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Figure 11. Detail of the meshes used in the simulations. To assess the variation of the previous quantities with the poloidal location, FMESE tallies were defined for a thin slice between y = 10 cm and y = 11 cm. As shown in Figure 11 the mesh elements are very small (1.7 cm x 1cm x 1.7 cm), to provide an accurate estimate of the fluxes and loads at each of the 60 positions described in Figure 9. Nevertheless, smal deviations between the results presented in Table 1 and the ones obtained with the FMESF tallies are always to be expected, as the elements of the FMESH tallies have a differen volume compared to the F4 tally cells. To keep the statistical errors as low as possible witl such small elements, 5 x 101° particles were run in each simulation.

Figure 11 Detail of the meshes used in the simulations. To assess the variation of the previous quantities with the poloidal location, FMESE tallies were defined for a thin slice between y = 10 cm and y = 11 cm. As shown in Figure 11 the mesh elements are very small (1.7 cm x 1cm x 1.7 cm), to provide an accurate estimate of the fluxes and loads at each of the 60 positions described in Figure 9. Nevertheless, smal deviations between the results presented in Table 1 and the ones obtained with the FMESF tallies are always to be expected, as the elements of the FMESH tallies have a differen volume compared to the F4 tally cells. To keep the statistical errors as low as possible witl such small elements, 5 x 101° particles were run in each simulation.

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results for the full DSC and its impact on the neutron and gamma fluxes in the VV. A work focused on an early design of the divertor survey visible high-resolution spectrometer has also been published, which aimed mainly to assess the loads in the first mirrors and the impact of the number of doglegs in the EP ducts on the radiation streaming to the port cells [25]. The objective now is to extend those simulations to more complex geometries and to include additional diagnostics that were not studied before. Figure 1. Representation of one DEMO sector and foreseen locations for diagnostics, represented in red (for visualization only—diagnostics will be distributed in different sectors). DSC: Diagnostics Slim Cassette (red). EP: Equatorial Port (red). UP: Upper Port (red). BB: Breeding Blanket (blue—inboard and pink—outboard). DIV: Divertor (red). VV: Vacuum Vessel (green).
results for the full DSC and its impact on the neutron and gamma fluxes in the VV. A work focused on an early design of the divertor survey visible high-resolution spectrometer has also been published, which aimed mainly to assess the loads in the first mirrors and the impact of the number of doglegs in the EP ducts on the radiation streaming to the port cells [25]. The objective now is to extend those simulations to more complex geometries and to include additional diagnostics that were not studied before. Figure 1. Representation of one DEMO sector and foreseen locations for diagnostics, represented in red (for visualization only—diagnostics will be distributed in different sectors). DSC: Diagnostics Slim Cassette (red). EP: Equatorial Port (red). UP: Upper Port (red). BB: Breeding Blanket (blue—inboard and pink—outboard). DIV: Divertor (red). VV: Vacuum Vessel (green).
Figure 2. DEMO MCNP reference model used for the simulation of in-vessel diagnostics (excluding port diagnostics). Left: Plane y = 10.5 cm. Right: Plane z = 0.
Figure 2. DEMO MCNP reference model used for the simulation of in-vessel diagnostics (excluding port diagnostics). Left: Plane y = 10.5 cm. Right: Plane z = 0.
Figure 3. Reference model used in the simulations of the ex-vessel Faraday sensors. The reference model used for ex-vessel diagnostics (Faraday sensors) is represented in Figure 3 [42]. This is a smaller model when compared to the previous one (11.25° instead of 22.5°), containing a semi-heterogeneous representation of the WCLL blanket which provides good accuracy for ex-vessel simulations while decreasing the simulation times [43].
Figure 3. Reference model used in the simulations of the ex-vessel Faraday sensors. The reference model used for ex-vessel diagnostics (Faraday sensors) is represented in Figure 3 [42]. This is a smaller model when compared to the previous one (11.25° instead of 22.5°), containing a semi-heterogeneous representation of the WCLL blanket which provides good accuracy for ex-vessel simulations while decreasing the simulation times [43].
Figure 4. MCNP reference model used in the simulations of equatorial port diagnostics. Left: Plane y = 28 cm. Right: Plane z = 10 cm. The reference MCNP model used for equatorial port diagnostics is illustrated in Figure 4 [44]. The model features an upper port, equatorial limiter port and lower pumping port and includes layered representations of two HCPB BBs and one layered representation of the WCLL BB, as described with more detail in reference [45]. For these studies, the WCLL option was chosen for the BB (MCNP universe u = 882). All the remaining geometry definitions were kept unchanged except for the equatorial port (universe u = 210 in the MCNP model) and part of the bioshield and cryostat (u = 900), which were adapted to include the models created for the equatorial port, defined in Section 3.3.
