Complex Finite Element Model Research Articles

Predicting and optimizing maximum flexural strength of planar composite plate shear walls – concrete filled with the application of LR and RSM

Traditional theoretical models, while conservative, overlook the complex, nonlinear interactions between material and geometric parameters that influence wall flexural strength. Additionally, the extent to which these models maintain their conservative assumptions across varying parameters remains uncertain. This study aims to develop advanced predictive models for the flexural strength of planar composite plate shear walls—concrete filled (C-PSW/CF) by employing Linear Regression (LR) and Response Surface Methodology (RSM). Central Composite Design (CCD) was utilized to design numerical experiments to analyze the effects of varying parameters, including steel plate yield strength, concrete compressive strength, wall depth, depth-to-thickness ratio, and reinforcement ratio. A validated complex finite element modeling (FEM) procedure was used to analyze numerical experiments involving varying parameters of the selected variables. Both LR and RSM were applied to the generated dataset to formulate predictive equations for the maximum moment capacity of walls. Interaction plots were developed to reveal the nonlinear relationships between the variables and identify the most effective parameters influencing the wall strength. Comparisons between theoretical predictions, RSM, and LR models revealed that RSM provided the most accurate predictions, closely aligning with FEM results and effectively capturing the nonlinear interactions between wall parameters. The findings of this paper contribute to the development of more practical, accurate and optimized design methods for C-PSW/CF, ultimately improving both structural safety and efficiency.

Development of a spinopelvic complex finite element model for quantitative analysis of the biomechanical response of patients with degenerative spondylolisthesis.

Research on degenerative spondylolisthesis (DS) has focused primarily on the biomechanical responses of pathological segments, with few studies involving muscle modelling in simulated analysis, leading to an emphasis on the back muscles in physical therapy, neglecting the ventral muscles. The purpose of this study was to quantitatively analyse the biomechanical response of the spinopelvic complex and surrounding muscle groups in DS patients using integrative modelling. The findings may aid in the development of more comprehensive rehabilitation strategies for DS patients. Two new finite element spinopelvic complex models with detailed muscles for normal spine and DS spine (L4 forwards slippage) modelling were established and validated at multiple levels. Then, the spinopelvic position parameters including peak stress of the lumbar isthmic-cortical bone, intervertebral discs, and facet joints; peak strain of the ligaments; peak force of the muscles; and percentage difference in the range of motion were analysed and compared under flexion-extension (F-E), lateral bending (LB), and axial rotation (AR) loading conditions between the two models. Compared with the normal spine model, the DS spine model exhibited greater stress and strain in adjacent biological tissues. Stress at the L4/5 disc and facet joints under AR and LB conditions was approximately 6.6 times greater in the DS spine model than in the normal model, the posterior longitudinal ligament peak strain in the normal model was 1/10 of that in the DS model, and more high-stress areas were found in the DS model, with stress notably transferring forwards. Additionally, compared with the normal spine model, the DS model exhibited greater muscle tensile forces in the lumbosacral muscle groups during F-E and LB motions. The psoas muscle in the DS model was subjected to 23.2% greater tensile force than that in the normal model. These findings indicated that L4 anterior slippage and changes in lumbosacral-pelvic alignment affect the biomechanical response of muscles. In summary, the present work demonstrated a certain level of accuracy and validity of our models as well as the differences between the models. Alterations in spondylolisthesis and the accompanying overall imbalance in the spinopelvic complex result in increased loading response levels of the functional spinal units in DS patients, creating a vicious cycle that exacerbates the imbalance in the lumbosacral region. Therefore, clinicians are encouraged to propose specific exercises for the ventral muscles, such as the psoas group, to address spinopelvic imbalance and halt the progression of DS.

