UPuZrThermal

Computes the thermal conductivity and specific heat for U-Pu-Zr fuels based on mole fractions, porosity, and temperature.

Description

This UPuZrThermal and ADUPuZrThermal calculate the thermal conductivity and heat capacity of U-Pu-Zr, where and refers to the atomic fraction of Pu and Zr respectively. When weight fractions are required for individual models, this model internally converts the atom fractions into weight fractions: where is the atomic weight of each element in kg/mol, and is the average atomic mass of the fuel mixture in kg/mol.

Thermal Conductivity Models

A number of thermal conductivity models can be selected via the thcond_model parameter. Each model is described below. Note, these models calculate the fully dense thermal conductivity, with the porosity correction applied later: Here, is the thermal conductivity of the fuel as a function of temperature , composition, porosity , and logged porosity , given the fresh-fuel thermal conductivity , and the porosity correction .

The LANL model is the default for thcond_model, and is the recommended thermal conductivity model.

Constant Model

By setting thcond_model=constant, the can be set to a constant value given by the thermal_conductivity input parameter.

Function Model

By setting thcond_model=function, the can be provided by a MOOSE function named in the thermal_conductivity_func input parameter.

Billone Thermal Conductivity Model

A generic model for the thermal conductivity of U, U-Zr and U-Pu-Zr alloys is given by Billone et al. (1968). The thermal conductivity of unirradiated fuel in units of W/m-K is given by where is the temperature in Kelvin and , , and are temperature coefficients. These coefficients are given by where and are the weight fractions of plutonium and zirconium respectively in the fuel mixture.

Galloway Thermal Conductivity Model

A model for the thermal conductivity of U-Pu-Zr fuel with any concentration of constituents is given by Galloway et al. (2015). Data used to develop the empirical model for thermal conductivity of U-Pu-Zr and U-Zr fresh fuels are obtained from Janney and Papesch (2015), Kim and Hofman (2003), Touloukian et al. (1971), Takahashi et al. (1988), and Bauer (1995). The basis for the model is derived from the formulation given by Touloukian et al. (1971) with coefficient adjustments to minimize the standard deviation of error between data and the current empirical model. The model consists of calculation of the thermal conductivity of each constituent, the thermal conductivity of the binaries U-Zr and Pu-Zr, and finally the thermal conductivity of the ternary UPuZr.

The thermal conductivities in W/m-K for each constituent is calculated by (1)

(2) where is temperature in K. The binary thermal conductivities are calculated by where the adjusted weight fractions for the binary formulations are given as

The correction terms for the binaries are given as

Finally, the ternary thermal conductivity is calculated by (3)

This empirical model gives an average error of -0.02 W/m-K with a standard deviation of 1.46 W/m-K.

Ternary Thermal Conductivity Model: Kim

The ternary thermal conductivity model is very similar to the model used by Galloway, Eq. (3), albeit with different coefficients and different formulation of the ternary thermal conductivity. The original formulation comes from Kim et al. (2014).

The thermal conductivities in W/m-K for each constituent is calculated using Eq. (1) and Eq. (2), with the formulation for plutonium as where is temperature in K. The U-Zr binary thermal conductivity is calculated by: where the adjusted weight fractions for the binary formulations are given as: The correction terms for the U-Zr binary are given as,

The thermal conductivity of the ternary fuel is then where is the weight fraction of plutonium in the fuel and the plutonium thermal conductivity correction is given by

Ternary Thermal Conductivity Model: LANL

Recent work has been applied to extend Kim's model to more data, resulting in new coefficients (Matthews and Unal, 2015). These coefficients are also available as a separate model, designated LANL:

Although only slightly different, when the updated coefficients are plugged into the remainder of the ternary model, the calculation of thermal conductivity results in a standard deviation of less than 1 W/m-K.

