Experimental and Numerical Analysis of the Deformation Behavior of Adaptive Fiber-Rubber Composites with Integrated Shape Memory Alloys

Fiber-reinforced rubber composites with integrated shape memory alloy (SMA) actuator wires present a promising approach for the creation of soft and highly elastic structures with adaptive functionalities for usage in aerospace, robotic, or biomedical applications. In this work, the flat-knitting technology is used to develop glass-fiber-reinforced fabrics with tailored properties designed for active bending deformations. During the knitting process, the SMA wires are integrated into the textile and positioned with respect to their actuation task. Then, the fabrics are infiltrated with liquid silicone, thus creating actively deformable composites. For dimensioning such structures, a comprehensive understanding of the interactions of all components is required. Therefore, a simulation model is developed that captures the properties of the rubber matrix, fiber reinforcement, and the SMA actuators and that is capable of simulating the active bending deformations of the specimens. After model calibration with experimental four-point-bending data, the SMA-driven bending deformation is simulated. The model is validated with activation experiments of the actively deformable specimens. The simulation results show good agreement with the experimental tests, thus enabling further investigations into the deformation mechanisms of actively deformable fiber-reinforced rubbers.     

Hardening and Softening Behavior of Caliber-Rolled Wire

The different behaviors of the mechanical properties of drawn and caliber-rolled wires with applied strain were investigated to determine the appropriate process between wire drawing and caliber rolling with consideration of materials and process conditions. Ferritic, pearlitic, and TWIP steels were drawn and caliber-rolled under the same process conditions. Caliber-rolled wires exhibited a hardening behavior in the early deformation stage and softening behavior in the later deformation stage compared with the drawn wires, regardless of the steel. The hardening behavior of the caliber-rolled wires was explained by the higher strain induced by caliber rolling compared with wire drawing, especially the higher amount of redundant work in caliber-rolled wire. The caliber-rolled wire had approximately 36% higher strain than the drawn wire and approximately 85% higher strain than nominal strain. The softening behavior of the caliber-rolled wire in later deformation stages was related to the Bauschinger effect or low-cycle fatigue effect caused by the roll geometries and loading conditions during caliber rolling. The different intersection points of the tensile strength between drawn and caliber-rolled wires with the steels were attributed to the different strain hardening rates of each steel. Between the options of the caliber rolling and wire drawing processes, the appropriate process should be selected according to the strain hardening rate of the material and the amount of plastic deformation. For instance, when the wires need to deform at high levels, wire drawing is the better process because of the appearance of the Bauschinger effect in caliber-rolled wire.     

Precise Modeling of Thermal and Strain Rate Effect on the Hardening Behavior of SiC/Al Composite

Temperature and strain rate have significant effects on the mechanical behavior of SiC/Al 2009 composites. This research aimed to precisely model the thermal and strain rate effect on the strain hardening behavior of SiC/Al composite using the artificial neural network (ANN). The mechanical behavior of SiC/Al 2009 composites in the temperature range of 298–623 K under the strain rate of 0.001–0.1 s⁻¹ was investigated by a uniaxial tension experiment. Four conventional models were adopted to characterize the plastic flow behavior in relation to temperature, strain rate, and strain. The ANN model was also applied to characterize the flow behavior of the composite at different strain rates and temperatures. Experimental results showed that the plastic deformation behavior of SiC/Al 2009 composite possesses a coupling effect of strain, strain rate, and temperature. Comparing the prediction error of these models, all four conventional models could not provide satisfactory modeling of flow curves at different strain rates and temperatures. Compared to the four conventional models, the suggested ANN structure dramatically improved the prediction accuracy of the flow curves at different strain rates and temperatures by reducing the prediction error to a maximum of 4.0%. Therefore, the ANN model is recommended for precise modeling of the thermal and strain rate effect on the flow curves of SiC/Al composites.     

