Abstract
It is essential for the safety assessment of a repository to analyze the release and transport of radionuclides from the near-field to the geosphere and subsequently to the surface environment. A new model has been developed in COMSOL Multiphysics based on input data from the safety case for the disposal of spent nuclear fuel at Olkiluoto. Complex processes, for example, nuclide decay, material corrosion, diffusion, sorption, and advection, are coupled in COMSOL Multiphysics. Under reasonable assumptions, the release rates of C-14, Cl-36, I-129, Cs-135, and Ni-59 are compared with results from simulations by GoldSim. Higher release rates are observed for these five isotopes. This discrepancy may arise from two factors. On the one hand, an excessively coarse grid in GoldSim enhances nuclide transport properties, leading to a greater accumulation of nuclides in the buffer in areas below the failed canister. On the other hand, important information is omitted in the 2D model. This suggests that the release rates calculated by GoldSim may require reconsideration. Although higher release rates were confirmed in this 3D model, the release rates of Tc-99, Np-237, Pu-239, and Pu-242 remain at low levels after 106 years (the timeframe for safety assessment in Finland and Sweden). Further development is possible in COMSOL Multiphysics, such as the replacement of spent fuel with vitrified glass and the implementation of a chemical reaction module. With this new model, greater confidence is achieved in the calculation of radionuclide release and transport. This is crucial for the safety assessment of repositories.
1 Introduction
Due to the long-lived radioactivity and mobility potential of key radionuclides, the safe disposal of high-level radioactive waste (HLW) and spent nuclear fuel (SNF) in deep geological repositories (DGRs) remains a central challenge in nuclear waste management (Apted and Ahn, 2017). Geological disposal concepts are internationally accepted, in which a multi-barrier system integrating engineered barriers, such as waste matrix, containers, and buffer/backfill materials, with the natural geological rocks is proposed to isolate radionuclides for time scales up to 106 years (Kuhlman et al., 2024; Lee et al., 2023; McCartin et al., 2020; Pereira and Koppe, 2025). It is a critical prerequisite for a repository that the quantitative simulation of radionuclide, activity, or dose release from the near-field to the far-field and their subsequent transport in the surface environment and eventually exposure to human beings is validly calculated. However, the inherently complex processes, for instance, engineered barrier degradation, geochemical interactions, and transport processes, jointly render such quantitative simulation a significant challenge. Reactive transport modeling, which couples groundwater flow, solute transport, and reaction kinetics, offers a powerful framework for evaluating these processes under evolving repository conditions. Such models have been applied to investigate near-field release and retention in systems including clay and crystalline host rocks (de Vries et al., 2014; Grandia et al., 2007; Joyce et al., 2015; Lee Hartley et al., 2015; Schwartz, 2012), highlighting the importance of sorption, diffusion, and barrier integrity on radionuclide migration (Fredrik, 2008; Piqué et al., 2013).
Extensive simulations of radionuclide release are performed using a case study approach for the safety assessment of a repository in Finland and Sweden (Hedin and Andersson, 2014; Posiva, 2012a). Processes, events, and features are well defined and carefully evaluated. Radionuclide release was computed with the REPCOM code (Nordman and Vieno, 1994; Nordman and Vieno, 2003; Vieno and Nordman, 2000) at the very beginning. Due to its overly conservative estimation and the lack of clarity of the user interface, most simulations are now performed with MARFA (Painter and Mancillas, 2013; Poteri and Posiva, 2007) and GoldSim (Smith et al., 2012). This article presents a new model for near-field radionuclide release in a geological repository developed in COMSOL Multiphysics, aiming to make the estimates as realistic as possible while maintaining conservatism. The objective is to improve predictive capability for safety assessments and provide cross-verification for the calculation results. All the processes, events, and features are kept the same as in the reference case in the safety case for the disposal of spent nuclear fuel at Olkiluoto. These parameters are discussed in detail in the following context. The release rates of Tc-99, Np-237, Pu-239, and Pu-242, which are of concern in many research involving repository environment, are discussed and are observed at low levels at 106 years (the timeframe for safety assessment), although they continue to increase until 107 years.