Figure 4. MCNP reference model used in the simulations of equatorial port diagnostics. Left: Plane y = 28 cm. Right: Plane z = 10 cm. The reference MCNP model used for equatorial port diagnostics is illustrated in Figure 4 [44]. The model features an upper port, equatorial limiter port and lower pumping port and includes layered representations of two HCPB BBs and one layered representation of the WCLL BB, as described with more detail in reference [45]. For these studies, the WCLL option was chosen for the BB (MCNP universe u = 882). All the remaining geometry definitions were kept unchanged except for the equatorial port (universe u = 210 in the MCNP model) and part of the bioshield and cryostat (u = 900), which were adapted to include the models created for the equatorial port, defined in Section 3.3.
Figure 5. Detail of the MCNP reference model used in the simulations of equatorial port diagnostics, showing the EP and the bioshield plug. The equatorial port of the reference model is shown with more detail in Figure 5. The bioshield is made of concrete and has a thickness of 2 m, while the bioshield plug is a 50 cm thick slab of heavy concrete with a density of 3.6 g/cm®. As there were no CAD models available with details of the DEMO bioshield plugs at the start of this work, the design available in the reference neutronics model was used, with the addition of the diagnostic duct openings in the bioshield plug.
Figure 5. Detail of the MCNP reference model used in the simulations of equatorial port diagnostics, showing the EP and the bioshield plug. The equatorial port of the reference model is shown with more detail in Figure 5. The bioshield is made of concrete and has a thickness of 2 m, while the bioshield plug is a 50 cm thick slab of heavy concrete with a density of 3.6 g/cm®. As there were no CAD models available with details of the DEMO bioshield plugs at the start of this work, the design available in the reference neutronics model was used, with the addition of the diagnostic duct openings in the bioshield plug.
Figure 6. Weight windows used in the simulations. Left: Faraday sensors, installed on the outer layer of the VV. Right: EP diagnostics. Common to all cases studied in this paper was the use of weight windows for variance reduction, to reduce the statistical errors of the simulation results. This is a crucial point when the aim is to calculate fluxes or loads at large distances from the plasma, as is the case with most simulations presented here. Two examples are provided in Figure 6. Or of MCN and fina the left, the weight windows were tuned to calculate the fluxes and loads in the Faraday sensors, using the reference model of Figure 3. In this case, the weight window generato1 P was used, after multiplying the density of all materials in the model by 1/10 In subsequent simulations, the material densities were progressively increased (1/5, 1/2 ly 1), optimizing the weight windows at each step. This allowed us to bias the simulations towards the outer surface of the VV (from red to blue), where the sensors are ocated. For gammas, this weight window mesh was duplicated with the iWW-GVR [46] code and multiplied by 0.1.
Figure 6. Weight windows used in the simulations. Left: Faraday sensors, installed on the outer layer of the VV. Right: EP diagnostics. Common to all cases studied in this paper was the use of weight windows for variance reduction, to reduce the statistical errors of the simulation results. This is a crucial point when the aim is to calculate fluxes or loads at large distances from the plasma, as is the case with most simulations presented here. Two examples are provided in Figure 6. Or of MCN and fina the left, the weight windows were tuned to calculate the fluxes and loads in the Faraday sensors, using the reference model of Figure 3. In this case, the weight window generato1 P was used, after multiplying the density of all materials in the model by 1/10 In subsequent simulations, the material densities were progressively increased (1/5, 1/2 ly 1), optimizing the weight windows at each step. This allowed us to bias the simulations towards the outer surface of the VV (from red to blue), where the sensors are ocated. For gammas, this weight window mesh was duplicated with the iWW-GVR [46] code and multiplied by 0.1.
Figure 7. MCNP model of the DSC, containing the antennas and WGs designed for reflectometry Left: Plane y = 10.5 cm. Right: Plane y = 6 cm. The model of model of Figure 2. the DSC is presented in Figures 7 and 8, in As described in more detail in [16], the DSC egrated in the reference has a thickness of 25 cm in the toroidal direction and the same poloidal shape as the blankets, ~12 m in height and approximately 52 mixture of EUROF and 16.4%, respec tons in weight (similar density to the WCLL b in a previous wor k [24]. This water volume fraction is similar ankets). A homogenized ER and water was assumed for the DSC, with volume fractions of 83.6% ively, representative of a small module with a cooling system studied to the one in the blanket (15.9%). The MW antennas and waveguides were kept in the geometry, to provide a more conservative estimation and because they have been shown to have a small impact on the neutron fluxes and nuclear loads in the VV.
