Composite Geometry Research Articles

Vibration-Based Damage Prediction in Composite Concrete–Steel Structures Using Finite Elements

The prediction of structural damage through vibrational analysis is a critical task in the field of composite structures. Structural defects and damage can negatively influence the load-carrying capacity of the beam. Therefore, detecting structural damage early is essential to preventing catastrophic failures. This study addresses the challenge of predicting damage in composite concrete–steel beams using a vibration-based finite element approach. To tackle this complex task, a finite element model to a quasi-static analysis emulating a four-point pure bending experimental test was performed. Notably, the numerical model equations were carefully modified using the Newton–Raphson method to account for the stiffness degradation resulting from material strains. These modified equations were subsequently employed in a modal analysis to compute modal shapes and natural frequencies corresponding to the stressed state. The difference between initial and damaged modal shape curvatures served as the foundation for predicting a damage index. The approach effectively captured stiffness degradation in the model, leading to observable changes in modal responses, including a reduction in natural frequencies and variations in modal shapes. This enabled the accurate prediction of damage instances during construction, service, or accidental load scenarios, thereby enhancing the structural and operational safety of composite system designs. This research contributes to the advancement of vibration-based methods for damage detection, emphasizing the complexities in characterizing damage in composite structural geometries. Further exploration and refinement of this approach are essential for the precise classification of damage types.

Tailoring the Properties of 2D Nanomaterial‐Polymer Composites for Electromagnetic Interference Shielding and Energy Storage by 3D Printing—A Review

3D‐printed 2D nanomaterials‐based polymer composites, with their exceptional electrical conductivity and structural functionalities, have become leading‐edge engineering materials for electromagnetic interference (EMI) shielding, sensors, and energy storage applications. This review begins with a brief introduction to various types of 2D nanomaterials and their fabrication techniques, specifically different types of 3D printing. The subsequent sections highlight key factors such as rheological properties, surface tension, additives, and binders that influence the printability of 2D nanomaterials‐based polymer composites. The advancements in 2D nanomaterials‐based polymers, including MXene, graphene, and graphene derivatives, are then presented. The interaction, dispersion, and/or network formation of 2D nanomaterials in the polymer matrix is a crucial factor in determining the electrical performance of the composites. This review also discusses surface modification strategies for 2D nanomaterials to enhance their sensing, EMI shielding, and energy storage capabilities. Finally, the impact of various 3D‐printed polymer composite geometries, such as rectangular, cylinder, and circular, on shielding performance is thoroughly examined, engaging the reader in the exploration of these materials.

Designing optimized geometry and fiber orientation of composites for dynamic tension via artificial intelligence

Machine learning is quickly becoming an invaluable tool for examining large databases to find patterns and predictions based on similar parameters tested in previous studies. A natural application of this subset of artificial intelligence revolves around material data sets where tests are repeated for basic studies (e.g. tension, compression, bending, or shear) and extrapolating the data for tests not yet considered. Dynamic testing and validation with machine learning is examined here, as a significant time and cost is required for understanding larger-sized specimens (cm scale and larger) especially when the samples are composite materials in tension. This is due in part to the challenges involved in ensuring failure at the region of interests for an anisotropic material and minimizing the number of repeated tests. In this study, the data sets were generated artificially via finite element analysis with failure, and a machine learning code applied to infer the shape of the tensile test coupon knowing only the failure and stress field. Then the algorithm was run to generate a library of ideal coupon geometries based on ply angle and area location of failure within the test specimen. The result is a highly efficient prediction algorithm that can create the ideal specimen shape for tensile testing at speeds orders of magnitude faster than comparable finite element codes.

