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Results for “lifetime prediction models”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12

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DOE OSTI2020

An ab initio molecular dynamics exploration of associates in Ba-Bi liquid with strong ordering trends

Fictive associates are widely used to describe and model liquid phases with strong ordering trends. However, little evidence is known about the assumed associates in most cases. In the present work, an ab initio molecular dynamics (AIMD) study is employed to investigate the characters of the Ba-Bi liquid, in which associates have been assumed in existing thermodynamic modeling. It is found that in the Ba rich melt, the Bi atoms are almost completely surrounded by Ba atoms. The Bi-centered coordination polyhedrons are strongly associated to crystalline structures of Ba 5 Bi 3 and Ba 4 Bi 3 with a longer lifetime than other polyhedrons during the AIMD simulations. In addition, these Bi-centered polyhedrons in Ba rich melt connect with each other through vertex, edge, face, and/or bipyramid sharing to form medium range orders (MRO). In the Bi rich melt, the Ba-centered polyhedrons also form MROs, but they are both structurally and compositionally diverse with a shorter lifetime. These findings from AIMD study provide evidences that there exist a strongly ordering Ba 4 Bi 3 associate and a weakly ordering BaBi 3 associate in the Ba-Bi liquid. Here, the predicted enthalpy of mixing in the liquid agrees well with the results by the CALPHAD modeling in the literature.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Electrode Erosion and Prefire Studies Towards Fusion Scale Pulsed Power

This study presents a comprehensive investigation of electrode erosion and discharge behavior in spark gap switches over long switching cycle lifetimes. Brass, copper–tungsten (CuW), and stainless steel electrodes are tested under controlled conditions to quantify material degradation, debris accumulation, and changes in breakdown voltage. High-resolution imaging and statistical analysis of spark channel locations and gap breakdown voltages reveal how surface evolution influences long-term performance and reliability. These results provide essential data for lifetime modeling and inform design strategies for pulsed power systems in emerging applications such as private sector fusion energy and large-scale facilities like Sandia’s Z Machine and proposed ZX upgrades, where high repetition reliability and predictable behavior are critical.

electrical breakdown↗

DOE OSTI2022

Spark plasma sintered, MoNbTi-based multi-principal element alloys with Cr, V, and Zr

MoNbTi, MoNbTiZr, CrMoNbTiZr, and MoNbTiVZr multi-principal element alloys (MPEAs) were fabricated via spark plasma sintering (SPS) and investigated for use in high-strength applications. The fabrication method by SPS and powder metallurgy differs from those presented in the prior literature, where most MPEAs are fabricated using arc melting (AM) methods. Here cryogenic milling was used to maximize potential defect sinks (grain boundaries) for radiation resistance and to increase ultimate tensile strength through the Hall-Petch effect. SPS was chosen for consolidation in order to maintain a fine-grained structure during densification. Each alloy was characterized using x-ray diffraction and scanning electron microscopy for phase identification and compositional homogeneity. The base ternary alloy MoNbTi presented a predominantly single BCC system with minor cubic phases. The introduction of additional alloying elements—Zr, V, and Cr—heightened the phase complexity and increased the fractions of a secondary BCC phase and an HCP phase from Zr. The addition of Cr induced a larger fraction of the Laves phase to form. The addition of V caused the precipitation of small Mo inclusions. Thermodynamic analysis was performed to understand the separation of phases in each alloy. Discrepancies among the phase predictions generated by thermodynamic models, phases previously presented in the literature, and the characterization results suggest that MPEA fabrication methods, especially solid-state methods, require significant investigation to ensure that alloys can remain stable throughout their anticipated service lifetimes.