2 Methods
2.1 Conceptual model
Radionuclide release is calculated by coupling corrosion, radionuclide decay, diffusion, sorption, and advection in COMSOL Multiphysics (Faisal et al., 2020), which is a leading and advanced multiphysics coupling simulation platform for modeling the interactions of different physical phenomena. The general assumptions remain the same as those discussed in the safety case for the disposal of spent fuel at Olkiluoto by Posiva (2012A), for instance, the location of the repository is maintained over several million years, the canister remains located coaxially with the deposition hole with no significant sinking, and criticality does not occur. The conceptual model is kept the same as well and is described in detail in the safety case study at Olkiluoto (Posiva, 2012a). In brief, the simulated scenario involves radionuclides released from a reference spent fuel, dissolving in water inside the canister, diffusing through an initial defect and transporting through the defective hole, bentonite buffer, and backfill materials to three possible fractures (as shown in Figure 7-1 in Posiva (2012a), or in Supplementary Figure S1), which are flow paths defined by groundwater flow modeling (Hartley et al., 2013; Löfman and Karvonen, 2012). The time required for establishing a stable transport path is assumed to be 1000 years. The dominant processes are diffusion in the canister, diffusion and sorption in the buffer, and diffusion, sorption, and advection in the backfill materials. Radionuclide decay occurs in all near-field domains, while it is not considered in the source term.
The Transport of Diluted Species in Porous Media module is used for radionuclide release calculation in COMSOL Multiphysics. Mass conservation is applied in each computational cell or point, as illustrated in Equations 1–3.
In Equations 1–3, ci is the concentration of nuclide i; t is the simulation time; ɛp is the porosity of materials. The first term in Equation 1 stands for nuclide concentration changes; the second term represents sorption by solid material P, becoming Equation 2 with further derivation; KP,i refers to the distribution coefficient Kd in sorption experiments. The third and fourth terms in the equation stand for diffusion, dispersion, and advection. The other two terms on the right side refer to the reaction for removing nuclide calculation volume and the source term for producing more nuclide.
2.2 Geometry
First, to compare the simulated result with the safety case study, a 2D model was described as in the safety case study. The 2D geometry of the simulated near-field is shown in Figure 1. All geometric parameters are kept the same as in the safety case study at Olkiluoto (Posiva, 2012b) and are also listed in Supplementary Table S1. A 3D geometry of the near-field is set up with the same parameters, as shown in Figure 2. The spent fuel is represented as a cylinder encompassed by a hollow cylinder with a thickness of 0.05 m, representing the canister. An initial defect is located close to the top of the canister. The buffer is divided into three parts. However, the damaged zone is considered differently. Two cylindrical rings are used, with internal and external diameters of 1.75 m and 1.85 m, respectively. The smaller one represents the intersection with the fracture, and the other represents the damaged zone around the deposition hole. A large diffusion coefficient is assigned to the damage zone to ensure thorough mixing, which corresponds to the mixed zone in the safety case study.
FIGURE 1
FIGURE 2
2.3 Source term
Consistent with the safety case, the source term of radionuclide inventory inside the spent nuclear fuel is assigned to four characteristic locations: the spent fuel matrix, void spaces in the fuel rod (referred to as the instance release fraction (IRF) in the safety case), zirconium alloys, and other metal parts. Based on the assumption of stable homogeneous corrosion, the corrosion rates of the fuel matrix, zirconium alloys, and other metals are estimated as 10–7 1/a (Röllin et al., 2001; Serrano-Purroy et al., 2012), 10–4 1/a (Shoesmith and Zagidulin, 2011), and 10–3 1/a (King, 2010), respectively. In this study, a reference spent fuel is used. The reference fuel with an average uranium content of 2 tonnes was estimated by Anttila (2005a); Anttila (2005b). The inventories and distributions of C-14, Cl-36, I-129, Cs-135, Ni-59, Tc-99, Np-237, Pu-239, and Pu-242 are summarized in Table 1 (Posiva, 2012a). These radionuclides are estimated to be the main contributors to activity or dose release from the near-field. Tc-99 and Np-237 are two other radionuclides of concern in a repository environment.
