Finite Element Analysis Simulation Research Articles

Investigation of Torque and Reduction of Torque Ripples through Assisted-Poles in Low-Speed, High-Torque Density Spoke-Type PMSMs

In this article, rotor designs utilizing assisted-poles are investigated for a high-torque density spoke-type permanent magnet synchronous machine (PMSM) with fractional slot concentrated winding (FSCW) to explore the rich air-gap magnetic field harmonics and torque generation mechanism. Due to their higher average torque output, spoke-type PMSMs with FSCW are increasingly used in high-torque density applications. However, slot harmonics generate torque ripples that are difficult to eliminate in FSCW spoke-type PMSMs. Removing slot harmonics from the stator or winding results in a large drop in torque since their winding factors are identical to those of the main harmonic. Therefore, rotor designs having assisted-poles (symmetrical and asymmetrical) are investigated in this work to mitigate slot harmonics and minimize torque ripples. Firstly, the air-gap flux density is analyzed for the machines having assisted-poles, and a model of interaction between the stator and rotor-MMF harmonics is created and validated through Finite element analysis (FEA) to analyze the torque production mechanism. In addition, an analytical relationship between the assisted-poles’ dimensions and the generated torque harmonics is proposed. Furthermore, a generalized torque ripple reduction concept for the FSCW spoke-type PMSM having asymmetrically designed assisted-poles is presented. The proposed design and optimization method are validated through analytical calculations and FEA simulations, and a brief comparative analysis is presented for the analyzed machine prototypes. It has been established that the machine designed by applying the proposed asymmetrical assisted-poles can achieve a reduction in torque ripples while also significantly lowering cogging torque in comparison to the conventional spoke-type PMSMs and other spoke-type PMSMs with rotor having symmetrical assisted-poles.

An artificial neural network model for determining stress concentration factors for fatigue design of tubular T-joint under compressive loads

PurposeThe stress concentration factor (SCF) is commonly utilized to assess the fatigue life of a tubular T-joint in offshore structures. Parametric equations derived from experimental testing and finite element analysis (FEA) are utilized to estimate the SCF efficiently. The mathematical equations provide the SCF at the crown and saddle of tubular T-joints for various load scenarios. Offshore structures are subjected to a wide range of stresses from all directions, and the hotspot stress might occur anywhere along the brace. It is critical to incorporate stress distribution since using the single-point SCF equation can lead to inaccurate hotspot stress and fatigue life estimates. As far as we know, there are no equations available to determine the SCF around the axis of the brace.Design/methodology/approachA mathematical model based on the training weights and biases of artificial neural networks (ANNs) is presented to predict SCF. 625 FEA simulations were conducted to obtain SCF data to train the ANN.FindingsUsing real data, this ANN was used to create mathematical formulas for determining the SCF. The equations can calculate the SCF with a percentage error of less than 6%.Practical implicationsEngineers in practice can use the equations to compute the hotspot stress precisely and rapidly, thereby minimizing risks linked to fatigue failure of offshore structures and assuring their longevity and reliability. Our research contributes to enhancing the safety and reliability of offshore structures by facilitating more precise assessments of stress distribution.Originality/valuePrecisely determining the SCF for the fatigue life of offshore structures reduces the potential hazards associated with fatigue failure, thereby guaranteeing their longevity and reliability. The present study offers a systematic approach for using FEA and ANN to calculate the stress distribution along the weld toe and the SCF in T-joints since ANNs are better at approximating complex phenomena than standard data fitting techniques. Once a database of parametric equations is available, it can be used to rapidly approximate the SCF, unlike experimentation, which is costly and FEA, which is time consuming.

Multiscale Analysis of the Flexural Performance of FRP Reinforced Concrete Structures

Based on existing experimental data and analysis, seven different FRP bar models including Carbon Fiber Reinforced Polymer (CFRP), Basalt Fiber Reinforced Polymer (BFRP), Aramid Fiber Reinforced Polymer (AFRP), Glass Fiber Reinforced Polymer (GFRP), GFRP and CFRP combined (G-C), GFRP and AFRP combined (G-A), BFRP and CFRP combined (B-C), and BFRP and AFRP combined (B-A) were established. Finite element simulation analysis was conducted on seven different FRP bar combinations under static load bending tests. The flexural behavior of the specimens reinforced with different FRP bar combinations and their influencing factors were analyzed. The results showed that using AFRP as the reinforcement material for FRP composite bars in FRP reinforced concrete beams cannot effectively enhance the overall load-carrying capacity of the composite bars. The combination of CFRP with GFRP and BFRP bars significantly increases the stiffness of the FRP bar structure and improves the structural load-carrying capacity of the concrete beams.

