Structural health monitoring (SHM) of spacecraft demands sensors to be not only adequately sensitive to subtle changes in structural status, but also resilient to extreme working conditions in outer space. This work presents a fully aerosol-jet-printed (AJP) flexible piezoresistive sensor, monolithically fabricated for robust, durable in-situ monitoring of orbiting space structures. The multi-layer architecture of the sensor is additively manufactured and cured directly onto the host space structure. It features an adhesive-free, space-resilient POSS-polyimide (PI) substrate and an encapsulation providing superior adhesion and intrinsic resistance to atomic oxygen and radiation. The nanocomposites-based sensing layer is printed and cured with an ink specially formulated with a synergistic nanocomposite blend including graphene, multi-walled carbon nanotubes (MWCNTs), and carboxylated MWCNTs (c-MWCNTs) within a polyamic acid (PAA) matrix. The graphene/CNT hybrid structure ensures a high-density, multi-dimensional conductive pathway, while the c-MWCNTs play a dual critical role: the carboxyl groups ensure excellent dispersion within the PAA solution to prevent nanocarbon agglomeration and in the meantime strengthen the interfacial bonding with the final PI matrix. A customized auxetic (re-entrant) geometric design innovatively enhances the performance of the sensor. By strategically concentrating stress in desired areas, this structure translates a given global strain into an amplified local deformation within the sensing element, which simultaneously boosts mechanical stretchability and remarkably increases the gauge factor to ~210, far surpassing conventional rectangular or serpentine geometries. Characterization confirms the performance of the sensor, showing high fidelity in detecting quasi-static strain and dynamic ultrasonic guided waves (20-500 kHz), as well as its proven survivability under simulated space environments (vacuum thermal cycling, atomic oxygen, and radiation). The practical SHM capabilities of the sensor are demonstrated in critical, application-relevant scenarios. Simulated on-orbit thermal strain measurement of spacecraft plate-like components via a distributed flexible sensing network achieves strain field reconstruction with a relative error of less than 5% subjected to a local loading under -50 ℃ to 100 ℃. Furthermore, during the hypervelocity impact (HVI) experiments on sensor-integrated flexible solar arrays, the sensor demonstrates effective acoustic emission (AE) signal acquisition. This capability enables impact localization with a spatial error of less than 3 mm, confirming the suitability of the sensors for monitoring large-area, fragile, non-planar space structures under micrometeoroid and orbital debris (MMOD) impacts. This research delivers a scalable, conformal sensing platform that uniquely integrates (i) an adhesive-free, space-resilient POSS-PI architecture, (ii) a synergistic nanocarbon composite with enhanced interfacial properties, and (iii) geometry-driven sensitivity enhancement. The demonstrated multifunctionality of the sensor—spanning static strain measurement, guided-wave reception, and AE-based impact localization—positions it as a transformative sensing device for next-generation, on-demand SHM of critical space assets.

Piezoresistive nanocomposites have emerged as a promising alternative for structural monitoring, combining low sensor cost, simple fabrication and analysis, and real-time measurement capability. Despite advances in developing new nanocomposites and their experimental applications, there remains a gap in studies addressing the mathematical modeling of their electromechanical behavior. This work presents the development of a constitutive model for a piezoresistive nanocomposite composed of a natural rubber matrix reinforced with carbon nanotubes (CNT) and carbon black (CB), which has previously been employed to detect tightening loss in bolted joints with promising results. The sensor has a washer-shaped geometry and is installed between the bolt washer and the bolted joint interface, so that the deformation generated in the joint alters the electrical response of the sensor. Samples with different nanofiller proportions were fabricated and characterized to extract their piezoresistive properties. Mechanical stress and electrical conductivity under cyclic deformation were approximated by linear relationships whose coefficients varied with nanofiller concentration. Subsequently, a nonlinear formulation was proposed to describe the combined influence of CNT and CB on these coefficients. The model was calibrated using Bayesian inference, enabling the estimation of both conductivity and mechanical stress under various deformation conditions. The proposed constitutive model can be integrated into multiphysics simulation software, enabling virtual testing of the sensor within complex structures and optimizing its characteristics for different applications. The agreement between simulated and experimental results confirms the model’s capability to simulate and tune the sensitivity of nanocomposite sensors by adjusting CNT and CB contents, facilitating the design of customized real-time structural monitoring sensors for specific bolted joint configurations.

Structural health monitoring is becoming increasingly important for the extension of service life, reliability, and safety of large civil, mechanical, and marine structures. While conventional monitoring systems such as Fibre Bragg Gratings, wired electrical strain gauges, and distributed fibre-optic sensing usually offer high accuracy, their installation process is generally complex or requires careful handling and/or expensive instrumentation. In this context, this work presents the development and testing of a new family of low-cost, robust, and scalable strain sensors based on short carbon fibre-reinforced high-density polyethylene. SCF-PP sensors make use of the piezoresistive behaviour of a conductive polymer composite network to allow real-time strain monitoring suitable for integration into large structural components.

For this work, PP was compounded with up to 15 wt% short carbon fibres to produce conductive composite filaments with the ability to transduce mechanical deformation into a measurable electrical resistance change. This filler range was selected based on consideration of percolation behaviour, mechanical compatibility, and manufacturability to ensure a stable conductive network in the resulting composite while maintaining the flexibility and toughness necessary for long-term deployment. The conductive sensors were 3D printed with certain dimensions and cross-sectional area to interpret electrical signals and monitor mechanical strains.

Electrical and mechanical characterisation was carried out to evaluate the piezoresistive performance (Keithely 6485 picoammeter and power supply) of the sensors under controlled tensile loading (tensile machine). A Python code was developed to collect current-time data and convert them to resistance-time data and combine the electrical data with the mechanical results (strain, displacement, load, and stress) in the uniaxial tensile load direction. Linearity in the variation of resistance due to applied strain was seen in different formulations, confirming the suitability of the conductive network for real-time monitoring applications. The sensors were embedded into glass/Epoxy composite substrates representative of those used in large structures, including wind turbine blades and tidal turbine foils, in order to assess application potential. Both static and dynamic loading tests demonstrated a strong correlation between sensor output and conventionally measured applied strain, validating the effectiveness of the SCF–PP sensors for practical structural health monitoring use. The sensors are inherently thin and light in weight, and they can quite readily be conformed to curved geometries; they can also be embedded between composite layers without compromising structural integrity.

A novel nondestructive evaluation, structural health monitoring method based on highly nonlinear solitary waves (HNSWs) has recently emerged. The method is based on the actuation and detection of solitary waves propagating along a 1-D array of identical spheres, the last of which is in dry point contact with the material to be evaluated or monitored. The technique relies on the proved hypothesis that the dynamic interaction between the waves and the material is dependent upon the condition of the latter. The method makes use of the so-called HNSW transducer, which is a generic term to indicate an assemble of a 1-D chain of particles, an electromagnet that lifts and releases the first sphere of the chain, and a sensor embedded in the particles. A typical inspection/monitoring setup is such that the transducer stands still on the sample to be probed while wired to a data acquisition system that controls the excitation and detection of the waves. In the study presented in this paper, the transducer becomes part of a robotic system meant to nondestructively inspect flat and curved metallic surfaces. The functionality of the robot and the ability to perform possible solitary waves based inspection was proven by testing a metallic plate with simulated corrosion. The experimental results are compared to some numerical predictions obtained using commercial software. In certain contexts related to the local inspection or monitoring of pavements, concrete, metallic structures etc., the embedment of HNSW methodology in a moving robot may offer certain advantages (cost, speed, multi-features), which however are yet to be demonstrated.