TABLE 1
| Radionuclide | Species | Half-life (a) | Molar mass (mol/tU) | Partitioning of activity (%) | |||
|---|---|---|---|---|---|---|---|
| Fuel matrix | IRF | Zirconium alloy | Other metal | ||||
| C-14 | C(IV) | 5.70 × 103 | 7.98 × 100 | 0.0 | 0.0 | 0.0 | 100.0 |
| Cl-36 | Cl(−I) | 3.01 × 105 | 1.52 × 10−1 | 0.0 | 0.0 | 100.0 | 0.0 |
| I-129 | I(−I) | 1.57 × 107 | 1.87 × 100 | 95.0 | 5.0 | 0.0 | 0.0 |
| Cs-135 | Cs(I) | 2.30 × 106 | 1.92 × 101 | 95.0 | 5.0 | 0.0 | 0.0 |
| Ni-59 | Ni(II) | 7.60 × 104 | 1.21 × 102 | 0.0 | 0.0 | 0.0 | 100.0 |
| Tc-99 | Tc(IV) | 2.11 × 105 | 8.48 × 102 | 98.8 | 1.0 | 0.0 | 0.2 |
| Np-237 | Np(IV) | 2.14 × 106 | 2.37 × 101 | 100.0 | 0.0 | 0.0 | 0.0 |
| Pu-239 | Pu(III, IV) | 2.41 × 104 | 1.42 × 104 | 100.0 | 0.0 | 0.0 | 0.0 |
| Pu-242 | Pu(III, IV) | 3.75 × 105 | 2.17 × 102 | 100.0 | 0.0 | 0.0 | 0.0 |
Inventory and partition of radionuclides of concern in this study.
2.4 Radionuclide migration process
Radionuclides are congruently released from different parts of the spent fuel based on their corrosion rates after groundwater ingress into the canister. The time for water ingress and filling the void space in the canister is estimated as 1000 years. Diffusion and precipitation are the dominant processes occurring inside the canister. A large diffusion coefficient is assigned to ensure radionuclides are mixed well inside the canister. Radionuclide migration through the initial defect is dominated by diffusion (it is assumed the defect is filled with groundwater). The deposition hole and tunnel are filled with buffer and backfill materials, respectively. They are assumed to be homogeneous porous media. The dominant processes in the buffer are sorption and diffusion. In addition to sorption and diffusion, advection occurs in the tunnel with a velocity of 2.65 × 10−5m/a (Löfman and Karvonen, 2012). Key parameters for sorption, diffusion, and advection are the distribution coefficient (Kd) and the effective diffusion coefficient (De). Their values are listed in Table 2. Sorption onto the buffer and backfill is assumed to be linear, meaning sorption is proportional to the concentration of radionuclides. Radionuclides are transported to the geosphere via a fracture intersecting the deposition hole and/or tunnel. In the safety case study, three paths are assumed to exist. They are denoted as the F-path, DZ-path, and TDZ-path, representing fractures intersecting the deposition near the defective location in the canister, intersecting the damaged zone around the tunnel, and intersecting the tunnel itself. These three paths are shown in the safety case study and also in Supplementary Figure S1. Radionuclides diffuse from the buffer into this damaged zone or mixed zone, and then are transported to the far-field via a fracture that intersects with the deposition hole or via the damaged zone to further fractures. Radionuclides are partitioned between these two paths. The release rate is calculated based on the relative equivalent flow rates through these three paths, that is, the relative equivalent flow rates multiplied by the concentration of radionuclides. The relative equivalent flow rates are 6.14 × 10−3 m3/a, 2.69 × 10−4 m3/a, and 2.39 × 10−3 m3/a (Löfman and Karvonen, 2012) for the F-path, the DZ-path, and the TDZ-path, respectively.