Finite element modeling of concentrated impact loads on the masticatory muscles at the head

AbstractNumerical simulation has great potential to provide a more comprehensive understanding of human impact response to injury mechanisms. Finite Element (FE) models are used as a tool to study human injuries in greater detail, for example, the THUMS (Total Human Model Safety of TOYOTA) model, which is widely used as a reliable human model in different fields to predict human injuries such as fractures, internal organ damage, and brain tissue injuries. However, no available FE model can be used to simulate human‐robot collisions based on standards ISO/TS 15066 and the biomechanical characteristics of human soft tissues in vivo. The authors have developed a head model based on the structures (dimensions and anatomy) of the THUMS head model, specifically designed to simulate impact loads on the masticatory muscles. Based on medical imaging (MRI) data, the soft tissues at the location of the masticatory muscles in the THUMS head are transformed from monolayer to multilayer, that is, a composite geometry of skin‐fat‐muscle each with its own material model and parameters. The model was optimized and validated using the experimental data from the Fraunhofer IFF subjects study, which determined biomechanical thresholds for specific body locations in ISO/TS 15066 under dynamic collisions.

Process-structure–property study of 3D-printed continuous fiber reinforced composites

3D-printed fiber-reinforced composites hold many advantages compared to conventional composites in terms of individualization, mass customization, design freedom, and tailoring the composite geometry to load-bearing specifications. Among candidate continuous fibers for reinforcement, basalt fibers (BFs) serve as an eco-friendly alternative with excellent physical and thermal properties. However, the applicability of continuous BFs to be used for 3D-printed polymer composites was rarely addressed in existing literature. Especially, the effects of impregnation density during manufacturing and the influence of local fiber distribution on the fracture behavior of BF-reinforced composites remain unclear. In this study, a solution coating process was employed as a fiber pre-treatment to improve the packing density of BF in a polylactide (PLA) matrix. The effects of the resulting fiber volume fraction (8–31 %) and the local fiber distribution on the tensile fracture mechanisms of 3D printed BF/PLA samples are thoroughly analyzed using three-dimensional X-ray tomography. It was found that at a concentration of 3 wt%, the coating solution uniformly dispersed optimally between the fibers, resulting in improved impregnation densities of the BF in the PLA matrix. Thus, the resulting composite exhibited a tensile strength of 175 MPa and a Young’s modulus of 6.2 GPa, respectively. A standard linear solid (SLS) model is used for property prediction within a composite design framework to be applied to 3D-printed BF/PLA structures. The model is validated with experimental data from tensile tests. The obtained results demonstrate the applicability of eco-friendly BF/PLA composites for 3D printing of industrial high-performance applications with an individualized property profile.

SonoPrint: Acoustically Assisted Volumetric 3D Printing for Composites.

Advances in additive manufacturing in composites have transformed aerospace, medical devices, tissue engineering, and electronics. A key aspect of enhancing properties of 3D-printed objects involves fine-tuning the material by embedding and orienting reinforcement within the structure. Existing methods for orienting these reinforcements are limited by pattern types, alignment, and particle characteristics. Acoustics offers a versatile method to control the particles independent of their size, geometry, and charge, enabling intricate pattern formations. However, integrating acoustics into 3D printing has been challenging due to the scattering of the acoustic field between polymerized layers and unpolymerized resin, resulting in unwanted patterns. To address this challenge, SonoPrint, an innovative acoustically assisted volumetric 3D printer is developed that enables simultaneous reinforcement patterning and printing of the entire structure. SonoPrint generates mechanically tunable composite geometries by embedding reinforcement particles, such as microscopic glass, metal, and polystyrene, within the fabricated structure. This printer employs a standing wave field to create targeted particle motifs-including parallel lines, radial lines, circles, rhombuses, hexagons, and polygons-directly in the photosensitive resin, completing the print in just a few minutes. SonoPrint enhances structural properties and promises to advance volumetric printing, unlocking applications in tissue engineering, biohybrid robots, and composite fabrication.

