Structural Mechanics Research Articles

Analyze the temperature-dependent elastic properties of single-walled boron nitride nanotubes by a modified energy method

The elastic properties of boron nitride nanotubes (BNNTs) were investigated utilizing an enhanced energy method. By considering small deformations and applying the principle of minimum potential energy, the variations in atomic bonds and bond angles within the nanotube structure were determined. The modified model incorporated the contribution of inversion energy to the overall potential energy of the system, leading to the derivation of analytical expressions for the Young's modulus, shear modulus, and strain energy of both armchair and zigzag BNNTs under varying temperatures. The results indicate that compared to zigzag BNNTs, the impact of inversion energy on the elastic constants of armchair BNNTs is more significant, especially at small diameters (<1 nm). In thermal environment, this study demonstrates that the change in Young's modulus of BNNTs is lower than that of carbon nanotubes (CNTs), confirming the superior thermal stability of BNNTs over CNTs. Furthermore, molecular structure mechanics (MSM) and continuum mechanics models were employed to analyze the strain energy of BNNTs. The effects of different bonds, bond angles, and inversion angles on strain energy were analyzed in a thermal environment, revealing distinct differences between the two types of BNNTs. These findings provide more accurate theoretical guidance for thermal applications based on the stretching of BNNTs.

On the Determination of Elastic Properties of Single-Walled Nitride Nanotubes Using Numerical Simulation.

In recent years, tubular nanostructures have been related to immense advances in various fields of science and technology. Considerable research efforts have been centred on the theoretical prediction and manufacturing of non-carbon nanotubes (NTs), which meet modern requirements for the development of novel devices and systems. In this context, diatomic inorganic nanotubes formed by atoms of elements from the 13th group of the periodic table (B, Al, Ga, In, Tl) and nitrogen (N) have received much research attention. In this study, the elastic properties of single-walled boron nitride, aluminium nitride, gallium nitride, indium nitride, and thallium nitride nanotubes were assessed numerically using the nanoscale continuum modelling approach (also called molecular structural mechanics). The elastic properties (rigidities, surface Young's and shear moduli, and Poisson's ratio) of nitride nanotubes are discussed with respect to the bond length of the corresponding diatomic hexagonal lattice. The results obtained contribute to a better understanding of the mechanical response of nitride compound-based nanotubes, covering a broad range, from the well-studied boron nitride NTs to the hypothetical thallium nitride NTs.

PRECICE nail bending in femur lengthening

IntroIntramedullary nails (ILNs) are commonly used in orthopedic surgery for the fixation of long bone fractures and limb lengthening. Understanding the structural mechanics (i.e. nail bend) of an ILN device is crucial in determining its performance under various loading conditions. Furthermore, nail diameter was found to play a key role in an ILN's susceptibility to plastic deformity. This study aims to investigate the degree of nail bending and incidence of plastic deformity in patients receiving antegrade femoral ILNs (PRECICE, NuVasive, Inc.). MethodsRetrospectively evaluated 130 ILNs (PRECICE, NuVasive, Inc.) in 100 adult patients who underwent limb lengthening done in a single center. Patients who had concomitant osteotomies, tibial lengthening, malunion, non-union, mechanical failure, or revision surgery for any reason were excluded. All nails were inserted through the greater trochanter or piriformis. Patients’ age, weight, height, and body mass index (BMI)were extracted. Radiologic assessments involved analyzing long lower limb standing X-rays before, during, and at consolidation for total distraction and nail bend. Naildiameter and patient characteristics were directly sourced from medical records. ResultsNail bend at consolidation averaged 2.4° (SD 2.4), ranging from 0 to 9. Additionally, total femoral lengthening was assessed, with a mean value of 5.3 cm (SD 2.1). A significant positive association was observed in the nail bend and weight (weight in kg/nail diameter in mm) coefficient (P < 00.01). Bilateral limb lengthening was also correlated to increase nail bend (P < 00.05). ConclusionPatient's weight to nail diameter ratio and bilateral limb lengthening were found to be significant factors affecting nail bend. These findings advance our understanding of the interrelation between the nail biomechanical profile and the patient's physical attributes, offering important implications for limb lengthening. Level of evidenceIII.

