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DOE OSTI2021

Enhancing fatigue life by ductile-transformable multicomponent B2 precipitates in a high-entropy alloy

Catastrophic accidents caused by fatigue failures often occur in engineering structures. Thus, a fundamental understanding of cyclic-deformation and fatigue-failure mechanisms is critical for the development of fatigue-resistant structural materials. Here we report a high-entropy alloy with enhanced fatigue life by ductile-transformable multicomponent B2 precipitates. Its cyclic-deformation mechanisms are revealed by real-time in-situ neutron diffraction, transmission-electron microscopy, crystal-plasticity modeling, and Monte-Carlo simulations. Multiple cyclic-deformation mechanisms, including dislocation slips, precipitation strengthening, deformation twinning, and reversible martensitic phase transformation, are observed in the studied high-entropy alloy. Its improved fatigue performance at low strain amplitudes, i.e., the high fatigue-crack-initiation resistance, is attributed to the high elasticity, plastic deformability, and martensitic transformation of the B2-strengthening phase. This study shows that fatigue-resistant alloys can be developed by incorporating strengthening ductile-transformable multicomponent intermetallic phases.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Enhancing fatigue life of aluminum alloy castings through cavitation water jet peening: Experiments and simulations

This study presents an investigation into the enhancement of the fatigue life of aluminum castings through the application of cavitation water-jet peening (CWJP). CWJP harnesses the impacts of water cavitation to induce surface compressive residual stress within metallic materials. In this work, CWJP was applied to a high pressure die-cast (HPDC) Al–Si alloy A380 with three different water-jet traverse velocities. The fatigue-life improvement, evaluated in a 4-point bending configuration (stress ratio R = 0.1), was found to vary with applied stress level and ranges from 1.6 to 10 times that of the parent alloy. The data also shows that decreasing the traverse velocity results in greater compressive residual stresses within the surface layer and a concurrent increase in surface roughness. This residual stress layer extends to a depth of 400 μm below the surface, as confirmed by through-thickness residual stress and microhardness measurements. CWJP treatment effectively slows down fatigue crack propagation, as evidenced by microstructural observations of narrower striation spacing. Simulations reveal that compressive residual stresses, in addition to surface hardening during CWJP, are key to improving fatigue life. A 20% increase in surface hardness and 150 MPa compressive residual stress imposed by CWJP process provides an average 5-fold enhancement of fatigue life across different stress levels. This study demonstrates the potential of CWJP as an effective surface treatment to enhance the fatigue life of aluminum castings, such as HPDC components for automotive applications.

Al casting↗

DOE OSTI2023

A verification study of fatigue-based methods in API RP 1183 for estimating fatigue life of pipeline dents

Pipeline dents are mechanical damage caused by a third party in buried pipelines during construction or maintenance repair. Dents are recognized as a leading cause of pipeline failures for both liquid and gas transmission lines, and their assessment and management are critical to pipeline integrity. To meet the industry need, American Institute of Petroleum (API) in 2020 published a recommended practice (RP) 1183 – Assessment and Management of Pipeline Dents. This API code provides the pipeline industry “standard methods” for evaluating severity and fatigue life of pipeline dents with a single peak. This paper performed an initial verification study of fatigue-based methods prescribed in API RP 1183 for estimating fatigue life of pipeline dents. A brief review was first given to the dent fatigue-based methods, including three dent screening methods for estimating dent fatigue life in Sections 7.4.1, 7.4.2, and 7.4.3 of API 1183 and one dent assessment method for predicting fatigue life in Section 8.3.4. In order to verify these fatigue life prediction methods, a set of “standard examples” of dents provided in Annexes A.1 to A.5 of API RP 1183 were utilized in this study to calculate fatigue life, to determine restraint condition, and to evaluate both screening and assessment methods for single-peak dents. Through detailed calculations and comparisons, this study confirmed some specifications of API RP 1183, but also found some self-inconsistences and errors existing in this new API code. Furthermore, this includes the self-inconsistences between three screening methods and the self-inconsistence between the screening and assessment methods. On this basis, recommendations were made on how the operators should use API RP 1183, and what actions API should take to improve this code.

