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Temperature and humidity measurements in electrochemical energy devices are essential for maximizing their overall performance under different operating conditions and avoiding hazardous consequences that may arise from the malfunction of these systems. Using sensors for in situ measurements of temperature and relative humidity (RH) is a promising approach for continuous monitoring and management of electrochemical power sources. Here, we report on the feasibility of using thread-based sensors for in situ measurements of temperature and RH in proton exchange membrane fuel cells (PEMFCs) as an example of electrochemical energy devices. Commodity threads are low-cost and flexible materials that hold great promise for the creation of complex three-dimensional (3D) circuits using well-established textile methods such as weaving, braiding, and embroidering. Ex situ and in situ characterization show that threads can be introduced in the gas diffusion layer (GDL) structure to inscribe water highways within the GDL with minimal impact on the GDL microstructure and transport properties. Fluorinated ethylene propylene (FEP) is coated on thread-based sensors to decouple the response to temperature and humidity; the resulting threads achieve a linear change of resistance with temperature (−0.31%/°C), while RH is monitored with a second thread coated with poly(dimethylsiloxane) (PDMS). The combination of both threads allows for minimally invasive and dynamically responsive monitoring of local temperature and RH within the electrode of PEMFCs.

Inter-ply slippage is known to be an important mechanism taking place during forming processes of textile composites, especially with respect to multi-layer fabric lay-ups. The coefficient of friction between the plies strongly depends on the structure and the orientation of forming fabric. Despite many numerical and experimental investigations, this dependency and its effect on the interaction between the plies has been overlooked. In this paper, the effect of fiber orientation on the interlayer friction of a typical thermoplastic fabric prepreg at room temperature is investigated. Results, through a polar representation of data, revealed that both static and dynamic coefficients of friction are statistically dependent on the lay-up orientation, applied normal load, along with their interaction. Further, it was identified that the repeated frictional loading of the plies results in a hysteresis, particularly for asymmetric layups due to non-negligible movement and realignment of filaments at the micro-scale. Finally, an empirical model was developed using an interpolation function (for pressure dependency) combined with a Fourier series (for orientation dependency), to predict the coefficients of friction.

In this article, the viscoelastic behavior of fabric yarns is modeled by a new means of fractional calculus. First, the constitutive relation of the fractional “Poynting-Thomson” model is developed to investigate the behavior of yarns. The proposed material constitutive relation is a differential equation of fractional order, where the response to a unit step of stress (for determination of creep compliance), or a unit step of strain (for stress relaxation modulus) can be readily found in the literature. Here, focusing on the stress relaxation, the response function is fitted to the experimental data of yarns in a typical woven fabric prepreg, at both dry and partially consolidated conditions. The yarns were made of E-glass fibers comingled with polypropylene fibers. The results showed a significant agreement with experimental data along with improved predictions of the new fractional modeling approach when compared to other approaches such as the integer order model and Prony series. For early relaxation times, especially for [Formula: see text] a considerable discrepancy was observed between the values of relaxation modulus obtained by the experiments and that by the integer-order derivative model. However, the results extracted via the fractional derivatives were in close agreement with experimental results at all relaxation times. Using the fractional properties of the yarns, the variation of storage and loss moduli of the yarns with external frequency loading was also predicted, capturing both the rubbery and glassy regions of the material frequency response.

Three-dimensional flexible porous conductors have significantly advanced wearable sensors and stretchable devices because of their specific high surface area. Dip coating of porous polymers with graphene is a facile, low cost, and scalable approach to integrate conductive layers with the flexible polymer substrate platforms; however, the products often suffer from nanoparticle delamination and overtime decay. Here, a fabrication scheme based on accessible methods and safe materials is introduced to surface-dope porous silicone sensors with graphene nanoplatelets. The sensors are internally shaped with ordered, interconnected, and tortuous internal geometries (i.e., triply periodic minimal surfaces) using fused deposition modeling (FDM) 3D-printed sacrificial molds. The molds were dip coated to transfer-embed graphene onto the silicone rubber (SR) surface. The presented procedure exhibited a stable coating on the porous silicone samples with long-term electrical resistance durability over ∼12 months period and high resistance against harsh conditions (exposure to organic solvents). Besides, the sensors retained conductivity upon severe compressive deformations (over 75% compressive strain) with high strain-recoverability and behaved robustly in response to cyclic deformations (over 400 cycles), temperature, and humidity. The sensors exhibited a gauge factor as high as 10 within the compressive strain range of 2-10%. Given the tunable sensitivity, the engineered biocompatible and flexible devices captured movements as rigorous as walking and running to the small deformations resulted by human pulse.

Manufacture and characterization of a novel, environmentally friendly stone composite based on acrylonitrile butadiene styrene (ABS) and recycled natural granite stone particles is introduced. The proposed composite can be considered as a byproduct of natural stone processing, and potentially lead to a solution to the associated waste management problem. Results indicated that the composite’s tensile strength and fracture property generally deteriorated with increasing the stone particle content, especially beyond 50%. Stiffness and thermal conductivity, however, continually increased with the addition of the granite powder, which would suggest multi-functional applications of this material.

In the present investigations, Zinc oxide (ZnO) and ZnO-ZrO2 composite nanoparticles were synthesized by ultrasonic assisted wet chemical method to investigate their structural, optical and humidity sensing properties. The synthesized nanoparticles were characterized by the techniques like X ray diffraction (XRD), UV–Vis absorption spectroscopy, Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS). XRD and EDS were employed to confirm the phase formation and phase purity respectively. SEM micrographs showed that morphology of the parent compound ZnO is considerably changed with varying concentration of ZrO2. The optical absorption spectra showed that optical absorption of ZnO decreases with increase in ZrO2 content in the composite. The observed band gap values for ZnO and ZnO-ZrO2 composites were higher as compared to the bulk sample. The humidity sensing performance was substantiated for all the samples and the result of effect of concentration of ZrO2 in ZnO-ZrO2 composites on sensitivity, response and recovery time are discussed in detail.

