Finite Element Model Predictions Research Articles

Veneer-wrapped steel columns: Proof-of-concept experimental and numerical investigations

This paper presents and discusses the structural behaviour of a novel type of steel–timber composite column to be used in residential building applications. It consists of a circular hollow section wrapped by multiple beech veneer sheets and where the composite action is ensured by a structural bi-component glue applied over the contact surfaces. As part of a proof-of-concept study, five short and three long columns with lengths of 0.27 m and 2.00 m, respectively, were tested under vertical concentric load with fibres parallel to the load direction and inclined by 15°. The global response of the specimens in terms of load-displacement behaviour and failure modes was studied, along with localised strain measurements through strain gauges and a digital image correlation (DIC) system. Results showed a significant increase in buckling resistance due to the stiffness added by the veneer layers. Already with the still-moderate veneer layer thicknesses used in this study, an increase in strength of over 25 % could thus be achieved. This enhancement highlights the effectiveness of veneer wrapping in stabilizing the inner core and delaying the occurrence of flexural buckling failure. A 3D non-linear finite element model (FEM) validated these findings, showing a good correlation with experimental results in resistance and stiffness. A parametric study was conducted to explore different geometries and materials, thus creating an extended FEM-based database. A relatively good agreement with modest deviation between the FEM predictions and analytical formulations available in the European Standards was found, considering the appropriate introduction of the mechanical properties of timber.

Numerical investigation on flexural performance of dowel laminated timber with laminas made of laminated veneer lumber

Horizontal dowel laminated timber (H-DLT) is a doweled engineered wood product with laminas made of solid timber. H-DLT has excellent bending resistance. However, the height of cross-section of H-DLT as a beam is limited by the width of solid wood laminas. Laminated veneer lumber (LVL) is an engineered wood product formed by hot-pressed gluing thin veneers, which is flexible in cross-section size compared to solid timber. Horizontal dowel laminated veneer lumber (H-DLVL) was developed by utilizing the H-DLT production methods and LVL material characteristics. H-DLVL has flexible size and good mechanical properties, and it can be made into beams and panels with large cross-sections. In this paper, the flexural performance of H-DLVL beams was investigated. A predictive finite element model of H-DLVL beams was created by the extended finite element method (XFEM) with cohesive zone model (CZM). The numerical models using solid-beam elements without fictitious cracks were verified and calibrated by experimental results. The influence of five variables, including lamina width, thickness, and quantity, dowel spacing along the grain, and dowel row (edge distance), on the flexural performance of H-DLVL beams was analyzed, and the flexural strength of H-DLVL beams was parameterized. The results showed that the failure mode of H-DLVL beams could be well predicted by XFEM without considering fictitious cracks combined with CZM, and the error range of simulated flexural strength of H-DLVL beams was within ±10 %. The flexural strength of H-DLVL beams was directly affected by lamina thickness and dowel spacing along the grain. The flexural strength of H-DLVL beams increased with the increase of those two variables. Lamina width and dowel row (edge distance) affected the flexural strength of H-DLVL beams indirectly by influencing the failure mode of H-DLVL beams. Based on this research, the recommended dowel spacing along the grain of H-DLVL beams was 6.25–12.5 times the wood dowel diameter, and the recommended edge distance of H-DLVL beams was 5–7 times.

Effect of ply misalignment on the notched strength of composite laminates

Predicting the notched strength of carbon fiber-reinforced polymers is a crucial aspect of composite structure design, particularly when considering the uncertainties stemming from geometric features, material variability and defects. This study focuses on the influence of ply misalignment at the meso-scale level. The research employs a comprehensive methodology to establish notched strength allowables, integrating analytical (low fidelity), which have limitations in the representation of stacking sequence effects and in the generation of ply misalignments, and computational tools (high fidelity), employing a finite element model (FEM). The investigation emphasizes the need for a holistic understanding of these factors to enhance the accuracy of predictions. The results predicted by the analytical and, specially, the numerical models are in good agreement with experimental results. Both models underscore the decrease of the notched strength due to ply misalignment. Finally, a hybrid approach is proposed given that FEM predictions offer more accuracy and a detailed comprehension of the failure mechanisms, while fast analytical models can be used to propagate the uncertainties and to determine the allowables.

