Purpose This paper aims to systematically investigate the coalescence modes and coalescence criteria of circular defects. Design/methodology/approach In this work, a homogeneous plate containing circular double defects was used, and based on the Gurson–Tvergaard–Needleman (GTN) damage model, a series of finite element simulations were conducted. These circular double defects have different sizes, horizontal distances s, and vertical distances h. Then, the coalescence behaviors of these double defects were obtained, and the coalescence results was plotted with the horizontal defect spacing ratio s/(2R + s) as the abscissa and the vertical defect spacing ratio h/(2R + h) as the ordinate. Findings First, the results showed that there are three types of coalescence modes for circular double defects: defect tip is coalesced with defect tip (DT-DT), the middle of defect is coalesced with the middle of defect (DM-DM), and defect tip is coalesced with the middle of defect (DM-DT). Moreover, in the coordinate system constructed with the defect spacing ratio, there is a clear boundary between the defect coalescent area and the independent area. Then, based on the defect spacing ratio, a new coalescence criterion for circular double defects was established. Originality/value A new coalescence criterion for circular double defects is established based on the defect spacing ratios, providing a theoretical basis for evaluating defect interaction and structural integrity.
Purpose This paper aims to address the limitations of single-sensor feature capture and the interference of environmental noise during the dynamic stress acquisition of built-in axle box bogies for rail vehicles under wheel flat conditions, while avoiding the unintended elimination of periodic impact features by conventional denoising methods.Design/methodology/approach A targeted denoising method is proposed: Multi-Sensor Dynamic Weighted Fusion (MSDWF) fuses multi-sensor data using correlation coefficient-based dynamic weights, wavelet packet-optimized Further ICEEMDAN (F-ICEEMDAN) overcomes the fixed noise intensity constraint of the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), Multi-Dimensional Feature Screening (MDFS) screens Intrinsic Mode Functions (IMFs) through entropy-weighted Median Absolute Deviation (MAD) and energy curvature detection, Impact Enhancement (IE) strengthens weak impacts through Hilbert envelope analysis. The effectiveness of the method is validated by simulations (SNR = 5/10/15 dB) and field tests (50-300 km/h), compared with wavelet denoising, Variational Mode Decomposition (VMD), and Singular Spectrum Analysis (SSA).Findings The method outperforms traditional approaches in signal unbiasedness, morphological fidelity, and fatigue damage calculation accuracy (minimal Miner damage deviation (Delta D)), enhancing dynamic stress signal reliability for precise bogie structural fatigue life evaluation.Originality/value Targeting dynamic stress signals of built-in axle box bogies under wheel flat conditions, this study innovatively integrates four modules (MSDWF, F-ICEEMDAN, MDFS, IE). It breaks the contradiction between denoising and impact feature retention in traditional methods via adaptive noise injection, multi-dimensional IMF screening and weak impact enhancement, ensuring efficient retention of key impact features for reliable fatigue evaluation.
Purpose Accurate reliability evaluation of turbine runners under long-term and complex loads is essential, but reliability analysis of turbine runners often suffers from high computational cost, high input dimensionality and low failure probability. This paper aims to develop an accurate and efficient method for reliability analysis of turbine runners. Design/methodology/approach A support vector regression (SVR)-based enhanced quasi-Monte Carlo simulation (EQMCS) method is proposed for reliability analysis of turbine runners. An efficient scaling formula is also established to improve the robustness of failure probability assessment. The proposed method is validated through a high-dimensional numerical case and a turbine runner case. Findings The results show that the proposed method can effectively reduce computational cost while maintaining the accuracy of reliability analysis in high-dimensional problems and improve the efficiency and robustness of failure probability evaluation for complex structures. Originality/value This paper proposes a novel reliability analysis framework that integrates SVR, EQMCS and an efficient scaling strategy. The method can improve the accuracy, efficiency and robustness of reliability assessment for turbine runners.