Piezoelectric, piezoresistive, and optical fiber sensors have attracted considerable attention in structural health monitoring (SHM) applications for strain/temperature measurements in advanced mat...

Tuning the piezoresistive behavior of conductive polymeric composites requires an in-depth understanding of the structure-property relationships and deformation mechanisms at the polymer/conductive filler interface. In this paper, the unknown sources of nonlinearity (as frequently observed for specific material systems) are identified for the flexible and stretchable chopped carbon fiber (CCF)/polydimethylsiloxane (PDMS) conductive yarns. It is found that under cyclic loading the resistance initially reduces (negative piezoresistivity) up to a specific transition strain, beyond which positive piezoresistivity is observed until the onset of unloading. Apart from the opposing effects of fiber separation and Poisson's effect, the results suggest that such nonlinearity stems from carbon fiber (CF) buckling induced by CCF/PDMS interfacial friction upon unloading. Nevertheless, a low percolation threshold (1.41 wt%) was attained along with high sensitivity (gauge factors as high as ∼60 in cyclic loading) and stretchability (up to 25%). These characteristics make the CCF/PDMS sensors suitable for 3D-printable inks and stain sensing applications. For the latter, the sensors were integrated with a picture frame shear test setup to monitor the strain along the yarns in fiberglass/polypropylene fabrics subjected to Picture Frame test. Also, the capability of the sensors was demonstrated while used as wearable devices for detecting human joint motion.

Picture frame test (PFT) is frequently employed for characterizing the shear behavior of woven fabrics. In the present study, the main sources of possible imperfections in the PFT, arising from the operator error during sample installation, to the fixture misalignment and the inherent non-uniformities within the fabric, are reviewed and modeled using the kinematic as well as continuum-based approaches. Upon new understandings from these models, a new test methodology was designed where the shearing frame boundary condition is inscribed on the fabric sample itself during sample preparation; in lieu of fabricating and installing a metallic picture frame. The new frameless picture frame (FPF) test was proven to effectively mitigate the imperfections and provide a simple operation and better control and uniformity of the fabric installation and deformation. Contrary to the conventional PFT, the wrinkling behavior and normalized force response in the FPF was in agreement with the conventional bias extension test, with no close-to-arm fiber bending, while showing a superior test repeatability at both loading and unloading stages. Finally, a mechanically compatible, stretchable sensor was developed and integrated into the fabric samples to monitor and verify the induced local deformation along the yarns under different test methods.

Laser additive manufacturing has led to a paradigm shift in the design of next-generation customized porous implants aiming to integrate better with the surrounding bone. However, conflicting design criteria have limited the development of fully functional porous implants; increasing porosity improves body fluid/cell-laden prepolymer permeability at the expense of compromising mechanical stability. Here, functionally gradient porosity implants and scaffolds designed based on interconnected triply periodic minimal surfaces (TPMS) are demonstrated. High local porosity is defined at the implant/tissue interface aiming to improve the biological response. Gradually decreasing porosity from the surface to the center of the porous constructs provides mechanical strength in selective laser melted Ti-6Al-4V implants. The effect of unit cell size is studied to discover the printability limit where the specific surface area is maximized. Furthermore, mechanical studies on the unit cell topology effects suggest that the bending-dominated architectures can provide significantly enhanced strength and deformability, compared to stretching-dominated architectures. A finite element (FE) model developed also showed great predictability (within ∼13%) of the mechanical responses of implants to physical activities. Finally, in vitro biocompatibility studies were conducted for two-dimensional (2D) and three-dimensional (3D) cases. The results of the 2D in conjunction with surface roughness show favored physical cell attachment on the implant surface. Also, the results of the 3D biocompatibility study for the scaffolds incorporated with a cell-laden gelatin methacryloyl (GelMA) hydrogel show excellent viability. The design procedure proposed here provides new insights into the development of porous hip implants with simultaneous high mechanical and biological responses.

Blending lignin as the second most abundant polymer in Nature with nanostructured compounds such as dendritic polymers can not only add value to lignin, but also increase its application in various fields. In this study, softwood Kraft lignin/polyamidoamine dendritic polymer (PAMAM) blends were fabricated by the solution electrospinning to produce bead-free nanofiber mats for the first time. The mats were characterized through scanning electron microscopy, Fourier transform infrared (FTIR) spectroscopy, zeta potential, and thermogravimetry analyses. The chemical intermolecular interactions between the lignin functional groups and abundant amino groups in the PAMAM were verified by FTIR and viscosity measurements. These interactions proved to enhance the mechanical and thermal characteristics of the lignin/PAMAM mats, suggesting their potential applications e.g. in membranes, filtration, controlled release drug delivery, among others.

Initiation and propagation of cracks in composite materials can severely affect their global mechanical properties. Due to the lower strength of the interlaminar bonding compared to fibers and the matrix, delamination between plies is known to be one of the most common failure modes in these materials. It is therefore deemed necessary to gain more insight into this type of failure to guide the design of composite structures towards ensuring their robustness and reliability during service. In this work, delamination of interlaminar bonding in composite end-notched flexure (ENF) samples was modeled using a newly developed stochastic 3D extended finite element method (XFEM). The proposed numerical scheme, which also incorporates the cohesive zone model, was used to characterize the mode II delamination results obtained from ENF testing on polyphenylene sulfide (PPS)/glass unidirectional (UD) composites. The nonrepeatable material responses, often seen during fracture testing of UD composites, were well captured with the current numerical model, demonstrating its capacity to predict the stochastic fracture properties of composites under mode II loading conditions.

