Forming an overlayer on the ceramic coating with ductile metals is an alternative approach to in situ healing to compensate for cracks in the insulator layer. Current efforts for fabricating the two-layer
coating use pure V, V-alloys, and pure Fe, as shown in Figure 9. In these cases, only modest compatibil­ity with Li would be required for the insulator ceramics. Instead, the compatibility of V, V-alloys, and pure Fe with Li needs to be verified. It is also necessary to avoid shorting between the over­layer and the substrate. The Er2O3-V and Y2O3-V two-layer coatings on a V-alloy substrate fabricated using the EB-PVD process showed sufficient resis­tivity in Li.31

Recently, a mono-metallic thermal convection Li loop was constructed using V-4Cr-4Ti alloy. The two-layer coatings were tested in addition to uncoated V-alloy substrates at 700 °C for >2000 h in flowing Li. The tentative results showed that the corrosion loss, degradation of the coating, and mechanical property changes to the substrate were small.32 However, a full characterization remains to be completed.

Breeding blanket and associated systems in fusion power plants have to ensure tritium breeding self­sufficiency, show a sufficient power conversion effi­ciency, and withstand high neutron fluences.50 TBMs for ITER should be representative for such blanket modules (see Giancarli eta/.23 and Chuyanov eta/.24).

Among the technical objectives of ITER, it is specifi­cally stated that ‘‘ITER should test tritium breeding module concepts that would lead in a future reactor to tritium self-sufficiency and to the extraction of high-grade heat and electricity production.’’51 The main testing objectives shall be

• Validation of structural integrity theoretical pre­dictions under combined and relevant thermal, mechanical, and electromagnetic loads

• Validation of tritium breeding predictions

• Validation of tritium recovery process efficiency and T-inventories in blanket materials

• Validation of thermal predictions for strongly heterogeneous breeding blanket concepts with volumetric heat sources

• Demonstration of the integral performance of the blanket systems.

Table 1 also provides values for the ITERTBM loading parameters and tentative requirements for DEMO as a next step. It is seen that the neutron wall load in ITER is relatively small, which requires specific measures to make meaningful nuclear tests with TBMs. Four versions of a TBM are considered with specific objectives as follows:

1. H-phase and H-He-phase: focus on electromag­netic behavior;

2. D-phase: focus on thermal and neutronic behavior;

3. First D-T-phase: DEMO-relevant data acquisi­tion on neutronics, tritium production and man­agement, and thermomechanics;

4. Second D-T-phase: DEMO-relevant data acquisi­tion with high duty, long pulses with an integral TBM.

All ITER parties consider helium-cooled ceramic breeder (HCCB) blankets. This type of blanket requires beryllium as the neutron multiplier and ferritic-martensitic steel as the structural material. The ceramic breeder is a Li-based compound, either Li2TiO3 or Li4SiO4, and is used in pebble beds. A water-cooled ceramic breeder (WCCB) blanket is proposed for the Japanese TBM.

ITER prepares three horizontal ports for TBM testing, and two TBMs can be installed in one port. Though TBMs will be installed and tested as part of the ITER activities, each TBM will be developed under the responsibility of the distinct ITER party. Four of the ITER parties, China, European Union (EU), Japan, and Russian Federation (RF), have made TBM design proposals with solid breeder materials, while the United States and Korea propose to test submodules integrated into one of them. All ceramic breeder-based TBMs use pebble beds and ferritic — martensitic steel structures and He coolant at 8 MPa with inlet temperature of 300 °C and outlet up to 500 °C depending on the operating conditions. Only the Japanese party proposes a water-cooled concept in addition. Figure 10 shows the typical arrangement of a port cell in ITER to accommodate TBMs.

4.15.2.1 Ceramic Breeder Requirements

The development of any ceramic breeder blanket concept toward demonstration and realization of fusion power must ensure that the ceramic breeder material meets the following specific requirements:

• Though the ceramic breeder has no structural function in the blanket, the pebbles or pellets must withstand the stresses induced under reactor operating conditions (pressures, temperatures, temperature gradients and thermal shocks, irradiation-induced swelling, creep) without an excessive fragmentation, which might result in degradation of the heat transfer parameters and purge gas flow, up to end of life (EOL) peak burnup and displacement damage.

• Stability of the ceramic at the maximum operating temperature with regard to lithium transport (e. g., by evaporation or redistribution).

• Compatibility between the ceramic and the structural material in the reference purge gas con­ditions under neutron irradiation. Compatibility is one of the criteria defining the maximum inter­face temperature between ceramic breeder and the structural material.

