A Computational Fluid Dynamics Simulation Study on the Variation of Temperature and Pressure in the Container During the Dry Storage Process of Radioactive Metal Oxides

Abstract

Radioactive metal oxides are highly radioactive, hygroscopic spent fuel reprocessing products generally stored in container-sealed dry storage. During the storage process of metal oxides, a large amount of heat is generated due to radioactive decay, and helium is produced by α-decay, which leads to an increase in the temperature and pressure of the storage container. In order to ensure the safety of the radioactive metal oxides in the long-term storage process, computational fluid dynamics simulations are used to investigate the effects of storage conditions on the temperature and pressure of the container. Based on a large amount of simulated temperature data under different storage conditions, a power function is used to construct a mathematical model of ventilation speed, ventilation temperature, stack density, loading volume, heating power, water content, and cumulative helium mass versus metal oxide temperature to obtain a safe, reliable, and economical storage method. The results show that reducing the loading volume and increasing the density of metal oxides, increasing the ventilation speed, and lowering the ventilation temperature are beneficial to the heat transfer and cooling in the dry storage process; increasing the density of metal oxides and lowering the water content of metal oxides and increasing the ventilation temperature and speed are beneficial to avoid the high pressure inside the container. Based on the optimized storage conditions, the temperature peak in the storage process occurs near 25 years, and its temperature reaches 527.6 K. The mathematical model of storage temperature constructed in this study has high computational accuracy, and the maximum relative error of storage temperature is less than 1.80%.

1. Introduction

Radioactive metal oxides are a kind of reprocessing product of the nuclear industry and have the characteristics of high radioactivity and easy moisture absorption, etc., in which radioactive decay will continue to release a large amount of heat, α-decay generates helium, and moisture generates hydrogen due to irradiation [1,2,3,4,5]. In this regard, the nuclear industry generally adopts special storage containers to store them in a hermetically sealed manner [6]. The release of heat and the generation of hydrogen and helium during the storage phase of this metal oxide lead to an increase in the temperature and pressure of the container, which poses a more significant challenge for its safe storage.

There have been many reports on simulation studies in the field of nuclear energy concerning the decay heat export process during the storage of spent fuel. Bae studied temperature changes during the dry storage of multiple spent fuel rods under the effect of additives and found that the addition of additives can significantly benefit the cooling down of spent fuel during dry storage [7]. Benavides’ computational fluid dynamics approach to studying the influence of the gap between the inner and outer containers on the export of decay heat during dry storage of spent fuel showed that the size of the gap between the inner and outer containers not only affects the temperature distribution but also affects the temperature distribution of decay heat, which is the most important factor in the dry storage of spent fuel [8]. Zuo studied the heat transfer process of the QM400 spent fuel dry storage equipment at Qinshan Nuclear Power Station in the third phase and found that the heat transfer process involves natural convection, heat conduction, and coupled heat transfer and thermal radiation, and the simulation results match well with the experimental data [9]. Tseng numerically investigated the heat transfer performance of a new tubular dry storage system in storing 61 spent fuel rods using computational fluid dynamics [10]. Wang investigated the airflow pattern as well as the heat transfer characteristics during the dry storage of spent fuel using wind tunnel experiments and computational fluid dynamics [11]. The above spent fuel decay heat calculation objects are spent fuel elements unloaded from nuclear power plants, the energy of which is relatively low. After the reprocessing of spent fuel, radioactive metal oxides with high energy density are obtained, which have high energy density and more stringent storage conditions. Since there are only nine countries that have mastered the technology of spent fuel reprocessing, they are France, Russia, the UK, India, Japan, the United States, Belgium, Germany, and China. As a product of spent fuel reprocessing metal oxides, few studies have been reported. At present, except for the DOE-STD-3013-2012 standard [12] of the U.S. Department of Energy, which consists of theoretical calculations and experimental monitoring of the temperature of the dry storage of plutonium dioxide, there is no report on CFD simulation of the change rule of the temperature of the dry storage container of metal oxides. The U.S. Department of Energy (DOE) has used theoretical calculations to roughly evaluate the storage temperature and pressure of metal oxides, and experimental monitoring is only one-sided storage conditions.

In order to realize the safe storage of radioactive metal oxides, this study adopts a numerical model to verify the reasonableness of the container and explore the influence of the storage conditions on the container temperature and pressure based on its storage characteristics. Based on a large number of simulated temperature data under different storage conditions, the power function mathematical model is used to construct a mathematical model of the relationship between the ventilation air velocity, ventilation temperature, stack density, loading volume, heating power, water content, and the cumulative mass of helium and the temperature of the metal oxides. Oxide temperature is used to obtain a safe, reliable, and economical storage method.