Debonding behavior of non-welded wrapped composite X-joints subjected to monotonic tensile load – Numerical study and validation

The dominant failure mode in the non-welded wrapped composite joints made with GFRP composite material wrapped around steel circular hollow sections (CHS) is characterized as interface debonding. However, in the ultimate load joint experiments, debonding process was merely inferred from the surface strain distribution obtained by the digital image correlation (DIC). A thorough understanding and explicit illustration of debonding mechanism in wrapped composite X-joints is needed with help of finite element modeling (FEM), in order to provide prediction models for design of wrapped composite joints in engineering structures. In this paper, two FE models were developed to simulate the debonding behavior of small-scale and medium-scale wrapped composite 45° X-joints in monotonic tensile tests previously conducted by the authors. A new strategy of modeling complex composite geometry using 4-node tetrahedral elements (C3D4) without defining composite lay-up was proposed. The cohesive zone modeling (CZM) approach was utilized to simulate the debonding behavior of composite-steel interface with introduction of a new four-linear traction-separation law. The generated FE models were validated by good agreement between numerical and experimental results in terms of load-displacement response and surface strain distribution throughout the failure process at two joint scales. The validated models gained good insight into the joint debonding mechanism and determined the surface strain threshold for quantifying the debonding length. Development and validation of the FE models with unique set of parameters aligned well with the experiment results at two different scales is an important step for prediction and design of wrapped composite joints.

Failure analysis of 3D woven composites under tension based on realistic model

The failure behavior of the three-dimensional (3D) woven composites under tension are evaluated via experimentation and simulation. To accurately depict the intricate geometry of the woven composites, including the fluctuation of yarn paths, variations in cross-section, and resin distribution, the image-aided digital elements modeling approach is employed. Subsequently, to further assess both the tensile performance and damage response, a realistic voxel model is established with the integration of a well-suited progressive damage model. The obtained stress–strain curves align with the experimental results, and damage progression and underlying mechanisms involved are clearly revealed. Specifically, when subjected to warp tension, severe transverse damage and fiber bundle pull-out towards the warp yarns are observed within the curved section. Similarly, under weft loading, longitudinal damage is found to occur in the weft yarns, while the warp yarns suffer from transverse damage, leading to the formation of a smooth and brittle crack. Ultimately, the findings of this study hold potential to advance the engineering applications of the 3D woven composites.

Heat transfer and fluid flow analysis of PCM-based thermal energy storage concept for double pass solar air heater

Solar air heaters (SAHs) are flat plate collectors used for drying applications without causing any negative impact to the environment. However, SAH suffers from two drawbacks: first is the low convective heat transfer due to formation of boundary layer along the absorber plate, and second is the low thermal efficiency resulting from the lack of solar energy available after sunshine hours. The present study aims to examine the heat transfer and friction factor characteristics of double-pass SAH using two composite roughness geometries: perforated baffles and semicylindrical PCM tubes. The study is conducted at design parameters: blockage ratio (eb/Hd) of 0.4 to 0.8 and tube radius ratios (rt/Hd) of 0.2 to 0.5 under different Reynolds numbers (Re) from 3000 to 13,000. The maximum Nusselt number (Nu) and friction factor (f) are determined to be 200 at Re of 13,000 and 0.629 at Re of 3000, respectively, for the constant value of rt/Hd as 0.3 and eb/Hd as 0.8. In the range of parameters analyzed, maximum increase in Nu and f is determined to be 5.08 times and 65.80 times, respectively, over the smooth duct. Furthermore, correlations are derived for Nu and f with mean absolute error of 4.7% and 3.8%, respectively.

Dimension-reduced mathematical modeling of self-shaping wooden composite bilayers

ABSTRACT Swelling and shrinkage of wood provides challenges when used as construction material. On the positive side, it allows for manufacturing curved wood elements by self-shaping upon drying. We present a two-dimensional model for simulating the moisture-induced bending of wooden bilayers and more general composite plates with multiple, periodically distributed material phases. The model is derived in a mathematically rigorous way from a fully three-dimensional nonlinear hyperelasticity model of the plate and is computationally cheap to handle. We focus specifically on the scenario of free deformations. While the derived model is capable to describe general isometric bending deformations, it has the property that free deformations in equilibrium are given by uniaxial bending deformations that can be computed without the need for solving the plate equations via finite element simulations. The hereby gained computational efficiency enables extensive parameter studies to be conducted regarding the design of wooden composite plates with complex composite geometry. We validate the model for homogeneous wooden bilayers and obtain good agreement between simulations and experimental data. Then we use the model to predict the bending behavior of periodically perforated bilayers. The comparison to other existing models and implications for practical use are discussed.