TABLE 2
| Nuclide | Kd (m3/kg) | De (m2/s) | ɛ | |||
|---|---|---|---|---|---|---|
| Buffer | Backfill | Buffer | Backfill | Buffer | Backfill | |
| C | 0 | 0 | 1.3 × 10−10 | 9.0 × 10−11 | 0.43 | 0.38 |
| Cl | 0 | 0 | 7.8 × 10−12 | 7.4 × 10−12 | 0.08 | 0.07 |
| I | 0 | 0 | 7.8 × 10−12 | 7.4 × 10−12 | 0.08 | 0.07 |
| Cs | 4.8 × 10−2 | 6.1 × 10−1 | 1.0 × 10−9 | 9.5 × 10−10 | 0.43 | 0.38 |
| Ni | 2.4 × 10−1 | 1.5 × 100 | 1.3 × 10−10 | 9.0 × 10−11 | 0.43 | 0.38 |
| Np | 6.3 × 101 | 1.1 × 102 | 1.3 × 10−10 | 9.0 × 10−11 | 0.43 | 0.38 |
| Tc | 6.3 × 101 | 1.1 × 102 | 1.3 × 10−10 | 9.0 × 10−11 | 0.43 | 0.38 |
| Pu | 9.9 × 101 | 1.9 × 102 | 1.3 × 10−10 | 9.0 × 10−11 | 0.43 | 0.38 |
Values of distribution coefficient (Kd) and effective diffusion coefficient (De) in the buffer and backfill.
3 Results and discussion
3.1 Comparison with safety case
Figure 3a shows the evolution of the calculated release rates for radionuclides C-14 and Cl-36 from the near-field in the 2D geometry. Compared with the simulated result from GoldSim in the safety case study of the reference case (Figure 3c), although the shape of the evolution of the release rate of C-14 remains almost the same, the release rate from this simulation is approximately six orders of magnitude higher. It is worth noting that discrepancies exist in the inventory of radionuclides in the reference spent fuel and their distribution inside the canister, as shown in Table 6.5 and Table 6.6 in Posiva (2012b) for the safety case study. This may introduce significant uncertainties. Therefore, a more sophisticated 3D geometry was established. The calculation result is shown in Figure 3b. Comparing the results from Figure 3b with Figure 3c, the release evolution shape in the 3D geometry is more similar to the GoldSim result than in the 2D geometry, with all input parameters kept at the same values. The release rate in the 3D geometry decreases by approximately two orders of magnitude. This suggests that important functions may not work properly or may be omitted in the 2D geometry. The 2D geometry model in COMSOL Multiphysics is not suitable for near-field radionuclide release calculation. However, the release rate calculated from the 3D geometry is still four orders of magnitude higher than that from the GoldSim calculation.
FIGURE 3
The observed discrepancy can be attributed primarily to differences in model dimensionality and grid resolution between the two simulation approaches. The simulation in GoldSim employs a relatively coarse 2D representation of the near-field geometry, with a limited numerical grid consisting of 17 cells in the vertical direction and 14 cells in the horizontal direction for the deposition hole, and 5 cells in the vertical direction and 11 cells in the horizontal direction for the tunnel (Poteri et al., 2014). This coarse discretization has a significant influence on the accuracy of the simulated transport processes. The large cell size affects the simulation results in two critical ways. First, coarse grids inherently introduce numerical dispersion, which artificially accelerates solute transport by smoothing concentration gradients and reducing the resolution of diffusion-controlled fronts. This leads to an overestimation of transport rates through the buffer and backfill materials. Second, and perhaps more importantly, the limited spatial resolution prevents accurate representation of concentration gradients near the canister defect and within the buffer, resulting in an artificial accumulation of radionuclides at the bottom of the buffer rather than allowing their proper migration toward fractures. This accumulation effectively reduces the calculated release rates to the geosphere, as radionuclides remain trapped in the buffer rather than being transported to fractures. Furthermore, the inherent limitations of a 2D axisymmetric representation cannot fully capture the three-dimensional nature of radionuclide transport pathways. In reality, transport occurs through complex 3D networks, including the azimuthal variation around the deposition hole and the intersection geometry between the buffer, damaged zone, and multiple fractures. The 2D approximation constrains transport to a single plane, potentially omitting important 3D effects such as lateral spreading and preferential pathways that would exist in a realistic repository geometry. Figure 4 illustrates the influence of cell size on the evolution of the release rate of C-14 from the near-field, demonstrating that finer grid resolutions yield different release behaviors. Given that all other assumptions and parameters are identical between the simulations, the results from COMSOL Multiphysics, which solves the full 3D transport equations with significantly higher spatial resolution, are considered more physically accurate and reliable. Importantly, the higher release rates predicted by the COMSOL model provide a more conservative estimate for safety assessment purposes, which is preferable for demonstrating repository safety as it avoids underestimating potential radionuclide releases to the biosphere.