Predicting the Output Performance of Triboelectric Nanogenerators Using Highly Representative Data‐Based Neural Networks

Triboelectric nanogenerators (TENGs) are promising potential sustainable power sources for wireless sensing networks within the Internet of Things (IoT) realm. Developing an efficient TENG evaluation model, characterized by high speed, accuracy, and representativeness, facilitates its integration into practical applications, which is urgent and lack of investigation currently. Herein, an artificial intelligence (AI) based evaluation model is developed to predict the performance of freestanding rotational TENGs (FR‐TENGs) for demonstration. An accurate and representative train dataset is essential for development of AI‐based evaluation model, which has been generated using finite element analysis and equivalent circuit simulation alongside the non‐dominated sorting genetic algorithm II. Through comprehensive experiments and simulations, the accuracy of the model has been verified in predicting the power output performance of FR‐TENGs, which has 99.6% (three design parameters) and 99.2% (seven design parameters) maximum train set accuracy. More importantly, the predicted results from the AI‐based evaluation model have notably expanded the coverage of data and significantly expedited the generation time from days to seconds. Herein, the use of AI in assessing the performance of TENGs is enhanced. The TENG design process can be significantly simplified, while maintaining a high evaluation model accuracy, thus promising advancements of IoT applications in future.

Prediction of allowable compression load for notched composite laminates combining FEA simulation and machine learning

Determining the allowable compression load (ACL) of notched composite laminates (NCL) requires consideration of buckling, intra- and inter-laminar damage, which is a costly and repetitive task due to the high dimensional and nonlinear relation of ACL to the numerous design variables. In this work, a high-throughput finite element analysis (FEA) and machine learning (ML) combined approach is proposed to predict ACL of laminates. First, the high-throughput FEA model of NCL covering all of the design variables is generated, and the corresponding critical compression loads in terms of buckling, intra- and inter-laminar damage are obtained. Then, ML models are trained, with inputs being the design variables of NCL and outputs being the critical compression loads. ACL and initial failure mode are determined by the minimum compression load of the three failure modes. Moreover, transfer learning is introduced to laminates with new design variables of new ply number, notch shape and laminate type. By fine-tuning the pre-trained ML model using scarce new data, the fine-tuned models are suitable for new laminates. Consequently, ACL and initial failure mode of notched laminates with various design variables are predicted.

Design and experimental investigation of a positive feedback magnetic-coupled piezoelectric energy harvester

A positive feedback magnetic-coupled piezoelectric energy harvester (PFM) is proposed to address the limitations of current piezoelectric energy collectors, including restricted acquisition direction, limited acquisition bandwidth, and low energy output. Firstly, the dynamic theoretical model of the energy harvester was established, and the optimization factors were explored, providing a solid theoretical foundation for subsequent research endeavors. The energy capture characteristics of rectangular beam and compound trapezoidal beam were compared through finite element simulation analysis. Subsequently, an experimental platform was constructed and an optimized experimental methodology was devised to analyze the energy capture characteristics and enhance the performance of the energy harvester. The results demonstrate that the positive feedback magnetic-coupled PFM with a trapezoidal beam exhibits superior energy capture efficiency. Furthermore, it is observed that the optimized energy harvester possesses wide frequency coverage, multi-directional capabilities, low-frequency adaptability, and facilitates easy vibration. When the 45 kΩ resistor is connected in series and subjected to a longitudinal external excitation amplitude of 0.5 g, it is capable of generating an average voltage and power output of 4.20 V and 0.39 mW respectively at a vibration frequency of 9 Hz. Similarly, when exposed to a transverse external excitation amplitude of 1 g, it can produce an average voltage output of 6.2 V and power output of 0.85 mW at a vibration frequency of 19 Hz. When the inclination angle of the energy harvester is set to 35 degrees, the maximum voltage output occurs at a frequency of 18 Hz and the Z-axis to X-axis force ratio of the energy harvester is 1.428. These research findings can serve as valuable references for piezoelectric energy harvesting applications in self-powered microelectronic systems.