2. Calculation Conditions and Methods

2.1. Radioactive Metal Oxide Storage Containers

The storage containers for metal oxides are shown in Figure 1. The metal oxides are loaded into the inner container, and the sealing of the inner container is realized through threading. Five inner containers are loaded into one outer container, and then the sealing of the outer container is realized through welding. Inner containers are numbered 1 to 5 from top to bottom. The inner and outer containers are made of 304 stainless steel, with an inner container size of Φ 150 mm × 180 mm and an outer container size of Φ 210 mm × 1175 mm. The inner container has a volume of about 2.255 L, the designed filling capacity is 3.0 kg, and the actual filling capacity is between 2.6 and 3.2 kg.

2.2. Materials and Their Properties

Radioactive metal oxides consist of five isotopes with a density of 11,460 kg/m³. The average metal content in 1 kg of the metal oxide is about 0.8822 kg. The power of heat release from the metal oxide due to radioactive decay and the cumulative amount of helium produced due to α-decay are shown in Figure 2.

The density, specific heat, thermal conductivity, viscosity, and radiation coefficient of the material all affect the heat transfer of metal oxides. The densities of air, hydrogen, and helium were calculated at 308 K at atmospheric pressure. Considering that the storage temperature is mainly around 500 K, the specific heat, thermal conductivity, and viscosity of the three gases are calculated at 500 K. The specific heat and thermal conductivity of the metal oxides were calculated based on the formulas reported in the literature [11], as shown in Equations (1) and (2). λ, A_m, N_p, C_p, and T are thermal conductivity (W/m·K), elemental mass content, mass content, specific heat (J/kg·K), and absolute temperature (K), respectively. According to the literature, the Am content in metal oxides is low, about 0.0006~0.0026 [13,14,15]. Stainless steel 304 belongs to the nickel-chromium alloy, and its radiation coefficient is taken as a median of 0.45, according to the radiation coefficient range of frosted nickel-chromium alloy, 0.3~0.6. The physical property data used in this study are shown in

Table 1. Physical property data.

	Air	Water Vapor	Hydrogen	Helium	304 Stainless Steel	Radioactive Metal Oxides
Density (kg/m3)	1.146	0.71223	0.080	0.158	7900	11,460
Specific heat (J/kg·K)	1030	2984	14,520	5193	500	297
Thermal conductivity (W/m·K)	0.0407	0.0436	0.266	0.22	18	7
Viscosity (Pa·s)	2.7 × 10−5	1.67 × 10−5	1.26 × 10−5	2.83 × 10−5	/	/
Emissivity	/	/	/	/	0.45	/

.

λ(W/m·K) = (0.3583 A_m + 0.06317 N_p + 0.01595 + 0.0002494 T)⁻¹

(1)

C_p (J/kg·K) = 68,061,313.87 e^474.5/T/[T²(e^474.5/T−1)² + 0.03408 T]

(2)

2.3. Simulation of Areas and Meshing

Based on the container storage method, the space area for numerical simulation was defined as 2000 mm × 2000 mm × 2000 mm, and the outer container was placed in the center of this area. In order to facilitate the production of high-quality meshes, the storage containers were regularized while maintaining the effective volume of the inner storage containers, and the air between the inner and outer containers was also regularized. The wall thickness of the inner container was regularized as a 4 mm cylinder, and the five inner containers were placed in the outer bottle in the form of a top and bottom stack. In order to reduce the number of grids and the workload of simulation calculation, according to the principle of symmetry, the simulation area is halved, and the corresponding containers are cut in half vertically from the center of the axis so that the corresponding gridding and simulation calculation area coordinates range from X = −1000 mm~1000 mm, Y = 0 mm~1000 mm, and Z = −1000 mm~1000 mm. The meshes and mesh sensitivity analysis are shown in Figure 3, and the maximum temperature of the metal oxides inside the five inner containers (storage conditions: cooling air temperature 308 K, storage for 25 years) is used as an index for the sensitivity analysis of the number of meshes. The results show that when the number of meshes reaches about 550,000, the temperature change of the metal oxides inside the five inner containers is insensitive. Therefore, the number of hexahedral meshes used in this paper is 556,607, and the maximum mesh skewness is 0.4153.