Discrete element method simulation of high-speed vehicle collisions with road barrier systems

AbstractThe behavior of road or perimeter protection barriers under vehicle impact are usually investigated based on crash tests and finite element (FE) numerical approaches, which are ether expensive or time-consuming. Several studies have proposed to reduce the computation time of the numerical analysis by substituting the complex FE models of vehicles using simplified mass–spring–damper system models. However, these models have drawbacks since consideration of different vehicle impact angles is difficult and they are unable to correctly simulate the risk of high-speed vehicle collision running over the barrier. In this paper, a new approach is proposed to simulate the collision of vehicles with barriers based on the discrete element method (DEM). Here, to save computation time only a handful of 3D non-spherical particles are used to represent the barrier and vehicle. These particles are generated based on the super-quadric function, which is capable of generating a variety of shapes needed for the model. The contact detection and evaluation are carried out based on discrete function representation of the particles with uniform sampling. The bond between two discrete elements is defined using a nonlinear cohesive beam model since the distance between the elements is relatively large. The simulation results obtained based on this approach are more accurate and complete than the simplified mass–spring models and computationally more efficient than the FE model.

Predicting maximum deflection of N-Edged thin-shelled hyperbolic-Paraboloid umbrella using machine learning techniques

Many thin-shelled hyperbolic paraboloid (hypar) umbrella forms have been built in the last 60 years as roof coverings. While the stresses in these forms remain relatively low, the deflections are a critical design parameter, and one that must be considered by architects and engineers in the conceptual design phase, meaning the design stage when the scale and form is given to the structure. To-date, there is no closed-form solution that can predict the maximum deflection of umbrellas due to their highly varying and complex geometry. The best option for predicting deflection is via finite element analysis, which is time-consuming for conceptual (preliminary) design purposes. In response, this paper uses machine learning via genetic programming (GP) and gene expression programming (GEP) to develop closed-form equations that predict the maximum corner deflection of N-edged hypar umbrellas – where N = 3, 4, 5, 6, 7, and 8. For a given a boundary condition and material, geometry is the most significant parameter influencing a shell's stiffness; thus, elastic finite element (FE) models use geometric properties as input variables (N, projected area, normalized rise, and shell thickness). The maximum corner deflection is recorded as an output and the FE analyses generate a large dataset of 53,754 results. It is observed that both GP and GEP can effectively parameterize the maximum deflection of N-edged hypar umbrellas, with GEP producing more concise, but relatively less accurate, equations than GP. While the formulations are trained using concrete material, a material factor multiplier transforms the results to other material properties within the assumption of elastic limits. The results of the study can be used to assist with conceptual design of hypar umbrellas and to validate complex FE models of hypar umbrellas. This research also illustrates the use of machine learning techniques as applied to the conceptual design of structures with highly varying geometries.

Analytical solutions for static longitudinal displacements of suspension bridges under a moving vertical concentrated load

The longitudinal displacement at the girder ends of long-span suspension bridges is a crucial issue that affects structural safety, durability, as well as traffic safety and ride comfort. The primary cause of these reciprocating displacements is the action of moving live loads, which induces quasi-static displacements in the longitudinal direction. This paper theoretically investigates the static longitudinal displacements of suspension bridges under a moving vertical concentrated load and elucidates the underlying deformation mechanisms. Considering geometrical nonlinearity, analytical equations are established for the longitudinal deformations of the main cable and stiffening girder under a vertical concentrated load. By analyzing the geometrical deformation conditions of the suspenders, the relationship between the longitudinal displacements of the stiffening girder and the main cable is derived. Due to the coupling between longitudinal and vertical displacements, the vertical displacement of the stiffening girder must be solved to obtain its longitudinal displacement. Based on deflection theory and considering the bending stiffness of the stiffening girder, this paper derives the vertical deformations of the stiffening girder for single-span suspension bridges and those with short continuous side spans under a vertical concentrated load, which is then used to calculate the longitudinal displacement. Finite element models are used to verify the accuracy of the analytical solutions. Differences between the proposed solutions and previous solutions neglecting the bending stiffness of the stiffening girder are compared and analyzed. The effects of neglecting the longitudinal displacement at the bridge tower top and the presence of short continuous side spans on the longitudinal displacement of stiffening girder are also investigated. The results demonstrate the high accuracy of the proposed analytical solution for the longitudinal displacement at the girder ends of suspension bridges. Importantly, the bending stiffness of the stiffening girder cannot be neglected in calculating the longitudinal displacement. The longitudinal displacement at the girder ends is primarily caused by the longitudinal deformation of the main cable, while the contribution from the flexural deformation of the girder is negligible. Furthermore, the longitudinal displacement at the bridge tower top has a negligible effect on the longitudinal displacement of the girder, and the presence of short continuous side spans is beneficial for reducing the longitudinal displacement of the stiffening girder. The proposed analytical solution method provides a rapid approach for calculating the static longitudinal displacement at the girder ends of suspension bridges under passing live loads and reveals the deformation mechanism. This is beneficial for preliminary design and structural optimization, as it avoids the complex finite element modeling and solution process.

