Design Of Composite Materials Research Articles

Estimation of optimal process parameters for minimum wear in the application of SiC/RHA reinforced Al7075 hybrid composites using ANN, ANFIS, and GA

Increasing demand for high-performance materials has led to the exploration of composite materials for enhanced mechanical properties. In this study, a composite of silicon carbide particulate and rice husk ash (RHA) in varying proportions was utilized to reinforce an aluminum alloy (Al7075) hybrid composite fabricated through the stir casting technique. Microstructure examination via an optical microscope ensured the homogeneous distribution of reinforced particles. Wear was evaluated using a pin-on-disc apparatus, considering material factors (% of SiC and % of RHA) and mechanical wear factors (load applied, speed of rotation, and sliding distance). Experimental data were used to develop artificial neural network and adaptive neural fuzzy inference system models, which demonstrated high predictive accuracy. An objective function, formulated to minimize wear via regression analysis, guided the application of a genetic algorithm to determine optimal process parameters. The optimal combination, resulting in a minimum wear of 34.5 µm, comprised 12% SiC, 7% RHA, a sliding speed of 1.9 m/s, an applied load of 11.5 N, and a sliding distance of 715 mm. This study concludes with recommendations for further research and implications for composite material design and optimization.

Enhanced spectrum prediction using deep learning models with multi-frequency supplementary inputs

Recently, the rapid progress of deep learning techniques has brought unprecedented transformations and innovations across various fields. While neural network-based approaches can effectively encode data and detect underlying patterns of features, the diverse formats and compositions of data in different fields pose challenges in effectively utilizing these data, especially for certain research fields in the early stages of integrating deep learning. Therefore, it is crucial to find more efficient ways to utilize existing datasets. Here, we demonstrate that the predictive accuracy of the network can be improved dramatically by simply adding supplementary multi-frequency inputs to the existing dataset in the target spectrum predicting process. This design methodology paves the way for interdisciplinary research and applications at the interface of deep learning and other fields, such as photonics, composite material design, and biological medicine.

Carbon fiber pull-out analysis for composite materials by considering interface properties

ABSTRACT An improved shear-lag model is adopted in this paper to study the fiber pull-out by considering interface properties in a representative volume element (RVE). The surface roughness, represented by grooves distributed around the fiber, is introduced to analyze the influence of roughness on fiber pull-out comparing it with a round fiber. The influence of groove shapes is also discussed. The interfacial stiffness is introduced in the improved shear-lag model by the cohesive zone modeling to simulate a practical interface connection. To represent the residual stress in composites, a pressure load is added on the surface of the RVE to analyze its influence on the fiber pull-out. The results show that the proposed theory can accurately predict the stress distribution in the RVE. Furthermore, the maximum reaction force increases with an improvement in roughness and interfacial stiffness, while the pressure can improve the reaction force in the third stage of fiber pull-out process. The proposed theory can predict the stress field and fiber pull-out process accurately. It can improve the efficiency and effectivity of micro-experiment with the reference of theoretical results. The results obtained using the proposed theory in this research can also be useful for the design and analysis of composite materials.

High fidelity FEM based on deep learning for arbitrary composite material structure

Due to the outstanding performance, composite materials are widely used and analyzing their properties and designing them based on performance has become a crucial task in the field of many manufacturing industries. Composite materials possess complex multiscale structures, and traditional fine-scale finite element modeling and analysis may lead to severe computational resource challenges. To overcome this difficulty, breakthroughs in key technologies of multiscale accelerated analysis algorithms are required. In this study, an innovative approach based on artificial intelligence and multiscale finite element method is presented. This approach involves partitioning the entire composite material structure into coarse grids that resemble homogenous structures of similar size, providing results consistent to fine-grid finite element analysis. By utilizing CNN for image feature recognition and employing the CGAN adversarial method, coarse-grid equivalent stiffness matrices and multiscale shape functions from completely random microstructures of composite materials can be obtained. Consequently, this enables a rapid response process from microstructure to low-resolution grid to high-resolution physical field, with remarkably accurate physical field results. Moreover, compared to traditional fine-grid finite element methods, this approach significantly reduces memory usage and computation time. This method is applicable to composite materials with varying shaped inclusions, different component properties, and diverse geometric distributions, allowing these materials to perform high-fidelity finite element calculations on coarse grids and predict their mechanical behavior. Furthermore, this breakthrough opens avenues for accelerating the optimization design of composite materials with diverse mechanical functionalities, by employing a bottom-up approach.

