This study presents the development and validation of a hybrid Structural Health Monitoring (SHM) methodology applied to a full-scale morphing flaperon demonstrator, representing the final stage of the building-block approach within the Next Generation Civil TiltRotor (NGCTR) initiative of the Clean Sky 2 programme. The component is manufactured from Toray Cetex® TC1200 PEEK carbon-fibre reinforced laminate, combining high mechanical performance with recyclability and therefore aligning with the sustainability targets of next-generation aerostructures.

The proposed SHM system integrates a piezoelectric (PZT) transducer network and distributed fibre-optic sensors (DFOS) within a multimodal architecture. UGW data are acquired using a round-robin pitch–catch scheme, where each PZT is sequentially driven as an actuator while the remaining transducers operate as receivers. DFOS measurements are performed using a custom Brillouin Optical Frequency-Domain Analysis (BOFDA) interrogator, providing distributed strain measurements with spatial resolution down to 8 mm. The sensors are deployed as a surface-bonded patch including PZT transducers and a polyimide-coated single-mode fibre; the fibre is bonded with cyanoacrylate adhesive following a zigzag layout to maximise surface coverage. While surface bonding supports retrofit-friendly deployment, adhesive durability under cyclic loading and thermal variations remains a key consideration; mitigation options include adhesive qualification, protective coatings, or sensor embedding where feasible.

A hybrid numerical–experimental test matrix supports the validation campaign. Finite element models are used to simulate guided-wave propagation and load–damage interactions and are verified on the real demonstrator under four representative conditions: (i) undamaged and unloaded, (ii) undamaged under quasi-static loading, (iii) damaged and unloaded, and (iv) damaged under load. Experimentally, impact-like damage is emulated via an added-mass surrogate to reproduce first-order guided-wave scattering effects without compromising structural integrity. Aerodynamic-type quasi-static loading is applied at the leading edge using a custom-designed fixture to reproduce in-flight stress states, ensuring accurate load transfer and repeatable boundary conditions. This enables assessment of the combined effects of load and damage on both ultrasonic and optical responses.

Numerically, impact-like damage is represented through a localized stiffness-reduction (delamination-like) surrogate, enabling direct UGW propagation simulations that capture first-order scattering trends and load–damage coupling.

Experimental and simulated data are processed through UGW damage imaging and multimodal discrimination: UGW signals are converted into damage-sensitive indices and imaged using the probabilistic multistage (PM) localisation framework previously developed and validated by the authors, while DFOS strain fields are analysed to identify localised strain anomalies. Finally, UGW indices and DFOS-derived strain features are combined at decision level to discriminate between damaged-only, loaded-only, and loaded-damaged scenarios, mitigating load-induced ambiguity in UGW-based diagnostics.

Overall, the results confirm the robustness of the proposed hybrid SHM methodology, demonstrating its applicability to a real aerospace component in a relevant environment and supporting a significant increase in Technology Readiness Level (TRL).

The long-term structural integrity of road infrastructures represents a critical challenge to transportation efficiency, public safety, and maintenance and rehabilitation costs of a nation’s infrastructure. Traditional inspection methodologies often fail to capture the full extent of pavement deterioration. As the pavement network continues to age, it becomes increasingly important to implement innovative and more accurate methods of condition evaluation, promoting continuous monitoring of the overall network. This study presents an innovative on-road demonstration of a distributed fibre optic sensing (FOS) system for long-term pavement damage detection, developed within the framework of the InfraROB EU Project.

The primary objective of this research is to validate the effectiveness, durability, and reliability of embedded distributed FOS technology for real-time SHM of pavements under operational conditions, including: (1) demonstrating the feasibility of automated fibre integration during the paving process, (2) evaluating sensor integrity after embedding operations, and (3) assessing the system's capability to detect strain and temperature variations indicative of structural anomalies.

The experimental demonstration was conducted on the A9 highway near Spielfeld, Austria, by using a specially developed automatic drop-off system for fibre integration. Two types of FOS were embedded during asphalt lay-down: distributed strain-sensitive (Solifos BRUsens DSS 3.2 mm V9 grip fibres) and temperature-sensitive cables (Solifos BRUsens DTS STL PA 2F fibres).

After the asphalt lay-down process, Optical Backscatter Reflectometry (OBR) characterisation, by using Luna Technologies' OBR 4600, was carried out. The OBR measurements verified fibre integrity and continuity following the embedding process, identifying potential defects such as breaks and attenuations. Moreover, the system enabled high-resolution strain and temperature measurements.