Assessment of RANS turbulence models based on the cell-based smoothed finite element model for prediction of turbulent flow

There is a growing body of literature that recognizes the importance of Smoothed Finite Element Method (S-FEM) in computational fluid dynamics (CFD) fields and, to a lesser extent, in complex turbulent flow problems. This study evaluates the performance of Reynolds-averaged Navier-Stokes (RANS) turbulence models within the S-FEM framework for predicting incompressible turbulent flows. Our assessment of three turbulence models based on the cell-based S-FEM (CS-FEM) is convincingly supported by testing on three flow problems. It is found that the CS-FEM exhibits superior mesh robustness compared to the Finite Volume Method (FVM) and achieves higher computational accuracy than the Finite Element Method (FEM). Notably, the CS-FEM combined with the standard k-epsilon model (CS-FEM-SKE) and the realizable k-epsilon model (CS-FEM-RKE) demonstrate robust performance in handling severely distorted meshes, with CS-FEM-RKE outperforming in regions of strong flow separation and convection. The Spalart-Allmaras model with CS-FEM (CS-FEM-SA) offers faster computational speed but shows poor mesh robustness. The hexcore mesh based on CS-FEM-RKE is employed to evaluate the aerodynamic performance of High-speed train (HST), resulting in enhanced computational efficiency. The outcomes show good agreement with other numerical studies and experimental data. Overall, it also highlights the latent capability of CS-FEM in solving complex engineering problems.

Mode conversion of fundamental guided ultrasonic wave modes at part-thickness crack-like defects

Guided ultrasonic waves can be employed for efficient structural health monitoring (SHM) and non-destructive evaluation (NDE), as they can propagate long distances along thin structures. The scattering (S0 mode) and mode conversion of low frequency guided waves (S0 to A0 and SH0 wave modes) at part-thickness crack-like defects was studied to quantify the defect detection sensitivity. Three-dimensional (3D) Finite Element (FE) modelling was used to predict the mode conversion and scattering of the fundamental guided wave modes. Experimentally, the S0 mode was excited by a piezoelectric (PZT) transducer in an aluminum plate. A laser vibrometer was used to measure the out-of-plane displacement to characterize the mode-converted A0 mode, employing baseline subtraction to achieve mode and pulse separation. Good agreement between FE model predictions and experimental results was obtained for perpendicular incidence of the S0 mode. The influence of defect depth and length on the scattering and mode conversion was studied and the sensitivity for part-thickness defects was quantified. The maximum mode conversion (S0-A0 mode) occurred for ¾ defect depth and the amplitude of the mode-converted A0 and scattered S0 modes mostly increased linearly as the defect length increased with an almost constant A0/S0 mode scattered amplitude ratio. Similar forward and backward scattering amplitude was found for the mode converted A0 mode. The mode conversion of the S0 to SH0 mode has the highest sensitivity for short defects, but the SH0 mode amplitude only increased slightly for longer defects. Employing the information contained in the mode-converted, scattered guided ultrasonic wave modes could improve the detection sensitivity and localization accuracy of SHM algorithms.

Concurrent geometrico-topological tuning of nanoengineered auxetic lattices fabricated by material extrusion for enhancing multifunctionality: Multiscale experiments, finite element modeling and data-driven prediction

This study demonstrates the multifunctional performance of innovative 2D auxetic lattices through a combination of multiscale experiments, finite element modeling and data-driven prediction. A geometric modeling approach utilizing Voronoi partitioning and a unique branch-stem-branch (BSB) structure, patterned according to 2D wallpaper symmetries, enables precise concurrent geometric and topological tuning of lattices across a continuous parameter space. Selected architectures are physically realized via material extrusion of polylactic acid (PLA) infused with carbon black (CB). Experimental characterizations, supported by Finite Element modeling, reveal the significant influence of BSB structure's design parameters on mechanical and piezoresistive performance under tensile loading, with a remarkable Poisson’s ratio of -0.74, accompanied by a 15-fold increase in elastic stiffness and a 34-fold increase in strain sensitivity. Additionally, architecturally, and topologically tailored lattice structures exhibit tunable damage sensitivity, reflecting the rate of conductive network destruction within the lattice. This offers insights into the rapidity of cell wall failure, with a steeper slope of the piezoresistance curve in the inelastic regime indicating a faster breakdown and quicker onset of mechanical failure. Integration of Gaussian Process Regression enables accurate exploration of the design space beyond realized structures, highlighting the potential of these intelligent lattice structures for applications such as sensors and in situ health monitoring, marking a significant advancement in multifunctional materials.