• Sufficiently low tritium residence time to mini­mize the tritium inventory in blanket and auxiliary systems that determine source term in off-normal and accidental conditions.

• Activation as low as possible under neutron irradi­ation, including activation from impurities, so as to reduce the D-T fuel cycle back-end issues (includes the materials’ recycling aspects).

Structural materials for a fusion reactor are simply those that comprise a majority of the plant. They are not directly exposed to the plasma, but most are exposed to high doses of neutrons and electromag­netic radiation. Many of these materials are used in the reactor blanket where the tritium is bred by the nuclear reaction 6Li(n, a)3H. It is in the blanket and in the fuel reprocessing area that the structural materials are most likely to be exposed to tritium. The following sections review the structural materi­als that have been considered for fusion reactors.

4.16.3.2.1 Austenitic stainless steels

Austenitic stainless steels, particularly type 316, have been used extensively as a construction mate­rial for nuclear reactors (see Chapter 2.09, Proper­ties of Austenitic Steels for Nuclear Reactor Applications). The type 300-series austenitic stain­less steels (Fe-Cr—Ni) have relatively high nickel content (8-12 wt% for the 304 family of austenitic stainless steels and 10-14 wt% for 316 alloys), which is a detriment for fusion applications for several reasons including the susceptibility of nickel to acti­vation (induced radioactivity).88-90 The solubility and the diffusivity of gaseous hydrogen and its iso­topes through type 300-series austenitic stainless steels have been extensively studied and reviewed in San Marchi et a/.1 Higher strength austenitic stainless steels (such as the Fe-Cr-Ni-Mn alloys, which have not been widely considered for fusion applications) feature solubility and diffusivity that differ by a factor of about 2 compared to the type 300-series alloys.1 The so-called prime candidate alloy (PCA) is a variant of type 316 austenitic stain­less steel modified for fusion applications (although interestingly enough with higher nickel content); from a permeation perspective PCA is anticipated to behave in a manner essentially similar to conven­tional type 316 alloys.91

The Fe-Cr-Mn austenitic stainless steels have been considered as a substitute for the more com­mon grades of austenitic stainless steels since

they have only a nominal nickel content,88,89,90

although low-activation ferritic/martensitic steels have received more attention (see subsequent sec­tion). Alloys that have been considered typically contain both chromium and Mn in the range 10-20 wt%, often with small amounts of other alloying elements (Sahin and Uebeyli90 provides a list of a number of alloys that have been explored for fusion applications). Unlike the Fe-Cr-Ni austenitic stainless steels, there are few reports of transport properties for the Fe-Cr-Mn austenitic alloys; data for oxidized Fe-16Cr-16Mn are reported in Gro­mov and Kovneristyi.92

Austenitic stainless steels can contain ferritic phases in the form of residual ferrite from alloy production, ferrite in welds formed during solidifica­tion, and in some cases, strain-induced martensite from deformation processing. The ferritic phases can result in a fast pathway for the transport of hydrogen and its isotopes at a relatively low temper­ature because the ferritic phases have a much higher diffusivity for hydrogen and its isotopes than austen — ite.93,94 In the absence of ferritic second phases, how­ever, hydrogen transport in austenitic stainless steels is independent of whether the material is annealed or heavily cold-worked95-97 and relatively insensitive to composition for the type 300-series alloys.1

Reported values of hydrogen diffusivity in aus­tenitic stainless steels are less consistent than per­meability as a consequence of surface effects and trapping, as mentioned earlier and elsewhere.1 Figure 10 shows the reported diffusivity of hydro­gen from a number of studies in which special pre­cautions were taken to control surface conditions. The activation energy for diffusion is relatively large for austenitic stainless steels (ED = 49.3 kJ mol-1), and thus the diffusivity is sensitive to temperature, approaching the values of the ferritic steels at very high temperatures (>1000K), while being many orders of magnitude lower at room temperature.

The exceptionally low diffusivity of hydrogen near room temperature results in austenitic stainless steels having significantly lower permeability of hydrogen than other structural steels.

The solubility of hydrogen and its isotopes in the type 300-series austenitic stainless steels is high rela­tive to most structural materials. Compilation of data from gas permeation studies shows that most studies are consistent with one another,93,95,96 while studies that considered a variety of alloys within this class show that the solubility of hydrogen is essentially the same for a wide range of type 300-series austenitic stainless.93,95,96 The heat of solution of hydrogen in austenitic stainless steels is relatively low (AHs = 6.9 kJ mol-1), and thus the equilibrium content of hydro­gen in the metal remains high even at room tempera­ture. The solubility of hydrogen and its isotopes is plotted in Figure 11, while Table 1 lists the recom­mended transport properties for austenitic stainless steels (and a number of other metals and alloys).

