UO2Thermal

Computes thermal conductivity and specific heat capacity of uranium dioxide fuel.

Description

The UO2Thermal model computes specific heat and thermal conductivity for oxide fuel. A number of correlations are available. This model is also compliant for use in AD-based simulations by adding the AD prefix to the type name.

Thermal Conductivity

Five empirical models are available in BISON to compute UO thermal conductivity and its dependence on temperature, porosity, burnup, and, for four of the models, Gadolinia content. Choices for UO fuel include:

The Halden, NFIR and modified NFI models can account for Gadolinia content. Empirical fits for the temperature dependent specific heat of UO accompany the Fink-Lucuta conductivity model.

For the most part, the thermal conductivity of urania is represented as the sum of a lattice vibration (phonon) and an electronic (electron hole pair effect) term or for unirradiated material at 95% theoretical density (TD) (1) The first term in Eq. (1) is typically inversely proportional to the sum of temperature and burnup dependent functions, while the second term, usually an exponential function of inverse temperature, is inversely proportional to temperature or temperature squared. For example, (2) (3) where , , and are constants, is burnup, is temperature, and , , , and are functions of burnup or temperature. While each of the thermal conductivity models has the basic form given by Eq. (2) and Eq. (3), each has their own specific set of constants and perhaps additional corrections that account for effects of dissolved fission products, precipitated fission products, porosity, deviation from stoichiometry, and radiation damage. In general, the final conductivity corrected for these effects is given as (4) where is the dissolved fission products correction, is the precipitated fission products correction, is the porosity correction, is the deviation from stoichiometry (1.0 for uranium fuel but 1 if Gadolinia is present), and is the radiation damage correction.

Fink-Lucuta

In the Fink-Lucuta model, the temperature-dependence of unirradiated material is defined using the equation suggested by Fink (2000). This relationship is then modified to account for the effects of irradiation, porosity and burnup using a series of multipliers, as outlined in detail by Lucuta et al. (1996). The Fink equation is (5) where is the temperature in K divided by 1000. Eq. (5) is multiplied by the following factor to obtain 100% TD thermal conductivity (6) Eq. (6) is then corrected per Eq. (4) as perscribed by Lucuta with the following correction factors.

The dissolved fission products correction is given as (7) and the precipitated fission products correction is calculated as (8) where is the burnup in atomic percent and is the temperature in K. The porosity correction is determined with (9) where is the porosity.

Finally the radiation damage correction factor is given by (10) where is the temperature in K, and bu is the burnup in atomic percent. The Fink-Lucuta model is valid from 298 to 3120 K (Carbajo et al., 2001).

Halden

The Halden model has the following form for the thermal conductivity (95% theoretical density): (11) where the reciprocal expression and term6 correspond to k and k, respectively. For 95% TD fuel, the terms for Eq. (11) are given in Table 1.

Table 1: Parameters used in the Halden Thermal Fuel Model (Lanning et al., 2005)

Model ExpressionParameter Value
0.1148
1.1599 Gdcon
1.1599
BuUO2
1

where is the Gadolinia concentration in weight percent, is the deviation from stoichiometry, i.e. (2 - oxygen/metal ratio), is the burnup in MWd/kgUO, and is the temperature in C.

Eq. (11) is multiplied by the appropriate factor to return the thermal conductivity to 100% TD and then multiplied by a density correction factor (similar to Eq. (9) but written in terms of percent TD) to provide a thermal conductivity representative of the material of interest (12) where is the fractional TD. The multiplier 1.0789 is the inverse of the density correction factor evaluated at 0.95 TD. The Halden UO correlation is valid over the following ranges (Lanning et al., 2005)

Figure 1 compares the the Fink-Lucuta and Halden models as a function of temperature and burnup for 95% theoretical density UO.

Figure 1: A comparison of the Fink-Lucuta and Halden empirical models for the thermal conductivity of 95% theoretical density UO, as a function of temperature and burnup.

