Journal of Intelligent Material Systems and Structures

Shape memory polymers (SMPs) represent a materials class capable of recovering their initial shape, when submitted to deformations, through an external stimulus. This paper focuses on a Shape Memory Thermoplastic Polyurethane (SMPU), characterized by a one-way shape memory effect (SME) activated by temperature. The material was characterized by Differential Scanning Calorimetry (DSC) to find transition temperature; then, it was manufactured by an injection molding machine to perform a campaign of characterization tests. Thermomechanical tests were conducted varying the prescribed strain (up to 25%, 50%, and 80%), imposed at both different strain rates ( 10 − 3 , 10 − 2 , and 10 − 1 s⁻¹), and temperatures (50°C, 60°C, and 70°C); the results were investigated in terms of shape fixity and shape recovery ratios. An excellent memory capability was observed for all the tested conditions; otherwise, the shape recoverability is strongly influenced by all investigated parameters, especially by the strain rate, resulted to be the most effective one. In fact, the shape recovery ratio can increase as much as 20%, when the strain rate is increased from 10 − 3 to 10 − 1 s⁻¹. An opposite effect was observed with the variation of prescribed strain and temperature, the increase of which reduces the ability of the material to return to its original shape.

In a guided-wave-based damage detection hybrid system which combines piezoelectric transducers (PZT) and fiber Bragg grating (FBG) sensors, changes of temperature will affect both the propagation of Lamb waves and the fiber optic (FO) sensor’s spectrum. These variations will mask the changes caused by the occurrence of damage and thus make the damage detection unreliable, if not compensated for. This paper addresses the temperature effect calibration for Lamb wave signals measured by FBG-based Fabry Perot (FP) sensors. First, the temperature effect on the sensor’s spectrum is investigated, and a corresponding calibration method is derived and validated experimentally. After that, FBG-based FP sensor’s capability in measuring both Lamb wave signal (i.e. strain wave) and temperature separately is demonstrated. Finally, a validation test is conducted in which the current state signals are measured under a random temperature, different from that of the baseline temperature. Temperature effect on both sensor sensitivity and guided wave is calibrated based on the proposed calibration algorithm. The compensated signal is then tested with different types of damage index and its reliability in damage detection after applying the compensation algorithm is demonstrated.

In order to track the maximum power point of piezoelectric energy harvesters, an effective approach consists in designing interfaces able to electrically tune the harvester dynamics. Such interface should exhibit—at least—two tunable parameters in order to independently optimize the harvester damping and resonant frequency, that is, an electromechanical impedance matching of the real and imaginary parts of the electrical load. In order to optimize and control these two parameters, it is necessary to implement two control loops that simultaneously impact the harvester dynamics. Furthermore, these loops should combine quick convergence time with low-power consumption in order to react sufficiently fast to compensate for any shift in the vibration frequency and to consume only a small portion of the harvested power. In this paper, we propose a control-law based on the successive evaluation of couples of parameters in order to select the optimal one. First, we determine analytically the expression of a set of optimal couples valid for any two-parameters electrical interfaces. Thereafter, we prove that only a few well-chosen couples of parameters are sufficient to maximize the power on a large frequency band. The proposed methodology has been experimentally verified on a tunable interface, the short-circuit synchronous electric charge extraction. Combined with a strongly coupled piezoelectric energy harvester, we have been able to maintain the harvested power close to the maximal achievable power (i.e. >70% of the maximal achievable power) on a 20 Hz frequency band, with only five couples of parameters. Such approach allows to substitute a multi-parameters convergence algorithm by a single-couple of parameters convergence algorithm, greatly simplifying the algorithm and reducing its convergence time.

The yield stress of ferrofluids has been a hot topic in their rheological studies, and it is still controversial which method could obtain the more accurate yield stress value. In this work, we used varieties of methods to obtain the yield stress of the ferrofluid, including steady shear and oscillatory shear. We obtained the static yield stress and dynamic yield stress of the ferrofluid by Herschel–Bulkley fitting of the flow curves measured by the controlled shear rate mode and the controlled shear stress mode, and found that at any magnetic field strength, the static yield stress was always significantly greater than the dynamic yield stress. We then performed oscillatory shear of the ferrofluid and determined the yield stress using three methods, where the yield stress value corresponding to the intersection of the storage modulus G′ and the loss modulus G″ is similar to the static yield stress value fitted by H-B at low magnetic field strength. The power law function and shear stress as a function of shear strain consistently gave the maximum value of the yield stress. Ultimately, we believe that which method is ultimately chosen depends on the practical application conditions of interest.