Purpose To characterize the nonlinear damage evolution, a new coupled damage term is proposed within the framework of the Palmgren-Miner (P-M) rule, explicitly considering the interaction between the maximum load, stress amplitude ratio, and frequency ratio. Design/methodology/approach The robustness and accuracy of the proposed model were validated using experimental results from the welded joints and four additional alloy materials. Findings By effectively mitigating the non-conservative bias and excessive conservatism inherent in existing methods, this study provides a reliable tool for fatigue life prediction of welded structures under CCF loading spectra. Originality/value By effectively mitigating the non-conservative bias and excessive conservatism inherent in existing methods, this study provides a reliable tool for fatigue life prediction of welded structures under CCF loading spectra.
Purpose This study aims to develop a robust notch fatigue life prediction model for hydro turbine components, specifically addressing fatigue failures in welded joints induced by severe stress concentrations at transition fillets. The research focuses on overcoming the inherent limitations of the conventional theory of critical distance (TCD) in the finite life regime and its heavy dependency on empirical fitting parameters.Design/methodology/approach An enhanced TCD framework is proposed by incorporating the evolutionary characteristics of the baseline S-N curve to formulate a novel expression for the characteristic length L. A stress gradient threshold is introduced to physically define the effective damage zone, and the effective stress is refined using a root-mean-square formulation. Additionally, a path resampling strategy is implemented to optimize finite element data extraction and eliminate numerical errors associated with mesh sensitivity. The model is validated using experimental results from 04Cr13Ni5Mo/ER316 L welded specimens.Findings Results demonstrate that predicted fatigue lives exhibit strong agreement with experimental observations, significantly outperforming the conventional line method in accuracy and robustness. The proposed model effectively captures the accelerated damage at notch roots without requiring additional empirical parameter calibration. It achieves high predictive precision comparable to extensively calibrated mainstream frameworks.Originality/value The study establishes a novel mathematical formulation for critical distance derived from S-N curve evolution, enabling the autonomous determination of L and eliminating empirical fitting requirements. This provides a promising and efficient theoretical framework for the structural health assessment of hydroelectric infrastructures.
Purpose This study aims to design a damage detection and characterization system (targeting cracks and delamination) for aeronautical composite structures. Design/methodology/approach This methodology relies on a multidisciplinary approach combining polymer-reinforced/metallic carbon fiber hybrid structures with an integrated network of PZT sensors. It leverages experimental data and employs advanced signal processing and imaging techniques to monitor structural integrity and assess the severity of damage. Findings Verified experimental results confirm the method's reliability in real-life situations. Research limitations/implications Research Limits: “The primary challenges involve signal processing complexity due to the hybrid nature of AL7075-T6 and CFRP materials, as well as the potential influence of environmental factors (temperature, pressure) on PZT sensor reliability”. Research Implications: “This work enables a shift toward condition-based maintenance, significantly reducing operational costs while enhancing structural safety and extending the service life of critical aerospace and maritime assets.” Practical implications This study enables a shift from scheduled to real-time structural monitoring. There is a drastic reduction in inspection time and aircraft downtime. Monitoring the fatigue of hybrid AL/CFRP structures helps to safely extend their service life. The study helps in providing precise diagnostics to optimize repair strategies and minimize human error. Social implications There is a drastic reduction of structural failure risks through early-stage damage detection. Cost savings in maintenance can lead to more affordable air travel for the general public. The study helps in promoting a circular economy by safely extending the lifespan of complex structures and reducing material waste and also in shifting maintenance roles toward high-tech data analysis and specialized software expertise. Originality/value The study investigates the complex damage mechanics at the interface of AL7075-T6 and CFRP laminates and helps in combining PZT sensor networks with advanced imaging software for real-time damage characterization. Beyond mere detection, the system assesses “structural criticality,” providing high-value diagnostic data for maintenance optimization and cost reduction.