Corrected Odaira Thermal Conductivity Model

The main purpose of this model is to provide thermal conductivity approximations during and after melting of the fuel. As such, if no fuel is melting, one of the other thermal conductivity models should be chosen. The model found in Odaira and Arita (2019) had typo errors and an attempt has been made to correct the values to bring the results fairly close to experimental values. Only low Pu approximations from Odaira and Arita (2019) are currently included for ternary fuel.

This model uses the Wiedemann-Franz law to relate the thermal conductivity to electrical conductivity. With the Nordheim's rule, the solid alloy's electrical resistivity relation is assumed to be valid for thermal conductivity as well. As there is no data for liquid U-Pu-Zr's thermal conductivity and the Wiedemann-Franz law is somewhat applicable to liquid alloys (Giordanengo et al., 1999), this model is assumed to be a suitable approximation of liquid U-Pu-Zr thermal conductivity until models based on experimental data become available.

Each separate element's thermal conductivity is approximated by where is temperature in Kelvin and the coefficients , , , and are from Table 1 for each element.

Table 1: Polynomial Coefficients for U, Pu, and Zr

Elementabcd
U21.690.018370
Pu-1.534
Zr27.48-0.025150

For temperatures above 1300 K, becomes unreliable and goes negative. The value at 1300 K is used for all K. In fact, liquid thermal conductivity data for U, Pu, and Zr would improve these polynomial coefficients as the fits are mainly from data below melting of each element.

Using Nordheim's rule for a binary alloy and applying it to thermal conductivity produces where is the Lorentz number set at W / K and .

Repeating the process provides the approximate ternary alloy thermal conductivity of where .

Porosity Correction Models

As the fuel is irradiated, the thermal conductivity becomes degraded due to the growth of fission gas bubbles. Once these bubbles become interconnected, the porosity degradation will improve slightly. Several models exist to account for the impact of gas and sodium filled porosity on the thermal conductivity, with a handful of these models implemented here via the 'porosity_model' input parameter, and described below.

Fractional Porosity Correction Model

Following formulations in Billone et al. (1968) and Hofman et al. (2019) the degradation of the thermal conductivity can be given using a fractional formulation, (4) where is the porosity_factor input parameter, typically taken as 2.5 for conservatism as recommended by Billone et al. (1968).

Power Porosity Correction Model

Following the formulation given in Bauer (1995), the porosity correction factor can also be expressed using a power term, where is the porosity_factor input parameter, typically taken as 1.72.

Logged Porosity Correction Model

A formulation for the porosity correction due to gas and sodium filled porosity has been adopted based on the original formulation in Bauer (1995). Here, the onset of porosity interconnection results in sodium infiltration into the fuel. Given the amount of sodium-flled porosity, , typically calculated via UPuZrSodiumLogging, the porosity correction can be calculated via, where is the thermal conductivity of sodium computed from SodiumProperties, is the porosity_factor input parameter, typically taken as 1.72, and is the amount of gas filled porosity,

Partially Logged Porosity Correction Model

A second sodium infiltration model based on limited radial infiltration of the sodium is also available. As described in Karahan (2009), a thermal conductivity multiplier can be computed as, (5) where is the total porosity and is a infiltrated porosity correction given by, Here, is the fractional penetration depth of sodium into the fuel, is the thermal conductivity of the solid fuel, and the sodium thermal conductivity is given as, where T is in K and is in W/m/K. The correction factor is applied to thermal conductivity depending on the interconnection of the porosity and position in the fuel. If the porosity of the fuel is less than the porosity interconnection threshold, the porosity correction factor is given by Eq. (4). Also, for positions where sodium does not penetrate (i.e. in the center of the pin) defined by the fractional sodium penetration, the porosity correction factor is also given by Eq. (4). For all other cases, the porosity correction factor is given by Eq. (5).

Specific Heat Capacity Models

There are a few different models available for heat capacity that can be selected using the spheat_model input parameter. These models are described in the following sections. The default model is the Savage formulation, and should be utilized due to model inconsistencies with the formulation of the Karahan model.