Structural design and experimental research of a micro-feed tool holder based on topology optimization

Abstract. In the present study, a new configuration for a micro-feed tool rest driven by piezoelectric ceramics with a rigid–flexible phase is designed. The flexible driving part of the micro-feed tool rest is optimized using the topology optimization method, which not only improves the driving stiffness, resolution and structural stability but also increases the maximum displacement. The structural stiffness achieved in finite element simulation analysis is 16.28 N µm−1, and the first natural frequency reaches 2521 Hz. A prototype of a piezoelectrically driven micro-feed tool holder and a testing platform are constructed, and the structural stiffness of the prototype is determined to be 15.53 N µm−1 via analysis and testing, resulting in an error of 4.8 % compared with the finite element simulation results. The first-order natural frequency is 2636 Hz given a resolution of 12 nm and a maximum output displacement of 12.983 µm. Compared with the double-parallel flexible hinge, the maximum stroke of the micro-feed tool holder increases by about 5.4 µm and the resolution is improved by about 50 %. The new micro-feed tool holder developed in this paper features a cross-plate-type flexible mobile guiding mechanism. Combining stiffness, maximum travel and displacement resolution, it is applicable to precision and ultra-precision machining.

Engineering Interconnected Nanofluidic Channel in a Hydrogel Supernetwork toward K+ Ion Accelerating Transport and Efficient Sensing.

Ion transportation via the mixed mechanisms of hydrogels underpins ultrafast biological signal transmission in nature, and its application to the rapid and sensitive sensing detection of human specific ions is of great interest for the field of medical science. However, current research efforts are still unable to achieve transmission results that are comparable to those of bioelectric signals. Herein, 3D interconnected nanochannels based on poly(pyrrole-co-dopamine)/poly(vinyl alcohol) (P(Py-co-DA)/PVA) supernetwork conductive hydrogels are designed and fabricated as stimuli-responsive structures for K+ ions. Distinct from conventional configurations, which exhibit rapid electron transfer and permeability to biosubstrates, interconnected nanofluidic nanochannels collaborated with the P(Py-co-DA) conductive polymer in the supernetwork conductive hydrogel significantly improve conductivity (88.3 mS/cm), ion transport time (0.1 s), and ion sensitivity (74.6 mV/dec). The faster ion response time is attributed to the synergism of excellent conductivity originating from the P(Py-co-DA) polymer and the electronic effect in the interconnected nanofluidic channels. Furthermore, the supernetwork conductive hydrogel demonstrates K+ ion selectivity relative to other cations in biofluids such as Na+, Mg2+, and Ca2+. The DFT calculation indicates that the small solvation energy and low chemical transfer resistance are the main reasons for the excellent K+ ion selectivity. Finite element analysis (FEA) simulations further support these experimental results. Consequently, the P(Py-co-DA)/PVA supernetwork conductive hydrogels enriched with the 3D interconnected nanofluidic channels developed in this work possess excellent sensing of K+ ions. This strategy provides great insight into efficient ion sensing in traditional biomedical sensing that has not been explored by previous researchers.

A Magnetic Actuator Device for Fully Automated Blinking in Total Bidirectional Eyelid Paralysis: First Proof of Concept in a Human Participant.

Currently, no solution exists to restore natural eyelid kinematics for patients with complete eyelid paralysis due to loss of function of both the levator palpebrae superioris and orbicularis oculi. These rare cases are prone to complications of chronic exposure keratopathy which may lead to corneal blindness. We hypothesized that magnetic force could be used to fully automate eyelid movement in these cases through the use of eyelid-attached magnets and a spectacle-mounted magnet driven by a programmable motor (motorized magnetic levator prosthesis [MMLP]). To test this hypothesis and establish proof of concept, we performed a finite element analysis (FEA) for a prototype MMLP to check the eyelid-opening force generated by the device and verified the results with experimental measurements in a volunteer with total bidirectional eyelid paralysis. The subject was then fitted with a prototype to check the performance of the device and its success. With MMLP, eye opening was restored to near normal, and blinking was fully automated in close synchrony with the motor-driven polarity reversal, with full closure on the blink. The device was well tolerated, and the participant was pleased with the comfort and performance. FEA simulation results conformed to the experimentally observed trend, further supporting the proof of concept and design parameters. This is the first viable approach in human patients with proof of concept for complete reanimation of a bidirectionally paretic eyelid. Further study is warranted to refine the prototype and determine the feasibility and safety of prolonged use. This is first proof of concept for our device for total bidirectional eyelid paralysis.

