Secondary Development Of ABAQUS Research Articles

Effect of dynamic constitutive differences in materials on the impact performance of CFST via secondary development of ABAQUS

To investigate the effect and adaptability of dynamic constitutive models on the impact performance of concrete-filled steel tubes (CFST), a numerical study on the dynamic properties of CFST under impact loading is conducted. By analyzing the impact response, including impact force, mid-span displacement, energy absorption, and mid-span bending moment, the effect of dynamic constitutive differences in materials on the impact performance of CFST is assessed quantitatively. Moreover, the HJC dynamic model was developed and validated by secondary development in ABAQUS. The findings show that the material model without considering strain rate effects would significantly underestimate the impact performance of CFST members. In contrast, the impact resistance of CFST is overestimated by using the J-C model and the C-S model with biased elastic conditions. The results obtained using the DIFavg model are most in agreement with the results of the actual model. The impact resistance of CFST is only slightly influenced by variations in the dynamic constitutive model of concrete. The impact performance of CFST is accurately predicted by using the VUMAT subroutine to program the HJC dynamic constitutive model.

Effect of void defects on mechanical behavior and failure features of C/C honeycomb structure

The combination of honeycomb structure and carbon/carbon (C/C) composites offers unique high load-bearing and light-weight advantages in satellite-bearing platforms. However, the defects generated by the imperfect preparation process are inevitable. This paper employs the chemical vapor infiltration (CVI) technique to fabricate novel C/C honeycomb structures and considers the presence of internal void defects. Based on micro-computerized tomography (μ-CT) images, the void distribution and porosity as well as the micro-structure characteristics are acquired. Meso-scale representative volume element (RVE) models is established to predict the performance of honeycomb wall material. A secondary development of ABAQUS is performed to establish a model of honeycomb structure containing void defects. Multi-scale models are developed for investigating the mechanical performance of the C/C honeycomb structure. Experimental methods and finite element simulations are utilized to examine the effects of porosity and different weave structures on the compression and shear properties, as well as damage modes of C/C honeycomb structures in detail. The results demonstrate that the presence of low porosity ρ = 1 % severely diminishes the load-bearing capacity of the honeycomb and affects its damage pattern. Twill-2 weave C/C honeycomb inherits the advanced performance of the composites and exhibits superior comprehensive properties compared to plain weave and twill-1 weave honeycomb structures.

Mechanical properties of corrugated structure with negative Poisson’s ratio and its application on energy absorbing box based on parametric modeling method

A novel corrugated structure is proposed owing to its "compression-contraction" negative Poisson’s ratio characteristics. Firstly, theoretical predictions of Poisson's ratio, elastic modulus and platform stress for corrugated structure are derived. Then, finite element models of corrugated structure are established by utilizing parametric modeling approach based on secondary development of Abaqus. Moreover, quasi-static compression test of corrugated structure is executed to verify the accuracy of theoretical predictions and parametric models. Subsequently, the influences of geometric parameters and various base material combinations on mechanical properties of corrugated structure are investigated, and the optimal base material combination Al-ABS is obtained. Afterwards, impact performances of Al-ABS corrugated structure under various impact velocities and impact angles are studied, and deformation modes, stress-strain curves and specific energy absorptionSEAare acquired. In addition, the accuracy and reliability of the FEM of energy absorbing box embedded with corrugated structure is verified through energy curves and quasi-static compression test on 3D printed energy absorbing box. Finally, multi-objective optimization design on energy absorbing box embedded with Al-ABS corrugated structure is performed with design variables of θ,r1,r2,d and optimization objectives of minimum massMs, minimum peak crushing forcePCF and maximum energy absorption EA by employing NSGA III algorithm. Compared with un-optimized corrugated structure energy absorbing box, the MsandPCFof post-optimized box decrease by 1.31%, 13.98%, accordingly, and the EA and SEA of post-optimized box increase by 10.86% and 12.33%, separately.