Purpose This study aims to investigate the effect of specimen size on the fracture resistance of V-notches with end holes (VO-notched) polymeric samples under opening mode loading experimentally and theoretically. Design/methodology/approach First, a number of VO notched Brazilain disk (VONBD) and VO notcehd semi-circular bend (VONSCB) samples with different sizes were made from polymethyl methacrylate and general-purpose polystyrene sheets and then were tested under pure Mode I loading. After that, it is tried to predict the fracture resistance of notched samples using two stress-based criteria [point stress (PS) and mean stress (MS)] considering the size effect. Findings First, it is found from experiments that the fracture resistance of polymeric VO-notched specimens varies with the size of specimen in such a way that notch fracture toughness increases by increasing the specimen size. Secondly, it is found that the PS and MS criteria are able to predict in good accuracy the fracture resistance of tested samples. Originality/value The size effect on the notch fracture toughness of VO-notched polymeric samples is investigated for the first time, and it is the main novelty of this research.
Purpose The primary objective of this study is to investigate the influence of the stochastic variability of fatigue crack growth (FCG) model parameters on the structural FCG life and reliability. Design/methodology/approach This study focused on a high-temperature steam turbine rotor involved in a fatigue fracture accident at a power plant. From the perspective of the randomness of FCG model parameters (C, m) and the initial crack length a0, the probabilistic characteristics of the random variable a0 and the bivariate random vector (C, m) under different distribution types were investigated. A method based on the Nataf model was proposed to construct the bivariate Weibull distribution. On this basis, the probabilistic distribution of FCG life and the prediction of failure probability in probabilistic damage tolerance analysis were studied. Findings The results reveal that the distribution type and coefficient of variation significantly affect the probabilistic distribution of FCG life. In terms of failure probability prediction, the variation patterns of failure probability curves under different distribution types and coefficients of variation were obtained. Furthermore, sensitivity analysis shows that for the bivariate random vector (C, m), the failure probability is consistently more sensitive to m than to C, even under different distribution types. Therefore, particular attention should be paid to accurately quantifying the randomness of m and addressing its correlation with C, in order to achieve more accurate reliability predictions. Originality/value This work provides a reference for the development of more comprehensive probabilistic damage tolerance analysis methods for structural applications.
PurposeThis paper studies the response of building integrated photovoltaic (BIPV) floor tiles under normal thermo-mechanical conditions and superimposed short-term sustained loads. While the thin glass covers are in general minimally affected by ordinary thermal effects, the typical BIPV section suffers for possible loss of mechanical capacity, due to the sensitivity of the constituent materials, especially the encapsulant. Also, the features of fixing systems have further influence on the mechanical response.Design/methodology/approach3D numerical models are inspired from real BIPV tiles and used to investigate the coupled thermo-mechanical performance of BIPV tiles under ordinary conditions. The effects of temperature variations are highlighted in terms of deflection, stress and bending stiffness.FindingsKey mechanical performance indicators of typical use for laminated glass are critically discussed for the examined BIPV floor tiles. As shown, the serviceability deflection check of BIPV tiles is a key parameter of their performance assessment, which implicitly suffers from the progressive modification of the bending stiffness with increasing temperature.Originality/valueStructural glass members are usually designed as load-bearing elements in terms of serviceability deflection and ultimate tensile stress verifications. One of the most influencing parameters in their mechanical analysis is represented by the shear flexibility of the interlayer in use to bond the glass panels. This aspect is even more pronounced for BIPV solutions, where both the glass covers and the encapsulant are subjected to non-uniform temperature scenarios due to ordinary heating, whilst their load-bearing role and mechanical capacity should be in any case preserved. This study shows the key role of thermo-mechanical considerations for similar systems, even under ordinary operational conditions.
