Life Of Components Research Articles

Fatigue Crack Segmentation and Characterization of Additively Manufactured Ti‐6Al‐4V Using X‐Ray Computed Tomography

ABSTRACTX‐ray computed tomography (XCT) is extremely useful for the non‐destructive analysis of additively manufactured (AM) components. AM components often show manufacturing defects such as lack‐of‐fusion (LoF), which are detrimental to the fatigue life of components. To better understand how cracks initiate and propagate from internal defects, we fabricated Ti‐6Al‐4V samples with an internal cavity using electron beam powder bed fusion. The samples were tested in high‐cycle and very high‐cycle fatigue regimes. XCT was used to locate crack initiation sites and to determine characteristic properties of cracks and defects with the aid of deep learning segmentation. LoF defects exposed to the outer surface of the samples after machining were found to be as detrimental to fatigue life as the internal artificial defects. This work can benefit industries that utilize the AM of high‐strength, lightweight alloys, in the design and manufacturing of components to improve part reliability and fatigue life.

Comparative Analysis of Machine Learning Techniques for Identifying Multiple Force Systems from Accelerometer Measurements.

The knowledge of the forces acting on a structure enables, among many other factors, assessments of whether the component's useful life is compromised by the current machine condition. In many cases, a direct measurement of those forces becomes unfeasible, and an inverse problem must be solved. Among the solutions developed, machine learning techniques have stood out as powerful predictive tools increasingly applied to engineering problem-solving. This study evaluates the ability of different machine learning models to identify parameters of multi-force systems from accelerometer measurements. The models were assessed according to their prediction potential based on correlation coefficient (R2), mean relative error (MRE), and processing time. A computational numerical model using the finite element method was generated and validated by vibration measurements performed using accelerometers in the laboratory. A robust database created by the response surface methodology in conjunction with Design of Experiment (DOE) was used for the evaluation of the ability of machine learning models to predict the position, frequency, magnitude, and number of forces acting on a structure. Among the six machine learning models evaluated, k-NN was able to predict with a 0.013% error, and Random Forests showed a maximum error of 0.2%. The innovation of this study lies in the application of the proposed method for identifying parameters of multi-force systems.

Time-Dependent Failure Assessment of Ceramic Receivers

The outlet temperature targets for Gen 3 Concentrating Solar Power (CSP) systems pose a significant challenge to the structural reliability of high temperature metallic components, including those manufactured from nickel-based superalloys. Advanced ceramics present a potential solution due to their excellent high-temperature strength. However, accurate assessment of ceramic components requires an entirely different approach compared to metallic components. This paper describes the implementation of time-dependent reliability analysis of ceramic components in srlife – an open-source software package for estimating the life of high temperature CSP components. This new capability will allow high temperature CSP designers to make fair comparisons between competing metallic and ceramic designs and accurately assess the performance of different ceramic materials for CSP receivers and other components. The current version of the tool is available at https://github.com/Argonne-National-Laboratory/srlife.

Integrated FEM-Multibody Co-Simulation of Additively Manufactured Hip Prosthesis containing cracks.

The increase in life expectancy and attention to the quality of life of elderly people spurred the need, in the last decades, to increase the capabilities of medical and surgical techniques. Among these, the development of prosthetic implants has been a staple of biomedical engineering research since the 70’s. In order to satisfy the challenging demands, the latest novelties in industrial engineering are being tested in their applicability to subjects. The 3D printing of metal alloys can produce a highly customizable product, which, after the proper heat treatments, can possess adequate mechanical properties to ensure a satisfactory component life. Defective products are often the results of wrong or absent post-processing treatments which may cause an uncontrolled crack propagation and a premature total failure of the implant. The behavior of such a product, with various critical crack conditions, was investigated by an integrated MBD-FEM co-simulation environment, focused on a femur subjected to total hip replacement. It was concluded that the Stress Intensity Factor (SIF) computed by the model is compatible with the premature failures experienced by patients, and as such, this model opens the possibility for further analyses aimed at understanding the role of defects on the durability of prothesis

Fatigue crack closure assessment by wavelet transform of infrared thermography signals

The occurrence of crack closure significantly impacts the fatigue life of materials and structural components. Whether it is induced by the nature of the loading, the fabrication process or the geometry of the structure, its magnitude and effect should be considered to further improve predictive models of fatigue crack propagation. However, the definition of reliable experimental methods for the observation and assessment of fatigue crack closure, and in particular suited to structure testing, remains a challenge. The present study aims to provide a novel approach for the assessment of fatigue crack closure via the continuous wavelet transform of infrared thermography data. The processing of the temperature signal close to the crack in a coherent time–frequency space allows for the identification of crack closing and opening instants associated with high-frequency components. The method is meant to be suited to any testing configuration (conventional compact tension specimen or full-scale structures) with minimum operator-dependent parameters.