Machine learning models for predicting axial compressive capacity of circular CFDST columns

Machine learning (ML), widely recognized for its advanced predictive capabilities, is progressively being employed in structural design. Concrete-filled double skin steel tubular (CFDST) members are extensively utilized due to their exceptional mechanical behavior. However, existing formulas encounter challenges in accurately calculating the axial compressive capacity of circular CFDST members, particularly when high-strength concrete and steel materials are involved, leading to complexity and low accuracy. This paper presents a data-driven framework that leverages the superior predictive performance of machine learning approaches to predict the axial compressive capacity of circular CFDST columns. Finite element models are developed through secondary development of ABAQUS using custom script, which are then validated against experimental data, confirming their effectiveness and applicability. A general database is established, comprising 226 test results and 550 finite element results obtained from the script, to facilitate the prediction of axial compressive capacity for circular CFDST columns. By incorporating the physical mechanisms of CFDST members and conducting correlation analysis, the input parameters for the machine learning models are determined. Decision Tree, Artificial Neural Network (ANN), K-nearest neighbor (KNN) and two ensemble methods including Random Forest, XGBoost, are trained and optimized using the database to provide accurate predictions. The results demonstrate that the KNN model exhibits superior performance and high accuracy, outperforming the four commonly used calculation formulas in the field, particularly for circular CFDST columns using high-strength materials. The proposed data-driven framework shows promising potential for achieving outstanding predictive performance.

Study on mechanical properties of cellular structures with negative Poisson's ratio based on the development of Abaqus plug-in tool

A parametric modeling approach is proposed based on secondary development of Abaqus and a plug-in tool is designed for emulation analysis on cellular structures through graphical user interface. Firstly, star honeycomb (SH), double-headed arrow honeycomb (DAH), and re-entrant hexagon honeycomb (RHH) are chosen, and prediction models are established to estimate their mechanical properties based on homogenization theory. Then, equivalent Poisson's ratio, elastic modulus and platform stress are verified through quasi-static compression tests and simulation analysis on DAH. Subsequently, the corresponding prediction models can be integrated into the plug-in tool to pre-analyze mechanical properties of cellular structures by inputting various geometric parameters. Secondly, parametric modeling on the three cellular structures is executed. Then, attribute assignments of material, load and constraint properties are set based on Python program. Based on this, the plug-in tool is utilized to output geometric models automatically and acquire target output data employed to draw curves by MATLAB. Then, quasi-static compression tests on RHH are performed to verify the accuracy of parametric models generated by plug-in tool. Eventually, multi-condition impact mechanical properties of RHH and the influences of structural parameters on mechanical properties of the SH are investigated based on the developed plug-in tool.

The effect of chipbreaker parameters on the cutting temperature of Inconel 718 alloy based on the secondary development of Abaqus

Inconel 718 alloy has high strength and generates high temperature during cutting. The impact of chipbreaker dimensions on the cutting temperature when cutting Inconel 718 alloy was investigated. Based on the finite element software Abaqus, a kernel script program is written to develop a cutting simulation plug-in that can quickly change parameters so that users can select tools with different chipbreaker structures, and quickly set tool and cutting parameters to complete a series of pre-processing operations such as modeling, assembly, and meshing. The impact of chipbreaker channel characteristics on the cutting temperature of Inconel 718 alloy is also analyzed by example to verify the effectiveness of the developed plug-in. It provides a convenient tool for subsequent control and optimization of cutting temperature.

Study of the unified strength theory for seismic response of frame building on loess considering soil‐structure interaction

SummaryTo investigate the effect of soil‐structure interaction (SSI) on the seismic response of frame buildings on collapsible loess, the secondary development of Abaqus was used to realize the embedding of the unified strength theory constitutive model. Meanwhile, a new nonlinear elastic model generated by the unified strength theory (b, the failure criterion parameter in the unified strength theory, equals 0.5) was developed. Seven‐ and nine‐story frame buildings were selected as engineering examples in this study. The outcomes indicate that the nonlinear behavior of the loess–pile has a significant effect on the dynamic interaction of both group pile foundations and the superstructure under strong earthquakes. This results in an amplification of the displacement response and a reduction in inter‐story shear force. As the foundation soil becomes softer, the K‐type distribution of both peak accelerations and inter‐story displacements along height becomes more obvious in general.

Micro-damage analysis and numerical simulation of composite solid propellant based on in situ tensile test

Abstract In order to quantitatively analyze the mesoscopic damage process of hydroxyl-terminated polybutadiene composite solid propellant under external load, periodic boundary conditions were applied to the representative volume element model based on sample composition and morphology, the mixed matrix containing aluminum powder was homogenized, and the hyperelastic matrix damage and bilinear/exponential particle–matrix interface cohesive model with initial damage were compiled through the secondary development of Abaqus. At the same time, a data interaction platform was constructed by means of Python and MATLAB, matrix and cohesion parameters were inverted according to the optimization algorithm and experimental data, and the whole process of propellant damage and fracture was simulated from the mesoscopic perspective. The results show that combining the adaptive particle swarm optimization algorithm and the Hooke–Jeeves algorithm can achieve the global optimal parameter inversion in 102 calculations, compared with the single local search algorithm, which can cut about 11% of the objective function values. Considering the matrix damage and the exponential cohesion model with initial damage, the optimal objective function value is 0.01635, which can more accurately simulate the propellant damage and fracture process compared with 0.02136 of a bilinear cohesion model.

