Finite Element Analysis Results Research Articles

Computational modelling of historic masonry railroad arch bridges

The problems encountered during the analyzes of structural response of historic masonry railroad arch bridges are described in this paper. The attention is mainly focused on the stiffness of the masonry arches, their strengths and appropriate estimation of railroad load intensity. Issues related to computational modelling of two, existing, almost 130 years old masonry arch railroad bridges are presented in this context. The main properties and results of detailed inspection of the structures are shown. Computational models that were created in the finite element method environment in order to efficiently describe the responses of the bridges under typical loading conditions and estimate their load carrying abilities are presented. The outcomes of several nonlinear static analyses that were conducted for this purpose are discussed. What is more the results of finite element analyses are reviewed against the inspected bridge condition and final conclusions are formulated on that basis. All the analyses allowed to find the possible causes of the deterioration of the bridges condition.

Research on Vertical Bearing Performance of Precast Concrete Pile Reinforced with Cement-Treated Soil under Different Loading Modes

Precast concrete pile reinforced with cement-treated soil (PCRC) is a composite pile formed by inserting a precast concrete (PC) pile into a deep cement mixing (DCM) column. It has become widely recognized and used for soft soil ground treatment. Despite its extensive application, the cooperative bearing mechanism of PCRC has not been fully investigated under diverse loading conditions. This paper presents the results of finite element analysis, comparing the bearing performances of the PCRCs under two loading forms: load applied solely to the PC pile (Form 1) and the entire cross-section (Form 2). The results reveal that the inner and outer cores of the PCRC loaded under Form 2 can synergistically work together, exhibiting a 13.2% higher ultimate bearing capacity than the PCRC with Form 1. The load sharing ratio, μ, of the inner core of the PCRC loaded under Form 2 ranges from 0.86 to 0.93, while μ of the inner core under Form 1 remains stable at approximately 0.96. Increasing the loading plate size improves the DCM column’s load sharing capacity. Furthermore, axial load tests in Form 1 underestimated the bearing capacity of PCRC to a certain extent. It is, therefore, recommended in engineering design that the top of the DCM column be positioned higher than that of the PC pile to achieve the actual force mode of Form 2.

Comparative Study of Mechanical and Electrical Characteristics of High-Strength and Conventional Electrical Steel for EV Traction High-Speed Multilayer IPMSM Using Rare-Earth Free PM

In this article, the electrical and mechanical characteristics of multilayer interior permanent magnet synchronous motors (ML-IPMSMs) using ferrite permanent magnets (PMs) are compared when driven at high speeds with respect to the type of electrical steel. In high-speed operation, the mechanical and electrical characteristics of ML-IPMSMs vary depending on the number of PM layers, PM shape, number of bridges, and bridge thickness. Additionally, ferrite PMs have a lower coercive force than neodymium (Nd) PMs; therefore, irreversible demagnetization (ID) must be considered, and it is affected by the number of PM layers and PM shape of ML-IPMSMs. Thus, when designing a multilayer IPMSM using ferrite PMs for electric vehicle (EV) traction, all characteristics should be considered. Compared to conventional electrical steel (CES), high-strength electrical steel (HSES) offers advantages in mechanical properties, allowing for greater flexibility in ML shape. Consequently, it is possible to design a shape with improved electrical performance when compared to CES by adjusting the ML shape. In this article, all characteristics of each ML-IPMSM using HSES and CES are reviewed via finite element analysis (FEA), and the benefits of HSES applied motors for high-speed driving motors are presented. To verify the validity of the review content in this article, experiments are conducted on the manufactured motor, and FEA results are compared with the test results.

Finite Element Analysis Results and Analysis of Attraction Cases Between Like Poles of NdFeB Magnets

A novel phenomenon of attraction between unequally sized magnet like poles with different permeance coefficients ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P_c</i> ) has been experimentally discovered. This attraction occurs only when a localized region of the low | <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P_c</i> | magnet reverses its polarity, forming an unlike pole region with respect to the high | <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P_c</i> | magnet. The attraction of like pole magnets is caused by the localized demagnetization ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LD</i> ) and is influenced by the factors, including the linearity of the BH curve, magnets’ geometries, and alignment. This paper reports more detailed finite element analysis (FEA) simulation and verification of the experimental results. Additionally, FEA simulation results for other untested unequally sized magnet pairs with various geometries are presented. The factors affecting the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LD</i> level, based on the field/force map from FEA results, are demonstrated. The potential of FEA simulation results for developing novel devices with unequally sized like poles in various applications is emphasized. The results have significant implications for the development of novel magnetic devices with enhanced performance and efficiency.