NFIR

The NFIR correlation also has the general form of Eq. (1). However, the NFIR model contains a temperature dependent thermal recovery function that accounts for self-annealing of defects in the fuel as it heats up. The ultimate effect of the self- annealing is a slight increase of the thermal conductivity over a range of temperatures up to 1200 K. As a result of this formulation, two components of are used, one at the start of thermal recovery and one at the end of thermal recovery. The thermal recovery function is used to interpolate between these two values to compute k. Thus (13) where is the thermal recovery function, is temperature in , is the phonon contribution at the start of thermal recovery, and is the phonon contribution at the end of thermal recovery. This model has a gadolinium correction associated with it. Gadolinium is reported as weight percent with the default set to zero. The individual terms are (14) (15)

(16)

(17)

(18)

(19)

(20)

(21) where is burnup in MWd/kgU and is gadolinia content in wt.%. Eq. (13) is then multiplied by a temperature dependent density correction factor to give (22) where is the fractional density. Figure 2 compares the the Fink-Lucuta and NFIR models as a function of temperature and burnup for 95% theoretical density UO.

Figure 2: A comparison of the Fink-Lucuta and NFIR empirical models for the thermal conductivity of 95% theoretical density UO, as a function of temperature and burnup.

Modified NFI

The modified NFI model is also of the form of Eq. (11). Terms are defined in Table 2.

Table 2: Parameters used in the Modified NFI Thermal Fuel Model

Model ExpressionParameter Value
0.0452
1.1599 Gdcon
T
Bu

where is the Gd concentration in weight percent, is the temperature in K, is the burnup in MWd/kgU. Again, Eq. (12) is used to convert to the TD of interest. The modified NFI model is valid over the following ranges (Lanning et al., 2005)

Figure 3 compares the Fink-Lucuta and NFI modified models as a function of temperature and burnup for 95% theoretical density UO.

Figure 3: A comparison of the Fink-Lucuta and modified NFI empirical models for the thermal conductivity of 95% theoretical density UO, as a function of temperature and burnup.

Ronchi-Staicu Models

The thermal conductivity at 95% TD (i.e., normalized to 5 vol.% as-fabricated porosity), (W/m/K) is expressed in the following form:

where is the burnup (GWd/t), is the irradiation temperature (K), is the maximum temperature reached during out-of-pile annealing (K), is the instant application temperature (K), and . is assumed to be in the form given by Ronchi et al. (1999). is formulated in terms of the semi-empirical models of and by Ronchi et al. (2004) and Staicu et al. (2014) as follows:

  • Ronchi et al. (2004) formulates a model for as:

    (27)

    In Staicu et al. (2014), in Eq. (27) is replaced by for zero gadolinia addition and for non-zero gadolinia addition, where is the gadolinia content in wt.%.

    The effect of the irradiation defects on is defined in terms of the out-pile self-irradiation effect () and the effective concentration of irradiation defects at end of life (EOL) () as where is the maximum temperature of and (i.e., ).

    (28) In Staicu et al. (2014), in Eq. (28) is replaced by .

    The contribution of nonvolatile and volatile fission products is incorporated into the thermal conductivity model by Ronchi et al. (2004) and Staicu et al. (2014) as: where is the fraction of volatile fission products present as dispersed atoms in the fuel matrix and is expressed by in terms of

  • Ronchi et al. (2004) formulates a model for as:

    (29)

    In Staicu et al. (2014), in Eq. (29) is replaced by for zero gadolinia addition and for non-zero gadolinia addition, where is the gadolinia content in wt.%.

Toptan Model

The thermal conductivity at 95% TD (i.e., normalized to 5 vol.% as-fabricated porosity), (W/m/K) is expressed by Toptan et al. (2020) in the following form:

with where is the fuel temperature (), is the fraction of the gadolinia content (weight fraction), and is the burnup (MWd/kgU).

The thermal conductivity normalized to a given porosity (fraction) is obtained by

Crumbled Fuel Thermal Conductivity

When simulating LOCA conditions some portions of the fuel column may collapse into a crumbled mixture of fuel fragments and gas. In these regions the effective fuel thermal conductivity of the mixture is calculated by the model proposed by Chiew and Glandt (1983). This model can be used for both UO and mixed oxide (MOX) fuel.

The correlation is given by: where is the reduced thermal polarizability, is the thermal conductivity of the fuel determined by one of the models above, is the packing fraction of the crumbled fuel, and is a function of and defined later. The reduced thermal polarizability is given by: where is the thermal conductivity of the gas surrounding the crumbled fuel particles. The function is approximated by: where Jernkvist and Massih (2015) used best fit approximations to the tabulated values of Chiew and Glandt (1983) to obtain:

Porosity Correction in the high burnup structure

Our current approach uses an ad hoc porosity model to model the porosity evolution due to the high burnup structure (HBS) formation. We calibrated a surrogate model that is obtained from measured local burnup and measured porosity. The porosity, is given by where is the local burnup (GWd/t). The porosity-burnup relation is illustrated in Figure 4 along with the experimental data.