Data-driven collapse strength modelling for the screen pipes with internal corrosion defect based on finite element analysis and tree-based machine learning

Aiming to address the difficulties in predicting the collapse strength of sand control screen pipes with internal corrosion defects under the external pressure in offshore unconsolidated sandstone oil and gas reservoirs development, a parametric analysis model of a screen pipe with corrosion defects was established based on secondary development of ABAQUS by Python script, and was verified by the published experimental data. Then, the effect of corrosion defect and hole parameters on the collapse strength of the screen pipes was analyzed. Furthermore, a novel data-driven model with the gradient boosting regression tree (GBRT) method was used to explore and characterize the laws contained in the numerical simulation data based on a large volume of numerical simulation data. The results demonstrated that the proposed data-driven prediction model for the collapse strength of screen pipes exhibited a stable prediction average difference of 3.97% in the test set. And a large number of generalization practices based on data-driven prediction model indicated that corresponding corrosion parameter warning interval existed when the screen pipe design structure was determined, and when the corrosion defect size was greater than the warning interval, the collapse capacity of the screen pipe was considerably weakened. Moreover, the collapse strength was the lowest when the corrosion defect was located at the center of the screen pipe. And the collapse strength of the screen pipe gradually decreased with an increase of corrosion defects parameter and hole arrangement parameter. This study can provide a reference for evaluating the strength and establishing a safety-related warning mechanism of sand control screen pipes with corrosion defects.

Fully decouple convolutional network for damage detection of rebars in RC beams

This paper proposes a fully decouple convolutional neural network equipped with an anchor-free mechanism for the non-destructive identification of structures with internal damages. Two 3D cylinder IoU optimization and evaluation algorithms are designed to improve model training effect and to estimate model performance, respectively. The generation and preparation of the datasets is exceedingly time consuming and challenging, to overcome these difficulties, datasets of random damages of rebars in RC beams are established based on the secondary development of ABAQUS. The mapping relationship of the model takes the displacement contour image of damaged structures as the input and damage parameters of rebars as the output. The image feature extraction is performed to capture damage features in surface displacement information of the damaged structures based on proposed model, then, the structure internal damage identification is realized through multi-regression on damage parameters of rebars. To verify the efficiency of the proposed method, model comparison and numerical verification is utilized to evaluate the proposed model. The results show that the presented model has high accuracy and is superior to traditional coupled networks. The method can also be extended to the internal damage detection of other components, providing a new idea for the internal non-destructive health monitoring of prefabricated structures.

Delamination failure analysis of G10 insulator in electromagnetic rail launcher

AbstractThe electromagnetic (EM) rail launcher G10 insulator is prone to delamination damage during launch, which affects the service life of the insulator. Through the secondary development of ABAQUS® commercial finite‐element software, an EM‐structure coupling launch dynamics model considering projectile‐barrel coupling is established. The simulation indicates that the transverse swing of the projectile changes in a sine‐like law, and the time of the upper half wave corresponds to the pulse width of the impact force pulse waveform. The stress concentration occurs on the inner surface of the insulator where the contact‐impact occurs, resulting in impact damage. The midline of the insulator inner surface bears a large compressive strain under the action of pre‐tightening force, and the insulator is compressed oscillatingly under the influence of the time‐varying load of the rail during launch. Under the condition of repeated launch, the launch package repeatedly impacts the insulator, and the alternating load of the rail is cyclically loaded on the insulator with impact damage, which will cause the compression fatigue of the insulator and the expansion of impact damage crack. They are the main reasons for the delamination failure of insulator, and the experimental analysis is carried out. This study provides a method to study the delamination failure mechanism of the insulator, and provides guidance for improving the life of the insulator.