High-temperature mechanical properties of additively manufactured 420 stainless steel

Martensitic stainless steels are indispensable alloys in various high stress and temperature applications such as plastic injection molds and components in steam generators. Subtractive manufacturing methods used to fabricate these parts, however, limits its functionality and performance due to design constraint of cooling channels. This limitation can be resolved by means of additive manufacturing while ensuring that acceptable high-temperature properties can be achieved. In this work, the mechanical behavior of additively manufactured 420 stainless steel (AM420SS) is explored through material constitutive modeling to determine the mathematical model that best describes its flow stress in extreme conditions. This is accomplished by subjecting the samples to hot compression under the strain rates of 0.1–1.0 s−1, and temperatures between 973–1423 K (700 °C–1150 °C) via Gleeble thermomechanical test. The experimental data were used to generate the predictive flow stress curves of constitutive models which includes Johnson-Cook, Zerilli-Armstrong, Zener-Hollomon, and Hensel-Spittel equations. Results showed that Zener-Hollomon and Hensel-Spittel models are the most accurate material constitutive equations with relatively high R values of 0.986 and 0.976, and low average absolute relative error values of 6.96% and 7.69%, respectively. The material constants derived from these models can be applied in finite element analysis simulations to assess the performance of using AM420SS parts at high temperature and strain conditions.

Research on Symmetrical Flexible Clamping Conveyor for Scallion Harvester

Aiming at the problems of low conveying efficiency, poor adaptability of conveying Scallion poles of different diameters, and little innovation of the mechanism that exist in the existing clamping conveyor device, a symmetrical flexible clamping conveyor device suitable for Scallion harvesting was innovatively designed. The design and analysis of the overall structure of the clamping conveyor, the clamping mechanism, the clamping pulley and other key mechanisms were carried out, and finally the finite element simulation analysis of the clamping conveyor was carried out, and the analysis of the deformation cloud and stress cloud showed that the designed clamping conveyor could meet the requirements of the working strength. The designed symmetric flexible clamping and conveying device can automatically adjust the clamping force according to the diameter of Scallion stalks to realize efficient and lossless clamping, which is more innovative than the existing clamping and conveying devices.

Integrating Experimental and Computational Analyses for Mechanical Characterization of Titanium Carbide/Aluminum Metal Matrix Composites.

This study investigates the mechanical properties of titanium carbide/aluminum metal matrix composites (AMMCs) using both experimental and computational methods. Through accumulative roll bonding (ARB) and cryorolling (CR) processes, AA1050 alloy surfaces were reinforced with TiCp particles to create the Al-TiCp composite. The experimental analysis shows significant improvements in tensile strength, yield strength, elastic modulus, and hardness. The finite element analysis (FEA) simulations, particularly the microstructural modeling of RVE-1 (the experimental case model), align closely with the experimental results observed through scanning electron microscopy (SEM). This validation underscores the accuracy of the computational models in predicting the mechanical behavior under identical experimental conditions. The simulated elastic modulus deviates by 5.49% from the experimental value, while the tensile strength shows a 6.81% difference. Additionally, the simulated yield strength indicates a 2.85% deviation. The simulation data provide insights into the microstructural behavior, stress distribution, and particle-matrix interactions, facilitating the design optimization for enhanced performance. The study also explores the influence of particle shapes and sizes through Representative Volume Element (RVE) models, highlighting nuanced effects on stress-strain behavior. The microstructural evolution is examined via transmission electron microscopy (TEM), revealing insights regarding grain refinement. These findings demonstrate the potential of Al-TiCp composites for lightweight applications.

