Finite Element Simulation Research Articles

Progressive Damage Simulation of Wood Veneer Laminates and Their Uncertainty Using Finite Element Analysis Informed by Genetic Algorithms

Within the search for alternative sustainable materials for future transport applications, wood veneer laminates are promising, cost-effective candidates. Finite element simulations of progressive damage are needed to ensure the safe and reliable use of wood veneers while exploring their full potential. In this study, highly efficient finite element models simulate the mechanical response of quasi-isotropic [90/45/0/−45]s beech veneer laminates subjected to compact tension and a range of open-hole tension tests. Genetic algorithms (GA) were coupled with these simulations to calibrate the optimal input parameters and to account for the inherent uncertainties in the mechanical properties of wooden materials. The results show that the continuum damage mechanistic simulations can efficiently estimate progressive damage both qualitatively and quantitatively with errors of less than 4%.Variability can be assessedthrough the relatively limited number of 400 finite element simulations as compared to more data-intensive algorithms utilised for uncertainty quantification.

Modeling confined concrete behavior in finite element with a non-orthogonal elastoplastic model

The accuracy of a constitutive model for confined concrete largely relies on its capability to capture concrete's dilatancy behavior. In this paper, a non-orthogonal flow rule (NFR) is used to reasonably characterize the concrete's volume change law in relation to the stress state without the necessity for a plastic potential function. Then, the non-orthogonal plastic model is implemented in the finite element (FE) software ABAQUS using the implicit stress update algorithm, which employs the line search method and the numerical consistent tangent stiffness matrix to ensure the robustness and computational efficiency of FE analysis. Finally, FE simulations are performed to evaluate the constitutive model's capabilities in actively and passively confined concrete. In the latter case, steel tubes restrict the concrete's lateral deformation. An analysis and discussion are conducted regarding the impact of dilatancy behavior on concrete-filled steel tube (CFST) columns. The consistency between experimental data and simulation results demonstrates that the FE modeling with a non-orthogonal constitutive model provides an effective tool to describe the behavior of confined concrete.

Efficient Simulation of the Laser-Based Powder Bed Fusion Process Demonstrated on Open Lattice Materials Fabrication

Strut-based or open lattice materials are a category of advanced materials used in medical and aerospace applications due to their properties, such as high strength-to-weight ratio and energy absorption capability. The most prominent method for the fabrication of lattice materials is the Laser-based Powder Bed Fusion (L-PBF) additive manufacturing (AM) process, due to its ability to produce parts of complex geometries. The current work presents an efficient meso-scale finite element (FE) modeling methodology of the L-PBF process demonstrated in the fabrication of body-centered cubic (BCC) lattice materials. The modeling efficiency is gained through an adaptive mesh refinement technique, which results in accurate and efficient prediction of the temperature field during the process evolution. To examine the efficiency of the modeling method, the computational time is compared with that of a conventional FE simulation, based on the element and birth technique. The temperature history difference between the two approaches is minor but the adaptive mesh modeling requires only a small portion of the simulation time of the conventional model. In addition, the computational results present a good correlation with the available experimental measurements for various process parameters validating the presented efficient method.

Nanoscopic Imaging of Self-Propelled Ultrasmall Catalytic Nanomotors.

Ultrasmall nanomotors (<100 nm) are highly desirable nanomachines for their size-specific advantages over their larger counterparts in applications spanning nanomedicine, directed assembly, active sensing, and environmental remediation. While there are extensive studies on motors larger than 100 nm, the design and understanding of ultrasmall nanomotors have been scant due to the lack of high-resolution imaging of their propelled motions with orientation and shape details resolved. Here, we report the imaging of the propelled motions of catalytically powered ultrasmall nanomotors─hundreds of them─at the nanometer resolution using liquid-phase transmission electron microscopy. These nanomotors are Pt nanoparticles of asymmetric shapes ("tadpoles" and "boomerangs"), which are colloidally synthesized and observed to be fueled by the catalyzed decomposition of NaBH4 in solution. Statistical analysis of the orientation and position trajectories of fueled and unfueled motors, coupled with finite element simulation, reveals that the shape asymmetry alone is sufficient to induce local chemical concentration gradient and self-diffusiophoresis to act against random Brownian motion. Our work elucidates the colloidal design and fundamental forces involved in the motions of ultrasmall nanomotors, which hold promise as active nanomachines to perform tasks in confined environments such as drug delivery and chemical sensing.

