Specific Loading Conditions Research Articles

Multistable States and Snap-Through Instabilities in an Interconnected Dielectric Elastomer Actuators System

Abstract Snap-through instabilities in single and interconnected dielectric elastomer actuators have demonstrated their potential in enabling many functionalities such as large deformation, high-speed actuation, and enhanced flowrates in fluid pumps. However, the nonlinear nature of dielectric elastomers and the complex interplay of mechanics in interconnected inflated actuators, make the modeling of such systems challenging. In this paper, we present a methodology to analytically model the instabilities in a system of three interconnected homogeneous spherical dielectric elastomer actuators through graphical and numerical approaches. The simulation results reveal the presence of a locus of initial stable states that the interconnected actuators can achieve at zero voltage. In specific loading conditions, the system exhibits multiple stable states which can be cyclically transitioned between by selectively applying voltage to specific actuators. In other conditions, the system may undergo two successive instabilities when the voltage applied to a single actuator in the system is increased monotonically. These results retrieve existing experimental results theoretically for the first time and identify a new behavior of cascading instabilities in inflated dielectric elastomer actuators. We hope this work will pave the way for programmable design of multistable systems to unravel new capabilities in dielectric elastomer actuators and soft robotics.

Nonlocal damage evaluation of a sigmoid-based damage model for fibrous biological soft tissues.

The comprehension and modeling of the mechanical behavior of soft biological tissues are essential due to their clinical applications. This knowledge is essential for predicting tissue responses accurately and enhancing our ability to compute the behavior of biological structures and bio-prosthetic devices under specific loading conditions. The current research is centered on modeling the initiation and progression of soft tissues damage, which typically exhibit intricate anisotropic and nonlinear elastic characteristics. For this purpose, the following study presents a comparative analysis of the computational performance of two distinct damage modeling techniques. The first technique employs a well-established damage model, based on a piece-wise exponential damage function as proposed by Calvo et al. (Int J Numer Methods Eng 69:2036-2057, 2007. https://doi.org/10.1002/nme.1825 ). The second approach adopts a sigmoid function, as proposed by López-Campos et al. (Comput Methods Biomech Biomed Eng 23(6):213-223. https://doi.org/10.1080/10255842.2019.1710742 ). The aim of this study is to verify the validity of the López-Campos sigmoid-based damage model to be used in finite element simulation, the implementation of which is unknown. For this proposal, both models were implemented within a commercial Finite Element software package, and their responses to local and non-local damage algorithms were assessed in depth through two standard benchmark tests: a plate with a hole and a ball burst. The results of this study indicate that, for a wide range of cases, such as in-plane stresses, out-plane stresses, stress concentration and contact, all over large displacement conditions, the López-Campos damage model shows a good response to non-local algorithms achieving mesh independence and convergence in all these cases. The results obtained are in line with those obtained for the Calvo's damage model, showing, in addition, larger deformations under in-plane stress and stress concentration conditions and a lower number of iterations under out-plane stress and contact conditions. Consequently, the López-Campos' damage model emerges as a valuable and useful tool in the field of mechanical damage research in biological systems.

Fatigue reliability assessment of load‐carrying cruciform welded joints with undercuts and misalignments

AbstractThe additional local stress concentration caused by undercut and misaligned defects could lead to lower fatigue strength of welded joints. The paper aims to investigate the effects of undercuts and misalignments on fatigue performance and reliability of Load‐carrying Cruciform Welded Joint (LCWJ) quantitatively by probabilistic statistics theory and fracture mechanics theory. Firstly, the geometrical characteristics of undercut and misalignment are summarized from the literature and our experiments. Subsequently, the probabilistic distributions of material fracture properties, the configurations of geometries, and flaws were evaluated under specific loading conditions. The fatigue strengths are further estimated by the probabilistic reliability theory by combining the actual fatigue data. The results demonstrate a clear disparity of fatigue crack growth threshold and resistances for the tested data of base metal and weldment. The level of defects determines the interval of fatigue life, and the larger the dispersion accompanying earlier fatigue failure occurs.

