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Abstract: A finite element procedure, developed in order to account for the effect of high anisotropy at folding of coated papers, is presented. The anisotropic behaviour (with very low stiffness in the thickness direction) is modelled using stiff structural elements (trusses and beams). The numerical results indicate that high elastic anisotropy leads to lower strain levels at folding than reported in previous analyses where this effect was not accounted for. High plastic anisotropy, on the other hand, will contradict this result. [Copyright &y& Elsevier]

Folding of coated paper is examined numerically using the finite element method. Particular emphasis is put on the behaviour of field variables relevant for cracking of the coating layers. In the numerical analysis, the basepaper is modelled as an anisotropic elastic–plastic material (both elastic and plastic anisotropy is accounted for) while the constitutive behaviour of the coating layers are approximated by classical (Mises) elastoplasticity. The numerical results suggest, among other things, that particular forms of plastic anisotropy can substantially reduce the maximum strain levels in the coating. It is also shown that delamination buckling, in the present circumstances, will have a very small influence on the strain levels in the coating layer subjected to high tensile loading. [Copyright &y& Elsevier]

Folding of coated papers is examined numerically using the finite element method. The analysis is focused on the influence from dynamic effects on the folding process. In particular, the behaviour of field variables relevant for cracking of the coating layers are studied in some detail. The results presented indicate that dynamic effects are of little importance as regards maximum strain levels in the coating but will influence the stress and strain distributions. Accordingly, a quasi-static analysis of the problem will be sufficient in order to describe many of the important features related to cracking. [Copyright &y& Elsevier]

[Display omitted] • The digital twin of a CNT-polymer nanocomposite is developed. • CNT intrinsic resistivity cannot be neglected. • Uniform boundary potentials overestimate effective electrical conductivity. • Control of CNT torsion removes the dependence on the segmentation length. • The critical percolation index lies in the range 1.2–1.7. The paper describes digital twins for an electrically conductive isotropic CNT-polymer nanocomposite, using representative volume element with boundary conditions being periodic geometrically and electrically. During the CNT generation, the torsion and curvature of CNTs are controlled. The percolation threshold is analysed with scaling towards the infinite RVE. The digital twin sensitivity to model parameters is found as follows: (1) restrictions on the curvature/torsion ensure the independence of the homogenised conductivity on the CNTs discretisation; (2) the conductivity of the nanocomposite increases (for the same CNT volume fraction) with the increase of the CNT length and maximum torsion and decrease of the maximum curvature; (3) the percolation threshold, is in the range of 0.3–0.7% for different CNT parameters; it reduces in half with doubling the CNT length; the curvature and torsion have lesser influence. The critical percolation index is 1.2–1.7, which corresponds to the theoretical values for 3D networks. [ABSTRACT FROM AUTHOR]

Abstract: Natural continuous bast fibres (hemp, flax, etc.) are gaining popularity in composite materials because they can advantageously replace glass fibres. It is found that intrinsic properties of unidirectional (UD) composites are almost equivalent to those of unidirectional glass fibre composites. Unfortunately it is difficult to get repeatable results because of the inherent variability in the properties of bast fibres compared to glass fibres. Their quality is largely affected by the weather conditions, the extraction location along the plant and the techniques used to extract them (retting, bleaching, etc.). In this work, unidirectional hemp/paper/epoxy and flax/paper/epoxy composites are manufactured by adding one or two sheets of paper at the surface of a unidirectional layer of hemp or flax fibres before molding. The composites are tested under tensile loads and the results compared with those obtained for UD composites made without paper. The results show a significant increase in strength and modulus repeatability when the paper layer is present. A significant increase in strength and modulus was also obtained compared to the base epoxy properties. The resin permeability of the flax–paper reinforcement has also been evaluated and compared to that of a standard glass fabric. Globally, the results suggest that adding thin sheets of paper at the surface of reinforcement layers stabilizes and increases the composite strength but slightly reduces the Young’s modulus. However the permeability of the flax–paper reinforcement was much lower than that of the glass fabric. Modifications to the paper architecture will be required to improve this aspect. [Copyright &y& Elsevier]