Vibration Suppression of Graphene Reinforced Laminates Using Shunted Piezoelectric Systems and Machine Learning

The implementation of a machine learning approach to predict vibration suppression, as derived from nanocomposite laminates with piezoelectric shunted systems, is studied in this article. Datasets providing the vibration response and vibration attenuation are developed using parametric finite element simulations. A graphene/fibre-reinforced laminate cantilever beam is used in those simulations. Parameters, including the graphene and fibre reinforcements content, as well as the fibre angles, are among the inputs. Output is the vibration suppression achieved by the piezoelectric shunted system. Artificial Neural Networks are trained and tested using the derived datasets. The proposed methodology can be used for a fast and accurate prediction of the vibration response of nanocomposite laminates.

Normal fault reactivation induced by hydraulic fracturing: Poroelastic effects

Numerous surface-felt earthquakes have been spatiotemporally correlated with hydraulic-fracturing operations. Because large deformations occur close to hydraulic fractures (HFs), any associated fault reactivation and resulting seismicity must be evaluated within the length scale of the fracture stages and based on the precise fault location relative to the simulated rock volumes. To evaluate the changes in Coulomb failure stress (CFS) with injection, we conduct fully coupled poroelastic finite-element simulations using a pore-pressure cohesive zone model for the fracture and fault core in combination with a fault-fracture intersection model. The simulations quantify the dependence of CFS and the fault reactivation potential on the host rock and fault properties, spacing between the fault and the HF, and the fracturing sequence. We find that fracturing in an anisotropic in-situ stress state does not lead to fault tensile opening but rather dominant shear reactivation through a poroelastic stress disturbance over the fault core ahead of the compressed central stabilized zone. In our simulations, poroelastic stress changes significantly affect fault reactivation in all the simulated scenarios of fracturing 50–200 m away from an optimally oriented normal fault. Asymmetric HF growth due to the stress shadowing effect of the adjacent HFs leads to (1) a larger reactivated fault zone following the simultaneous and sequential fracturing of multiple clusters compared with single-cluster fracturing and (2) a larger unstable area ([Formula: see text].1) over the fault core or a higher potential of the fault slip following sequential fracturing compared with simultaneous fracturing. The fault reactivation area is further increased for a fault with lower conductivity and a higher opening-mode fracture toughness of the overlying layer. To reduce the risk of fault reactivation by hydraulic fracturing under the reservoir characteristics of the Barnett Shale, Fort Worth Basin, it is recommended to (1) conduct simultaneous fracturing instead of sequential and (2) maintain a minimum distance of approximately 200 m for HF operations from known faults.

Thermal finite element modeling and simulation of a squirrel-cage induction machine

Finite element models of electrical machines allow insights in electrothermal stresses which endanger the insulation system of the machine. This paper presents a thermal finite element model of a 3.7 kW squirrel-cage induction machine. The model resolves the conductors and the surrounding insulation materials in the stator slots. A set of transient thermal scenarios is defined and measured in the machine laboratory. These data are used to assess the finite element model.

Bidirectional large strain monitoring using a novel graphene film-based patch antenna sensor

Abstract This study proposes a rectangular microstrip patch antenna sensor based on a high-conductivity graphene film for bidirectional strain detection in structural health monitoring (SHM). By using a highly conductive graphene film instead of traditional metal foil to produce a patch antenna, the antenna possesses a higher flexibility and a larger sensing range. The mechanical, electromagnetic, and radiative properties were investigated. The strain sensing principle based on the resonant frequency offset of the graphene film antenna was proposed. The relationships between the resonant frequency shift and structural strain were quantitatively explored through theoretical deductions, finite element simulations, and experiments. According to the experimental results, the shift in the resonant frequency was linearly related to the lateral and longitudinal strains. The sensitivity coefficients for the lateral and longitudinal strains were 2.2037 kHz/με and 3.6198 kHz/με, respectively. The thermal strain can be distinguished based on the linear resonant frequency-temperature relationship. The results demonstrated the advantages and prospects of the proposed novel patch antenna for SHM.