Intelligent materials such as magnetoelectrothermoelastic (METE) nanoplates offer great potential to supply more efficient energy harvesting devices, transducers, sensors, and actuators. In this study, the influences of slanted angle of the METE nanoplate and orthotropic angle of Pasternak foundation on the magnitude of surface energy layers are investigated through a vibrational analysis. The nanoplate is exposed to outer thermal, electric, magnetic and in-plane loadings. For modeling the plate’s nonlocal behavior and surface stresses, the governing equations are constructed based on Hamilton’s principle. Galerkin method is implemented to solve the equilibrium motions, and also for the authenticity of the solution, the equations are resolved by the Navier’s method. Obtained results are deemed useful for the mechanical analysis and design of nano-/microelectromechanical system nanostructures constructed from the METE materials. The numerical examples indicated that after a particular value of slanted angle of the nanoplate, α ≥ 80, the magnitude of surface energy layers in the vibration behavior becomes opposite to the case when the slanted angles are 0°

Detailed characterization of fabric reinforcements is necessary to ensure the quality of manufactured composite parts, and subsequently to prevent structural failure during service. A lack of consensus and standardization exists in selecting test methods for the mechanical characterization of fabrics. Moreover, in reality, during any experimentation there are sources of uncertainties which may result in inconsistencies in the interpretation of data and the comparison of different testing methods. The aim of this article is to show how simple statistical data analysis methods may be used to enhance the characterization of composite fabrics under individual and combined loading modes while accounting for inherent material/test uncertainties. Results using a typical glass non-crimp fabric (NCF) show that, statistically, there are significant differences between the warp and weft direction responses of a presumably balanced NCF under all deformation modes, with weft yarns being generally stiffer. Moreover, the statistical significance of warp-weft couplings under both simultaneous and sequential biaxial-shear loading modes became statistically evident, when compared to a pure biaxial deformation.

Seeking high profitability by improving energy efficiency and production quality is the prime goal of manufacturing industries. However, achieving this aim involves the realization of several conflicting objectives. In carbon fiber industry, the stabilization process is the most vital step with high energy consumption. The aim of this study is to use intelligent modeling methods in the stabilization process to maximize energy efficiency while considering better production quality, avoiding defects, and not scarifying the prediction accuracy. To this aim, a modified DOE method was used to reduce the number of required experiments. The mechanical and physical properties were then modeled based on input-output data derived from the experiments. In this way, the SVR method is used to develop a set of mathematical models for mechanical and physical properties of the fibers. The skin-core defect and energy consumption were considered as objective functions within the given range of physical and mechanical properties of fibers. The state-of-the-art NSGA-II algorithm used to find the optimum Pareto front, including non-dominated solutions among these conflicting objective functions. The results showed that by using the integrated NSGA-II and technique for order preference by similarity to ideal solution (TOPSIS), the energy efficiency of the system was improved. Moreover, the discussions showed how similar hybrid algorithms with high accuracy can be used by other industries to reduce the overall energy consumptions.

The vibration absorption of rectangular functionally graded cross-ply thick laminates is achieved analytically. The high-order shear deformation theory containing von Karman strains is employed to study the plate. The laminate structure is assumed to function in a thermal environment subjected to in-plane loadings. Mechanical properties are assumed to vary continuously through the thickness, while each layer of the plate represent an orthotropic composite lamina. The governing equations are derived using Hamilton’s principle and the Levy solution is utilized for the direct implementation of various boundary conditions, including simply support, free, and clamped on the edges of the structure. A particular solution is derived that takes into account the in-plane thermal stresses. Effect of the temperature variation, in-plane loadings, and boundary conditions on the natural frequency of the plate was quantified. Finally, the magnitude of the in-plane forces has been designed in such a way that it can suppress the vibration of the plate under each thermal and boundary condition.

Textile preforms have become materials of choice in numerous modern industries, partly due to their superior conformability onto complex 3D mould shapes. Maximum formability of this category of composite reinforcements, however, is still limited by defects such as wrinkling, which remains a challenging issue for composite designers during optimization of thermo-stamping operations. The aim of this article is to gain a deeper understanding of the effect of blank holding boundary condition on the extent of wrinkling as well as other local defects such as tow slippage and yarn jamming, and thereby to introduce a passive defect mitigation approach via geometrical modification of the blanks. To verify the applicability of the approach, a series of hemisphere forming experiments under unmodified and modified forming boundary conditions have been performed and compared on both single and multiple ply lay-ups, using a comingled polypropylene/E-glass thermoplastic plain weave.

This paper reports on the damage mechanisms of 3D circular braided composite tubes under transverse impact, applied by a Split Hopkinson Pressure Bar (SHPB) system. X-ray computed tomography (XCT) was employed to obtain 3D images of the 3D braided composite tubes after the impact test. Effects of impact velocity, braiding angle and the number of braiding layers on the damage mechanisms were researched, using the XCT data. For low impact velocity, it was found that cracks nucleate in weak areas and propagate along the path of least resistance between yarns, which give rise to matrix cracking and debonding between yarns. For high impact velocities, cracks develop along a relatively straight path with fiber breakage under high shear and tensile stresses. The orientation of yarns in the tubes showed a great effect on crack propagation.