Analytical solution of conductor tensile force in asymmetrical spans used in overhead power lines and substations with influence of tension insulators

Introduction. Designing electrical substations involves analyzing the horizontal tensile force in flexible tension conductors under varying temperatures. These temperature changes affect the conductor’s length and forces. Problem. Existing methods for calculating horizontal tensile force in conductors often focus on symmetric spans or require complex finite element modeling (FEM), which is impractical for routine substation design. Asymmetric spans with tension insulators present a more complex challenge that current solutions do not adequately address. Purpose. Universal analytical solution and algorithm for calculating the horizontal tensile forces in conductors in asymmetric spans with tension insulators used in power substations or short overhead power line spans. The solution is designed to be easily implementable in software without requiring complex tools or extensive FEM. Methodology. The methodology involves deriving an analytical solution based on the catenary curve formed by the conductor between attachment points at different heights. The analysis includes calculating the conductor’s length for a given tensile force and using a state change equation to determine forces under new temperature conditions. Validation is performed using FEM calculations. Results. The proposed solution was validated against FEM models with varying height differences (5 m and 15 m) and conductor temperatures (–30 °C, –5 °C, +80 °C). The results showed a minimal error (less than 0.15 %) between the analytical solution and FEM results, demonstrating high accuracy. Originality. This paper presents a novel analytical solution to the problem of calculating tensile forces in asymmetric spans with tension insulators. Unlike existing methods, our solution is straightforward and easily implementable in any programming language. Practical value. The solution is practical for routine design tasks in electrical substations or short overhead power lines. Especially in power substations, accurate tensile forces are needed not only for mechanical design and sag calculations but also for calculating the dynamic effects of short-circuit currents. References 23, tables 4, figures 3.

An efficient physics-guided Bayesian framework for predicting ground settlement profile during excavations in clay

Recently, the application of Bayesian updating to predict excavation-induced deformation has proven successful and improved prediction accuracy significantly. However, updating the ground settlement profile, which is crucial for determining potential damage to nearby infrastructures, has received limited attention. To address this, this paper proposes a physics-guided simplified model combined with a Bayesian updating framework to accurately predict the ground settlement profile. The advantage of this model is that it eliminates the need for complex finite element modeling and makes the updating framework user-friendly. Furthermore, the model is physically interpretable, which can provide valuable references for construction adjustments. The effectiveness of the proposed method is demonstrated through two field case studies, showing that it can yield satisfactory predictions for the settlement profile.