42 ENGINEERING↗

DOE OSTI2025

Fatigue life prediction of powder bed fused–laser beam AlSi10Mg: Incorporating critical defects via crystal plasticity modelling

The current study provides a microstructurally-based computational framework to predict the fatigue life of additive manufactured (AM), i.e., powder bed fused–laser beam (PBF-LB), AlSi10Mg specimens using the crystal plasticity finite element method (CPFEM). The fractography analysis, electron backscatter diffraction (EBSD), uniaxial and cyclic responses, and fatigue life of specimens were used to inform the computational framework. CPFE simulation was used to compute fatigue indicator parameters (FIPs) as fatigue driving forces. A new fatigue criterion is introduced based on FIPs, which was calibrated using experimental fatigue data. The proposed fatigue measure was evaluated versus the specimens with critical defects of various sizes and locations subjected to different stress amplitudes. The results show that the developed framework can capture the fatigue life of samples with different critical defect locations and sizes along with different stress amplitudes for both high-cycle fatigue (HCF) and very high-cycle fatigue (VHCF) regimes.

Additive manufacturing↗

DOE OSTI2025

Assessment of irradiation embrittlement effect on fatigue life of a pressurized-water reactor pressure vessel using the fracture toughness master curve approach

The reactor pressure vessel (RPV) is a critical structural component in pressurized-water reactors, and it is designed to withstand extreme conditions, such as high pressures, elevated temperatures, and prolonged radiation exposure. Ensuring RPV integrity is essential for the safe and reliable long-term operation of nuclear power plants, especially as aging mechanisms such as fatigue and irradiation embrittlement pose increased risks. Fatigue, caused by cyclic thermal and mechanical loading, can lead to crack initiation in localized high-stress regions. Simultaneously, neutron irradiation, particularly in the beltline region, progressively reduces fracture toughness, increasing susceptibility to brittle fracture. These combined effects of fatigue and irradiation embrittlement potentially impact the RPV structural integrity, necessitating fitness-for-service assessments. This study applies the fracture toughness master curve approach to evaluate the impact of irradiation embrittlement on RPV fatigue life. A coupled thermo-mechanical stress analysis identifies critical stress locations under normal service transients, pinpointing regions most vulnerable to fatigue crack initiation and growth. Stress intensity factors for postulated flaws at these locations are calculated, enabling an assessment of fatigue life under irradiated and unirradiated conditions. The results indicate that neutron irradiation embrittlement accelerates the conditions in which a critical crack can form and lead to failure, particularly at lower temperatures. The failure occurs where reduced fracture toughness limits the material’s resistance to crack growth. Axial cracks at nozzle corners are the most life limiting without irradiation, while circumferential cracks demonstrate longer fatigue lives. The findings highlight the importance of incorporating irradiation effects into fatigue life predictions to ensure the long-term structural integrity of RPVs.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Corrosion Fatigue Life Evaluation of 17-4PH in Support of Water Filled Turbine Hubs

High cycle corrosion fatigue (HCCF) life S-N tests were conducted on wrought 17-4PH in various water environments under accelerated testing conditions. For tests conducted in aerated Columbia River water and in aerated ASTM Type IV water, at ~10 6 cycles, the HCCF stress amplitude was ~70% of the value in air. For deaerated water, the value was ~80%. These values are consist with the small amount of literature data on HCCF life of 17-4PH in water environments. The measured fatigue life both in air and water are much better than the ASME trend curve of high cycle fatigue life of moderate and high strength steels. Measured values were also much better than found in a hydropower-relevant study in the literature on cast 17-4PH. The effect of Amersite 61W on HCCF life was evaluated and found to cause very low times to specimen failure compared to all other water environments.

13 HYDRO ENERGY↗

DOE OSTI2025

Mechanistic Insights Into Fatigue Life Enhancement of High‐Strength Steel via Ultrasonic Impact Treatment