Figure 4: A comparison of the surrogate model as a function of local burnup (experimental data from Spino et al. (1996), Spino and Papaioannou (2000), and Spino et al. (2006)).

The rim thermal conductivity is computed using three methods according to

  1. Kämpf and Karsten (1970):

(23)

  1. Lee et al. (2001), Schulz (1981), and Kleykamp (1999):

(24)

  1. Maxwell-Eucken model:

(25) where is the rim thermal conductivity, is the thermal conductivity of conducting pores, is the porosity (dimensionless), and is the thermal conductivity of the continuous material.

It is assumed that the pores are filled with xenon. Thus, the pore thermal conductivity is computed using the following relation:

where is the temperature (K).

Note that the second method is expressed in terms of a third-order polynomial. The rim thermal conductivity is computed by solving this cubic equation given in Eq. (24). There may be three possible solutions. The highest real root is assigned for the rim thermal conductivity, . We employ a root-finding algorithm to solve the cubic equation analytically (Toptan et al., 2020).

When modeling the porosity correction due the formation of the HBS, the amount of fuel at given location within the fuel that has restructured needs to be known. This hbs_volume_fraction is computed in the HighBurnupStructureFormation model. Using this volume fraction a weighted average of is used to compute the effective thermal conductivity:

Specific Heat Capacity

The specific heat capacity (J/kg-K) is expressed by (26) where is the temperature (K), is the oxygen-to-metal ratio (dimensionless), and is the universal gas constant (8.3145 J/mol-K). The empirical coefficients (, , , , and ) are tabulated in Table 3 for UO, and GdO.

The specific heat capacity of -doped UO fuel is computed as: where is the fraction of gadolina or plutonium content (dimensionless) and is the specific heat capacity for UO, and GdO.

Table 3: The empirical constants used in Eq. (26) from Luscher et al. (2015).

Constant (J/kg-K) (J/kg-K) (J/kg) (K) (J/mol)
UO296.72.43108.74510535.2851.57710
GdO315.864.044100.0348.00.0

Example Input Syntax

[Materials<<<{"href": "../../syntax/Materials/index.html"}>>>]
  [fuel_thermal]
    type = UO2Thermal<<<{"description": "Computes thermal conductivity and specific heat capacity of uranium dioxide fuel.", "href": "UO2Thermal.html"}>>>
    block<<<{"description": "The list of blocks (ids or names) that this object will be applied"}>>> = 2
    thermal_conductivity_model<<<{"description": "The thermal conductivity model."}>>> = FINK_LUCUTA
    initial_porosity<<<{"description": "Initial porosity.  Must be between 0.0 and 1.0."}>>> = 0.0
    temperature<<<{"description": "Coupled temperature"}>>> = temperature
    burnup_function<<<{"description": "Burnup function"}>>> = burnup
  []
[]
(test/tests/sifgrs/uo2/athermal_release.i)

Input Parameters

  • temperatureCoupled temperature

    C++ Type:std::vector<VariableName>

    Unit:(no unit assumed)

    Controllable:No

    Description:Coupled temperature

  • thermal_conductivity_modelFINK_LUCUTAThe thermal conductivity model.

    Default:FINK_LUCUTA

    C++ Type:MooseEnum

    Options:FINK_LUCUTA, HALDEN, NFIR, MODIFIED_NFI, RONCHI, STAICU, TOPTAN

    Controllable:No

    Description:The thermal conductivity model.

Required Parameters

  • Gd_content0Weight fraction of gadolinium in fuel.

    Default:0

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Weight fraction of gadolinium in fuel.

  • axial_relocation_objectName of the AxialRelocationUserObject that determines whether the fuel has crumbled.

    C++ Type:UserObjectName

    Controllable:No

    Description:Name of the AxialRelocationUserObject that determines whether the fuel has crumbled.