Dynamic Behaviors of Mortar Reinforced with NiTi SMA Fibers under Impact Compressive Loading

In this study, a compressive impact test was conducted using the split Hopkinson pressure bar (SHPB) method to investigate SMA fiber-reinforced mortar’s impact behavior. A 1.5% fiber volume of crimped fibers and dog-bone-shaped fibers was used, and half of the specimens were heated to induce recovery stress. The results showed that the appearance of SMA fibers, recovery stress, and composite capacity can increase strain rate. For mechanical properties, the SMA fibers reduced dynamic compressive strength and increased the peak strain. The specific energy absorption of the reinforced specimens slightly increased due to the addition of SMA fibers and the recovery stress; however, the effect was not significant. The composite behavior between SMA fibers and the mortar matrix, however, significantly influenced the dynamic compressive properties. The higher composite capacity of the SMA fibers produced lower dynamic compressive strength, higher peak strain, and higher specific energy absorption. The composite behavior of the dog-bone-shaped fiber was less than that of the crimped fiber and was reduced due to heating, while that of the crimped fiber was not. The mechanical properties of the impacted specimen followed a linear function of strain rate ranging from 10 to 17 s⁻¹; at the higher strain rates of about 49–67 s⁻¹, the linear functions disappeared. The elastic modulus of the specimen was independent of the strain rate, but it was dependent on the correlation between the elastic moduli of the SMA fibers and the mortar matrix.     

Hot Deformation and Constitutive Modeling of TC21 Titanium Alloy

Titanium alloys are extensively employed in the fabrication of various aviation structural parts, of which the most crucial processing step is hot working. In order to study the high-temperature deformation behavior of the TC21 titanium alloy, high-temperature tensile tests were performed. The results reveal that the flow stress of the material gradually decreases with an increased strain rate, and the stress increases rapidly with an increase in strain during the deformation of the alloy. Following this, flow stress gradually decreases. Flow stress decreases sharply, and the sample fractures when the appearance of necking and microvoids is observed. The Arrhenius and Radial basis function (RBF) neural network constitutive models are established in order to accurately describe the high-temperature deformation behavior of the material. In the modified Arrhenius model, strain rate indexes are expressed as a function of deformation temperature and strain rates; furthermore, the high prediction ability of the model was obtained. For the Radial basis function, the network parameters were obtained using the trial-and-error method. The established models could better forecast the flow stress of materials, and highly accurate results are obtained using the radial basis function model. The relationships between the stress index and the deformation activation energy with strain indicate that the primary deformation mechanism involves grain boundary slip and viscous slip of dislocations. The process of dynamic recrystallization primarily promotes the softening of the material.     

Machine-Learning-Based Atomistic Model Analysis on High-Temperature Compressive Creep Properties of Amorphous Silicon Carbide

Ceramic matrix composites (CMCs) based on silicon carbide (SiC) are used for high-temperature applications such as the hot section in turbines. For such applications, the mechanical properties at a high temperature are essential for lifetime prediction and reliability design of SiC-based CMC components. We developed an interatomic potential function based on the artificial neural network (ANN) model for silicon-carbon systems aiming at investigation of high-temperature mechanical properties of SiC materials. We confirmed that the developed ANN potential function reproduces typical material properties of the single crystals of SiC, Si, and C consistent with first-principles calculations. We also validated applicability of the developed ANN potential to a simulation of an amorphous SiC through the analysis of the radial distribution function. The developed ANN potential was applied to a series of creep test for an amorphous SiC model, focusing on the amorphous phase, which is expected to be formed in the SiC-based composites. As a result, we observed two types of creep behavior due to different atomistic mechanisms depending on the strain rate. The evaluated activation energies are lower than the experimental values in literature. This result indicates that an amorphous region can play an important role in the creep process in SiC composites.     

Investigation on the Cyclic Response of Superelastic Shape Memory Alloy (SMA) Slit Damper Devices Simulated by Quasi-Static Finite Element (FE) Analyses

In this paper, the superelastic shape memory alloy (SMA) slit damper system as an alternative design approach for steel structures is intended to be evaluated with respect to inelastic behavior simulated by refined finite element (FE) analyses. Although the steel slit dampers conventionally used for aseismic design are able to dissipate a considerable amount of energy generated by the plastic yielding of the base materials, large permanent deformation may occur in the entire structure. After strong seismic events, extra damage repair costs are required to restore the original configuration and to replace defective devices with new ones. Innovative slit dampers fabricated by superelastic SMAs that automatically recover their initial conditions only by the removal of stresses without heat treatment are introduced with a view toward mitigating the problem of permanent deformation. The cyclically tested FE models are calibrated to experimental results for the purpose of predicting accurate behavior. This study also focuses on the material constitutive model that is able to reproduce the inherent behavior of superelastic SMA materials by taking phase transformation between austenite and martensite into consideration. The responses of SMA slit dampers are compared to those of steel slit dampers. Axial stress and strain components are also investigated on the FE models under cyclic loading in an effort to validate the adequacy of FE modeling and then to compare between two slit damper systems. It can be shown that SMA slit dampers exhibit many structural advantages in terms of ultimate strength, moderate energy dissipation and recentering capability.     