In this work we explore the impact of Ultrasonic Impact Treatment (UIT) on the fatigue performance of high‐strength microalloyed steel commonly used in crankshaft applications. Building on prior observations of fatigue life improvement with UIT, this work focuses on unraveling the process–structure–performance relationships underpinning these enhancements. Microstructural analysis revealed significant grain refinement in the near‐surface layers, with deformation depth increasing at higher impact energies. This led to increased surface hardness and the development of deeper compressive residual stresses, particularly in samples treated with higher impact energy. Rotating bending fatigue testing showed a substantial improvement in fatigue life for UIT‐treated samples, with the endurance limit nearly doubling compared with untreated specimens. Fractographic analysis revealed a transition in crack initiation from surface defects in untreated samples to interior regions in UIT‐treated samples, characterized by the formation of noninclusion‐induced granular bright facets (GBFs). The observed fatigue enhancement is attributed to the synergistic effects of strain hardening and compressive residual stresses, which increase the surface crack threshold and promote interior crack initiation. This study provides new mechanistic insight into UIT‐induced fatigue resistance and interior failure behavior in high‐strength steels.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Extreme variation in fatigue: Fatigue life prediction and dependence on build volume location in laser powder bed fusion of 17-4 stainless steel

Laser powder bed fusion (LPBF), a metal additive manufacturing technology, is well-suited for design optimization but fatigue life is limited by manufacturing defects. In this work, 17-4 stainless steel components were manufactured in densely populated build volumes, simulating at-scale LPBF production. Tests revealed extreme variability in fatigue life data, analyzed via rigorous statistical tools. The El-Haddad model, modified for finite-life, enabled defect-based life prediction. Specimen location within the build volume correlated to life, which was heteroscedastic. Investigating defect concentration over the build volume explained typical life and scatter. Finally, these findings argue for qualification approaches which acknowledge high material lot variability.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Infusible Thermoplastic Composites for Wind Turbine Blade Manufacturing: Fatigue Life of Thermoplastic Laminates under Ambient and Low-Temperature Conditions

Traditionally, thermoset resins such as polyesters (PE) and epoxies are used as the polymer matrix for construction of wind turbine blades. However, concern about their end-of-life treatment garners interest to use thermoplastics for increased recyclability. However, the high viscosity of molten thermoplastics inhibits their use in manufacturing wind turbine blades with injection or compression molding. A recently developed, infusible, reactive thermoplastic resin overcomes this technological barrier. Toward verifying that this recyclable resin is suitable for use in wind turbine blades, a dataset of R?=?0.1 and R?=?10 fatigue data for glass fiber-reinforced acrylic composites is provided and equal fatigue life to industry standard epoxy and unsaturated PE resin systems is demonstrated. Specifically, R?=?0.1 fatigue data for acrylic composites at room temperature and -30?degrees C for verification of low-temperature performance are tabulated. To elucidate failure mechanisms, in situ mechanical testing with X-ray computed tomography demonstrates that damage accumulation occurs by crack propagation along the fiber-matrix interface under cyclic loading. Infrared (IR) thermography predicts failure points in composites specimens with porosity defects introduced from nonideal manufacturing processes. Furthermore, these manufacturing defects are shown to compromise the fatigue life of the acrylic laminates by an order of magnitude.

effect of defects↗

DOE OSTI2021

Development of a Vibration Technique Based on Geometric Optimization for Fatigue Life Evaluation of Sandwich Composite Structures

A major obstacle to obtaining cost-effective experimental data on the fatigue life of sandwich panels is the prohibitive amount of time and cost required to carry out millions of cycles. On the other hand, vibration techniques applied to sandwich geometries fail to match the stress patterns that are obtained from standard flexural fatigue tests. To overcome such limitations, a vibration-based fatigue technique is proposed, which entails the use of sandwich specimens whose geometries are optimized to reproduce the stress distribution observed during three point bend loading while vibrating at the first resonant frequency. The proposed vibration technique was experimentally validated. The results, compared with the average number of cycles to failure at different stress ratios obtained via the Three-Point Bending test, showed high levels of accuracy. The proposed method is robust and time effective and indicates the possibility of attaining fatigue lifetime prediction of a wide class of composite elements, such as sandwich panels.

