Roadmap to Establish an Integrated TPBAR Performance Model

DE BURKES, DJ SENOR, G LONGONI AND JM JOHNSPacific Northwest National LaboratoryTritium Focus Group, Rochester, NY

25 October 2016 1

Objective

Briefly describe current tritium target technologyExplain observations and implications of current technologyBriefly describe transportation pathways within the current technologyDescribe the approach and goal

Methodically build a collection of mechanistic models that are effectively integratedExtrapolation of TPBAR performance and behavior to new conditions and designs

Provide some [very] early examples

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Current Tritium Target Technology

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5

ritiumroducingurnablebsorberod

( )

Each rod is12 feet long~ 3/8 inchdiameter

AluminideCoating on

Inner Surfaceof Cladding

Reactor GradeStainless Steel

Cladding

Nickel-PlatedZircaloy

Tritium Getter

LithiumAluminate

PelletsZircaloy

Liner

Not to Scale

Stainless Steel Cladding

Aluminum Coating

Zircaloy (zirconium alloy) Tritium Getter

Nickel Plating

- Similar to reactor fuel elements. Contains all TPBAR components

- Prevents diffusion of tritium through the stainless steel cladding into the reactor coolant. Also prevents hydrogen in the coolant from entering the TPBAR.

- Absorbs free tritium gas.

- Protects the tritium getter from oxidation.

Lithium Aluminate Pellets

Zircaloy Liner

- High-temperature ceramic material containing Lithium-6, the material that transmutes to tritium when a neutron is absorbed.

- Removes oxygen to improve getter performance.

During and after irradiation, nearly all the tritium is held tightly in the ceramic, the tritium getter, and the zircaloy liner until it is released by the extraction process. There is little or no free tritium gas.

Functions of TPBAR Components

Assemblies consist of24 rods suspended from a base plate.

TPBAR Observations and Implications

WBN1Cycle

QtyTPBARs

TPBARDesign

CycleDuration

2 32 LTA F97– S99

6 240 Production F03– S05

7 240 Production S05– F06

8 240 Production F06– S08

9 368 Mark9.2 S08– F09

10 240 Mark9.2 F09– S11

11 544 Mark9.2 S11– F12

12 544 Mark9.2 F12– S14

13 704 Mark9.2 S14– F15

14 704 Mark9.2 F15-

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In 2004, during Cycle 6, it was determined that TPBAR tritium permeation was higher than predicted by performance models

Predicted ≈ 0.5 Ci/TPBAR/cycleActual ≈ 4 Ci/TPBAR/cycle

Even 4 Ci/TPBAR/cycle represents only about 0.04% of the tritium produced Mechanisms responsible for differences between predictions and observations are not well characterized or understoodIncreasing the number of TPBARs per cycle increases tritium permeation

Approx. Prediction Before Testing

Approx. Prediction withTesting Results to Date

TPBAR Design Transport Pathways

Cycle 6 demonstrated original vision was inadequatePIE and ex-reactor testing led to revised vision that drove Mark 9.2 designSubsequent TPBAR irradiation and test reactor experiments suggested that Mark 9.2 model does not fully explain performance

Pellet speciation and burnupdependenciesCarbon transport and depositionTritium transport and distribution

Pellets

Liners

Getter

Cladding

Coolant

T2O

T2

T2

Pellets

Liners

Getter

End Plugs/Cladding

Coolant

T2

T2O

T2

T2OT2

Original Vision Mark 9.2 Vision

Tritium Transport within TPBAR

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Integrated TPBAR Performance Model Roadmap

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Permeation

Neutronics

VERAROSA

Grain SizeGeometryPorosity (volume)Porosity (type)Porosity (size)Porosity (distribution)EnrichmentPhaseGeometryTextureGeometryTextureGeometryComposition

MacroModels

ProcessInputs

MechanisticModels

TMED-3TMIST-3

C13 LURsC14 LURs

TMED-4C12 LURs

TMED-1C12 LURsTMIST-1

PIE

DiffusivityRelease rateSpeciationSwellingTemperatureFugacityOrientationGetter ratePartial pressureOxidation rateHydrogen uptakeSwellingFugacityOxidation rateHydrogen uptakeSwellingPermeation rateDeposition

Pellet Retention

COMSOLOpen Foam

Oxidation

PhaseOpen Foam

H3FR

DAKOTA

Gas Diffusion

Phase

Surface Reactions

Phase

Microstructural Evolution

FEM

Getter / Liner Absorption

Open Foam

Process Outputs

Thermal

COMSOL

C9 SurvTMIST-2

Solid Diffusion

Phase

Thermal Conductivity

Phase COMSOL

Structural

FEM

Phase

Pellets GettersLiners Cladding

Pellet Retention Model (benchmark)

Multi-Ionic Diffusion ModelImplemented ambipolar diffusion model described by Kirkaldy et al.Benchmarked numerical solutions for a glass coupleModel is capable of representing migration inversion due to slight changes in the initial composition of the glass couple

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Pellet Retention Model (application)

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Phase-field Simulations of Microstructure and Property Evolution in Metal Fuel

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GenerationofInitialMicrostructurefromexperimentalimagesandphase-fieldsimulations

Computeelastic-plasticdeformationusingIterationmethodandcrystalplasticitymodel

Radiationdamage Nucleation

Updatethemicrostructureandpropertiesbyevolvingphase-fieldfunctions

Microstructureevolution

Spatial Distributions of Intra-granular Gas Bubbles and Xe Concentration

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A Bubble density Xe atom number

Gas bubble radius Xe concentration

S. Hu et al., JNM 479 (2016) 202-215 & S. Hu et al., JNM 480 (2016) 323-331

density, per intragranular

Effective Thermal Conductivity with Inter-and Intra-granular Gas Bubbles

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KmWKmW

KTKT

nmdzdydxdzdydx

gas

bulk

//01.0//18

403443

30200200200

2

1

==

==

===´´

kk

Simulation conditions

S. Hu et al., JNM 462 (2015) 64-76

H3FR – H3 Framework

Understand measurement uncertaintiesDevelop mathematical representations of physical phenomena, where applicableDevelop tool suite for uncertainty quantification and detailed analysis and parameterizationSweep Permeation model with suite to inform modeling challenges compared to mathematical representationsDevelop physics-based mechanistic models to develop experimental needs to address challenges with Permeation model

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