Mechanical Response and deformation mechanism of the utility tunnel crossing earth fissure

The structural safety of the utility tunnel is adversely affected when it passes through an area with earth fissures. Using the comprehensive tunnel project at the f7 earth fissure site in Xi'an as the engineering prototype, finite element simulation was employed to investigate the mechanical responses and deformation laws of the utility tunnel under different relative positions of earth fissures and deformation joints. Simultaneously, the deformation mechanism of a utility tunnel crossing an earth fissure was explored by using theoretical analysis. The results show that the influence of the earth fissure on the surface deformation of the hanging wall is greater than that of the footwall, and the main deformation is near the earth fissure. In addition, because the rigidity of the utility tunnel greatly exceeds that of the soil, the surface deformation at the earth fissure does not show a sudden change in form as dislocation generated by the hanging wall and footwall. Earth fissure movement mainly affects the stress change in the utility tunnel in the crossing ground fissure section. Moreover, the void area will be generated by the dislocation of the earth fissure near the earth fissure position at the bottom of the utility tunnel, which is not conducive to the stress of the utility tunnel. The research results contribute to optimizing the design of utility tunnel projects and enhancing the structural safety of tunnels. Additionally, they provide important reference points for the maintenance and management of comprehensive utility tunnels, enabling timely identification and resolution of the impacts of earth fissures on tunnel structures, thus ensuring the long-term stable operation of the tunnels.

Residual Magnetic Field Testing System with Tunneling Magneto-Resistive Arrays for Crack Inspection in Ferromagnetic Pipes

Ferromagnetic pipes are widely used in the oil and gas industry. They are subject to cracks due to corrosion, pressure, and fatigue. It is significant to detect cracks for the safety of pipes. A residual magnetic field testing (RMFT) system is developed for crack detection in ferromagnetic pipes. Based on this background, a detection probe based on an array of tunneling magneto-resistive (TMR) sensors and permanent magnets is exploited. The probe is able to partially magnetize the pipe wall and collect magnetic signals simultaneously. First, a theoretical analysis of RMFT is presented. The physics principle of RMFT is introduced, and a finite element model is built. In the finite element simulations, the effects of the crack length and depth on the RMFT signal are analyzed, and the signal characteristics are selected to represent the crack size. Next, the validated experiments are conducted to demonstrate the feasibility of the proposed RMFT method in this paper.

An active learning framework for the rapid assessment of galvanic corrosion

The current present in a galvanic couple can define its resistance or susceptibility to corrosion. However, as the current is dependent upon environmental, material, and geometrical parameters it is experimentally costly to measure. To reduce these costs, Finite Element (FE) simulations can be used to assess the cathodic current but also require experimental inputs to define boundary conditions. Due to these challenges, it is crucial to accelerate predictions and accurately predict the current output for different environments and geometries representative of in-service conditions. Machine learned surrogate models provides a means to accelerate corrosion predictions. However, a one-time cost is incurred in procuring the simulation and experimental dataset necessary to calibrate the surrogate model. Therefore, an active learning protocol is developed through calibration of a low-cost surrogate model for the cathodic current of an exemplar galvanic couple (AA7075-SS304) as a function of environmental and geometric parameters. The surrogate model is calibrated on a dataset of FE simulations, and calculates an acquisition function that identifies specific additional inputs with the maximum potential to improve the current predictions. This is accomplished through a staggered workflow that not only improves and refines prediction, but identifies the points at which the most information is gained, thus enabling expansion to a larger parameter space. The protocols developed and demonstrated in this work provide a powerful tool for screening various forms of corrosion under in-service conditions.