An analytical-experimental study of the shear wrinkling behavior of plain woven composite preforms under bias extension test (BET) and picture frame test (PFT) is presented. The intentionally induced tension in the PFT has been regarded in a large portion of the literature as the source of delay in fabric wrinkling initiation as compared to the BET. Through this study, however, it is demonstrated that shear within yarns – known as intra-yarn shear – could be another cause of the delayed wrinkling in the PFT, even when the tension level in yarns is kept at zero. To better explain this hypothesis, an analytical model has been developed and the meso-level nature of wrinkle formation in the BET and PFT is compared. Analytical equations are provided to predict both the fabric locking and wrinkling onsets under these characterization tests, and verified experimentally on a carbon fiber plain woven fabric.

Multiscale properties of fabric-reinforced composites are commonly modeled via numerical and experimental methods, which are often highly time-consuming and complex. In this paper, a materials informatics-based approach has been developed to link the micro/meso-level features of woven fabric composites, obtained via nondestructive micro-CT images, to their effective Young's moduli. To this end, a reduced-order quantification of a typical glass fiber/polypropylene lamina's microstructure is established using two-point spatial correlations and the principal component analysis. Next, a machine-learning model is implemented to predict the material microstructure-property (modulus) relationship via the captured images. Despite the limited number of samples, the presented data-driven techniques led to a model with highly interpretable components and excellent accuracy for different ply orientations, regardless of apparent uncertainties such as waviness. The findings appear to be a promising step forward for the potential use of materials informatics for smart design and optimization of woven fabric composites in prominent industries, including aerospace and transportation.

The thermal stabilisation process of the carbon fibre production line, as an energy consuming oxidation reaction, is diffusion limited. Therefore the kinetic parameters, estimated from traditional methods, cannot be applied due to the significance of oxygen diffusivity. Moreover, this process involves multiple chemical reaction systems, which are interconnected and often too complex to explain via analytical frameworks. One common solution to comprehend such a process and optimise its parameters is mathematical deterministic models. In the present study, a comprehensive deterministic model was developed to predict the kinetic parameters with a finite number of experiments by an optimisation algorithm. Then the model was used to study the progress of the process, particularly in the first steps of the process to explain the decrement of CO bonds in the oxidised fibre by adding a reduction step to the stabilisation mechanism and considering the role of oxygen as a catalyst in cyclisation. The developed model is based on the structure of the PAN precursor, fibre tow and governing differential equations for the underlying phenomena, including chemical kinetics and mass transfer, associated with empirical relations for oxygen diffusivity and physical properties under isothermal conditions. The results presented up to 95% improvement in outcomes of the model for a pilot carbon fibre production line.

Inter-ply friction plays a dominant role in the generation of fiber-path defects (e.g. wrinkling) in the consolidation stage of composites manufacturing. In particular, for most thermoset prepregs, the mixed lubrication regime can be a dominating factor controlling the frictional response over the range of the processing window. This article presents a generic computational modelling approach to describe the mixed lubrication regime by combining an inverse hydrodynamic‐lubrication (IHL) theory and an asperity contact model. A homogenized resin film thickness can be derived from this analysis, rather than postulating it as in earlier conventional models. Thermal effects and fiber bed compliance in the inter-layer contact area as well as the influence of the resin rheology are assessed, finally enabling the model to be verified against inter-ply friction experiments under a wide range of processing conditions. The model has been exemplified on a fabric carbon/epoxy prepreg.

This study attempts to provide an improved insight into the significant role of inherent coupling in the mechanical behavior of woven fabric composites. In particular, applying yarns tension to postpone the wrinkling defect has now become a common technique in industry during shear forming of fabric reinforcements. Yet, in-depth understanding of this coupling characteristics is rather limited. The article first distinguishes between the meso-level (inherent) coupling and the macro-level coupling expressed by the general Hook’s law. Then, specific types of inherent couplings are identified, including tension–tension, tension-shear, and shear-tension. A fixture capable of performing combined loadings was employed to characterize the coupling modes in a typical glass/polypropylene plain weave. Results revealed a highly dominant influence of tension-shear coupling on the effective mechanical properties of the fabric, followed by the tension-tension and shear-tension couplings. Discussions are made as to how these macro-level observations may be linked to underlying deformation mechanisms at lower material scales.

Developments in carbon fiber mechanical properties are directly dependent on its manufacturing process, especially the thermal process of carbonization through a High Temperature (HT) furnace. These mechanical properties cannot be straightforwardly predicted experimentally since the thermal process involves complex parameters such as: (i) zones temperature, (ii) applied fiber tension, (iii) the N2 gas flow rate which is influenced by uncertain disturbances. The aim of this paper is to optimize the carbon fiber modulus based on the given range of tensile strength using a predictive modelling technique. The data collection of the carbonization thermal process is significantly costly and time consuming, hence we used a novel DOE method to minimize the number of required experiments. The carbon fiber with the highest and lowest tensile and modulus properties were initially analyzed by X-ray diffraction and Raman Spectroscopy, but no significant differences were observed that could account for the differences in measured mechanical and physical properties, thus a surrogate modelling approach was adopted. Four different mathematical methods were employed for modelling and compared with one another. These are (i) non-linear multivariable regression, (ii) Levenberg-Marquardt neural network algorithm, (iii) thin plate splines, and (iv) a convex hull technique. The results clearly showed that the convex hull technique has less error compared to the other tested methods. This method was selected to optimize the carbon fiber modulus based on the given range of tensile strength. Using the convex hull technique along with an evolutionary search (Genetic Algorithm) method, it is shown that the modulus of carbon fiber can be optimized for any given range of tensile strength, providing an optimum set of control parameters are chosen during the process.

