Suitable Constitutive Model Research Articles

Numerical simulation of friction characteristics of bionic flexible contact surface of front axle rocker arm sleeve of car

Based on the finite element software ABAQUS, the friction process of the flexible friction pair of the front axle rocker bushing of a car with a convex structure similar to the mantis head is established.The finite element model of the process is constructed and its friction characteristics are verified. By selecting a suitable hyperelastic constitutive model and changing the size of the convex structure on the surface of the sleeve,The simulation analysis of the mechanical characteristics of the flexible friction pair in radial and torsional directions shows that the bionic convex hull design changes the maximum stress of the bushing when it is subjected to force.The force and strain position are adjusted to reduce the possibility of cracking of the rubber bushing; the contact friction force and friction coefficient of the bionic bushing surface are significantly reduced, and the type 2 modelThe drag reduction and wear resistance of the profiled surface are the best.

Enhancing Deep Excavation Optimization: Selection of an Appropriate Constitutive Model

To minimize the impact on nearby structures during deep excavations, choosing an appropriate soil constitutive model for analysis holds significant importance. This study aims to conduct a comparative analysis of various constitutive soil models—namely, the Mohr–Coulomb (MC) model, the hardening soil (HS) model, the hardening soil small strain (HSS) model, and the soft soil (SS) model—to identify the most suitable model for the lacustrine deposit. To implement these models, the soil’s index properties and mechanical behavior were evaluated from undisturbed soil samples. The numerical simulation and verification of these properties were carried out by comparing the laboratory test results with the outcome of the finite element method; the most suitable constitutive soil model for the soil was identified as the HSS model. Upon analyzing the wall deflection and ground settlement profiles obtained from respective constitutive models, it was observed that the HS and HSS models exhibit similar characteristics and are well-suited for analyzing typical lacustrine soil. In contrast, the MC and SS models yield overly optimistic results with lower wall deflection and ground settlement and fail to predict realistic soil behavior. As a result, this research highlights the significance of selecting the appropriate constitutive soil model and refining the parameters. This optimization process contributes significantly to the design of support systems, enhancing construction efficiency and ensuring overall safety in deep excavation projects.

Constitutive and numerical modelling for timber-metal connections under large deformations

Computational modelling of complex timber-metal connections undergoing large deformations is crucial for the design of safe and robust multi-storey timber structures. Accurate simulation through large deformations requires constitutive models that suitably capture the full post-elastic behaviour of materials. Post-elastic behaviour of timber is particularly challenging to model due to strong anisotropy and material non-linearity in the post-elastic regime. Efficient simulation of complex connections requires advanced numerical modelling techniques to expedite explicit solution in the finite element domain. In this study, a suitable constitutive model for ductile metal components through large deformations, including consideration of stress localisation and triaxiality post-necking, is described. Some existing constitutive models for timber are discussed, and new constitutive models capturing both ductile and brittle failure modes are presented. A new formulation of the Hoffmann yield criterion with isotropic hardening for explicit solution is presented, and new VUMAT user subroutines for explicit solution in ABAQUS for Hoffmann, Sandhaas, Gharib, Hill-Gharib and Hoffmann-Gharib models are developed and made available for the benefit of other researchers. A benchmarked numerical model incorporating advanced modelling techniques to improve computational efficiency without compromising accuracy is presented for a complex timber, aluminium and steel dowelled beam-column connection tested shear and moment dominated testing. The simulation results compare favourably with experimental results in the literature, demonstrating that the proposed constitutive models and numerical modelling techniques provide realistic predictions of behaviour, including failure mode, and thus have the potential to support the design of complex timber-metal connections through large deformations under quasi-static and dynamic loading.

