Finite Element Calculations Research Articles

Impact of surface roughness on the formation of necking instabilities in additive manufactured porous metal plates subjected to dynamic plane strain stretching

This paper investigates the influence of surface roughness on multiple necking formation in additive manufactured porous ductile plates subjected to dynamic plane strain stretching. For this purpose, we have developed a computational model in ABAQUS/Explicit (2019) which includes surface texture and discrete voids measured from 3D-printed metallic specimens using optical profilometry and X-ray tomography analysis, respectively. The mechanical behavior of the material is described using an elastic–plastic constitutive model, with yielding defined by the isotropic von Mises criterion, an associated flow rule, and a power-law function for the yield stress evolution which depends on plastic strain, plastic strain rate, and temperature. The finite element calculations have been conducted across a broad range of strain rates, from 5000s−1 to 50000s−1, to explore the interactions among inertia, surface roughness, and porosity in determining the necking pattern that emerges in the plates at large strains. The finite element results show that surface roughness induces perturbations in the deformation field of the specimen, which lead to early necking localization, while the location and number of necks formed are primarily controlled by the porous microstructure and the loading rate. The results for the neck spacing have shown quantitative agreement with the analytical stability analysis predictions and the unit-cell finite element calculations reported by Rodríguez-Martínez et al. (2021). Moreover, integrating discrete voids into simulations that already account for surface roughness results in a minor reduction in necking strain: surface roughness and porosity demonstrate similar quantitative impacts on necking ductility, which is primarily influenced by inertia effects at the highest strain rates studied. To the best of the authors’ knowledge, this paper presents the first calculations that explore dynamic plastic localization in additive manufactured metals, incorporating actual surface roughness and explicit void representation derived from experimental measurements. This work marks progress in the analysis of 3D-printed structures under impact loading, aiming to understand and predict the mechanics influencing their energy absorption capacity at high strain rates.

A micromechanics-based artificial neural networks model for rapid prediction of mechanical response in short fiber reinforced rubber composites

The complex microstructural characteristics inherent in short fiber reinforced rubber composites (SFRRCs) impose considerable computational burdens in predicting the mechanical behavior of such composite materials. To address this challenge, this research extends the applicability of the homogeneous model predicated on the orientation averaging method to encompass composite materials featuring hyperelastic matrices. Combined with finite element method, a comprehensive mechanical response database encompassing various volume fractions and fiber orientation distributions is established. Leveraging this database, a micromechanics-based artificial neural network (ANN) model is meticulously designed to rapidly predict the mechanical response of SFRRCs across varying volume fractions and fiber orientation distributions, utilizing a fixed strain step strategy. To ascertain the efficacy and precision of the developed ANN model, representative volume elements portraying both planar and three-dimensional random distributions of composites are constructed and subjected to finite element analysis. Results indicate that the predicted outcomes from the ANN model align closely with finite element calculations within a certain strain range, while significantly reducing computational costs.

Analyzing the Impact of Multiple Foundation Stiffness Correlation on the Natural Frequency of Offshore wind turbines

The analysis of wind turbine behavior should avoid unplanned resonance, as it can increase fatigue damage. It is essential to rigorously evaluate the natural frequency of wind turbines in the initial design stage. This estimation can be done through two steps, the first one is the computing of the fixed base natural frequency of the wind turbine. The second is the estimation of the foundation stiffness effect. This paper examines the error margin of four correlations of foundation stiffness namely Randolph, Davies and Budhu, DNV, and Higgins in the estimation of the natural frequency of wind turbines. The fixed base natural frequency was estimated in this paper using a special-purpose finite element computer program called TurbiSoft through beam and volume elements. A reference 5.0 MW offshore wind turbine and 9 other turbines from different wind farms have been analyzed. For the fixed base natural frequency, obtained results demonstrate the reliability of the finite element program TurbiSoft through an error margin between 1-4% for the reference 5.0 MW offshore wind turbine. For the natural frequency of the whole system, the estimated error marking was between 9-20% which is an important value.This significant error is attributed to the low accuracy of these four correlation formulas for predicting the foundation flexibility contribution. The results from the four correlation formulas used are quite similar, with a difference in the error margin of less than 1%. However, the largest error margins are observed with the Higgins formula, which has been originally developed for short monopiles, even though the analyzed monopiles can be considered short, with monopile slenderness ratios less than 8.

Influence of natural hyoid bone position and surgical repositioning on upper airway patency: A computational finite element modeling study.