While in practice cell ingrowth in scaffolds mostly occurs radially, the recent literature has mainly emphasized on modeling permeability under unidirectional flows. In this article, we attempt to introduce the radial flow direction as another important factor for scaffold internal architecture design, and thereby show its trade-off with the conventionally studied longitudinal permeability. To this end, a set of computational models is developed for different lattice and triply periodic minimal surface-based geometries to predict the corresponding structure-property relationships with respect to different porosity levels. Also, permeability is experimentally investigated for different values of porosity through 3D-printing of the selected critical structures as identified by the numerical models; namely Hexagonal and Rhombic Dodecahedron. Relative to the longitudinal permeability, the normalized radial permeability is shown to change by −51.2% and 39.4% for Hexagonal and Rhombic Dodecahedron, respectively, implying the necessity of including radial permeability as a more realistic computational tool for the design of scaffold pore architecture. Moreover, the permeability-porosity relationship was developed through both the power law as well as the Kozeny-Carman models and the effects of experimental conditions on the permeability values were discussed. Keywords: Permeability, Specific surface area, 3D-printing, Scaffold, Kozeny-Carman model

Recently, nanomaterials have been widely utilized in tissue engineering applications due to their unique properties such as the high surface to volume ratio and diversity of morphology and structure. However, most methods used for the fabrication of nanomaterials are rather complicated and costly. Among different nanomaterials, anodic aluminum oxide (AAO) is a great example of nanoporous structures that can easily be engineered by changing the electrolyte type, anodizing potential, current density, temperature, acid concentration and anodizing time. Nanoporous anodic alumina has often been used for mammalian cell culture, biofunctionalization, drug delivery, and biosensing by coating its surface with biocompatible materials. Despite its wide application in tissue engineering, thorough in vivo and in vitro studies of AAO are still required to enhance its biocompatibility and thereby pave the way for its application in tissue replacements. Recognizing this gap, this review article aims to highlight the biomedical potentials of AAO for applications in tissue replacements along with the mechanism of porous structure formation and pore characteristics in terms of fabrication parameters.

Sensing the electrical activity of peripheral nerves with high spatial resolution is needed to accurately capture dynamic and detailed movement intent of amputees and could be helpful to adapt the treatment of other disease states through closed-loop neuromodulation of bioelectronic medicines. However, existing nerve interfaces have designs that significantly limit their recording performance. To overcome these limitations, we have combined micromachined neural interfaces with tissue- engineered hydrogel-based scaffolds. These tissue-engineered electronic nerve interfaces (TEENI) enable highly scalable nerve interfaces that provide significant interface-design freedom. To speed the development of a robust microfabrication processes, a high-temperature reactive-accelerated-aging (RAA) soak test is used. Chronic electrophysiological experiments demonstrate high- SNR recording performance for implanted TEENI devices.

An efficient macro-scale finite element approach is introduced to predict defects that arise from the consolidation of carbon fibre woven fabric prepregs. The model incorporates the through-thickness compaction and inter-ply shear behaviour of the plies in the form of a compliant penalty contact in an explicit finite element simulation. For describing the compressibility of uncured prepregs, a one-dimensional compaction model is implemented via a user-subroutine. The model parameters were identified from an experimental programme and validated against compaction and inter-ply shear experiments on a Carbon/Epoxy prepreg. Moreover, the in-plane and out-of-plane behaviour of the woven fabric is captured through a hybrid hypo-elastic membrane and shell modelling approach. The applicability of the model is further demonstrated through a number of industrially relevant case studies. The method is simple, efficient, and it can be applied to assess various scenarios for modelling textile forming and consolidation behaviour.

Reliability evaluations play a significant role in engineering applications to ensure the serviceability and safety of advanced structures such as those made of composites. Here, a dynamic reliability evaluation analysis based on the probability density evolution Method (PDEM) has been adapted to assess the reliability of composite structures under uncertainties within the material properties and the external loadings. A Back-Propagation Neural Network approach is employed to identify the system's nonlinear structural response, which is often the case under large deformations. To exemplify, a split Hopkinson pressure bar system was employed to mimic the mechanical behavior of a polypropylene/fiberglass woven composite plate structure under repeated high-strain rate impacts. Subsequently, the reliability prediction was performed offline via the system model and integration of uncertainties, as well as via an online SHM-based approach, and compared to full-scale (direct) experimental reliability values by repeating the impact tests on a population of samples. A material degradation factor has been introduced within the PDEM approach to account for surface damage induced during impacts. Results clearly showed the accuracy of the PDEM in predicting the remaining reliability of the composite after each impact. The method is generic and may be applied to other types of loadings and structures.

It has been well recognized that intra-ply shear and inter-ply slippage are the principal mechanisms allowing the woven fabrics to conform to doubly-curved geometries. The implication of boundary conditions on the forming response of this class of reinforcements is complex in nature, and time-consuming simulations are often needed during process optimization. This study aims to better understand the influence of sliding boundary conditions during forming process of woven fabrics, via a new well-controlled 2D characterization test (termed Slip-bias Extension test). Thereby, a modified shear stress formulation has been developed for the sake of faster 3D simulations, while accounting for the effect of frictional interactions between the fabric and blank holder at different shear angles, normal pressures, and under asymmetric gripping conditions. A key advantage of the new equivalent formulation is that the frictional contact between the ply and the tool at various shear angles and normal pressures does not need to be explicitly modeled in the simulations. The overall applicability of the proposed test and modeling framework is validated against a hemispherical forming of a plain carbon woven fabric. Results suggested an improved modeling accuracy under different forming configurations while reducing the run time by 20%.