Parameter Identification of a Large-Scale Vibroacoustic Finite Element Model with a One-Dimensional Convolutional Neural Network

Uncertainties are significant in the early vibroacoustic development, e.g., of a car body, to prevent costly modifications close to the start of production. First, engineers must know which uncertain parameters are sensitive: Our previous work identified 170 uncertain parameters being sensitive out of a complex finite element model with 1,300 uncertain parameters – a parameter reduction of approximately 87%. Second, engineers aim to find reliable distributions of these sensitive input parameters for finite element simulations. Finding these distributions is very demanding in a large-scale vibroacoustic model with several connecting parameters, as research already acknowledges regarding simplified connections. In this paper, we address this challenge with neural networks. For this, we use data in the frequency domain. Due to the curse of dimensionality, it is difficult to determine the parameter set of 170 parameters with a neural network. Therefore, we examine the influence of the number of parameters on the performance of neural networks. Furthermore, we train a fully connected feed-forward neural network and compare this to a one-dimensional convolutional neural network. The latter exhibits a better performance. Finally, we show how to determine distributions of the analyzed parameters based on artificial measurement data. Due to this process, we can significantly improve our finite element simulations and show how to deal with the challenge of determining uncertain parameters in a large-scale vibroacoustic finite element model based on data in the frequency domain.

Real-time damage identification of hinge joints in multi-girder bridges using recursive least squares solution of the characteristic equation

Hinge joint damage is commonly observed in assembled multi-girder bridges, which may jeopardize their serviceability, safety, and sustainability. Timely detection of such damage is crucial for bridge management. Existing damage identification methods regarding hinge joints are either inconvenient in calculation or less sensitive to damage, and struggle with real-time monitoring. Therefore, to overcome these defects regarding assembled multi-girder bridges, this study proposes a real-time damage identification method that can directly estimate the stiffness of hinge joints without any complex finite element model. The proposed method is based on the recursive least squares solution of the characteristic equation of multiple beam systems, which is easy to implement and allows real-time evaluation. The effect of hinge joint damage on the dynamic characteristics of the bridge is quantified through numerical simulation, and the accuracy of the proposed method is verified. Finally, the proposed method is validated on an on-site measured bridge. The bridge consists of 16 girders with a length of 20 m. The results demonstrate that the proposed method practically achieves accurate identification of damage in the real bridge, indicating that the proposed method can be applied to the real-time monitoring of actual bridges to locate and assess hinge joint damage.

Low-velocity impact performance of integrally-3D printed continuous carbon fibre composite sandwich panels

Sandwich panels are heavily used in industrial sectors where specific mechanical properties are of utmost importance due to their high weight-stiffness ratio and energy absorption capacity. Lightweight sandwich cores with bio-inspired topologies have been used as an advanced alternative to conventional bulk cores to improve performance. Nowadays, sandwich structures comprised of core and skins are typically manufactured with two different processes and are afterwards adhesively joined together. Here, with a less time-consuming and more efficient assembly procedure in mind, an integrally 3D-printing strategy is proposed. This investigation analyses the low-velocity impact and quasi-static perforation performance of sandwich core designs inspired by the beetle's forewing trabecular structure. It was found that the core material was responsible of the rate dependence observed in the force–displacement curves. More complex finite element models than those employed here are necessary to capture all the fracture modes observed experimentally.

Deformation and Strength Characteristics of Marine Soft Soil Treated by Prefabricated Vertical Drain-Assisted Staged Riprap under Seawall Construction

Prefabricated vertical drains (PVDs) with staged riprap preloading have been widely used in soft soil ground improvement and embankment construction. However, ground treatment effectiveness evaluation is still a difficult problem due to multiple factors. Considering this, in situ monitoring and numerical simulation were conducted to study the deformation and strength characteristics of marine soft soil ground treated by PVD-assisted staged riprap under the Lingni Seawall construction in China. Monitoring and analysis of results showed that use of PVD-assisted staged riprap resulted in a good improvement effect. In particular, in the PVD-treated zone within 10 m in depth, corresponding to a half-length of the PVD, the average radial degree of consolidation reached up to 75–100%, and the soil strength increased significantly by 200–700%. Moreover, numerical simulation showed that the linear 1-dimensional drain element of PVD closely met the engineering accuracy requirements with good consistency with the monitoring data. Compared with a totally solid element model, the numbers of elements and nodes were reduced and the calculating efficiency and model accuracy were increased by using a PVD linear element, which provides a basis for building large complex finite element models.