2.4. Calculation Method and Boundary Conditions

Fluent 15.0 software was used for the calculations in this study. The mass transfer model was used, and the DO radiative heat transfer model was turned on by considering component diffusion and heat diffusion. The external environment of the storage vessel is mechanically ventilated, the k-ω turbulence model is used, and the laminar flow model is used for the gas flow in the outer vessel and inner vessel. The heat transfer process in this study involves natural convection, forced convection, heat conduction, and thermal radiation heat transfer (the relevant governing equations are shown in Appendix A). The charging space of the metal oxide is set to the porous media area, the porous medium solid is the metal oxide, and the void is a mixture of air, hydrogen, and helium. The porosity of the porous medium is determined by the mass of the metal oxide charge, the density of the metal oxide, and the effective volume of the inner container. The viscous resistance (symbol 1/α, unit 1/m²) and inertial resistance (symbol C, unit 1/m) in the porous media region were estimated according to Ergun’s empirical formula.

The heat released from the decay of the metal oxides is added to the charging area of the inner packaging through an energy source term (N) in W/m³. The energy source term is calculated based on the charging mass of the metal oxide (m in kg), the volume of the charging area (V in m³), and the heating power (P in W/kg) corresponding to the year of storage of the metal oxide in this simulation; its calculation formula is shown in Equation (3), where 0.8822 is the conversion factor of the mass of the metal oxide to the mass of the metal.

N = 0.8822 mP/V

(3)

The outer container is placed vertically. Horizontal ventilation means that the cooling air is blown from the side of the outer vessel, while vertical ventilation means that the cooling air is ventilated upward from the bottom of the outer vessel. The ventilation inlet is the velocity inlet, while the air outlet is the pressure outlet; the XZ profile of the simulation area is set as the symmetric surface, and the remaining external surface of the air is set as the adiabatic wall. The heat transfer at the air-solid interface is set as the coupled heat transfer mode, and the material of the vessel wall is set as stainless steel, with its corresponding radiation coefficient set as 0.45. The density of the gas mixture in the inner vessel is calculated according to the total mass of air, hydrogen, and helium, along with the volume of the inner vessel. Then, the density data are imported through the UDF. The mass of the three gas mixtures is distributed directly into the inner vessel after initialization based on the mass fraction of each gas.

This simulation requires the determination of both temperature and pressure data. The floating operating pressure setting and the unsteady state simulation method can be used to calculate temperature and pressure data. However, this method requires too much computation and is very time-consuming. For this reason, this simulation first uses the steady-state simulation method to obtain reasonable temperature data. Then, it calculates the pressure based on the amount of gas substance, temperature, space volume, and gas equation of state. The above method can greatly reduce calculation time and, at the same time, can ensure the accuracy of the calculated temperature and pressure data. Based on a large number of temperature data obtained under different storage conditions, a power function empirical mathematical model was used to construct mathematical relationships between the gas velocity, cooling air temperature, stack density, loading volume, heating power, water content, and cumulative mass of helium and various temperatures, and to obtain the model parameters in order to provide mathematical tools for the calculation of temperatures and pressures after changes in metal oxides and storage conditions in engineering applications.

The influencing factors examined in this study include the cooling air ventilation method, the cooling gas ventilation rate, the cooling gas temperature, the inner container filling mass, the heat release power of the metal oxides, the metal oxide water content, the helium cumulant mass, and the stack density of the metal oxide filling. Due to the limitation of the single factor, the maximum temperatures of metal oxides were calculated for 188 sets of different storage conditions, and a power function form was used to construct mathematical models for temperature and seven factors.

For the accounting of gas pressure, the ideal gas equation of state, the van der Waals equation, and the RK equation can calculate the pressure change data of mixed gases, and the errors between them are small so that the calculation of the pressure of mixed gases can meet the requirements of calculation accuracy. In order to facilitate the calculation, the ideal gas equation of state is used in this study for gas mixture pressure accounting.

3. Results and Discussion

3.1. Effect of Ventilation Process Parameters on the Temperature of Radioactive Metal Oxides

Figure 4 shows the effect of the ventilation method and air velocity on the maximum temperature of metal oxides at a ventilation temperature of 308 K for an inner container filled with 3 kg of metal oxides with a moisture content of 0.5% and a stack density of 2200 kg/m³ for 25 years of storage. The temperature decreases with increasing cooling air velocity for horizontal and vertical ventilation. It indicates that increasing the cooling air intake velocity favors the cooling of metal oxides. At high cooling air velocities (0.7 m/s and 0.9 m/s), the cooling effect of vertical ventilation on metal oxides is better than that of horizontal ventilation; when the air velocity is equal to or less than 0.5 m/s, the difference between the cooling effect of horizontal and vertical ventilation is not apparent.