Multi-view information fusion using multi-view variational autoencoder to predict proximal femoral fracture load.

Hip fracture occurs when an applied force exceeds the force that the proximal femur can support (the fracture load or "strength") and can have devastating consequences with poor functional outcomes. Proximal femoral strengths for specific loading conditions can be computed by subject-specific finite element analysis (FEA) using quantitative computerized tomography (QCT) images. However, the radiation and availability of QCT limit its clinical usability. Alternative low-dose and widely available measurements, such as dual energy X-ray absorptiometry (DXA) and genetic factors, would be preferable for bone strength assessment. The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion. We developed new models using multi-view variational autoencoder (MVAE) for feature representation learning and a product of expert (PoE) model for multi-view information fusion. We applied the proposed models to an in-house Louisiana Osteoporosis Study (LOS) cohort with 931 male subjects, including 345 African Americans and 586 Caucasians. We performed genome-wide association studies (GWAS) to select 256 genetic variants with the lowest p-values for each proximal femoral strength and integrated whole genome sequence (WGS) features and DXA-derived imaging features to predict proximal femoral strength. The best prediction model for fall fracture load was acquired by integrating WGS features and DXA-derived imaging features. The designed models achieved the mean absolute percentage error of 18.04%, 6.84% and 7.95% for predicting proximal femoral fracture loads using linear models of fall loading, nonlinear models of fall loading, and nonlinear models of stance loading, respectively. The proposed models are capable of predicting proximal femoral strength using WGS features and DXA-derived imaging features. Though this tool is not a substitute for predicting FEA using QCT images, it would make improved assessment of hip fracture risk more widely available while avoiding the increased radiation exposure from QCT.

A Body-frame Beam Constraint Model

Compliant Mechanisms (CMs) have presented their inherently advantageous properties since the nature of CMs is to utilize elastic deformation of the built-in elementary flexible members to transfer motion, force and energy. To predict the performances of CMs and optimize their designs, modeling CMs turns out to be a major concern in this field, particularly, such as high-precision flexure-based CMs. Reported in the literature, the well-known Beam Constraint Model (BCM) expressed in Cartesian coordinate system serves as an effective tool to model the deflection of flexures. Inspired by BCM, in this paper, we take one step further to propose a Body-frame Beam Constraint Model (BBCM) to handle buckling and intermediate-range deflections under typical beam-end loading conditions. Numerical and analytical analysis also proves that BBCM can also provide reliable accuracy in complex loading conditions and complex beam geometries within small-to-intermediate-range deflections and may accurately characterize large deflections under some specific loading conditions as well.

Numerical Investigation of the Evolving Inelastic Deformation Path of a Solder Ball Joint under Various Loading Conditions

Solder joints of ball grid arrays (BGA) have been widely used to connect electronic components to printed circuit boards (PCBs) and are often subjected to mechanical stress. Several studies have been conducted on the mechanical reliability of solder joints. While these studies have been useful in the industry, detailed studies on how the inelastic deformation path of the solder ball joints evolves under specific loading conditions have not been sufficiently reported. This study aims to understand how the inelastic deformation path evolves when a solder joint is subjected to a constant external force by utilizing the theory of mechanics. It has also been found that the mechanical failure is strongly influenced by the evolution history of the deformation modes in materials. For this study, an elastoplastic constitutive model and a ductile fracture criterion were implemented into the vectorized user-defined material (VUMAT) subroutine of the ABAQUS program for finite element (FE) analysis. With the model, the evolution of the inelastic deformation path of a single solder ball under different loading conditions was numerically analyzed. Three loadings (shear, compression, and bending) were chosen as the basic loading conditions. In addition, combinations of the basic loadings resulted in three dual loadings and one complex loading. The simulation results showed that the shear and bending caused the fracture for both single and dual loadings, but when combined with compression, the fracture was suppressed. The results indicate that fracture is not solely determined by the magnitude of equivalent plastic strain but also by the evolution of inelastic deformation mode. This research offers an improved understanding of the significance of the inelastic deformation path and fracture.

