Method for evaluating corrosion life of structural materials in lead-bismuth environment
By constructing a multi-level prediction system and combining static corrosion experiments and dynamic loop simulation, the problem of corrosion lifetime uncertainty in traditional assessment methods has been solved, enabling accurate assessment of the corrosion lifetime of structural materials in lead-bismuth environments and the long-term safe operation of nuclear devices.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- TIANJIN UNIV
- Filing Date
- 2026-03-24
- Publication Date
- 2026-06-19
Smart Images
Figure CN122245556A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of nuclear reactor cooling system technology, and in particular to a method for assessing the corrosion life of structural materials in a lead-bismuth environment. Background Technology
[0002] Lead-bismuth eutectic alloys, as liquid heavy metals with excellent thermal and neutronic properties, have shown broad application prospects in fourth-generation nuclear reactors. However, corrosion of structural materials in LBE environments is one of the key challenges restricting their engineering applications. Corrosion not only leads to material performance degradation and reduced structural integrity, but may also cause serious safety hazards such as radioactive material leakage. Therefore, accurately assessing the corrosion life of structural materials in lead-bismuth environments is of great significance for ensuring the long-term safe operation of reactors.
[0003] The following problems exist: Traditional corrosion life assessments are mostly based on empirical extrapolation from short-term experimental data, failing to deeply reveal the degradation nature and dynamic evolution of materials in liquid lead-bismuth environments. This leads to significant uncertainty in the assessment results, making it difficult to reliably predict the long-term safe operation of nuclear devices. Existing technologies struggle to accurately quantify the coupled effects of temperature, oxygen concentration, flow field characteristics, and time on corrosion behavior. In particular, there is insufficient mechanistic description of the flow field-material interaction induced by high-speed flowing lead-bismuth fluid on the destruction of oxide film integrity, and a lack of profound understanding of corrosion damage behavior under multi-field coupling environments. Summary of the Invention
[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.
[0005] To solve the above problems, the present invention adopts the following technical solution.
[0006] A method for assessing the corrosion life of structural materials in a lead-bismuth environment includes the following steps: S1. Corrosion Mechanism and Kinetics Research: This study aims to reveal the degradation nature and dynamic evolution of materials in a liquid lead-bismuth environment, and to achieve a fundamental leap in lifetime assessment from empirical speculation based on short-term data to reliable prediction based on failure physics, thus laying a theoretical foundation for the long-term safe operation of nuclear devices. S2. Quantification of key influencing factors: Relying on the liquid lead-bismuth experimental loop system with precise temperature and oxygen control capabilities, the system conducts corrosion exposure experiments on candidate materials under multiple working conditions, and investigates in depth the coupled influence of temperature, oxygen concentration, flow field characteristics and time factors on corrosion behavior, so as to achieve quantitative characterization of key environmental parameters. S3. Acquisition of experimental data: By comprehensively utilizing static corrosion experiments, dynamic loop simulations, and mechanical property testing methods, key parameter data covering material corrosion kinetics, microstructure evolution, and mechanical property degradation are obtained, providing reliable data support for model construction and mechanism analysis. S4. Establishment of Corrosion Life Model: Based on experimental data, integrating the principles of multiple disciplines such as electrochemical theory, corrosion science, materials science, fluid mechanics, interface chemistry and damage mechanics, a multi-level prediction system covering empirical models, mechanism models, damage accumulation models and artificial intelligence models is constructed to achieve accurate simulation of material corrosion behavior and scientific inference of service life. S5. Determination and Standards of Safety Factor: By extrapolating and using finite element numerical simulation, the short-term data obtained from accelerated corrosion experiments are reasonably extended to the amount of corrosion damage under the reactor design life. Based on the introduction of safety margin, the candidate materials are systematically evaluated to determine whether they meet the full life service requirements, providing quantitative criteria and standard basis for the engineering application of materials.
[0007] As a further description of the above technical solution: In step S2, a quantitative correlation between temperature and corrosion reaction rate is established based on Arrhenius's law. Temperature significantly affects the corrosion behavior of materials by regulating the activation energy of interfacial reaction and the element diffusion coefficient. High-speed flowing lead-bismuth fluid can induce fluid erosion effect and interfacial mass transfer enhancement effect, further aggravating the corrosion damage rate of structural materials by destroying the integrity of the surface oxide film and accelerating the dissolution and migration of corrosion products.