Figure 7. MCNP model of the DSC, containing the antennas and WGs designed for reflectometry Left: Plane y = 10.5 cm. Right: Plane y = 6 cm. The model of model of Figure 2. the DSC is presented in Figures 7 and 8, in As described in more detail in [16], the DSC egrated in the reference has a thickness of 25 cm in the toroidal direction and the same poloidal shape as the blankets, ~12 m in height and approximately 52 mixture of EUROF and 16.4%, respec tons in weight (similar density to the WCLL b in a previous wor k [24]. This water volume fraction is similar ankets). A homogenized ER and water was assumed for the DSC, with volume fractions of 83.6% ively, representative of a small module with a cooling system studied to the one in the blanket (15.9%). The MW antennas and waveguides were kept in the geometry, to provide a more conservative estimation and because they have been shown to have a small impact on the neutron fluxes and nuclear loads in the VV.
factors. Using Paraview, the values for each of these quantities were obtained at the 60 poloidal positions where the magnetics sensors are expected to be placed, for the two studied configurations: with the DSC (sensors located behind the DSC) and without the DSC but considering a BB with the full (toroidal) width and having the sensors in the same positions (sensors located behind the blanket). These positions are illustrated on the right side of Figure 9. Figure 9. Left: Detail of the DSC, highlighting the cells used to tally fluxes, heat loads and dose rates (plane z = 0). Right: The 60 poloidal positions around the plasma foreseen for magnetics sensors.
factors. Using Paraview, the values for each of these quantities were obtained at the 60 poloidal positions where the magnetics sensors are expected to be placed, for the two studied configurations: with the DSC (sensors located behind the DSC) and without the DSC but considering a BB with the full (toroidal) width and having the sensors in the same positions (sensors located behind the blanket). These positions are illustrated on the right side of Figure 9. Figure 9. Left: Detail of the DSC, highlighting the cells used to tally fluxes, heat loads and dose rates (plane z = 0). Right: The 60 poloidal positions around the plasma foreseen for magnetics sensors.
rates, the neutron contribution to the total is included (remaining contribution by gammas). Table 1. Neutron fluxes, nuclear heat loads and dose rates at 3 toroidal positions in the equatorial plane IB. For the flux calculations, the statistical errors are also presented. For the heat loads and dose rates, the neutron contribution to the total is included (remaining contribution by gammas). Comparing the two configurations, the heat loads and dose rates are very similar when he sensors are located between the blanket modules, as neutrons are the main contributors o the total heat loads and dose rates in that position and the neutron fluxes are similar etween the two cases. Behind the DSC/BB (y = 10.5 cm) the heat loads and dose rates are 7% to 69% higher in the DSC configuration, depending on the material. In the position ehind the middle of the BBs (y = 45 cm) the heat loads and dose rates are 5% to 9% higher n the case without DSC. Table 1. Neutron fluxes, nuclear heat loads and dose rates at 3 toroidal positions in the equatorial
rates, the neutron contribution to the total is included (remaining contribution by gammas). Table 1. Neutron fluxes, nuclear heat loads and dose rates at 3 toroidal positions in the equatorial plane IB. For the flux calculations, the statistical errors are also presented. For the heat loads and dose rates, the neutron contribution to the total is included (remaining contribution by gammas). Comparing the two configurations, the heat loads and dose rates are very similar when he sensors are located between the blanket modules, as neutrons are the main contributors o the total heat loads and dose rates in that position and the neutron fluxes are similar etween the two cases. Behind the DSC/BB (y = 10.5 cm) the heat loads and dose rates are 7% to 69% higher in the DSC configuration, depending on the material. In the position ehind the middle of the BBs (y = 45 cm) the heat loads and dose rates are 5% to 9% higher n the case without DSC. Table 1. Neutron fluxes, nuclear heat loads and dose rates at 3 toroidal positions in the equatorial
To finalize the comparison, the neutron flux spectra for the DSC case are presented in Figure 10. Although the statistical errors are large in most bins, and therefore unsuitable to be used as input in inventory or activation analyses, the ones related to the total flux are 1.8%, 3.6% and 4.7%, for the cases between blankets, behind the DSC and behind the blanket, respectively. The 14 MeV peak of uncollided neutrons is evident for the tally cell between the blankets (y = 0), vanishing completely in the remaining positions. For the case without the DSC the spectra are very similar and were not included in the plot. Figure 10. Neutron flux spectra (n cm~? s~!) and statistical error fraction behind the DSC and WCLL blanket.
To finalize the comparison, the neutron flux spectra for the DSC case are presented in Figure 10. Although the statistical errors are large in most bins, and therefore unsuitable to be used as input in inventory or activation analyses, the ones related to the total flux are 1.8%, 3.6% and 4.7%, for the cases between blankets, behind the DSC and behind the blanket, respectively. The 14 MeV peak of uncollided neutrons is evident for the tally cell between the blankets (y = 0), vanishing completely in the remaining positions. For the case without the DSC the spectra are very similar and were not included in the plot. Figure 10. Neutron flux spectra (n cm~? s~!) and statistical error fraction behind the DSC and WCLL blanket.
xes (n cm~* s~') and statistical errors behind the WCLL blanket in plane The neutron fluxes and statistical errors obtained for the configuration without the DSC are presented in Figure 12. As expected, the fluxes in the first wall are of the order of 3-4 x 10/4 n cm~?s~!, while behind the blanket they vary between ~1 x 10! and 1 x 10'* ncm~? s~!, depending on the position. In general, the statistical errors behind the DSC are less than 10%. Figure 12. Neutron fluxes (n cm~* s—!) and statistical errors behind the WCLL blanket in plane a Aaf*\ ™ ....
xes (n cm~* s~') and statistical errors behind the WCLL blanket in plane The neutron fluxes and statistical errors obtained for the configuration without the DSC are presented in Figure 12. As expected, the fluxes in the first wall are of the order of 3-4 x 10/4 n cm~?s~!, while behind the blanket they vary between ~1 x 10! and 1 x 10'* ncm~? s~!, depending on the position. In general, the statistical errors behind the DSC are less than 10%. Figure 12. Neutron fluxes (n cm~* s—!) and statistical errors behind the WCLL blanket in plane a Aaf*\ ™ ....