PurposeThis study focuses on a first-stage stator vane of a gas turbine that developed fatigue cracks during service. A finite element-based fracture mechanics simulation was performed under thermo-mechanical coupling conditions with the aim of providing a practical approach for fatigue crack growth (FCG) analysis and FCG life prediction of the vane.Design/methodology/approachFirst, the potential crack growth directions were identified through a crack growth likelihood analysis. Then, initial cracks were introduced based on actual inspection data from the turbine blade, and the crack growth process was analyzed. Finally, the randomness of FCG life was investigated assuming that the Paris model parameters (C, m) follow a bivariate normal distribution with a correlation coefficient of -0.9, with a focus on the distribution characteristics of FCG life.FindingsThe crack growth is more likely to occur toward the leading edge of the blade and along the rib direction. The crack growth rate throughout the process exhibits non-monotonic behavior with turning points. The FCG life can be approximately described by a Weibull distribution, and both the mean and dispersion of the FCG life increase as the coefficients of variation for C and m increase.Originality/valueThis research provides the FCG characteristics and the probabilistic distribution of FCG life for the turbine vane, offering a useful reference for probabilistic damage tolerance assessment of turbine blades under thermo-mechanical loading.
Purpose This research aims to determine and evaluate fatigue properties using estimation methods based on the monotonic tensile strength properties of old metallic bridge materials – puddled iron (pre-1900) and mild steel (post-1900) – and to rank the estimation methods. Design/methodology/approach Fatigue properties can be estimated using monotonic tensile strength data. In this study, 10 estimation methods were employed: Manson's universal slopes (1965), four-point correlation (1965), Mitchell's method (1977, 1979), modified universal slopes (1988), uniform material law (1993), modified four-point correlation (1993), modified Mitchell's method (1996), Meggiolaro's median (2004), modified Park–Song's method (2018) and GP-symbolic regression (2024). This investigation uses the monotonic tensile strength properties of old metallic bridge materials (Eiffel, Luiz I, Fão, Pinhão, Trezói and Várzeas) to evaluate estimation methods. A comparison and discussion are made between the known experimental and estimated strain-life data. Findings The Mitchell's, modified Mitchell's and Manson's universal slopes methods consistently provide accurate and robust estimates of fatigue parameters for puddled iron (pre-1900) and mild steel (post-1900). The modified Park–Song method is effective only for Luiz I and for puddled iron (pre-1900), but it lacks robustness in general. The modified four-point correlation and GP-symbolic regression methods show poor agreement with experimental fatigue data and fatigue curves for the old metallic materials, especially in the high- and low-cycle regimes. The fatigue properties of the puddled iron (pre-1900) and the mild steel (post-1900) were estimated to serve as reference mean values. Originality/value This research contributes to the quality evaluation and ranking of estimation methods used to predict the fatigue properties of old metallic bridge materials (pre-1900 and post-1900) based on their monotonic strength properties. In many cases, only the monotonic strength behaviour of these materials is known. This makes it essential to evaluate and develop formulations that allow the identification of relationships between fatigue resistance and monotonic strength properties.
PurposeReliability-based design optimization (RBDO) is a vital framework for safe design by considering the economic cost of engineering structures when the structural problem involves uncertainties in the design process. The double-loop (DL) methods using the reliability index approach (RIA) method commonly have two main issues as an effectively framework for efficient computational burden and robust convergence property to solve nonlinear probabilistic constraints. The current work aims to address these limitations by proposing a novel inexact RIA (IRIA) to enhance both the efficiency and robustness of the RBDO while it provides a reliable condition of optimal design under uncertainties.Design/methodology/approachThe proposed IRIA modifies the traditional RIA by introducing a dynamic relaxed factor, which decreases from an initial value of 2 to 0, within the search direction for the most probable point. The factor undergoes adaptive changes through an inexact line search method, which utilizes current and past reliability analysis data along with its associated sensitivity vectors. The relaxed factor reaches its maximum value through an iterative process, which maintains stable convergence conditions while reducing the need for costly function evaluations.FindingsThe implementation of IRIA on five standard RBDO benchmarks shows its ability to outperform all other methods. The proposed method provides substantial stability improvements for reliability analysis, which surpasses DL methods according to the results because it effectively resolves convergence issues in highly nonlinear performances. The IRIA system achieves better computational efficiency through its method of reusing earlier analysis data, which enables it to calculate a larger stable relaxed factor.Originality/valueThe study presents a new practical solution that enables researchers to solve the traditional RIA convergence issues, which exist as fundamental problems. The IRIA system dynamically controls its relaxed factor through past data analysis to achieve better results in complex RBDO problem-solving, which benefits engineers and researchers working on structural integrity and reliability engineering.