36 MATERIALS SCIENCE↗

DOE OSTI2025

The advanced evolution of massive stars

The nuclear rates for reactions involving 12 C and 16 O are key to computing the energy release and nucleosynthesis evolution of massive stars during their advanced burning phases. Ultimately, these burning rates shape the stellar structure and evolution and influence the nature of the compact objects produced at the end of the stellar life. We explore the implications of new nuclear reaction rates from both experimental and theoretical studies for 12 C(α, γ) 16 O, 12 C+ 12 C, 12 C+ 16 O, and 16 O+ 16 O reactions for massive stars. Our goal is to investigate how the chemical structure and nucleosynthesis evolve from the He-exhaustion stage to the O-burning phase and how these processes influence the ultimate stellar fate. We computed rotating and non-rotating models for stars of different masses at solar metallicity. We used the stellar evolution code GENEC, which includes a large network of nuclear reactions and isotopes involved in advanced phases, as well as updated rates for 12 C(α,γ) 16 O. For the three fusion reactions involving 12 C and 16 O, we considered new rates following a data-driven fusion suppression scenario (hereafter HIN(RES)) and new theoretical rates obtained with time-dependent Hartree-Fock (TDHF) calculations. The updated 12 C(α, γ) 16 O rates mainly impact the chemical structure evolution changing the 12 C/ 16 O ratio at He-exhaustion and have little effect on the CO core mass. This variation in the 12 C/ 16 O ratio is in some cases critical for predicting the final fate of the model, which is very sensitive to 12 C abundance, and in particular the 20 M ⊙ remnant may change from a black hole to a neutron star. The He-burning (C-burning) lifetime is also decreased (increased) by about −2% (+15%). The combined new rates for 12 C+ 12 C and 16 O+ 16 O fusion reactions according to the HIN(RES) model lead to shorter C- and O-burning lifetimes by ≈ − 10%, and −50%, respectively, and shift the ignition conditions to higher temperatures and densities. In contrast, the theoretical TDHF rates primarily affect C-burning, increasing its duration by about 30% and lowering the ignition temperature. These changes modify the chemical structure of the core, the size and duration of C-burning shells, and hence their compactness. They also impact the central and shell nucleosynthesis (by ±1 dex and by factors of ±2–10, respectively), while 12 C+ 16 O reaction rates variations remain the least important.

abundances↗

DOE OSTI2026

Proposal to search for long-lived neutral particles in CERN service shafts

Long-lived particles are predicted by many extensions of the Standard Model and have been gaining interest in recent years. In this paper the original proposal is presented for AN Underground Belayed In-Shaft (ANUBIS) detector that substantially extends the sensitivity to particle lifetimes by instrumenting the existing service shafts above the ATLAS or CMS experiments with tracking stations. For scenarios with electrically neutral long-lived particles with 𝑚 ≳ 1~GeV produced at the electroweak scale and above, the lifetime reach is increased by 2-3 orders of magnitude compared to currently operating and approved future experiments at the LHC. Here, the original ANUBIS detector design proposal is outlined along with the projected costs.

ANUBIS↗

DOE OSTI2026

Diagnostics, Prognostics, and Optimization for Lithium-Ion Battery Systems

Health management of lithium-ion battery systems presents a host of challenges due to their complex physics, large numbers of components, and a wide variety of degradation behaviors across different battery types. Dr. Paul Gasper will present on research from the Electrochemical Energy Storage Group on Lithium-ion battery diagnostics, prognostics, and optimization. Diagnostics research, including state-estimation via machine-learning from electrochemical impedance spectroscopy and DC pulses as well as continuous state-estimation via Kalman filters, will highlight the ongoing challenges for accurately measuring the state of batteries without performing time-consuming characterization tests. NLR's industry-recognized battery prognostics work, which predicts real-world battery degradation by identifying degradation rate models from accelerated aging data using statistical modeling and machine-learning, will be used to demonstrate the critical impact of battery controls, thermal management, and operating strategy on durability and lifetime. Finally, the use of prognostic models for financial or lifetime optimization will be discussed.

25 ENERGY STORAGE↗

DOE OSTI2021

AI-Batt (Autonomous Identification of Battery Life Models) [SWR 21-36]