Figure 13. Neutron fluxes (n cm~? s~!) and statistical errors behind the WCLL blanket at 60 poloidal locations in plane y = 10.5 cm. Figure 13 shows the values of the neutron fluxes at the 60 poloidal positions foreseen for magnetics sensors. Values vary from 1.1 x 10'! ncm~* s~ in position 6 (see Figure 9) to 5.2 x 10'*ncm~*s~! below the divertor (more than one order of magnitude of variation). In the equatorial plane, at position 14 (z = —13.5 cm), the neutron flux is 1.4 x 10!2 ncem-? 57! which agrees with the value provided in Table 1. The largest statistical error is 10.1%. y
Figure 13. Neutron fluxes (n cm~? s~!) and statistical errors behind the WCLL blanket at 60 poloidal locations in plane y = 10.5 cm. Figure 13 shows the values of the neutron fluxes at the 60 poloidal positions foreseen for magnetics sensors. Values vary from 1.1 x 10'! ncm~* s~ in position 6 (see Figure 9) to 5.2 x 10'*ncm~*s~! below the divertor (more than one order of magnitude of variation). In the equatorial plane, at position 14 (z = —13.5 cm), the neutron flux is 1.4 x 10!2 ncem-? 57! which agrees with the value provided in Table 1. The largest statistical error is 10.1%. y
Figure 14. Left: Neutron flux ratios (with DSC/without DSC) in plane y = 10.5 cm. Right: Values at 60 poloidal locations. For comparison between the two cases, the ratios between the results obtained with the DSC and without the DSC are presented in Figure 14. The neutron fluxes with the DSC are slightly higher close to the first wall, but lower at almost all positions behind the DSC/blanket. The main conclusion is that the neutron fluxes are very close between configurations, with differences below 20% at most positions.
Figure 14. Left: Neutron flux ratios (with DSC/without DSC) in plane y = 10.5 cm. Right: Values at 60 poloidal locations. For comparison between the two cases, the ratios between the results obtained with the DSC and without the DSC are presented in Figure 14. The neutron fluxes with the DSC are slightly higher close to the first wall, but lower at almost all positions behind the DSC/blanket. The main conclusion is that the neutron fluxes are very close between configurations, with differences below 20% at most positions.
The gamma fluxes behind the blanket are plotted Figure 15. They reach2 x 10! y cm~? s~ at the equatorial plane (three orders of magnitude lower than at the first wall), while in the divertor region they reach 7 x 10!* -y cm~* s~!. These simulations were run with larger mesh elements (5 cm x 1 cm x 5 cm), to reduce the statistical errors of the simulations, which ex ceeded 10% in some positions with the initial mesh. Similar values were obtained between the two simulations (smaller and larger mesh elements), with statistical errors < 10% for the larger elements. Figure 15. Gamma fluxes (y cm~* s~!) and statistical errors behind the WCLL blanket at 60 poloidal locations.
The gamma fluxes behind the blanket are plotted Figure 15. They reach2 x 10! y cm~? s~ at the equatorial plane (three orders of magnitude lower than at the first wall), while in the divertor region they reach 7 x 10!* -y cm~* s~!. These simulations were run with larger mesh elements (5 cm x 1 cm x 5 cm), to reduce the statistical errors of the simulations, which ex ceeded 10% in some positions with the initial mesh. Similar values were obtained between the two simulations (smaller and larger mesh elements), with statistical errors < 10% for the larger elements. Figure 15. Gamma fluxes (y cm~* s~!) and statistical errors behind the WCLL blanket at 60 poloidal locations.
Figure 16. Left: Gamma flux ratios (with DSC/without DSC) in plane y = 10.5 cm. Right: Values at 60 poloidal locations. The ratios between the gamma fluxes with and without the DSC are presented in Figure 16. Except for the divertor region—where the ratios are 1—the gamma fluxes increase with the DSC by a factor of 2-3. This is because more gammas are produced in the DSC than in the BB, due to the higher radiative capture cross-sections of iron and chromium (the main constituents of EUROFER) when compared to the radiative capture cross-section of lead (from the WCLL BB).