A hydrogel-based moist-electric generator with superior energy output and environmental adaptability

Harvesting energy from ubiquitous moisture has emerged as a promising way to collect energy irrespective of location and time. However, the electrical output of moist-electric generators (MEGs) is currently insufficient for practical applications. In this study, a highly efficient electricity-generating film was constructed by combining silicon dioxide (SiO2) nanofibers, sodium alginate (SA) and reduced graphene oxide (rGO) matrix impregnated with calcium chloride. The resulting SA–SiO2–rGO (SSG) film demonstrates a strong moisture-adsorption ability of 1.6 g/g at 80 % RH and 30 °C, and a relatively high ionic conductivity of 1.46 S m-1. The SSG film's strong moisture-adsorption capacity allows rapid ion dissociation, and its excellent electrical conductivity enhances ion migration. Thus, a single centimeter-sized device generates an open-circuit voltage (Voc) of up to ∼0.6 V and a short-circuit current (Isc) of ∼2.24 mA (0.14 mA cm−2). This short-circuit current is more than 10 times those of most reported MEGs. Moreover, an SSG-film-based MEG maintains a voltage output of ∼0.6 V over rather wide ranges of temperature (0–40 °C) and relative humidity (20 %–80 %), demonstrating superior environmental adaptability. In summary, this study provides fresh insights into the design of high-performance composite materials for efficient moist-electric energy conversion.

Optimal Molecular Dynamics System Size for Increased Precision and Efficiency for Epoxy Materials.

Molecular dynamics (MD) simulation is an important tool for predicting thermo-mechanical properties of polymer resins at the nanometer length scale, which is particularly important for efficient computationally driven design of advanced composite materials and structures. Because of the statistical nature of modeling amorphous materials on the nanometer length scale, multiple MD models (replicates) are typically built and simulated for statistical sampling of predicted properties. Larger replicates generally provide higher precision in the predictions but result in higher simulation times. Unfortunately, there is insufficient information in the literature to establish guidelines between MD model size and the resulting precision in predicted thermo-mechanical properties. The objective of this study was to determine the optimal MD model size of epoxy resin to balance efficiency and precision. The results show that an MD model size of 15,000 atoms provides for the fastest simulations without sacrificing precision in the prediction of mass density, elastic properties, strength, and thermal properties of epoxy. The results of this study are important for efficient computational process modeling and integrated computational materials engineering (ICME) for the design of next-generation composite materials for demanding applications.

Multi-electron transfer mechanism and band structures of CNTs in MOF-derived CNTs/Co hybrids for enhanced electromagnetic wave absorption property

Metal-organic framework (MOF)-derived magnetic metal/carbon nanocomposites have received widespread attention for electromagnetic wave (EMW) absorption. The present study introduces a novel approach to MOF composite material design by constructing composites modified with carbon nanotubes (CNTs) and magnetic Co nanoparticles. The carbon confinement effect in CNT/Co not only regulates the electronic structure of Co-C bonds, but also maintains the redox cycle of Co0/2→Co3+→Co0/2+, improving electronic activity and exhibiting synergistic integration characteristics of efficient electromagnetic wave absorption. Particularly, the maximum reflection loss (RLmin) of CNTs/Co-900 reached −52.7 dB at 4.67 GHz in the case of an absorber thickness of 1.6 mm. The excellent microwave absorption performance may be attributed to the interwoven structure formed by novel ZIF-67, CNTs, and Co metal nanoparticles and the double loss of magnetic Co and dielectric CNTs. In addition, the band gap of CNTs was calculated to be Eg = 0.27 eV by the semi-empirical tight-binding method with DFTB+. It is confirmed that CNTs have high electron migration ability, which is beneficial to conductive loss. It is confirmed that CNTs have high electron migration ability, which is beneficial to conductive loss. This study provides a novel strategy for the development of metal-organic framework-based magnetic particles/carbon nanocomposites for electromagnetic wave absorption.