Predicting the impact of water transport on carbonation-induced corrosion in variably saturated reinforced concrete

A modelling framework for predicting carbonation-induced corrosion in reinforced concrete is presented. The framework constituents include a new model for water transport in cracked concrete, a link between corrosion current density and water saturation, and a theory for characterising concrete carbonation. The theoretical framework is numerically implemented using the finite element method and model predictions are extensively benchmarked against experimental data. The results show that the model is capable of accurately predicting carbonation progress, as well as wetting and drying of cracked and uncracked concrete, revealing a very good agreement with independent experiments from a set of consistent parameters. In addition, insight is gained into the evolution of carbonation penetration and corrosion current density under periodic wetting and drying conditions. Among others, we find that cyclic wetting periods significantly speed up the carbonation progress and that the induced corrosion current density is very sensitive to concrete saturation.

Mechanistic Study of Failure in CFRP Hybrid Bonded-Bolted Interference Connection Structures under Tensile Loading.

Hybrid bonded-bolted composite material interference connections significantly enhance the collaborative load-bearing capabilities of the adhesive layer and bolts, thus improving structural load-carrying capacity and fatigue life. So, these connections offer significant developmental potential and application prospects in aircraft structural assembly. However, interference causes damage to the adhesive layer and composite laminate around the holes, leading to issues with interface damage. In this study, we employed experimental and finite element methods. Initially, different interference-fit sizes were selected for bolt insertion to analyze the damage mechanism of the adhesive layer during interference-fit bolt installation. Subsequently, a finite element tensile model considering damage to the adhesive layer and composite laminate around the holes post-insertion was established. This study aimed to investigate damage in composite bonded-bolted hybrid joints, explore load-carrying rules and failure modes, and reveal the mechanisms of interference effects on structural damage and failure. The research results indicate that the finite element prediction model considering initial damage around the holes is more effective. As the interference-fit size increases, damage to the adhesive layer transitions from surface debonding to local cracking, while damage to the composite matrix shifts from slight compression failure to severe delamination and fiber-bending fracturing. The structural strength shows a trend of initially increasing and then decreasing, with the maximum strength observed at an interference-fit size of 1.1%.

Verification and Validation of finite element models for laminated timber structures using solid, solid-beam and solid-shell approaches

This paper presents a numerical approach to assess efficiently the vibration performance of adhesive-free engineered wood products assembled through compressed wood dowels. Predictive finite element models are obtained by applying the Verification and Validation methodology. The models are first developed using solid elements. Then, solid-beam and solid-shell approaches based on standard solid elements are developed with first-order or higher-order theories. Beam or shell kinematic assumptions are applied throughout the cross-section of the dowels and through the thickness of the layers. From a numerical point of view, a modification of the system of algebraic equations, based on the concept of independent and dependent nodes, is developed. Dependent nodes are eliminated, resulting in a significant reduction in the number of degrees of freedom and floating-point operations. The methodology is evaluated for the calculation of frequencies and mode shapes of adhesive-free laminated timber beams and timber panels with a mix of solid elements, solid-shell and solid-beam approaches. The study highlights the efficiency of the proposed modelling approach in terms of quality of results and model size reduction.