Numerical analysis of soil arching effect in piles-reinforced airport foundation

The soil arching effect is the key mechanism for load transfer in pile-supported reinforced road (runway) foundations. To investigate the formation and evolution process of soil arching effect in the whole process of embankment filling and soft soil foundation consolidation, a three-dimensional hydro-mechanical coupled numerical model of pre-fabricated high-strength concrete (PHC) pile-reinforced soft soil runway foundation was established based on the foundation treatment project in Pudong Airport. The laws of variation of soil settlement, pore water pressure and pile soil stress were analysed, and the influence of pile spacing was considered. These data from both numerical simulation and field test indicate the soil arching effect in the foundation reinforced by PHC piles and preliminarily reveal the evolution of soil arching in the process of embankment filling and soft soil foundation consolidation. The preliminary results encourage the authors to continue this research to investigate the evolution of soil arching under aircraft dynamic loads through adding a more suitable constitutive model or subroutine in this numerical model.

Testing and modelling of aluminium cans for prismatic lithium-ion cells under crash loading

The mechanical performance of a deep-drawn AA3003-H14 aluminium can, which serves as an external shell for vehicle lithium-ion cells, was investigated in the present study. The experimental program included material testing at different locations on the cell, at different orientations, at various strain rates, and component testing. The material was found to be mildly anisotropic and significantly strain rate sensitive. A suitable constitutive model was proposed and validated against experiments to describe the material’s mechanical behaviour. Quasi-static and dynamic tests were performed on the cans and compared with finite element simulations to validate the proposed material model. The limitations of large-scale models suitable for industrial applications were assessed. The results show how this large-scale model can be built for an accurate prediction of the crash behaviour of aluminium cans for prismatic lithium-ion cells.

A damage constitutive model for consistent description of static and fatigue behaviors of ultra-high performance concrete containing coarse aggregate

A suitable constitutive model for describing the mechanical behaviors of ultra-high performance concrete (UHPC) under various loading histories plays a vital role in analyzing its structural performance. In this work, a consistent elastoplastic damage model is developed for UHPC containing coarse aggregate (UHPC-CA) subjected to static and fatigue loads, in which the driving and alleviating effects induced by the inclusions of coarse aggregate and steel fiber are considered. For damage evolution, based on the acting mechanism of the non-uniformity of stress wave propagation determined by the loading rate on the mechanical responses of UHPC-CA, the loading rate is skillfully integrated into the damage evolution rule to achieve the consistent description of mechanical behaviors of UHPC-CA under static and fatigue loading conditions. Regarding plasticity growth, an empirical plastic deformation model is adopted to improve the computational efficiency of structural nonlinear analysis. To verify the applicability of the proposed model, a user-defined UMAT subroutine is further developed for the subsequent numerical implementation. The comprehensive comparisons between the numerical predictions and independent experimental results at both the material level and structural level solidly demonstrate the capacity of the consistent model to capture the main features concerning the mechanical performance of UHPC-CA subjected to different loading paths.

Interpretable machine learning for selection of site-specific soil constitutive models and consolidation settlement analysis

Machine learning (ML) has achieved great breakthroughs in many fields, such as computer vision and speech recognition, and it also gains an increasing attention in geotechnical engineering. However, it is often criticized for a lack of interpretability. This study proposes an interpretable sparse dictionary learning (ISDL) approach for selection of suitable soil constitutive models (SCMs) and geotechnical consolidation analysis in a specific site. ISDL is inherently interpretable since it expresses prediction of geotechnical responses (e.g., consolidation settlement) as a weighted summation of many elementary datasets (i.e., dictionary atoms in ISDL). The dictionary atoms are constructed using numerical analyses (e.g., finite element model) with different candidate SCMs and parameters. Interpretability of ISDL is improved by a small number of non-trivial atoms (or SCMs) selected for model prediction using site-specific monitoring data and further enhanced by contribution ranking of the selected SCMs using a game theory-based approach. The proposed method is illustrated using a real reclamation project in Hong Kong, and it is shown to effectively select the most suitable constitutive models for the given site, quantify contributions of the selected models, and significantly improve settlement predictions with rigorously quantified prediction uncertainty, particularly at locations without monitoring or future time steps.