Figure 16. Left: Gamma flux ratios (with DSC/without DSC) in plane y = 10.5 cm. Right: Values at 60 poloidal locations. The ratios between the gamma fluxes with and without the DSC are presented in Figure 16. Except for the divertor region—where the ratios are 1—the gamma fluxes increase with the DSC by a factor of 2-3. This is because more gammas are produced in the DSC than in the BB, due to the higher radiative capture cross-sections of iron and chromium (the main constituents of EUROFER) when compared to the radiative capture cross-section of lead (from the WCLL BB).
Table 2. Total heat loads in six materials at 60 poloidal locations behind the WCLL blanket.
Table 2. Total heat loads in six materials at 60 poloidal locations behind the WCLL blanket.
Figure 17. Left: dpa/FPY behind the WCLL blanket. Right: dpa/FPY behind the DSC.
Figure 17. Left: dpa/FPY behind the WCLL blanket. Right: dpa/FPY behind the DSC.
Table 2. Cont. As seen before, DP-951 and SiO, are the materials with lower values in general, although the variations between materials are mostly within 40%. As an example, the heat loads at the equatorial plane inboard in the configuration without the DSC vary from 5.3 mW cm~® in SiO, to 7.1 mW cm~? in AlyO3 (a variation of ~30%). Apart from the divertor region, the highest heat loads are at the equatorial plane inboard (a factor ~3 higher than at the outboard).
Table 2. Cont. As seen before, DP-951 and SiO, are the materials with lower values in general, although the variations between materials are mostly within 40%. As an example, the heat loads at the equatorial plane inboard in the configuration without the DSC vary from 5.3 mW cm~® in SiO, to 7.1 mW cm~? in AlyO3 (a variation of ~30%). Apart from the divertor region, the highest heat loads are at the equatorial plane inboard (a factor ~3 higher than at the outboard).
Table 3. Dose rates in six materials at 60 poloidal locations behind the WCLL blanket.
Table 3. Dose rates in six materials at 60 poloidal locations behind the WCLL blanket.
Table 3. Cont. The results presented in this section show that the DSC leads to an increase in the gamma fluxes and heat loads in the VV without compromising its integrity. The heat loads in the VV obtained with the DSC are well below the limit of 0.3 W/cm?, while the dpa
Table 3. Cont. The results presented in this section show that the DSC leads to an increase in the gamma fluxes and heat loads in the VV without compromising its integrity. The heat loads in the VV obtained with the DSC are well below the limit of 0.3 W/cm?, while the dpa
Table 4. Neutron fluxes and fluences in the magnetics sensors (behind the WCLL blanket) As mentioned before, with the HCPB blanket the fluences in the sensors would be increased up to a factor of 10 or more, which would increase the loads when compared to ITER. Furthermore, the WCLL blanket design changes every year, and a reduction of the blanket dimensions cannot be ruled out at this stage. It is also important to highlight that the present analysis is very preliminary, as it assumes homogeneous material compositions in the blanket and DSC. Therefore, it is important to repeat the analysis when the new models are available, if possible using a fully heterogeneous model of the WCLL blanket [50], with the required adaptations to provide space for the inclusion of magnetic sensors.
Table 4. Neutron fluxes and fluences in the magnetics sensors (behind the WCLL blanket) As mentioned before, with the HCPB blanket the fluences in the sensors would be increased up to a factor of 10 or more, which would increase the loads when compared to ITER. Furthermore, the WCLL blanket design changes every year, and a reduction of the blanket dimensions cannot be ruled out at this stage. It is also important to highlight that the present analysis is very preliminary, as it assumes homogeneous material compositions in the blanket and DSC. Therefore, it is important to repeat the analysis when the new models are available, if possible using a fully heterogeneous model of the WCLL blanket [50], with the required adaptations to provide space for the inclusion of magnetic sensors.
Table 5. Fluxes, heat loads and dose rates in the 72 positions of the FOCS (WCLL blanket).
Table 5. Fluxes, heat loads and dose rates in the 72 positions of the FOCS (WCLL blanket).
Figure 18. Left: Location of the FOCS in the MCNP model. Right: Poloidal positions used in the simulations to tally fluxes and energy deposition.
Figure 18. Left: Location of the FOCS in the MCNP model. Right: Poloidal positions used in the simulations to tally fluxes and energy deposition.
Table 5. Cont.
Table 5. Cont.
Table 5. Cont.
Table 5. Cont.
Figure 19. Neutron fluxes (n/ cm? /s) and statistical errors (%) in 4 FOCS positions (WCLL blanket). This is further illustrated in Figures 19 and 20, which show the neutron and gamma flux spectra in four positions, two at the equatorial port level (15 inboard and 53 outboard), one in the divertor region (31) and the remaining one above the plasma (70). In the divertor region the fluxes are clearly higher when compared to the other positions, for both neutrons and gammas. In position 53 (but also 15 and 31), the statistical errors in the bins are inevitably large, due to the very small binning and the blanket thickness in that area. Nevertheless, the statistical errors in the total neutron and gamma fluxes are only 4.8% and 4.5%, respectively.