The primary traps in type 300-series austenitic stainless steels are dislocations with relatively low binding energy 10kJ mol-. Therefore, the

amount of trapped hydrogen (in the absence of irra­diation and implantation damage) is relatively low at elevated temperatures. Moreover, due to the high sol­ubility of hydrogen and its isotopes in austenitic
stainless steels, the density of trapping sites would need to be impractically high to measurably increase the inventory of hydrogen and its isotopes in the metal.20 For these reasons, trapping from a microstruc­tural origin is anticipated to have little, if any, impact on the transport and inventory of hydrogen and its isotopes in austenitic stainless steels at temperatures greater than ambient.

The recombination-rate constant (kr) for austenitic stainless steels near ambient temperature is typically less than about 10-9 m4 s-1 per mol of H2.113 At higher temperatures (^700 K), the value varies between ~10-5 and 10-7 m4 s 1 per mol of H2, depending on the surface condition.80,113-116

The simulation of disruptions (<20 MJ m~2, t = 5 ms) on VPS-W and W alloys irradiated to a dose of 0.2 dpa at 350 and 750 °C resulted in heavy melting of the material241 but yielded no measurable degra­dation by neutron irradiation. This is understandable because the decrease in thermal conductivity, which is the most important material parameter for melting experiments, is almost negligible for the given irradia­tion conditions.217 Because of the continuous modifi­cation of the material composition by transmutation described above, with increasing levels of Re and Os, the thermal conductivity and the related melting threshold power density is expected to decrease steadily.

In further investigations applying ELM-like loads on pure W and W-La2O3 irradiated to 0.6 dpa at 200 °C, the crack pattern generated after irradiation exhibited an increased crack density in combination with a smaller crack width. Furthermore, in W-0.2% Re SC that was exposed to the same neutron irradia­tion conditions and exhibited no crack formation in the nonirradiated state, cracks were formed along the crystallographic planes (see Figure 9).177 The effect was more obvious in the results for the SC material, but in both cases the observed degradation was a result of mechanical property changes and a rise of the DBTT in particular. This would indicate a rise in the threshold temperature for crack forma­tion (see also Section 4.17.4.3.3), which has not been verified yet. For the evaluation of the material’s performance in DEMO, both higher transmutation rates and significantly higher temperatures that are expected to stimulate defect recovery have to be taken into account.

4.17.4.3.1 Thermal fatigue on irradiated W components

Information on the thermal fatigue resistance of W components is limited to the experience obtained in two irradiation campaigns for ITER which reached neutron doses of 0.15 and 0.6 dpa at 200 °C. Refer­ence and irradiated actively cooled mock-ups with W—1% La2O3 as the PFM were exposed to 1000 cyclic steady state heat loads at power densities up to 18 MW m~2 213,216,217

The results obtained indicate that at these neutron fluences the material changes occurring in tungsten do not have any significant influence on the component’s performance. However, mock-ups based on the macro­brush design experience a degradation ofthe maximum achievable power density from 18 to 10MWm~2, which is related to neutron embrittlement and subsequent cracking failure of the Cu-heat sink mate­rial. In contrast, monoblock mock-ups show identical high-level performance before and after irradiation, which makes it the favored design for ITER.

Despite these positive results, based on the irradiation-induced mechanical property changes outlined above, the use of tungsten in any highly stressed component at low temperatures <500 °C

has to be avoided.108

As was pointed out in the previous section, it is impor­tant to have accurate knowledge of a target’s surface composition to predict its erosion rate. A small impu­rity concentration contained within the incident plasma can drastically alter the surface composition of a target subjected to bombardment by the impure plasma. Oxygen impurities in the plasma, either from ionization of the residual gas, or due to erosion from some other surface, will readily lead to the formation of beryllium oxide on the surface of a beryllium target. Depending on the arrival rate of oxygen to the surface compared to the erosion rate of oxygen off the surface, one can end up measuring the sputtering rate of a clean beryllium surface or a beryllium oxide surface. Careful control of the residual gas pressure in ion beam sput­tering experiments55 has documented this effect. Unfortunately, it is not always so easy to control the impurity content of an incident plasma.