Impact of Atomic Vacancy Defects on Vibrational Characteristics of Chiral MWCNT for Viruses/Bacteria

In this study the authors investigated the vibrations performance of chiral multi-walled carbon nanotubes (MWCNTs). They examined chiral MWCNTs with attached bacteria positioned at both the tip and middle sections of the nanotubes. The main goal of this research was to create a sensor with the ability to detect and distinguish bacteria or viruses that could potentially adhere to the surfaces of chiral MWCNTs. The authors considered two boundary conditions, fixed-fixed and fixed -free for the chiral MWCNT. They utilized a molecular structural mechanics approach. In this approach the vibrational responses of chiral MWCNT-based nano-biosensors with different diameters of the chiral MWCNTs were examined. The study’s objective was to fill research gaps by introducing an innovative approach for detecting defects in chiral MWCNTs through vibrational analysis. They simulated 432 MWCNT samples to investigate the vibrational performance of defective chiral MWCNTs. The results suggested that the first mode of the vibrational frequency of the chiral MWCNT is particularly significant for sensing applications. It was observed that as the percentage of vacancy defects increased, the natural frequency decreased for both boundary conditions.

Hofmeister-Effect-Driven Hybrid Glycerogels for Perfect Wide-Temperature Shape Fixity and Shape Recovery in Soft Robotics Applications.

Shape memory gels have emerged as crucial elements in soft robotics, actuators, and biomedical devices; however, several problems persist, like the trade-off between shape fixity and shape recovery, and the limited temperature range for their application. This article introduces a new class of shape memory hybrid glycerogels (GGs) designed to address these limitations. The well-modulated internal structure of the GGs, facilitated by the Hofmeister salting-out effect, strategically incorporates a higher crystallite content, abundant crosslinking points, and a high elastic modulus. Unlike reported shape memory gels, the GG exhibits a perfect triple-step shape memory behavior in air with 100% shape fixity in a wide programming temperature range (75-135°C) and simultaneously achieves 100% shape recoverability. The gel recovers its shape at -40°C under near-infrared light across a wide programming temperature range (25-135°C), showing unexpected initiation even at subzero temperatures. Inspired by the mechanics of composite structures, a method is proposed to integrate the GG seamlessly with a shape memory alloy, which further expands the temperature range that yields perfect shape memory properties. Finally, two light-controlled fluttering and crawling soft robot prototypes are engineered to illustrate the versatility and potential applications of the composite gel in soft robotics.

Deformation and Plasticity of Reinforced Concrete

Statement of the problem.Development of the model of plasticity of reinforced concrete structures is based on the intensity of the "stress-strain" relation to project tensors using transitions, as well as the coefficients of the steps of forces and axes (principal angle and strain-strain, total shear strain, etc.). Results. The dependences of plasticity modulus of concrete, transverse coefficient have been obtained. Complex functions of generalized hypotheses of deplanation of linear and angular deformations and jumps for crack formation breakaway and stiffness are constructed. It includes force flows, i.e., blocks of compressed and tensile concrete for isotropic medium (the first object), "main cracks" from fracture mechanics, functional and two-cone element for the deformation effect of reinforced concrete. The resistance of the tensile concrete is transferred to the working reinforcement using the total average longitudinal and transverse forces for the transversal-isotropic environment, including the average modulus of reinforcement and the reduced tensile concrete coefficient of the second limit state group. The special dowel effect is derived from the second level model of structural mechanics for a rebar with two pinched ends, as well as crack opening (a development of the Thomas –– author hypothesis), crack-track bank shear, and buckling. The main vector of forces in the reinforcement is characterized by two values of longitudinal and transverse displacements and the width of opening and shear of the crack-track (the third object). Conclusions. The energetic theory on the surface of the sphere and the determination of the integral of the mean square value of the tangential stresses of plasticity theory allowed to develop an alternative to the ge-neral model in the form of a paraboloid by summing the volume sectors, radius-levels from the matrix of sliding planes (including octahedral and pure shear) in concrete medium from microcracks to macrocracks.