  • base_nameOptional parameter that allows the user to define multiple material systems on the same block, i.e. for multiple phases

    C++ Type:std::string

    Controllable:No

    Description:Optional parameter that allows the user to define multiple material systems on the same block, i.e. for multiple phases

  • blockThe list of blocks (ids or names) that this object will be applied

    C++ Type:std::vector<SubdomainName>

    Controllable:No

    Description:The list of blocks (ids or names) that this object will be applied

  • boundaryThe list of boundaries (ids or names) from the mesh where this object applies

    C++ Type:std::vector<BoundaryName>

    Controllable:No

    Description:The list of boundaries (ids or names) from the mesh where this object applies

  • burnupCoupled burnup

    C++ Type:std::vector<VariableName>

    Unit:(no unit assumed)

    Controllable:No

    Description:Coupled burnup

  • burnup_functionBurnup function

    C++ Type:FunctionName

    Unit:(no unit assumed)

    Controllable:No

    Description:Burnup function

  • burnup_materialMaterial property name for burnup.

    C++ Type:MaterialPropertyName

    Unit:(no unit assumed)

    Controllable:No

    Description:Material property name for burnup.

  • computeTrueWhen false, MOOSE will not call compute methods on this material. The user must call computeProperties() after retrieving the MaterialBase via MaterialBasePropertyInterface::getMaterialBase(). Non-computed MaterialBases are not sorted for dependencies.

    Default:True

    C++ Type:bool

    Controllable:No

    Description:When false, MOOSE will not call compute methods on this material. The user must call computeProperties() after retrieving the MaterialBase via MaterialBasePropertyInterface::getMaterialBase(). Non-computed MaterialBases are not sorted for dependencies.

  • constant_onNONEWhen ELEMENT, MOOSE will only call computeQpProperties() for the 0th quadrature point, and then copy that value to the other qps.When SUBDOMAIN, MOOSE will only call computeQpProperties() for the 0th quadrature point, and then copy that value to the other qps. Evaluations on element qps will be skipped

    Default:NONE

    C++ Type:MooseEnum

    Options:NONE, ELEMENT, SUBDOMAIN

    Controllable:No

    Description:When ELEMENT, MOOSE will only call computeQpProperties() for the 0th quadrature point, and then copy that value to the other qps.When SUBDOMAIN, MOOSE will only call computeQpProperties() for the 0th quadrature point, and then copy that value to the other qps. Evaluations on element qps will be skipped

  • declare_suffixAn optional suffix parameter that can be appended to any declared properties. The suffix will be prepended with a '_' character.

    C++ Type:MaterialPropertyName

    Unit:(no unit assumed)

    Controllable:No

    Description:An optional suffix parameter that can be appended to any declared properties. The suffix will be prepended with a '_' character.

  • gap_thermal_conductivityThe layered average thermal conductivity across the gas gap.

    C++ Type:std::vector<VariableName>

    Unit:(no unit assumed)

    Controllable:No

    Description:The layered average thermal conductivity across the gas gap.

  • hbs_porosity_correctionNONEThe porosity correction method for the thermal conductivity model in the high burnup structure.

    Default:NONE

    C++ Type:MooseEnum

    Options:NONE, KAMPF, LEE, MAXWELLEUCKEN

    Controllable:No

    Description:The porosity correction method for the thermal conductivity model in the high burnup structure.

  • initial_porosity0.05Initial porosity. Must be between 0.0 and 1.0.

    Default:0.05

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Initial porosity. Must be between 0.0 and 1.0.

  • model_hbs_formationFalseFlag on whether to take into account the volume fraction of high burnup structure that has formed on the thermal conductivity calculation.

    Default:False

    C++ Type:bool

    Controllable:No

    Description:Flag on whether to take into account the volume fraction of high burnup structure that has formed on the thermal conductivity calculation.

  • oxy_to_metal_ratio2Oxygen-to-metal ratio.

    Default:2

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Oxygen-to-metal ratio.

  • porosityCoupled porosity

    C++ Type:std::vector<VariableName>

    Unit:(no unit assumed)

    Controllable:No

    Description:Coupled porosity

  • porosity_materialFalseWhether a material property for porosity is supplied.

    Default:False

    C++ Type:bool

    Controllable:No

    Description:Whether a material property for porosity is supplied.

Optional Parameters

  • control_tagsAdds user-defined labels for accessing object parameters via control logic.

    C++ Type:std::vector<std::string>

    Controllable:No

    Description:Adds user-defined labels for accessing object parameters via control logic.

  • enableTrueSet the enabled status of the MooseObject.

    Default:True

    C++ Type:bool

    Controllable:Yes

    Description:Set the enabled status of the MooseObject.