A novel design method based onmulti–objective optimization for graded lattice structure by additive manufacturing

Purpose While performance demands in the natural world are varied, graded lattice structures reveal distinctive mechanical properties with tremendous engineering application potential. For biomechanical functions where mechanical qualities are required from supporting under external loading and permeability is crucial which affects bone tissue engineering, the geometric design in lattice structure for bone scaffolds in loading-bearing applications is necessary. However, when tweaking structural traits, these two factors frequently clash. For graded lattice structures, this study aims to develop a design-optimization strategy to attain improved attributes across different domains. Design/methodology/approach To handle diverse stress states, parametric modeling is used to produce strut-based lattice structures with spatially varied densities. The tailored initial gradients in lattice structure are subject to automatic property evaluation procedure that hinges on finite element method and computational fluid dynamics simulations. The geometric parameters of lattice structures with numerous objectives are then optimized using an iterative optimization process based on a non-dominated genetic algorithm. Findings The initial stress-based design of graded lattice structure with spatially variable densities is generated based on the stress conditions. The results from subsequent dual-objective optimization show a series of topologies with gradually improved trade-offs between mechanical properties and permeability. Originality/value In this study, a novel structural design-optimization methodology is proposed for mathematically optimizing strut-based graded lattice structures to achieve enhanced performance in multiple domains.

All-Textile Piezoelectric Nanogenerator Based on 3D Knitted Fabric Electrode for Wearable Applications.

Flexible, air permeable and elastic self-powered sensors for human motion monitoring and assisted medical rehabilitation have recently become a hot research topic. However, most current piezoelectric sensors can not account for many characteristics. Addressing this challenge, an all-textile piezoelectric sensor (ATPS) based on 3D structured knitted fabric electrodes is reported. The ATPS consists of a piezoelectric element polyvinylidene fluoride nanofiber membrane, flexible knitted fabric electrodes, and an elastic self-adhesive bandage. Based on the flexible and efficient knitting technology, the sensor has the advantages of low cost, flexibility, simple structure, and convenient large-area manufacturing. Experimental and finite element simulation results show that the knitting pattern of fabric electrodes can enhance the piezoelectric output of ATPS. The optimal ATPS has a high voltage response sensitivity of up to 0.68 V/kPa. The proposed ATPS responds to a wide range of input forces from 0.098 to 724 N in self-powered mode, verifying its feasibility as a tactile sensor for human motion detection and recognition (throat swallowing, wrist bending, elbow bending, knee bending, walking slowly, running fast) and as a pressure sensor (Morse code, digit recognition) and demonstrating its potential for motion tracking, medical rehabilitation, and human-computer interaction.

Structural Strength Analysis and Optimization of Commercial Aircraft Nose Landing Gear under Towing Taxi-Out Conditions Using Finite Element Simulation and Modal Testing

In the field of civil aviation, the nose landing gear is a critical component that is prone to damage during taxiing. With the advent of new technologies such as towing taxi-out and hub motors, the nose landing gear faces increasingly complex operational environments, thereby imposing higher performance demands. Ensuring the structural safety of the nose landing gear is fundamental for the successful application of these technologies. However, current research on aircraft nose landing gear under these new conditions is somewhat lacking, particularly in terms of reliable analysis models for real-world scenarios. This study focuses on a typical Class C aircraft, specifically the B-727 model, for which a finite element model of the nose landing gear is developed. Modal testing of the aircraft’s nose landing gear is conducted using the impact hammer method, and the results are compared with those from the simulations. The experimental data indicate that the error range for the first seven natural frequencies is between 0.23% and 9.27%, confirming the high accuracy of the developed landing gear model. Furthermore, with towing taxi-out as the primary scenario, a dynamic model of the aircraft towing system is established, and an analysis on the structural strength and topological optimization of the nose landing gear under various conditions, including high speeds and heavy loads, is performed. The results show that the developed model can effectively support the analysis and prediction of the mechanical behavior of the nose landing gear. Under high-speed, heavy-load conditions, the nose landing gear experiences significantly increased loads, with the maximum deformation primarily occurring at the lower section of the shock strut’s outer cylinder. However, no damage occurred. Additionally, under these conditions, an optimized structural design for the landing gear was identified, which, while ensuring structural strength, achieves a 22.32% reduction in the mass of the outer cylinder, also ensuring safety in towing taxi-out conditions.