Lifing Assessment of Gas Turbine Blade Root Affected by Out-of-Tolerances.

Current and future heavy-duty gas turbines (GTs) are being developed as an alternative or support to renewable energy sources (RESs). Therefore, GTs are subjected to several instances of being switched on and off; thus, the material fatigue limit can be reached in a short time. In such a scenario, possible out-of-tolerances (OoTs) in critical components must be considered. In this paper, OoTs related to critical parameters in the attachment geometry of a rotor blade are considered to estimate their impact on component life through a 2D finite element (FE) analysis. First, a mesh refinement is performed to obtain mesh-independent results; second, OoT geometries are simulated to determine stresses and strains at the blade attachment and disc groove. The mesh refinement process is critical to ensure model accuracy for both nominal and OoT geometries. The results show that OoTs can lead to important reductions in the life of the intended component, both on the blade and disc sides. These results could be useful in updating the maintenance plan for components and could be used for future insights, with further work extending the study to 3D geometry, for example, and evaluating the effect of other geometries.

Turbopump Parametric Modelling and Reliability Assessment for Reusable Rocket Engine Applications

The development of modern reusable launchers, such as the Themis project with its LOX/LCH4 Prometheus engine, CALLISTO—a reusable VTVL-launcher first-stage demonstrator with a LOX/LH2 RSR2 engine, and SpaceX’s Falcon 9 with its Merlin 1D engine, underscores the need for advanced control algorithms to ensure reliable engine operation. The multi-restart capability of these engines imposes additional requirements for throttling, necessitating an extended controller-validity domain to safely achieve low thrust levels across various operating regimes. This capability also increases the risk of component failure, especially as engine parameters evolve with mission profiles. To address this, our study evaluates the dynamic reliability of reusable rocket engines (RREs) and their subcomponents under different failure modes using multi-physics system-level modelling and simulation, with a particular focus on turbopump components. Transient condition modelling and performance analysis, conducted using EcosimPro-ESPSS software (version 6.4.34), revealed that turbopump components maintain high reliability under nominal conditions, with turbine blades demonstrating significant fatigue life even under varying thermal and mechanical loads. Additionally, the proposed predictive model estimates the remaining useful life of critical components, offering valuable insights for improving the longevity and reliability of turbopumps in reusable rocket engines. This study employs deterministic, thermally dependent structural simulations, with key control objectives including end-state tracking of combustion chamber pressure and mixture ratios and the verification of operational constraints, exemplified by the LUMEN demonstrator engine and the LE-5B-2 engine class.

Tribological properties of graphene oxide reinforced aramid paper-based composites

Self-lubricating paper-based composites can provide technological solutions such as low friction and extended service life for the aerospace airframe kinematic mechanical components. To improve the tribological properties of aramid short fibers, this study chemically combined graphene oxide (GO) with aramid nanofibers (ANF) through intermolecular forces, creating a self-lubricating GO-reinforced aramid paper-based composite GO/ANF. Mechanical performance tests have shown that the introduction of GO can significantly improve the fracture strength, Young's modulus, and toughness of paper-based composites. The frictional performance test results show that compared with ANF, the GO/ANF paper-based composites can maintain the lowest coefficient of friction (COF) and wear under high load and high sliding rate conditions. When the amount of GO added is 1 wt%, the COF and volume wear rate of GO/ANF paper-based composites are reduced by 23 % and 89 %, respectively. Mechanism analysis indicates that synergistic effects and friction transfer films are important factors contributing to the excellent performance of paper-based composites. This GO/ANF paper-based composite has good application prospects as a good anti-wear liner material in self-lubricating sliding bearing.