Machine learning-based stiffness optimization of digital composite metamaterials with desired positive or negative Poisson's ratio

Mechanical metamaterials such as auxetic materials have attracted great interest due to their unusual properties that are dictated by their architectures. However, these architected materials usually have low stiffness because of the bending or rotation deformation mechanisms in the microstructures. In this work, a convolutional neural network (CNN) based self-learning multi-objective optimization is performed to design digital composite materials. The CNN models have undergone rigorous training using randomly generated two-phase digital composite materials, along with their corresponding Poisson's ratios and stiffness values. Then the CNN models are used for designing composite material structures with the minimum Poisson's ratio at a given volume fraction constraint. Furthermore, we have designed composite materials with optimized stiffness while exhibiting a desired Poisson's ratio (negative, zero, or positive). The optimized designs have been successfully and efficiently obtained, and their validity has been confirmed through finite element analysis results. This self-learning multi-objective optimization model offers a promising approach for achieving comprehensive multi-objective optimization.

Performance analysis of aluminium wound double fed induction generator for cost-efficient wind energy conversion systems

Abstract Currently, both limited fossil fuel resources and environmental factors have increased the use of renewable energy sources. Renewable energy resources, such as wind energy systems, are gaining popularity, resulting in increased competition among manufacturers. This study aims to achieve a cost-efficient wind energy conversion system by designing and analysing the performance of a 250 kVA aluminium wound double-fed induction generator (DFIG). The advantages and disadvantages of aluminium windings are compared with those of copper windings, and three DFIG models are created: Model-1 with a copper winding set, Model-2 with the same geometry as Model-1 but designed with an aluminium winding set, and Model-3 with an aluminium winding set and slightly different stator and rotor diameters. The three DFIG models were analysed using finite element analysis (FEA) in ANSYS Maxwell, and the simulation results were obtained. According to the FEA results, Model-1 with copper windings had a higher efficiency than Model-2 with aluminium windings, but Model-2 had better cost and weight performance than Model-1. Model-3 and Model-1 had similar efficiencies, but Model-3 had a slightly greater torque ripple compared to Model-1 because of a slightly different stator and rotor diameter. Although the total machine weight of the aluminium-wound DFIGs was slightly increased, the total manufacturing costs were less than those of the copper-wound DFIGs at the same efficiency levels.

A multi-state fusion informer integrating transfer learning for metal tube bending early wrinkling prediction

Wrinkling is one of the most fatal defects of metal tube bending, which may seriously affect the forming quality and even lead to forming failure. Traditional wrinkling prediction methods fail to provide accurate results due to the complexity of multi-die coupling in the bending process and the neglect of time-varying effects. To this end, a novel early wrinkling prediction method is proposed in this paper, distinct from conventional methods, realizing to forecast future wrinkling trends during the bending process and laying the foundation for real-time wrinkling prediction. It leverages the wrinkling factor (WrF), calculated using the energy method, as temporal data during the bending process to indirectly predict future tube wrinkling trends. Since the wrinkling occurs at the beginning of the bending process, a multi-state informer-based early prediction of tube wrinkling is put forward utilizing the limited WrF collected at the start of the bending process. To meet the demand for high accuracy and efficiency of wrinkling early prediction in a dynamic process, the model pre-trained by the multi-state fusion wrinkling data from the fully bent tube is migrated to the target model through the transfer learning approach. A stainless-steel tube bending case is conducted as the verification experiment, which is simultaneously compared with the finite element analysis (FEA) result. The results show the superior prediction accuracy and higher efficiency of the proposed method mainly compared with the traditional Informer model, Transformer model, and Long Short-Term Memory (LSTM).

Innovative Insights on the Thin Square Plate Large Deflection Problem.

