Vibration-based structural health monitoring (SHM) of (large) infrastructure through operational modal analysis (OMA) is a commonly adopted strategy. This is typically a four-step process, comprising estimation, tracking, data normalization, and decision-making. These steps are essential to ensure structural modes are correctly identified, and results are normalized for environmental and operational variability (EOV). Other challenges, such as nonstructural modes in the OMA, for example, rotor harmonics in (offshore) wind turbines (OWTs), further complicate the process. Typically, these four steps are considered independently, making the method simple and robust, but rather limited in challenging applications, such as OWTs. Therefore, this study aims to combine tracking, data normalization, and decision-making through a single machine learning (ML) model. The presented SHM framework starts by identifying a “healthy” training dataset, representative of all relevant EOV, for all structural modes. Subsequently, operational and weather data are used for feature selection and a comparative analysis of ML models, leading to the selection of tree-based learners for natural frequency prediction. Uncertainty quantification (UQ) is introduced to identify out-of-distribution instances, crucial to guarantee low modeling error and ensure only high-fidelity structural modes are tracked. This study uses virtual ensembles for UQ through the variance between multiple truncated submodel predictions. Practical application to monopile-supported OWT data demonstrates the tracking abilities, separating structural modes from rotor dynamics. Control charts show improved decision-making compared to traditional reference-based methods. A synthetic dataset further confirms the approach’s robustness in identifying relevant natural frequency shifts. This study presents a comprehensive data-driven approach for vibration-based SHM.

Typically, the fuselage of a modern military aircraft is designed in such a way that the propulsion system is integrated into it. The main reasons are reduction of installation space and minimisation of radar signature. Those requirements can be achieved by using highly bent engine intakes, which are occluding a direct line of sight to the compressor system. Depending on their design, secondary flows and flow separation can be expected due to the strong curvature of the intake system. In this study, a serpentine intake in front of the Larzac 04 test engine is investigated experimentally and its performance compared with and without flow stabilising measures. In detail, a configuration with vortex generators was compared experimentally with a configuration of active flow control by injected air. In order to analyse and compare the efficiency of both systems, the dimensionless total pressure coefficient, the distortion coefficient (DC60) and detailed surface pressure distributions as well as the aerodynamic interface plane are evaluated. In addition, different throttle lines were recorded for surge line evaluation of the low pressure compressor of the Larzac engine and compared for each flow-stabilising measure investigated. It was found that the application of injecting air showed a larger improvement in surge margin and reduction in distortion coefficients compared to the passive flow control.

In this paper, we designa robust Successive Generalised Dynamic Inversion (SGDI) flight control system for high-performance trajectory tracking of target sun-synchronous orbit Satellite Launch Vehicles (SLVs). The robust SGDI control system is designed to track an optimal reference trajectory such that the desired orbital terminal conditions of the ascent flight phase are achieved. The proposed SGDI is composed of two loops. The attitude control loop employs Dynamically Scaled Generalised Inversion (DSGI) of Servo Constraint Dynamics (SVD) in the deviations of Euler attitude angles from their desired optimal trajectories. The inner-dynamics control loop employs DSGI of an SVD in the SLV angular velocity components. Robustification control elements are augmented within the two loops of the baseline SGDI control system to overcome control performance degradation due to dynamic scaling of the Moore-Penrose generalised inverse, modeling and parametric uncertainties, and exogenous disturbances. The robust SGDI control system works to enforce global convergence of the SLV attitude trajectories to the reference trajectories. The high-performance attributes of the robust SGDI control system are verified via comparisons with a classical sliding mode control system, and by performing numerous runs of Monte Carlo simulations under various types of uncertainties and external wind disturbances.

Aiming at the problems of poor coordination effect and low positioning accuracy of unmanned aerial vehicle (UAV) formation cooperative navigation in complex environments, an adaptive time-varying factor graph framework UAV formation cooperative navigation algorithm is proposed. The proposed algorithm uses the factor graph to describe the relationship between the navigation state of the UAV fleet and its own measurement information as well as the relative navigation information, and detects the relative navigation information at each moment by the double-threshold detection method to update the factor graph model at the current moment. And the robust estimation is combined with the factor graph, and the weight function measurements are used in the construction of the factor nodes for adaptive adjustment to make the system highly robust. The simulation results show that the proposed method realises the effective fusion of airborne multi-source sensing information and relative navigation information, which effectively improves the UAV formation cooperative navigation accuracy.

An advanced deformable Kirkpatrick–Baez (K-B) mirror system was developed, equipped with high-speed piezoelectric actuators, and designed to induce beam decoherence and significantly enhance the quality of X-ray imaging by minimizing undesirable speckles in synchrotron radiation or free-electron laser facilities. Each individual mirror is engineered with 36 independent piezoelectric actuators that operate in a randomized manner, orchestrating the mirror surface to oscillate at a high frequency up to 100 kHz. Through in situ imaging single-slit diffraction measurement, it has been demonstrated that this high-frequency-vibration mirror system is pivotal in disrupting the coherent nature, thereby diminishing speckle formation. The impact of the K-B mirror system is profound, with the capability to reduce the image contrast to as low as 0.04, signifying a substantial reduction in speckle visibility. Moreover, the coherence of the X-ray beam is significantly lowered from an initial value exceeding 80% to 13%.

This study investigates the influence of release timing on the trajectory of internal store separation through numerical solutions of continuity, momentum, energy equations and six degrees of freedom equations in a coupled manner. The internal store separation process in advanced fighter aircraft is analysed using computational fluid dynamics (CFD) and six degrees of freedom equations of motion. Initially, the equations of motion are validated by reenacting the Eglin Air Force Base study, an external store separation example with documented experimental results. Subsequently, validation is extended to the M219 cavity problem. In the internal store separation analysis, a cavity with an L/D ratio of 5, a freestream velocity of 0.85 Mach, and a generic store are utilised. Detached eddy simulation (DES) is applied using both static and dynamic mesh techniques in all numerical solutions. The generic store, positioned within a clean cavity with a 90-degree flap angle, was released at two distinct times, corresponding to the points of maximum and minimum gravitational forces. Interestingly, the results show that releasing the store when the normal force acting on it is at its maximum does not necessarily provide an optimal separation. Specifically, when the force coefficient was at its maximum (0.14), the store collided with the cavity door flap after 0.171465 seconds. In contrast, when the force coefficient was at its minimum (-0.04), the store contacted the cavity door after 0.170295 seconds at the same location. Despite the differences in force magnitudes, the trajectories were nearly identical, suggesting that the timing of the release may not have a significant effect on preventing collision. This further emphasises the need for flow control methods to ensure safe and effective store separation.

Molnupiravir Form I crystallizes in space group C2 (#5) with a = 6.48110(17), b = 8.71848(19), c = 27.0607(19) Å, β = 91.920(4)°, V = 1528.22(12) Å3, and Z = 4 at 295 K. The crystal structure consists of supramolecular double layers of molecules parallel to the ab-plane. The layer centers consist of hydrogen-bonded rings forming a 2D network and the outer surfaces of isopropyl groups, with van der Waals interactions between the layers. Each O atom acts as an acceptor in at least one hydrogen bond. A strong O–H⋯O hydrogen bond forms between the hydroxyl group of the oxolane ring and the carbonyl group of the oxopyrimidine ring. The other oxolane hydroxyl group forms bifurcated intra- and intermolecular hydrogen bonds. The hydroxylamino group forms an intramolecular O–H⋯N hydrogen bond with an N atom of the oxopyrimidine ring. The amino group forms an intermolecular N–H⋯N hydrogen bond to the same N atom of the ring. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).