Dependence of shear rigidity of woven fabrics on yarn pre-tension has been reported in the recent literature, however some conflict regarding the trend of this effect is observed. Sources of this conflict are discussed and resolved in the present article using a new characterization framework and a custom-design combined loading fixture. It is shown that in order to correctly characterize the tension-shear coupling behavior in woven fabrics, instead of using global measured data, local normalized forces and displacements should be driven via a non-orthogonal transformation procedure, while considering kinematic force coupling in the setup. In addition, the effect of fabric shear on the tensile behavior of yarns has been investigated, suggesting that the coupling under question is in fact two-way. In particular, results revealed that applying yarn pre-tension increases the shear resistance of the fabric reinforcement, while the tensile behavior of the material becomes more compliant when undergoing shear deformation.

Optimization of forming process of fabric reinforced composites requires a multifaceted characterization of the reinforcement material and its implementation in customized simulations. This manuscript investigates the effect of inclusion of ‘shear-tension coupling’ (interaction) in woven fabric models on the ensuing predictions of forming simulations. To this end, a constitutive model estimating the shear stiffness as a function of axial tension along warp and weft in a typical glass plain weave has been selected. The model was implemented into the Abaqus numerical package using a customized fabric element, capable of simulating the non-orthogonal behaviour of the fabric as well as its tension-shear interaction. Subsequently, the model was employed for studying forming processes with three different punch geometries including hemisphere, double-dome, and tetrahedral shapes. In each case, comparisons were made between the model with the effect of shear-tension interaction and the conventional model assuming the shear stiffness is merely a function of shear angle (i.e., with no interaction). Results revealed that although the conventional models could be acceptable in predicting the general shear deformation pattern of the fabric (in particular in the presence of sufficient blank holder forces), the forming models that included the shear-tension interaction had lower formation of local wrinkles as well as notably higher residual stresses in all simulation cases, especially in critical sharp corners of the part and the fabric free regions.

An improved modelling of the viscoelastic behavior of fabric composites at different temperatures is presented by a new means of fractional calculus. To this end, a four-parameter fractional derivative Zener model is first used to describe the dynamic behavior of the fabric, where the constitutive relation’s response to a unit step of strain (for determination of the time dependent stress relaxation modulus) can be readily found in the literature. This response function is then fitted to the experimental data of samples of a typical prepreg composite made of E-glass fibers comingled with polypropylene fibers, both at the dry and consolidated conditions. It is shown that the Zener model can better capture the experimental data when compared to the conventional approaches such as integer order modelling and Prony series. The results, particularly, showed that the viscoelastic behavior of the material at lower temperature regimes is far more accurate using the fractional derivatives approach. Finally, the variation of storage and loss moduli of the dry fabric with external cyclic loading were scrutinized, to determine the rubbery and glassy regions of the frequency response.

The effect of cerium (Ce) addition (0.1, 0.3, 0.5, and 1.0 wt%) on the ambient and high-temperature mechanical properties of a commercially available B319 powertrain aluminum alloy was investigated. In addition, to characterize the effects that Ce has on the microstructure of the B319 alloy, field emission scanning electron microscopy, optical microscopy, X-ray diffraction, energy dispersive X-ray spectroscopy and X-ray micro computed tomography were employed. Statistical significance of the results was evaluated using the single-factor ANOVA analysis. The microstructural analyses revealed that Q-AlCuMgSi, α-Al, Al2Cu, eutectic silicon (Si), and Al15(Fe,Mn)3Si2 were present in all of the B319 and B319 + Ce specimens. However, the addition of Ce led to the formation of Al3Ce4Si6 and AlCeSi2 as well as a refinement of eutectic Si. It was found that, addition of 0.1 wt% Ce to the B319 alloy considerably increased the yield and tensile strength at ambient temperature (~10% and ~9%, respectively) and at 250 °C (~14% and ~7%, respectively) as well as the alloy's % elongation and micro hardness (~18–60% and 11%, respectively). However, it was observed that further addition of Ce (up to 1.0 wt %) results in a slight decrease in the materials tensile strength, as compared to the B319 + 0.1% Ce sample. This is presumed to be attributed to the escalating amount of porosity and needle-like Ce bearing intermetallics that were observed in the higher Ce content samples. The results from this study provide the automotive industry with a new cost-effective method of improving the mechanical properties of their currently used powertrain alloys, allowing for greater efficiency and improved performance.

In the present study, polydimethylsiloxane (PDMS) porous scaffolds are designed based on minimal surface architectures and fabricated through a low-cost and accessible sacrificial mold printing approach using a fused deposition modeling (FDM) 3D printer. The effects of pore characteristics on compressive properties and fluid permeability are studied. The results suggest that radially gradient pore distribution (as a potential way to enhance mechanically-efficient scaffolds with enhanced cell/scaffold integration) has higher elastic modulus and fluid permeability compared to their uniform porosity counterparts. Also, the scaffolds are fairly strain-reversible under repeated loading of up to 40% strain. Among different triply periodic minimal surface pore architectures, P-surface was observed to be stiffer, less permeable and have lower densification strain compared to the D-surface and G-surface-based pore shapes. The biocompatibility of the created scaffolds is assessed by filling the PDMS scaffolds using mouse embryonic fibroblasts with cell-laden gelatin methacryloyl which was cross-linked in situ by UV light. Cell viability is found to be over 90% after 4 days in 3D culture. This method allows for effectively fabricating biocompatible porous organ-shaped scaffolds with detailed pore features which can potentially tailor tissue regenerative applications. Statement of Significance Printing polymers with chemical curing mechanism required for materials such as PDMS is challenging and impossible to create high-resolution uniformly cured structures due to hard control on the base polymer and curing process. An interconnected porous mold with ordered internal architecture with complex geometries were 3D printed using low-cost and accessible FDM technology. The mold acted as a 3D sacrificial material to form internally architected flexible PDMS scaffolds for tissue engineering applications. The scaffolds are mechanically stable under high strain cyclic loads and provide enough pore and space for viably integrating cells within the gradient architecture in a controllable manner.