Optimization of cutout characteristics in AISI 1045 steel plates for high-cycle fatigue life extension

Crack growth is a pivotal concern in structural engineering, directly impacting structures’ stability, quality, and overall lifespan. This study addresses this challenge by investigating structural optimization strategies to mitigate fatigue crack growth (FCG) by strategically incorporating stop-drilled cutouts near the crack tip. The research introduces three optimization problems, focusing on determining the optimal cutout position with a fixed radius, the optimal cutout radius with a fixed position, and the optimal cutout shape with a constant position for the cutout’s center. Experimental assessments are conducted on an edge-cracked AISI 1045 steel plate to evaluate the effectiveness of these optimization strategies in enhancing fatigue life. Employing the Extended Finite Element Method (XFEM) for numerical simulations and Particle Swarm Optimization (PSO) for the optimization process, the findings reveal that strategically positioned cutouts substantially reduce the crack growth rate. Optimal cutout placement significantly improves fatigue life, demonstrating an approximate 287% increase. The analysis affirms the accuracy of the numerical model in predicting fatigue life and crack growth paths, validated through comparison with experimental data. In summary, this research underscores the effectiveness of optimization techniques in mitigating fatigue crack growth, providing valuable insights for structural integrity enhancement in structural mechanics.

Recognition of local fiber orientation state in prepreg platelet molded composites via deep learning

This paper presents a novel deep learning approach for reconstruction of local through-the-thickness fiber orientation distribution (FOD) in discontinuous long-fiber, prepreg-platelet molded composites (PPMC). The thermal-residual strains on composite surfaces are used as inputs to train a fully convolutional neural network, named U-Net, to predict spatially varying, local FOD. High fidelity synthetic data was generated via computational simulation of PPMC with stochastic material orientation state and was used for training the deep learning model. The proposed U-Net model allowed for rapid recognition of PPMC morphology by solving the inverse structural mechanics problem of determining the average fiber orientation through the composite thickness based on the provided surface strain measurements. Upon training and validation, the U-Net deep learning model was deployed to rapidly predict complex distributions of the local through-the-thickness FOD in PPMC.

Weak-formulated physics-informed modeling and optimization for heterogeneous digital materials.

Numerical solutions to partial differential equations (PDEs) are instrumental for material structural design where extensive data screening is needed. However, traditional numerical methods demand significant computational resources, highlighting the need for innovative optimization algorithms to streamline design exploration. Direct gradient-based optimization algorithms, while effective, rely on design initialization and require complex, problem-specific sensitivity derivations. The advent of machine learning offers a promising alternative to handling large parameter spaces. To further mitigate data dependency, researchers have developed physics-informed neural networks (PINNs) to learn directly from PDEs. However, the intrinsic continuity requirement of PINNs restricts their application in structural mechanics problems, especially for composite materials. Our work addresses this discontinuity issue by substituting the PDE residual with a weak formulation in the physics-informed training process. The proposed approach is exemplified in modeling digital materials, which are mathematical representations of complex composites that possess extreme structural discontinuity. This article also introduces an interactive process that integrates physics-informed loss with design objectives, eliminating the need for pretrained surrogate models or analytical sensitivity derivations. The results demonstrate that our approach can preserve the physical accuracy in data-free material surrogate modeling but also accelerates the direct optimization process without model pretraining.

Development of 6-way CFD-DEM-FEM momentum coupling interface using partitioned coupling approach

Fluid-particle-structure interactions (FPSI) govern a wide range of natural and engineering phenomena, from landslides to erosion in abrasive water jet cutting nozzles. Despite the importance of studying FPSI, existing numerical frameworks often simplify or neglect certain physics, limiting their applicability. This work introduces a novel 6-way CFD-DEM-FEM momentum coupling for FPSI using a partitioned coupling approach, providing a flexible and adaptable solution.Our prototype uses the preCICE coupling library to couple three numerical solvers: OpenFOAM for fluid dynamics, eXtended Discrete Element Method (XDEM) for particle motion, and CalculiX for structural mechanics. The coupling approach extends existing adapters and introduces a novel XDEM preCICE adapter, allowing data exchange over surface and volumetric meshes.Numerical experiments successfully demonstrate the 6-way coupling, showcasing fluid-structure interactions and particle dynamics. The versatility of the partitioned coupling approach is highlighted, allowing the interchangeability of different single-physics solvers and facilitating the study of complex FPSI phenomena.This article offers a thorough description of the methodology, coupling strategies, and detailed results, offering insights into the advantages and disadvantages of the proposed approach. This work lays the groundwork for a scalable and customizable FPSI simulation framework with a wide range of applications.