The effect of interfacial properties of PBO fiber surface modified by oxygen plasma on quasi-static and dynamic mechanical properties of monofilament composites

PBO(p-phenylene benzobisoxazole) fibers have great application potentials in various engineering fields while the excessively smooth surface hinders their property to a large extent. In present work, the surface of PBO fiber was modified by oxygen plasma treatment with different power and time, and the epoxy resin composite before and after PBO fiber modification was prepared. The results show that the O/C ratio increases with the introduction of carboxyl group on the surface of PBO fiber. With the increase of plasma treatment power and time, the surface roughness of the fiber surface increases first and then decreases. When the treatment time of 5 minutes under 150 W, the IFSS increases from 21.01 MPa to 56.60 MPa, reaching the optimum property. After modification, the maximum strength of monofilament fiber decreases slightly under quasi-static and dynamic conditions. The results in present work can provide reference for the subsequent structural design of overall composite materials.

Enhanced Visible Light Photocatalytic Activity of Exfoliated Boron‐TiO2 Composite for Degradation of Rhodamine B and Nitrogen Fixation

AbstractThe design of an efficient, recyclable, visible light photocatalytic system was examined as a viable new green way to address environmental challenges such as removal of pollutants from wastewater and N2 fixation. The exfoliated boron (Bexf)‐Titanium oxide (TiO2) composite visible light active photocatalysts were successfully constructed via a simple wet chemical method by utilizing acetone as a solvent. The composite was evaluated for the photodegradation of Rhodamine B (RhB) dye and reduction of N2, which exhibits improved photocatalytic activity for degradation of RhB as well as for reduction of N2. Experiments with different quenchers indicate that the photogenerated superoxide radical anion (O2⋅−) plays a significant role in the degradation of RhB as well as for N2 reduction reactions. The composite catalyst shows good photostability and there is no significant reduction of the catalyst activity for dye degradation up to 4 cycles of reaction. This work affords a significant view into the design of reusable TiO2 composite materials for photocatalytic RhB degradation and nitrogen fixation.

Coupling RGO with magnetic components derived from basic ferric cobalt carbonate (BFCC) for efficient microwave absorption

In this work, reduced graphene oxide (RGO)-based composites loaded with magnetic CoFe2O4 (CFO) and CoFe were successfully synthesized via heat treatment of basic ferric cobalt carbonate (BFCC) under different temperatures. The impact of adding CFO and CoFe on the electromagnetic parameters and absorption properties was investigated. When 40 wt% CFO flakes and CoFe particles are added to the RGO matrix and the filler content is 20 wt% in paraffin, there gives a reflection loss of −48 dB with a 5.5 GHz absorption bandwidth at 2.1 mm thickness, and −50 dB with 4.8 GHz at 2.9 mm, respectively. The coupling of a magnetic medium can change the electromagnetic loss mechanism in the material, which ultimately affects the absorption properties of the material. This study provides a good basis for the design of composite materials of RGO as microwave absorbing materials, enabling large-scale production of high-performance absorption materials.