Seismic Performance Assessment of the 18th Century Jesuit College in Dubrovnik’s Old City

The seismic performance assessment of heritage architecture presents many challenges due to the restrictions set forth by the conservation principles to protect the associated social and cultural values. These buildings are typically characterized by unreinforced masonry walls connected by tie-rods, vaults, and wooden floors. The era of construction dates to the time when seismic design regulations were largely unknown, making heritage structures potentially vulnerable to earthquake damage. This study presents the seismic performance assessment of the Jesuit College located in the southern part of the Old City of Dubrovnik. A series of field surveys were conducted to qualitatively examine the material composition and obtain geometrical details in part of the Croatian Science Foundation research project IP-2020-02-3531 entitled “Seismic Risk Assessment of Cultural Heritage in Croatia—SeisRICHerCRO”. The structural response is thoroughly investigated by means of a complex finite element model calibrated using the frequencies determined from ambient vibration measurements and material characteristics obtained from the literature review of representative cultural heritage buildings. The seismic performance is evaluated using linear static and response spectrum analysis in accordance with Eurocode 8 guidelines for the demand seismic action level. The numerical analysis indicates several structural components in the building exhibiting high shear stress concentration and exceeding the elastic tensile limit under the demand ground acceleration level. The assessment further reveals substantial out-of-plane bending of vulnerable wall components (identified by local mode shapes) at low peak ground acceleration levels. The stress concentration in numerous structural components leads to the identification of vulnerable zones where retrofitting measures are essentially required.

Combined ANN-FEM approach for spatial–temporal structural response prediction: Method and experimental validation

The prediction of the mechanical behavior and possible failure mechanisms of engineering systems is essential in the design process. It is a challenging task in view of numerous influencing parameters, various unavoidable uncertainties and time-consuming numerical analyses based on complex finite element models. Therefore, a combined hierarchical ANN-FEM approach is proposed in this contribution. By means of this approach, the advantages of both simulation methods are used to predict uncertain spatial–temporal structural responses with less effort and comparable accuracy. A non-linear stability analysis of a three-dimensional carbon fiber reinforced plastic (CFRP) structure is conducted to illustrate the efficiency of the combined ANN-FEM approach. The individual components space, time and uncertainty are investigated in detail regarding their influence on the ANN architecture and complexity. The numerical predictions of the buckling behavior and the material failure have been compared then to experimental values measured in a symmetric three-point bending test. A sensitivity analysis is finally conducted which clarifies the strong dependence of the outcomes for the ultimate limit state on the fiber volume content, the structural thicknesses and the stiffness in fiber direction.

Implicit parametric modal expansion method for single-layer reticulated shells based on generative adversarial network

Single-layer reticulated shells (SLRSs) are a prevalent form of roofing used in public buildings, including stadium and exhibition centers. Structural health monitoring (SHM) systems have been installed on SLRSs to obtain modal parameters for their design, assessment, and maintenance. However, modifying a complex finite element (FE) model with modal information acquired from a limited number of sensors can be challenging, especially for SLRSs. It is necessary to expand the measurement mode to obtain the complete mode before modifying the FE model. This paper proposes an implicit parametric modal expansion method for SLRSs based on generative adversarial network (GAN) to accomplish modal expansion without prior knowledge of the stiffness and mass of SLRSs. A GAN is trained to establish mapping relationship under different combinations of stiffness and mass of the SLRS. Then the expanded modals can be obtained through the trained GAN after obtaining measuring modals. The effectiveness of the proposed method is verified through numerical examples of spherical SLRSs. Using the method proposed in this paper, the accurate modal expansion results of numerical models can be obtained with a small number of measuring points. The results of the numerical examples indicate that the proposed method can achieve modal expansion through obtained measuring modals and trained GANs without prior knowledge stiffness and mass of SLRS.

