Reinforced Polymer Composite Materials Research Articles

Unveiling the untapped potential of Hibiscus Rosa-sinensis lignocellulosic fiber: A multifaceted characterization for advancing sustainable biocomposite applications

In the pursuit of sustainable advancements in bio-inspired fiber reinforced polymer composite materials, the exploration of novel natural fibers has become a focal point of research. This experimental study aims to elucidate the unexplored potential of Hibiscus Rosa-sinensis fiber (HRF) as a versatile reinforcement material for high-performance composites. Through an integrated approach, this research offers a meticulous analysis of the HRF's physico-chemical properties, and single fiber tensile strength. The crystalline structure are revealed by X-ray diffraction (XRD), thermal behavior are characterized through thermo-gravimetric analysis (TGA), and surface morphology has been visualized using field emission scanning electron microscopy (FESEM) studies. From the results, it is found that the HRF contains a cellulose content of 79.50 %, positioning it as a prime bast fiber among its counterparts. This composition is complemented by hemicellulose (10.36 %), lignin (4.62 %), wax (0.84 %), and ash (2.96 %). The Fourier-transform infrared spectroscopy (FTIR) spectra unveils the intricate functional groups present in the fibers. XRD analysis highlights a crystallinity index (CI) of 66.93 %, confirming a well-organized and structured crystalline arrangement. The thermal stability established through TGA underscores HRF's resilience up to 284 °C, presenting it is an optimal reinforcement material for bio-inspired green composites operating within 280 °C. The surface morphology of HRF is examined through FESEM and three-dimensional profiling, showcasing its inherent morphological intricacies. The multidimensional characterization provided herein contributes significantly to the evolving landscape of biocomposite research, fostering a platform for future advancements and innovations in HRF-based composite materials.

Effect of radiation-induced graft polymerization onto pineapple nonwoven fabric reinforced polymer composite

Natural fiber-reinforced polymer composites are gaining attention for their environmental benefits, such as biodegradability and reduced carbon footprint, as well as the potential of the natural fibers to replace or partially substitute synthetic fibers in various applications. However, challenges, such as poor interfacial adhesion and moisture absorption, limit the effectiveness of natural fibers, such as pineapple nonwoven fabric (PNWF) as reinforcement materials in polymer composites. To address these challenges, this study aims to enhance the properties of PNWF through glycidyl methacrylate grafting via radiation-induced graft polymerization. A 22 factorial design was employed to assess the effects of absorbed dosage and monomer concentration on the properties of the grafted PNWF. Infrared spectroscopy and electron microscopy analyses confirmed successful grafting. The grafted PNWF exhibited improved thermal stability and mechanical properties. The resulting composites showed significant enhancements in tensile and flexural strength, specifically, with tensile strength increase ranging from 23.32 to 34.49 MPa and flexural strength from 39.14 to 54.59 MPa. Additionally, the tensile modulus ranged from 0.77 to 1.29 GPa, while the flexural modulus varied from 1.17 to 2.06 GPa. These findings highlight the potential of PNWF grafted with polyglycidyl methacrylate (PNWF-g-PGMA) as an effective reinforcement material for various applications.

Highly thermal conductivity polymer composites reinforced by BNNS/UHMWPE fabric for reliable electronic thermal protection and management

With the rapid development of 5G communication and microelectronics technology, the heat accumulation of high-power electronic devices puts forward an urgent demand for high thermal conductivity (TC) composites. However, it's still a great challenge through electrically insulating polymer to achieve good comprehensive performance of high TC, flexibility, and safety reliability. Herein, ultra-high molecular weight polyethylene (UHMWPE) fabric was coated with boron nitride nanosheets (BNNS) by dispersion and interfacial reinforcement of cellulose nanofibers (CNFs), and the BNNS/UHMWPE fabric-reinforced polymer composite (B/UF-PC) with 3D continuous thermal pathway was obtained by further composite with polydimethylsiloxane (PDMS). The continuous thermal pathways of highly aligned UHMWPE fibers in the fabric and the synergistic effect of the BNNS network enhance the out-of-plane and in-plane TC to 6.02 and 11.78 W/m K, respectively. Moreover, B/UF-PC exhibits flexible, lightweight (0.89 g/cm3), and significantly higher tensile strength (87.40 MPa) and energy absorption efficiency (98 %) than those of polymer composites, which allows it to be used in reliable electronic thermal management to prevent heat accumulation and external mechanical impact. This work provides a strategy for efficiently preparing flexible polymer composites with high TC and insulation properties.