Figure 19. Neutron fluxes (n/ cm? /s) and statistical errors (%) in 4 FOCS positions (WCLL blanket). This is further illustrated in Figures 19 and 20, which show the neutron and gamma flux spectra in four positions, two at the equatorial port level (15 inboard and 53 outboard), one in the divertor region (31) and the remaining one above the plasma (70). In the divertor region the fluxes are clearly higher when compared to the other positions, for both neutrons and gammas. In position 53 (but also 15 and 31), the statistical errors in the bins are inevitably large, due to the very small binning and the blanket thickness in that area. Nevertheless, the statistical errors in the total neutron and gamma fluxes are only 4.8% and 4.5%, respectively.
Figure 20. Gamma fluxes (y/ cm*/s) and statistical errors (%) in four FOCS positions (WCLL blanket).
Figure 20. Gamma fluxes (y/ cm*/s) and statistical errors (%) in four FOCS positions (WCLL blanket).
Figure 21. EP configuration with the X-ray spectroscopy (light blue), divertor monitoring (X-point and outer divertor tangential line-of-sight in purple, outer divertor surface views in red) and pellet monitoring (green) systems. In this integration proposal the six optical paths of the divertor monitoring and pellet monitoring systems are grouped together on the left side of the port (when looking towards the plasma) in two rows with three paths each. The X-ray spectroscope is placed on the right side, with the ducts angled slightly in the EP to increase the space for the port cell optical components of the other systems. This setup is presented in Figure 21.
Figure 21. EP configuration with the X-ray spectroscopy (light blue), divertor monitoring (X-point and outer divertor tangential line-of-sight in purple, outer divertor surface views in red) and pellet monitoring (green) systems. In this integration proposal the six optical paths of the divertor monitoring and pellet monitoring systems are grouped together on the left side of the port (when looking towards the plasma) in two rows with three paths each. The X-ray spectroscope is placed on the right side, with the ducts angled slightly in the EP to increase the space for the port cell optical components of the other systems. This setup is presented in Figure 21.
Figure 22. Possible radiation shielding locations proposed for the EP (units in mm).
Figure 22. Possible radiation shielding locations proposed for the EP (units in mm).
The diagnostic with the largest openings is the X-ray spectroscopy system, with a first wall opening of 23 cm x 10 cm (230 cm?) that spreads into three ducts behind the first wall. As illustrated in Figure 25, these ducts are straight paths from the plasma to the port cell, with openings in the bioshield plug of 10.6 cm x 10 cm (106 cm’). As there are no doglegs in this diagnostic, direct neutron streaming is expected through these ducts. Figure 23. CAD model of the EP used in the simulations.
The diagnostic with the largest openings is the X-ray spectroscopy system, with a first wall opening of 23 cm x 10 cm (230 cm?) that spreads into three ducts behind the first wall. As illustrated in Figure 25, these ducts are straight paths from the plasma to the port cell, with openings in the bioshield plug of 10.6 cm x 10 cm (106 cm’). As there are no doglegs in this diagnostic, direct neutron streaming is expected through these ducts. Figure 23. CAD model of the EP used in the simulations.
Figure 24. CAD model of the EP used in the simulations with transparent cells, showing the diagnostic ducts.
Figure 24. CAD model of the EP used in the simulations with transparent cells, showing the diagnostic ducts.
Figure 25. X-ray spectroscopy ducts along the EP.
Figure 25. X-ray spectroscopy ducts along the EP.
Figure 26. MCNP model of the EP. Left: X-ray spectroscopy ducts. Right: Near-ultraviolet (bottom) and visible (top) divertor spectroscopy ducts (poloidal view, plane y = —15 cm).
Figure 26. MCNP model of the EP. Left: X-ray spectroscopy ducts. Right: Near-ultraviolet (bottom) and visible (top) divertor spectroscopy ducts (poloidal view, plane y = —15 cm).
Figure 27. Materials used in the MCNP model of the equatorial port. Most of the materials used in the equatorial port model are summarized in Figure 27 The first wall has 2 mm thick armor made of tungsten, with a second layer of 6.09% water and 93.91% EUROFER, taken directly from the definition of the WCLL BB which follows the material distribution set out in [57]. The definition for the first wall shield block behind it was adopted from the technical specification for the equatorial outboard limiter [58]: 60% EUROFER and 40% water. For the remaining shielding behind this block a mixture of 70% SS316L(N)-IG stainless steel and 30% water was assumed, while in the second shielding block (yellow in Figure 26, second dogleg) a homogenized mixture of 65% B4C, 10% stainless steel and 25% void (to account for the spacings between the components) was defined, with an effective density of 2.28 ¢/ em? [55]. This mixture represents the ByC shielding trays used in the ITER DSMs for the equatorial ports [55].