Thin plates subjected to transverse load and undergoing large deflections have been widely studied and published in the literature. However, there is still a lack of information and understanding about the membrane stresses created under large deflections and their associated Airy stress function, as displayed in the well-known von Kármán equations set. The present study aims at providing explicit expressions for the membrane stresses, the deflections, and the Airy stress function for a general square plate area vertically uniformly loaded to reach large deflection state. This was obtained by using the results of a high-fidelity finite element analysis applied on a lateral loaded simply supported thin square plate, which are then casted to yield approximate Fourier series expressions for the membrane stresses, deflections, and the Airy stress function. The stress map figures provide a good understanding of the critical points on the plate, while the explicit mathematical expressions enabled the calculation of deflections and stresses for the entire plate area. Among other interesting findings, the presence of relatively high tensile and compressive membrane stresses existing near the plate edges was revealed, which might lead to potential failure hazards. The derivatives of the deflections and the Airy stress function enabled the validation of the large deflections von Kármán equations set for the investigated case, and it turned out that the generated expressions for the stresses and the lateral deflection based on a high-fidelity finite element model satisfy the second equation with a good accuracy, while the first one remains to further be investigated. Moreover, using the generated explicit equations, the load influence on the deflections and stresses was also analyzed to yield general novel expressions for the medium and very large deflections states. To generalize the investigated case, the stresses and the deflections were non-dimensionalized so they can be used for any material and plate dimensions.

Experimental Study and Numerical Analysis of the Seismic Performance of Glass-Fiber Reinforced Plastic Tube Ultra-High Performance Concrete Composite Columns.

To investigate the impact of the filament winding angle of glass-fiber reinforced plastic (GFRP) on the seismic behavior of GFRP tube ultra-high performance concrete (UHPC) composite columns, this study designs two types of GFRP tube UHPC composite columns. Quasi-static tests are conducted on the specimens subjected to horizontal reciprocating load and axial force, and the skeleton curve characteristics of the structure are analyzed. Furthermore, a finite element analysis model of the composite column is established to explore the effects of the diameter-thickness ratio, circumferential elastic modulus of confined tubes, and tensile strength of concrete on the seismic performance of the composite column. The analysis includes a review of the skeleton curve, energy dissipation capacity, and stiffness degradation of the structure under different designs. The results indicate that the use of GFRP tubes effectively enhances the seismic performance of UHPC columns. The failure mode, peak load, and peak displacement of the composite columns are improved. The finite element analysis results are in good agreement with the experimental results, validating the effectiveness of the analysis model. Extended analysis reveals that the bearing capacity of the specimen increases while the energy dissipation capacity decreases with a decrease in the diameter-thickness ratio and an increase in the circumferential elastic modulus. Although the tensile strength of concrete has some influence on the seismic performance of the specimen, its effect is relatively small. Through regression analysis, a formula for shear capacity suitable for GFRP tube UHPC composite columns is proposed. This formula provides a theoretical reference for the design and engineering practice of GFRP tube UHPC composite columns.

An integrated modeling method for piezo-actuated compliant mechanisms

Piezo-actuated compliant mechanisms are widely employed in precision positioning and micro/nano manipulation due to their advantages of compact structure, high displacement resolution, and fast response. However, it is still challenging to accurately analyze the designed mechanisms due to the complicated coupled electromechanical behaviors of piezoelectric actuators and compliant mechanisms, which prevents further performance improvement by configuration design and optimization. A novel modeling method is developed in this paper for the kinetostatic and dynamic analyses of piezoelectric actuators and their comprised systems with compliant mechanisms. The electromechanical model of piezoelectric actuators is derived from linear piezoelectric vibration theory and further simplified as a practical equivalent model in the form of dynamic stiffness matrices. With the proposed actuator model, an integrated modeling method based on the dynamic stiffness matrix method is proposed for analyses of the piezo-actuated compliant mechanism with complicated configurations of piezoelectric actuators and flexible structures. Two case studies, including a piezoelectric actuator and a fast scanning stage, are analyzed to verify the effectiveness of the proposed approach. Both finite element analysis and experimental results validate that the presented modeling method can be used to resolve the kinetostatics and dynamics of complex piezo-actuated compliant mechanisms efficiently and effectively.

Статична стійкість тришарових панелей із стільниковими заповнювачами, виготовленими адитивними технологіями