Constant Model

By setting spheat_model=constant, the specific heat can be set to a constant value given by the specific_heat input parameter.

Function Model

By setting spheat_model=function, the specific heat can be provided by a MOOSE function named in the specific_heat_func input parameter.

Savage Heat Capacity

The correlation for heat capacity from Savage is split into the low temperature region and the high temperature region: (6)

(7) where is temperature in C, and is given in cal/mol-C. A simple linear interpolation is used for the region: (8) where and are the transition temperature 600 C and 650 C respectively.

Lastly, is converted from cal/(mol-C) to J/(kg-K) by multiplying Eq. (6), Eq. (7), or Eq. (8) by 4.184 (J/cal) and dividing by 0.205 (kg/mol). It is important to note that the kg to mol conversion is kept constant, as it applies directly to the data captured by Savage. Changing the conversion factor will result in a dependency on the concentrations of Pu and Zr in the fuel that is not based on data, as is the case with the Karahan model described in Karahan Heat Capacity.

Karahan Heat Capacity

The specific heat capacity of U-Pu-Zr alloys are dependent upon the phase (, or ) as per Karahan (2009) where the transition temperatures are taken from Savage (2006), as = 600 C and = 650 C.

For the phase: (9) For the phase: (10) For the transition phase, interpolation has been performed such that, In the above equations for specific heat capacity, is the temperature in C and is the average atomic mass of the fuel mixture in kg.

It is worth noting that this model is presented by Karahan (2009) but fails to divide the leading constant term by , leading to miscalculation of the original data from Savage (2006). Furthermore, the original formulation by Savage was for U-15w/oPu-10w/oZr, yet the average atomic mass will be different depending of the concentration of Pu and Zr. This results in a correlation for other concentrations that have no experimental support.

Property Derivatives

ADUPuZrThermal automatically provides the correct derivatives for use in kernel evaluation via the automatic differentiation system. UPuZrThermal computes the derivatives as material properties for use in kernels. The available derivatives are the thermal conductivity with respect to temperature and zirconium, and the specific heat with respect to temperature.

Example Input Syntax

[Materials<<<{"href": "../../syntax/Materials/index.html"}>>>]
  [thermal]
    type = UPuZrThermal<<<{"description": "Computes the thermal conductivity and specific heat for U-Pu-Zr fuels                               based on mole fractions, porosity, and temperature.", "href": "UPuZrThermal.html"}>>>
    block<<<{"description": "The list of blocks (ids or names) that this object will be applied"}>>> = 0
    temperature<<<{"description": "Coupled temperature."}>>> = temp
    X_Pu<<<{"description": "Coupled plutonium atom fraction."}>>> = 0.16
    X_Zr<<<{"description": "Coupled zirconium atom fraction."}>>> = X_Zr
    porosity<<<{"description": "Porosity material property name. Required if porosity_model is not 'none'"}>>> = porosity
    outputs<<<{"description": "Vector of output names where you would like to restrict the output of variables(s) associated with this object"}>>> = all
    spheat_model<<<{"description": "Specific heat model. Choices are: karahan savage constant function"}>>> = karahan
  []
[]
(test/tests/upuzr_thermal/test.i)

Input Parameters

  • temperatureCoupled temperature.

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

    Unit:(no unit assumed)

    Controllable:No

    Description:Coupled temperature.

Required Parameters

  • A_Pu0.244Atomic weight of plutonium [kg/mol].

    Default:0.244

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Atomic weight of plutonium [kg/mol].

  • A_U0.238029Atomic weight of uranium [kg/mol].

    Default:0.238029

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Atomic weight of uranium [kg/mol].

  • A_Zr0.091224Atomic weight of zirconium [kg/mol].

    Default:0.091224

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Atomic weight of zirconium [kg/mol].