[0008] As a further description of the above technical solution: In step S3, static corrosion experiments are used to obtain basic data on material corrosion kinetics under different working conditions, including corrosion rate, element-selective leaching law, and oxide film evolution characteristics; dynamic loop simulation experiments are used to reproduce the real flow service environment, revealing the dissolution, migration, and deposition behavior driven by flow velocity, temperature gradient, and local turbulence effects; and mechanical property tests are used to quantitatively characterize the degradation law of mechanical properties such as tensile, creep, fatigue, and fracture toughness of the material after corrosion, and to establish the correspondence between the degree of corrosion damage and the attenuation of mechanical properties.
[0009] As a further description of the above technical solution: In step S4, the empirical model uses the Arrhenius equation as its core to construct a mathematical relationship between corrosion rate and key parameters such as temperature, oxygen potential, and flow rate, thereby enabling rapid prediction of corrosion depth.
[0010] As a further description of the above technical solution: In step S4, the mechanism model is based on the interfacial diffusion theory and oxide layer growth kinetics to describe the nucleation, thickening, densification and damage processes of the oxide film, revealing the intrinsic mechanism of material corrosion in a lead-bismuth environment.
[0011] As a further description of the above technical solution: In step S4, the damage accumulation model comprehensively considers the reduction in effective bearing area and the increase in local stress concentration caused by corrosion thinning, and couples high-temperature creep damage, and calculates the structural failure time based on the continuous damage mechanics theory; the artificial intelligence model uses multiple sets of experimental data as training samples, and constructs a high-precision prediction model of corrosion behavior under multi-field coupling conditions through machine learning.
[0012] As a further description of the above technical solution: In step S5, the corrosion damage threshold includes the wall thickness loss limit and the oxide layer rupture limit. The wall thickness loss limit is determined based on structural strength, pressure bearing capacity, and service safety, while the oxide layer rupture limit is determined based on the failure of the surface protective film and accelerated corrosion of the substrate. The two limits together serve as the core indicators for corrosion life assessment and structural safety boundary determination.
[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) By constructing an experimental platform based on multi-scale characterization and in-situ monitoring, and combining damage mechanics model and molecular dynamics simulation, the failure mechanism of lead-bismuth corrosion and multi-field synergy is systematically identified, and the life assessment is upgraded from empirical speculation based on short-term data to reliable prediction based on failure physics, laying a solid theoretical foundation for the long-term safe operation of nuclear devices. Relying on the liquid lead-bismuth experimental loop system with precise temperature and oxygen control capabilities, this application has thoroughly investigated the coupled effects of temperature, oxygen concentration, flow field and time factors. In particular, based on the Arrhenius law, the regulation of activation energy by temperature is quantified, and the mechanism of fluid erosion and mass transfer enhancement is revealed, realizing a mechanistic description of corrosion damage behavior under the coupled effect of temperature field and flow field.
[0014] (2) By comprehensively utilizing static corrosion experiments, dynamic loop simulations, and mechanical performance tests, this application has constructed a database of key parameters covering the entire process of corrosion kinetics, microstructure evolution, and mechanical performance degradation, realizing a quantitative correlation between corrosion damage and mechanical performance degradation, and providing high-precision, multi-dimensional data support for constructing a coupled corrosion and mechanical performance degradation model; This application innovatively constructs a multi-level prediction system covering empirical models, mechanism models, damage accumulation models, and artificial intelligence models. The four models complement each other and jointly construct a full-dimensional capability from rapid assessment and mechanism analysis to life calculation and intelligent prediction, realizing accurate simulation and reproduction of corrosion behavior in complex service environments; This application systematically defines the dual threshold standard for corrosion damage. The two core indicator systems are: first, the "wall thickness loss limit" based on structural strength; and second, the "oxide layer rupture limit" based on oxide film failure. This system represents a fundamental leap from single-dimensional damage monitoring to failure early warning based on both mechanical safety and chemical protection, providing quantitative durability indicators and theoretical basis for material engineering access, screening and optimization, and standard setting. By integrating degradation kinetics extrapolation with multi-physics coupled finite element simulation, this application reasonably extends short-term accelerated corrosion data to the reactor's full-life design goals. Based on the introduction of safety margins, it systematically evaluates the long-term adaptability of materials, ultimately realizing the transformation from experimental data to quantitative criteria for engineering applications, and providing a scientific basis for determining the structural safety boundaries of lead-bismuth cooled nuclear devices. Attached Figure Description
[0015] Figure 1 This is a schematic diagram of the system architecture of the present invention. Detailed Implementation
[0016] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
[0017] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.