• Accurate prediction of tape-spring folding behavior with new analytical model. • Proposed model outperforms classical models in predicting peak and steady-state moments. • Stretching and bending strain energy studied and analyzed during folding process. • Three key geometric parameters identified for optimizing tape-spring design. The tape-spring is widely used in aerospace, mechanical, and civil engineering due to its unique mechanical properties and compact size. This paper aims to establish a new analytical model to more accurately predict the folding behavior of the tape-spring, including the geometric configuration, folding moment versus longitudinal curvature curve, peak moment, and propagation moment. This model comprehensively considers the influence of stretching strain energy and bending strain energy on the total strain energy, and determines the folding behavior of the tape-spring through the minimum energy principle. The proposed analytical model was compared with Wuest's model, Yee's model, and Yao's model. Experiments of tape-springs made from two different materials were utilized for validation. The study shows that the proposed model has the highest prediction accuracy compared with the classical models, with the error of approximately 10%. The reason for the significant difference in the prediction results between the proposed model and Yao's model was given, and the relationship between stretching strain energy and bending strain energy during the folding process of the tape-spring was analyzed. The proposed model has broader applicability than classical models and provides new insights and solutions for accurate prediction of the folding behavior of the tape-spring. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents extensive test results of linear elastic mechanical properties of Nomex paper and Nomex honeycomb structures. The fundamental mechanical properties of the Nomex paper are then used in the finite element modeling and analysis of Nomex honeycomb structures. The finite element results are then compared with the experimental results and with the results using the well known theory from Gibson and Ashby [Gibson LJ, Ashby MF. Cellular solids: structures & properties. Pergamon Press; 1988]. Size effects are observed for the moduli of Nomex honeycombs. [Copyright &y& Elsevier]

A major disadvantage of polymer-based composite materials is their poor performance when exposed to relatively high heat flux. At temperatures typically above 300–400 °C, the organic matrix decomposes releasing heat, smoke, and toxic volatiles, jeopardising the composite mechanical performances. The heat flux resistance of composites can be improved by integrating protective coatings on their surface. In the present work, graphene nanoplatelet (GNP) films are employed as thermal barrier coatings (TBCs) to mitigate the thermal degradation of Carbon Fibres Reinforced Plastic (CFRP). The films were bonded onto the heat-exposed surface of CFRP laminates. Laser spot heating tests, with different laser power densities (25–150 kW/m2), were adopted to assess the effectiveness of the coating. The effect of the thickness of the protective layer has been tested too, by changing the number of layers (from 1 to 2 layers). From the results, a significant reduction in the temperatures and damages were observed. Moreover, the damage extension and residual mechanical performances of exposed samples have been assessed as a function of the power density and the protection level. A significant improvement of the post-heat flexural moduli and a significant reduction of the damaged areas have been obtained in laminates protected with high-loaded graphene nanoplatelet films. [ABSTRACT FROM AUTHOR]

• This paper realized the damage characterization of CFRP/steel double-lap bonded joints based on AE and DIC. • This paper achieved the damage pattern identification of joints based on the decision tree algorithm. • This paper obtained the damage mechanisms of joints under different loading conditions. CFRP/steel joints are commonly used in construction and can cause unpredictable damage when subjected to external loading. However, it is still challenging to characterize the damage evolution behavior of joints under different loads. In this study, acoustic emission (AE) and digital image correlation (DIC) techniques are used to monitor the damaged state of joints, and a decision tree (DT) algorithm was proposed. From the monitoring results of AE and DIC, it can be found that the damage process of the joint is divided into three stages and is mainly accompanied by four damage modes, namely adhesive failure, cohesive failure, skin failure, and steel deformation. In addition, it also reveals that the AE signal is more sensitive to the early damage of the joint, while the DIC is more sensitive to the late damage of the joint. The identification results of the DT algorithm show that the main damage mechanisms of the joints under the tensile loading conditions are adhesive failure and cohesive failure, while the primary damage mechanism under the bending loading conditions is adhesive failure. The combination of these two techniques successfully enables the damage characterization of joints and provides a framework for analyzing the damage mechanisms of joints. [ABSTRACT FROM AUTHOR]

