The impact of the investigated parameters has been quantified with respect to the selected reference case. In general, except for the nuclear energy demand, their influence is rather limited. However, as indicated in the previous section, the effect of some parameters becomes important in a more complex scenario, e.g. regional or global scenarios.
The parametric study concerning the "once-through" case has been summarized, in a qualitative way, in Table 4.17.
Indicators Parameters
Burn-up Nucl. Energy demand Reactor Intro. rate Reactor Lifetime
Uranium Mass Medium High-Medium Low Low
Plutonium Mass Medium High-Medium Medium Low
Spent Fuel Inventory Medium High-Medium Low Low
Radiotoxicity Low Low Low Low
Heat Load Low Low Low Low
Infrastructures needs Medium High-Medium Low Low
Table 4.17: Impact of each parameter over the indicators selected [High: impact considerably the trends; Medium: impact not drastically the trends; Low: impact negligibly the trends]
An indication about the level of the influence (low, medium, high) regarding the indicators chosen is reported too. This general overview can provide an indication of the most dominating and most important hypotheses to be studied more in detail for defining the boundary conditions of the scenario as well as it helps in defining which hypotheses can be neglected.
4.4
Summary
In the present Chapter the hypothesis of a nuclear energy development based on LWRs deployment has been analyzed in detail.
A reference case, suitable for future extrapolation at regional scale, has been defined.
The activity has been focused on the investigation of the implication on selected indicators which are natural uranium requirements, industrial infrastructure needs, waste inventory, radiotoxicity and heat load evolution in a repository.
In order to quantify the impact of the boundary conditions, a parametric study has been developed. Selected parameters (defining the boundary conditions) have been separately investigated and quan- tified with respect to the reference case (70 TWhe/y constant nuclear energy demand and "once-through" strategy).
The outcome of the parametric study is a kind of "database" containing the impact on the selected indicators (U and Pu mass flows, SF inventory, radiotoxicity and heat load) of each parameter considered (i.e. nuclear energy demand, reactor introduction rate, core burn-up, etc.).
These data can be used in order to take into account the uncertainties associated to the chosen hypothe- ses.
Moreover, the study has provided also an indication of the most critical boundary conditions (above all the nuclear energy demand) for the definition of a fuel cycle scenario.
Transition from Thermal to Fast
Reactors
The parametric study concerning the nuclear energy development by LWRs deployment presented in Chap- ter 4 has shown how quantities like the utilization of uranium resources and the waste produced can be modified by the hypotheses and constraints considered.
The effect becomes much important if the fuel cycle strategy is changed from the actual "once-through" case to the adoption of advanced fuel cycles based on Partitioning & Transmutation (P&T).
In the present Chapter, the analysis of the transition scenarios from an LWRs based fleet to an FRs based one is described. The activity has been developed highlighting, case by case, the most critical parameters affecting the sustainability indicators selected for the study (resources, waste inventory, radiotoxicity and heat load).
The period of interest remains unchanged: 2020-2200. This period, indeed, was chosen in order to allow the full transition toward a fast reactor based fleet (if possible according to the system considered) and to point out the advantages and possible disadvantages, difficulties and drawbacks of the selected strategy under equilibrium conditions.
The reference scenario remains practically unchanged (see Par. 4.2 for details). The only difference is the constant value assumed for the nuclear energy demand. In fact, the energy produced by 6 EPR units (55 GWd/tHM average burn-up) equal to 66.7 TWhe/y has been adopted instead of 70 TWhe/y initially considered (corresponding to ca. 6.3 units). As shown in Par. 4.3.2, the differences between the two cases are negligible. The data adopted for the EPRs model are listed in Table 4.1. The "equivalent reactor" approach has been used also in this part of the activity.
In order to define the "transition scenarios", additional constraints have been fixed in terms of Pu avail- ability and FRs start-up. The transition has been limited by the Pu available in the cycle, produced only by the thermal reactor fleet operated in the so called Italian scenario since 2030. Under this assumption, the breeding characteristics and the power density of the FRs considered play the central role in the dynamics of the transition.
This constraint has been fixed for several reasons. First of all, it has been assumed that at the time horizon in which FRs will be inserted in the scenario (toward the end of the century), the technology is mature. Moreover, it has assumed that no "spar" plutonium resource is available.
For the present activity, the FRs considered are all self-sustaining or slightly breeder systems, as de- scribed in Appendix D. This choice depends on observed technological trends in e.g. Europe [4, 84, 58].
In fact, the expected low energy demand increase (justified by the expected low population increase and by the already achieved level of industrialization) does not justify or even urge the adoption of strong
breeders at the moment.