Estimation of fracture behavior of CFRP/CFRP adhesively bonded joints under mixed-mode conditions using a cohesive zone model

Finite element (FE) simulations of adhesively bonded composite joints were conducted using the cohesive zone model (CZM). To clarify the effect of fracture criteria on the accuracy of the CZM simulation, two types of mixed-mode criteria including the ­linear summation model of Modes I and II energy release rates, G I / G IC + G II / G IIC = 1 , and the nonlinear power-law, ( G I / G IC ) n + ( G II / G IIC ) n = 1 , were employed. A CZM formulation using the power-law fracture criterion was developed in this study. The load–displacement curves calculated by the two models were compared with the experimental results obtained from mixed-mode Fernlund–Spelt-type double cantilever beam tests, and the Mode II end-notched flexure (ENF) tests. Calculations using the nonlinear fracture criterion were closer to the experimental results. Consequently, it is concluded that nonlinear fracture modeling is of vital importance for accurate strength analysis of mixed-mode adhesive joints.

Evaluation of residual load-bearing capacity for corroded steel strands via MMM technique

The quantitative evaluation of the residual load-carrying capacity of corroded cables is critical to the safe service of bridge structures. In this study, the locally corroded steel strands with different corrosion degrees were obtained through electrochemical experiments and the metal magnetic memory (MMM) signals were collected by the TSC-9 M-12 tester. The tensile failure tests of corroded steel strands were conducted by the WAW-1000 tensile testing machine. The distribution laws of the normal component Hz signals for steel strands in different corrosion cases were detailed and a three-dimensional (3D) magnetic dipole model of corroded steel strands was developed considering the end effects. The linear relationships between the magnetic characteristic quantity Hn and the corrosion cross-section loss rate As were revealed and verified by the theoretical and finite element simulation results. Based on the above relationships, a quantitative linear relationship between the residual load-carrying capacity F and the corrosion cross-section loss rate As of the corroded steel strand was proposed. The relative errors of the residual load-carrying capacity F calculated by the proposed quantitative method were overall within 20%. This study provides a basis for evaluating the residual load-carrying capacity of corroded cables using the MMM technique.

Efficient Neutral H2O2 Electrosynthesis from Favorable Reaction Microenvironments via Porous Carbon Carrier Engineering

The efficient electrosynthesis of hydrogen peroxide (H2O2) via two‐electron oxygen reduction reaction (2e‐ ORR) in neutral media is undoubtedly a practical route, but the limited comprehension of electrocatalysts has hindered the system advancement. Herein, we present the design of model catalysts comprising mesoporous carbon spheres‐supported Pd nanoparticles for H2O2 electrosynthesis at near‐zero overpotential with approximately 95% selectivity in a neutral electrolyte. Impressively, the optimized Pd/MCS‐8 electrocatalyst in a flow cell device achieves an exceptional H2O2 yield of 15.77 mol gcatalyst‐1 h‐1, generating a neutral H2O2 solution with an accumulated concentration of 6.43 wt.%, a level sufficiently high for medical disinfection. Finite element simulation and experimental results suggest that mesoporous carbon carriers promote O2 enrichment and localized pH elevation, establishing a favorable microenvironment for 2e‐ ORR in neutral media. Density functional theory calculations reveal that the robust interaction between Pd nanoparticles and the carbon carriers optimized the adsorption of OOH* at the carbon edge, ensuring high active 2e‐ process. These findings offer new insights into carbon‐loaded electrocatalysts for efficient 2e‐ ORR in neutral media, emphasizing the role of carrier engineering in constructing favorable microenvironments and synergizing active sites.