Metallic lattice structures are garnering increasing attention across various research domains for their potential to create lightweight yet high-strength solutions. Their appeal largely stems from a range of beneficial attributes, including their low weight, substantial specific strength and stiffness, and superior energy absorption qualities. These characteristics have facilitated their widespread use in industries like aerospace, shipping, defense, and automotive, particularly in scenarios demanding weight minimization, multifunctionality, and enhanced safety in intricate environments. The mechanical properties of these structures are, therefore, of paramount importance. This paper offers an exhaustive review and synthesis of existing research approaches, production techniques, and evaluations of both static and dynamic mechanical properties associated with metallic lattice structures. It starts by delineating the various types and manufacturing methods, followed by an analysis of factors impacting their mechanical properties. The paper concludes by exploring prospective research avenues concerning the static and dynamic mechanical performance of metallic lattice structures. [ABSTRACT FROM AUTHOR]

Digital image and volume correlation (DIC and DVC) are increasingly being used to measure the deformation and damage behaviour of composite materials. The heterogeneous nature of the composite microstructure results in complex local behaviour, which cannot be captured using traditional experimental characterisation techniques. DIC and DVC offer significant advantages in monitoring this behaviour for fibre-reinforced composite materials. However, as acceptance of these techniques is growing, careful consideration of testing setup and approach is nevertheless crucial for achieving accurate results. This paper reviews digital image and volume correlation methods for the characterisation of composite materials and reports current research applications. The review discusses essential considerations and provides recommendations to aid researchers in achieving quality deformation measurement and damage identification in composites. Finally, an outlook on possible future applications is presented as a motivator for further studies. • Digital image & volume correlation use with fibre-reinforced composites is explored. • Considerations for deformation, damage and defect characterisation are discussed. • Results of innovative recent studies are reported at micro-, meso- and macroscales. • The potential use of experimental deformation in high-fidelity models is evaluated. • Perspectives on existing advantages, limitations and future directions are presented. [Display omitted] [ABSTRACT FROM AUTHOR]

Inherent susceptibility of adhesive bonds to miniscule quantities of contamination can cause undetectable weakened bonds. For this reason, the Federal Aviation Administration (FAA) places strict regulations on adhesively bonded joints in primary aircraft structures. To meet certification requirements aircraft manufactures resort to redundant load paths in the form of fasteners which inherently add weight to the structure and increase manufacturing time. In prior work, a secondary bonding technique called AERoBOND was developed, which utilized off-stoichiometric epoxy-matrix resins to facilitate reflow and diffusion of the resin within the joint interface during a secondary bonding/cure process, thus achieving a bond similar to a co-cured joint. However, the AERoBOND process required tight spatial tolerances between the two parts being joined. This study examined the utilization of conventional adhesive with the AERoBOND method to act as a filler in the joint line, effectively reducing the need for tight tolerances on the joining parts and serving as a flexible alternative for existing manufacturing processes. Ultrasonic inspection, optical microscopy, and ASTM International standard tests were performed to analyze the joints for defects and to quantify the mode-I and mode-II interlaminar fracture toughness and short beam strength of the proposed methodology with varying manufacturing parameters. The comprehensive results indicate that the AERoBOND+ method with and without surface preparation performs comparably to co-cured and conventional, adhesively bonded joints when secondary cured in an autoclave with 791 kPa of pressure. As an example, the AERoBOND+ panel without surface preparation bonded with 791 kPa of pressure (referred to as AB+3 throughout paper) had a mode-I fracture toughness (G Ic) of 0.643 kJ/m2 and a mode-II fracture toughness (G IIc) of 4.000 kJ/m2 in the non-precracked condition and 4.218 kJ/m2 in the precracked condition at the adhesive-to-prepreg interface. These results were 96 %, 142 %, and 217 %, respectively, of a co-cured baseline panel (referred to as C1 throughout paper). [ABSTRACT FROM AUTHOR]