Fabrication and characterization of graphene oxide (GO)-modified micro-nano composite magnetic microspheres

Addressing the contradiction between the magneto-rheological properties and dispersion stability of MRFs poses a significant challenge in the preparation process. This paper proposes a micro-nano composite material design scheme using graphene oxide as a grafting agent to encapsulate nanoscale magnetite (Fe3O4) particles onto the surface of carbonyl iron powders. The prepared micro-nano composite magnetic microspheres achieve a reduction in density for enhanced stability while ensuring no compromise in magnetic performance. The effectiveness of the preparation process is ensured through the analysis of the microscopic morphology, crystal structure, and elemental characteristics of all process products using Field Emission Scanning Electron Microscopy (FE-SEM), powder X-ray diffraction (XRD), Raman Spectroscopy, and Fourier Transform Infrared Spectroscopy (FTIR). To obtain MRFs more suitable for magneto-rheological damper applications, this study synthesized micro-nano composite MRFs with different base liquids and varying volume fractions. The stability and magneto-rheological properties of each sample were analyzed through visual techniques and rheological testing platforms. The results indicated that micro-nano composite MRFs based on 40% to 50% silicone oil exhibit superior stability in various aspects, including sedimentation stability, redispersion stability, and temperature stability. Additionally, the micro-nano composite MRFs demonstrated significantly enhanced magnetic performance compared to pure micrometer-sized, pure nanometer-sized, and micro-nano hybrid MRFs.

Polymer dispersed cholesteric liquid crystals with combined photo- and mechanochromic response

The development of stimuli-sensitive systems is one of the newest and most promising directions in the field of modern materials science. The combination of various types of sensitivity in the same material opens the possibility of creating complex devices with a wide range of potential applications. This work deals with the design and preparation of new composite materials based on plasticized polyvinyl alcohol (PVA) films containing droplets of cholesteric liquid crystals (CLC). Mechanical stretching of elastic composite films results in a change in optical properties, namely selective light reflection (SLR), from CLC droplets. This in turn transforms the structure and optical properties of the entire polymer matrix. Such a process represents a certain mechano-optic response of the polymer matrix to the influence of mechanical deformation. The introduction of a chiral photochromic dopant into a composite film makes it possible to transform such a film into a photochromic material with the ability to control its optical properties using, for example, UV irradiation. Therefore, mechanical deformation of a polymer composite leads to a change in its optical properties (SLR) caused by a change chiral supramolecular structure of cholesteric mesophase. At the same time, UV irradiation of a polymer film induces E-Z isomerization process in the chiral photochromic dopant, altering its molecular shape and helical twisting power. This enables the using of this process for remote and contactless control of the composite optical properties. In addition, this feature allows one to implement the photopatterning and the recording of a latent image, which appears under the influence of a mechanical field.

Heterostructured SnSe-MnSe@rGO as a composite electrode for Li-ion batteries and high energy density asymmetric supercapacitors

Systematically fabricated hybrid nanomaterials have good outer walls and inherent features, which can significantly improve energy storage capabilities. Herein, we demonstrated the successful preparation of heterostructure SnSe-MnSe nanomaterials anchored reduced Graphene oxide using the hydrothermal method. The SnSe-MnSe@rGO is used as the composite electrode for lithium-ion battery and supercapacitor applications. The SnSe, MnSe, and SnSe-MnSe materials were also prepared and compared their performances with the SnSe-MnSe@rGO material. The first cycle charge/discharge capacity of SnSe-MnSe@rGO was 484.6/641.9 mAhg−1 at 0.1Ag−1 with coulombic efficiency of 75.49 %. After 1000 cycles at 1Ag−1, the SnSe-MnSe@rGO delivered the discharge capacity of 175.7 mAhg−1 at 1Ag−1 with 72.75 % retention of capacity. For supercapacitor application, the SnSe-MnSe@rGO exhibits the battery-type energy storage mechanism and provides a specific capacity of 210. 8 mAhg−1 at 1 Ag−1 with superior rate capability and it withstands 94 % of initial capacity after 5000 GCD cycles at 20 Ag−1 in three-electrode electrochemical cells. The asymmetric type such as activated carbon//SnSe-MnSe@rGO device delivers the capacity of 105.8 mAhg−1 and shows a high energy density of 84.7 Whkg−1 with the power density of 810.5 Wkg−1 at 1 Ag−1. The device holds 89 % of its initial capacity retention after 10,000 continuous GCD cycles at 10 Ag−1. This study emphasizes a comprehensive and fundamental understanding of the reaction mechanisms at the heterostructures, as well as the strategic design of composite materials for constructing advanced electrodes in the realm of sustainable energy storage applications.