Mechanical and morphological characterization of the emphysematous lung tissue

Irreversible alveolar airspace enlargement is the main characteristic of pulmonary emphysema, which has been extensively studied using animal models. While the alterations in lung mechanics associated with these morphological changes have been documented in the literature, the study of the mechanical behavior of parenchymal tissue from emphysematous lungs has been poorly investigated. In this work, we characterize the mechanical and morphological properties of lung tissue in elastase-induced emphysema rat models under varying severity conditions. We analyze the non-linear tissue behavior using suitable hyperelastic constitutive models that enable to compare different non-linear responses in terms of hyperelastic material parameters. We further analyze the effect of the elastase dose on alveolar morphology and tissue material parameters and study their connection with respiratory-system mechanical parameters. Our results show that while the lung mechanical function is not significantly influenced by the elastase treatment, the tissue mechanical behavior and alveolar morphology are markedly affected by it. We further show a strong association between alveolar enlargement and tissue softening, not evidenced by respiratory-system compliance. Our findings highlight the importance of understanding tissue mechanics in emphysematous lungs, as changes in tissue properties could detect the early stages of emphysema remodeling. Statement of significanceGas exchange is vital for life and strongly relies on the mechanical function of the lungs. Pulmonary emphysema is a prevalent respiratory disease where alveolar walls are damaged, causing alveolar enlargement that induces harmful changes in the mechanical response of the lungs. In this work, we study how the mechanical properties of lung tissue change during emphysema. Our results from animal models show that tissue properties are more sensitive to alveolar enlargement due to emphysema than other mechanical properties that describe the function of the whole respiratory system.

In-plane behaviour of masonry infill walls with openings strengthened using textile reinforced mortar

A numerical study was carried out to simulate the in-plane behaviour of a 1:2.5 scaled one-storey one-bay masonry-infilled reinforced concrete (RC) frame retrofitted with textile-reinforced mortar (TRM). The study used ABAQUS finite element analysis (FEA) software and a three-dimensional (3-D) finite element method. Using a ductile design and details, the TRM-reinforced structure encountered in-plane displacement-control cyclic loads during the test. This study assesses how accurately a representative numerical model can replicate the results of an experimental test. Parametric research was conducted following the numerical model's calibration. To develop a suitable numerical model, suitable constitutive models based on the concrete damage plasticity (CDP) approach were used to characterize the nonlinear response of TRM, masonry infill, and concrete. The experimental findings, which aggrandize the response simulation, served as the basis for calibrating the models. Using a finite element framework and the simplified micro model technique, the masonry structure is simulated at the infill component level. The numerical model demonstrated accurately the ability to simulate the in-plane behaviour of the modified RC frame with infill walls, including its initial stiffness, deterioration, deformation-resisting ability, and failure patterns. Furthermore, a parametric study was conducted to determine the significance of the full-bond scenario between the RC frame infilled with masonry and the TRM considering: (1) the location of the strengthening material on the specimen and (2) the number of layers of the strengthening material. All retrofitted wall specimens showed a considerable improvement in in-plane performance; some features of the wall's behaviour were found to be strongly influenced by the parameters under examination. It can be observed that the specimen with two layers of TRM on both sides of the infill wall exhibit the maximum lateral load carrying capacity and maximum deflection resisting characteristics while the other retrofitted specimens controlled the deflection to some extent and significantly enhancing the load carrying capacities of the masonry system.