Figure 27. Materials used in the MCNP model of the equatorial port. Most of the materials used in the equatorial port model are summarized in Figure 27 The first wall has 2 mm thick armor made of tungsten, with a second layer of 6.09% water and 93.91% EUROFER, taken directly from the definition of the WCLL BB which follows the material distribution set out in [57]. The definition for the first wall shield block behind it was adopted from the technical specification for the equatorial outboard limiter [58]: 60% EUROFER and 40% water. For the remaining shielding behind this block a mixture of 70% SS316L(N)-IG stainless steel and 30% water was assumed, while in the second shielding block (yellow in Figure 26, second dogleg) a homogenized mixture of 65% B4C, 10% stainless steel and 25% void (to account for the spacings between the components) was defined, with an effective density of 2.28 ¢/ em? [55]. This mixture represents the ByC shielding trays used in the ITER DSMs for the equatorial ports [55].
this estimation) are of the order of 2 x 10!°ncm~?:s~1, decreasing to 4 x 10? ncm7~2 s7! in the mirror behind the bioshield. The gamma fluxes reach 3 x 10? y cm~? s~! at the inner surface of the bioshield and 2 x 10? y cm~* s~! and 2 x 108 y cm~? s~! in the mirror, while the dose rates in silicon obtained in these positions were 2E6 Gy/FPY and 5E5 Gy/FPY, respectively. The flux and dose rate values in the port cell are more than three orders of magnitude higher than those obtained with the reference model of the port without diagnostics (neutron fluxes below 1 x 107 ncm~* s~! were obtained in the port cell with the reference model). For the remaining port diagnostics, the design of the first doglegs is effective to reduce the streaming, as shown in a previous study [25]. Figure 28. Neutron and gamma fluxes (cm~? s~!) in plane y for the configuration with diagnostics in the EP.
this estimation) are of the order of 2 x 10!°ncm~?:s~1, decreasing to 4 x 10? ncm7~2 s7! in the mirror behind the bioshield. The gamma fluxes reach 3 x 10? y cm~? s~! at the inner surface of the bioshield and 2 x 10? y cm~* s~! and 2 x 108 y cm~? s~! in the mirror, while the dose rates in silicon obtained in these positions were 2E6 Gy/FPY and 5E5 Gy/FPY, respectively. The flux and dose rate values in the port cell are more than three orders of magnitude higher than those obtained with the reference model of the port without diagnostics (neutron fluxes below 1 x 107 ncm~* s~! were obtained in the port cell with the reference model). For the remaining port diagnostics, the design of the first doglegs is effective to reduce the streaming, as shown in a previous study [25]. Figure 28. Neutron and gamma fluxes (cm~? s~!) in plane y for the configuration with diagnostics in the EP.
Figure 29. Neutron and gamma fluxes (cm~? s~!) in plane z for the configuration with diagnostics ir the EP.
Figure 29. Neutron and gamma fluxes (cm~? s~!) in plane z for the configuration with diagnostics ir the EP.
Figure 30. Statistical errors of the neutron fluxes, for the planes y = 80 cm and z = 0.
Figure 30. Statistical errors of the neutron fluxes, for the planes y = 80 cm and z = 0.
Figure 31. Neutron flux (n/ cm? /s) and statistical error 2 m behind the bioshield plug (x = 2400 cm, y = 70 cm, z = 0), for a circular duct with r = 1.5 cm.
Figure 31. Neutron flux (n/ cm? /s) and statistical error 2 m behind the bioshield plug (x = 2400 cm, y = 70 cm, z = 0), for a circular duct with r = 1.5 cm.
Figure 32. Gamma flux (y/cm?/s) and statistical error 2 m behind the bioshield plug (x = 2400 cm y = 70 cm, z = 0), for a circular duct with r = 1.5 cm. The F5 tallies also allowed us to calculate the gamma spectra in the port cell, as shown 4.5 x in Figure 32 for the same case and position as before. The total gamma flux 0” y cm~? s~!) is almost one order of magnitude lower than the neutron flux. The statistical errors are larger in this case, but still below 10%. The uncollided spectrum ‘efers to gammas that were created somewhere in the geometry and traveled to the port ell wi -rrors hout interactions. For both cases (neutron and gammas), reducing the statistical below 10% in all bins would be mandatory if these results were to be used as nput in inventory or activation calculations; however, this would be prohibitive in terms yf com: putational resources. Furthermore, the “collided” part of the spectrum depends 1eavily on the shielding configurations, which are very preliminary at this stage.
Figure 32. Gamma flux (y/cm?/s) and statistical error 2 m behind the bioshield plug (x = 2400 cm y = 70 cm, z = 0), for a circular duct with r = 1.5 cm. The F5 tallies also allowed us to calculate the gamma spectra in the port cell, as shown 4.5 x in Figure 32 for the same case and position as before. The total gamma flux 0” y cm~? s~!) is almost one order of magnitude lower than the neutron flux. The statistical errors are larger in this case, but still below 10%. The uncollided spectrum ‘efers to gammas that were created somewhere in the geometry and traveled to the port ell wi -rrors hout interactions. For both cases (neutron and gammas), reducing the statistical below 10% in all bins would be mandatory if these results were to be used as nput in inventory or activation calculations; however, this would be prohibitive in terms yf com: putational resources. Furthermore, the “collided” part of the spectrum depends 1eavily on the shielding configurations, which are very preliminary at this stage.