This paper presents approaches to and the results of finite-element analysis of static buckling in cylindrical sandwich panels. The core layer of the panels is a polylactide honeycomb core 3D printed using the Fused Deposition Modeling (FDM) additive technology. The two thin face layers are made of carbon fiber reinforced polymer. Such structures are promising for use as structural elements of rockets and drones. For them, the determination of stability under longitudinal and radial loads is an important issue. The global buckling of a cylindrical panel under longitudinal loads and the local buckling of a honeycomb core as a plate structure under radial loads are studied. The geometrically nonlinear deformation of a cylindrical panel under a combination of transverse and radial loads is studied. Seven cylindrical sandwich panels with the radius-to-thickness ratio in the range 5 ? R/h ? 50 and a sandwich plate are considered. The effect of the radius of curvature on the characteristics of local and global buckling is investigated. The problem is solved by the finite element method using the ANSYS software system. The convergence of the finite element model was investigated. For this purpose, a strained state under the action of a longitudinal load was studied. The finite-element mesh parameters were selected to ensure the convergence of the results. Two finite element models, an “exact” one and an “approximate” one, were constructed to investigate global buckling under longitudinal loads. The «exact» model includes a honeycomb core represented by its geometry. In the «approximate» model of the sandwich panel, the honeycomb core is replaced with an equivalent homogenized layer. It was found that for longitudinal loads the modes of the global buckling of the cylindrical sandwich panels and the sandwich plate under study are almost the same. It was shown that the critical loads obtained by the «exact» and the «approximate» model are close. It was found that when a cylindrical panel is deformed under the action of a combination of longitudinal and radial subcritical loads, the calculated results for the «exact» and the «approximate» model are close. Therefore, longitudinal buckling can be considered using the homogenized model, which is much simpler in terms of computations.

Axial Compression Behavior of Composite Sandwich Panel with Mixed Recycled Coarse Aggregate Concrete

The coarse aggregate produced from the construction and demolished waste of masonry structure is called mixed recycled coarse aggregate (MRA), which is mainly composed of concrete recycled coarse aggregate (CRA) and brick recycled coarse aggregate (BRA). The paper presents the results of an experimental and numerical study of concrete composite sandwich panel made with MRA. The composite sandwich panel with MRA (CSPMRA) were tested under axial compression to investigate the influence of concrete mix proportion, thickness of insulation board and added edge frame on the load-displacement curve, load-strain curve, vertical displacement, ultimate bearing capacity and failure mode of CSPMRA. Results of the experimental and finite element analysis (FEA) were compared with the results based on Chinese code, ACI design equation and other empirical equations developed by researchers which might be applicable to predict the ultimate load of sandwich panels. A semi-empirical equation was proposed to better fit the experimental and the FEA results.

Stress Intensity Factors for Pressurized Pipes with an Internal Crack: The Prediction Model Based on an Artificial Neural Network

During pipeline operation, internal cracks may occur. The severity around the crack tip can be quantified by the stress intensity factor (KI), which is a linear–elastic fracture mechanics parameter. For pressurized pipes featuring infinitely long internal surface cracks, KI can be interpolated from a function considering pressure, geometry, and crack size, as presented in API 579-1/ASME FFS-1. To enhance KI prediction accuracy, an artificial neural network (ANN) model was developed for such pressurized pipes. Predictions from the ANN model and API 579-1/ASME FFS-1 were compared with precise finite element analysis (FEA). The ANN model with an eight-neuron sub-layer outperformed others, displaying the lowest mean squared error (MSE) and minimal validation discrepancies. Nonlinear validation data improved both MSE and testing performance compared to uniform validation. The ANN model accurately predicted normalized KI, with differences of 2.2% or lower when compared to FEA results. Conversely, API 579-1/ASME FFS-1′s bilinear interpolation predicted inaccurately, exhibiting disparities of up to 4.3% within the linear zone and 24% within the nonlinearity zone. Additionally, the ANN model effectively forecasted the critical crack size (aC), differing by 0.59% from FEA, while API 579-1/ASME FFS-1′s bilinear interpolation underestimated aC by 4.13%. In summary, the developed ANN model offers accurate forecasts of normalized KI and critical crack size for pressurized pipes, providing valuable insights for structural assessments in critical engineering applications.