RC beams flexurally strengthened with CFRP sheets combined with FRC layer for mitigating debonding failures

A hybrid strengthening system, comprising a carbon fiber reinforced polymer (CFRP) sheet combined with fiber reinforced concrete (FRC) layer is proposed in this study as a mitigatory solution to brittle debonding problems. Five reinforced concrete (RC) beams, comprising both control cases and those strengthened with the hybrid CFRP-FRC system at various FRP reinforcement ratios, were fabricated and tested to assess the system's effectiveness. A comprehensive finite element (FE) model was also developed to complement the experimental campaign and extend it into a parametric investigation on the effects of FRP reinforcement ratio (ρf), fiber percentage in FRC (vf), and FRC layer thickness (tFRC). Compared with beams strengthened with FRP alone, using the FRC layer increased the ultimate load (Pult.) of FRP-strengthened beams by 29–59%, depending on ρf and vf. The ductility of the hybrid FRP-FRC strengthened beams also increased by more than twice compared to the beams strengthened with only FRP. For the FRP reinforcement ratio (ρf) of 0.18%, use of an FRC layer with vf = 2% yields the highest increase in Pult. and ductility for the hybrid system. Ultimately, the brittle FRP debonding failure was successfully eliminated using the FRC layer, leading to desirable FRP rupture. Built with capabilities to capture material nonlinearity, contact, and debonding phenomena, the FE model predictions excellently matched those of the test results in terms of the beam’s capacity, failure modes as well as load-deflection and load-strain responses.

Nanofabricated high turn-density spiral coils for on-chip electromagneto-optical conversion

Circuit-integrated electromagnets are fundamental building blocks for on-chip signal transduction, modulation, and tunability, with specific applications in environmental and biomedical micromagnetometry. A primary challenge for improving performance is pushing quality limitations while minimizing size and fabrication complexity and retaining spatial capabilities. Recent efforts have exploited highly involved three-dimensional synthesis, advanced insulation, and exotic material compositions. Here, we present a rapid nanofabrication process that employs electron beam dose control for high-turn-density diamond-embedded flat spiral coils; these coils achieve efficient on-chip electromagnetic-to-optical signal conversion. Our fabrication process relies on fast 12.3 s direct writing on standard poly(methyl methacrylate) as a basis for the metal lift-off process. Prototypes with 70 micrometer overall diameters and 49–470 nm interturn spacings with corresponding inductances of 12.3–12.8 nH are developed. We utilize optical micromagnetometry to demonstrate that magnetic field generation at the center of the structure effectively correlates with finite element modeling predictions. Further designs based on our process can be integrated with photolithography to broadly enable optical magnetic sensing and spin-based computation.

Unreinforced masonry walls under two-way out-of-plane bending: Comparison of FE model predictions with analytical models

Four existing design guidelines based on the virtual work method have been compared to predict the out-of-plane (OOP) bending capacities of unreinforced masonry (URM) walls to one-way and two-way actions. The two-way OOP bending design equation as per the Australian masonry standard (AS 3700) and the three subsequent models developed by other researchers are based on specific wall geometries, support conditions, dimensions and strengths of masonry units and mortar. Due to limited experimental data available on URM walls under two-way bending, it is difficult to carry out a detailed investigation of the performance of these two-way design models against all the design parameters. This paper applies the finite element (FE) modelling technique to generate data and extensively investigate the influence of support conditions, pre-compression and aspect ratio on the two-way OOP bending capacity of URM walls. An explicit FE model previously developed by the authors where masonry is macroscopically modelled as an anisotropic composite material, is used for this purpose. Performances of three key parameters (i.e., moment capacity under horizontal bending and diagonal bending and torsional shear strength of masonry) that differentiate the four design models are investigated against varying levels of vertical pre-compression and flexural tensile strength of masonry. The OOP bending capacity predicted by the FE model is compared with the predictions of the design models. Results show that three out of four design models generally overpredict the two-way OOP bending capacities of square and taller walls. Further refinement to the AS 3700 design equation has been proposed in a modified model. The outcomes of this research will help to improve the design of masonry walls under OOP bending.

Pull-out resistance of connected K-wires for osteosynthesis: development of a numerical model

A predictive finite element model was developed to investigate the best configuration of a fixation pins system consisting of two K-wires inserted in a synthetic model (Sawbones®) at different angles and secured to a connecting rod. Two key parameters were considered to determine the best configuration delivering the higher pull-out strength and lower pull-out length: the diameter and insertion angle. Results show that as the diameter and insertion angle increased, the pull-out force increased, while the pull-out length decreased. Results are successfully compared with available experimental data in literature. This model can be used as an alternative to experimental study.