Morphological and biomechanical analyses of the human healthy and glaucomatous aqueous outflow pathway: Imaging-to-modeling

Background and objectiveIntraocular pressure (IOP) is maintained via a dynamic balance between the production of aqueous humor and its drainage through the trabecular meshwork (TM), juxtacanalicular connective tissue (JCT), and Schlemm's canal (SC) endothelium of the conventional outflow pathway. Primary open angle glaucoma (POAG) is often associated with IOP elevation that occurs due to an abnormally high outflow resistance across the outflow pathway. Outflow tissues are viscoelastic and actively interact with aqueous humor dynamics through a two-way fluid-structure interaction coupling. While glaucoma affects the morphology and stiffness of the outflow tissues, their biomechanics and hydrodynamics in glaucoma eyes remain largely unknown. This research aims to develop an image-to-model method allowing the biomechanics and hydrodynamics of the conventional aqueous outflow pathway to be studied. MethodsWe used a combination of X-ray computed tomography and scanning electron microscopy to reconstruct high-fidelity, eye-specific, 3D microstructural finite element models of the healthy and glaucoma outflow tissues in cellularized and decellularized conditions. The viscoelastic TM/JCT/SC complex finite element models with embedded viscoelastic beam elements were subjected to a physiological IOP load boundary; the stresses/strains and the flow state were calculated using fluid-structure interaction and computational fluid dynamics. ResultsBased on the resultant hydrodynamics parameters across the outflow pathway, the primary site of outflow resistance in healthy eyes was in the JCT and immediate vicinity of the SC inner wall, while the majority of the outflow resistance in the glaucoma eyes occurred in the TM. The TM and JCT in the glaucoma eyes showed 1.32-fold and 1.13-fold larger beam thickness and smaller trabecular space size (2.24-fold and 1.50-fold) compared to the healthy eyes. ConclusionsCharacterizing the accurate morphology of the outflow tissues may significantly contribute to constructing more accurate, robust, and reliable models, that can eventually help to better understand the dynamic IOP regulation, hydrodynamics of the aqueous humor, and outflow resistance dynamic in the human eyes. This model demonstrates proof of concept for determining changes to outflow resistance in healthy and glaucomatous tissues and thus may be utilized in larger cohorts of donor tissues where disease specificity, race, age, and gender of the eye donors may be accounted for.

Evaluating numerical techniques with HPC systems in predicting vibratory responses of large finite element models

Finite element (FE) analyses have been widely used to support design optimizations in various disciplines to improve performance and possibly save material, cost, and schedule. As computational resources (i.e., CPU, memory, storage, and accelerator) are getting more powerful and cost effective, the complexity and model sizes of numerical models are greatly increasing to capture geometry details and features of the design. Correspondingly, the computational time for complex and large FE models are significantly growing. Traditional brute-force approach is not quickly enough to support design iterations. In this presentation, various numerical techniques are investigated and exercised in the DoD High Performance Computing systems to identify their advantages and limitations in conducting large FE analyses. Those techniques include utilization of GPGPU, direct versus iterative solvers, approximation of frequency sweep, etc. As a benchmark case, frequency response functions of a flat plate with viscoelastic material is exercised at the DoD HPC systems to examine the numerical techniques' impacts.