On shear adhesion of adhesive fibrils

Natural fibrillar adhesives, widely recognized for their strong and reversible adhesion, have inspired the development of numerous synthetic adhesive systems applied in diverse fields. These biological and bioinspired adhesive fibrils exhibit a wide range of aspect ratios spanning four orders of magnitude. Accurate prediction of their adhesion performance is crucial for their practical applications. Prior investigations have primarily focused on adhesion under normal loading, although shear loading is also commonly encountered in various scenarios. To date, only a few shear adhesion models exist, and they are limited to either high or low aspect ratios. Rigorous mechanics analysis of adhesive fibrils’ shear adhesion strength across a wide range of aspect ratios is lacking. In this study, we developed a mechanics model based on the compliance method for evaluating the energy-controlled interfacial failure of the adhesive fibrils, estimated the shear adhesion strength of a lap shear system across a wide range of fibrillar aspect ratios, and carried out the finite element analysis (FEA) to validate the model prediction. Our model reveals that, depending on the fibrillar aspect ratio, the adhesive fibril exhibits three distinct deformation regimes: thin film shearing, thick block shearing, and slender beam bending. The important parameters governing the shear adhesion of the lap shear system are the aspect ratio of fibrils, elastic moduli of the fibrils and substrates, while the Poisson's ratio of fibrils has no noticeable effect. Our model captures the shear compliance across a wide aspect ratio range from 10−4 to 102 accurately and is in excellent agreement with the FEA results. Based on this compliance solution, a rigorous scaling law for shear adhesion strength is derived, which can predict the energy-controlled adhesion regime as well as the theoretical strength-limited regime, as the aspect ratio decreases. These results reveal the underlying mechanisms governing the shear adhesion strength of fibrillar adhesives and provide guidance for future design and optimization of fibrillar adhesives.

Model test and finite element analysis results of a monopile in very dense sand under unidirectional horizontal cyclic loading

This study is carried out to understand the response of a monopile for a large (8–9 MW) offshore wind turbine located at a 45m water depth under lateral cyclic loading. Firstly, a 1g large-scale model pile test was performed in saturated very dense sand under numerous cycles of lateral loading, N=2000. The test results show that the lateral pile head displacement and rotation increase while the secant stiffness of pile decreases with increasing N. The numerical model was then validated by comparing the pile head displacement results of the test and the finite element (FE) model analysis. The soil was modelled using the UBC3D-PLM constitutive model to understand the development of the excess pore pressure ratio (EPPR) around the monopile. The FE analysis was performed cycle by cycle up to N=5 for a large diameter “XL monopile” with diameter D=9m and embedded length L=50m. The results showed that the EPPR around the monopile is insignificant. Furthermore, the effect of the number of loading cycles on the evolution of the EPPR, pile head deformation and pile head rotation are insignificant. In addition, a relatively high maximum pile head rotation accumulation θmax≅0.13° was obtained during cyclic loading.

Optimal Design Method of Post-Assembly Magnetizing Device with Field–Circuit Coupling Analysis

Post-assembly magnetization can significantly simplify the manufacturing of the rotor of permanent magnet (PM) electrical machines. The optimization of the post-assembly magnetizing device using finite element analysis (FEA) is time-consuming; therefore, a globally optimal solution aiming at achieving an adequate magnetizing level and minimal energy consumption is difficult to achieve. In this paper, a field–circuit coupling analysis (FCCA) model is proposed to optimize the auxiliary stator-type magnetizing device for interior permanent magnet synchronous machines (IPMSMs). A reasonable simplification of the highly saturated magnetic circuit is made based on FEA results so that the magnetic equivalent circuit (MEC) model can be established. On the other hand, the eddy currents in the PMs are equivalent to an eddy current short-circuit; thus, by converting the field calculation into a circuit calculation, the time cost can be reduced significantly, which greatly improves the speed of multi-objective optimization of the magnetizing device with multiple degrees of freedom. A V-type IPMSM is taken as a study case, and its post-assembly magnetizing device is optimized with the proposed method. FEA and experimental results show that the PMs are fully magnetized, while the required energy consumption is greatly reduced when compared with an existing magnetizing device.

Study of blister phenomena on polymer liner of type IV hydrogen storage cylinders

Type IV hydrogen storage cylinder is a rising high-pressure hydrogen storage equipment, which is composed of a polymer liner and a fully wrapped carbon fiber composite. It is found that local blisters occur on polymer liners after rapid depressurization tests during the research and development process. Some manufacturers choose to add adhesives at the liner-composite interface to avoid blisters. In order to study the effect of adhesives to the local blisters, two type IV cylinders have been manufactured and tested, in which one has adhesives at the interface and the other does not. The depressurization tests were conducted from around 70 MPa–2 MPa under various mass flow rates. Digital radiography (DR) and videoscope have been used to conduct post-test inspections. Finite element analysis (FEA) was performed to verify the effect of adhesives, as well as estimating the pressure differential at the interface based on test results. According to the results of the test and FEA results, the use of adhesives at the interface does not effectively prevent the occurrence of local blisters. However, it does serve to slow down the blister propagation though. The results also indicate that the mass flow rate plays a crucial role in affecting the size of the local blister. Furthermore, based on the test and FEA results, an estimation of the local pressure differential at the interface that causes local blister was made. During the post-test inspection, it was observed that the size of several blisters initially increased but eventually decreased over time. Additionally, adjacent blisters were observed to merge as a single larger blister after the hydrostatic test. These results provide valuable insights into the formation and behavior of local blisters, which can inform future research and practical applications in relevant fields.