3D-DXA Based Finite Element Modelling for Femur Strength Prediction: Evaluation Against QCT.

Osteoporosis is characterised by the loss of bone density resulting in an increased risk of fragility fractures. The clinical gold standard for diagnosing osteoporosis is based on the areal bone mineral density (aBMD) used as a surrogate for bone strength, in combination with clinical risk factors. Finite element (FE) analyses based on quantitative computed tomography (QCT) have been shown to estimate bone strength better than aBMD. However, their application in the osteoporosis clinics is limited due to exposure of patients to increased X-rays radiation dose. Statistical modelling methods (3D-DXA) enabling the estimation of 3D femur shape and volumetric bone density from dual energy X-ray absorptiometry (DXA) scan have been shown to improve osteoporosis management. The current study used 3D-DXA based FE analyses to estimate femur strength from the routine clinical DXA scans and compared its results against 151 QCT based FE analyses, in a clinical cohort of 157 subjects. The linear regression between the femur strength predicted by QCT-FE and 3D-DXA-FE models correlated highly (coefficient of determination R2 = 0.86) with a root mean square error (RMSE) of 397 N. In conclusion, the current study presented a 3D-DXA-FE modelling tool providing accurate femur strength estimates noninvasively, compared to QCT-FE models.

Numerical analysis and optimization of CFRP buckle arrestors in subsea pipelines

This research investigates the collapse mechanisms and crossover pressure capacity of carbon fiber-reinforced polymer (CFRP) buckle arrestors in subsea pipelines. A nonlinear three-dimensional finite element (FE) model was formulated using ANSYS framework, incorporating a nonlinear geometric algorithm to simulate the collapse and crossover failures. The study underscored a good agreement between the FE model predictions, experimental observations done by the author, and previous research outcomes. Two principal crossover modes; flattening and U-shape modes were identified, though initiated similarly, differ in progression, attributed to the arrestor's attributes. The arrestor thickness ratio (h/t) emerged as a significant determinant of arresting efficiency, particularly impactful when h/t ≥ 1.5. An inverse relationship between σyp/σuc and PX/PP was identified. Furthermore, specific geometric parameters, like h/t and L/D, delineate the predominant crossover mode. Finally, new empirical expressions including the geometric and material parameters are proposed to predict the crossover pressure (PX) for each crossover mode, separately. Also, the findings suggest that CFRP arrestors, especially those with configurations of L = 1.5D and h = 3t, can offer optimum resilience to external pressure.

Piezoelectric impedance-based high-accuracy damage identification using sparsity conscious multi-objective optimization inverse analysis

Two elements are essential in structural health monitoring utilizing dynamic responses: response measurement with high-frequency contents, i.e., small characteristic wavelengths, that can adequately reflect damage features, and effective inverse identification analysis that is however oftentimes under-determined. The advancement of smart structure integration has led to active interrogation through frequency-sweeping piezoelectric impedance measurement at high frequency range. In this research we develop a multi-objective optimization formulation for the identification of damage location and severity utilizing piezoelectric impedance. While one optimization objective is to match the response measurement with finite element model prediction in the damage parametric space, the other is the number of locations of damage, i.e., the sparsity of damage index as the solution vector, since damage usually occurs within a small number of locations. This multi-objective formulation fits well the under-determined nature of damage identification, as it naturally provides multiple solutions as basis for further elucidation. The challenge remaining is how to find a small solution set that can include the actual damage scenario. Here we develop a novel inverse identification framework utilizing the intelligent swarm optimizer which possesses flexibility for enhancement. We first embed a sparsity enforcement process into the population generation of the optimizer, which yields a solution repository intrinsically possessing sparsity. We then apply reinforcement learning so the agents can adaptively opt for local strategies with the aim of enriching the searching patterns to diversify the solutions. Through the incorporation of a Q-table, searching toward more promising directions will be rewarded. Our case analyses employing experimental data indicate that this sparsity-conscious multi-objective particle swarm optimization technique can lead to a small solution set which generally encompasses the true damage scenario. This effectively solves the structural damage identification problem with piezoelectric impedance measurement.