[0018] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments. The present invention provides the following embodiments. Example 1
[0019] Please see Figure 1This invention provides a method for assessing the corrosion life of structural materials in a lead-bismuth environment, comprising the following steps: S1. Corrosion Mechanism and Kinetics Research: This study aims to reveal the degradation nature and dynamic evolution of materials in a liquid lead-bismuth environment, and to achieve a fundamental leap in lifetime assessment from empirical speculation based on short-term data to reliable prediction based on failure physics, thus laying a theoretical foundation for the long-term safe operation of nuclear devices. S2. Quantification of key influencing factors: Relying on the liquid lead-bismuth experimental loop system with precise temperature and oxygen control capabilities, the system conducts corrosion exposure experiments on candidate materials under multiple working conditions, and investigates in depth the coupled influence of temperature, oxygen concentration, flow field characteristics and time factors on corrosion behavior, so as to achieve quantitative characterization of key environmental parameters. S3. Acquisition of experimental data: By comprehensively utilizing static corrosion experiments, dynamic loop simulations, and mechanical property testing methods, key parameter data covering material corrosion kinetics, microstructure evolution, and mechanical property degradation are obtained, providing reliable data support for model construction and mechanism analysis. S4. Establishment of Corrosion Life Model: Based on experimental data, integrating the principles of multiple disciplines such as electrochemical theory, corrosion science, materials science, fluid mechanics, interface chemistry and damage mechanics, a multi-level prediction system covering empirical models, mechanism models, damage accumulation models and artificial intelligence models is constructed to achieve accurate simulation of material corrosion behavior and scientific inference of service life. S5. Determination and Standards of Safety Factor: By extrapolating and using finite element numerical simulation, the short-term data obtained from accelerated corrosion experiments are reasonably extended to the amount of corrosion damage under the reactor design life. Based on the introduction of safety margin, the candidate materials are systematically evaluated to determine whether they meet the full life service requirements, providing quantitative criteria and standard basis for the engineering application of materials.
[0020] In step S2, a quantitative correlation between temperature and corrosion reaction rate is established based on Arrhenius's law. By revealing the regulation mechanism of temperature on the activation energy of interfacial reaction and the element diffusion coefficient, the corrosion acceleration law under the synergistic effect of thermodynamic and kinetic factors is elucidated. At the same time, by analyzing the flow field and material interaction induced by high-speed flowing lead-bismuth fluid, the mechanism of fluid erosion effect and interfacial mass transfer enhancement effect promoting the destruction of surface oxide film integrity and the dissolution and migration of corrosion products is revealed. This achieves a mechanistic description of the corrosion damage behavior of structural materials under the coupling effect of temperature field and flow field, and provides a theoretical basis for constructing a multi-field coupled corrosion prediction model.
[0021] In step S3, static corrosion experiments are conducted systematically to obtain basic data on the corrosion kinetics of materials under different working conditions, including corrosion rate, element-selective leaching patterns, and oxide film evolution characteristics. Dynamic loop simulation experiments are used to reproduce the real flow service environment, revealing the dissolution, migration, and deposition behavior of corrosion products driven by flow velocity, temperature gradient, and local turbulence effects. Mechanical property tests are used to quantitatively characterize the performance degradation patterns of the corroded material in terms of tensile strength, creep, fatigue, and fracture toughness, achieving a quantitative correlation from the degree of corrosion damage to the attenuation of mechanical properties throughout the entire process. This provides multi-dimensional and traceable experimental data support for constructing a coupled corrosion and mechanical property degradation model.
[0022] In step S4, an empirical model based on the Arrhenius equation is constructed to establish a mathematical correlation between corrosion rate and key parameters such as temperature, oxygen potential, and flow rate, enabling rapid engineering prediction of corrosion depth. A mechanistic model based on interfacial diffusion theory and oxide layer growth kinetics accurately describes the entire process of oxide film formation, thickening, densification, and failure, providing a profound understanding of the intrinsic corrosion mechanism of materials in lead-bismuth environments. A damage accumulation model is introduced, comprehensively considering the reduction in effective load-bearing area and local stress concentration caused by corrosion thinning, coupled with high-temperature creep damage, to achieve scientific calculation of structural failure time based on continuous damage mechanics theory. An artificial intelligence model using multiple sets of experimental data as training samples leverages machine learning algorithms to uncover high-dimensional nonlinear laws under multi-field coupling conditions, enabling accurate prediction of corrosion behavior in complex service environments. These four models complement each other, jointly constructing a comprehensive predictive capability system encompassing rapid assessment, mechanistic analysis, lifespan calculation, and intelligent prediction.