In the case of a magnetic confinement device composed of groups of different plasma-facing mate­rial surfaces, erosion from a surface in one location of the device can result in the transport of impurities to other surfaces throughout the device. Mixed- material surfaces are the result. To first order, a mixed-material surface will affect the sputtering of the original surface material in two ways. The first is rather straightforward, and is true even for materials which do not form chemical bonds, in that the surface concentration of the original material is reduced thereby reducing its sputtering rate. The second effect changing the sputtering from the surface results from changes in the chemical bonding on the surface, which can either increase, or decrease the binding energy of the original material. If the chemical bonds increase the binding energy, the sputtering rate will decrease. If the bonding acts to reduce the surface binding energy, the sputtering rate will increase (assuming the change in surface concentration does not dominate this effect). A recent review of mixed materials62 provides some background information on the fundamental aspects of general mixed-material behavior.

If a plasma incident on a beryllium target contains sufficient condensable, nonrecycling impurities (such as carbon), it will affect the sputtering rate of the beryllium. This effect was first referred to as ‘carbon poisoning.’5,9,63 A simple particle balance model has been used to adequately explain the results for formation of mixed carbon-containing layers on beryllium at low surface temperature.64 However, as the target temperature increases, additional chemical effects, such as carbide formation, have to be included in the model.

An interesting change occurs when the bombard­ing species is a mixture of carbon and oxygen.

Measurements of the chemical composition of a beryllium surface bombarded with a CO+ ion beam showed almost exclusive bonding of the oxygen to the beryllium in the implantation zone.65,66 The formation of BeO on the surface left the carbon atoms easily chemically eroded. The amount of oxy­gen present in the incident particle flux plays a strong role in the final chemical state of the surface atoms and their erosion behavior.

The inverse experiment, beryllium-containing plasma incident on a carbon surface, has also been investigated.67-69 In the case of beryllium impurities in the plasma, a much more accurate measurement of the impurity concentration was possible. Contrary to the carbon in beryllium experiments, a simple particle balance model could not account for the amount of beryllium remaining on the surface after the plasma exposure. Clearly, the inclusion of chemi­cal effects on the surface needs to be taken into account to interpret the results.

Beryllium carbide (Be2C) was observed to form on the surface of carbon samples exposed to beryllium — containing deuterium plasma even during bombard­ment at low surface temperature. Carbide formation will also act to increase the binding of beryllium atoms to the surface and decrease the binding of carbon atoms. This effect will result in an increase in the concentration of beryllium on the surface compared to a simple particle balance equation and must be included to understand the evolution of the surface. In addition, the formation of the carbide was correlated with the decrease of carbon chemical ero — sion70 (see Section 4.19.3.3.1 for more discussion of the chemical erosion of the beryllium-carbon system).

PH copper alloys are heat-treatable alloys. The high strength of PH copper alloys is attributed to the uniform distribution of fine precipitates of second — phase particles in the copper matrix. PH copper alloys are produced by conventional solution treatment

and aging treatment. Solution treatment produces a homogeneous solid solution by the heating of an alloy to a sufficiently high temperature to dissolve all solutes. The alloy is then quenched to a lower temperature to create a supersaturated condition. A subsequent aging treatment heats the alloy to an intermediate temperature below the solvus tem­perature, to precipitate fine second-phase particles. Precipitates not only give rise to high strength, but also reduce the solute content in the matrix, main­taining good conductivity. The strength of a PH alloy depends on particle size, particle shape, volume frac­tion, particle distribution, and the nature of the inter­phase boundary.7 Despite their ability to develop significant strength, PH copper alloys may be soft­ened substantially as a result of precipitation coars­ening (overaging) at intermediate to high service temperatures or because of recrystallization during brazing or diffusion bonding. Therefore, heat treat­ment and thermal processing histories can have a large influence on the strength and conductivity of this class of alloys.

A number of commercial PH copper alloys have been investigated for applications in fusion design, for example, CuCrZr, CuNiBe, and CuNiSi.