An experimental and numerical framework to assess the temperature distribution in complex He II-cooled magnet geometries

In the context of the High Luminosity upgrade of the Large Hadron Collider at CERN, a framework implementing experimental techniques and numerical analysis has been developed to systematically assess the temperature distribution in complex He II-cooled composite magnet geometries. The experiments are designed to measure the heat transfer coefficients in the magnet coil layers using coil samples in a stagnant superfluid helium bath. A numerical tool-kit has been developed to facilitate intensive parametric studies, in addition to estimation of helium content via a phenomenological model. The workflow of the tool-kit is built to handle complex geometries composed of different materials each with their temperature-dependent properties, at low computational cost. This framework has been validated with experimental data obtained from laboratory-scale experiments on impregnated coil samples, reported and discussed here. Three use cases for the developed numerical tool, with increasing levels of complexity, are presented and its results discussed.

Combining Lightness and Stiffness through Composite-Reinforced Additive Manufacturing in the Yacht Industry: Case Study Analysis and Application on Large Functional Components

This paper explores applications of additive manufacturing (AM) for producing structural components in the yacht industry. Several case studies illustrate how AM is applied to create lightweight composite panels and complex geometries that are challenging to produce with traditional methods. Experimental and simulation studies demonstrate the mechanical performance of AM-produced parts. The key benefits demonstrated include design flexibility and zero-tool manufacturing. The potential roles of AM in addressing industry challenges, such as customisation possibilities and more sustainable production methods, are discussed. The case studies indicate the technical feasibility of 3D printing for functional yacht applications across various scales. Overall, AM shows promise in revolutionising design and manufacturing approaches by enabling optimised structures and on-demand production without traditional manufacturing constraints. This research study highlights the technology’s role in evolving yacht design and production practices.

Three-Dimensional Finite Element Modeling of Ultrasonic Vibration-Assisted Milling of the Nomex Honeycomb Structure

Machining of Nomex honeycomb composite (NHC) structures is of critical importance in manufacturing parts to the specifications required in the aerospace industry. However, the special characteristics of the Nomex honeycomb structure, including its composite nature and complex geometry, require a specific machining approach to avoid cutting defects and ensure optimal surface quality. To overcome this problem, this research suggests the adoption of RUM technology, which involves the application of ultrasonic vibrations following the axis of revolution of the UCK cutting tool. To achieve this objective, a three-dimensional finite element numerical model of Nomex honeycomb structure machining is developed with the Abaqus/Explicit software, 2017 version. Based on this model, this research examines the impact of vibration amplitude on the machinability of this kind of structure, including cutting force components, stress and strain distribution, and surface quality as well as the size of the chips. In conclusion, the results highlight that the use of ultrasonic vibrations results in an important reduction in the components of the cutting force by up to 42%, improves the quality of the surface, and decreases the size of the chips.

Towards the realization of composite metastructures: A failure analysis of connections

Metastructures hold significant potential for applications such as adaptive structures and soft robotics. Architectures of fiber-reinforced polymer metastructures may relate to modular arrangement of straight and curved laminates, with their connections to resemble perfect cracks, thus susceptible to delamination. This study investigated geometrical effects on the load-carrying capabilities of these connections upon a global tensile deformation, as well as lean modeling tools to facilitate the development of architected composite metastructures. Numerical fracture mechanics approach on different connection geometries and thicknesses showed that connection delamination is a critical failure mode, but crack-driving-force has low dependence on connection shape for given ligament thickness (and stiffness). Adopted analytical models could capture either moment or force-driven delamination failure, while the intermediate regime necessitates numerical tools. First-ply failure may precede depending on shape and ligament stiffness. These trends were also verified on an exemplary rotating chiral composite geometry. Furthermore, interface load-carrying capability improvements were studied via design considerations including connection filler material and element variable thickness. Indicatively, the latter showed a 157 % increase in bending deflection (and global deformations), while reducing crack driving force by 38 % for a given load case. The conducted analysis offers valuable insights into the design of lightweight, load-carrying composite metastructures.