考虑土应变软化和率效应的桶形基础上拔模拟

It is of great significance to study the uplift bearing characteristics of suction caisson foundations for the safe service performance of offshore tension leg platform (TLP) and multi-leg wind turbine. Based on the secondary development of ABAQUS, a numerical model of suction caisson foundations considering strain softening and rate effect of soft clay is established. The numerical results are compared with the theoretical and experimental results to verify the reliability of the numerical model. The simulation results show that the change of soft clay strain softening parameters has less than five percent influence on the peak of uplift load, while the rate effect has obvious influence on the peak of uplift load and the difference caused by the change of rate effect parameters is more than forty percent. The peak of uplift load increases linearly withthe caisson outer wall roughness, and the effect of strain softening and rate effect on the uplift load caused by the caisson outer wall roughness can be ignored. For the caisson groups foundation, the caisson group effect becomes obvious with the decrease of caisson spacing, and the bearing capacity can be reduced by up to ten percent. When the caissons spacing is more than one and a half times of the caisson diameter, the caisson groups effect can be ignored.

A Modeling Method for Finite Element Analysis of Corroded Steel Structures with Random Pitting Damage

Aiming at simulating the surface morphology of corroded steel and providing a modeling method with higher accuracy, the accelerated corrosion test was used to obtain six groups of corroded specimens, and then applied to stochastic finite element analysis (FEA) for studying the mechanical behavior of corroded steel. The pitting parameters (the depth, width, and diameter–depth ratio) of all specimens were investigated and statistically analyzed. Considering the irregularity of corroded surface, the random pitting model (RPM) was established based on the secondary development of ABAQUS. Moreover, the rough surface meshing method (RSMM) was subsequently proposed to optimize the element quality of the FEA model. At last, the modeling method was applied to investigate the bearing capacity of corroded steel beams. The results indicate that, firstly, the pitting parameters of all specimens obeyed log-normal distribution, and their logarithmic mean values grew with increase in corrosion time. The corroded surface the RPM can reproduce the evolution behaviors of a corroded surface with higher accuracy. In addition, the FEA model of corroded steel structures can be meshed easily into hexahedron elements by using the RSMM and effectively optimizing the number and quality of elements. By comparing with other test results, the calculation results of the FEA model of steel beams established by using the modeling method proposed in this study demonstrate a good accuracy in mechanical behavior analysis. The modeling method provides further support for the study of mechanical properties of corroded steel structures.

Artificial neural network prediction of residual compressive strength of composite stiffened panels with open crack

Openings can be introduced into composite stiffened panels during assembly or use, which can cause degradation and cracking. Therefore, the effect of the initial damage, such as open cracks, on the residual bearing capacity of stiffened panels must be investigated. In this study a back-propagation neural network model was established to predict the ultimate compressive load of single-stiffened panels with open cracks. The crack position, length, width, and angle were used as the input parameters and the dataset was established in batches via the secondary development of ABAQUS in Python. Subsequently the learning effects of artificial neural networks (ANN) with different network structures were evaluated. The results show that an ANN model with a 5-15-30-15-10-5-1structure, activated by a tanh function, not only possesses excellent learning ability but also demonstrates excellent generalization; furthermore, it can accurately and efficiently predict the ultimate compressive load of single-stiffened panels with open cracks.

Numerical Investigation of Interlaminar Stress of CRTS II Slab Ballastless Track Induced by Creep and Shrinkage of Concrete.

The secondary development of ABAQUS was carried out to calculate the shrinkage and creep of concrete, and a finite element model of the China Railway Track System (CRTS) II slab ballastless track was established. Then, the interlaminar stress of CRTS II slab ballastless track at different ages of the track slab during laying (AOTSL) caused by concrete shrinkage and creep was studied. The obtained results showed that the stress redistribution occurred in the sliding layer, which resulted in the generation of a gap. Although the gap length was slightly reduced due to the shear cogging, the sliding layer at the slab edge is more prone to produce gaps. Under the effect of shrinkage and creep of the ballastless track, large additional shear stress, up to 0.676 MPa, was induced at the interface between CA mortar and the track slab. Meanwhile, the appearance of additional vertical and lateral forces of the shear cogging was caused by the shrinkage and creep of the ballastless track. Additionally, by further analysis, the recommended AOTSL ranges from 120 days to 180 days.

Effects of Strength and Distribution of SiC on the Mechanical Properties of SiCp/Al Composites.

In this paper, considering the strength and geometric discrete distribution characteristics of composite reinforcement, by introducing the discrete distribution function of reinforcement, the secondary development of ABAQUS is realized by using the Python language, the parametric automatic generation method of representative volume elements of particle-reinforced composites is established, and the tensile properties of silicon carbide particle-reinforced aluminum matrix composites are analyzed. The effects of particle strength, particle volume fraction, and particle random distribution on the mechanical properties of SiCp/Al composites are studied. The results show that the random distribution of particles and the change in particle strength have no obvious influence on the stress–strain relationship before the beginning of material damage, but have a great influence on the damage stage, maximum strength, and corresponding failure strain. With the increase in particle volume fraction, the damage intensity of the model increases, and the random distribution of particles has a great influence on the model with a large particle volume fraction. The results can provide a reference for the design, preparation, and characterization of particle-reinforced metal matrix composites.