PurposeThe present study is aimed at developing a computationally efficient residual stress modelling method that is suitable for arc directed energy deposition (Arc-DED) additive manufacturing applications using macroscopic continuum finite element techniques adapted from weld modelling.Design/methodology/approachThe approaches were undertaken on the NeT-TG9 Arc-DED benchmark, which comprises five depositions on an SS316 L substrate. A thermo-mechanical modelling workflow was developed using guidelines from the R6 structural integrity assessment procedure and realised with FEAT-WMT and Abaqus solvers. Bead lumping (BL) and moving torch (MT) simulations were compared for computational time and accuracy. This was followed by pass lumping (PL), which simplified the BL method further with reductions in computational time. PL was implemented by adjusting the heat input to maintain the mid-length fusion zones. The thermo-mechanical simulation results were validated against experimental measurements.FindingsThermal analyses showed similar temperature distributions between the MT and BL simulations, and the experimental data. The two approaches were also comparable in their residual stress predictions, closely matching experimental measurements. BL was the more computationally efficient technique. PL also predicted the longitudinal residual stresses within the acceptable threshold for accuracy and reduced the computational time by 92% from the MT simulation.Originality/valueWhile the methods discussed have been implemented in weld modelling, their use in Arc-DED additive manufacturing is still limited. The PL method can be applied to the TG9 benchmark and similar problems and produce accurate results. Optimisation of the technique could speed-up Arc-DED modelling to more industrially practical timeframes.
Purpose This study aims to address the environmental and economic limitations associated with conventional epoxy-based adhesive joints by introducing a re-entrant auxetic interlayer concept that reduces adhesive usage while preserving structural performance in composite–metal joints. Design/methodology/approach Single-lap joints were fabricated using aluminum–aluminum, aluminum–composite, and composite–composite adherend combinations. A 3D-printed polylactic acid auxetic interlayer was incorporated between the adherends and bonded using Araldite 2015 epoxy. Mechanical performance was assessed through comparative testing between fully bonded joints and joints containing the auxetic interlayer, with specific attention to adhesive volume reduction and failure behavior. Findings The auxetic interlayer reduced adhesive consumption by 61.8% with only an approximately 26% reduction in joint strength relative to fully bonded counterparts. Additionally, interlayered joints demonstrated more gradual and predictable failure characteristics, indicating improved damage tolerance and more stable mechanical response. Originality/value This study presents a novel application of re-entrant auxetic geometry as an interlayer for adhesive joints, offering a sustainable design strategy that simultaneously decreases adhesive usage and enhances failure predictability. The concept provides a promising pathway for environmentally conscious and mechanically efficient adhesive joint design in next-generation composite–metal assemblies.
PurposeThis study aims to address the challenges of concealed corrosion damage, limited samples and strong environmental variability in metal pressure-resistant structures of underwater equipment by proposing a corrosion localization method integrating data augmentation and deep learning to enhance accuracy and reliability under small-sample conditions.Design/methodology/approachThe geometrical configuration of this structure is analyzed, and the geometrical modeling method is proposed. When necessary parameters are determined, such as the structural span, length, vault rise, longitudinal and lateral giant grid number and section height to top chord length ratio of the lattice member, the structure geometrical model can be generated.FindingsNumerical simulations and experimental results yielded a global generalization RMSE of 0.04 (on normalized, unitless data) in ambient air. In a targeted underwater validation for a corrosion defect, a physical RMSE of 2.38 mm was obtained (after denormalization). These findings indicate the robustness and effectiveness of the proposed approach in aquatic environments.Originality/valueThis study presents a novel framework that integrates dual-domain data augmentation with deep learning for corrosion localization under small-sample conditions, providing a high-precision and generalizable approach for structural health monitoring of underwater equipment with significant theoretical and engineering value.