The applied fracture model12 defines a conditional probability of fracture assuming that the distribution of flaws in the material follows a statistical distribu­tion. The conditional probability term takes into account the possibility of void formation (blunting of a crack initiator) and the crack arrest-propagation event (Figure 4). The fracture event is controlled in the model by assessing the criticality of a single crack initiator from the weakest link principle. The basic elements of the methodology — the scatter definition and the specimen size correction6,7 — are based on this cleavage fracture model. It is assumed that the material has uniform macroscopic properties and

Pr{I} = Probability of cleavage initiation Pr{V} = Probability of void initiation Pr{O} = Probability of ‘no event’

Pr{I/O} = Conditional probability of cleavage initiation (no prior void initiation)

Pr{V/O} = Conditional probability of void initiation (no prior cleavage initiation)

Pr{P/I} = Conditional probability of propagation (in the event of cleavage initiation)

Pr{A/I} = Conditional probability of arrest (in the event of cleavage initiation)

Figure 4 Definition of the conditional probability of cleavage fracture. Reproduced from Wallin, K.; Laukkanen, A. Eng. Fract. Mech. 2008, 75(11), 3367-3377.

that no global interaction exists between the crack initiators. An overview (basic equations) of the cleav­age fracture model (also called the Wallin, Saario, Torronen (WST) model) is described next.

The conditional probability of cleavage initiation, Pr{I/O}, is expressed as a product of the probability of having a cleavage initiation and that of not having a void initiation as follows:

Pr{I/O} = Pr{I}(1 — Pr{V/O}) [7]

Equation [7] can be approximated as:

Pr{I/O} « Pr{I}(1 — Pr{I}) [8]

The WST model expresses Pr{I/O} as the product of the particle fracture and nonfracture probabilities so as to take into account the previously broken parti­cles which do not contribute to the cleavage process as follows:

The probability of particle fracture is described by a Weibull-type dependence accounting for particle size (d) and particle stress (spart) as follows:

Pfr = 1 — exp

where dN and s0 are scaling factors.

The particle size distribution, P{d}, is given by eqn [12], which describes the size distribution with two parameters, the average particle size (d) and the shape factor n. For pressure vessel steels, the shape factor appears generally to be in the range 4-6.

P{d}

A detailed description of the WST model is given in Wallin et at}2 and Wallin and Laukkanen.1 The recent numerical validation ofthe model is presented in Wallin and Laukkanen.13

define the curves for the mean and lower bound fracture toughness. If the dataset covers several test temperatures, T0 is found as a solution of equations giving the maximum likelihood estimate to this value. Other than the LEFM testing standards for fracture characterization, there is no specified limit for the minimum specimen size. However, the number of specimens to be tested has to be at least six and generally increases when the specimen size is decreased in order to produce a statistically accept­able confidence level for the estimate. The method also includes a censoring procedure that allows the use of adjusted invalid test data, which contain statis­tically useful information.

The probability of cleavage fracture initiation is described as a three-parameter Weibull distribution, which defines the relationship between the cumula­tive failure probability (Pf) and the fracture toughness level before or at KI as follows:

Pf (KJc < K) = 1 — exp where Kmin is the theoretical lower bound fracture toughness, set normally to 20 MPa Vm for steels with yield strength from 275 to 825 MPa, and K0 is the scale parameter corresponding to Pf = 63.2%. The Weibull exponent is assumed to have a constant value equal to 4 based on theoretical and experimental arguments.7

The measuring capacity (maximum KJc) of a spec­imen depends on its dimensions (ligament size) and the material yield strength as follows:

Eb0s ys

Kjc(limit) = M(1 — n2)

where E is the modulus of elasticity, n is Poisson’s coefficient, b0 is the initial specimen ligament length (specimen width minus the initial crack depth, W — a0), M is the constraint value (usually set equal
to 30), and sys is the material yield strength at the test temperature. Toughness values exceeding this mea­suring capacity require censoring and are set at the level of maximum Kjc.

The expression for predicting the specimen size effect is based on the cleavage fracture model. The fracture toughness (Кед) corresponding to the desired specimen thickness or crack front length (Bx) is obtained from the values of Kc(o) and B0, respectively, as follows:

Kjc(x) = Kmin + (Kjc(0) — Kmin) [15]

When analyzing measured data according to ASTM E 1921, the size adjustment is normally made to 1 in. (Bx = 1 in. or 25.4 mm). Note that the influence of side grooves on the specimen thickness is ignored. After the size adjustment is made for each Kjc mea­surement, the data for different size specimens can be described as one population following the same Master Curve form and scatter as shown in Figure 5. The aforementioned formula applies in the transi­tion range, and it is not necessary to perform the size conversion at temperatures below (T0 — 50 °C), because the size effect diminishes (see the fracture toughness curve 50 MPa Vm shown in Figure 6).

