Hidden cracks in metallic lap-joint structures are difficult to detect, and conventional risk assessment methods rely heavily on offline nondestructive inspections. To address these challenges, an integrated diagnosis and prognosis dynamic risk assessment method within a digital twin framework has been proposed. The method employs an experimental strain driven physics and data fusion crack propagation model and implements a dynamic Bayesian network to close the loop between virtual and physical models. Crack initiation is detected using the Cumulative Sum Control Chart (CUSUM) algorithm; crack location is determined by a k-Nearest Neighbors (KNN) classifier; crack size is estimated through a Multi-Output Gaussian Process Regression (MOGPR) model; subsequently, a Dynamic Bayesian Network (DBN) is employed to dynamically update the crack propagation parameters C and m in real time. Based on these updated parameters, the Single Flight Probability of Failure (SFPOF) is computed through Monte Carlo simulation. Experimental results demonstrate that the combined CUSUM and SFPOF criterion provides timely crack warnings and reduces dependence on high-precision Equivalent Initial Flaw Size (EIFS). As monitoring data accumulate, the standard deviations of C and m decrease, lowering uncertainty in life predictions. The proposed method enables continuous online quantitative risk evaluation of metallic lap-joint structures, offering reliable support for condition-based maintenance decisions.

The fan disk is a critical fracture-prone component in aero-engines. To ensure its operational safety and reliability, it is essential to develop load spectra that accurately reflect operating conditions, which are crucial for fatigue life assessment. This study conducts statistical analysis of single-parameter loading on fan disks based on operational data from two mission types of a specific aero-engine, and develops a median speed spectrum through mission segment analysis methodology. The load spectrum damage was calculated using the SWT (Smith-Watson-Topper) equation and linear cumulative damage theory. Load spectrum similarity analysis was conducted with the DTW (Dynamic Time Warping) method. Based on group tests of TC17 titanium alloy simulated specimens, a damage analysis method based on load spectrum similarity was proposed. The damage of the fleet fan disk rotational speed spectrum was calculated to obtain a set of load spectrum damage samples. Goodness-of-fit tests indicate that the fan disk rotational speed spectrum damage follows a lognormal distribution. The damage corresponding to the median rotational speed spectrum closely approximates the median damage of the fleet rotational speed spectrum, validating the rationality of the spectrum development methodology. This provides critical support for accurately assessing the safe service life of fan disks.

The gust load is the primary source of fatigue damage for air-to-ground missiles carried on the fuselage of bomber-type aircraft. To assess the lives of these missiles, it is necessary to develop the gust load spectrum for air-to-ground missile launches. This study provided an explanation of the characteristics of air-to-ground missiles and analyzed the gust load environment during their service. Based on the typical mission profiles of air-to-ground missiles, discrete gust speed exceedance curves were collected from measured data. A discrete gust model was applied to calculate gust load responses, resulting in a family of gust vertical acceleration cumulative exceedance curves applicable to a wide range of altitudes for air-to-ground missile spectrum development. A representative curve for typical usage situations was obtained by statistical analysis. A flight-by-flight spectrum for air-to-ground missile launch was created from a 5-by-5 spectrum of gust vertical acceleration based on mission segments. This spectrum presented herein serves as an indicative reflection of the anticipated gust environment for air-to-ground missiles. This study addresses the challenge of formulating the gust spectrum for air-to-ground missiles during the design phase, particularly in situations where measured loads are lacking.

Previous studies have shown that the fatigue life distribution of metal materials fabricated with Additive Manufacturing (AM) methods, such as Direct Energy Deposited (DED) Ti-6.5Al-2Zr-1Mo-1V alloys, exhibits two peaks. To promote the application of AM in aerospace and other engineering fields, developing a fatigue strength evaluation method suitable for AM materials based on their unique fatigue behaviours and fatigue life distributions is necessary. In this paper, a novel Detail Fatigue Rating (DFR) method was developed to evaluate the fatigue strength of DED Ti-6.5Al-2Zr-1Mo-1V based on a bimodal Weibull distribution and the excessive restriction on the allowable stress of potential was improved. Meanwhile, a Bimodal Weibull distribution model for fatigue life and its parameter estimation method were established based on a two-parameter Weibull distribution. The fatigue life at a specific reliability level and confidence level was calculated by using the bootstrap method. The calculation results showed that fatigue life estimated by using the bimodal Weibull distribution at the high reliability level and high confidence level is higher than that estimated by using the two-parameter Weibull distribution. Furthermore, The S-N curve at the specified confidence level and reliability level was fitted.