Suitable COSI6 libraries (including one group cross sections and fluxes; burn-up dependent) have been generated for the reactor systems considered in the study. The 3D core models and burn-up evolution have been treated by means of the ERANOS code [182] in agreement with the procedure described in Par. 3.4 and in Appendix D.
For the study, three fast reactor concepts have been considered:
- European Lead-cooled System: so-called ELSY-like system [74, 75, 188]. The ELSY system is a medium size (600 MWe) lead cooled critical fast reactor [68]. The model considered in the study is the HEX-Z model developed at SCK-CEN [189] characterized by three core zones with different Pu content (14.6, 15.4, 17.3 at% Pu/HM). The fuel residence time is ca. 5 years with 4 batches reloading scheme.
- European Sodium Fast Reactor: so-called ESFR-like systems [58, 31, 30]. The ESFR system is a large (1440 MWe) sodium cooled fast reactor [58]. The oxide fuel configuration has been considered in the study. The core is composed of two zones with different Pu content (14.43 and 16.78 at.%) in order to achieve a rather flat power profile. The total residence time is 2050 efpd with 5 batches reloading scheme.
- European Fast reactor: so-called EFR-like systems [103, 190, 191]. It is a large (1500 MWe) sodium cooled fast reactor. The applied model is a HEX-Z core, with three enrichment zones. In order to reach a near zero BG, axial and radial blanket zones of depleted uranium oxide have been considered. The fuel residence time is ca. 4.5 years with 5 batches reloading scheme. The same time and reloading strategy is considered for the axial blankets. For the radial blanket the total residence time is ca. 9 years.
In particular, the ELSY and ESFR neutronic models have been assessed for the Ph.D. purpose adopting the ERANOS2.2 neutronics code and JEFF3.1 data libraries [182, 192]. The relative BBL libraries for COSI6 code have been generated on the basis of the ERANOS(DARWIN)-APOGENE-COSI chain [183].
On the contrary, the EFR library for COSI6 simulations has been generated at CEA. This library has been applied in other studies (e.g. [4, 193, 150]). Some details about the EFR model can be found in [103]. For all the cases, the earliest introduction date of fast reactors is fixed at 2080, i.e. after an assumed LWR
reactor lifetime1. A partially closed fuel cycle where only Pu is multi-recycled in FRs has been considered.
The fuel cycle scheme is indicated in Figure 5.1.
5.1
Introduction of Fast Reactor
As indicated previously, for the transition to FRs only the Pu available in the cycle has been considered. The Pu produced by the LWR fleet, the breeding characteristics, and the power density of the fast systems are the main factors for the transition strategy in a country or region that wants to develop nuclear energy in isolation as elucidated by the results of the transition scenarios performed (see Par. 5.1.1).
In the study, the spent fuel cooling time (for both thermal and fast reactor fleet) before reprocessing has been maintained fixed: 5 years for LWRs SF and 2 years for FRs SF.
Fabrication and reprocessing times have been kept unchanged irrespective of the considered scenarios and equal to 0.5 years each.
1This date is essentially a consequence of the shut-down and substitution of the first LWR NPP; it does not necessarily mean that
Figure 5.1: A simplified flow scheme for the reference scenarios: the partially closed fuel cycle
These hypotheses have not been changed in order to better highlight the effects of other parameters (e.g. breeding characteristics). However, it is well known that these parameters can strongly affect the dynamics of the transition (influencing the amount of Pu in the cycle) as indicated also by [55, 84, 4].
The main characteristics of the FRs considered are listed in Table 5.1. The data involved in the transition evolution (early start-up, shares, etc.) are specified case by case in accordance with the obtained results.
ELSY ESFR EFR
MWth 1500 3600 3625
MWe 600 1440 1450
Coolant Lead Sodium Sodium
Spectrum Fast Fast Fast
Load factor (%) 85 85 85
efpd 4*456 5*410 5*340
Efficiency (%) 40 40 40
Burn-up (GWd/tHM) 60 100 136
HM mass (tons) ca.50 ca.75 ca.45
Power density (kgHM/MWe) 83.3 52.1 31.0
Fuel Volume Fraction (%) 30.7 52.4 43.7
Fissile content (%) 16.4 15.6 21.5
BR ca.1.01 ca.1.03 ca.1.02
Fuel (geometry) MOX(HEX,z) MOX(HEX,z) MOX(HEX,z)
Table 5.1: Main characteristics of Fast Reactors
The data listed in Table 5.1 are directly used as the input in COSI6 code. The other needed data, as one group equivalent burn-up dependent cross-sections are provided by the libraries generated. The description of the neutronic models for obtaining the suitable COSI6 libraries is included in Appendix D.