Further investigation of two-parameter J-A estimation for clamped SET specimens

Based on the J-A two-parameter characterization, this paper presents a systematic study of the crack-tip constraint for clamped single-edge notched tension (SET) specimens. Extensive finite element analyses (FEA) are conducted to obtain the A solutions for the modified boundary layer (MBL) model and the SET specimen. The material used in the analysis is the Ramberg-Osgood power-law material, with varying yield stress and strain hardening exponents. Based on previous studies, the T-stress-related A solutions for MBL problems under small-scale yielding conditions are obtained from FEA results, and the A solutions for the SET specimen are found to scale with normalized applied load under large-scale yielding conditions. By summing up these two solutions, the total A for the SET specimen can be estimated, covering the entire range from small-scale to large-scale yielding conditions. A key geometry factor is introduced as a function of material properties, crack depths and applied load. Some fitting equations are proposed in this estimation method, and a Python program is developed to quickly and accurately obtain the total A for the SET specimen. The results of the present study show good agreement for all the simulated cases. The proposed solutions of constraint parameter A can be used to establish the constraint-corrected J-R curve for SET specimens.

Inverse design of polymer alloys using deep learning based on self-consistent field analysis and finite element analysis

In this study, a framework that deals with the inverse design of material structures based on macroscopic properties using deep learning models is proposed. For the framework, “polymer alloy’s phase separation structures” as material structures and “stresses” as macroscopic properties are considered. The results of self-consistent field analysis are used as structure data, in particular, the analysis result of two-dimensional phase separation structures of a diblock copolymer melt in the equilibrium state. For the stress data, the results of finite element analysis are used, in particular, the analysis results of average stresses over the system under the small-enforced-displacement condition. This framework consists of two deep learning models—one aimed at generating phase separation structures, and the other at predicting properties from structures. For the second model, we incorporate a convolutional neural network. By implementing a random search toward a model that combines these two deep learning models, we constructed the framework for the inverse design of phase separation structures that possess desired macroscopic properties. This framework is demonstrated to be able to suggest phase separation structures that realize desired stresses that are input to the framework through examples. The innovation of the method is the development of framework to propose the optimal structure of polymer alloys by using machine learning. The main novelties of this method are the construction of generative adversarial network that reproduces the phase-separation structure of polymer alloy specified by label information, realization of inverse analysis based on mechanical properties, and the simultaneous optimization of multiple mechanical properties.

Revolutionary auxetic intravascular medical stents for angioplasty applications

Due to the significant mortality rate associated with atherosclerosis-induced cardiovascular disease, the utilization of advanced intravascular stents with superior mechanical performance is imperative for the restoration of obstructed arteries. This study proposes novel auxetic medical stents that aim to enhance critical parameters of biomedical stents. This includes load-bearing capacity, expanded opening percentage, and reduced recoil percentage. On this matter, the missing rib auxetic unit cell has been considered and geometrically modified to achieve these objectives. Two-dimensional (2D) metamaterials were fabricated through additive manufacturing technique and subjected to experimental testing. Then, finite element analysis (FEA) was employed to gain comprehensive insights into the mechanical behaviour of the proposed medical stents. Remarkably, an excellent correlation was observed between the FEA and experimental results, validating the high precision of the analysis. The findings reveal that the stents classified as “E-category” exhibit the highest final opening percentage while concurrently demonstrating the lowest recoil percentage. The base stent exhibited a relatively high recoil percentage of 15.56%, indicating a significant amount of recoil or spring-back after deformation. In contrast, the modified “E-category” stent displayed a substantially lower recoil percentage of 1.62%. This notable reduction in recoil percentage indicates that the modifications made to the rib-unit cells had a significant and beneficial effect on the stent's recoil behaviour and minimizing potential damage to arterial tissue during stent deployment (angioplasty) and balloon pressure. The modified design likely enhances the stent's ability to maintain its shape and resist recoil, making it more effective and reliable in its intended application. Additionally, more aspects of biomedical stents such as foreshortening, and dog-boning of the modified missing rib stents were meticulously examined through FEA.