A custom-built test device was developed to measure the inter-ply shear resistance of dry carbon woven fabrics as well as prepregs at different temperatures, consolidation pressures, and forming rates typical to those used in autoclave processing. A quantitative understanding of the nature of the shear forces encountered during fabric consolidation was established, suggesting the strong dependence of these forces on the process conditions along with the dominance of a mixed lubrication regime. Among the most influential state variables, the resin viscosity and distribution of the resin on the prepreg surface, as well as the surface roughness of the reinforcing fibers could be identified.

This study presents a low-cost, tunable, and stretchable sensor fabricated based on spandex (SpX) yarns coated with graphene nanoplatelets (GnP) through a dip-coating process. The SpX/GnP is wrapped into a stretchable silicone rubber (SR) sheath to protect the conductive layer against harsh conditions, which allows for fabricating washable wearable sensors. Dip-coating parameters are optimized to obtain the maximum GnP coating rate. The covering sheath is tailored to achieve high stretchability beyond the sensing limit of 104% for SpX/GnP/SR sensors. Adjustable sensitivity is attained by manipulating SpX immersion times broadening its application for a wide range of strains: Gauge factors as high as two orders of magnitude are achieved at tensile strains greater than ≈40%. The fabricated sensors are tested for two applications: First, the SpX/GnP sensors are integrated into composite fabrics (with no negative impact on the structural integrity of the part) for screening the yarn displacements, resin flow, solidification during the hot press forming process, and structural health monitoring under mechanical loads with minimal cross-sensitivity to temperature/humidity. Second, the capability of SpX/GnP/SP sensors in detection of a wide range of bodily motions (from the joint motion to arterial blood pressure) is demonstrated.

To produce high quality and low cost carbon fiber-based composites, the optimization of the production process of carbon fiber and its properties is one of the main keys. The stabilization process is the most important step in carbon fiber production that consumes a large amount of energy and its optimization can reduce the cost to a large extent. In this study, two intelligent optimization techniques, namely Support Vector Regression (SVR) and Artificial Neural Network (ANN), were studied and compared, with a limited dataset obtained to predict physical property (density) of oxidative stabilized PAN fiber (OPF) in the second zone of a stabilization oven within a carbon fiber production line. The results were then used to optimize the energy consumption in the process. The case study can be beneficial to chemical industries involving carbon fiber manufacturing, for assessing and optimizing different stabilization process conditions at large.

Evaluated effect of micro-fiber distribution on properties of UD composite yarns.Random unit cell modeling results were assessed against theoretical predictions.The transverse Poisson's ratios were highly affected by fiber distribution.Shear-wall artifact in imaging yarns can cause deviations from actual behavior. A combined X-ray micro-computed tomography (XMT) and micro-Finite Element Analysis study is presented to quantify the effects of micro-scale random fiber distributions on the effective (homogenized) elastic properties of unidirectional (UD) yarns, as often used by designers for component-level computational modeling of composite structures. In addition, it is shown how the XMT artefacts can yield unreliable FE homogenization of the composite yarns by overestimating the stress transfer capacity between the material constituents. Finally, the micro-FEA modeling results under fiber distribution randomness are compared to the macro-level predictions such as the classical rule of mixture and Halpin-Tsai equations.

This article investigates the potential impact of manufacturing uncertainty in composite structures here in the form of thickness variation in laminate plies, on the robustness of commonly used Artificial Neural Networks (ANN) in Structural Health Monitoring (SHM). Namely, the robustness of an ANN SHM system is assessed through an airfoil case study based on the sensitivity of delamination location and size predictions, when the ANN is imposed to noisy input. In light of the observed poor performance of the original network, even when its architecture was carefully optimized, it had been proposed to weigh the input layer of the ANN by a set of signal-to-noise (SN) ratios and then trained the network. Both damage location and size predictions of the latter SHM approach were increased to above 90%. Practical aspects of the proposed robust SN-ANN SHM have also been discussed.

Based on the modified couple stress theory, the free vibration behavior of micro scale Bernoulli–Euler nanocomposite cantilever beams is analytically investigated by introducing a material length scale parameter. The mechanical properties of polymer composite micro-beams reinforced by multi-walled carbon nanotubes (MWCNTs) are assumed to vary continuously in the longitudinal direction of the beam. A new exponential distribution of the volume fraction of the constituents is proposed to achieve the beam's highest fundamental natural frequency given a weight percent (wt.%) of MWCNTs. The effect of the material length scale parameter on the fundamental natural frequency of the ensuing axially functionally graded (FG) composite micro-beam is investigated for various CNT gradient indices. The difference between the frequencies, predicted by the modified couple stress theory and the classical continuum mechanics theory is considerable when the ratio of the beam thickness to the internal material length scale is approximately less than two. It is also observed that with a 1.0 wt.% addition of MWCNTs to the polymer-based microcantilevers, almost a two-fold improvement in the relative change of the fundamental natural frequency is achieved by adopting the proposed optimum CNT dispersion pattern rather than the commonly used uniform CNT distribution pattern.