Autonomous Identification of Battery Life Models (AI-Batt) AI-Batt is a MATLAB code base for developing lifetime models for batteries from accelerated aging data. The code base provides many functions for processing, visualizing, and modeling battery aging data, making the data processing, exploration, and modeling workflow substantially faster. These tools are tailored for working with battery aging data sets, which usually consist of many separate time-series for each cell, with many test conditions and possible replicates at each condition, which makes it difficult to simply process or visualize the data set. Complex modeling tasks, such as cross-validation, sensitivity analysis, and uncertainty quantification have been implemented to enable thorough statistical investigation of model predictions. Additionally, several machine-learning algorithms are implemented to autonomously identify suitable models via symbolic regression. Data processing functions automatically cast data from the struct data type, which is commonly used to store experimental data, but is not an acceptable input for most algorithms, to the table data type, which can be easily used as input to any optimization algorithm. Also, the data can be separated into time-invariant and time-variant data tables, which is helpful for exploring the data set as well as developing separate models for time-variant and time-invariant aging mechanisms. For example, in aging tests with constant temperature, temperature is a time-invariant experimental condition. Visualization tools enable plotting of data, model fits, and model simulations possible with single-line function calls, empowering data exploration of complex data sets with both time-varying and time-invariant trends. Plots can be automatically generated for the whole data set, or separated by data group (groups of test replicates) or individual data series. Data points or data series can be automatically colored by the value of a variable with a variety of color maps, and model predictions can also be colored by the value of a fit statistic. Comparisons between data sets and the predictions/simulations of different models on the same data set can be easily plotted as well. Distributions of parameter values from bootstrap resampling can be plotted to visualize the reliability of parameter estimation, or determine any correlations between parameters. Modeling tools handle the complex task of creating and parsing symbolic equations for modeling battery lifetime. Equations are parsed to grab relevant data variables, parameter values, or specified sub-models for input into optimization, evaluation, or simulation functions. Models can be optimized locally (one set of parameters for each data series), bi-level (some parameters shared across the data set), or globally (single set of parameters for all data). Functions implementing symbolic regression algorithms help users to discover effective model equations, even in poorly sampled, high-dimensional data.

Smith, Kandler↗

DOE OSTI2023

Incorporating Operational Uncertainties into the Dispatch of an Integrated Solar and Storage System

The economic assessment of hybrid energy systems (HES) pairing battery energy storage systems (BESSs) and photovoltaics (PV) is highly important for advancing their deployment in power systems. This paper presents an innovative assessment framework, including an optimal control policy for dispatch under uncertainty and procedures for exploring control parameters that maximize economic benefits. The proposed dispatch policy consists of two steps using system forecast information. The first step is to determine whether a BESS will be used within an operational scheduling time frame based on the probability of events and their thresholds. Once the dispatch of BESS is triggered, a model predictive control (MPC) is carried out in the second step for scheduling using the expected value of system information. By exercising this policy with different thresholds, one can explore the trade-offs between short-term benefits and battery lifetime, and identify an optimal threshold that maximizes the total economic benefits within the battery lifetime. An evaluation study in a real-world HES project is presented to illustrate the proposed framework. Compared with traditional optimal dispatch algorithms, the proposed method can significantly improve the economic benefits of an HES scheduled under forecast uncertainties.

Ma, Xu↗

DOE OSTI2023

Sensitivity Analysis of Modal Parameters of a Jacket Offshore Wind Turbine to Operational Conditions

Accurate estimation of offshore wind turbine (OWT) modal parameters has a prominent effect on the design loads, lifetime prediction, and dynamic response of the system. Modal parameters can vary during the operation of OWTs. This paper studies the variation and sensitivity analysis of an OWT’s modal parameters with respect to operational and environmental conditions. Three finite element models of a jacket-supported OWT at the Block Island Wind Farm are created within the OpenSees, SAP2000, and OpenFAST platforms and validated using experimental measurements. The OpenFAST model is used to simulate the modal parameters of the turbine under various wind speed, rotor speed, power, yaw angle, mean sea level, blade pitch angle, and soil spring values. The model-predicted modal parameters of the first fore–aft (FA) and side–side (SS) modes are compared to those identified from experimental measurements. Results from the simulations show that the first FA natural frequency and damping ratio mostly depend on the rotor speed and wind speed, respectively, while yaw angle and mean sea level do not have a visible effect. It is observed that there is about 8% stiffening in the first FA frequency and an aerodynamic damping of 7.5% during the operation of the OWT.