FIGURE 4
Figure 5 shows that a large fraction of C-14 is released via the F-path. This is reasonable because radionuclides travel the shortest distance to reach the fracture intersecting the deposition hole. Only the buffer continues to immobilize radionuclides in the event of canister failure. This implies that the flow rate through the fracture is the most important factor affecting the release rate of radionuclides. The release fractions from the DZ- and TDZ-path are much smaller and depend on either the position of the fractures intersecting the tunnel and the damaged zone or the travel distance of the radionuclide.
FIGURE 5
3.2 Activity release of Np-237 and Tc-99
In the context of long-term safety assessment covering at least 1,000,000 years, radionuclides with short half-lives and/or small inventories may not have a significant effect on the total activity or dose released to the geosphere. In this study, attention is focused on the release rates of three key radionuclides in the repository environment: neptunium (Np), plutonium (Pu), and technetium (Tc). Americium (Am) is not calculated because of its short half-life. The isotopes considered are Tc-99, Np-237, Pu-239, and Pu-242. Their parameters are listed in Table 1.
As shown in Figure 6, during the entire safety assessment timeframe (106 years), the release rates of these isotopes from the near-field to the far-field remain at low levels. The release rates are in the range of 0–100 Bq/a and are almost zero before 105 years. Because Tc-99, Np-237, Pu-239, and Pu-242 are almost entirely distributed in the fuel matrix, these isotopes are assumed to be congruently released from the fuel matrix with a corrosion rate of 10–7/a. A long simulation time was used. Therefore, it is reasonable to observe their release rates reaching a maximum at 107 years. Overall, the release rates of these four isotopes are low enough to be neglected during the safety assessment period. These isotopes contained in the fuel matrix can decay over time; however, in this simulation, isotopes are assumed to exist as a source term, in which decay is not considered. This leads to overestimation of the release rate.
FIGURE 6
4 Summary
It is essential for the safety assessment of a repository to analyze radionuclide release and transport from the near-field to the geosphere and further to the surface environment. A new model has been developed using COMSOL Multiphysics based on input data from the safety case for the disposal of spent nuclear fuel at Olkiluoto, integrating complex processes such as nuclide decay, material corrosion, diffusion, sorption, and advection. Under reasonable assumptions, the release rates of C-14, Cl-36, I-129, Cs-135, and Ni-59, which are identified as the five radionuclides making the greatest contributions in the safety case, are compared with results from simulations performed with GoldSim. The release rates of Tc, Np, and Pu are further discussed. Although the release rates of these five isotopes from the near-field are higher than those calculated by GoldSim, the 2D model is confirmed to overestimate the release rates compared to the 3D model. The simulation results from GoldSim may require further consideration, as both the coarse grid size and the 2D geometry significantly influence the release of radionuclides. The release rates of Tc-99, Np-237, Pu-239, and Pu-242, which are widely investigated in the context of a repository environment, remain at low levels during the safety assessment timeframe. Further development is possible in COMSOL Multiphysics, for instance, the replacement of spent fuel with vitrified glass and the implementation of a chemical reaction module. With this new model, greater confidence is achieved for radionuclide release and transport calculations, which is crucial for the safety assessment of repositories.