In order to clarify the temperature distribution inside the storage vessel, Figure 5 shows the temperature cloud for a lateral wind speed of 0.5 m/s. The top and bottom inner containers are cooled by heat transfer more quickly than the middle three containers, resulting in significantly lower temperatures in the top and bottom inner containers than in the middle three inner containers, where the temperature of the middlemost container is the highest, at about 512 K. The temperatures in the area where the metal oxide particles are in contact with the wall surface of the charging bottle are lower than those in the center area since the heat transfer effect makes it easier for heat to be transferred out of the vicinity of the wall surface. The heat in the center region is more challenging to transfer.

The effect of ventilation gas temperature on the temperature of the storage vessel is shown in Figure 6, which demonstrates the maximum temperature of metal oxides stored for 25 years in each of the five inner containers at ventilation temperatures from 298 K to 323 K, respectively. The maximum temperatures of metal oxides keep increasing linearly with the increase in ventilation gas temperature. When the ventilation temperature is lower than 308 K, due to the low ventilation temperature, the outermost container dissipates heat quickly, and the heat is conducted from the middlemost container to the two ends, which is manifested as the highest temperature of the middlemost container. When the ventilation temperature is greater than or equal to 313 K, the heat dissipation of the outermost container is not effective, resulting in the middle three containers reaching thermal equilibrium.

3.2. Effect of Metal Oxide Filling and Moisture Content on Temperature

Figure 7 shows the maximum temperature of metal oxides with 0.5% water content stored for 25 years at a gas velocity of 0.5 m/s and an air temperature of 308 K. The temperature of the metal oxides is shown in the figure. The more the container is filled with metal oxides, the higher its temperature, with the maximum temperature occurring in the third container. As the mass of the metal oxide is larger, its heat generation is larger. Under the same storage conditions, the transfer of energy becomes more difficult with the increase in the mass of the filling, which ultimately leads to an increase in the temperature of the metal oxide.

Water in metal oxides is converted to water vapor at high temperatures, and water vapor is converted to hydrogen in a radiation environment. When the metal oxide is dry, 1 kg of the metal oxide produces about 0.00495 mL to 0.01021 mL of hydrogen per day; when the relative humidity of the water vapor is 50%, 1 kg of the metal oxide produces about 0.00911 mL to 0.18333 mL of hydrogen per day. When 3 kg of the metal oxide has a water content of 0.5%, the mass of the water is 15 g, and the corresponding standard volume of hydrogen gas is about 18,666.7 mL. According to the upper limit of the rate of hydrogen produced by irradiation under dry conditions, it takes about 1669 years to irradiate water into hydrogen completely; according to the maximum rate of hydrogen produced by irradiation when the relative humidity of water vapor is 50%, it takes about 93 years to irradiate into hydrogen completely. This shows that it takes a long time for water to be converted entirely to hydrogen due to the irradiation of metal oxides. Since it is difficult to characterize the amount of water vapor and hydrogen produced quantitatively, we calculated the temperature distribution in two states, where water vapor is completely converted to hydrogen and is not converted to hydrogen at all. As shown in Figure 8, when 0.5% water in the metal oxide is completely converted to water vapor, the heat transfer effect is better than the conversion to hydrogen. The temperature difference between the two cases can be up to 64.5 K. This is due to the absorption ability of water vapor for infrared wavelengths, which leads to the fact that the water vapor can absorb radiative heat transfer, which is conducive to enhancing the heat transfer effect of the gas mixture on the heat production of the metal oxide.

Since the irradiation of water into hydrogen is more unfavorable to the storage of metal oxides, according to the conservative principle, we assume that all the water in the metal oxides is irradiated into hydrogen and carry out the calculation of the temperature of the metal oxides with a water content of 0.5~1.5% stored for 25 years, in which the other boundary conditions are as follows: transverse air velocity of 0.5 m/s, air temperature of 308 K, loading of 2.8 kg, and the density of the heap is 1331 kg/m³. The results of the computational fluid dynamics simulation are shown in Figure 9. The temperature of the metal oxide decreases with the increase of water content. The temperature of the metal oxide with 1.5% water content is 15.7 K lower than that of the metal oxide with 0.5% water content, which is mainly due to the fact that hydrogen generated by water irradiation has a better heat transfer property than that of air and helium.