A Comprehensive Interturn Fault Severity Diagnosis Method for Permanent Magnet Synchronous Motors Based on Transformer Neural Networks

This paper proposes a novel deep learning (DL) based inter-turn short circuit fault (ISCF) severity diagnosis method using the transformer neural network (TNN). The input features are the currents in alpha-beta reference frame, while the outputs are the number of shorted turns and short circuit (SC) current amplitude. By only monitoring the stator currents, this method provides a comprehensive overview of the fault severity. The proposed TNN creates multiple representations of the input using the multi-head attention (MHA) mechanism. This allows the network to focus on specific parts of the input signals and create an accurate estimate. The dataset was collected using a motor with re-wound windings to simulate stator ISCF, which was operated under nine specific load and speed conditions and three numbers of shorted turns. Both the shorted turns and SC current amplitude estimations on the test dataset have higher than 96% accuracy. A comparison of several methods is presented based on various criteria. Based on the comparison and considering the achieved accuracy, the proposed method shows high potential in terms of comprehensiveness, accuracy, practicability, and cost.

Step and scarf joint elastic and failure behavior comparison under tensile and flexural loading

Step and scarf joints are the two most commonly used joint types in composite laminate bonding, offering distinct characteristics and behavior in response to specific loading conditions. In order to gain a comprehensive understanding of the mechanical behavior step and scarf joints, a comparative study of adhesive bonded step and scarf joint carbon fiber reinforced composite laminate under tensile and flexural loading condition was performed. The test specimens were fabricated with carbon fiber reinforced composite laminate. The step and scarf joints were precisely manufactured using a precise milling machine, and the joints were bonded with an epoxy adhesive with controlled bondline thickness. To assess the behavior of the bonded joint structure under various loading scenarios, both tensile and four-point bending flexural tests were performed. Strain measurement during these tests was carried out using digital image correlation (DIC) technology. The step joint showed multiple sequential bondline crack propagations while the scarf joint experienced a single catastrophic failure. The test result showed that the step joint retained 10% and the scarf joint retained 32% of tensile strength compared to the no-joint test specimen. Also, the step joint retained 13% and the scarf joint retained 44% of flexural strength compared to the no-joint test specimen. As a result, the scarf joint had significantly higher ultimate tensile strength, tensile modulus, and tensile strain at failure. The scarf joint also showed higher ultimate flexural strength and flexural modulus compared to the step joint.

Experimental investigation on fatigue life and tensile strength of carbon fiber-reinforced PLA composites based on fused deposition modeling

Fused deposition modeling (FDM) is a widely used additive manufacturing (AM) method that offers great flexibility in fabricating complex geometries without requiring expensive equipment. However, compared to other manufacturing methods, FDM-produced parts generally exhibit lower strength and fatigue life. To overcome this limitation, researchers have explored the use of fibers and reinforcements to enhance the mechanical properties of FDM parts. Nevertheless, the performance of FDM-produced parts can be significantly affected by various manufacturing parameters, including infill density, which is a key factor in balancing time and cost. In this study, the tensile strength and fatigue life of carbon fiber-reinforced polylactic acid (PLA) composites produced by FDM were investigated by varying the infill density (50 and 75%) and raster angle (0°, 45°, and 90°). The effects of 100% filling density, raster width, and nozzle diameter on mechanical properties were also examined. The experimental results demonstrated that increasing the infill density and decreasing the raster angle can enhance the tensile strength, although the fatigue behavior was found to be more complex and dependent on the infill density. The optimal parameters for producing FDM parts with improved mechanical properties were identified based on the analysis of the tensile strength and fatigue life data. This research has yielded significant findings concerning the diverse fatigue behavior associated with the raster angle at different infill densities. Specifically, noteworthy observations reveal that a raster angle of 45 degrees at 50% infill density, and a raster angle of 0 degrees at 75% infill density, exhibited the most prolonged fatigue life. This outcome can be ascribed to the specific loading conditions and the inherent strength of the sediment layer at the critical point of stress concentration.