Experimental determination of hypoplastic parameters and cyclic numerical analysis for railway bridge backfills

AbstractLong integral bridges experience an enhanced cyclic soil structure interaction with their granular backfills, especially due to seasonal thermal loading. For numerical modelling of this interaction behaviour under cyclic loading, it is important to employ a suitable constitutive model and calibrate it thoroughly. However, up to the present, experimental data and calibrated soil models for this purpose with focus on typical well-graded coarse-grained bridge backfill materials are rarely available in the literature. Therefore, one aim of this paper is to present results of a comprehensive cyclic laboratory testing programme on highly compacted gravel backfill material. Based on this, a hypoplastic constitutive model with intergranular strain extension for small strain and cyclic behaviour is calibrated and evaluated against the experimental test data. The soil model’s abilities and limitations are discussed at element test level. In addition, cyclic FE analyses of an integral bridge are conducted with several hypoplastic parameter sets from the literature and compared to the calibrated gravel backfill material. The investigation highlights that poorly-graded sands show significantly smaller cyclic earth pressures compared to well-graded gravels intended for the backfilling of a bridge. The soil structure interaction behaviour is clearly governed by the general soil model stiffness, including the small strain stiffness.

Investigation of friction modeling on numerical Ti6Al4V cutting simulations

Friction significantly influences chip formation, thereby highlighting its modeling critical in numerical cutting simulations. Notably, issues like the underestimation of feed force in simulations are often attributed to inadequate friction models. Nevertheless, diverse conclusions in the literature regarding friction’s behavior complicate the accurate implementation of this input. Additionally, the enormous number of the available friction models and their varied calibration methods introduce further debates over which aspects of friction modeling should receive more focus. These controversies and deficiencies hinder progress in further understanding friction’s role in chip formation through numerical studies. Instead of proposing or calibrating new friction models, the current study, based on Ti6Al4V machining simulations, attempts to readdress the aforementioned controversies in a neutral stance by conducting sensitivity studies using a hybrid Smoothed Particle Hydrodynamics (SPH) - Finite Element Method (FEM) solver with Graphics Processing Units (GPU) acceleration, which is capable of efficiently executing high-resolution computations. The significant impact of friction particularly at the end of the tool-chip contact on the chip formation, physical contact states and process forces are highlighted. The behaviors of physical parameters including normal contact pressure, sliding velocity, and temperature-dependent friction models in the literature are also evaluated. Several aspects such as the shear flow stress limit, the relationship between friction and process forces, and the selection of different models are discussed. In conclusion, pragmatic recommendations for friction modeling and cutting simulation work are provided. On the one hand, the available complex physical parameter dependent friction models could not prove their necessity and should be approached cautiously. Instead, the constant Coulomb friction model without the shear stress limit, despite its simplicity, demonstrates effective and sufficient for a single set of metal cutting simulations. On the other hand, reliable on-site measurement techniques of the coefficient of friction (COF) at the tool-chip sliding contact area should be developed, with consideration of the contact length and the state of material flow. Combined with careful cutting edge preparation and suitable constitutive models, the overall accuracy of numerical cutting simulations including the feed force prediction is expected to be improved.

Mechanical insights into jawbone characteristics under chronic kidney disease: A comprehensive nanoindentation approach

The mechanical properties of the jawbone play a critical role in determining the successful integration of dental prostheses. Chronic kidney disease (CKD) has been identified to abnormally accelerate bone turnover rates. However, the impact of CKD on the mechanical characteristics of the jawbone has not been extensively studied. This study sought to evaluate the time-dependent viscoelastic behaviors of rat jawbones, particularly in the scenarios both with and without CKD. We hypothesized that CKD might compromise the bone's innate toughening mechanisms, potentially owing to the time-dependent viscoelasticity of the bone matrix proteins. The maxillary and mandibular bones of Wistar rats were subjected to nanoindentation and Raman micro-spectroscopy. Load-hold-displacement curves from the cortical regions were obtained via nanoindentation and were mathematically characterized using a suitable viscoelastic constitutive model. Raman micro-spectroscopy was employed to identify nuanced vibrational changes in local molecular structures induced by CKD. The time course of indenter penetration onto cortical bones during the holding stage (creep behavior) can be mathematically represented by a series arrangement of the Kelvin–Voigt bodies. This configuration dictates the overall viscoelastic response observed during nanoindentation tests. The CKD model exhibited a reduced extent of viscoelastic contributions, especially during the initial ramp loading phase in both the maxillary and mandibular cortical bones. The generalized Kelvin–Voigt model comprises 2 K–Voigt elements that signify an immediate short retardation time (τ1) and a subsequent prolonged retardation time (τ2), respectively. Notably, the mandibular CKD model led to an increase in the delayed τ2 alongside an increase in non-enzymatic collagen cross-linking. These suggest that, over time, CKD diminishes the bone's capability for supplementary energy absorption and dimensional recovery, thus heightening their susceptibility to fractures.