Deformation prediction for shot peening of compressor blades based on time sequential loading equivalent residual stress

The compressor blade is a vital component of the aero-engine. This is a curved, thin-walled structural component that may undergo deformation after machining. Deformation prediction is essential for studying the deformation caused by residual stresses in compressor blades. This paper investigates the prediction of deformation caused by residual stresses based on the shot peening time sequential (path and sequence) under actual shot peening conditions. The compressor blade as a target for shot peening and measuring residual stresses on its surface and superficial layers. The equivalent residual stresses after shot peening were calculated based on the principle of equal moments. The equivalent residual stresses were loaded onto the blade model based on the shot peening time sequential in the finite element simulation analysis (FEA) to simulate the deformation. The model’s feasibility was confirmed by comparing the simulated deformation with the measured blade deformation. The shot peening time sequential of the blade was then optimized using this model. The prediction of shot peening deformation of compressor blades based on time-sequential loading residual stresses is a crucial reference value for studying residual stress deformation in blade machining. This study can also be applied to other processes besides shot peening.

Intelligent Space Thermal Control Radiator Based on Phase Change Material with Partial Visible Transparency

Coating structures with dynamically adjustable infrared emissivity are crucial in spacecraft components to cope with the transient thermal environments of space. For a long time, thermochromic phase change materials have been widely used in applications requiring emissivity adjustment, and optimizing the range of adjustable infrared emissivity has always been at the forefront of research. However, reducing the absorption of solar radiation has significant implications for the practical application and thermal stability of spacecraft components in space environments. In this paper, we propose a multilayer film structure based on the phase change material VO2 combined with the materials ZnSe and ITO to achieve low solar radiation absorption and adjustable infrared emissivity for intelligent thermal radiators in space. Through finite element simulation analysis of the structure, we achieve a solar radiation absorption rate of 0.3 and an adjustable infrared emissivity of 0.49. According to Stefan–Boltzmann’s law, the structure exhibits strong radiative heat dissipation at high temperatures and weak energy dissipation at low temperatures to maintain the thermal stability of the device and ensure efficient operation. The intelligent thermal radiator operates based on the principles of Fabry–Perot resonance. Therefore, the multilayer structure based on the phase change material VO2 demonstrates excellent performance in both solar radiation absorption and adjustable infrared emissivity, showcasing its tremendous potential in the field of intelligent thermal control in aerospace.

Structural Optimization of 60T Electric Mining Vehicle Frame: Finite Element Simulation Model and Analysis

Based on the research under the ore loading condition of the electric mine vehicle, this paper measures the physical frame of the 60T electric mine vehicle by means of rangefinder, ruler and drawings, and uses the software CATIA to complete the three-dimensional model of the frame and carriage of the electric mine vehicle, combined with the characteristics of ANSYS workbench software. The structure of the model is simplified. By comprehensively applying relevant knowledge of automobile dynamics, the frame load under full load condition is calculated, and the electric mine vehicle frame is applied by using ANSYS workbench software to simulate and optimize the three conditions of stationary, high-speed driving and turning before the mine car, and the position where the stress concentration and deformation of the frame structure are greatest. By increasing the thickness of the support plate and increasing its stress area, the overall weight was increased by 90.35kg, accounting for 0.9% of the total weight, and the weight increase was very small. Mechanical analysis was carried out on the three working conditions of the optimized frame of the mine car, and the stress was reduced by 25%, 24.1% and 39.2% respectively, effectively eliminating the stress concentration. The actual use of the vehicle can extend the service life of the frame, while improving the economy and stability of the vehicle.

FEA and CFD analysis and optimization of tube in tube heat exchanger for various cases

This research describes the use of advanced simulation techniques to investigate use of different materials for a tube-in-tube heat exchanger. Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) simulations are employed to simulate thermal aspects and optimize the heat exchanger design. The objective is to identify the best-Suitable material combination considering both design and thermal considerations. The findings of this research contribute to the development of more efficient heat exchanger designs.