[Display omitted] • The manuscript developed an hourglass negative Poisson's ratio structure (HNPRS). • The HNPRS has a high negative Poisson's ratio of −1.004 and a high compressive capacity of 1.83 kN. • This is the first time to apply the 3D structure has been used as a substrate for magnetostrictive sensors. • The HNPRS effectively solves the dead zone problem of magnetostrictive sensors. Currently, dead zones and low sensitivity have hindered the utilization of magnetostrictive sensors. In this paper, a new negative Poisson's ratio structure inspired by an hourglass is proposed to provide a feasible idea for this problem. The novel negative Poisson's ratio structure exhibits a high Poisson's ratio and a high compression resistance. Theoretical studies have demonstrated that the structure's performance is strongly dependent on four design parameters. The structure is analyzed and tested via finite element analysis simulation by changing the design parameters. This structure's negative Poisson's ratio can reach up to −1.004. It possesses a compressive strength of 1.83 kN and an energy absorption capacity of 8.72 J. A magnetostrictive sensor using the proposed negative Poisson's ratio structure as the base realizes a 271.7 % sensitivity improvement. The problem of dead zones in magnetostrictive sensors can be also solved simultaneously. The proposed structure in this paper provides a feasible solution for further expanding the applications of magnetostrictive sensors. [ABSTRACT FROM AUTHOR]

The invisible damage caused by low-velocity impacts are safety threats to engineering structures. Thus, impact force identification is crucial in the context of composite structures for both structure health monitoring (SHM) and composite structure design. This paper investigates the process of identifying impacts on composite structures subjected to low-velocity impact. Considering the damage evolution in the composite structure during impact, this paper explores the influence of impact damage on the accuracy of force identification. Impact experiments on carbon fiber reinforced polymer (CFRP) laminates were conducted to obtain impact force peaks and displacement responses. Furthermore, a validated finite element model (FEM) is established for more elaborate analysis on the mechanism. The findings reveal that the structural damage can lead to significant deviations in force identification if the damage is not considered. Finally, a neural network is employed to predict the force history taking impact damage into consideration. This research provides a reference for the composite structures design and health monitoring of engineering structures considering impact damage. [ABSTRACT FROM AUTHOR]

The discrete material optimization method optimizes the distribution of materials by setting candidate materials using a multi-phase material penalty model. Addressing the issue of reduced efficiency in fiber orientation optimization due to a large number of candidate materials, this paper proposes a dichotomous angle refinement discrete material optimization method to enhance solution speed. This method leverages the efficiency of the bisection approach to rapidly refine the angle in discrete optimization results, thereby narrowing the range of candidate fiber orientations. Furthermore, by introducing fiber orientations perpendicular to the optimized orientation, it mitigates potential local optimization issues during the optimization process, thereby enhancing the method's optimization capability. Compared to traditional discrete material optimization methods, this method employs a special dichotomy method to determine the candidate materials for each element, thereby decreasing the number of design variables. This method demonstrates higher computational efficiency when solving fiber orientation optimization problems with a large number of candidate materials. Several numerical examples provided in the paper validate the efficiency and stability of the proposed method in addressing optimization problems. [ABSTRACT FROM AUTHOR]