The Application of Ni–Ti SMA Wires in the External Prestressing of Concrete Hollow Cylinders

An innovative method for prestressing structural elements through the use of shape memory alloys (SMAs) is gaining increasing attention in research as this method does not require the use of mechanical anchorages for tendons. The activation of the memory effect by means of temperature variations (Joule effect) in effect produces high stresses in SMA components attached to concrete components as reported in the literature. This paper presents the work performed for the purpose of prestressing concrete hollow cylinders with the use of nickel–titanium (Ni–Ti) SMA wires. In the tests, a variety of hollow cylinders were made using the same concrete mix and with the same wall thickness (20 mm), but with different external diameters (200 mm, 250 mm, and 300 mm). Their prestressing was achieved by the means of Ni-Ti SMA wires of different diameters (1 mm, 2 mm, and 3 mm) wrapped around the cylinders. Longitudinal and circumferential strain during the thermal activation of the SMA wires by Joule heating was measured using gauges located on the internal surface of the hollow cylinders. The experimental protocol, recorded observations, and discussion of the effectiveness of the prestressing of concrete elements as a function of the test parameters are included in the text in detail. Comments on the conditions for effective prestressing of concrete cylinders with SMA wires are proposed in the conclusions of the paper.     

Constitutive Descriptions and Restoration Mechanisms of a Fe-17Cr Alloy during Deformation at Temperatures of 700–1000 °C

The deformation behavior for highly purified Fe-17Cr alloy was investigated at 700~1000 °C and 0.5~10 s⁻¹. The microstructure evolution and corresponding mechanism during deformation were studied in-depth, using electron backscattering diffraction, transmission electron microscopy and precession electron diffraction. During deformation, dynamic recrystallization (DRX) occurred, along with extensive dynamic recovery, and the active DRX mechanism depended on deformation conditions. At higher Zener-Hollomon parameter (Z ≥ 5.93 × 10²⁷ s⁻¹), the development of the shear band was promoted, and then continuous DRX was induced by the formation and intersection shear band. At lower Zener-Hollomon parameter (Z ≤ 3.10 × 10²⁵ s⁻¹), the nucleation of the new grain was attributed to the combination of continuous DRX by uniform increase in misorientation between subgrains and discontinuous DRX by grain boundary bulging, and with increasing temperature, the effect of the former became weaker, whereas the effect of the latter became stronger. The DRX grain size increased with the temperature. For alleviating ridging, it seems advantageous to activate the continuous DRX induced by shear band through hot deformation with higher Z. In addition, the modified Johnson-Cook and Arrhenius-type models by conventional way were developed, and the modified Johnson-Cook model was developed, using the proposed way, by considering strain dependency of the material parameters. The Arrhenius-type model was also modified by using the proposed way, through distinguishing stress levels for acquiring partial parameter and through employing peak stress to determine the activation energy and considering strain dependency of only other parameters for compensating strain. According to our comparative analyses, the modified Arrhenius-type model by the proposed approach, which is suggested to model hot-deformation behavior for metals having only ferrite, could offer a more accurate prediction of flow behavior as compared to other developed models.     