Study on the interaction between nanosecond laser and 6061 aluminum alloy considering temperature dependence

The particle pollution caused by the stray light of the high-energy laser system irradiating the frame aluminum alloy is one of the most important reasons that hinder the stable operation of the system. Therefore, accurately revealing the mechanism of the interaction between the stray light and the aluminum alloy frame is an important and challenging task to ensure that inertial confinement fusion (ICF) system can generate clean and sustainable energy. In this paper, based on the secondary development of ABAQUS, a transient-stabilized thermal-mechanical direct coupling model is developed and experimentally investigated for the laser-material interaction in the high-energy nanosecond laser system with an energy density of 2 J/cm2. The mechanical damage, thermal ablation, and especially the temperature dependence of the thermal optical parameters of the aluminum alloy are considered in the modeling. Through comparative analysis, the results indicate that the effect of the variable optical properties must be considered in order to accurately reveal the mechanism of intense laser irradiation. On this basis, we found that the pulsed intense laser is absorbed by the aluminum alloy with a smaller absorption rate, after the aluminum alloy surface reaches the melting point and liquefies. This means more laser is reflected to the laser system, reducing the stability and reliability of the system. The whole process includes thermal expansion, thermal melting and potential mechanical damage, while no vaporization ablation occurs. The simulation conclusions are verified by the characterization of the experimental specimens, and it is verified that the diameter of the melting area is close to the full width at half maximum (FWHM) of the Gaussian laser source. This study provides a more accurate numerical model for precisely revealing the mechanism of high-energy nanosecond laser irradiation on metallic materials, and thus promoting the sustainable and reliable generation of clean energy from inertial confinement fusion.

Simulation of creep deformation of faced rockfill dam based on secondary development of ABAQUS

The creep deformation of concrete face rockfill dam is one of the key factors affecting the safety and performance of a concrete faced rockfill dam. In this paper, creep deformation process was carried out by secondary development based on ABAQUS software. A concrete faced rockfill dam in Laos is the research object of long-term deformation inversion. The calculated results are in good agreement with the measured analysis results. The proposed method can provide reference for the long-term deformation of earth-rockfill dam.

Polycrystalline simulation and experimental study of spatiotemporal anisotropy aluminum alloy irradiated by nanosecond laser

Revealing the mechanism of the interaction between nanosecond lasers and metallic materials is an important and challenging task. This paper focuses on model development and experimental studies of the interaction of AA6061 and nanosecond lasers in high-energy laser systems. A numerical model based on the secondary development of ABAQUS is developed for the irradiation of aluminum alloy specimens by nanosecond lasers with an energy density of 2 J/cm2. The model takes into account the spatiotemporal anisotropy of the laser irradiation, including the temperature dependence of the physical parameters, the inhomogeneous distribution of the material, and the differential laser ablation threshold at different positions. The results indicate that at an energy density of 2 J/cm2, the interaction of the laser and aluminum alloy is accompanied by thermal expansion, thermal melting, thermal ablation, and mechanical damage, which are randomly distributed in a circular area with a diameter of one-half of the facula. In addition, the experimental results obtained by laser targeting are consistent with the simulation results. This study provides a more accurate numerical model and experimental guidance for precisely revealing the interaction mechanism of the irradiation of metallic materials by high-energy nanosecond lasers.

Research on Deformation Mechanism of Cutting Nickel-Based Superalloy Inconel718 Based on Strain Gradient Theory

Abstract The traditional material constitutive model can effectively simulate the mechanical properties during the cutting process. However, the scale characteristics contained in materials are not considered in the traditional cutting model, and the inherent scale effect of materials is also ignored. Therefore, the traditional cutting constitutive model cannot effectively reflect the size effect in the cutting process, and then cannot obtain the accurate stress, strain, and temperature. In this present paper, a material constitutive model which can reflect the scale effect is established based on the strain gradient plasticity theory. Through the established model and secondary development of abaqus, the two-dimensional dynamic finite element simulation model of cutting Inconel 718 is established. By comparing the cutting experiment results with the simulation results, the established simulation model can more accurately reflect the effects of temperature, strain gradient effect, equivalent stress, and its scale effect on cutting deformation during the machining process.