Filament-wound Composite Pressure Vessels (CPVs) are employed largely for gas or fluid storage under pressure in aerospace, automotive and naval industries. Composite vessels are subjected to harsh conditions such as critical loadings, extreme temperatures, and bursting; therefore, a permanent in-situ and online monitoring approach for the structural integrity of the vessels is essential. Hence, this review paper focuses on the description of the most trending used sensors such as piezoelectric (PZT and PVDF), piezoresistive (BP and MXene) and fiber optic (SOFO®, OBR and FBG) sensors, for developing a Structural Health Monitoring (SHM) approach to create self-sensing composite pressure vessels. The novelty of this review paper lies in providing an overview of existing works covering the integration of sensors in composite vessels, including sensor types, localization, and their impact on composite integrity. Particularly, an analysis of the literature is provided concerning the sensor's integration and especially their monitored parameters, layout design and arrangement in CPVs. Additionally, the interaction between the host composite material and sensors is analyzed to understand how to integrate sensors with the minimum possible defects that alter the mechanical performance of composite vessels. Lastly, a discussion of a CPV's SHM system is provided to offer researchers a foundation for upcoming experimental work. [ABSTRACT FROM AUTHOR]

With the development of flexible pressure sensors, an increasing number of microstructures and their preparation methods have been developed. However, how to reduce the cost and complexity of microstructure preparation while ensuring sensors' performance and microstructure diversity remains a significant challenge. This paper explores the feasibility and diversity of origami craft in the microstructure preparation. Based on origami craft, various different microstructures, such as linear, cross, wrinkle and wave, could be prepared using low-cost silicone paper as mold material and simple steps. Due to the diversity of origami craft in microstructure preparation, our sensors with different microstructures also have their own advantage interval of pressure detection (0–4.4 kPa: the sensitivities of piezoresistive sensors with linear and cross microstructures are S o = -0.31 kPa−1, S t = -0.34 kPa−1; 4.4–13.3 kPa: the sensitivity of the piezoresistive sensor with wave microstructure is S wa = -0.028 kPa−1), some of the sensors have rapid response times, excellent response characteristics, repeatability, and hysteresis. Sensors designed for low-pressure applications can detect pressures as low as 22 Pa. Additionally, it was observed that they possess significant potential in human motion environments, office environments, and equipment testing environments. This indicates that origami craft offers excellent diversity and feasibility in the preparation of sensor microstructures. [ABSTRACT FROM AUTHOR]

Conical-cylindrical shells are common geometries in launch-vehicle structures as stage adapters and payload adapters, and they are susceptible to buckling due to their large radius-to-thickness ratios. Buckling design guidance is available but it is limited for conical and cylindrical shells. There is no available buckling design guidance for conical-cylindrical shells. This paper presents the validation of two finite element models used to successfully predict the buckling behavior of a composite conical-cylindrical shell with and without reinforcement tested in two separate campaigns. The laminate design for the first test campaign consisted of a quasi-isotropic layup. For the second test campaign, additional composite plies were applied to reinforce the transition region of the original laminate. The work presented demonstrates the ability to predict the buckling behavior of a composite conical-cylindrical shells with two different designs, which may aid in creating buckling design guidance for conical-cylindrical shells. Additionally, this paper shows that there is no appreciable benefit to adding reinforcement to the transition region if the intent is to increase the buckling load, due to the fact reinforcement brings increased buckling imperfection sensitivity to the shell. [ABSTRACT FROM AUTHOR]

Due to the high cost and complex operation of fatigue tests, a multi-scale fatigue damage analysis and life prediction method for 3D braided SiC/SiC composites is proposed in this paper. In this method, the fatigue behavior of the interface is characterized by the cyclic cohesive zone model (CCZM), which is based on the cohesive zone model (CZM) obtained from molecular dynamics (MD) simulations. The fatigue damage evolution of the yarn and matrix is described by a continuous damage model (CDM) along with an exponential damage-cycle number (D - n) relationship. Geometrically, a representative volume element (RVE) model consisting of a zero-thickness interface, yarn and matrix is constructed. The fatigue analysis is carried out by the software ABAQUS, in which the fatigue life of 3D braided SiC/SiC composites at different fatigue loading factors is predicted, and the maximum fatigue stress versus the number of cycles (S-N) curves are plotted. When the maximum fatigue stress is 18 % of the tensile strength, the fatigue life prediction accuracy of the proposed method is within 2.2 times error band, which demonstrates the effectiveness and reliability on the proposed method in this paper. This work provides an innovative perspective for fatigue damage and life prediction to braided SiC/SiC composites. [ABSTRACT FROM AUTHOR]