Failure mechanisms and process defects of 3D-printed continuous carbon fiber-reinforced composite circular honeycomb structures with different stacking directions

3D printing of continuous carbon fiber-reinforced composites relieves molds in composite manufacturing and gives flexibility to the design of lightweight and robust circular honeycomb structures. Nevertheless, how process defects affect the failure mechanisms of 3D-printed continuous carbon fiber-reinforced honeycomb structures remains undisclosed. To advance this research area, it requires a comprehensive investigation of the failure mechanisms and process defects of 3D-printed continuous carbon fiber-reinforced composite circular honeycomb structures (CCFRCCHSs), with particular attention to the influence of stacking orientations. In this study, 3D printing has been introduced to fabricate CCFRCCHSs using the identical composite material and geometry but different stacking orientations. Both in-plane and out-of-plane quasi-static compression experiments were carried out on these CCFRCCHSs. The mechanical properties and failure mechanisms were investigated through experimental analysis and cross-section observation, from which the microscopic voids and weak interfaces were identified as the dominating factors influencing the failure modes of CCFRCCHSs. This study provides insights into the association between process defects and failure mechanisms of 3D-printed CCFRCCHSs with different stacking directions, which offers guidance for the design of lightweight and robust composite circular honeycomb structures.

Effect of tool feed rate and tool rotation speed on the microchannel geometry of AA6063-SiC composites machined by micro ED milling

ABSTRACT Miniaturisation of products is an emerging trend in the current scenario. Conventional micromachining of metal matrix composites poses difficulties due to the heterogeneous nature of the material and the presence of hard reinforcement particles. Micro-electric discharge machining has emerged as a proficient method for the precision machining of challenging materials. In this work, micro-ED milling of AA6063–4 wt. % SiC composite was carried out using a graphite electrode. Being the primitive unit of 3D machining, microchannels were machined on the workpiece at different discharge energies, tool feed rates, and tool rotation speeds. The geometrical features of the channel such as channel width, kerf width, taper of the microchannels, and process indicators like tool wear rate and material removal rate were studied. The 6 µm/s tool feed rate, 500 rpm tool rotation speed, and 500 µJ discharge energy provided the desired results for the studied responses.

Influence of processing parameters on the resin pocket geometry of smart composites embedded with Fiber Bragg Grating sensor and its fast prediction

AbstractSmart composites embedded with Fiber Bragg Grating (FBG) sensors are getting increasingly popular in aircraft structures due to their self‐sensing and monitoring capability. However, a resin pocket around the FBG sensor would be formed in the manufacturing process, which strongly impacts the mechanical properties of the composite host. Therefore, the influence of primary processing parameters (FBG orientation angle, preforming temperature, and preforming pressure) on the formation of resin pockets was investigated in this work. It is found that there is a sinusoidal relation between the resin pocket geometry and the FBG orientation angle. A negative linear relation is noted between the resin pocket geometry and the preforming temperature and pressure. A prediction model based on the backpropagation neural network (BPNN) was established, which was able to quickly and accurately predict resin pocket geometry subjected to given processing parameters. This work provides useful guidance for the processing control of smart composites embedded with FBG sensors.Highlights Resin pocket geometry was formed primarily in the preforming stage. Effect of processing parameters on resin pocket geometry was characterized. A BPNN model was established for the fast prediction of resin pocket geometry.

Designed Microbial Biosynthesis of Hierarchical Bone-Mimetic Biocomposites in 3D-Printed Soft Bioreactors.