The Longitudinal Compression Capacity of Hollow Concrete Cylinders Prestressed by Means of an SMA Wire

This paper deals with the mechanical behavior of hollow concrete cylinders prestressed with nickel-titanium (Ni-Ti)-shape memory alloy (SMA) wires wound around them. Prestresses can be created by the thermal activation of the memory effect of SMA wire placed on the outer surface of concrete cylinders. In order to assess the stress level in concrete, a model was used to analyze the thermal stresses in the concrete shell resulting from a temperature gradient in the thickness. Another model was used to calculate the circular concentric loading applied by the wound wire resulting from the impairment of its memory effect by the concrete cylinder. Finally, longitudinal compression tests were performed on the prestressed hollow cylinders. Longitudinal and circumferential strains were measured using gauges located on the surfaces of the hollow cylinders. The tests were performed almost one year after the application of prestressing by means of Ni-Ti SMA wire, confirming that the residual stress in the wire remained present. It may therefore be concluded that the prestressing of concrete elements designed with the use of Ni-Ti SMA material is effective for a long time.     

Assessment of individual risk of death using self-report data: an artificial neural network compared with a frailty index

OBJECTIVES: To evaluate the potential of an artificial neural network (ANN) in predicting survival in elderly Canadians, using self-report data. DESIGN: Cohort study with up to 72 months follow-up. SETTING: Forty self-reported characteristics were obtained from the community sample of the Canadian Study of Health and Aging. An individual frailty index score was calculated as the proportion of deficits experienced. For the ANN, randomly selected participants formed the training sample to derive relationships between the variables and survival and the validation sample to control overfitting. An ANN output was generated for each subject. A separate testing sample was used to evaluate the accuracy of prediction. PARTICIPANTS: A total of 8,547 Canadians aged 65 to 99, of whom 1,865 died during 72 months of follow-up. MEASUREMENTS: The output of an ANN model was compared with an unweighted frailty index in predicting survival patterns using receiver operating characteristic (ROC) curves. RESULTS: The area under the ROC curve was 86% for the ANN and 62% for the frailty index. At the optimal ROC value, the accuracy of the frailty index was 70.0%. The ANN accuracy rate over 10 simulations in predicting the probability of individual survival mean+/-standard deviation was 79.2+/-0.8%. CONCLUSION: An ANN provided more accurate survival classification than an unweighted frailty index. The data suggest that the concept of biological redundancy might be operationalized from health survey data.     

Vibration Control of a Wind-Excited Transmission Tower-Line System by Shape Memory Alloy Dampers

To be typical electrical power infrastructures, high-rise tower-line systems are widely constructed for power transmission. These flexible tower structures commonly possess small damping and may suffer strong vibrations during external excitations. The control approaches based on various devices have been developed to protect transmission towers against strong vibrations, damages, and even failure. However, studies on the vibrant control of wind-excited tower-line systems equipped with SMA dampers have not yet been reported. To this end, the control approach for wind-excited tower-line systems using SMA dampers is conducted. The mechanical model of the tower-line system is established using Lagrange’s equations by considering the dynamic interaction between transmission lines and towers. The vibration control method using SMA dampers for the tower-line coupled system is proposed. The control efficacy is verified in both the time domain and the frequency domain. Detailed parametric studies are conducted to examine the effects of physical parameters of SMA dampers on structural responses and hysteresis loops. In addition, the structural energy responses are computed to examine the control performance.     

Application of ANN for Analysis of Hole Accuracy and Drilling Temperature When Drilling CFRP/Ti Alloy Stacks

Drilling of Carbon Fiber-Reinforced Plastic/Titanium alloy (CFRP/Ti) stacks represents one of the most widely used machining methods for making holes to fasten assemblies in civil aircraft. However, poor machinability of CFRP/Ti stacks in combination with the inhomogeneous behavior of CFRP and Ti alloy face manufacturing and scientific community with a problem of defining significant factors and conditions for ensuring hole quality in the CFRP/Ti alloy stacks. Herein, we investigate the effects of drilling parameters on drilling temperature and hole quality in CFRP/Ti alloy stacks by applying an artificial neuron network (ANN). We varied cutting speed, feed rate, and time delay factors according to the factorial design L₉ Taguchi orthogonal array and measured the drilling temperature, hole diameter, and out of roundness by using a thermocouple and coordinate measuring machine methods for ANN analysis. The results show that the drilling temperature was sensitive to the effect of stack material layer, cutting speed, and time delay factors. The hole diameter was mainly affected by feed, stack material layer, and time delay, while out of roundness was influenced by the time delay, stack material layer, and cutting speed. Overall, ANN can be used for the identification of the drilling parameters–hole quality relationship.     