Development and characterization of Cu-Ni- Al2O3 surface composite developed by friction stir process technique

In this study, a copper-based composite reinforced with Al2O3 and Ni with different weight percent was produced using the Friction Stir Processing (FSP) technique. The macrostructure and microstructure of the composite were characterized to understand the arrangement and distribution of the reinforcement particles. The wettability of the composite was evaluated to determine its ability of reinforcement to interact with the matrix material. Uniform distribution and fair interaction of Al2O3 and Ni particles were found in the Cu-based matrix material Tensile and hardness tests were conducted to measure the mechanical properties of the composite and assess its strength and resistance to deformation. The hardness and tensile strength of copper after the addition of 5 % Al2O3 and 2 % Ni was improved by about 43.33 % and 50.45 % respectively. The number of grains was found to be about 2740.07 per square inch for Cu/5 % Al2O3/2 % Ni processed composite with FSP per square inch at 500 magnifications. Additionally, wear analysis was carried out to investigate the wear behavior of the composite under specific loading conditions. XRD analysis was performed to examine the crystallographic behavior and integrity of the composite. The identified phases of the Cu/Al2O3/Ni composite after XRD analysis were Cu, Al2O3, Ni, and Cu2O. The results obtained from these various analyses provided valuable insights into the structural, mechanical, and wettability properties of the copper-based composite reinforced with Al2O3 and Ni, fabricated using the FSP technique.

Quantifying narrowing partition thickness in a vertical pneumatic separation channel for soybean seed cleaning

The paper highlights that the study of the soybean seed separation processes in a vertical deep aspirating channel contributes to the improvement of technical and economic indicators in grain cleaning equipment. (Research purpose) The research aims to substantiate the thickness of narrowing partitions in the vertical deep aspirating channel. (Materials and methods) A prototype of a vertical deep aspirating channel with three sections of varying height, was used for cleaning soybean seeds. The optimal thickness of the narrowing partitions in the channel has been justified. Impurity extraction completeness and seed separation efficiency within a vertical aspirating channel were assessed for soybean seed cleaning under maximum specific grain load conditions. (Results and discussion) The following parameters have been determined: the optimal thickness for the narrowing partitions is 70 millimeters under a maximum specific grain load of 5 kilograms per square centimeter per hour. Seed losses do not exceed 3 percent in the aspirating channel with narrowing partitions, with impurity extraction completeness of 74 percent for the «Waste» fraction. The efficiency of the separation process stands at 71 percent, and the purity level of the «Seeds» fraction reaches 81 percent in a single pass during the preliminary cleaning stage. (Conclusions) It has been established that the use of narrowing partitions in a vertical aspirating channel during soybean seed cleaning leads to an increase in the specific grain load up to 5 kilograms per square centimeter per hour, compared to 2 kilograms per square centimeter per hour achieved by traditional pneumatic separation channels. The proposed technical solution reduces soybean seed losses to 3 percent (compared to the initial requirements of no more than 10 percent) in a single pass and reduces machine power consumption from 4.5 to 2.25 kilowatt-hours.

Path-driven shell lattices designed for continuous fiber composite 3D printing

3D printing of continuous fiber reinforced composites (CFRC) significantly strengthens the mechanical properties of the printed parts. However, design for CFRC 3D printing coupled with continuous path planning is challenging and still underdeveloped, especially for the novel lattice structures. Hence, this work develops a shell lattice design method and a series of 3D shell lattices for CFRC 3D printing. First, the feasibility of fabricating existing shell lattices like triply periodic minimal surface (TPMS) by CFRC 3D printing is discussed. Then, a path-driven shell lattice (PDSL) design method for CFRC 3D printing is presented. The proposed PDSL is constructed from a stack of multi-directional continuous paths defined by a novel periodic function. Both the periodicity and path continuity are guaranteed to enable the continuous fiber deposition. The mechanical properties of the PDSL are optimized with the inverse homogenization method. The surface mean curvatures of the PDSL are optimized with the Surface Evolver to realize a minimal surface with close-to-zero mean curvatures. Finally, both the PDSLs and TPMSs are fabricated by CFRC 3D printing and evaluated by the three-point bending test. The test result demonstrates that the proposed PDSLs realize better mechanical performance under the specific loading condition.