This paper proposes the use of a two-dimensional refined finite element model, based on the Carrera Unified Formulation (CUF), to predict the variation in capacitance of embedded piezoelectric sensors. The accurate stress field of laminated structures with embedded sensors has been evaluated by exploiting the capabilities of refined layer-wise models. A fully coupled electro-mechanical formulation has been adopted to predict the piezoelectric response of embedded sensors. Different piezoelectric materials have been considered and a parametric analysis has been carried out including geometrical and physical parameters. The results show that the variation in capacitance is highly affected by the through-the-thickness deformations, that is, classical models cannot be used to predict this phenomenon. The variation in the capacitance value has been confirmed by experimental results proposed in the literature and can be used as a parameter for evaluating the internal stress field.

Self-sensing structures are tremendously needed in transport or energy applications. Nevertheless, structures are rarely designed in advance to harvest energy in realistic operational conditions, leading to sensing functions using most of the time batteries. Thus, this paper proposes a complete application of self-powered sensing using an integrated piezoelectric transducer on a representative composite structure, namely a smart composite reduced-model car. Based on an optimized self-powered Synchronized Switch Harvesting on Inductor circuit (SSHI) coupled with a complete electromechanical behavior study, up to 40 μ W can be harvested on a resistive load of 3M Ω for a linear velocity of 12.5km.h⁻¹. This power allows supplying a temperature sensor and its wireless transmitter, whose data can be sent each 60s. Our functionalized car is a first step toward real industrial application cases and demonstrates the ability of the proposed method to enhance the energy harvesting process on an existing weakly coupled structure and use the vibrations as an energy source for relevant embedded microgenerators and associated self-powered sensors.

The implementation of deterministic design approaches in the presence of uncertainty is an adequate design task. Probabilistic methods are then used in structural design procedures, offering structural safety predictions. In this study, reliability-based analysis of a piezoelectric laminated composite plate subjected to the mechanical loads was investigated, accounting for the epistemic source of uncertainty. Material properties of the plate were considered temperature-dependent. The sophisticated mesh-free finite volume approach was employed to actively control the vibration of the temperature-dependent piezoelectric laminated composite plate through the first-order shear deformation principles. The induced vibration was treated as a non-stationary random process, and the generalized failure index was estimated using the first-passage probability concept by adopting the novel asymptotic sampling technique. The veracity of the suggested model was corroborated by alternate approaches in the literature, comprising the finite element approach. Furthermore, the temperature-dependent piezoelectric laminated composite plate with different ply orientations was considered to assess the safety index variation against changes in the ambient temperature and the laminate stacking orientation. The obtained results revealed that with increasing temperature, the reliability of the composite plate reduced. It was also realized that the reliability index is directly correlated with the piezoelectric voltage.

This study focuses on the electromechanical analysis of functionally graded graphene reinforced piezoelectric composite (FG-GRPC) structures in order to identify circuit metrics such as voltage and power. The graphene platelets (GPLs) scatter evenly and parallelly in each graphene platelets reinforced piezoelectric composite (GRPC) tile. The effective modulus of elasticity for the GRPC tile is calculated by the Halpin-Tsai (HT) parallel model. The rule of the mixture (ROM) is employed to estimate the effective mass density, poisson’s ratio, and piezoelectric properties of GRPC structure. A simple power law distribution is responsible for the spatial disparity in composition over the thickness to generate FG-GRPC structural tiles. The first-order shear deformation theory and Hamilton’s principle are used to derive the governing finite element equations for the FG-GRPC plates. The impact of external resistance, frequency, volume fraction, piezoelectric characteristics, and geometry of the tile on the circuit metrics of FG-GRPC structures are thoroughly examined. Our results reveal that the circuit metrics of FG-GRPC plates are significantly enhanced due to consideration of material grading exponent and a small quantity of GPLs. This article will provide the necessary physical insights for modeling the electromechanical coupling in multipurpose piezoelectric materials, devices, and large-scale systems, allowing them to be used in industrial applications such as pressure sensors, miniature ultrasonic motors, fuel injectors, active controllers, and robotic systems.