17 WIND ENERGY↗

DOE OSTI2026

Reductions in wind farm main bearing rating lives resulting from wake impingement

This paper studies the impacts of wake impingement on main bearing rating lives predicted during the wind turbine design stage. A computational tool chain was developed to explore and quantify these effects across a wind farm populated by 10 MW wind turbines. Wind field and turbine load modelling was undertaken using the Dynamiks Python package, including application of a dynamic wake meandering model. The ISO 281 basic bearing rating life formulation was subsequently applied in order to evaluate impacts from wake effects. Analyses included a two-turbine parametric analysis, followed by a full wind farm analysis undertaken for the TotalControl 32-turbine reference wind farm, including full wind rose simulations across all operational wind speeds. Site conditions were accounted for using a Weibull wind speed distribution and a range of parametric wind direction rose models. Results indicate that wind farm main bearing rating lives are negatively impacted by the effects of wake impingement, resulting in rating life reductions for the analysed wind farm of the order of 16 % on average and as much as 20 %–25 %, both for the locating main bearing. Despite these high sensitivities, it is important to note that these resultant rating lives (i.e. the predicted lives) still far exceed the standard wind turbine operational lifetimes of 20–30 years. Wake impacts were also found to be asymmetrically related to the side on which the rotor is impinged, suggesting that, for the main bearing, there may be a “better” side for wake impingement to occur. Rating life sensitivities to wind rose shape were also observed. While these findings must be interpreted with due consideration for the various methodological limitations present, they provide compelling evidence that wake effects at the wind farm level should necessarily be included when undertaking main bearing operational load modelling, rating life assessment, or other load-related analyses.

17 WIND ENERGY↗

DOE OSTI2023

Unconventional gas-phase preparation of the prototype polycyclic aromatic hydrocarbon naphthalene (C 10 H 8 ) via the reaction of benzyl (C 7 H 7 ) and propargyl (C 3 H 3 ) radicals coupled with hydrogen-atom assisted isomerization

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in the interstellar medium and in meteorites such as Murchison and Allende and signify the missing link between resonantly stabilized free radicals and carbonaceous nanoparticles (soot particles, interstellar grains). However, the predicted lifetime of interstellar PAHs of some 108 years imply that PAHs should not exist in extraterrestrial environments suggesting that key mechanisms of their formation are elusive. Exploiting a microchemical reactor and coupling these data with computational fluid dynamics (CFD) simulations and kinetic modeling, we reveal through an isomer selective product detection that the reaction of the resonantly stabilized benzyl (C 7 H 7 ) and the propargyl (C 3 H 3 ) synthesizes the simplest representative of PAHs – the 10π Hückel aromatic naphthalene (C 10 H 8 ) molecule – via the novel Propargyl Addition–BenzAnnulation (PABA) mechanism. The gas-phase preparation of naphthalene affords a versatile concept of the reaction of combustion and astronomically abundant propargyl radicals with aromatic radicals carrying the radical center at the methylene moiety (aromatic-CH 2 ) as a previously passed over source of aromatics in high temperature environments thus bringing us closer to an understanding of the aromatic universe we live in.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Modelling uranium dioxide corrosion under repository conditions: A pore-scale study of the chemical and thermal processes

This paper investigates the corrosion behaviors of spent uranium dioxide (UO 2 ) fuel when placed in geological repositories. We performed pore-scale reactive transport simulations of the UO 2 corrosion process in a defective fuel rod with different orientations of breach or fracture on its clad. It is found that the corrosion rate has strong dependency on the breach orientation. The highest corrosion rate of UO 2 is calculated when the angle between the groundwater flow direction and the clad fracture reaches 180°. UO 2 corrosion simulations with different flow rates are compared. The results show the higher flow rate accelerates the corrosion of UO 2 fuel. The effect of pH on the corrosion process is also determined. It is indicated that higher pH can limit the corrosion of UO 2 by reducing the reaction rate. The dependence of reaction rate and time on reactive surface area is explored. Spent fuel with lower surface area demonstrates longer lifetime under corrosion conditions. A numerical model coupling thermal conduction and chemical reactions is developed to assess the impact of temperature on the process of UO 2 corrosion. The results show that higher temperature leads to larger corrosion rates for UO 2 . Here, the predicted reaction rates are higher in comparison with the isothermal results. Hence, our results can help improve the fundamental understanding of UO 2 corrosion in geological repositories for long-term storage of spent nuclear fuels and provide guidance for the safe operations and selection of appropriate repositories.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Validation of MFUEL Metal Fuel Performance Models of SAS4A/SASSYS-1