The aim of this contribution is to investigate whether the order of load ratios applied to a textile structure impacts the biaxial stiffness behaviour of the structural textile itself. These investigations are performed based on biaxial tests on an architectural woven glass fibre fabric, a representative of such membranes. The first part of the paper investigates the existence and extent of load history dependency in the material response. Biaxial test results show that effects of a previous load history on the weave geometry cannot be eliminated by further load cycling in all biaxial stress ratios. Moderate to strong effects are recognized in two stress ratios, although not in both weave directions. The second part of the paper examines how these effects influence material stiffness parameters and structural calculations. Two boundary value problems are investigated: a pressure chamber test and a roof structure. Parameters obtained by fitting biaxial tests with or without history are considered. By incorporating an adaptive load-ratio dependent scheme, highly predictive numerical results are obtained, showing that while the effect of load history may appear small in the biaxial tests and pressure chamber test, it can be significant in complex structural problems like roof structures. [ABSTRACT FROM AUTHOR]

• Analytical Method for Wafer Bonding Quality Assessment: The paper introduces an analytical method that connects external conditions such as normal pressure, planarity deviation, and impurity particle counts with key mechanical variables like wafer deflection and strain energy during the direct wafer bonding process. This is a significant advancement as previous research did not account for the impact of impurities on bonding quality. • Influence of Impurities on Bonding Process: The study establishes a mechanical model of the adhesive process that elucidates the relationship between impurity particle count and strain energy. It reveals how impurities affect wafer deflection and strain energy, showing nonlinear variations with changes in particle position. The results indicate that wafer curvature, thickness, and impurity count are critical factors determining deflection under specific pressures. • Theoretical Guidance for Practical Bonding: The proposed mechanical model, verified through finite element simulation, offers theoretical guidance for selecting adhesive materials and evaluating the feasibility of wafer bonding in industrial applications. It provides insights into the effects of initial wafer geometry, adhesive energy, and particle positions on successful bonding outcomes under applied external pressures. Direct wafer bonding technology has been widely used in the manufacturing of microelectromechanical systems (MEMS). The chip deflection and strain energy can be used to evaluate the bonding quality. Current research assumes that the wafer surface is perfectly clean and neglects the influence of impurities, lacking an analytical model to characterize the effects of external conditions (normal pressure, planarity deviation, impurity particle counts) on key mechanical variables (wafer deflection and strain energy) during the bonding process. In this paper, an analytical method is used to establish a bridge between external conditions and bonding variables. A mechanical model of the adhesive process is established, and the relationship between impurity particle count and strain energy is obtained. By considering the bonding pressure, chip geometry, and impurity particle count, analytical expressions for deflection and strain energy are derived, revealing the influence of external conditions and internal geometry on wafer deflection and strain energy. The results show that under certain pressure, the curvature and thickness of the wafer, as well as the impurity particle count, jointly determine the wafer deflection. The wafer deflection and strain energy exhibit nonlinear variations with changes in particle position. The correctness of the proposed model is verified through finite element simulation. This work provides a reference for judging wafer bonding with impurity particles in industrial applications. [ABSTRACT FROM AUTHOR]

For fibrous materials such as nonwoven fabrics, paper and paperboards, inter-fiber bonds play a critical role by holding fibers, thus providing internal cohesion. Being a physical phenomenon, inter-fiber bonds occur at every fiber crossing and can be also geometrically detected. In relation to the idea, a statistical geometrical model was developed to investigate the effects of fiber geometry, (i.e. length and cross-sectional properties), spatial distribution, (i.e. location and orientation), and specimen size on fiber network connectivity, which refers to inter-fiber bonds at fiber crossings. In order to generate the fiber network, a geometrical fiber deposition technique was coded in Mathematica technical computing software, which is based on the planar projections and intersections of fibers and provided as supplementary material to the present article. According to this technique, fiber geometries in discrete rectangular prismatic segments were generated by using uniform distributions of the geometrical and spatial parameters and projected onto the transverse plane. Then, projected geometries were trimmed within the transverse boundaries of the specified specimen shape, rectangular prism in this particular study. After this step, fiber crossings were determined through a search algorithm, which was also used as the basis for the fiber spatial regeneration. Thereafter, fibers were accumulated on top of each other by taking fiber crossings into account and eventually fiber networks based on selected properties were formed. By means of the proposed technique, a series of simulation experiments were conducted on paper fiber networks to investigate the correlation between the fiber network connectivity and fiber length, cross-sectional properties, orientation and specimen length, width and thickness. [ABSTRACT FROM AUTHOR]