Bead-like Co/C@MoS2Composites connected by Multi-Walled carbon nanotubes for high-efficiency electromagnetic wave absorption

This study presents a novel approach to synthesize a composite material composed of bead-like Co/C nanoparticles anchored on MWCNTs, encapsulated by MoS2 nanosheets through a combination of carbonization and hydrothermal treatment using ZIF-67 as the precursor. The resulting composite demonstrates exceptional electromagnetic wave (EMW) absorption performance, with a minimum reflection loss (RL) of −63 dB at a thickness of 2.44 mm and an effective absorption bandwidth (EAB) of 7.2 GHz when RL is below 10 dB together with an expanded EAB of 12.3 GHz (d = 5 mm).The superior absorption capabilities arise from a well-thought-out design of material composition and structure. The synergy of Co/C and MWCNTs enhances ferromagnetic resonance, conductivity, and polarization loss, while sulfur vacancies in MoS2 act as polarization centers, facilitating dipole polarization and efficient conversion of electromagnetic wave energy. The core–shell structure and heterogeneous interfaces introduce various energy loss mechanisms, including multiple polarizations, scattering effects, and dielectric loss. This work introduces a facile method for synthesizing a composite material with outstanding EMW absorption performance. The synergistic combination of unique material components and the carefully engineered structure make this composite a promising candidate for advanced applications in electromagnetic wave absorption technology.

Highly efficient solar-thermal-electric conversion based on asymmetric binary-architecture design in solid-solid composite phase change materials

The application of phase change materials (PCMs) in solar-thermal conversion is largely limited by the inherently inferior thermal conductivity (TC) and poor solar-thermal energy transition capacity of PCMs. Herein, 1,1,1-tri(hydroxymethyl)ethane@melamine foam/cellulose nanofiber/graphene nanoplate (TME@MCGx) shape-stable composite PCMs (ss-CPCMs) are prepared by encapsulating TME into MCGx aerogels. Profited by the effective heat-conducting MCG25 networks, the resulting TME@MCG25 ss-CPCM achieves high TC of 0.73 Wm-1k−1 for internal heat conduction. Meanwhile, the combination of surface photothermal etching and hydrophobic polydimethylsiloxane (PDMS) coating endows the obtained T-TME@MCG25 highly efficient solar-thermal conversation efficiency of 93.1 %, arising from the exposed 3D MCG25 skeletons for absorbing sunlight and the thin PDMS layer for preventing the absorbed solar-thermal energy from radiating and dissipating. Consequently, the solar-thermal-electric (STE) conversion system equipped with T-TME@MCG25 generates the prominent output voltage of 213.0 mV and current of 37.6 mA. Furthermore, the acquired T-TME@MCG25 exhibits remarkable hydrophobicity and self-cleaning performances, due to the micro-nano structures of MCGx skeleton surfaces and the low surface energy of PDMS coating. The design strategy of asymmetric binary-architecture containing 3D photothermal absorption layer and water repellency layer provides a valuable insight into STE energy conversion associated with hydrophobic ss-CPCMs, which can alleviate the looming energy crisis.