A validated finite element model of the rabbit UA was advanced and used to simulate changes in BHP and SHR, alone and in combination. The hyoid was displaced in cranial, caudal, anterior, anterior-cranial and anterior-caudal directions from 1-4mm. Model outcomes included UA collapsibility, measured using closing pressure (Pclose), cross-sectional area (CSA) and soft tissue mechanics (displacement, stress and strain). Graded BHP increments increased Pclose for all directions, and up to 29-43% at 4mm (relative to the original BHP). Anterior-based SHR decreased Pclose (~-115% at 4mm) and increased ΔCSA (~+35% at 4mm). Cranial SHR decreased ΔPclose (-29%), minimally affecting CSA. Caudal SHR increased ΔPclose (+27%) and decreased ΔCSA (-7%). Anterior-cranial and anterior-caudal SHR produced the highest stresses and strains. SHR effects on UA outcomes were dependent on BHP, with more caudal BHPs leading to less effective surgeries. BHP (phenotype) and SHR both alter UA outcomes, with effects dependent on hyoid displacement direction and magnitude. BHP influences the effectiveness of SHR in reducing UA collapsibility. These findings provide further insights into the hyoid's role in UA patency and suggest that considering the hyoid's baseline position and surgical repositioning direction/increment may help improve hyoid surgeries for OSA treatment.

Uniform electric-field optimal design method using machine learning

The demand for uniform electric fields (UEFs) in engineering is very high, particularly in high-voltage devices. The existing methods encounter limitations in terms of optimization region and universality. Herein, we propose a method for designing UEFs based on finite element calculations of electromagnetic fields and machine learning. First, the electric-field distribution of the plate-to-plate electrode structure determined using three electrode-shape parameters (ESPs) is calculated using finite element software and is drawn. Thereafter, a dataset of 2000 images is created with different electric-field strength distributions using various ESPs. Net, we employ image-processing techniques to extract nine statistical features from the gray-level information in the images. Models are trained through machine learning to predict ESPs based on the gray-level features (GLFs). Finally, the electric-field strength distribution image of the expected ideal uniform field is artificially selected. In addition, the ESPs from which the uniform electric-field is produced are predicted by the models. The proposed method provides an accurate solution for optimizing the design of a uniform electric-field and a new approach for solving inverse problems of electric-field. This involves drawing the required electric-field strength distribution image for high-voltage engineering and obtaining the required ESPs.

Integral equation based wellbore preconditioner for 3D electromagnetic response modeling

Modeling subsurface controlled-source electromagnetic (CSEM) responses using the finite-element (FE) method is challenging in the presence of highly conductive wellbore casing. The very large conductivity contrast between the casing and the host formation leads to increased computation time and potentially unstable solutions. We address this difficulty by preconditioning an FE solver with an integral equation (IE) primary solution that captures the CSEM response of a realistic-sized steel wellbore casing. Our hybrid IE-FE approach determines the primary field using 2D integral-equation forward modeling and then interpolates the IE-computed solution onto the nodes. Then using an existing FE simulator, we solve for the secondary electric and magnetic fields. This approach removes the need for an ultra-fine FE mesh around the wellbore, thereby improving FE solution stability while greatly reducing FE computation time. Our method is illustrated by modeling the CSEM responses of idealized fluid-bearing zones.

Optimization of dissipative mufflers

The method of selecting the configuration of dissipative mufflers with the required acoustic efficiency is considered. The peculiarity of the considered approach is the use of an integral indicator of acoustic efficiency and dimensionless geometric parameters. The studies were carried out using finite element calculations. In the finite element model of a dissipative mufflers, acoustic characteristics of a fibrous sound-absorbing material obtained from experimental studies were used.

Determination of the moment–rotation relation of continuous timber–concrete composite floors based on the component method

Timber–concrete composite (TCC) combines the advantages of timber and reinforced concrete construction. In multi-storey buildings, the design of TCC floors is often governed by the deformation serviceability requirements. One way to improve deformation serviceability is through the design of continuous floor systems. However, the current practice of TCC slab systems is often limited to load-carrying as single-span beams. This paper presents an analytical model based on the component method for determining the moment–rotation relation of continuous TCC slabs in the range with negative bending moments. The investigations involve the development of load–displacement curves for the individual force-transmitting components, including timber and reinforced concrete, followed by their assembly into a component model. The model has been verified using finite element calculations and the results demonstrate that the moment–rotation relation of continuous TCC systems can be accurately captured. As the variability of the material properties strongly influences the stiffness of the joint and therefore the deformation and stresses in the TCC slab, a probabilistic analysis of the material parameters was performed using the Monte Carlo method. The probabilistic investigations show that the variability of the input parameters has a significant impact on the joint stiffness, with notable scattering observed in the moment–rotation relation, especially in the range of the cracking phase of the concrete. The results from the probabilistic investigations enable initial statements about the joint stiffness of continuous timber–concrete composite slabs in ranges with negative bending moments.