PurposeThe purpose of this article is to comprehensively investigate the load characteristics of the high-speed train bogie frame with inner axle-box and analyze the applicability of the EN 13749 standard.Design/methodology/approachThis article studies the load characteristics and the maximum load extrapolation approach for the high-speed train bogie frame with inner axle-box. The bench calibration experiments and field line measurements are carried out.FindingsThe measured variable-amplitude loads are converted to an equivalent constant-amplitude load and compared against the standard limit values, which are found to be below the specified limits. The response frequencies of the three loads show a correlation with respect to changes in velocity. The maximum load amplitude responses of both transverse damper loads and antisnaking damper loads are concentrated around 1.5 Hz. Axle-box traction link loads are primarily concentrated within the 0-50 Hz frequency range. Compared with the extrapolation results of polynomial regression, the errors of locally weighted least squares regression (LWLS) are all below 5%, validating the feasibility of this method for load extrapolation of bogie frame with inner axle-box.Originality/valueBased on axle-box traction link load data and bogie load analysis, the equations for rhombic loads and traction loads are established. Weighted least squares reflects the differences in the data used by varying the weights assigned to the fitting parameters. This work provides reasonable guidance for future research and optimization of the high-speed train bogie frame with inner axle-box.
PurposeThe accurate characterisation of the dynamic behaviour of inhomogeneous materials is a challenging task. Examples of such materials are composites, which are becoming increasingly common in the industrial world. Wave propagation studies in these materials, which are hard to model, are usually very complicated and difficult or even impossible to generalise to other composites. The authors aim to develop a special, easy-to-use finite element method to investigate wave propagation in any composite in a memory-efficient and accurate way.Design/methodology/approachThe study combines the substructure technique, a method published in the 1970s, with the central difference method (CDM) in a specific way. This can be called as Combined Method (CM). It is important to note that CM and CDM are completely identical in accuracy, as using the substructure technique is only an equation rearrangement.FindingsFor metal matrix syntactic foams (MMSFs), it has been shown that CM can significantly decrease the memory requirements of the finite element models without loss of accuracy. Moreover, it greatly reduces the time-consuming construction of large-scale inhomogeneous finite element models. The comparison between the CDM and CM shows that the larger the model in which the wave propagation is investigated, the greater the advantage of CM.Originality/valueThe CM methodology is not only applicable to the study of the wave propagation characteristics of MMSFs, but can easily be transferred to the study of other composites.
PurposeAccurately predicting the high-cycle fatigue (HCF) reliability of single-crystal turbine blades is essential for the structural integrity and service safety of aero-engine components. However, this task remains challenging due to two main limitations in existing methods: the high computational cost required to quantify aerodynamic excitation dispersion and the absence of models capable of characterizing HCF strength dispersion under multi-factor coupling. To overcome these limitations, this study aims to develop an integrated framework with two major innovations.Design/methodology/approachFirst, a novel rapid aerodynamic response prediction method is proposed by combining dynamic mode decomposition, proper orthogonal decomposition and long short-term memory networks. Second, a multi-factor synergistic HCF strength model is established based on systematic tests of DD6 single-crystal specimens under varying crystal orientations, temperatures and stress ratios. This model improves the K-T diagram by integrating the EI-Haddad intrinsic crack length, critical distance theory and a Gerber-based mean stress correction.FindingsThis hybrid DMD-POD-LSTM model achieves high-fidelity predictions of unsteady aerodynamic loads with errors below 6.6%, while providing a computational speedup of over 11.4 times. This method makes the previously exhaustive quantification of aerodynamic excitation dispersion feasible. The multi-factor synergistic HCF strength model improves the K-T diagram by integrating the EI-Haddad intrinsic crack length, critical distance theory and a Gerber-based mean stress correction. It accurately captures the coupled effects of multiple factors, with prediction errors below 7.7%.Originality/valueBy integrating these two high-precision models within the reliability prediction framework, a comprehensive HCF reliability analysis is achieved that simultaneously accounts for uncertainties in aerodynamic excitation and material HCF strength. The analysis yields a probabilistic reliability of 96.82% for the blade under design conditions, offering a robust and quantitative basis for fatigue-resistant design.