[0023] In step S5, by systematically defining dual threshold standards for corrosion damage, the scientific quantification of material service limits and the precise determination of structural safety boundaries are achieved. Specifically, by establishing a wall thickness loss limit based on structural strength, pressure bearing capacity, and service safety, the mechanical integrity and pressure bearing function of the material are preserved. By establishing an oxide layer rupture limit based on the failure of the surface protective film and accelerated corrosion of the substrate, the critical point of chemical protection failure of the material is identified. These two types of limits together constitute the core indicator system for corrosion life assessment and structural safety boundary determination, achieving a fundamental leap from single damage monitoring to failure early warning in both mechanical safety and chemical protection dimensions, and providing a quantitative control benchmark for the engineering access and life management of materials. Example 2
[0024] This embodiment explains the content of Embodiment 1. Please refer to [link / reference]. Figure 1Specifically, in step S1: by constructing an experimental platform based on multi-scale characterization and in-situ monitoring, and combining damage mechanics models and molecular dynamics simulations under multi-field coupling environments, the failure mechanisms of lead-bismuth corrosion, liquid metal embrittlement, and irradiation-thermal-mechanical synergy are systematically identified; on this basis, by establishing a lifetime prediction model that integrates degradation kinetics theory and data assimilation technology, a fundamental leap is achieved in material lifetime assessment from empirical speculation based on short-term data to reliable prediction based on failure physics; ultimately, a solid theoretical foundation is laid for the long-term safe operation of lead-bismuth cooling core devices, supporting their safety assessment and design optimization throughout their entire life cycle. Example 3
[0025] This embodiment explains the content of Embodiment 1. Please refer to [link / reference]. Figure 1 Specifically, in step S2: by conducting long-term corrosion exposure experiments on candidate materials under multiple working conditions, and combining high-resolution material characterization and in-situ electrochemical testing technology, the coupling influence mechanism of temperature, oxygen concentration, flow field characteristics and time factors on corrosion behavior is systematically analyzed, so as to achieve accurate quantitative characterization of key environmental parameters and in-depth revelation of corrosion kinetic laws, and provide high-confidence experimental support for revealing the nature of material degradation and constructing failure physics models. Example 4
[0026] This embodiment explains the content of Embodiment 1. Please refer to [link / reference]. Figure 1 Specifically, in step S3: by systematically integrating static corrosion experiments, dynamic loop simulations, and mechanical performance tests, a multi-dimensional experimental research system is constructed to obtain key parameter data covering the entire process of material corrosion kinetics, microstructure evolution, and mechanical property degradation. This leads to the establishment of a cross-scale material degradation database, enabling in-depth exploration of the correlation between corrosion mechanisms and mechanical behavior. This provides high-precision, traceable data support and verification foundation for subsequent failure physics model construction and multi-field coupling mechanism analysis. Example 5
[0027] This embodiment explains the content of Embodiment 1. Please refer to [link / reference]. Figure 1 Specifically, in step S4: by systematically integrating multi-dimensional experimental data from static corrosion, dynamic circuits, and mechanical testing, and deeply integrating interdisciplinary principles such as electrochemical theory, corrosion science, materials science, fluid mechanics, interface chemistry, and damage mechanics, a multi-level, complementary prediction system is constructed, encompassing empirical correlation models, mechanism analysis models, damage accumulation models, and artificial intelligence prediction models. This enables accurate simulation and reproduction of the corrosion behavior of materials in the service environment, ultimately achieving a fundamental leap from short-term experimental data to scientific inference of service life based on failure physics, providing a solid theoretical basis for the engineering application and life management of materials. Example 6
[0028] This embodiment explains the content of Embodiment 1. Please refer to [link / reference]. Figure 1 Specifically, in step S5: by integrating the extrapolation method based on degradation dynamics with the finite element numerical simulation coupled with multiphysics, the short-term data obtained from accelerated corrosion experiments are reasonably extended to the cumulative corrosion damage under the reactor's full-life design target; on this basis, considering the discreteness of material performance data and model uncertainty, an appropriate safety margin is introduced to systematically evaluate the long-term adaptability of candidate materials under extreme service environments, ultimately realizing the transformation from "experimental phenomena" to "engineering criteria", providing quantitative durability indicators and theoretical basis for the engineering access, screening optimization and standard setting of materials.
[0029] The above description, in conjunction with specific embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, several simple deductions or substitutions can be made without departing from the concept of the present invention, and all such deductions or substitutions should be considered to fall within the scope of protection defined by the claims submitted herein.