Synergy in bio-inspired hybrid composites with hierarchically structured fibrous reinforcements

In response to the global energy crisis, high-performance transportation sectors are rapidly embracing lightweight materials to enhance energy efficiency and sustainability, while grappling with the persistent challenges of developing structural materials that meet stringent safety standards with robust mechanical performance and ease of scalability. Thus, this work presents a combined experimental and theoretical framework to develop a profound understanding of the synergistic effect in hybrid composites with bio-inspired fibrous reinforcements, by elucidating the interfacial interactions across multiple length-scales, encompassing atomic covalent bonding to micro-morphology. A model hybrid composite system, containing a self-assembled fibrous reinforcement consisting of nano-sized Graphene Nanoplatelets (GnP) covalently bonded onto chemically-modified micro-sized Glass Fibers (GF), was utilized to showcase the synergistic effect and highlight its associated mechanisms. The interfacial interactions of the reinforcement were optimized by obtaining the maximum density of covalent bonds, which was achieved with 0.5 wt% GnP for the hybrid composites containing 10 wt% GF, increasing the work of adhesion by 33 %, compared to the biphasic GF composites. The composite’s morphology contains minimal agglomeration with ∼68 % of GnPs oriented with the melt flow, supressing high-stress concentration areas, while the formed crystalline microstructure, with ∼18 % β-crystals, allows the matrix to absorb substantial energy. Furthermore, the increased trans-crystallization encapsulating the hierarchical reinforcement induced nanoscale stiffness variations, increasing rigidity, and forming an ∼16 µm gradient interphase that facilitates load transfer. The greatest synergistic effect observed was ∼54 %, ∼37 %, and ∼75 % for the tensile modulus, tensile strength, and impact strength, respectively. Additionally, a theoretical framework accounting for the synergistic effect was formulated, using a two-step core/shell homogenization model, which shows great potential in expediting the design and optimization of innovative hybrid composite materials.

Research progress on microstructure tuning of heat-resistant cast aluminum alloys

AbstractWith development of present energy-saving society, lightweight and green development in the automotive and aerospace industries have put forward urgent demands for heat-resistant cast aluminum alloys. Present cast aluminum alloys are of lightweight and have excellent mechanical properties when serving in ambient environment. However, when serving at temperatures of 200–300 ℃ or even higher, the alloys inevitably soften and the high-temperature mechanical properties decline rapidly, hardly meeting the requirements for high-performance equipments. This paper summarizes the development process of classic heat-resistant aluminum alloys, especially the microstructural characteristics of heat-resistant cast aluminum alloys in the past decade, and reviews the current microstructure tuning strategies of heat-resistant aluminum alloys from the aspects of intrinsic heat resistance of the second phases, phase interface modification, diffusion-controlled phase transition, grain boundary stabilization and composite material design. Finally, we propose the prospects for the future development of heat-resistant aluminum alloys. Graphical abstract

Study of the Effect of NaOH Treatment on the Properties of GF/VER Composites Using AE Technique.

The purpose of this study is to use acoustic emission (AE) technology to explore the changes in the interface and mechanical properties of GF/VER composite materials after being treated with NaOH and to analyze the optimal modification conditions and damage propagation process. The results showed that the GF surface became rougher, and the number of reactive groups increased after treating the GF with a NaOH solution. This treatment enhanced the interfacial adhesion between the GF and VER, which increased the interfacial shear strength by 25.31% for monofilament draw specimens and 27.48% for fiber bundle draw specimens compared to those before the GF was modified. When the modification conditions were a NaOH solution concentration of 2 mol/L and a treatment time of 48 h, the flexural strength of the GF/VER composites reached a peak value of 346.72 MPa, which was enhanced by 20.96% compared with before the GF was modified. The process of damage fracture can be classified into six types: matrix cracking, interface debonding, fiber pullout, fiber relaxation, matrix delamination, and fiber breakage, and the frequency ranges of these failure mechanisms are 0~100 kHz, 100~250 kHz, 250~380 kHz, 380~450 kHz, 450~600 kHz, and 600 kHz and above, respectively. This paper elucidates the fracture process of GF/VER composites in three-point bending. It establishes the relationship between the AE signal and the interfacial and force properties of GF/VER composites, realizing the classification of the damage process and characterizing the mechanism. The frequency ranges of damage types and failure mechanisms found in this study offer important guidance for the design and improvement of composite materials. These results are of great significance for enhancing the interfacial properties of composites, assessing the damage and fracture behaviors, and implementing health monitoring.