A new model of thermo-mechanical actuation for twisted and coiled polymer muscles with initial curvature

The twisted and coiled polymer (TCP) artificial muscle is one type of novel soft actuator for mimicking natural skeletal muscle that can provide large linear and torsional actuation and energy density. Twisting and coiling are the pivotal steps in fabricating TCP muscles. The influence of twisting on the actuation response of TCP muscles has been extensively investigated recently. However, the influence of coiling remains unclear. Based on the finite strain theory, we establish a new thermo-mechanical actuation model for TCP muscles with initial curvature. The theoretical predictions based on the model align well with the finite element simulations, accurately capturing the actuation response of thermally-activated TCP muscles. It is revealed that twisting contributes positively to the actuation, while coiling has a passive effect. Geometrical parameters, such as the helix radius and helix angle, can effectively regulate the actuation performance of TCP muscles. Furthermore, an optimal bias angle is identified that maximizes both the recovery torque and the linear actuation. This study sheds light on the structural optimization design of TCP muscles.

Enhanced Energy Storage in PVDF-Based Nanocomposite Capacitors through (00l)-Oriented BaTiO3 Single-Crystal Platelets.

Flexible nanocomposite dielectrics with inorganic nanofillers exhibit great potential for energy storage devices in advanced microelectronics applications. However, high loading of inorganic nanofillers in the matrix results in an inhomogeneous electric field distribution, thereby hindering the improvement of the energy storage density (Ue) of the dielectrics. Herein, we proposed a strategy that utilized (00l)-oriented barium titanate (BT) single-crystal platelets to fabricate trilayered nanocomposite dielectrics for energy storage applications. The trilayered nanocomposites consisted of two high-permittivity layers of (Ta2O5, Al2O3) codoped TiO2 nanoparticles (Ta-Al@TiO2 nps) dispersed in a poly(vinylidene fluoride) (PVDF) matrix to facilitate large electric displacement and a middle layer of (00l)-oriented BT single-crystal platelets to provide high breakdown strength. Hence, the trilayered PVDF/Ta-Al@TiO2 nps/BT single-crystal platelet nanocomposite film attains an outstanding Ue of 16.9 J cm-3 at 370 kV mm-1, which is ∼625% higher than that of the single-layer PVDF/Ta-Al@TiO2 nps film. Finite element simulation further clarified that the successive inner layer of highly (00l)-oriented BT single-crystal platelets could effectively restrain the propagation of electrical treeing in trilayered nanocomposites. This research offers an effective approach for developing flexible dielectric capacitors with an excellent energy storage performance.

Analysing the shape memory behaviour of GnP-enhanced nanocomposites: A comparative study between experimental and finite element analysis

Abstract Shape memory polymers (SMPs) are capable of enduring significant deformations and returning to their original form upon activation by certain external stimuli. However, their restricted mechanical and thermal capabilities have limited their broader application in engineering fields. To address this, the integration of graphene nanoplatelets (GnPs) with SMPs has proven effective in enhancing their mechanical and thermal properties while maintaining inherent shape memory functions. The study evaluated shape memory nanocomposites (SMNCs) using dynamic mechanical, thermogravimetric, and static tensile, flexural, and shape memory tests, along with scanning electron microscopy to analyse tensile fractures. The results indicate that the optimal content of GnP is 0.6 wt%, resulting in excellent shape memory, thermal, and mechanical properties. Specifically, this composition demonstrates a shape recovery ratio of 94.02%, a storage modulus of 4580.07 MPa, a tensile strength of 61.42 MPa, and a flexural strength of 116.37 MPa. Additionally, the incorporation of GnPs into epoxy reduces recovery times by up to 52% at the 0.6 wt% concentration. While there is a slight decrease in the shape fixity ratio from 98.77% to 93.02%, the shape recoverability remains consistently high across all samples. Current finite element (FE) models often necessitate complex, problem-specific user subroutines, which can impede the straightforward application of research findings in real-world settings. To address this, the current study introduces an innovative finite element simulation method using the widely used ABAQUS software to model the thermomechanical behaviour of SMNCs, importantly incorporating the time-dependent viscoelastic behaviour of the material. The effectiveness of this new approach was tested by comparing experimental results from bending test of SMNCs cantilever beam with outcomes derived from FE simulations. The strong agreement between the experimental data and simulation results confirmed the precision and reliability of this novel technique.