Multi-Objective Parametric Shape Optimisation of Body-Centred Cubic Lattice Structures for Additive Manufacturing

There has been significant interest in additively manufactured lattice structures in recent years due to their enhanced mechanical and multi-physics properties, making them suitable candidates for various applications. This study presents a multi-parameter implicit equation model for designing body-centred cubic (BCC) lattice structures. The model is used in conjunction with a multi-objective genetic algorithm (MOGA) approach to maximise the stiffness of the BCC lattice structure while minimising von-Mises stress within the structure under a specific loading condition. The selected design from the MOGA at a specific lattice density is compared with the classical BCC lattice structure and the designs generated by a single-objective genetic algorithm, which focuses on maximising stiffness or minimising von-Mises stress alone. By conducting a finite element analysis on the optimised samples and performing mechanical testing on the corresponding 3D-printed specimens, it was observed that the optimised lattice structures exhibited a substantial improvement in mechanical performance compared to the classical BCC model. The suitability of multi-objective and single-objective optimisation approaches for designing lattice structures was further investigated by comparing the corresponding designs in terms of their stiffness and maximum von-Mises stress values. The results from the numerical analysis and experimental testing demonstrate the significance of the application of an appropriate optimisation strategy for designing lattice structures for additive manufacturing.

Experimental and numerical analysis of shape memory sinusoidal lattice structure: Optimization through fusing an artificial neural network to a genetic algorithm

Shape memory polymers are smart materials that can “remember” their original shape and return to it when exposed to certain stimuli, such as heat, light, or a change in pH. This research investigates the compressive nonlinear response of a sinusoidal shape memory unit cell made of PLA. Different architectures with diverse thicknesses are optimized through a finite element analysis, and the values of absorbed energy, dissipated energy, and peak force are extracted. The obtained data is subsequently used to train a judiciously structured artificial neural network. Three algorithms, including Levenberg-Marquardt, Bayesian regularization, and scaled conjugate gradient backpropagation, are utilized for training the neural network. The function obtained is employed to formulate the objective function to be minimized- (or maximized), and the optimal geometric dimensions are extracted. In the experimental part, the sinusoidal cell is made using a 3D printer and PLA material, and a quasi-static test is performed. After each quasi-static test, the structure is exposed to heat, and thanks to its shape memory properties, it returns to its original shape. This cycle is repeated up to four times. Testing results showed that the proposed sinusoidal structure possessed an attractive mechanical behaviour relevant to the specific geometric parameters and loading conditions. It was observed that the amount of absorbed energy and the maximum forces decreased in each cycle compared to the previous cycle. The experimental results demonstrate that the absorbed energy by the sinusoidal cell decreased by 4.7% in the second loading, 12.98% in the third loading, and 33.7% in the fourth loading. The results reveal that the reduction in the peak force of structure is more pronounced compared to the decrease in absorbed energy under cyclic loading–unloading. Based on the obtained results, it can be concluded that the proposed structure can be used as a suitable energy absorber with the ability to recover the original shape and maintain the mechanical properties up to several cycles of loading.

Numerical fatigue modeling and simulation of interacting surface cracks in offshore wind structural connections

The structural integrity of marine structures is significantly influenced in many practical applications by their fatigue behavior, especially when dealing with dynamically sensitive structural systems, e.g., offshore wind substructures. The propagation of cracks found in structural components can be estimated through fracture mechanics-based methods, in which the crack growth under cyclic loading is mainly driven by the stress intensity factor (SIF). To simplify the computation of the SIF, closed-form solutions are often suggested in industrial standards, yet their applicability is limited to specific geometries and loading conditions. Overcoming the aforementioned constraints, we propose here a general methodology for numerically simulating the SIF and growth of multiple cracks by computing the SIF of adjacent cracks in an integrated finite element analysis, in which interaction effects are implicitly considered. In our proposed method, the coalescence of bordering cracks is also adequately modeled and fatigue failure is defined based on fracture mechanics principles. With the objective of enabling an efficient SIF computation, we also provide the necessary modeling details for the appropriate implementation of the corresponding finite element analysis. The proposed methodology is then tested and validated in a finite thickness plate under cyclic loading setting, whereas in a more practical case study, we investigate the fatigue analysis of interacting surface cracks in an offshore wind structural connection. The results emphasize the importance of considering interaction effects and crack coalescence when simulating the fatigue evolution of structural details in practical applications, and within the study, specific insights are additionally provided for the fatigue analysis of offshore wind structural components. With respect to the investigated fatigue failure criteria, the results show that a through-thickness limit state might yield slightly conservative fatigue life estimates compared to the fatigue limit that results when failure is defined based on the material fracture toughness.