Hierarchical micro-nanostructured Zr-based metallic glass with tensile plasticity

Metallic glasses (MGs) exhibit many unique properties because of their disordered microstructure. However, the absence of tensile plasticity at room temperature severely restricts the potential of MGs as high-performance structural materials. Here, Zr-based MG with a hierarchically heterogeneous structure in length was fabricated to enhance the tensile plasticity. Higher structural heterogeneity with a characteristic length of 12-20 nm was obtained by thermal cycling treatment. Subsequently, a micron array with a lower elastic modulus was prepared via high-frequency vibration. The hierarchical micro-nanostructured Zr-based MG exhibits a tensile plasticity of 0.68% at room temperature. Combined with finite element calculations and molecular dynamics simulations, the mechanism of the plastic deformation is attributed to more activated deformation units at the nanoscale and shear bands blocking and branching by complicated stress distributions at the micrometer scale. The findings presented herein can expand the understanding of structural heterogeneity, and provide a theoretical foundation for enhancing the tensile plasticity of MGs.

Hierarchical meta-porous materials as sound absorbers

The absorption of sound has great significance in many scientific and engineering applications, from room acoustics to noise mitigation. In this context, porous materials have emerged as a viable solution towards high absorption performance and lightweight designs. However, their performance is somewhat limited in the low-frequency regime. Inspired by the concept of recursive patterns over multiple length scales, typical of many natural materials, here, we propose a hierarchical organization of multilayered porous media and investigate their performance in terms of sound absorption. Two types of designs are considered: a hierarchical periodic (HP) and a hierarchical gradient (HG). In both cases, it is found that in some frequency ranges the introduction of multiple levels of hierarchy simultaneously allows for: (i) an increase in the level of absorption compared with the corresponding bulk block of porous material (or to the previous hierarchical levels (HLs)), and (ii) a reduction in the quantity of porous material required. Another advantage of using this approach is on the fabrication, since only one porous material is required. The performances are examined for both normal and oblique incidences, as well as for different values of the static air-flow resistivity. The methodological approach is based on the transfer-matrix method, optimization algorithms such as the metaheuristic greedy randomized adaptive search procedure (GRASP), finite-element calculations and measurements performed in an impedance tube.

Finite element analysis method for the sliding cable analysis: The sliding variable method

A sliding cable structure is typically characterized by uncertainty of sliding and complexity of friction at the cable-strut joints, which makes accurate and efficient analysis difficult. In this study, we have proposed the sliding variable method, to simulate the cable sliding process considering friction equivalently and analyze the internal force and deformation response at the equilibrium state quickly and accurately. The sliding variable method takes the sliding vector of the cable at cable-strut joints as the basic variable, extracts the slippage stiffness matrix and establishes the cable force balance equation to solve the sliding vector, and simulates the change of cable original length and cable force by applying equivalent temperature load. In this paper, first, the basic principles and calculation procedures of the sliding variable method without considering friction, are discussed in detail to simulate frictionless slip of continuous cable, using with roller-type cable-stayed joints. as an example. On this basis, a calculation model incorporating the effects of friction is analyzed, a method to judge the sliding situation and balance relation of cable-forces is revealed, and the calculation principle and steps of the method are further deduced. Meanwhile, choosing a multi-joint cable–pulleys model as an example, the accuracy and rationality of the sliding variable method with and without considering friction are verified respectively. This method requires a conventional finite element calculation and second calculation alternately. Finally, to improve the practicability and computational efficiency of the sliding variable method, a macro document was compiled using the secondary development function of ANSYS parametric programming language (APDL) according to the basic framework of the sliding variable method. The frictional sliding behaviors in two typical engineering cases, a cable girder and a prestressed fish-belly girder on a foundation pit, are analyzed by using the compiled macro document in finite element program. The results show that the compiled macro document can be both accurate and efficient in calculating and analyzing cable sliding problems and can be easily popularized and applied in engineering practices.