The procedure for estimating the maximum like­lihood solution for T0 from data measured at various temperatures was published in 199514 and added to the second and later revisions of ASTM E 1921. The value of T0 is solved iteratively from the fol­lowing equation, which includes a factor d for data censoring:

di exp{0.019[T, — T0]}

11 + 77exp{0.019[Tj — T0]}

ys (J) — Kmin)4exp{0.019[Ti — T0]} 1=1 (11 + 77exp{0.019[Ti — T0]})5

B (mm)

where is the size-adjusted fracture toughness measured at temperature T) and d, is the censoring coefficient: d, = 1 if the KjcW datum is valid (less than the limit determined from eqn [14]) or d= 0 if the KJc(i) datum is not valid but may be included as censored data.

When the value of T0 has been solved, the fracture toughness curves for specific levels of fracture prob­ability are obtained from the following equations for probability level 0.xx

KJc(0.xx) = 20 +

{11 + 77 exp[0.019(T — T>)]} [17]

The mean curve (50% failure probability) for

25.4 mm specimen thickness is obtained as a function of temperature from

KJc(mean)1 T = 30 + 70 exp[°.°19(T — T0)] [18]

4.15.4.4.1 Thermal conductivity

There are several advanced models to describe the thermal conductivity of pebble beds, which take into account the relevant parameters such as the thermal conductivity of the pebble material ks as a function of temperature T, the thermal conductivities of the surrounding gas kg as a function of temperature Tand pressure p, the pebble diameter d, packing factor g, contact surface ratio pk2, and several other second — order effect parameters. In the following section the Schlunder Bauer Zehner model (SBZ model)114 is used to demonstrate the influence of some para­meters. Figure 23 shows ks as a function of tempera­ture for both Li4SiO4 and Li2TiO3 and kg for helium and other gases at 0.1 MPa.99 For most ceramic breeder materials, ks decreases first with increasing T, reaches at high temperatures a plateau, or increases again slightly; for details, see Abou-Sena eta/.116 The helium conductivity increases strongly with increasing T. Figure 24(a) and 24(b) from Reimann et a/.99 shows the influence of Tand pk2 on the pebble-bed conduc­tivity k of an Li4SiO4 pebble bed with mean diameter of d = 0.4 mm and g = 64%. For a noncompressed bed, pk = 0, k increases moderately with T because kg increases with T. For a moderately compressed bed,

pk2 = 0.02, k is larger than that for pk2 = 0, but the temperature dependence is quite small.

The thermal conductivity of noncompressed Li4SiO4 and Li2TiO3 pebble beds was measured by several authors. Figure 25 from Enoeda eta/.86 shows that there is a good agreement among different authors. The Li4SiO4 pebble-bed data are best fitted with a correlation established by Dalle Donne204; the Li2TiO3 data were well predicted by the SBZ model using a value pk2 = 0.0049.117 Li2TiO3 pebble-bed data for 2 mm pebbles from Abou-Sena116 are char­acterized by the tendency of a decrease in k with increasing T

Results for noncompressed beds including further ceramic breeder pebble materials were summarized by Abou-Sena eta/.116: k should increase with increas­ing ks in the sequence Li2ZrO3, Li4SiO4, Li2TiO3, Li2O for equal values of the other parameters. Because the other parameters differed, this tendency was masked.

For compressed pebble beds, the SBZ model con­tains the parameter pk, which is a priori not known. If the pebble-bed strain is measured, it is easier to use this quantity as the relevant parameter. Figures 26(a) and 26(b) from Reimann and Hermsmeyer99 show results for Li4SiO4 and Li2TiO3 pebble beds, differ­ent gas conditions, and strain values e. For noncom­pressed beds, pk = 0, the measured data agree fairly well with SBZ model predictions. With increasing strain, k increases; however, only very moderately compared with beryllium pebble bed. Even for a strain of about 4%, obtained in air at 800 °C because

of significant thermal creep, k is only increased by about 20% for both types of pebble beds. For helium atmosphere, this difference becomes even smaller.

Figure 26(b) also contains some results for binary Japanese Li2TiO3 pebble beds (0.2 and 2 mm peb­bles, g = 81.5%) in air atmosphere at ambient tem­perature. Compared with the monodisperse pebble bed with d = 2 mm pebbles and g = 64.3%, k is increased by a factor of 2. For blanket relevant con­ditions, this factor reduces to ~1.3 for T = 600 °C and helium atmosphere.

Experiments with compressed Li2TiO3 pebble beds (d = 2 mm, g = 65-67%) were also performed by Tanigawa eta/.113 For a strain of about 1%, T = 600 ° C, and helium at 0.1 MPa, k increased only by 3% compared with the noncompressed pebble bed. After annealing the pebble bed at 700 °C without com­pression for 1 day, larger bed strains (factor 2) were obtained in the subsequent cycles and with this an additional increase in conductivity.