A Review of the Accuracy of Primal Assembly Model Order Reduction Techniques

Model order reduction (MOR) techniques have been used in structural dynamics for over sixty years as a quick and effective way to examine the dynamic behavior of complex finite element (FE) models. Various macroscopic phenomena arise from the physics and mechanics of the underlying microstructure, and MOR approaches can be employed in conjunction with the multiscale computational homogenization approach, which is deriving local macroscopic constitutive responses from underlying microstructure; to predict the dynamic behavior of heterogeneous macrostructures. The accuracy and efficiency of the most representative approaches from dynamic condensation, component mode synthesis (CMS), and general model reduction (GMR) methods are compared in this paper. The techniques considered are Guyan and the improved reduced system (IRS) from classical dynamic condensation, Craig-Bampton (CB) and enhanced Craig-Bampton (ECB) from CMS, IRS-based substructuring, GMR, and GMRPlus. All the substructuring methods employ primal assembly at the boundary interface of the substructures. The accuracy and computing efficiency of the techniques are compared in-depth using real-world engineering problems, and the effect of the number of substructures on the accuracy and computational cost is also examined.

A receptance based method for the calculation of nonlinear normal modes of large ordered structures with distributed localized nonlinearities

In recent years, the concept of nonlinear normal modes (NNMs) has gained interest for interpreting a broad range of nonlinear dynamic phenomena. Present study introduces a simple and efficient computational framework to compute NNMs of large order nonlinear structures overcoming difficulties associated with commonly used time-integration and discretization methods. In this paper, a Receptance Based Nonlinear Normal Mode Calculation Method (RBNM) is developed to determine the NNMs of large ordered realistic finite element models in frequency domain. Describing Function Method (DFM), which makes it possible to write the nonlinear internal forcing vector as a nonlinear displacement dependent stiffness matrix multiplied by displacement vector, is used to model the internal nonlinear forcing vector in frequency domain. A unique matrix manipulation based on dynamic stiffness and receptance concepts is used, as a result of which the number of governing nonlinear equations becomes independent from the total number of degrees of freedom of the model and it only depends on the number of degrees of freedom associated with the nonlinear elements. This brings a significant computational advantage over the classical reduced order modeling techniques. A simple 2-degree of freedom (DOF) system, the results of which are available in the literature, is used to verify the proposed method in determining NNMs. A 20-DOF lumped parameter system model and later a complex finite element model of a large structure are used to demonstrate the applicability of RBNM in determining NNMs of larger systems with several different types of nonlinear elements distributed among the degrees of freedom.

Time domain homogenisation of elastic and viscoelastic metamaterials

The mechanical behaviour of metamaterials typically depends on their microstructural configuration and composition, in addition to their relative density. The design of these materials requires extensive experiments or complex finite element models which tend to be numerically demanding. In order to understand, control and optimise the macroscopic mechanical behaviour, in this paper numerical homogenisation is applied to a simple square unit cell with a single inclusion using a combination of elastic and viscoelastic responses on the micro level. Through a systematic analysis of unit cell behaviour with increasingly complex microstructural configurations, it is shown how certain macroscale constitutive laws can be obtained in a controlled and controllable manner.

Influence of loading sequence on wind induced fatigue assessment of bolts in TV-tower connection block

Bolted connections are widely employed in structures like transmission poles, wind turbines, and television (TV) towers. The behaviour of bolted connections is often complex and plays a significant role in the overall dynamic characteristics of the structure. The goal of this work is to conduct a fatigue lifecycle assessment of such a bolted connection block of a 193 m tall TV tower, for which 205 days of real measurement data have been obtained from the installed monitoring devices. Based on the recorded data, the best-fit stochastic wind distribution for 50 years, the decisive wind action, and the locations to carry out the fatigue analysis have been decided. A 3D beam model of the entire tower is developed to extract the nodal forces corresponding to the connection block location under various mean wind speeds, which is later coupled with a detailed complex finite element model of the connection block, with over three million degrees of freedom, for acquiring stress histories on some pre-selected bolts. The random stress histories are analysed using the rainflow counting algorithm (RCA) and the damage is estimated using Palmgren-Miner's damage accumulation law. A modification is proposed to integrate the loading sequence effect into the RCA, which otherwise is ignored, and the differences between the two RCAs are investigated in terms of the accumulated damage.