  • implicitTrueDetermines whether this object is calculated using an implicit or explicit form

    Default:True

    C++ Type:bool

    Controllable:No

    Description:Determines whether this object is calculated using an implicit or explicit form

  • seed0The seed for the master random number generator

    Default:0

    C++ Type:unsigned int

    Controllable:No

    Description:The seed for the master random number generator

  • use_displaced_meshFalseWhether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.

    Default:False

    C++ Type:bool

    Controllable:No

    Description:Whether or not this object should use the displaced mesh for computation. Note that in the case this is true but no displacements are provided in the Mesh block the undisplaced mesh will still be used.

Advanced Parameters

  • output_propertiesList of material properties, from this material, to output (outputs must also be defined to an output type)

    C++ Type:std::vector<std::string>

    Controllable:No

    Description:List of material properties, from this material, to output (outputs must also be defined to an output type)

  • outputsnone Vector of output names where you would like to restrict the output of variables(s) associated with this object

    Default:none

    C++ Type:std::vector<OutputName>

    Controllable:No

    Description:Vector of output names where you would like to restrict the output of variables(s) associated with this object

Outputs Parameters

  • prop_getter_suffixAn optional suffix parameter that can be appended to any attempt to retrieve/get material properties. The suffix will be prepended with a '_' character.

    C++ Type:MaterialPropertyName

    Unit:(no unit assumed)

    Controllable:No

    Description:An optional suffix parameter that can be appended to any attempt to retrieve/get material properties. The suffix will be prepended with a '_' character.

  • use_interpolated_stateFalseFor the old and older state use projected material properties interpolated at the quadrature points. To set up projection use the ProjectedStatefulMaterialStorageAction.

    Default:False

    C++ Type:bool

    Controllable:No

    Description:For the old and older state use projected material properties interpolated at the quadrature points. To set up projection use the ProjectedStatefulMaterialStorageAction.

Material Property Retrieval Parameters

  • specific_heat_scale_factor1Optional scaling factor applied to the overall specific heat.

    Default:1

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Optional scaling factor applied to the overall specific heat.

  • thermal_conductivity_scale_factor1Optional scaling factor applied to the overall thermal conductivity.

    Default:1

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Optional scaling factor applied to the overall thermal conductivity.