Gas solubility enhancement and hydrogen bond recombination regulated by terahertz electromagnetic field for rapid formation of gas hydrates

The low solubility of methane in water and the formation of hydrate film at methane-water interface restrict interfacial mass transfer between methane and water, thereby impeding the rapid formation of hydrate. Herein, THz electromagnetic field (TEMF) is introduced to destroy hydrogen bonds through resonance with water molecules for decreasing methane-water interfacial tension (IFT) and improving methane solubility in water. Thereafter, TEMF is removed to restore hydrogen bonding interaction for hydrate nucleation within bulk-phase water rather than at methane-water interface, thereby accelerating hydrate formation. The results show that a TEMF at 15.8 THz can increase methane solubility by 50-fold and provide more nucleation sites for hydrate formation by lowering the IFT by 15-fold. Furthermore, the hydrate nucleation follows “blob” nucleation at low solubility and Local Structuring Mechanism nucleation at high solubility. The higher solubility of methane shortens the induction period of hydrate nucleation form 58.5 ns to 29 ns. Particularly, small 512 cages form preferentially regardless of nucleation pathway. The underlying mechanism for TEMF-induced the acceleration of hydrate formation is attributed to the transition of water phase from a disordered to an ordered structure. This transition arises from the resonance of the TEMF with water molecules, disrupting the hydrogen bond between water molecules and providing sufficient driving force for their rearrangement after removing the TEMF. In rearrangement process, weakly hydrogen-bond interactions correspondingly are converted into strongly hydrogen-bond ones. These findings are expected to improve the understanding of hydrate formation mechanism and promote the applications of terahertz technology in gas hydrates.

Physics-based reduced order modeling for uncertainty quantification of guided wave propagation using Bayesian optimization

Guided wave propagation (GWP) is commonly employed for the design of SHM systems. However, GWP is sensitive to variations in the material properties, often leading to false alarms. To address this issue, uncertainty quantification (UQ) is employed to improve the reliability of the predictions. Computational structural mechanics is a useful tool for the simulation of GWP. Even so, the application of UQ methods requires numerous solutions, while large-scale, transient GWP simulations increase the computational cost. In this paper, we propose a machine learning (ML)-based reduced order model (ROM), annotated as BO-ML-ROM, to decrease the computational time of the GWP simulation. The ROM is integrated with a Bayesian optimization (BO) framework to adaptively sample the data for the ROM training. The results showed that BO outperforms one-shot sampling methods, both in terms of accuracy and speed. The developed ROM, which is orders of magnitude faster than the original solver, is then applied for forward uncertainty quantification of the GWP in an aluminum plate and a composite panel under varying material properties. The UQ analysis reveals the higher impact of the uncertainties in the wave reflections. Furthermore, to compute the influence of the material properties on the predictions, a sensitivity analysis (SA) is performed using the variance-based Sobol’ indices and the Shapley additive explanations, where it is shown that the uncertainties in the elastic properties have a varying influence across time. The predicted results reveal the efficiency of BO-ML-ROM for the simulation of the GWP and demonstrate its utility for UQ and SA.

The axially-loaded behaviours of Schwarz Primitive (SP)-based structures: An experimental and DEM study

This study delves into the axial responses of Schwarz Primitive (SP) structures. Emphasising on bearing capacity, force distribution, cracking phenomena, load-displacement curve and energy absorption. Discrete element method (DEM) is adopted to analyse the axial load-bearing behaviour and fracture mechanics of Main SP and Secondary SP structures under various unit cell configurations after validated by experimental tests. The results indicates that despite sharing the same 1/8th cell structure, the axially-loaded behaviours of the Main SP and Secondary SP structures are not identical, particularly in scenarios involving a large unit cell size and a small number of unit cells. The Main SP structures display an axial load-bearing behaviour that is largely unaffected by variations in the number of unit cells along the x and y axes, while Secondary SP structures show a more pronounced improvement in average strength and energy absorption capacity when the number of unit cells increases. Main SP structures offer superior axial load-bearing capabilities and energy absorption efficiency, which is a significant consideration for their application in scenarios demanding high structural integrity. This distinction underlines the importance of tailored design and selection of SP configurations based on specific engineering requirements.