ELASTOPLASTIC CONSTITUTIVE MODEL AND MECHANICAL BEHAVIOR OF UNSATURATED LOESS

To address the issue of the absence of a suitable loess constitutive model in the study of seismic response in loess tunnels, the elastoplastic constitutive model of unsaturated loess was established by replacing the fixed yield surface with the yield surface (i.e., the variable loading surface). This model improves the algorithm of integration since the shape and position change in the stress space due to the continuous loading of unsaturated loess after yielding. In this study, the elastoplastic constitutive model was used in isotropic compression, drained triaxial compression, and undrained triaxial compression tests. The test results were compared with the Cambridge model. The results revealed that the elastoplastic constitutive model achieved a smooth transition between elasticity and plasticity and can effectively simulate soil behavior. The numerical experiment of triaxial drainage compression conformed to the theoretical concept of the boundary surface model and provided ideal simulation properties. From the undrained dynamic triaxial compression numerical test, it was seen that the constitutive model can describe the elastoplastic deformation in the yield surface and better reflect the cyclic strength softening and cyclic stiffness degradation of soil.

Multiple Parameters Determination Method of Hardening Soil Model Based on Particle Swarm Optimization

The utilization of numerical analytic techniques has become essential in evaluating the environmental consequences of excavation in foundation pits. The careful selection of suitable soil constitutive models has significant importance in this regard. The Hardening Soil (HS) model has become widely utilized in the numerical analysis of foundation pits among the several models considered. The essence of a constitutive model is in the identification and determination of its calculation parameters. The stress–strain curve is derived by conducting triaxial testing, utilizing the inherent properties of the particle swarm optimization (PSO) technique. The objective function entails quantifying the disparity between stress–strain curves obtained from various parameters and experimental curves while iteratively searching for five crucial parameters of soil‐hardening models: effective internal friction angle φ, effective cohesion, failure ratio Rf, stiffness level‐dependent power exponent, and standard triaxial‐drained test secant stiffness . The objective of this research is to create a computational software utilizing the Python programming language to execute PSO with the purpose of determining sets of five fundamental soil constitutive parameters. This research employs optimized parameters acquired from PSO to construct a numerical model for foundation pits and performs numerical computations. Accurate findings may be reached by comparing the measured deformation in the numerical simulation with that seen in actual foundation pits. The results demonstrate a high degree of consistency between the experimental curves and the five parameter combinations obtained through the PSO algorithm, with an error rate not exceeding 8.2%. Moreover, the optimized curves exhibit closer alignment with theoretical expectations. The settlement values calculated using a numerical model based on optimized parameters show only a 6.12% deviation from actual measurements while closely following the trend of the observed curve. This outcome has the potential to greatly alleviate the burden of conducting indoor tests and holds considerable practical value in engineering applications. The observable optimization impact of PSO also serves as evidence of its viability in improving soil constitutive parameters, providing new perspectives and sources of information for future progress in this domain.