3.3. The Effect of Storage Year and Bulk Density on Temperature

Figure 10 shows the temperature variation with time during storage of metal oxides with 0.5% water content at a gas velocity of 0.5 m/s, an air temperature of 308 K, and a pile density of 1331 kg/m³. Temperature variations in all inner containers showed an increase and then a decrease, with the peak time occurring in the 25th year. The temperature variation with time can be regressed using a 5th-order polynomial, and the model parameters are shown in

Table 2. Five polynomial parameters.

Number	a0	a1	a2	a3	a4	a5
1	489.3	2.038	−6.98 × 10−2	9.79 × 10−4	−7.16 × 10−6	2.14 × 10−8
2	502.7	2.167	−7.41 × 10−2	1.05 × 10−3	−7.74 × 10−6	2.35 × 10−8
4	506.1	2.184	−7.45 × 10−2	1.04 × 10−3	−7.59 × 10−6	2.26 × 10−8
4	501.9	2.145	−7.26 × 10−2	9.97 × 10−4	−7.10 × 10−6	2.06 × 10−8
5	486.7	2.001	−6.80 × 10−2	9.43 × 10−4	−6.80 × 10−6	2.01 × 10−8

. The polynomials are shown in Equation (4), where a₀, a₁, a₂, a₃, a₄, and a₅ are polynomial coefficients and n is the year.

T = a₀ + a₁n + a₂n² + a₃n³ + a₄n⁴ + a₅n⁵

(4)

The tightness of metal oxide stacking in the vessel mainly affects the thermal conductivity and heat transfer. In order to investigate the effect of stacking density on heat transfer, the lower region of each inner container was therefore partitioned and gridded according to different stacking densities (2200 kg/m³, 2500 kg/m³) corresponding to the loading height. Under normal storage conditions (air velocity of 0.5 m/s, air temperature of 308 K, and moisture content of 0.5%), simulations were performed to calculate the temperature trends as the storage year changed. Figure 10 and Figure 11 show the variation of metal oxide temperature with time for heap densities of 1331 kg/m³, 2200 kg/m³, and 2500 kg/m³, respectively. The temperature corresponding to the heap density of 1331 kg/m³ is obviously higher than that at other heap densities, while the difference between the mutual temperatures of the heap densities of 2200 kg/m³ and 2500 kg/m³ is less obvious. The metal oxides showed the highest material temperatures in the third inner container under normal dry storage conditions, with peak temperatures occurring near the 25th year at a maximum of 527.6 K.

3.4. Construction of a Mathematical Model of Temperature Power Function

Although the above study can show the trend of the influence of individual factors on the temperature of metal oxides, it is not comprehensive enough, and its application in practice is not convenient enough. For this reason, in this study, based on 188 sets of simulated temperature data (188 sets of data are shown in Appendix B) under lateral ventilation conditions, the power function form is used to construct the mathematical model of temperature and seven factors (air velocity, air temperature, loading volume, moisture content, heating power, stack density, and cumulative helium volume). The power function is shown in Equation (5). T, x₁, x₂, x₃, x₄, x₅, x₆, and x₇ denote the absolute temperature (K), gas velocity (m/s), charge (kg), heating power (W/kg), water content (%), air temperature (K), accumulated helium amount (mol/kg), and the heap density of the metal oxides (g/cm³), respectively, and b₀~b₇ are the model parameters. Since the power function independent variable cannot be zero, the independent variable for the accumulated helium amount is represented in the form of plus one.

T = b₀x₁^b1x₂^b2x₃^b3x₄^b4x₅^b5(1 + x₆)^b6x₇^b7

(5)

The parameters b₀~b₇ of the power functions for various temperatures can be obtained using the nonlinear optimization technique in Matlab R2020a software. The optimized model parameters for various temperatures are shown in

Table 3. Parameters of the temperature exponentiation function model.