Investigation of higher-order springing of a ship in regular waves by experimental analysis and two-way CFD-FEA coupled method

In this paper, the higher-order springing phenomenon is addressed for a segmented barge ship model through experimental and numerical measures. An efficient in-house two-way coupled numerical solver between Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) is developed and validated against experimental results. The coupling method is based on a domain-separated approach and necessitates the resolution of individual boundary value problems in distinct domains. To ensure convergence within these individual domains, an implicit numerical scheme is employed and further facilitated exchange of variables for coupling. The current approach emphasizes the overall convergence between two solvers, maintaining a strongly coupled setup to comprehensively address fluid-structure interaction phenomena, including added mass and damping effects. A series of tank tests were conducted first to measure the wave-induced sectional loads and motions, during which the springing responses to very high-order harmonics of wave load were observed. By comparing the numerical prediction with the tank test results for rigid body motion and flexible vertical bending moment (VBM), the proposed numerical method demonstrated agreement with experimental results, affirming its validity and robustness. Finally, the springing response up to 14th order harmonics is discussed and investigated.

Impact resistance study of lime slag–stabilised steel slag mixes

ABSTRACT Given the transient nature of impact loading, exploring the microscopic damage characteristics and damage mechanisms of materials through indoor tests is difficult. In this study, the damage morphology and energy dissipation characteristics of lime slag–stabilised steel slag (LSSS) mixes under vertical impact loading is explored using ABAQUS software, a finite element model of LSSS for falling hammer impact test is established, the validity of finite element calculation is verified by comparing the results of indoor tests, and the strain characteristics, deflection changes, and energy transformation process of LSSS under vertical impact loading are analysed. Results show that the LSSS tensile and compressive strains under impact loading are roughly divided into low strain rate, precracking, and cracking phases with a rapid increase in strain. Under the same impact energy conditions, the LSSS bottom tensile strain, span deflection, drop hammer kinetic energy conversion time, and LSSS plastic energy consumption curve rising slope are sensitive to drop hammer mass. Thus, improvement in drop hammer mass will prolong the impact loading of the drop hammer–LSSS system internal energy conversion time, and the LSSS strain peak range to the central concentration, enhancing span deflection and bottom deformation.

Enhancing solar energy systems: The role of computational and automation techniques in achieving net zero by 2050

This review aims to show how computational and automation can be applied to optimize the solar power system toward net-zero emissions in 2050. It emphasizes the power of data analytics, machine learning and automated systems for optimizing business models and measuring the performance of solar technology. The role of solar power in decarbonizing our energy needs and lowering carbon emissions is discussed along the global climate agenda. It also discusses novel uses such as self-teaching robots for solar panel inspection and automated manufacturing to increase the efficiency and sustainability of solar power generation. Additionally, it addresses the need for sophisticated research tools such as computational fluid dynamics (CFD) and finite element analysis (FEA) to create new technologies in the solar market and ultimately meet the ambitious renewable energy targets of 2050.

Tunable magnonic crystal in a hybrid superconductor–ferrimagnet nanostructure

One of the most intriguing properties of magnonic systems is their reconfigurability, where an external magnetic field alters the static magnetic configuration to influence magnetization dynamics. In this paper, we present an alternative approach to tunable magnonic systems. We studied theoretically and numerically a magnonic crystal induced within a uniform magnetic layer by a periodic magnetic field pattern created by the sequence of superconducting strips. We showed that the spin-wave spectrum can be tuned by the inhomogeneous stray field of the superconductor in response to a small uniform external magnetic field. Additionally, we demonstrated that modifying the width of superconducting strips and separation between them leads to the changes in the internal field which are unprecedented in conventional magnonic structures. The paper presents the results of semi-analytical calculations for realistic structures, which are verified by finite-element method computations.

Simulation study on parameter optimization of transcranial direct current stimulation based on rat brain slices

Transcranial direct current stimulation (tDCS) is an important method for treating mental illnesses and neurodegenerative diseases. This paper reconstructed two ex vivo brain slice models based on rat brain slice staining images and magnetic resonance imaging (MRI) data respectively, and the current densities of hippocampus after cortical tDCS were obtained through finite element calculation. Subsequently, a neuron model was used to calculate the response of rat hippocampal pyramidal neuron under these current densities, and the neuronal responses of the two models under different stimulation parameters were compared. The results show that a minimum stimulation voltage of 17 V can excite hippocampal pyramidal neuron in the model based on brain slice staining images, while 24 V is required in the MRI-based model. The results indicate that the model based on brain slice staining images has advantages in precision and electric field propagation simulation, and its results are closer to real measurements, which can provide guidance for the selection of tDCS parameters and scientific basis for precise stimulation.