A machine learning method of accelerating multiscale analysis for spatially varying microstructures

Multiscale computing for heterogeneous materials provides a powerful and fidelity approach to handling situations where a suitable macroscopic constitutive model is unavailable. However, there have been very few instances in the industrial sector where concurrent multiscale modeling techniques have been adopted, primarily because they require significant computational resources. In particular, when dealing with large numbers of representative volume elements (RVEs) with different microstructure morphologies throughout the macrostructure. In this paper, the novelty lies in providing an artificial neural network (ANN) model-based multiscale approach for accelerating multiscale analysis of the elliptical inclusion-reinforced composites with spatially varying microstructures, which give up the assumption of global periodicity. To tackle this challenge, firstly, a series of RVEs with different microstructure morphologies characterized by inclusion orientations and aspect ratios, under different load conditions, are simulated to generate training data. Second, the back propagation neural network (BPNN) is trained offline using data acquired from the RVE simulation for learning the underlying and possibly RVE morphologies. The trained BPNN replaces the complex microscopic mechanical solution problems over each macroscopic integration point at each iteration, to update the macroscopic stress-strain responses and it significantly reduces the computational cost of multiscale simulations. Then, the trained neural network is implemented on ABAQUS via user-defined materials (UMAT) and its effectiveness is verified by comparison with the classical multiscale finite element method (FE2) method. Finally, the outstanding computational capability of the proposed approach is further demonstrated through two numerical examples.

An electroplastic constitutive model of fcc metals and their alloys under high current density

The mechanical behavior of fcc (face center cubic) metals and their alloys such as copper-based and aluminum-based materials changes obviously under high current density, but there is a lack of suitable constitutive model to describe the electroplastic behavior of these materials, which limits the accuracy of the mechanical response prediction in applications, such as electromagnetic launch. In this paper, a novel nonlinear constitutive model for electroplastic behavior under the high current density of fcc metals and their alloys is proposed. The model proposed is based on the theory of dislocation evolution, energy transfer theory and electron transport theory and takes into account the effects of high current density on dislocation density, strain rate and resistivity. Considering the evolution of forward and reverse dislocations caused by pulsed current, the relationship between the evolution rate of reverse dislocation and strain is established. Due to the sensitivity of the electroplastic effect to strain rate, the strain rate under electric current is obtained by combining the theory of dislocation thermal activation and energy transfer. According to the concept of thermal resistance and dislocation resistance, the relationship between resistance and current density is derived. The quantitative results demonstrate that this model can well capture the flow stress softening under high current density (>3000 A/mm2) and the transient hardening after current removal because of the consideration of a more suitable strain rate and dislocation evolution. The critical current density that has a significant effect on the strain rate and the current density corresponding to the subsection point of the resistivity are quantitatively obtained. Especially, it is shown that the evolution rate of the reverse dislocation decreases nonlinearly with the increase of strain after the current is removed. These results will be helpful to study the mechanical behavior of the rail during electromagnetic launch and further optimize the design of electromagnetic launch device.

Extension of a shell‐like RVE model to represent transverse shear effects in textile reinforced composites

AbstractTextile reinforcements have long been used in shell‐like components like tires, belts, hoses and, in particular, air spring bellows. These bellows consist of a certain number of cords embedded in soft rubber, resulting in high membrane stiffness to absorb tensile forces and low resistance to changes in curvature. The embedded cords are produced by twisting multifilament yarns. Modelling and simulation of bellows is a challenging task. Thereby, the complex internal geometry, large deformations as well as the strongly anisotropic and nonlinear material behavior have to be taken into account in a computationally efficient manner. One approach is the application of multiscale analyses in conjunction with representative volume elements (RVE). Within this study, a through‐thickness RVE based on in‐plane periodic microstructures is applied. The local behavior of the cords is represented by an anisotropic constitutive model that regards directions and mechanical properties of filaments, which result from previous cord twisting simulations. In this contribution, an extension of the classical periodic boundary conditions (PBC) is presented, which considers curvature, pressure load, and, in particular, transverse shear. The RVE is used to simulate the stresses and strains in cord‐rubber composites under realistic load conditions. Moreover, it is employed for homogenizing the mechanical behavior and, thus, for developing a suitable constitutive model for shells.