4.15.4.4.2 Heat transfer

Close to the wall, the pebble packing differs signifi­cantly from that in the bulk, as demonstrated in Figure 17. For noncompressed pebbles, the void fraction at the wall surface is close to 100%. Heat transfer characteristics in the wall zone are, therefore, different from those in the bulk. This fact is taken into account by using the heat transfer coefficient h,
which is defined with the temperature difference (Tew-Tw), where Tew is obtained by extrapolating the bulk pebble-bed thermal conductivity k up to the wall, and Tw is the undisturbed wall temperature. In measurements, (T;w-TO is very small and is sensitively dependent on extrapolated temperature profiles. Accurate measurements are, therefore, extremely difficult, and the discrepancies in experi­mental data are significant. The smaller the pebble diameter, the thinner the wall zone, and with this the difficulty to obtain accurate data increases. Again, different models exist to predict h exist, which have been validated in better suited experiments.

Figure 27 shows h = f(T) for Li4SiO4 and Li2TiO3 pebble beds for noncompressed beds calcu­lated with the model from Yagi and Kunii118: the strong increase of h with decreasing pebble diameter d is obvious. With progressing compression, the wall

contact surfaces increase and with this h. Again, this increase is expected to be much smaller than that in beryllium pebble beds because of the small thermal conductivity of ceramic breeder materials.

At present, mechanistic models are developed taking into account the pebble arrangements close to the wall as determined by tomography101,105,106,199 or by discrete-element modeling (DEM), outlined later. A typical example is the work of Gan eta/.133

In this chapter, the materials for the blanket region have been reviewed, and their permeation para­meters described. In this section, the need for barriers is evaluated. For example, consider the tritium migra­tion processes that might be associated with the liq­uid Pb-17Li systems. In a set of experiments, Maeda et at231 found the solubility of hydrogen in Pb-17Li to be on the order of 10-7 Pa-1/2 atom fraction (^10-6 mol H2 m-3 MPa-1/2). As tritium is pro­duced in the blanket, some of the tritium will be in solution and some will be in the vapor phase. It is the tritium in the vapor phase that will drive the perme­ation through the metal used to contain the liquid. For an 800 MW fusion reactor, Maeda et al. state that 1.5 MCi (150 g) of tritium will have to be bred each day. That means that 1.5 MCi of tritium will be flowing around in stainless steel or similar metal tubes at a temperature >600 K. To estimate tritium permeation in a generic 800 MW plant, we will scale the design parameters proposed by Farabolini eta/.232 for a much larger plant. Approximately 10 000 m2 of surface area will be needed for the tubes passing through the liquid Pb-17Li to extract the heat. We will assume that a sufficient number of detritia — tion cycles per day are performed to keep the amount of tritium in the liquid breeder at 10% of the 150 g listed above. Scaling to 800 MW, the amount of Pb-17Li will be ~-750 000 kg. This leads to a molar fraction of tritium equal to 6.7 x 10-7. Using the solubility of Maeda et a/.231 for Pb-17Li yields a tritium pressure of ^45 Pa. Assuming the contain­ment metal to be 1 mm of MANET with an alumi­nized coating, a temperature of 700 K and an effective PRF of 1000, a permeation rate of 2.7 x 10-10 T2 mols m-2 s-1 will occur.29,118,122,127,128 With the 10 000 m2 surface area, the daily permeation rate is 0.23 mol or 1.4g of tritium per day. To prevent subsequent permeation through the steam generator tube walls, a tritium clean up unit will have to be applied to this helium loop. Because the steam gen­erator tube wall must be thin to permit effective heat transfer, the tritium cleanup loop will have to be extremely effective to limit release of tritium to the environment. This calculation was performed simply to show the extreme need for barriers in the blanket region of fusion reactors. Even with an active detritiation unit and a barrier providing a PRF of 1000, 1.4 g or 14 000 Ci of tritium end up in the cooling system each day. The situation is not much better for the solid breeders. The same amount of tritium will obviously be required for that system. To minimize the tritium inventory in the ceramic breeder materials, temperatures equal to or greater than that of the liquid breeder will be maintained. The tritium will be released into the helium coolant as elemental tritium (T2) and tritiated water (T2O); the relative concentrations of these forms depend on the type of ceramic breeder. The steel or similar containment metal will be exposed to nontrivial pres­sures of tritium gas. We can conclude that effective barriers are needed for the blanket. It is difficult to imagine that, even with double-walled designs, fusion reactor facilities can meet radioactive release requirements for tritium without an effective barrier.