Чисельно-експериментальне дослідження високотемпературної багатоциклової втомної міцності монокристалічних лопаток газових турбін

The subject of the research is anisotropic single-crystal turbine blades of aircraft gas turbine engines (AGTE), as well as their multi-cycle fatigue strength characteristics at high temperatures. The goal of this study was to determine the endurance limit of single-crystal high-pressure turbine blades of an AGTE at high temperatures of 820°C. The objective of the study is to develop a method for calculating and experimentally investigating the characteristics of high-temperature multi-cycle fatigue strength of gas turbine blades made of single-crystal nickel heat-resistant alloys. The research methods used are: method of computer modelling, which was used to create a 3D model of a cooled high-pressure turbine blade; finite element method, which was used to determine the stress-strain state of the blade according to the selected form of resonant vibrations; strain and resonance methods, which were used to determine the fatigue strength characteristics of single-crystal turbine blades under high-temperature loading. The following results were obtained. Literary sources describing theoretical and experimental methods for determining the strength characteristics of blades under combined dynamic and high-temperature loading were analyzed. The developed special installation for testing turbine blades under conditions of temperature and dynamic (resonant) loading was described. A combined method for assessing the multi-cycle fatigue strength at high temperatures is proposed, which includes studies on full-scale turbine blades and finite element calculations. The dynamic and temperature characterization of single-crystal turbine blades selected for the study was carried out and described. Fatigue tests were performed to determine the endurance limit of the blades at a high temperature equal to T = 820 °C. Conclusions. The scientific novelty of the obtained results is as follows. A specialized experimental setup was developed to study the endurance limit of single-crystal AGTE blades under high-temperature loading. A method for combining numerical (ANSYS) and experimental (field tests) study of high-temperature multi-cycle fatigue strength of turbine blades made of single-crystal heat-resistant alloys was developed. The direction of further research is presented.

Damage analysis and assessment of concrete T-girder bridge based on fire scene numerical reconstruction

Fire is a sporadic disaster of concrete bridges, with diverse fire environments and complex damage mechanisms. Accurately evaluating the damage situation of concrete bridges after a fire is exceedingly challenging. This study formulates a damage analysis and assessment method based on the step-by-step and progressively deepening working principle. The method relies on fire scene numerical reconstruction and encompasses key technical aspects, including bridge detection and analysis during the fire incident, fire scene numerical reconstruction, and subsequent bridge damage assessment. Building upon these principles, the study utilizes results from the detection and analysis of the concrete T-girder bridge during a fire incident to establish Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) models for the numerical reconstruction of the fire scene. These models enable the calculation of varying temperature distributions and the evolution of the bridge under fire. Compared with the parameters obtained through the ISO834 method, the numerical reconstruction approaches not only enhances the accuracy of replicating the bridge combustion process but also enables the extraction of temperature field distribution patterns within the bridge fire space and its concrete components.

Simulation analysis of force and fatigue life of circular wheel of crawler vehicle

During loading and driving, the wheels bear the vertical load from the body mass and the excitation load generated by uneven road surface on the one hand, and bear the driving torque on the other hand. The load-bearing methods of wheels are generally divided into bottom load-bearing and top load-bearing. This paper describes the structural characteristics of the track system of the articulated track vehicle and the interaction relationship between the main components of the track system. Finite element calculation is carried out based on ANSYS software to obtain the stress distribution of each key component under various loading methods. It can be seen from the results that all key components of the track system can meet the strength and rigidity requirements; although there are also areas with large local stress, they are all within the safe range, which is mainly caused by stress concentration. Safe life is obtained through fatigue analysis.

Optimizing Transformation-Induced Plasticity to Resist Microvoid Softening

Many high-performance steels that are critical for energy-efficient, lightweight designs rely on transformation-induced plasticity (TRIP) to achieve superior combinations of strength and ductility/toughness. Further development of these alloys will require greater optimization of the metastable (retained) austenite phase responsible for TRIP. Considering the complex nature of TRIP and its effects on ductile fracture, an integrated computational materials engineering (ICME) approach to materials optimization is desired. In this work, we report the results of a large series of micromechanical finite element calculations that probe the interaction of TRIP and void-mediated ductile fracture mechanisms. The simulations identify the optimal austenite stability for maximizing the benefit of TRIP across a wide range of stress states. The applied stress triaxiality significantly influences the microvoid growth rate and the computationally determined optimal stability. The simulation results are compared with existing experimental data, demonstrating good agreement.