Predictive Behaviour from Finite Element Analysis on PVC-Ducted Reinforced Concrete Column

This research investigated the behaviour of square reinforced concrete columns with embedded PVC pipes, aiming to comprehensively analyze their performance. The study addressed the lack of significant research on the contributions and effects of embedded PVC pipes on structural performance compared to hollow columns. The objectives of the study sought to evaluate the contributions and effects of embedded PVC pipes on the structural performance of columns under loading conditions, determine how the presence of PVC pipes influenced the columns' ability to deform and dissipate energy, and identify the optimal size of PVC pipes to enhance column performance while maintaining stability and safety. Numerical analysis using ABAQUS CEA 2020 software was employed to simulate the behavior of reinforced concrete columns with embedded PVC pipes. The computational model used the same cross-sections with varying diameters of PVC pipes (50mm, 75mm and 100mm). The analysis focused on assessing load-bearing capacities, deformation characteristics, and energy dissipation patterns under axial vertical displacement loading scenario. Findings indicated that PVC-embedded columns exhibit, on average, approximately 0.5% higher load-bearing capacities than Perforated columns. With a composite average of 0.00543 for plastic strains (LE) in PVC-Embedded columns compared to 0.00673 in Perforated columns, a composite average of 5.87E-03 for Equivalent Plastic Strains (PEEQ) in PVC-Embedded columns compared to 7.41E-03 in Perforated columns, and a composite average of 0.0091 for Magnetic Potential Energy (PEMag) in PVC-Embedded columns compared to 0.012 in Perforated columns, collectively suggested that PVC pipes positively impact controlled deformation and energy dissipation. The observed trend is particularly evident in specific instances, with PVC-Embedded-50mm exhibiting a marginal load-bearing increase of approximately 0.2%, PVC-Embedded-75mm indicating an improvement of about 0.5%, and PVC-Embedded-100mm manifesting a load-bearing capacity increase of roughly 0.7%. Overall, these findings highlight that smaller sizes of embedded PVC pipes result in better load-bearing performance. The study recommended meticulous attention to material composition and structural design during PVC-embedded column implementation, careful selection of PVC pipe sizes based on structural requirements and project specifications, further research on dynamic loading conditions to comprehensively understand column behavior, and implementation of stringent quality control measures during manufacturing and construction processes.

An improved proportional topology optimization method combining a polarized material interpolation scheme and Heaviside threshold function

An improved proportional topology optimization (IPTO) method is proposed in this work. The main improvement of this method is that the conventional solid isotropic material with penalization (SIMP)-based material interpolation scheme is replaced by a polarized material interpolation scheme, and the Heaviside threshold function is adopted based on the original proportional topology optimization (PTO) method. By using this approach, the minimum compliance problem can be solved without requiring the numerical derivation of the sensitivity function. To verify the feasibility and effectiveness of the proposed method, two-dimensional (2D) and three-dimensional (3D) cantilevers and L-bracket beams are used as examples. The 2D results obtained by the IPTO method are compared with those obtained by the PTO and SIMP methods. Numerical examples demonstrate that IPTO can acquire better objective function values and more ideal topology structures compared to PTO and SIMP. Furthermore, IPTO offers significant advantages over PTO and SIMP in terms of convergence speed and the ability to suppress intermediate density elements. Additionally, this method enables topology optimization design under multiple working conditions. Therefore, it provides an effective approach for structural topology optimization in research and engineering applications. With appropriate adjustment, this method can also be applied to composite material design and heat conduction design.