4.16.4 Summary

In this chapter, we have presented tritium permeation characteristics and parameters for materials used in fusion reactors. These materials have included those used to face the plasma in the main chamber as well as materials used as structural materials for the main chamber and blanket. A description of the conditions that exist in those locations has also been provided. Reasons were given why direct contact of the plasma with the plasma facing materials would not lead to sizeable quantities of tritium being lost to the envi­ronment or to the cooling system. The same was not concluded for the blanket region. The need for per­meation barriers there was stressed. A number of materials were listed as possible tritium barriers. These materials included a few metals with some­what reduced permeation and a larger number of ceramics with very low tritium permeability. Due to the difficulty of lining large chambers with bulk ceramics, much of the tritium permeation barrier development around the world has been dedicated to thin ceramic layers on metal surfaces. Unfortu­nately, radiation testing219-222 of these materials has shown that these thin layers lose their ability to limit tritium permeation during exposure to radiation damage. It was suggested, but not proved, that this increase in permeation was due to cracking of the ceramics or the increase in defects.

To make this chapter more useful to the reader with a need for permeation data, tables and plots of the permeation coefficients are provided. The coefficients for metals are presented in Table 1 and Figure 21 and for the ceramics in Table 2 and Figure 22.

In summary, effective permeation barriers are needed for fusion reactors to prevent the release of sizeable quantities of tritium. Fusion is touted as a clean form of energy, and releasing tritium into the environment will eliminate any political advantage that fusion has over fission. Research is needed to find ways to place radiation-resistant ceramic permeation barriers on top of structural metals. The fusion com­munity must find a way to make this happen.

As seen in Table 1, the first wall must handle high plasma surface heat fluxes under normal operation and volumetric heat loadings due to the penetrating neutron and electromagnetic radiation. Surface heat loading is dependent on line-of-sight distance from the plasma and can be as high as several MW m— . These surface and volumetric heat loadings will induce temperature gradients on the PFMs and corresponding thermal stress, and stresses at the interface between the PFM and the heat sink. For example, if one assumes the ideal case of a 2.5 cm thick, infinitely wide graphite plate that is perfectly bonded to a 50 °C copper heat sink, the thermal stress at the graphite-copper interface for a heat flux of 5 MW m—2 has been shown to be 200 MPa.3 The ability of the PFC to withstand this heat flux and thermal stress will depend both on the material prop­erties and the component design. The two most obvi­ous design parameters are the thickness of the PFM and how it is attached to the heat sink. The critical material property of thermal conductivity, which to a great extent can be engineered to optimize con­duction to the heat sink, is a strong function of temperature. As discussed later in Section 4.18.3, this property and other performance properties such as elastic modulus and strength are also highly depen­dent on radiation-induced displacement damage. A typical design for a fusion reactor divertor is shown in Figure 2. In this design, the heat flux strikes the surface of CFC composite blocks and the heat flows into a water-cooled copper tube that has been brazed inside the block. The PFC is bolted to a stain­less steel support structure. This configuration ofPFC is called the monoblock structure, as compared to the flat plate and saddle types inset into Figure 2.

To provide a quantitative comparison of candidate PFMs, a number of figures of merit (FoMs) have been derived, one of which may be written as follows:

K Sy

a E(1 — v)

where K is the thermal conductivity, sy the yield strength, a the thermal expansion coefficient, E the Young’s modulus, and n the Poisson’s ratio. High values of FoMth provide guidance to superior
performing candidate materials. Figure 3 shows a comparison of the three primary candidate PFMs: graphite, beryllium, and tungsten. Graphite has been further broken down into fine and coarse-grained (Poco and H451 respectively) graphites, and a high-quality one-dimensional (1D) fiber architecture (MKC-1PH) and a balanced weave 3D fiber architecture (FMI-222) CFC. In Figure 3, it has been assumed that the high thermal conductivity direction for the 1D CFC is oriented at a normal angle to the surface of the PFC. From Figure 3, it is apparent that the graphites and graphite fiber composites, which possess higher strength and thermal conductivity, exhibit thermal FoMs considerably higher than either beryllium or tungsten. Thus, strictly from a thermal stress point of view, high-conductivity and high-strength graphite materials would be considered superior under normal operating conditions for fusion PFCs.