical properties have been recommended along with their uncertainties of 2-20%. This study tackles determining the effects of these high uncertainties by proposing a newly developed methodology to incorporate uncertainty propagation in a thermalhydraulic safety analysis for test reactor licensing. A hot channel model, Monte Carlo statistical sampling uncertainty propagation, and limiting safety systems settings (LSSS) approach are uniquely combined to ensure sufficient margin to fuel and material thermal limits during steady-state operation and to incorporate margin for high uncertainty inputs. The method calculates LSSS parameters to define safe operation. The methodology has been applied to two test reactors currently considered, the Chinese TMSR-SF1 pebble bed design and MIT's Transportable FHR prismatic core design; two candidate coolants, flibe (LiF-BeF 2) and nafzirf (NaF-ZrF 4); and forced flow and natural circulation conditions to compare operating regions and LSSS power (maximum power not exceeding any thermal limits). The calculated operating region accounts for uncertainty (2σ) with LSSS power (MW) for forced flow of 25.37±0.72, 22.56±1.15, 21.28±1.48, and 11.32±1.35 for pebble flibe, pebble nafzirf, prismatic flibe, and prismatic nafzirf, respectively. The pebble bed has superior heat transfer with an operating region reduced ∼10% less when switching coolants and ∼50% smaller uncertainty than the prismatic. The maximum fuel temperature constrains the pebble bed while the maximum coolant temperature constrains the prismatic due to different dominant heat transfer modes. Sensitivity analysis revealed 1) thermal conductivity and thus conductive heat transfer dominates in the prismatic design while convection is superior in the pebble bed, and 2) the impact of thermophysical property uncertainties are ranked in the following order: thermal conductivity, heat capacity, density, and lastly viscosity. Broadly, the methodology developed incorporates uncertainty propagation that can be used to evaluate parametric uncertainties to satisfy guidelines for non-power reactor licensing applications, and method application shows the pebble bed is more attractive for thermal-hydraulic safety. Although the method was developed and evaluated for coolant property uncertainties for FHR, it is readily applicable for any parameters of interest.

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“…1.025 [111], and 1.05 [100] respectively. The nature of this subfactor does not preclude subfactors from any of the three reactor designs from being applied to FHR reactor designs.…”

Section: Implementation Of Hot Channel Factorsmentioning

confidence: 99%

Section: Implementation Of Hot Channel Factorsmentioning

confidence: 99%

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Fluoride-Salt-Cooled High-Temperature Test Reactor Thermal-Hydraulic Licensing and Uncertainty Propagation Analysis

2019

Nuclear Technology

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“…The hot spot factors [4,[8][9][10], which consist of systematic factors and random factors, are used to account for various uncertainties and to assure that the specified maximum fuel temperature in the core does not ex-ceed the fuel design limit at any time and any location during the normal operation condition. The systematic (cumulative) factors show errors or uncertainties on reactor thermal power, power distribution, coolant flow rate, flow rate distribution, and inlet coolant temperature.…”

Section: Fuel Temperature Analysis With Hot Spot Factorsmentioning

confidence: 99%

“…It was confirmed experimentally that the coating layers of the coated fuel particles can maintain their intactness below 1600 • C [3]. In order to satisfy this requirement, the maximum fuel temperature in normal operation, which means rated operation with a reactor outlet coolant temperature of 850 • C and hightemperature test operation with a reactor outlet coolant temperature of 950 • C, needs to be lower than 1495 • C [2,4].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of maximum fuel temperature in HTTR

Inaba

Tochio

Ueta

et al. 2014

Journal of Nuclear Science and Technology

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In order to ensure the thermal integrity of fuel in the high temperature engineering test reactor (HTTR), it is necessary that the maximum fuel temperature in the normal operation is to be lower than a thermal design limit of 1495 • C. In the core thermal and hydraulic design of the HTTR, the maximum fuel temperature was estimated to be 1492 • C, which satisfied the thermal design limit. However, the estimated temperature was derived by using hot spot factors with a large safety margin for the consideration of uncertainties in the design stage without the HTTR practical operating data, and thus there is no doubt that the estimated temperature includes excessive conservativeness. In order to obtain the maximum fuel temperature with appropriate conservativeness, the maximum fuel temperature has been re-evaluated on the basis of the HTTR operating data. In this paper, the random factors of the hot spot factors are revised by using the HTTR first fuel fabrication data, and the new maximum fuel temperature is estimated. As a result, the estimated maximum fuel temperature can be reduced to 1424 • C. The reduction of the maximum fuel temperature leads to a larger thermal margin in nuclear and fuel designs.

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