The creation of 3D biomimetic composite structures has important applications in tissue engineering, lightweight structures, drug delivery, and sensing. Previous approaches in fabricating 3D biomimetic composites have relied on blending or assembling chemically synthesized molecules or structures, making it challenging to achieve precise control of the size, geometry, and internal structure of the biomimetic composites. Here, we present a new approach for the creation of 3D bone-mimetic biocomposites with precisely controlled shape, hierarchical structure, and functionalities. Our approach is based on the integration of programmable microbial biosynthesis with 3D printing of gas-permeable and customizable bioreactors. The organic and inorganic components are bacterial cellulose and calcium hydroxyapatite via a mineral precursor, which are generated by Komagataeibacter xylinus and Bacillus simplex P6A, respectively, in 3D-printed silicone bioreactors in consecutive culturing cycles. This study is of high significance to biocomposites, biofabrication, and tissue engineering as it paves the way for the synergistic integration of microbial biosynthesis and additive manufacturing.

Association of 20-Year Longitudinal Depressive Symptoms With Left Ventricular Geometry Outcomes in the Coronary Artery Risk Development in Young Adults Study: A Role for Androgens?

Depression is a risk factor for coronary heart disease and left ventricular hypertrophy (LVH) is a potent predictor of coronary heart disease events. Whether depression is associated with LVH has received limited investigation. This study assessed cross-sectional and 20-year longitudinal associations of depressive symptoms with LVH outcomes after accounting for important known confounders. From 5115 participants enrolled in 1985-1986 in the Coronary Artery Risk Development in Young Adults Study, 2533 had serial measures of depressive symptoms and subsequent echocardiography to measure normal LV geometry, concentric remodeling, and LVH. The primary exposure variable was trajectories of the Center for Epidemiologic Studies Depression (CES-D) scale score from 1990-1991 to 2010-2011. Multivariable polytomous logistic regression was used to assess associations of trajectories with a composite LV geometry outcome created using echocardiogram data measured in 2010-2011 and 2015-2016. Sex-specific conflicting results led to exploratory models that examined potential importance of testosterone and sex hormone-binding globulin. Overall CES-D and Somatic subscale trajectories had significant associations with LVH for female participants only. Odds ratios for the subthreshold (mean CES-D ≈ 14) and stable (mean CES-D ≈ 19) groups were 1.49 (95% confidence interval = 1.05-2.13) and 1.88 (95% confidence interval = 1.16-3.04), respectively. For female participants, sex hormone-binding globulin was inversely associated with LVH, and for male participants, bioavailable testosterone was positively associated with concentric geometry. Findings from cross-sectional and longitudinal regression models for female participants, but not male ones, and particularly for Somatic subscale trajectories suggested a plausible link among depression, androgens, and LVH. The role of androgens to the depression-LVH relation requires additional investigation in future studies.

Verifying institutionally developed hybrid 3D-printed coaxial cylindrical phantom for patient-specific quality assurance in stereotactic body radiation therapy of hepatocellular carcinoma.

An accurate and reliablepatient-specific quality assurance (PSQA) is crucial to ensure the safety and precision of Stereotactic body radiation therapy (SBRT) in treating Hepatocellular carcinoma (HCC). This study examines the effectiveness of a novel hybrid 3D-printed hybrid coaxial cylindrical phantom for PSQA in the SBRT of HCC. The study compared three different point dose verification techniques for PSQA: a traditional solid water phantom, two dimensional detector array I'MatriXX, and a newly developed hybrid 3D-printed phantom. Thirty SBRT HCC liver cases were examined using these techniques, and point doses were measured and compared to planned doses using the perpendicular composite method with solid water and I'MatriXX phantoms. Unlike the other two methods, the point dose was compared in true composite geometry using the hybrid 3D-printed phantom, which enhanced the accuracy and consistency of PSQA. The study aims to assess the statistical significance and accuracy of the hybrid 3D-printed phantom compared to other methods. The results showed all techniques complied with the institutional threshold criteria of within ± 3% for point-dose measurement discrepancies. The hybrid 3D-printed phantom was found to have better consistency with a lower standard deviation than traditional methods. Statistical analysis using Student's t-test revealed the statistical significance of the hybrid 3D-printed phantom technique in patient-specific point-dose assessments with a p-value < 0.01. The hybrid 3D-printed phantom developed institutionally is cost-effective and easy to handle. It has been proven to be a valuable tool for PSQA in SBRT for the treatment of HCC and has demonstrated its practicality and reliability.