Statements
Data availability statement
The original contributions presented in the study are included in the article/Supplementary Material; further inquiries can be directed to the corresponding author.
Author contributions
PC: Conceptualization, Writing – review and editing, Investigation, Writing – original draft, Validation, Data curation. QZ: Software, Investigation, Data curation, Writing – review and editing, Validation. CS: Validation, Writing – review and editing, Conceptualization, Investigation.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This work was supported as part of the release and transport behavior of radionuclide in the repository environment (Grant No.: BD21000103). Ping Chen is grateful for the support from the WU Tao Professorship at Huzhou University and the support from the editors.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnuen.2026.1798989/full#supplementary-material
References
1
AnttilaM. (2005a). Criticality safety calculations for three types of final disposal canisters.
2
AnttilaM. (2005b). Radioactive characteristics of the spent fuel of the Finnish nuclear power plants.
3
AptedM. J.AhnJ. (2017). Geological repository systems for safe disposal of spent nuclear fuels and radioactive waste. Cambridge, United Kingdom: Woodhead Publishing.
4
de VriesL.MolineroJ.EbrahimiH.SvenssonU.LichtnerP.AbarcaE. (2014). “Regional scale hpc reactive transport simulation of nuclear spent fuel repository in Forsmark, Sweden,” in SNA+ MC 2013-Joint International Conference on Supercomputing in Nuclear Applications+ Monte Carlo. Castanet-Tolosan, Occitania: EDP Sciences, 05411.
5
FaisalA. A.IbreesamM. M.Al-AnsariN.NajiL. A.NaushadM.AhamadT. (2020). COMSOL multiphysics 3.5 a package for simulating the cadmium transport in the sand bed-bentonite low permeable barrier. J. King Saud University-Science32, 1944–1952. 10.1016/j.jksus.2020.01.047
6
FredrikV. C. (2008). Near-field modelling in the safety assessment SR-Can. MRS Online Proc. Libr.1107, 665. 10.1557/proc-1107-665
7
GrandiaF.SenaC.ArcosD.MolineroJ.DuroL.BrunoJ. (2007). “Quantitative assessment of radionuclide retention in the near-surface system at forsmark,” in Development of a reactive transport model using forsmark 1.2 data.
8
HartleyL.HoekJ.SwanD.AppleyardP.BaxterS.RobertsD.et al (2013). Hydrogeological modelling for assessment of radionuclide release scenarios for the repository system 2012.
9
HedinA.AnderssonJ. (2014). “SKB's safety case for a final repository license application, the safety case for deep geological disposal of radioactive waste: 2013 state of the art,” Symp. Proc. 7-9 Oct.89–96.
10
JoyceS.ApplegateD.AppleyardP.GordonA.HeathT.HunterF.et al (2015). Groundwater flow and reactive transport modelling in ConnectFlow. Stockholm, Sweeden: SKB publications. SKB R-14–19.
11
KingF. (2010). Critical review of the literature on the corrosion of copper by water.
12
KuhlmanK. L.BartolJ.CarterA.LommerzheimA.WolfJ. (2024). Scenario development for safety assessment in deep geologic disposal of high‐level radioactive waste and spent nuclear fuel: a review. Risk Anal.44, 1850–1864. 10.1111/risa.14276
13
LeeJ.KimK.KimI.JuH.JeongJ.LeeC.et al (2023). High-efficiency deep geological repository system for spent nuclear fuel in Korea with optimized decay heat in a disposal canister and increased thermal limit of bentonite. Nucl. Eng. Technol.55, 1540–1554. 10.1016/j.net.2023.02.031
14
Lee HartleyS. J.WoollardH.MarsicN.SidbornM.GyllingB.PuigdomenechI.et al (2015). Coupled groundwater flow and reactive transport simulations of the evolution of groundwater chemistry for a deep geologic repository in shield rocks.