Inverse Determination of Johnson–Cook Parameters of Additively Produced Anisotropic Maraging Steel

In powder bed-based additive manufacturing (AM), complex geometries can be produced in a layer-wise approach. Results of material science experiments regarding material property identification, e.g., tensile strength, show interdependencies between the test load direction and the layer orientation. This goes hand-in-hand with the measured cutting force, changing with the relative angle between cutting direction and layer orientation in orthogonal cutting tests. However, due to the specific process characteristics, the layer orientation results in anisotropic material properties. Therefore, during machining, the material behaves depending on the buildup direction, which influences the cutting process. To predict this behavior, a simplified inverse approach is developed to determine the buildup direction-dependent parameters of a modified Johnson–Cook model for cutting simulation. To qualify these cutting models, mainly the cutting force and additionally the chip formation examined during orthogonal cuts are used. In the present paper, the influence of the laser-powder-bed-fusion (LPBF) process parameters on subtractive post-processing are shown. A good agreement between verification experiments and simulations is achieved.     

Mechanical Properties and Constitutive Model Applied to the High-Speed Impact of Aluminum Foam That Considers Its Meso-Structural Parameters

In this work, quasistatic mechanical compression experiments were used to study the stress–strain relationship of aluminum foam, and the mechanism of the compressive deformation of aluminum foam under quasistatic compression conditions is discussed based on the experimental observations. Since the interactions among cells of the aluminum foam and differences in compressive strength among cells substantially impacted the mechanical properties of the material, the cellular structural parameters, namely the cell size and cell wall thickness, were defined. Along with the mechanism of deformation of a single cell, the influence of structural parameters on the micro failure mechanism and the stress–strain relationship of the aluminum foam material was analyzed. In combination with the factors influencing the mechanical properties of the aluminum foam, a mechanical constitutive model of aluminum foam suitable for multi-density and multi-impact environments that considers cellular structure density was established to predict the complete stress–strain relationship of aluminum foam under a high strain rate. The coupling function of strain rate and temperature in the original model was verified and the parameters were determined by the compression experiments under different strain rates and different temperatures.     

Effect of Tension-Compression Asymmetry Response on the Bending of Prismatic Martensitic SMA Beams: Analytical and Experimental Study

This paper aims to analytically derive bending equations, as well as semi-analytically predict the deflection of prismatic SMA beams in the martensite phase. To this end, we are required to employ a simplified one-dimensional parametric model considering asymmetric response in tension and compression for martensitic beams. The model takes into account the different material parameters in martensite twined and detwinned phases as well as elastic modulus depending on the progress of the detwinning process. In addition, the model considers the diverse slope of loading and unloading in martensite detwinned phases favored by tension and compression. To acquire general bending equations, we first solve the pure bending problem of a prismatic SMA beam. Three different phases are assumed in the unloading procedure and the effect of neutral fiber distance from the centerline is also considered during this stage. Then according to the pure bending solution and employing semi-analytical methods, general bending equations of an SMA beam are derived. Polynomial approximation functions are utilized to obtain the beam deflection–length relationship. To validate the attained analytical expressions, several three- and four-point bending tests were conducted for rectangular and circular SMA beams. Experimental data confirm the reasonable accuracy of the analytical results. This work may be envisaged to go deep enough in investigating the response of SMA beams under an arbitrary transverse loading and stress distribution during loading and unloading, as well as findings may be applicable to a good prediction of bending behavior.     

Prediction of the Compressive Strength of Recycled Aggregate Concrete Based on Artificial Neural Network