The fuel characterization models of SAS4A/SASSYS-1 (SAS) have recently been extended to include a new U-Pu-Zr metal fuel model, MFUEL. MFUEL is equipped with mechanistic physics based models to predict the pre-transient characterization and transient response of metal fuel, with emphasis on fuel melting, cladding failure, and the metal fuel’s impact on core reactivity. The MFUEL model will be available in the full version of SAS4A/SASSYS-1 5.7, which is scheduled to be released in June 2023. Fast reactor fuel pins that operated in EBR-II and FFTF with low smear density U-Zr and U-Pu-Zr metal fuels and irradiation resistant ferritic-martensitic cladding showed significant advantages in achieving high burnups and assuring inherent safety characteristics during anticipated transients, design basis events, and beyond design basis events. For safety analysis, a fuel performance model must be able to predict (1) Fuel pin mechanics and compositional and dimensional changes, (2) Clad failure, and (3) Fuel pin thermal resistance. Achieving these high level goals accurately is strongly related to the model performance of individual physical processes taking place within a fuel pin during its lifetime. Metal fuels typically operate above the mid-point temperature of melting during normal, as well as off-normal, conditions. At these elevated temperatures, the availability of thermal activation provides a driving force for various diffusional processes leading to complex phase transformations, micro-structure evolution, significant amounts of fuel swelling, interconnected porosity formation, excessive amounts of fission gas release, and fuel clad chemical interactions. Clad failure in fast reactors primarily occurs as a result of creep rupture augmented by clad wastage formation. The reaction is driven by thermal creep induced dislocation motion, grain boundary cavity nucleation, growth and breakup of grain boundaries. The high level complexity and limited available data requires introducing physics-based modeling approaches to gain extrapolation ability and sensitivity with respect to various conditions. The objective of this report is to perform validation of MFUEL using the experimental data for (1) Normal operation EBR-II fuel behavior, (2) Normal operation PHENIX fuel behavior, (3) HT9 Pressure tube ramp-and-hold creep rupture tests, (4) Whole Pin Furnace (WPF) creep strain, creep rupture and eutectic tests, (5) Fuel Behavior Test Apparatus (FBTA) eutectic tests, and (6) TREAT M5-7 OverPower tests up to clad failure. Section-2 includes a brief description of the MFUEL models. A detailed description of the MFUEL physics-based, semi-empirical models will be presented in the SAS V 5.7 theory manual. Section-3, 4, and 5 describes the validation effort for the pre-transient irradiation, furnace transients, and TREAT M-Series transients, respectively.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Twist Angle-Dependent Interlayer Exciton Lifetimes in van der Waals Heterostructures

In van der Waals (vdW) heterostructures formed by stacking two monolayers of transition metal dichalcogenides, multiple exciton resonances with highly tunable properties are formed and subject to both vertical and lateral confinement. We investigate how a unique control knob, the twist angle between the two monolayers, can be used to control the exciton dynamics. We observe that the interlayer exciton lifetimes in MoSe 2 /WSe 2 twisted bilayers (TBLs) change by one order of magnitude when the twist angle is varied from 1° to 3.5°. Additionally, using a low-energy continuum model, we theoretically separate two leading mechanisms that influence interlayer exciton radiative lifetimes. The shift to indirect transitions in the momentum space with an increasing twist angle and the energy modulation from the moiré potential both have a significant impact on interlayer exciton lifetimes. We further predict distinct temperature dependence of interlayer exciton lifetimes in TBLs with different twist angles, which is partially validated by experiments. While many recent studies have highlighted how the twist angle in a vdW TBL can be used to engineer the ground states and quantum phases due to many-body interaction, our studies explore its role in controlling the dynamics of optically excited states, thus, expanding the conceptual applications of “twistronics”.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A novel method for quantifying irradiation damage in nuclear graphite using Raman spectroscopy

Raman spectroscopy has long been used in studying irradiation damage in carbon/graphite materials. It is however unclear if the measurements from different types of materials are directly comparable. Further, decoupling the contribution from irradiation temperature and fluence to the total damage in nuclear graphite possessing irradiation damage gradient is currently not readily feasible as it requires a complete set of test reactor irradiation experiments over the relevant temperature and fluence range. A novel methodology has therefore been proposed and developed to quantify total irradiation damage evolution at crystal level based on graphite Raman G-band position shift. Specifically, G-band positions derived from a large number of spectra collected from the fractured surface of microfine-grained POCO ZXF-5Q graphite possessing proton irradiation damage gradient were plotted with open literature Raman data on HOPG, BEPO (AXGP graphite), PCEA and IG-110 graphite as a function of dpa. The total damage level within 2σ beam radius in this POCO graphite was estimated to be equivalent to ~2–5 dpa at ~350–370 °C. Derived G-band positions were then mapped to the three-stage amorphization trajectory model indicating beam centre area has entered the second stage, i.e., transitioning from nanocrystalline graphite into amorphous carbon. G-band position relative shift (ΔG) curve with a ‘turn-around’ peak as a function of total damage can be used for in-service lifetime prediction. Importantly, the developed methodology has the potential to ‘unify’ total damage levels across different grades of nuclear graphite caused by ion, neutron and proton irradiation at different temperatures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2026