Improvement of gradient microstructure and properties of wire-arc directed energy deposition titanium alloy via laser shock peening

Wire-arc directed energy deposition (WADED) technology has been widely used in the remanufacturing of titanium alloy structural components benefited from with the advantages such as high deposition efficiency and low cost. However, due to the coarse and anisotropic microstructure, the complex internal stresses and processing-induced rough surface significantly reduce fatigue performance and reliability of the remanufactured structural components. In this work, surface modification of titanium alloy WADED repair component was carried out via laser shock peening (LSP), and its gradient structure, microhardness, residual stress and fatigue performance and enhancement mechanism were systematically investigated. Results indicated that the different microstructure of each region led to different responses under the action of LSP, which was related to the change of dislocation density. LSP induced crystal defects such as high-density dislocations, twins and stacking faults on the surface. A variety of crystal defects gradually decreased with the depth from the strengthened surface, formed a gradient microstructure and significantly affected the microhardness and residual stress of the repaired components. The surface hardness and compressive residual stress of the repaired components were greatly increased after LSP and the hardened layer and compressive residual stress depth affected layer were 600 μm and 800 μm, respectively. The average fatigue life of the additive repair component increased by 197 % under the synergistic effect of compressive residual stress and gradient microstructure.

CREEP-FATIGUE BEHAVIOR ANALYSIS OF THE 310 NBN STEEL: EXPERIMENTAL AND LIFE PREDICTION

With the increasing challenge of extending the service life of structural steels components subjected to high-temperature environments, there is an urgent need to investigate the mechanisms of creep-fatigue and to develop new steels that can effectively withstand these complex loading regimes. This study examines the creep-fatigue behavior of a novel 310 NbN austenitic stainless steel, enhanced with nitrogen and niobium, under high-temperature conditions. Specimens were subjected to tests at 675°C with varying hold-times of 0, 5, 60, and 600 s. Results indicated that longer hold times significantly increased crack growth rates and reduced cycles to fracture, highlighting a time-dependent crack propagation. Fracture surface analysis revealed a shift from transgranular to intergranular fracture with longer hold-times, indicating predominant creep damage. Predictive models, including the strip-yield model, aligned well with experimental data, emphasizing the critical role of hold-time in designing high-temperature steel components for improved durability.

New paradigms shift in buildings: experimental application of Digital Twin for safety and well-being

Abstract Enhancing durability and service life of buildings and components is pivotal for sustainable development. It constitutes an opportunity to reduce energy consumption, carbon emissions and life cycle impact of buildings in a climate neutral perspective. Issues strongly introduced and set as priorities by EU policies that highlight the urgent need to tackle them also through deeply heritage renovation and digital transformation in the building sector. Digitalization is a cornerstone of this transformation, instrumental in facilitating and enabling it sustainably. The Key Enabling Technologies (KETs) are directly associated with new technological potential and emerging technologies. Digital Twin (DT) approach appears alongside these. Its experimentation and widespread application are gaining prominence in innovating Life Cycle Management (LCM) and sustainability practices of buildings. In this scenario the paper explores the role and potentialities of DT approach presenting the experimental application of the DT4SEM. A digital infrastructure that, by integrating Internet of Things (IoT), synchronizes a physical building with its virtual counterpart. The two realities (physical and virtual) remain interconnected through the mutual exchange of data, both in real-time and asynchronously enabling proactive monitoring and analysis of seismic behaviour. The experimental setup involves simultaneously Big Data analytics, simulation tools and deploying sensors within the sample building. Data is then fed into the virtual DT model, allowing for continuous comparison and analysis to detect anomalies and predict potential risks. This approach facilitates enhanced decision-making, performance optimization and sustainability improvements across the building’s lifecycle: a new vision for built environment management that evolves from a process resulting in a sequence of operative phases into a complex digital infrastructure. The design of the DT4SEM and the current application for seismic monitoring in buildings, results from a collaborative effort involving the academic spinoff BIG srl, the startup Sysdev, the company Berna Engineering srl, and ACCA Software spa.

Material volume reduction for creep testing using composite cantilevers and its application for residual life assessment

Digital image correlation (DIC) and finite element analysis (FEA) demonstrate that creep deformation in bending occurs primarily in ≈30 % of the cantilever volume near the fixed end, especially when the creep stress exponent ranges from 5 to 7. As an alternative approach to minimize the material volume required for testing, the concept of fabricating composite cantilevers is proposed and validated in this study. A composite cantilever sample consists of an “active” creeping portion (e.g., T22 boiler steel) and an additively extended “passive” non-creeping portion (e.g., IN718). The volume reduction process involved varying the length of the “active” section, a, while keeping the total length of the cantilever, L, constant. The DIC measurements conducted at 600 °C to assess the creep behavior of T22 steel revealed that analytical expressions for monolithic cantilevers could aptly predict the constitutive steady-state creep laws from the composite cantilevers if measurements are made in a region at a critical distance away from the interface. FEA indicates that accurate stress estimation enables predicting monolithic creep behavior using composite samples with “a/L” ratios of as small as 5 %. Using the developed approach, the loss of creep resistance of T11 boiler steel that was in service for ∼ 240,000 h was ascertained in high throughput fashion using a composite cantilever having only 30 vol % of the “active” material. Guidelines to minimize the volume fraction of the “active” portion in the composite cantilever and the implications of the observations for estimating the residual life of in-service high-temperature components are discussed.