Biomimetic 3D printing of composite structures with decreased cracking

The development of tissue engineering and regeneration research has created new platforms for bone transplantation. However, the preparation of scaffolds with good fiber integrity is challenging, because scaffolds prepared by traditional printing methods are prone to fiber cracking during solvent evaporation. Human skin has an excellent natural heat-management system, which helps to maintain a constant body temperature through perspiration or blood-vessel constriction. In this work, an electrohydrodynamic-jet 3D-printing method inspired by the thermal-management system of skin was developed. In this system, the evaporation of solvent in the printed fibers can be adjusted using the temperature-change rate of the substrate to prepare 3D structures with good structural integrity. To investigate the solvent evaporation and the interlayer bonding of the fibers, finite-element analysis simulations of a three-layer microscale structure were carried out. The results show that the solvent-evaporation path is from bottom to top, and the strain in the printed structure becomes smaller with a smaller temperature-change rate. Experimental results verified the accuracy of these simulation results, and a variety of complex 3D structures with high aspect ratios were printed. Microscale cracks were reduced to the nanoscale by adjusting the temperature-change rate from 2.5 to 0.5 °C s−1. Optimized process parameters were selected to prepare a tissue engineering scaffold with high integrity. It was confirmed that this printed scaffold had good biocompatibility and could be used for bone-tissue regeneration. This simple and flexible 3D-printing method can also help with the preparation of a wide range of micro- and nanostructured sensors and actuators.

Thermo-mechanical aging of carbon-black reinforced styrene-butadiene rubber under cyclic-loading

PurposeThe research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.Design/methodology/approachThis study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.FindingsThis study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.Originality/valueThis research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.

The Tensile Behavior of Hybrid Bonded Bolted Composite Joints: 3D-Digital Image Correlation versus Finite Element Analysis.

This study examines the behavior of hybrid bolted/bonded (HBB) joints loaded in tensile shear comprising plain weave carbon/epoxy laminates in quasi-isotropic (QI) and cross-ply (CP) layups. It proposes a combined approach of 3D digital image correlation and finite element analysis (FEA) to assess their behavior. To apply the FEA simulation accurately, a single layer of plain fabric was replaced with [0/90]s lamination. Experimental standard open-hole tension test results, as well as only bolted (OB) and HBB, along with FEA predictions, confirmed the accuracy of the substitution method. The FEA, calibrated by experimental results, provides insight into the distinctive characteristics of HBB joints in comparison with bonded and bolted joints. Critical considerations include material properties, damage modeling, adhesive characteristics, and mass scaling. The FEA results underscored the pivotal role of adhesives in HBB joints, rendering them akin solely to bonded configurations. HBB joints retain their geometry better than OB joints with considerably less out-of-plane displacement, following a sinusoidal trend. Moreover, the overall behavior of the two layups demonstrates that CP benefits from having higher strength than QI, especially at the critical hole located closer to the grip side.

A comparison of traditional and net structured intersomatic cages in the lombosacral region: A biomechanical analysis for enhancing discopathy treatment

The vertebral column represents an essential element for support, mobility, and the protection of the central nervous system. Various pathologies can compromise these vital functions, leading to pain and a decrease in the quality of life. Within the scope of this study, a novel redesign of the Intersomatic Cage, traditionally used in the presence of discopathy, was proposed. The adoption of additive manufacturing technology allowed for the creation of highly complex geometries, focusing on the lumbosacral tract, particularly on the L4-L5 and L5-S1 intervertebral discs. In addition to the tensile analysis carried out using Finite Element Analysis (FEA) in static simulations, a parallel study on the range of motion (ROM) of the aforementioned vertebral pairs was conducted. The ROM represents the relative movement range between various vertebral pairs. The introduction of the intersomatic cage between the vertebrae, replacing the pulpy nucleus of the intervertebral disc, could influence the ROM, thus having significant clinical implications. For the analysis, the ligaments were modelled using a 1D approach. Their constraint reaction and deformability upon load application were analysed to better understand the potential biomechanical implications arising from the adoption of the cages. During the FEA simulations, two types of cages were analysed: LLIF for L4-L5 and ALIF for L5-S1, subjecting them to four different loading conditions. The results indicate that the stresses exhibited by cages with a NET structure are generally lower compared to those of traditional cages. This stress reduction in cages with NET structure suggests a more optimal load distribution, but it is essential to assess potential repercussions on the surrounding bone structure.