Incorporating uncertainty in stress‐strain data acquisition: extended model‐free data‐driven identification

AbstractBased on the increasing ability to collect and store large amounts of data and information, data‐driven methods have recently gained importance in the context of computational mechanics. Compared to the traditional approach of defining a suitable constitutive model and fit the parameters to experimental data, these methods aim to capture complex material behavior without the assumption of a certain material formulation. Distinguished are model‐based data‐driven methods, leading to an approximation of the constitutive material description for example, by neural networks, and model‐free data‐driven methods. The approach of data‐driven computational mechanics (DDCM), introduced by Kirchdoerfer and Ortiz (2016), enables to circumvent any material modeling step by directly incorporating material data into the structural analysis. A basic prerequisite for both types of data‐driven methods is a large amount of data representing the material behavior, in solid mechanics consisting of stresses and strains. Obtaining these databases numerically by multiscale approaches is computationally expensive and requires the definition of lower scale models. In case of an experimental characterization, constitutive descriptions are generally required to compute the stress states corresponding to displacement fields, for example, identified by full‐field measurement techniques, such as digital image correlation (DIC). The method of data‐driven identification (DDI), introduced in Leygue et al. (2018) based on the principles of DDCM, enables the determination of detailed information about the constitutive behavior based on displacement fields and applied boundary conditions without a specific material model. Stresses corresponding to given strains are identified by iteratively clustering and enforcing equilibrium. The algorithm has shown to be applicable to synthetic as well as real data taking linear and non‐linear material behavior into account. Generalized polymorphic uncertainty models, resulting as a combination of aleatoric and epistemic uncertainty models, are utilized to take variability, imprecision, inaccuracy and incompleteness of data into account. The consideration of uncertain material properties by data‐driven simulation approaches leads to the requirement of data sets representing uncertain material behavior. In this contribution, different sources of uncertainty occurring within DDI of stress‐strain relations are addressed and an efficient method for the identification of data sets representing uncertain material behavior based on the concept of DDI is proposed. In order to demonstrate the developed methods, numerical examples are carried out.

Parameter Selection for Concrete Constitutive Models in Finite Element Analysis of Composite Columns

Concrete, as a complex and anisotropic material, poses challenges in accurately simulating its behavior in numerical simulations. This paper focuses on selecting an appropriate constitutive model for simulating the behavior of a steel–concrete composite column using finite element analysis under compression and push-out tests. Two models are analyzed and compared, namely, Drucker–Prager and concrete damage plasticity. The results demonstrate that the concrete damage plasticity model outperforms the Drucker–Prager model in all six test cases, indicating its superior accuracy in capturing the composite column’s behavior. This study enhances the reliability of numerical simulations for steel–concrete composite structures by choosing the most suitable constitutive model, parallel with extensive sensitivity analysis and model calibration. The findings emphasize the significance of meticulous model selection and precise parameter definition for achieving accurate predictions of concrete behavior. This research contributes to advancing the understanding and modeling of concrete’s intricate behavior in structural analyses.

Nonlinear elastic constitutive model of clayey sand reservoirs during depressurization exploitation of natural gas hydrate

Accurate evaluation of the mechanical response of hydrate-bearing reservoirs is a prerequisite for safe and efficient exploitation of natural gas hydrate resources. Therefore, it is necessary to develop a suitable constitutive model and to determine reasonable model parameters for hydrate-bearing sediments (HBSs) during exploitation. In this study, based on the strain-hardening behavior of clayey sand reservoirs published in the previous study, Duncan–Chang model was used as the basic model to establish constitutive models for HBSs during exploitation. The model parameters, initial elastic modulus and ultimate deviatoric stress, were determined by modifying existing formulas and establishing empirical formulas. Four nonlinear elastic constitutive models were proposed by combining the model parameters determined by different methods. Multi-stage and single-stage triaxial test data were used to verify the applicability of the model and determine the optimal model suitable for the sediments under study.