Claims
1. A method for evaluating the corrosion life of a structural material in a lead bismuth environment, characterized by, Includes the following steps: S1. Corrosion Mechanism and Kinetics Research: This study aims to reveal the degradation nature and dynamic evolution of materials in a liquid lead-bismuth environment, and to achieve a fundamental leap in lifetime assessment from empirical speculation based on short-term data to reliable prediction based on failure physics, thus laying a theoretical foundation for the long-term safe operation of nuclear devices. S2. Quantification of key influencing factors: Relying on the liquid lead-bismuth experimental loop system with precise temperature and oxygen control capabilities, the system conducts corrosion exposure experiments on candidate materials under multiple working conditions, and investigates in depth the coupled influence of temperature, oxygen concentration, flow field characteristics and time factors on corrosion behavior, so as to achieve quantitative characterization of key environmental parameters. S3. Acquisition of experimental data: By comprehensively utilizing static corrosion experiments, dynamic loop simulations, and mechanical property testing methods, key parameter data covering material corrosion kinetics, microstructure evolution, and mechanical property degradation are obtained, providing reliable data support for model construction and mechanism analysis. S4. Establishment of Corrosion Life Model: Based on experimental data, integrating the principles of multiple disciplines such as electrochemical theory, corrosion science, materials science, fluid mechanics, interface chemistry and damage mechanics, a multi-level prediction system covering empirical models, mechanism models, damage accumulation models and artificial intelligence models is constructed to achieve accurate simulation of material corrosion behavior and scientific inference of service life. S5. Determination and Standards of Safety Factor: By extrapolating and using finite element numerical simulation, the short-term data obtained from accelerated corrosion experiments are reasonably extended to the amount of corrosion damage under the reactor design life. Based on the introduction of safety margin, the candidate materials are systematically evaluated to determine whether they meet the full life service requirements, providing quantitative criteria and standard basis for the engineering application of materials.
2. The method for assessing the corrosion life of structural materials in a lead-bismuth environment according to claim 1, characterized in that: In step S2, a quantitative correlation between temperature and corrosion reaction rate is established based on Arrhenius's law. Temperature significantly affects the corrosion behavior of materials by regulating the activation energy of interfacial reaction and the element diffusion coefficient. High-speed flowing lead-bismuth fluid can induce fluid erosion effect and interfacial mass transfer enhancement effect, further aggravating the corrosion damage rate of structural materials by destroying the integrity of the surface oxide film and accelerating the dissolution and migration of corrosion products.
3. The method for assessing the corrosion life of structural materials in a lead-bismuth environment according to claim 1, characterized in that: In step S3, static corrosion experiments are used to obtain basic data on material corrosion kinetics under different working conditions, including corrosion rate, element-selective leaching law, and oxide film evolution characteristics; dynamic loop simulation experiments are used to reproduce the real flow service environment, revealing the dissolution, migration, and deposition behavior driven by flow velocity, temperature gradient, and local turbulence effects; and mechanical property tests are used to quantitatively characterize the degradation law of mechanical properties such as tensile, creep, fatigue, and fracture toughness of the material after corrosion, and to establish the correspondence between the degree of corrosion damage and the attenuation of mechanical properties.
4. The method for assessing the corrosion life of structural materials in a lead-bismuth environment according to claim 1, characterized in that: In step S4, the empirical model uses the Arrhenius equation as its core to construct a mathematical relationship between corrosion rate and key parameters such as temperature, oxygen potential, and flow rate, thereby enabling rapid prediction of corrosion depth.
5. The method for assessing the corrosion life of structural materials in a lead-bismuth environment according to claim 1, characterized in that: In step S4, the mechanism model is based on the interfacial diffusion theory and oxide layer growth kinetics to describe the nucleation, thickening, densification and damage processes of the oxide film, revealing the intrinsic mechanism of material corrosion in a lead-bismuth environment.
6. The method for assessing the corrosion life of structural materials in a lead-bismuth environment according to claim 1, characterized in that: In step S4, the damage accumulation model comprehensively considers the reduction in effective bearing area and the increase in local stress concentration caused by corrosion thinning, and couples high-temperature creep damage, and calculates the structural failure time based on the continuous damage mechanics theory. The artificial intelligence model uses multiple sets of experimental data as training samples and constructs a high-precision prediction model of corrosion behavior under multi-field coupling conditions through machine learning.
7. The method for assessing the corrosion life of structural materials in a lead-bismuth environment according to claim 1, characterized in that: In step S5, the corrosion damage threshold includes the wall thickness loss limit and the oxide layer rupture limit. The wall thickness loss limit is determined based on structural strength, pressure bearing capacity, and service safety, while the oxide layer rupture limit is determined based on the failure of the surface protective film and accelerated corrosion of the substrate. The two limits together serve as the core indicators for corrosion life assessment and structural safety boundary determination.