A mesoscopic analytical model of wrinkling of Plain-Woven Composite Preforms (PWCPs) under the bias extension test is presented, based on a new instability analysis. The analysis is aimed to facilitate a better understanding of the nature of wrinkle formation in woven fabrics caused by large in-plane shear, while it accounts for the effect of fabric and process parameters on the onset of wrinkling. To this end, the mechanism of wrinkle formation in PWCPs in mesoscale is simplified and an equivalent structure composed of bars and different types of springs is proposed, mimicking the behavior of a representative PWCP element at the post-locking state. The parameters of this equivalent structure are derived based on geometric and mechanical characteristics of the PWCP. The principle of minimum total potential energy is employed to formluate the model, and experimental validation is carried out to reveal the effectiveness of the derived wrinkling prediction equation.

New stone composite samples, fabricated using nano- to micro-sized recycled granite particles with irregular shapes and random distribution within a ABS matrix, demonstrate a highly nonlinear and complex fracture behavior. To model this behavior, a mixed mode cohesive zone finite element model is identified using the single-leg bending (SLB), in order to represent the granite particles-ABS interfacial debonding. An inverse methodology is then proposed to determine the parameters of the cohesive zone (CZM). A direct method based on J-integral approach is employed to determine the effective parameters of the traction-separation law. A two dimensional micromechanical extended finite element model (XFEM) of the composite is generated using X-ray micro-computed tomography (XMT) to mimic the actual shape of the particles. Finally, the identified cohesive model parameters have been employed to simulate the crack growth within the granite particulates/ABS composite. The comparison of the numerical and experimental results of the SLB test demonstrated the effectiveness of the proposed simulation framework.

This paper explores a set of new equations to predict the bond strength between fiber reinforced polymer (FRP) rebar and concrete. The proposed equations are based on a comprehensive statistical analysis and existing experimental results in the literature. Namely, the most effective parameters on bond behavior of FRP concrete were first identified by applying a factorial analysis on a part of the available database. Then the database that contains 250 pullout tests were divided into four groups based on the concrete compressive strength and the rebar surface. Afterward, nonlinear regression analysis was performed for each study group in order to determine the bond equations. The results show that the proposed equations can predict bond strengths more accurately compared to the other previously reported models.

The cutting tool geometry is known to be an influential factor on damage induced during drilling of composite materials. Conversely, the geometry of the tool is affected under multiple drilling cycles due to highly abrasive nature of fibers. Building on earlier reports, the aim of this work is to create a better understanding of cutting parameters on the quality of drilled woven carbon fiber reinforced polymer (CFRP) laminates, given different tool wear conditions. Namely, a full factorial design of experiments has been conducted to quantify the significance of each process parameter (cutting velocity, feed rate and tool point angle), as well as their interactions, on the generation of entry- and exist- delaminations as well as the thrust force for different tool types. Finally, using a response surface methodology, a multi-objective optimization strategy has been presented to select optimum ranges of design parameters that can minimize the aforementioned output variables collectively. Such knowledge may be useful to explore further improvements toward defect-free drilling of woven CFRP composites. The authors acknowledge the financial support for this work from the Ministry of Economy and Competitiveness of Spain under the project DPI2011-25999 and FPI subprogram with the reference BES-2012-055162, and the Natural Sciences and Engineering Research Council (NSERC) of Canada. Publicado

The development and application of bio-sourced composites have been gaining wide attention, yet their deterioration due to the growth of ubiquitous microorganisms during storage/manufacturing/in-service phases is still not fully understood for optimum material selection and design purposes. In this study, samples of non-woven flax fibers, hemp fibers, and mats made of co-mingled randomly-oriented flax or hemp fiber (50%) and polypropylene fiber (50%) were subjected to 28 days of exposure to (i) no water-no fungi, (ii) water only and (iii) water along with the Chaetomium globosum fungus. Biocomposite samples were measured for weight loss over time, to observe the rate of fungal growth and the respiration of cellulose components in the fibers. Tensile testing was conducted to measure mechanical properties of the composite samples under different configurations. Scanning electron microscopy was employed to visualize fungal hyphal growth on the natural fibers, as well as to observe the fracture planes and failure modes of the biocomposite samples. Results showed that fungal growth significantly affects the dry mass as well as the tensile elastic modulus of the tested natural fiber mats and composites, and the effect depends on both the type and the length scale of fibers, as well as the exposure condition and time. Keywords: biocomposites; hemp and flax natural fibers; fungal deterioration; material properties; design considerations

With the advancement of testing tools, the ability to characterize mechanical properties of fiber reinforced polymer (FRP) composites under extreme loading scenarios has allowed designers to use these materials in high-level applications more confidently. Conventionally, impact characterization of composite materials is studied via nondestructive techniques such as ultrasonic C-scanning, infrared thermography, X-ray, and acoustography. None of these techniques, however, enable 3D microscale visualization of the damage at different layers of composite laminates. In this paper, a 3D microtomographic technique has been employed to visualize and compare impact damage modes in a set of thermoplastic laminates. The test samples were made of commingled polypropylene (PP) and glass fibers with two different architectures, including the plain woven and unidirectional. Impact testing using a drop-weight tower, followed by postimpact four-point flexural testing and nondestructive tomographic analysis demonstrated a close relationship between the type of fibre architecture and the induced impact damage mechanisms and their extensions. © 2013 M. Alemi-Ardakani et al.