Since carbon fiber woven composite panels contain complex fiber bundle structures, the aim of this paper is to investigate the factors influencing the macro-equivalent properties and topological flexibility of composite panels resulting from variations in fiber bundle configuration. Firstly, the structural topology optimization design of carbon fiber composite plates was achieved using a multi-scale modeling approach with the variable density method. Nonlinear relationships between carbon fiber bundle configuration parameters and macroscopic equivalent properties, as well as macroscale topological flexibility, were determined using deep learning methods, respectively. The maximum error in the predicted values of the deep learning network model does not exceed 0.5% when compared with the results of the finite element calculations. In addition, utilizing deep learning networks to predict macro-equivalent properties of composites can significantly decrease computational time. The impact of varying the number of filaments in fiber bundles and the spacing of the fiber bundles on the flexibility of the topology was determined using a deep learning network. The optimal topological flexibility, along with its corresponding fiber bundle spacing and number of fiber bundle filaments, are globally searched within the design domain using an adaptive genetic algorithm. The study in this paper can provide a reference for designing fiber bundle configurations of composites for practical applications. [ABSTRACT FROM AUTHOR]

• The cohesive bond model demonstrates good agreement with experimental results. • Significant dynamic enhancement occurs at the concrete-CFRP strip interface during blast loading. • Blast wave propagation induces interface damage between concrete and CFRP strip. • A dynamic increase factor (DIF) is necessary for modelling CFRP-concrete interface behaviour under blast loading. The paper is structured into two main sections. In the first part, the focus is on the finite element (FE) analysis of bond slip in a single bond shear test between concrete and carbon fiber reinforced polymer (CFRP) strips under static loads. To model the test set-up, a plastic damage material model and an elastic material model are used for the concrete prism and the unidirectional CFRP strip respectively. Three approaches, including a perfect bond model, a cohesive bond model, and contact algorithms based on recent bond slip models, are employed to simulate the bond interface. The numerical model's validity is confirmed through comparison with experimental results from the literature. The paper predicts the debonding failure mode, the strain evolution along the bond length, and the delamination loads of the CFRP strip. The cohesive bond model exhibits good agreement between numerical and experimental data. In the second part of the paper, the developed FE model is tested under blast loading and compared to the experimental results of the blast tests conducted by the authors. The experimental and numerical findings highlight a significant dynamic enhancement effect on bond-slip properties due to the propagation of the blast wave within the concrete and the high loading rate. [ABSTRACT FROM AUTHOR]

Accurately predicting Cure-Induced Distortion (CID) is paramount to ensuring manufacturing precision. Existing prediction models heavily rely on material parameters associated with the CID, which presents challenges for newly developed composites due to the time-consuming, expensive, and limited accuracy of parameter characterization processes. With recognizing the shared curing mechanism across various composites, this paper introduces a transfer learning-based approach that leverages a small dataset of practical CID data from the newly developed composite and historical knowledge from existing composites to achieve rapid and accurate CID predictions. This approach was validated for two typical CID prediction cases by implementing a transfer learning framework, and various sampling methods were explored to assess the stability and repeatability of prediction results. The results indicate that the proposed method can predict the CID within a 5% margin of error. This paper offers a promising approach for predicting CID in the design and manufacturing processes. [ABSTRACT FROM AUTHOR]