Advanced: Scaling Factors Parameters

Input Files

References

  1. J. Carbajo, L. Gradyon, S. Popov, and V. Ivanov. A review of the thermophysical properties of mox and uo2 fuels. Journal of Nuclear Materials, 299:181–198, 2001.[BibTeX]
  2. Y. C. Chiew and E. D. Glandt. The effect of structure on the conductivity of a dispersion. Journal of Colloid and Interface Science, 91(1):90–104, 1983. doi:10.1016/0021-9797(83)90238-2.[BibTeX]
  3. J. K. Fink. Thermophysical properties of uranium dioxide. Journal of Nuclear Materials, 279(1):1–18, 2000.[BibTeX]
  4. L. O. Jernkvist and A. Massih. Model for axial relocation of fragmented and pulverized fuel pellets in distending fuel rods and its effects on fuel rod heat load. Technical Report SSM-2015:37, StrÃ¥l säkerhets myndigheten, 2015.[BibTeX]
  5. H Kämpf and G Karsten. Effects of different types of void volumes on the radial temperature distribution of fuel pins. Nuclear Technology, 9(3):288–300, 1970. doi:10.13182/NT70-A28783.[BibTeX]
  6. H Kleykamp. Selection of materials as diluents for burning of plutonium fuels in nuclear reactors. Nuclear Materials, 275:1–11, 1999. URL: https://doi.org/10.1016/S0022-3115(99)00144-0, doi:10.1016/S0022-3115(99)00144-0.[BibTeX]
  7. D. D. Lanning, C. E. Beyer, and K. J. Geelhood. Frapcon-3 updates, including mixed-oxide fuel properties. Technical Report NUREG/CR-6534, Vol. 4 PNNL-11513, Pacific Northwest National Laboratory, 2005.[BibTeX]
  8. BH Lee, YH Koo, and DS Sohn. Rim characteristics and their effects on the thermal conductivity in high burnup UO$_2$ fuel. Nuclear Science and Technology, 38(1):45–52, January 2001. doi:10.1080/18811248.2001.9715006.[BibTeX]
  9. P.G. Lucuta, Hj. Matzke, and I.J. Hastings. A pragmatic approach to modelling thermal conductivity of irradiated UO$_2$ fuel: review and recommendations. Journal of Nuclear Materials, 232(2-3):166–180, 1996. URL: http://www.sciencedirect.com/science/article/pii/S0022311596004047, doi:10.1016/S0022-3115(96)00404-7.[BibTeX]
  10. WJ Luscher, KJ Geelhood, and IE Porter. Material property correlations: comparisons between FRAPCON-4.0, FRAPTRAN-2.0, and MATPRO. Technical Report PNNL-19417 Rev. 2, Pacific Northwest National Laboratory, 9 2015.[BibTeX]
  11. W. F. Lyon. Summary report: gd thermal conductivity model updates. Technical Report ANA-P1400138-TN03 Rev. 2, Anatech Corp., 2015.[BibTeX]
  12. K. Ohira and N. Itagaki. Thermal conductivity measurements of high burnup UO$_2$ pellet and a benchmark calculation of fuel center temperature. In Proceedings of the American Nuclear Society Meeting on Light Water Reactor Fuel Performance, 541. Portland, Oregon, Mar 2 to Mar 6, 1997.[BibTeX]
  13. C Ronchi, M Sheindlin, D Staicu, and M Kinoshita. Effect of burn-up on the thermal conductivity of uranium dioxide up to 100.000 mwdt< sup>- 1</sup>. Journal of Nuclear Materials, 327:58–76, 2004. doi:10.1016/j.jnucmat.2004.01.018.[BibTeX]
  14. C. Ronchi, M. Sheindlin, M. Musella, and G.J. Hyland. Thermal conductivity of uranium dioxide up to 2900 K from simultaneous measurement of the heat capacity and thermal diffusivity. Journal of Applied Physics, 85:776–789, 1999.[BibTeX]
  15. B Schulz. Thermal conductivity of porous and highly porous materials. High Temperatures - High Pressures, 13(6):649–660, 1981.[BibTeX]
  16. J Spino and D Papaioannou. Lattice parameter changes associated with the rim-structure formation in high burn-up uo2 fuels by micro x-ray diffraction. Journal of Nuclear Materials, 281:146–162, 2000. doi:10.1016/S0022-3115(00)00236-1.[BibTeX]
  17. J Spino, A D Stalios, H Santa Cruz, and D Baron. Stereological evolution of the rim structure in PWR-fuels at prolonged irradiation: Dependencies with burn-up and temperature. Journal of Nuclear Materials, 354:66–84, 2006. doi:10.1016/j.jnucmat.2006.02.095.[BibTeX]
  18. J Spino, K Vennix, and M Coquerelle. Detailed characterisation of the rim microstructure in PWR fuels in the burn-up range 40-67 GWd/tM. Journal of Nuclear Materials, 231:179–190, 1996. doi:10.1016/0022-3115(96)00374-1.[BibTeX]
  19. D Staicu, VV Rondinella, and others. Effect of burn-up on the thermal conductivity of uranium-gadolinium dioxide up to 100 GWd/tHM. Journal of Nuclear Materials, 453:259–268, 2014. doi:10.1016/j.jnucmat.2014.07.006.[BibTeX]
  20. A. Toptan, G. Pastore, R. L. Williamson, J. D. Hales, and S. R. Novascone. Engineering-scale modeling of thermal conductivity in BISON for UO2 and Gd bearing UO2 fuels. submitted to Journal of Nuclear Materials, ():, 2020. doi:.[BibTeX]
  21. Aysenur Toptan, Jason D. Hales, Richard L. Williamson, Stephen R. Novascone, Giovanni Pastore, and David J. Kropaczek. Modeling of gap conductance for LWR fuel rods applied in the BISON code. Journal of Nuclear Science and Technology, 57(8):963–974, 2020. doi:10.1080/00223131.2020.1740808.[BibTeX]
  22. A. Marion (NEI) letter dated June 13, 2006 to H. N. Berkow (USNRC/NRR). Safety Evaluation by the Office of Nuclear Reactor Regulation of Electric Power Research Institute (EPRI) Topical Report TR-1002865, "Topical Report on Reactivity Initiated Accidents: Bases for RIA Fuel rod Failures and Core Coolability Criteria". http://pbadupws.nrc.gov/docs/ML0616/ML061650107.pdf, 2006.[BibTeX]