Response of Topological Soliton lattice structures subjected to dynamic compression and blast loading

A novel topological soliton lattice (TSL) unit cell with fascinating behavioral characteristics is developed. Lattice structure as well as the sandwich composite panels are both constructed. Numerical simulation is utilized to simulate the dynamic compression and blast behavior of the proposed structures considering the rate-dependent properties, elastoplastic response and nonlinear contact. Mooney–Rivlin (MR) hyperelastic constitutive model and Generalized Maxwell model are used to model the TSL structure, and Johnson–Cook material model is implemented to model the plate material. The numerical model is validated by comparing with the experimental results. A series of parametric studies are conducted to gain insight into the effects of loading velocity, number of core layers, equivalent TNT loads and panel thickness on the dynamic mechanical behavior of the TSL lattice and sandwich structures. Testing results indicated that the proposed TSL lattice possessed an attractive mechanical behavior, which was relevant to the specific geometric parameters and loading conditions. The proposed novel lattice would expand the design space for the development of future materials with customized response characteristics.

Abrasive wear protection in material handling: Mechanism-based combination of lab-experiments for optimal material selection

Material processing of loose goods can be found ubiquitously in heavy industries such as steel production. In transportation, relocation or other processing routines of raw materials severe and manifold abrasive loads attack wear protection materials. As often plant engineers are not aware of the prevailing loads and wear mechanisms, the material choice might be suboptimal. Therefore, the objectives of this work were to identify wear mechanisms for several distinct applications and evaluate the suitability of applied wear solutions. Various forms of abrasive and impact-abrasive wear were simulated in lab experiments. A variation of ten common wear protection materials consisting of martensitic steels and hardfacings was applied in standard abrasion testing, in adapted high stress situations as well as in impact-abrasion testing. For the latter six original abrasives from field applications were utilized and their severity classified. Based on the wear results an application-oriented combination of the quantitative results was used for a qualified selection map of most favorable wear protection solutions for specific load conditions representative of certain wear components. By these selection maps a knowledge-based choice for wear protection solutions is provided, enabling wear resistance optimization and thereby increasing sustainability in material handling.

An experimental and numerical study of the mechanical response of 3D printed PLA/CB polymers

Fused Filament Fabrication is an Additive Manufacturing method that can produce bespoke components due to the high number of printing parameters available. Each of them plays a significant role in the final mechanical properties of the 3D printed device. This study aimed to uncouple the role of the mesostructure and crystallinity in the final mechanical performance of carbon black/PLA 3D printed samples as a function of the printing parameters. A thermodynamic model was developed to determine the influence of printing parameters, such as nozzle diameter and layer height, in the final crystallinity. Specimens were mechanically tested under uniaxial tensile loads to determine the main deformation and failure mechanisms and results showed that samples were strongly influenced by the printing direction. Furthermore, the nozzle diameter played a significant role in the mesostructure and failure mechanisms, resulting in large differences in ductility for samples printed at raster direction 45°. It was also found that the layer height had a strong influence on the temperature profile and the resulting crystallinity. The importance of crystallinity over porosity to improve the ductility of the material is a substantial contribution to the current state of the art. This work provides the basic fundamentals to manufacturing 3D printed components with tailored mechanical properties for specific loading conditions.