  • Na_depthPellet depth sodium has infiltrated as a percentage of fuel radius. Only required if porosity_model = partially_logged.

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Pellet depth sodium has infiltrated as a percentage of fuel radius. Only required if porosity_model = partially_logged.

  • X_Pu-1.0Coupled plutonium atom fraction.

    Default:-1.0

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

    Unit:(no unit assumed)

    Controllable:No

    Description:Coupled plutonium atom fraction.

  • X_Zr-1.0Coupled zirconium atom fraction.

    Default:-1.0

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

    Unit:(no unit assumed)

    Controllable:No

    Description:Coupled zirconium atom fraction.

  • 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

  • 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.

  • fuel_outer_radiusThe fuel outer radius. Only required if porosity_model = partially_logged.

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:The fuel outer radius. Only required if porosity_model = partially_logged.

  • initiating_porosityPorosity at which sodium infiltration begins. Only required if porosity_model = partially_logged.

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Porosity at which sodium infiltration begins. Only required if porosity_model = partially_logged.

  • porosityPorosity material property name. Required if porosity_model is not 'none'

    C++ Type:MaterialPropertyName

    Unit:(no unit assumed)

    Controllable:No

    Description:Porosity material property name. Required if porosity_model is not 'none'

  • porosity_factorFactor used when calculating porosity correction. If not overriden in the input file, this parameter is set to 2.5 when the porosity_model is fractional or partially_logged. For all other models, a default of 1.72 is used.

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Factor used when calculating porosity correction. If not overriden in the input file, this parameter is set to 2.5 when the porosity_model is fractional or partially_logged. For all other models, a default of 1.72 is used.

  • porosity_modelfractionalPorosity correction factor model. Choices are: none fractional power logged partially_logged

    Default:fractional

    C++ Type:MooseEnum

    Options:none, fractional, power, logged, partially_logged

    Controllable:No

    Description:Porosity correction factor model. Choices are: none fractional power logged partially_logged

  • sodium_logged_porositySodium logged porosity material property name. Required if porosity_model is 'logged'

    C++ Type:MaterialPropertyName

    Unit:(no unit assumed)

    Controllable:No

    Description:Sodium logged porosity material property name. Required if porosity_model is 'logged'

  • specific_heatSpecific heat value if spheat_model = 'constant'

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Specific heat value if spheat_model = 'constant'

  • specific_heat_funcSpecific heat function if spheat_model = 'function'

    C++ Type:FunctionName

    Unit:(no unit assumed)

    Controllable:No

    Description:Specific heat function if spheat_model = 'function'

  • spheat_modelsavageSpecific heat model. Choices are: karahan savage constant function

    Default:savage

    C++ Type:MooseEnum

    Options:karahan, savage, constant, function

    Controllable:No

    Description:Specific heat model. Choices are: karahan savage constant function

  • thcond_modellanlThermal conductivity model. Choices are: billone galloway lanl kim odaria_corrected function constant

    Default:lanl

    C++ Type:MooseEnum

    Options:billone, galloway, lanl, kim, odaria_corrected, function, constant

    Controllable:No

    Description:Thermal conductivity model. Choices are: billone galloway lanl kim odaria_corrected function constant

  • thermal_conductivityThermal conductivity value if thcond_model = 'constant'

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:Thermal conductivity value if thcond_model = 'constant'

  • thermal_conductivity_funcThermal conductivity function if thcond_model = 'function'

    C++ Type:FunctionName

    Unit:(no unit assumed)

    Controllable:No

    Description:Thermal conductivity function if thcond_model = 'function'

  • use_old_porosityFalseFlag to use old porosity

    Default:False

    C++ Type:bool

    Controllable:No

    Description:Flag to use old porosity

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_factor1The scaling factor on specific heat.

    Default:1

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:The scaling factor on specific heat.

  • thermal_conductivity_scale_factor1The scaling factor on thermal conductivity.