Understanding the role of alloying elements Cr, Ni in erosion–corrosion process of nuclear grade austenitic stainless steel 304 L by total reflection X-ray fluorescence

Stainless steel (SS) has gained an indispensable position as one of the most widely used industrial material. In nuclear industry, it is one of the technologically most important structural materials used in pressure tube, containment vessel and reprocessing-related applications. In fact, SS 304 L is the workhorse material of the reprocessing plant which faces the hostile conditions of acid, temperature as well as high radiation dose. These conditions can affect the erosion-corrosion behavior of the material and can lead to poor mechanical properties. This also affects the life of the reactor components. In the present study, a systematic work has been carried out to develop an in-depth understanding of the Corrosion Rates (CRs) with respect to the loss of major and minor elements from SS into the corrosive nitric acid medium using Total reflection X-Ray Fluorescence (TXRF). The effect of acid molarity as well as temperature, on the erosion-corrosion behavior of SS304L was studied. The TXRF studies have revealed that the CR was maximum in 2 M HNO3 and minimum in 8 M, showing that as the nitric acid molarity has an important role to play in the corrosion and as the molarity increases, the passivation of SS 304 L also increases. This observation was further corroborated with the concentrations of Fe, Cr and Ni, which had leached into the nitric acid medium. The role of alloying elements, Cr and Ni, in the passivation of SS was also studied. The effect of temperature showed that at 45 °C, the rate of corrosion was minimum, as compared to at 25 °C and 90 °C which reveals that the formation of chromium oxide passive layer was thermodynamically most favorable at this temperature.

Corrosion measurement of thermally sprayed carbide coatings on stainless steel pipes

The petrochemical industries face a formidable challenge from corrosion, which leads to high maintenance costs and lost production. Traditional corrosion monitoring methods frequently fail to provide accurate and reliable results. As a result, these components must be replaced or repaired promptly to avoid increasing costs and limiting component life, which will reduce operation efficiency. Novel techniques with demands for high surface qualities in the future will be applied to develop alloys with better performance and more diverse applications. This study examines the corrosion resistance of cermet coatings, such as tungsten carbide (WC) and Chromium carbide (Cr3C2), in acidic solution by electrochemical impedance spectroscopy and electrochemical potentiodynamic polarisation. Additionally, utilizing optical microscopy techniques, the microstructural characteristics of coatings were assessed. According to the results of the Tafel polarisation test, Cr3C2 coating exhibited a lower rate of corrosion than other coatings. The Cr3C2 coated, WC coated, and uncoated samples reported corrosion rates of 0.924, 1.122, and 2.599 mmpy respectively. The corrosion resistance of Cr3C2 and WC coatings was increased by 64% and 53%, respectively, in comparison to uncoated specimens. This suggests that the coating maximizes economy, minimizes maintenance costs, extends the structure's lifespan, and reduces down the rate of corrosion.

Predicting the fatigue life of T800 carbon fiber composite structural component based on fatigue experiments of unidirectional laminates

This study is based on the fatigue experiment results of unidirectional laminates and investigates the fatigue performance of T800 carbon fiber/epoxy resin composite structural components through experimental and numerical analysis. Fatigue experiments were performed on [0]16, [90]16, and [±45]8 laminates individually, obtaining the fundamental fatigue parameters necessary for modeling. The fatigue life model for T800 carbon fiber/epoxy resin unidirectional laminates was refined, and fatigue degradation rules were provided for the fatigue progressive damage model. A fatigue progressive damage analysis model for T800 laminates was established based on the 3D Hashin criterion, predicting the fatigue life and fatigue damage failure process of the laminates. A fatigue life prediction model was developed for T800 carbon fiber composite I-beam structural components, which can predict the primary types of fatigue failure, fatigue life and the location of fatigue failure occurrence. The predicted fatigue life of structural components shows good consistency with the experimental results. This method can calculate structural components including ply angles of 0°, 45°, and 90° and obtain the fatigue life contour.