Virtual Inspection of Advanced Manufacturing via Process-Scale Digital Twins (Abbreviated Report)

Inspection and certification comprise the most significant bottlenecks in advanced manufacturing for NNSA applications, often requiring far more time and resources than the fabrication of the parts themselves. Traditional methods, such as manual review and X-ray computed tomography, are not only slow and costly, but also struggle to provide a clear connection between manufacturing instructions and the final performance of critical components. This gap limits both the agility and assurance needed to support the modernization and safety of the United States nuclear stockpile. In response, our Strategic Initiative established a digital twin framework that integrates realtime process monitoring, automated data analysis, and immersive virtual reality collaboration into a unified inspection pipeline. By leveraging data from sensors, machine instructions, and imaging, we created high-fidelity virtual models of manufactured parts that could be rapidly analyzed and certified. This approach was first demonstrated with Direct Ink Write, and then extended to other manufacturing settings, including conventional (or “subtractive”) manufacturing and to predict the end of life performance of parts per the aging and lifetimes programs. The result is a transformational capability: inspection times have been reduced by a factor of 120,000 without loss of accuracy and while simultaneously improving traceability and confidence in part quality. This framework not only streamlines certification for critical applications, but also positions the national security enterprise to respond more flexibly to emerging challenges, supporting agile manufacturing and digital engineering practices across a broad range of mission-relevant domains.

42 ENGINEERING↗

DOE OSTI2024

PVDeg: Development of a Streamlined Tool for PV Degradation Modeling

The photovoltaic (PV) industry constantly aims for lower costs, higher-efficiency cells, and improved module designs. These trends lead to using new materials, designs, and manufacturing processes, resulting in a continually changing technological landscape. These changes can potentially introduce new, unknown degradation mechanisms and failure modes that are difficult to diagnose, analyze, test, and model. This introduces uncertainty into the expected lifetime of PV modules of 25 to 50 years. research efforts aim to achieve this while keeping performance degradation at a minimum for decades. This puts considerable pressure on improving the accuracy of long-term durability and reliability assessments. There is a need to organize the existing degradation data into an accessible format and to provide industry relevant tools for extrapolation from laboratory to field conditions. Because the core of this type of analysis involves calculations that are complicated but ubiquitous for many degradation processes, an enhanced predictive modeling framework will facilitate the analysis to help researchers keep up with the rapid pace of technological changes. In this work, we present an online tool that can be used to search for and analyze degradation information and extrapolate PV module performance and durability to field exposure. The tool will simplify many of the routine computational operations that are common to many degradation studies. The prediction tool will be built modular and published as open source, enabling users to expand on the existing framework. This repository will contain various degradation models and material parameters suitable for the reliability and durability assessment of materials and components deployed outdoors.

degradation↗

DOE OSTI2021

Combined modeling and experiments to predict corrosion and embrittlement in dual-phase stainless steels within the MARMOT framework

Extending service of Light Water Reactors (LWRs) to beyond 60 years will demand high integrity of materials and components in the reactors. The accurate evaluation and prediction of materials performance under anticipated operating conditions are of particular importance for ensuring the safety of nuclear power plants over their extended lifetime. Stainless steels are extensively used as structural alloys in light water reactor (LWR) systems because of their excellent combination of mechanical properties and corrosion resistance. Austenitic stainless steel welds and cast austenitic stainless steels (CASS) contain significant amounts of ferrite ~5-30% and are ubiquitous in LWR piping (elbows, pump casings, valves) and internal structural components. During their lifetime, these components are subjected to thermal aging at the temperature range of 288-327°C for pressurized water reactors (PWR). A phase transformation within the ferrite phase of these materials leads to embrittlement and degradation in corrosion resistance, which undermines the materials selection criteria.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