Development of micro-texture patterns of cemented carbide cutting tools to improve cutting performance

Micro texture on cutting tool inserts obtained via laser micro-machining has recently emerged as an environment friendly method to reduce adhesion on the tool’s rake face and to improve friction conditions during machining. However, these benefits are strictly correlated with a correct design and behavior of the texture to be replicated on the tool surface. This paper reports an experimental study of developing an array of dimples on both rake and flank of commercial, cemented carbide cutting inserts using a picosecond laser source. Experiments of orthogonal dry cutting on E235 steel tubes were performed using textured and untextured tools to evaluate the improvements obtained. The improvements achieved were assessed in terms of cutting force and their impact on cutting performances. A predictive finite element model was developed to optimize the design of the dimples, to be replicated onto the rake surface of the tool.

Investigation of single and multicell honeycomb reinforced shape memory polymer composites: Shape optimization and experimental characterization

Honeycomb materials as reinforcements for shape memory polymers have been considered for their commercial availability, ease of geometric tailoring, and high in-plane stiffnesses. The design optimization of these honeycomb cells remains an open field of research, with many approaches taken in formulating the structural optimization problems. This investigation focuses on implementing a shape variable parametrization of the honeycomb to study the possible value of both cell asymmetry and spatially varying cell geometries in multicell networks. A unit cell finite element model framework was developed to predict the in-plane elastic properties of these composites, and two design objectives were selected to be optimized. Pareto fronts were estimated for multiple loading cases and cell wall material models, and experimental results were collected for model validation. The optimization results find that these composites can achieve a large range of performances, with maximum moduli as high as 17.2 GPa. Large asymmetry is found in the optimized cell geometries, and relationships are identified between loading cases and for different wall materials. Furthermore, the experimental results validate the finite element model predictions, with relative errors as low as 20% for the predicted maximum modulus and 2% for the modulus ratio.

Verification Process for Finite Element Modeling Techniques Used in Biological Hard Tissue

Abstract An approach is presented for calculation verification of geometry-based and voxel-based finite element modeling techniques used for biological hard tissue. The purpose of this study is to offer a controlled comparison of geometry- and voxel-based finite element modeling in terms of the convergence (i.e., discretization based on mesh size and/or element order), accuracy, and computational speed in modeling biological hard tissues. All of the geometry-based numerical test models have hp-converged at an acceptable mesh seed length of 0.6 mm, while not all voxel-based models exhibited convergence and no voxel models p-converged. Converged geometry-based meshes were found to offer accurate solutions of the deformed model shape and equivalent vertebral stiffness, while voxel-based models were 6.35% ± 0.84% less stiff (p < 0.0001) and deformed 6.79% ± 0.96% more (p < 0.0001). Based on the controlled verification study results, the voxel-based models must be confirmed with local values and validation of quantities of interest to ensure accurate finite element model predictions.

Data-informed statistical finite element analysis of rail buckling

In this paper, the statistical finite element method is developed further to synthesize distributed rail response data with nonlinear finite element model predictions within and outside the measured loading range. In the data-generating model of the statistical finite element method, the distributed sensing data is decomposed into a finite element model component, a model-reality mismatch component, and a noise component. Each component is considered uncertain and is represented as a Gaussian random vector with a corresponding prior density. The finite element prior density is updated using the Bayesian statistical framework in light of the distributed fiber optic sensing data. The calculated posterior density enables one to infer the true structural response. The required finite element prior density is determined by solving a conventional stochastic forward problem using a polynomial chaos expansion of random fields and a non-intrusive pseudo-spectral projection approach. In this paper, a lab test involving a section of a rail (i.e., a beam-column structural member) instrumented with distributed fiber optic sensors and subjected to axial load causing progressive lateral buckling is considered to demonstrate the use of the statistical finite element method to improve rail response prediction. The results show improved prediction of true rail strain in linear and nonlinear regimes compared with a pure finite element model-based prediction.