Number	b0	b1	b2	b3	b4	b5	b6	b7
1	1.40 × 101	−3.49 × 10−2	2.25 × 10−1	3.07 × 10−1	−1.67 × 10−2	4.01 × 10−1	−1.33 × 10−1	−3.14 × 10−2
2	1.70 × 101	−3.55 × 10−2	2.33 × 10−1	3.15 × 10−1	−1.73 × 10−2	3.66 × 10−1	−1.39 × 10−1	−5.08 × 10−2
4	1.95 × 101	−3.52 × 10−2	2.40 × 10−1	3.18 × 10−1	−1.64 × 10−2	3.41 × 10−1	−1.35 × 10−1	−6.00 × 10−2
4	1.61 × 101	−3.58 × 10−2	2.33 × 10−1	3.15 × 10−1	−1.75 × 10−2	3.76 × 10−1	−1.34 × 10−1	−6.46 × 10−2
5	1.59 × 101	−3.54 × 10−2	2.26 × 10−1	3.04 × 10−1	−1.69 × 10−2	3.81 × 10−1	−1.32 × 10−1	−8.58 × 10−2

, and the statistical analysis data for the power function are shown in

Table 4. Statistical analysis of power function models.

Number	P2	F	10FT	R2	Mean Relative Error	Maximum Relative Error
1	0.9999	1,076,718	19.9	0.987	0.32	1.49%
2	0.9999	936,846	19.9	0.987	0.35	1.50%
4	0.9999	902,949	19.9	0.987	0.35	1.80%
4	0.9999	838,227	19.9	0.986	0.36	1.59%
5	0.9999	769,284	19.9	0.986	0.38	1.76%

. According to the statistical parameters of the model in Table 4, the statistical data of the model parameters corresponding to various temperatures can prove that the power function model is suitable. All of them satisfy the judgment criteria of P2 > 0.9 (more significant than 0.9999) and F > 10 FT (=19.9). The correlation index R² of the temperature power function model is more significant than 0.986, the average relative error between the calculated value of the temperature model and the simulated value is less than 0.38%, and the maximum relative error between the calculated value of the power function model and the simulated value is less than 1.80%. The effect of the simulated calculated temperature and power function model calculated temperature is shown in Figure 12a–e. Both the model statistics and the simulated regression effect of the data proved that the temperature power function influence model proposed in this study has good accuracy and can be used for temperature calculation in practical work.

According to the positive and negative relationship between the values of the model parameters, it can be seen that the increase in ventilation air velocity is conducive to reducing the temperature of metal oxides; the reduction of ventilation temperature is conducive to the cooling of metal oxides; an appropriate increase in the water content is conducive to the heat transfer of metal oxides; the increase in the density of metal oxides is conducive to the heat transfer and cooling; the increase in the cumulative helium substance is conducive to the cooling of metal oxides; the higher the amount of loading is, the more unfavorable is the cooling and heat transfer; the higher the power of heat generation is, the less favorable is the cooling of equipment and materials. The higher the heating power of the metal oxide, the more unfavorable it is for cooling.

3.5. The Pressure of the Storage Vessel Changes Regularly

Figure 13 shows the trend of the gas pressure in the inner vessel with time during storage for metal oxides of different stack densities. The continuous generation of helium from the decay of the metal oxides during storage does not decrease gas pressure even after the temperature peak has passed during storage. At the exact moment, containers with higher temperatures have higher internal pressures. Since the different stack densities of the metal oxide charge result in different heat transfer of the material, the higher the stack density, the lower the average temperature of the material, so the pressures at the other stack densities (2000 kg/m³, 2200 kg/m³, and 2500 kg/m³) are relatively low compared to the pressure at the 1331 kg/m³ stack density. The maximum pressure in year 0 is about 17.5 to 18.3 atm, and in 100 years of storage, the maximum pressure is about 24.5 to 25.6 atm.

4. Conclusions

In this study, the computational fluid dynamics method was used to study the temperature and pressure changes of radioactive metal oxides during long-term storage, and the influence of storage conditions on the temperature of metal oxides was determined.

The simulation results show that increasing the gas velocity, reducing the air temperature, reducing the amount of material, increasing the bulk density, and having the appropriate amounts of moisture content and cumulative helium content are conducive to the heat transfer and cooling of metal oxides in the dry storage process. The increase of the moisture content of metal oxides is very obvious to the increase of container pressure, and the moisture content needs to be strictly controlled in the actual storage process to avoid excessive container pressure and hazardous events. Based on the optimized storage conditions, the temperature peak during storage occurred around 25 years, and its temperature reached 527.6 K.

The parameter optimization results and statistical analysis of the power function model show that the mathematical model has good reproducibility of the CFD simulation results, and the maximum relative error of temperature is less than 1.80%. These mathematical models can be used to estimate temperature data during the dry storage of radioactive metal oxides and to calculate the trend of the pressure of the charging vessel based on the temperature, the amount of gaseous mixture, and the volume of the container.