    Default:1

    C++ Type:double

    Unit:(no unit assumed)

    Controllable:No

    Description:The scaling factor on thermal conductivity.

Advanced: Scaling Factors Parameters

Input Files

References

  1. T H Bauer. In-Pile Measurement of the Thermal Conductivity of Irradiated Metallic Fuel. Nuclear Technology, 110(3):1–15, 1995.[BibTeX]
  2. M. C. Billone, Y. Y. Liu, E. E. Gruber, T. H. Hughes, and J. M. Kramer. Status of Fuel Element Modeling Codes for Metallic Fuels. In Proceedings American Nuclear Society International Conference on Reliable Fuels for Liquid Metal Reactors. Tucson, Arizona, September 7-11 1968.[BibTeX]
  3. J Galloway, C Unal, N Carlson, D Porter, and S Hayes. Modeling constituent redistribution in U–Pu–Zr metallic fuel using the advanced fuel performance code BISON. Nuclear Engineering and Design, 286:1–17, May 2015.[BibTeX]
  4. B. Giordanengo, N. Benazzi, J. Vinckel, J.G. Gasser, and L. Roubi. Thermal conductivity of liquid metals and metallic alloys. Journal of Non-Crystalline Solids, 250-252:377–383, 1999. URL: https://www.sciencedirect.com/science/article/pii/S0022309399002689, doi:10.1016/S0022-3093(99)00268-9.[BibTeX]
  5. G. L. Hofman, M. C. Billone, J. F. Koenig, J. M. Kramer, J. D. B. Lambert, L. Leibowitz, Y. Orechwa, D. R. Pedersen, D. L. Porter, H. Tsai, and A. E. Wright. Metallic fuels handbook. Technical Report ANL-NSE-3, Argonne National Laboratory, 2019.[BibTeX]
  6. Dawn E Janney and Cynthia A Papesch. FCRD Transmutation Fuels Handbook 2015. Technical Report INL/EXT-15-36520, Idaho National Laboratory, September 2015.[BibTeX]
  7. Aydin Karahan. Modeling of thermo-mechanical and irradiation behavior of metallic and oxide fuels for sodium fast reactors. PhD thesis, Massachusetts Institute of Technology, Jun 2009. URL: https://tinyurl.com/y72vqvbn.[BibTeX]
  8. Yeon Soo Kim, Tae Won Cho, and Dong-Seong Sohn. Thermal conductivities of actinides (U, Pu, Np, Cm, Am) and uranium-alloys (U-Zr, U-Pu-Zr and U-Pu-TRU-Zr). Journal of Nuclear Materials, 445(1-3):272–280, February 2014.[BibTeX]
  9. Yeon Soo Kim and G. L. Hofman. AAA Fuels Handbook. Technical Report, Argonne National Laboratory, 2003.[BibTeX]
  10. C Matthews and C Unal. Unpublished work. 2015.[BibTeX]
  11. Naoya Odaira and Yuji Arita. An estimation of the thermal properties of Pu-rich metallic fuel. Advances in Materials Science and Engineering, 2019:7263721:1–7, 2019. doi:10.1155/2019/7263721.[BibTeX]
  12. H. Savage. The heat content and specific heat of some metallic fast-reacdtor fuels containing plutonium. Journal of Nuclear Materials, 25:583–594, 2006. doi:10.1016/0022-3115(68)90168-2.[BibTeX]
  13. Yoichi Takahashi, Michio Yamawaki, and Kazutaka Yamamoto. Thermophysical properties of uranium-zirconium alloys. Journal of Nuclear Materials, 154(1):141–144, June 1988.[BibTeX]
  14. Y S Touloukian, R W Powell, C Y Ho, and P G Klemens. \textbf Thermophysical Properties of Matter - The TPRC Data Series. Volume 2. Thermal Conductivity - Nonmetallic Solids. Defense Technical Information Center, New York, NY, January 1971.[BibTeX]