Impact of Tissue Damage and Hemodynamics on Restenosis Following Percutaneous Transluminal Angioplasty: A Patient-Specific Multiscale Model.

Multiscale agent-based modeling frameworks have recently emerged as promising mechanobiological models to capture the interplay between biomechanical forces, cellular behavior, and molecular pathways underlying restenosis following percutaneous transluminal angioplasty (PTA). However, their applications are mainly limited to idealized scenarios. Herein, a multiscale agent-based modeling framework for investigating restenosis following PTA in a patient-specific superficial femoral artery (SFA) is proposed. The framework replicates the 2-month arterial wall remodeling in response to the PTA-induced injury and altered hemodynamics, by combining three modules: (i) the PTA module, consisting in a finite element structural mechanics simulation of PTA, featuring anisotropic hyperelastic material models coupled with a damage formulation for fibrous soft tissue and the element deletion strategy, providing the arterial wall damage and post-intervention configuration, (ii) the hemodynamics module, quantifying the post-intervention hemodynamics through computational fluid dynamics simulations, and (iii) the tissue remodeling module, based on an agent-based model of cellular dynamics. Two scenarios were explored, considering balloon expansion diameters of 5.2 and 6.2mm. The framework captured PTA-induced arterial tissue lacerations and the post-PTA arterial wall remodeling. This remodeling process involved rapid cellular migration to the PTA-damaged regions, exacerbated cell proliferation and extracellular matrix production, resulting in lumen area reduction up to 1-month follow-up. After this initial reduction, the growth stabilized, due to the resolution of the inflammatory state and changes in hemodynamics. The similarity of the obtained results to clinical observations in treated SFAs suggests the potential of the framework for capturing patient-specific mechanobiological events occurring after PTA intervention.

Exploring the structural mechanics of titanium nickel solid alloy using COMSOL Multiphysics: A Poisson equation and continuity equation perspective

This study investigates the structural mechanics of titanium-nickel (Ti-Ni) alloy thin film using computational modelling through COMSOL Multiphysics based on Poisson’s equation and continuity equation for stress check by considering its linear elastic, conservation of charge and providing insight into nanomaterial deformation. In the COMSOL environment the parameters for titanium nickel (Ti-Ni) are embedded in the COMSOL Simulink interface. The Thin film layer was designed by defining the layer geometry of the size and shape of the layer with a width of 500 μm, depth of 200 μm and height of 3 μm subjected to boundary conditions such as von – mises stress, surface temperature, iso-surface temperature, multi-slice electric potential, displacement component, surface elastic strain energy density and total enthalpy. The results displayed a trend that is, as the surface temperature increases there will be an increase in the current densities associated with high electrical conduction. On the same note, the designed thin film layer will pass the percolation threshold. The results of surface elastic strain energy density and total enthalpy imply that the designed thin film layer is effective and efficient as a structural pseudopotential device (photodiode).

The Roofing System of the Tholos of Athena Pronaia in Delphi: Archaeological Hypotheses and Structural Suggestions

ABSTRACT This study aims to provide an integrated understanding of archaeological findings by evaluating reconstruction hypotheses from a technological and structural perspective, focusing on the Tholos of Athena Pronaia in Delphi, a prime example of 4th and 3rd-century BC Greek architecture. Archaeological research primarily focuses on proportional rules and decorative aspects. The original roof configuration remains uncertain despite its architectural significance and characteristic interlocking marble tiles. The investigation of structural problems is crucial for selecting the most feasible reconstructions and formulating hypotheses on materials, dimensions of structural elements, and how connections between elements were constructed. Due to the many reconstruction uncertainties, a reverse design approach was employed, utilizing schematic technological sections based on the known structural and technical knowledge of the time to ensure consistency between archaeological images and potential underlying structural diagrams. Variables were considered for uncertain dimensions, and the structure’s safety was analysed in terms of material strength and stability. This highlighted not only unsafe solutions but also potential novelties in structural conceptions. This contribution serves as a starting point for research, placing structural mechanics at the service of archaeology with a focus on the tholos roof system.