Table 6. Neutron fluxes as a function of the duct cross-sectional dimensions. BS refers to bioshield and M to a possible mirror location 2 m behind. Table 7. Gamma fluxes as a function of the duct cross-sectional dimensions. BS refers to bioshield and M to a possible mirror location 2 m behind.
Table 6. Neutron fluxes as a function of the duct cross-sectional dimensions. BS refers to bioshield and M to a possible mirror location 2 m behind. Table 7. Gamma fluxes as a function of the duct cross-sectional dimensions. BS refers to bioshield and M to a possible mirror location 2 m behind.
Figure 33. Neutron flux variation with the cross-sectional area, for rectangular ducts. Figure 33 shows the neutron fluxes plotted against the cross-sectional area of the ducts for the rectangular configuration (the results for the circular ducts are very similar and were omitted). The flux varies linearly with the duct area. The fits were obtained using Mathematica [36] for the simple expression f = c A, where f is the flux, A is the area of the duct and c is a constant, and they can be used as a first approximation to estimate the fluxes in ducts with different areas.
Figure 33. Neutron flux variation with the cross-sectional area, for rectangular ducts. Figure 33 shows the neutron fluxes plotted against the cross-sectional area of the ducts for the rectangular configuration (the results for the circular ducts are very similar and were omitted). The flux varies linearly with the duct area. The fits were obtained using Mathematica [36] for the simple expression f = c A, where f is the flux, A is the area of the duct and c is a constant, and they can be used as a first approximation to estimate the fluxes in ducts with different areas.
Figure 34. CAD model of the neutron and gamma cameras.
Figure 34. CAD model of the neutron and gamma cameras.
Figure 35. CAD model of the core radiated power and soft X-ray intensity system
Figure 35. CAD model of the core radiated power and soft X-ray intensity system
Figure 36. Neutronics model used in the simulations of the neutron/gamma cameras and core radiated power and soft X-ray intensity system (plane y = 50 cm).
Figure 36. Neutronics model used in the simulations of the neutron/gamma cameras and core radiated power and soft X-ray intensity system (plane y = 50 cm).
Table 8. Summary of the neutron and gamma fluxes at the 13 detector positions of Figure 36. The nuclear heat loads in beryllium are presented in Table 9. As these results were obtained with F5 tallies, the heat loads due to uncollided neutrons and gammas are also presented, along with the total heat loads obtained by summing the neutron and gamma contributions. Since beryllium is a neutron moderator and the neutron fluxes are higher than the gamma fluxes, neutrons have the highest contribution to the total heat loads, exceeding the gamma contribution by more than one order of magnitude. The total heat loads range from 3.0 hW/cm? at position 13 to 5.3 wW/cm? in the central detector positions (6 and 7). The statistical errors are below 1% for all positions.
Table 8. Summary of the neutron and gamma fluxes at the 13 detector positions of Figure 36. The nuclear heat loads in beryllium are presented in Table 9. As these results were obtained with F5 tallies, the heat loads due to uncollided neutrons and gammas are also presented, along with the total heat loads obtained by summing the neutron and gamma contributions. Since beryllium is a neutron moderator and the neutron fluxes are higher than the gamma fluxes, neutrons have the highest contribution to the total heat loads, exceeding the gamma contribution by more than one order of magnitude. The total heat loads range from 3.0 hW/cm? at position 13 to 5.3 wW/cm? in the central detector positions (6 and 7). The statistical errors are below 1% for all positions.
Table 9. Heat loads in Be by neutrons and gammas at the 13 detector locations of Figure 36.
Table 9. Heat loads in Be by neutrons and gammas at the 13 detector locations of Figure 36.
Figure 37. CAD model of the EP used in the simulations with transparent cells, showing the pre- reflectors and the diagnostic ducts of the X-ray spectroscopy system.
Figure 37. CAD model of the EP used in the simulations with transparent cells, showing the pre- reflectors and the diagnostic ducts of the X-ray spectroscopy system.
Figure 38. MCNP model of the EP, showing the X-ray spectroscopy ducts (plane z = 1 cm).
Figure 38. MCNP model of the EP, showing the X-ray spectroscopy ducts (plane z = 1 cm).
2 Figure 39. Neutron (n cm s_!) and gamma (y cm? s~!) fluxes in plane y with the alternative X-ray spectroscopy ducts.
2 Figure 39. Neutron (n cm s_!) and gamma (y cm? s~!) fluxes in plane y with the alternative X-ray spectroscopy ducts.
2, 2 Figure 40. Neutron (n cm™ s!) and gamma (y cm— s—!) fluxes in plane z with the alternative X-ray spectroscopy ducts.
2, 2 Figure 40. Neutron (n cm™ s!) and gamma (y cm— s—!) fluxes in plane z with the alternative X-ray spectroscopy ducts.
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