Multiscale identification and NTFA reduction of the elasto-viscoplastic polycrystalline behaviour of uranium dioxide (UO2) for wide range of loading conditions

This numerical study presents a micromechanical modelling of the behaviour of uranium dioxide fuel (UO2), a polycrystalline ceramic used in nuclear power plants, for loading condition typical of a reactivity initiated accident (RIA). Above a specific temperature, UO2 has an elasto-viscoplastic behaviour with strain hardening depending on both temperature and macroscopic strain rate (T,ε¯˙).In a first step, via a full-field approach, an inverse identification of the local single crystal evolution law is performed based on experimental data obtained at the macroscopic scale [4,5]. Beyond the macroscopic behaviour of the fuel pellet, it is sometimes necessary to go down in scale to study local phenomena. A first approach would be to perform a Finite Element Method squared to two (FEM2) resolution [37]. It consists to solve a thermomechanical problem on a first mesh defined at the pellet scale where at each integration point is solved another thermomechanical problem on a Representative Volume Element. The full-field approach guarantees access to the local field at the expense of relatively high computational time. It is not conceivable within industrial codes.In a second step it appeared necessary to replace the second full-field resolution by a model reduction method based on the Nonuniform Transformation Field Analysis (NTFA) approach. This method allows access to macroscopic quantities and local fields while drastically reducing the computational time. The NTFA model [21] with tangent second order (TSO) approximation [24,21] is developed and applied to the problem at hand. Two decompositions of the hardening variable are studied. It is taken as in the reference [21], as uniform per grain or taken as decomposed, like modes associated with the viscoplastic strain tensor. Then, work is done to integrate the specific loading conditions, i.e. temperatures and strain rates of the RIA, into the NTFA model while keeping the number of internal variables as low as possible. Finally, the results from the experimental, full-field and NTFA TSO models are compared. It is checked that the numerical results are not deteriorated either macroscopically or locally at the macroscopic and local scales for uniaxial and triaxial loading.

Seismic performance of elliptical FRP-concrete-steel tubular columns under combined axial load and reversed lateral load

By combining FRP composites with both steel and concrete, double-skin tubular columns (i.e., DSTCs) with a hollow core are a novel structural member to be used as bridge piers or other columns in harsh environments. Up to now, DSTCs with circular or square sections (i.e., C-DSTCs or S-DSTCs) have been investigated extensively, while DSTCs with an elliptical section (i.e., E-DSTCs) are rarely studied. E-DSTCs are composed of two concentric elliptical tubes (i.e., the external FRP tube and the internal steel tube) and a sandwiched concrete layer. E-DSTCs can be designed with two distinct bending stiffness with respect to the two axes of symmetry. Similar to C-DSTCs, E-DSTCs have an FRP tube with a continuously curved circumference, thus effectively confining the concrete layer. To extend the existing research, this paper tested six large E-DSTCs under combined axial load and reversed lateral load to investigate the effect of elliptical aspect ratio. The testing parameters also included the direction of reversed lateral load and the FRP thickness. Experimental results showed that, E-DSTCs performed with rounded hysteresis loops and remarkable ductility even for the specimen with a large aspect ratio (i.e., for the elliptical aspect ratio from 1.0 to 2.0, the ductility index increased monotonically from 6.50 to 7.75); a thicker FRP tube led to marginally higher peak load but noticeably better ductility (i.e., the specimen with 2.10 mm FRP had an average peak load of 77.65 kN and a ductility index of 7.14, while the corresponding specimen with 1.05 mm had an average peak load of 77.35 kN and a ductility index of 6.29); as expected, the specimen bending around its strong axis had much superior ductility than the companion specimen bending around its weak axis. A numerical column model was established based on OpenSees to simulate the hysteretic behavior of E-DSTCs, and a parametric study was conducted to assess the influences of FRP thickness, concrete strength, axial load ratio, steel tube thickness, void ratio as well as elliptical aspect ratio. In practical engineering design, it was recommended that: (a) the elliptical aspect ratio as well as other key parameters (e.g., the FRP thickness, the steel tube thickness, the area void ratio) should be optimized based on specific loading conditions; (b) to make more effective usage of FRP composites, the FRP tube thickness should be optimized for different height regions of the column according to the moment gradient caused by the reversed lateral load.