36 MATERIALS SCIENCE↗

DOE OSTI2021

On the influence of test speed and environment in the fatigue life of small diameter nitinol and stainless steel wire

Here, to better understand the complex interplay of speed and environment on metals commonly used in implants, rotary bend fatigue tests were conducted on stainless steel and nitinol wires. A range of alternating strains was tested to create ε-N curves at two speeds (physiologic and accelerated) and in three environments (deionized water at body temperature, phosphate buffered saline at body temperature, and laboratory air at ambient room temperature). Results indicate that speed and environment can affect the observed fatigue life in nuanced ways. An electropotential monitoring technique was demonstrated to characterize fatigue crack growth which may be useful in future investigations.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Physics-based Multiscale Additively Manufactured Superalloy Design for Optimized High Cycle Fatigue Life (Final Report)

The objectives of this project are to: (i) Gain fundamental understandings towards the microscopic damage mechanisms, as impacted by pertinent materials properties (e.g. stacking fault energy (SFE) and microstructure (e.g., grain size), leading to high-cycle fatigue (HCF) damage to AM Ni-based superalloy parts; (ii) Provide scientific insight into the effect of testing frequency on damage mechanisms and fatigue life of AM Ni-based superalloy parts under HCF regime, thereby establishing an appropriate correlation between accelerated testing and materials’ true service life; (iii) Devise an accurate, experimentally validated multiscale model across atomic, micro- and meso-scales, to predict the cyclic stress-strain responses and fatigue damage accumulation for AM Ni-based superalloys under various loading frequencies.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A Hybrid AI/ML and Computational Mechanics Based Approach for Time-Series State and Fatigue Life Estimation of Nuclear Reactor Components

Environmental fatigue modeling is a complex problem due to multiple failure modes and their intermixing. The failure modes are function of various underlying causes in addition to the corrosive effect of reactor coolant environment. Some of the major causes are time-dependence of material associated with cyclic loading, load sequence effect associated with random/variable amplitude loading, effect of strain amplitude and rates, effect of varying temperature (along both temporal and spatial directions) and the effect of mean strain and stress. The nonlinear intermixing of failure modes associated with above mentioned causing parameters makes the environmental fatigue modeling is a challenging task. Because of this challenge, fatigue is traditionally being modeled based on experimental data. However, test based empirical approach often requires hundreds of fatigue tests to model the above-mentioned intermixing failure causes even for a single material system. The problem is further exaggerated for reactor component made from multi-material systems such as made from both carbon and stainless-steel base metals and their similar and dissimilar metal welds. With the difficulty of conducting hundreds of fatigue tests to capture the above-mentioned intermixing failure causes, fatigue modeling approaches often depends on empirical models based on limited available test data such as available through ASME code and NUREG 6909. However, these limited test-data-based models may not be enough to accurately predict the life of reactor components. Accurate prediction of life of reactor component would become a necessity, particularly when the license of the reactors to be extended for long-term-operation (LTO) that is for well beyond its original design life of 40 years. The requirement of extending the license of reactor under LTO requires hundreds of fatigue tests to be conducted to understand the mechanism associated with the above-mentioned interdependent failure causes. However, conducting large number of fatigue tests is not a feasibility due to the cost involved. To address this issues Argonne National Laboratory (ANL) with the sponsorship of DOE Light Water Reactor Sustainability (LWRS) program trying to develop a hybrid predictive modeling approach. This is based on limited experiment-data, Artificial-intelligence (AI) – Machine-Learning (ML) - Deep-Learning (DL) based techniques and Multiphysics-computational-mechanics based modeling tools. The hybrid approach not-only can improve the accuracy of the existing stress analysis and fatigue modeling approach but also can reduce the over-dependency on test-based approach. Towards this goal following are some of the major contributions based on ANL’s FY-20 environmental fatigue modeling activities: 1) A cyclic plasticity material model database for 82/182 dissimilar metal weld, which can be readily shared with US nuclear industry and regulatory agency on request. 2) A well validated analytical modeling methodology to perform cycle-by-cycle stress prediction under both constant amplitude fatigue loading and variable amplitude fatigue loading (with load-sequence effect). 3) An AI/ML/DL based methodology to predict unmeasurable cyclic strain based on other available sensor signals. This type of approach can be used for estimating strain in real reactor components from other sensor readings. 4) An AI/ML based approach to improve the US capability on environmental fatigue testing. This is by improving ANL’s existing environmental fatigue testing capacity to conduct ASME required strain-controlled tests (by controlling strain amplitudes and its rate), while not measuring the strain (due to the difficulty of placing an extensometer in a narrow autoclave in a PWR-water-test system). 5) A simulation and experiment based probabilistic modeling methodology for time-series fatigue state and life estimation of reactor metal such as dissimilar metal weld.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025