Recycled aggregate concrete (RAC), due to its high porosity and the residual cement and mortar on its surface, exhibits weaker strength than common concrete. To guarantee the safe use of RAC, a compressive strength prediction model based on artificial neural network (ANN) was built in this paper, which can be applied to predict the RAC compressive strength for 28 days. A data set containing 88 data points was obtained by relative tests with different mix proportion designs. The data set was used to develop an ANN, whose optimal structure was determined using the trial-and-error method by taking cement content (C), sand content (S), natural coarse aggregate content (NCA), recycled coarse aggregate content (RCA), water content (W), water–colloid ratio (WCR), sand content rate (SR), and replacement rate of recycled aggregate (RRCA) as input parameters. On the basis of different numbers of hidden layers, numbers of hidden layer neurons, and transfer functions, a total of 840 different back propagation neural network (BPNN) models were developed using MATLAB software, which were then sorted according to the correlation coefficient R². In addition, the optimal BPNN structure was finally determined to be 8–12–8–1. For the training set, the correlation coefficient R² = 0.97233 and RMSE = 2.01, and for the testing set, the correlation coefficient R² = 0.96650 and RMSE = 2.42. The model prediction deviations of the two were both less than 15%, and the results show that the ANN achieved pretty accurate prediction on the compressive strength of RAC. Finally, a sensitivity analysis was carried out, through which the impact of the input parameters on the predicted compressive strength of the RAC was obtained.     

Complete Stress–Strain Relations of Early-Aged Cementitious Grout under Compression: Experimental Study and Constitutive Model

The compressive stress–strain behaviors of early-aged cementitious grout specimens were experimentally investigated, and the differences of characteristic parameters of the stress–strain curve and the energy evolution law of each specimen under uniaxial compression were discussed in this study. The results indicate that with an increase in the specimen age, the peak stress, peak strain, ultimate strain, elastic modulus, peak secant modulus, strain ductility coefficient, and energy-dissipation coefficient of the prism specimens gradually improved. Additionally, a comparison of the test results of cementitious grout specimens and concrete specimens with the same age reveals that the peak stress, peak strain, and ultimate strain of cementitious grout specimens were greater than that of concrete specimens, the elastic modulus and peak secant modulus of the specimens were less than that of concrete specimens, and the strain ductility coefficient and energy-dissipation coefficient show no consistent conclusions with respect to the material type. Moreover, comparing the energy evolution curves of specimens with different specimen ages shows that the decrease rate of the elastic strain rate and the increase rate of the dissipated energy rate gradually decreased with the increase in specimen age. The elastic strain rate and dissipated energy rate of the CGM−270 specimen and control specimens were greater than that of other specimens, and the decrease rate of the elastic strain rate was less than that of other specimens. Based on the statistical damage theory, a statistically stochastic damage constitutive model was derived by considering the characteristics of cementitious grout according to the compression test results. A comparison of the proposed models with the experimental results indicated that the proposed stress–strain constitutive models were sufficiently accurate.     

Damage Detection in Flat Panels by Guided Waves Based Artificial Neural Network Trained through Finite Element Method

Artificial Neural Networks (ANNs) have rapidly emerged as a promising tool to solve damage identification and localization problem, according to a Structural Health Monitoring approach. Finite Element (FE) Analysis can be extremely helpful, especially for reducing the laborious experimental campaign costs for the ANN development and training phases. The aim of the present work is to propose a guided wave-based ANN, developed through the use of the Finite Element Method, to determine the position of damages. The paper first addresses the development and assessment of the modeling technique. The FE model accuracy was proven through the comparison of the predicted results with experimental and analytical data. Then, the ANN was developed and trained on an aluminum plate and subsequently verified in a composite plate, as well as under different damage configurations. According to the results herein proposed, the ANN allowed to detect and localize damages with a high level of accuracy in all cases of study.     

A New Setup for Simulating the Corrosion Behavior of Orthodontic Wires

The aim of this study was to create a new reliable setup to evaluate commercially available orthodontic wires used during orthodontic treatment. The setup includes various techniques applied for testing metal alloy materials. The materials were tested under extreme conditions to simulate their behavior in the mouth. The alloy composition of each wire was tested. The electrochemical (EC) testing and characterization of the corrosion performance of the wires was calculated by the electrochemical curves at pH = 1 in two different applied potentials to test the reaction of the material. The liquid collected after the EC measurements was analyzed by inductively coupled plasma-mass spectrometry (ICP-MS) to verify the reliability of the EC curves and for a more accurate evaluation of the corrosion behavior of the wires. Therefore, the EC measurements were compared to the actual values obtained from the released ions found in the solution. At the end, a surface analysis was performed to detect corrosion on the wires. In conclusion, this study developed a setup to test and better understand the corrosion behavior and ion release of the orthodontic wires, metal alloy dental materials, and other metals used in the oral cavity. This method can contribute to dental material selection in patients with underlying health conditions.