Model reduction for fatigue life estimation of a welded joint driven by machine learning

In structural mechanics, the design of component assemblies is fundamental for ensuring structural integrity and durability. Fatigue, a common failure mode, particularly challenges the validation of welded joints' fatigue resistance. Various analytical and numerical methods estimate fatigue life but often involve costly processes requiring extensive parameter adjustments and software integration. This study applies machine learning (ML) for metamodeling of a complete finite element analysis and fatigue analysis workflow for estimating the fatigue life of welded joints, considering geometric characteristics, loading conditions, and weld classes. The comparison of the effect of learning database configuration for several regression estimators has led to a reduced model that provides design rules. Our findings demonstrate the significant potential of ML to streamline complex frameworks and accurately estimate the fatigue life of welded joints, advancing AI's application in mechanical engineering.

Reconstruction of the real 3D shape of the SARS-CoV-2 virus

The photographs of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus taken by electron transmission microscopy and cryoelectron microscopy provide only a 2D silhouette. The viruses appear to look like distorted circles. The present paper questions the real shape of the SARS-CoV-2 virus and makes an attempt to give an answer. Is this a general ellipsoid, a spheroid with rotational symmetry, a sphere, or something else? The answer requires the application of tools from three different disciplines: structural mechanics, microbiology, and statistics. A total of 590 virus photographs taken from 22 recently published papers were examined. From this experimental data pool, the histogram of diameter ratios was built from the 283 measurements where the virus images could be approximated as ellipses. The curve peaks at the diameter ratio of 1.22. The transformation equation for the spatial shape to the planar shade was derived for a fixed light source of the microscope. This equation involves an unknown orientation of the viruses with respect to the microscope. Two sets of models were developed, one with a uniform distribution of the virus orientation and the other with the orientation defined by the normalized beta distribution. In both sets of models, the unknown diameter ratio of the spheroidal virus was regarded as a random realization from translated gamma distributions. The parameters of the distribution of the kernel functions were determined by minimizing the mean square difference between the predicted and measured 2D histograms. The information included in the measured histograms was found to be insufficient to find an unknown distribution of the virus’s orientation. Simply too many unknown parameters render the solution physically unrealistic. The minimization procedure with a uniform probability of virus orientation predicted the peak of the aspect ratio of the 3D spheroid at 1.32. Based on this result, models of the virus will be developed in the continuation of this research for a full dynamic analysis.

Research and Practice of Structural Mechanics Teaching Design in the Digital Age

This paper explores innovative strategies and practical applications for teaching structural mechanics courses in the digital era. The focus is on analyzing how online-offline hybrid teaching models can optimize the educational process in structural mechanics and enhance teaching efficiency and student learning outcomes. The paper elaborates in detail on how digital technologies support the teaching of structural mechanics, including the use of various digital tools and platforms to foster student interaction and participation, as well as improve their understanding and mastery of course content. Additionally, the research discusses the effective integration of ideological and political education within structural mechanics teaching, aimed at fostering students' comprehensive abilities. This study provides new perspectives and methods for the teaching design of structural mechanics and related disciplines in a digital learning environment.

Numerical Simulation of a Submerged Floating Tunnel: Validation and Analysis

The dynamic response analysis of submerged floating tunnels (SFTs) under seismic action is a complex two-way fluid–structure coupling problem that requires expertise in structural dynamics, fluid mechanics, and advanced computational methods. The coupled Eulerian–Lagrangian (CEL) method is a promising method for solving fluid–structure interaction problems, but its application to SFTs is not well established. Therefore, it is crucial to verify the accuracy and reliability of the CEL method in fluid–structure coupling simulations. This study verified the applicability of the CEL method for simulating one-way and two-way fluid–structure coupling cylindrical flow problems, and then applied the CEL method for the analysis of a shaking table test of a model SFT. A comparison of results obtained with the CEL method with those obtained in a previous indoor model test of an SFT demonstrates the agreement between the results of the CEL method and the overall trend of the experimental results, indicating the reliability of the method for the seismic analysis of SFTs. Moreover, the analysis of the dynamic response characteristics of SFTs under seismic conditions provides data support and a technological means for the seismic design of SFTs.