The results obtained during the on-site demonstration highlight the functional performance of the embedded FOS in capturing the early-stage mechanical and thermal behaviour of the asphalt pavement. One DSS and one DTS were selected as representative cases under real installation conditions.

Figure 1(a) shows the strain profile detected along the DSS on the third day after pavement construction. The measurement is referenced to data acquired on the second day, when no external load was applied. Despite the absence of traffic or induced mechanical stress, the fibre recorded small, localised strain variations along its length. These fluctuations are associated with internal mechanical effects arising from the natural cooling and consolidation of the asphalt layer. The continuous and stable signal confirms that the fibre remained fully operational after the embedding process and was able to detect deformation phenomena linked to the evolving material conditions.

To properly correlate the strain response to the mechanical effect, avoiding thermal influences, a dedicated DTS temperature-sensing fibre was employed. Figure 1(b) displays the temperature profile along the embedded section of the fibre. The profile became stable and uniform, consistent with the expected thermal evolution of the asphalt layer during the early cooling phase, supporting the decoupling of thermal and mechanical effects.

Overall, the results verify that the embedded optical fibres remained operational after automated-installation and prove the ability of detecting strain and temperature variation, supporting the use of fibre optic sensing technologies for continuous SHM monitoring of road infrastructures.

Composite structures made of CFRPs are increasingly adopted in aerospace and high-performance engineering applications due to their superior strength-to-weight ratio and excellent fatigue resistance. However, their susceptibility to barely visible impact damage (BVID), especially following Low Velocity Impact (LVI) events, remains a critical challenge in structural integrity management. These damages, often invisible on the surface, can lead to internal delaminations that compromise long-term performance under cyclic loading conditions. To address this challenge, Structural Health Monitoring (SHM) systems have been increasingly adopted in aerospace and engineering fields. One of the most promising methods for SHM involves the use of distributed fiber optic sensors (DFOS), in virtue of their low size, light weight, high sensitivity and the ability to detect small strain changes, which makes them particularly effective in monitoring the early stages of damage progression.

As part of the TU-LEARN (Structural Life Extension Enhanced by Artificial Intelligence) project, funded by Unione Europea – Next Generation EU, under the PRIN 2022 PNRR – D.D. n. 1409 del 14-09-2022 program, this study investigates the fatigue-driven progression of LVI-induced damage using a Brillouin Optical Frequency-Domain Analysis (BOFDA) system capable of distributed strain measurements with 8-mm spatial resolution. The experimental investigation was conducted on multiple CFRP specimens with nominal dimensions of 100 mm × 150 mm × 2.7 mm. All laminates featured a symmetrical stacking sequence of [(45/−45/90/0)]₂_s. For DFOS measurements, a polyimide-coated optical fiber with an outer diameter of 145 μm was bonded to the surface of each specimen, as highlighted in orange in Fig. 1(a). Additionally, six PZT transducers were surface-mounted in a 2×3 array near the central area of each panel, to realize ultrasonic guided wave (UGW) investigation along multiple directions. Each specimen was impacted at its planar center with an energy level of 15 J using a StepLab DW 2000 drop tower. Then, a compressive-compressive fatigue loading was applied under cyclic conditions (stress ratio R = 0.1, fatigue load frequency f = 4 Hz), using a StepLab Dynamic UD040. In the pristine state, after the impact and at predetermined interruption points of the fatigue load, damage growth was tracked using BOFDA strain maps for 3 different compression loads (L = 5 kN, L = 10 kN, L = 15 kN), as well as UGW-based signal analysis across all actuator-receiver combinations. As an example, we show in Figure 1(b) the strain profiles acquired via our BOFDA sensor, under a constant compressive load of 5 kN and at various fatigue stages. The acquired profiles show a gradual increase in the compressive strain levels, compatible with the delamination growth and consequent stiffness degradation of the laminate. Some acceleration in the strain increase was observed when passing from 800k to 1000k fatigue cycles, i.e. in proximity of the panel failure occurred after 1010k cycles. Similar results, obtained on other panels and with different compressive loads, indicate that the high-resolution strain field measurements provided by BOFDA sensors are effective in indicating internal damage progression in CFRP panels subjected to cyclic loading.

Bridges are continuously exposed to temperature variations caused by solar radiation and environmental conditions. These fluctuations induce global structural deformations and stress redistributions due to material properties, structural configurations, and boundary restraints. Temperature also affects structural health monitoring sensors, which may produce biased outputs if thermal effects are not properly compensated. Understanding both structural and sensor-related thermal influences is therefore essential for the reliable interpretation of monitoring data in existing bridges.