Effects of nanoceramic particle size and content on the wear resistance of micro-arc oxidation coatings for 2A12 aluminum alloy

The 2A12 aluminum alloy, renowned for its exceptional mechanical properties, encounters significant limitations in applications involving abrasive environments or frequent contact with other surfaces due to its inadequate wear resistance. This shortcoming substantially reduces the service life of components and escalate maintenance costs, highlighting the urgent need for advanced surface modification techniques. This study meticulously investigates the influence of nanoceramic particle size and content on the wear resistance of micro-arc oxidation (MAO) coatings, a surface modification technique renowned for forming dense, adherent ceramic layers on aluminum alloys. The systematic experimentation revealed that the incorporation of 150 nm α-Al2O3 nanoparticles into the MAO matrix achieves an optimal dispersion, leading to a substantial enhancement in wear resistance. The sample with a 5 g/L concentration of 150 nm α-Al2O3 nanoparticles doping in the MAO electrolyte demonstrated the lowest mass loss, underscoring its enhanced wear resistance. The enhanced microstructure, enriched with hard ceramic phases such as α-Al2O3 and mullite, plays a pivotal role in withstanding wear. Moreover, this study identified that an optimal balance of surface roughness and coating thickness is essential for achieving enhanced wear resistance. The findings of this research provide a strategy for the design of wear-resistant coatings tailored for high-performance applications across aerospace, automotive, and general engineering industries. By optimizing the particle size and concentration in MAO coatings, this study paves the way for the development of durable materials capable of thriving in demanding environments, thereby extending the service life and reducing maintenance requirements of components.

Miniaturized-specimen creep testing: an alternative method for evaluating the remaining service life of CrMo steel components

Miniaturized-specimen creep testing: an alternative method for evaluating the remaining service life of CrMo steel components

Machine Learning-Driven RUL Prediction and Uncertainty Quantification for Ball Screw Drives in a Cloud-Ready Maintenance Framework

In today's rapidly evolving industrial landscape, efficient predictive maintenance solutions are essential for minimizing downtime and enhancing productivity. This research introduces an adaptive cloud-based model pipeline for predicting the Remaining Useful Life (RUL) of machine components, specifically ball screws. The pipeline integrates local preprocessing, edge computing, and cloud-based adaptive model training, ensuring data privacy and reducing data transmission volumes. The system classifies wear states using various machine learning mod-els and predicts RUL through regression analysis, incorporating uncertainty quantification for robust maintenance scheduling. The experimental setup includes accelerated degradation of ball screws, with data collected via a three-dimensional accelerometer. Feature extraction and data augmentation techniques are employed to enhance prediction accuracy. Random Forest and Gradient Boosting models demonstrate superior performance, with Random Forest selected for its robustness and uncertainty quantification capabilities. Empirical results indicate high prediction accuracy, with Random Forest achieving up to 91% accuracy in Phase 2. This cloud-ready predictive maintenance framework leverages scalable cloud infrastructure for efficient data processing and real-time updates, offering a practical solution for industrial applications. The proposed approach significantly advances the adoption of digital business models within the manufacturing industry, providing a reliable and efficient tool for predictive maintenance.

Response characteristics of platinum coated titanium bipolar plates for proton exchange membrane water electrolysis under fluctuating conditions

Voltage fluctuations in energy input not only impact the overall hydrogen production efficiency and stability of Proton Exchange Membrane Water Electrolysis (PEMWE) systems but also pose significant challenges to the long-term service life of individual components. This study focuses on the key component − bipolar plates and investigates the response behavior of platinum-coated titanium bipolar plates under simulated fluctuating voltage conditions. By integrating surface phase analysis and electrochemical testing results, this research elucidates the response characteristics of the bipolar plates to different voltage waveforms and frequencies. And the findings hold substantial significance for the upstream energy control in hydrogen production through water electrolysis.

Non-local fatigue criterion based on standard deviation for notches and defects in Ti-6Al-4V

The aim of this study is to propose a non local multiaxial fatigue criterion in order to assess the fatigue limit of stress concentrator such as notches or defects in Ti-6Al-4V. This criterion is based on the standard deviation of the stresses integrated over a given volume around the hot spot point. Up to now, the standard deviation has never been tested as an indicator of stress heterogeneity to assess fatigue life of notch components. Four parameters are necessary to identify the criterion. The criterion is first validated on notched samples based on literature results and shows very good results. A set of experimental tests is conducted on natural and artificial defects including clustering defects and demonstrates the flexibility and accuracy of the criterion.