15
LöfmanJ.KarvonenT. (2012). Simulations of hydrogeological evolution at olkiluoto.
16
McCartinT.TadesseR.LiJ.UmekiH.Bilbao y LeonS.PalosG. (2020). Management and disposal of high-level radioactive waste: global progress and solutions. Boulogne Billancourt, France: Economic Co-Operation and Development, Nuclear Energy Afency –OECD/NEA.
17
NordmanH.VienoT. (1994). Near-field model REPCOM.
18
NordmanH.VienoT. (2003). Modelling of near-field transport in KBS-3V/H type repositories with PORFLOW and REPCOM codes.
19
PainterS.MancillasJ. (2013). MARFA user's manual: migration analysis of radionuclides in the far field. Helsinki: Posiva Oy. (Finland).
20
PereiraW.KoppeJ. (2025). Coupled thermo-hydro-mechanical analysis of a deep geological repository for final disposal of spent nuclear fuel in Brazil. Numer. Heat. Transf. Part A Appl.86, 6055–6082. 10.1080/10407782.2024.2338256
21
PiquéÀ.ArcosD.GrandiaF.MolineroJ.DuroL.BerglundS. (2013). Conceptual and numerical modeling of radionuclide transport and retention in near-surface systems. Ambio42, 476–487. 10.1007/s13280-013-0399-1
22
PosivaOy. (2012a). Safety case for the disposal of spent nuclear fuel at olkiluoto. Synthesis12, 12–17.
23
PosivaOy. (2012b). Safety case for the disposal of spent nuclear fuel at olkiluoto, assessment of radionuclide release scenarios for the repository system 2012. Synthesis12, 12–17.
24
PoteriA.PosivaOy. (2007). A concept for radionuclide transport modelling. Helsinki: Posiva Oy. (Finland).
25
PoteriA.NordmanH.PulkkanenV.-M.SmithP. (2014). Radionuclide transport in the repository near-field and far-field. Posiva.
26
RöllinS.SpahiuK.EklundU.-B. (2001). Determination of dissolution rates of spent fuel in carbonate solutions under different redox conditions with a flow-through experiment. J. Nucl. Mater.297, 231–243. 10.1016/s0022-3115(01)00645-6
27
SchwartzM. O. (2012). Modelling radionuclide transport in large fractured-media systems: the example of forsmark, Sweden. Hydrogeology J.20, 673–687. 10.1007/s10040-012-0837-3
28
Serrano-PurroyD.ClarensF.González-RoblesE.GlatzJ.WegenD.De PabloJ.et al (2012). Instant release fraction and matrix release of high burn-up UO2 spent nuclear fuel: effect of high burn-up structure and leaching solution composition. J. Nuclear Materials427, 249–258. 10.1016/j.jnucmat.2012.04.036
29
ShoesmithD. W.ZagidulinD. (2011). The corrosion of zirconium under deep geologic repository conditions. J. Nucl. Mater.418, 292–306. 10.1016/j.jnucmat.2011.07.028
30
SmithP. A.BrommundtJ.MayerG. (2012). Modelling strategy report. Helsinki: Posiva Oy. (Finland).
31
VienoT.NordmanH. (2000). Updated compartment model for near-field transport in a KBS-3 type repository.
Summary
Keywords
3D model, COMSOL Multiphysics, near-field, radionuclide release, safety assessment
Citation
Chen P, Zhang Q and Shang C (2026) Activity release calculation from the near-field of a repository for spent fuel. Front. Nucl. Eng. 5:1798989. doi: 10.3389/fnuen.2026.1798989
Received
29 January 2026
Revised
13 March 2026
Accepted
13 March 2026
Published
22 April 2026
Volume
5 - 2026
Edited by
Tao Wu, Huzhou University, China
Reviewed by
Yumeng Wang, Helmholtz Association of German Research Centres (HZ), Germany
Shuo Meng, University of South China, China
Updates
Copyright
© 2026 Chen, Zhang and Shang.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Ping Chen, chenping@ciae.ac.cn
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.