This study investigates the influence of temperature on static load test results using an integrated monitoring system composed of distributed fiber optic sensing (DFOS) and linear variable differential transformers (LVDTs). The high spatial resolution of DFOS provides continuous strain measurements along the bridge girders, while LVDTs record discrete local displacements. Particular attention is given to separating mechanically induced strain from temperature-related effects at both the structural and sensor levels. The most appropriate temperature compensation strategies are therefore investigated to isolate the structural response due to external loading.

The methodology is applied to a prestressed concrete bridge in Switzerland through nine static load tests performed with a truck positioned at different locations along the bridge span. The results highlight the significant impact of temperature on both structural response and sensor measurements. After temperature compensation, bridge displacements predicted from DFOS measurements are compared with LVDT measurements, showing strong agreement and confirming the effectiveness of the proposed approach. These findings emphasize the crucial importance of properly accounting for thermal effects when interpreting monitoring data for existing bridges.

Buckling in slender members, including rods and plates, can cause a sudden loss of load-carrying capacity and stiffness, which poses safety risks. Point sensors such as strain gauges may miss localized curvature peaks and can fail when deformation becomes large. On the other hand, distributed fiber‑optic shape sensing based on OFDR‑FBG, implemented in a stress‑free, non‑bonded configuration, enables lightweight, full‑field measurements with high spatial resolution and real‑time updates without risking sensor failure at large curvature or altering the host stiffness (Fig. 1).

We present a four‑core multi‑core fiber (MCF) OFDR‑FBG shape‑sensing approach routed inside a PTFE tube and mounted non‑bonded along a thin aluminum rod. The system reconstructs the rod centerline shape in real time from distributed strain sampled at approximately 0.6 mm spacing, and it tracks the progression from pre‑buckling to post‑buckling while identifying changes in buckling mode. This capability does not rely on visual data, which is valuable when visual inspection is unavailable (e.g., underwater or in low‑light environments) and where accelerometers may not reliably resolve mode changes under complex boundary and loading conditions.

Our objectives are to demonstrate real-time buckling monitoring with a four-core OFDR-FBG system, to reconstruct shape with sub-millimeter spatial sampling, to monitor post-buckling behavior, and to define possible early-warning indicators based on the maximum curvature and its growth rate. Performance is evaluated by RMS error in shape, RMS error in curvature, and repeatability across runs, using the vision-derived shape as ground truth.

The current system delivers continuous distributed strain, supports real-time reconstruction, detects the onset of buckling, identifies buckling mode, and follows post-buckling deformation without sensor damage. Trends in maximum curvature and its rate increase as the instability approaches, suggesting that possible early warning is achievable once thresholds are tuned and verified.

We expect to show that a stress-free, non-bonded four-core OFDR-FBG configuration can track shape in real time to provide structural health monitoring for thin structures. We further expect to conclude that real-time monitoring, mode tracking, and post-buckling analysis are feasible with high spatial resolution, even in settings where visual inspection/data are unavailable.Anticipated limitations include thermal effects and sensitivity to boundary assumptions, which we plan to mitigate through temperature referencing and calibration. These results are intended to form a foundation for future SHM of slender components and to extend to other materials and geometries.

Despite the implementation of seals and coatings to protect structures such as bridges, defects can result in costly repairs and diminished usability. Conventional moisture sensors offer limited capabilities, providing only local measurements, which hinders the ability to detect and localize damage over large areas.
Distributed Fiber Optic Sensors (DFOS), which utilize optical frequency domain reflectometry (OFDR), facilitate the acquisition of precise spatial measurements. The application of a hygroscopic coating facilitates the detection of strains induced by humidity. In order to differentiate between the effects of temperature and humidity, two fibers with different sensitivities are combined. The reactivity of these materials is determined through calibration in a climate chamber with controlled temperature and humidity cycles.
Conventional calibration approaches are not standardized and rely on the assumption of linear behavior. This paper presents the preprocessing of DFOS data for the purpose of distributed humidity sensing.
The subsequent processing delineates the procedure for determining the reaction coefficients. When the temperature range is small, it is reasonable to assume linear behavior. This model is no longer viable for the purpose of extrapolating the regression. A polynomial regression model is recommended to achieve greater accuracy. The final step in the process entails the implementation of two distinct tests: the small calibration test and the extended calibration test.