Influence of Milled carbon fiber MCF on mechanical and dynamic mechanical behaviour of carbon fiber fabric reinforced polymer composites

Carbon fiber reinforced polymer (CFRP) composites are widely used in engineering applications. Better understanding about the thermo mechanical properties of CFRP composites are essential for their development. Static and dynamic mechanical properties of CFRP composites can be modified by the filler materials loaded on it. This study investigates the effect of Milled Carbon Fiber (MCF) filler reinforcement on flexural and thermo-mechanical properties of CFRP composites. Fabricated composites are quasi isotropic laminates with unidirectional carbon fibers. The composite laminates were fabricated by hand lay-up technique. XRD analysis illustrates that all the processed specimens are in non-crystalline nature. Three-point bending mode is followed to evaluate the flexural and Dynamic Mechanical Analysis (DMA) tests. MCF fillers are loaded at 6 wt%, 8 wt%, 10 wt%, 12 wt% to evaluate above mentioned properties, i.e, Flexural Strength and Break strain were found from flexural analysis. Storage Modulus (E'), Loss Modulus(E’'), under varying temperature and glass transition temperature (Tg) were determined from DMA. The test results indicated that, 8 wt% of MCF filler loading improves the static and dynamic mechanical properties of CFRP composites when compared to 10 wt% and 12 wt% of MCF content.

A finite crack growth energy release rate for interlaminar fracture analysis of composite material at different temperatures

The interlaminar fracture toughness of unidirectional fiber reinforced polymer composite material is temperature and crack growth history dependence. The non-constant interlaminar fracture toughness challenges the wide application of the linear elastic fracture mechanics-based approach for analyzing the interlaminar crack growth in composite material and structures. In addition, a quantitative relationship between the ductility of the matrix and interlaminar fracture toughness of the fiber reinforced composite is still highly desirable. In this paper, both pure resin and composite double cantilever beam (DCB) are tested at different temperatures. A finite crack growth energy release rate is used to analyze the interlaminar crack growth behavior of composite material at different temperatures. The plasticity of the composite DCB is modeled by Hill’s anisotropic plasticity, with the properties determined from multiscale analyses. It is found that a single constant finite growth energy release rate can well predict the interlaminar mode I crack growth of composite material at different temperatures. The roles of the ductility of matrix, thickness of the DCB, and crack growth history on the interlaminar mode I fracture toughness of composite material are quantitatively determined by using the present method.

Dynamic Behavior and Permanent Indentation in S2-Glass Woven Fabric Reinforced Polymer Composites under Impact: Experimentation and High-Fidelity Modeling

This paper studies the behavior of S2-glass woven fabric reinforced polymer composite under low-velocity impact at 18–110 J energy. A macro-homogeneous finite element model for the prediction of their response is implemented, considering the non-linear material behavior and intralaminar and interlaminar failure modes for the prediction of impact damage. The model accurately predicted the permanent indentation caused by impact. By applying the Ramberg-Osgood formulation, different initial stiffness values are examined to assess the post-impact unloading response. This approach reveals the significant role of initial stiffness in inelastic strain accumulation and its consequent effect on permanent indentation depth. A higher initial stiffness correlates with increased inelastic strain, influencing the impactor rebound and resulting in greater permanent indentation. By accurately predicting permanent indentation, and damage accumulation for different impact energies, this study contributes to a better understanding of the impact behavior of composite materials, thereby promoting their wider application.

Modelling and optimization of hybrid Kevlar/glass fabric reinforced polymer composites for low-velocity impact resistant applications

Kevlar and glass-based fabric-reinforced polymer composites possess excellent impact resistance, corrosion and high specific strength properties which makes them suitable candidature for the fabrication of industrial helmets, riot shields, automobile parts etc. The polymer composite components are prone to impact failure, which restricts their wide commercial usage. In this work, to enhance the impact damage resistance of polymer composite laminates, a hybridized material model consisting of glass and Kevlar fabric was employed. The hybridization of Kevlar ‘K’ with glass ‘G’ fabric [K/K/G/G/K] results in a cost reduction of 32 % without any significant variation in performance when compared to non-hybrid Kevlar fabric-based composite laminate [K/K/K/K/K]. In comparison to plain glass fabric laminates [G/G/G/G/G], the [K/K/G/G/K] configuration exhibits a significant 16.68 % improvement in energy absorption. This improvement is rooted in a parametric study and optimization process employing the Preference Selection Index (PSI) technique to determine the optimum stacking sequence of fabrics within the composite laminate. In addition, it evaluates the projectile limit velocity necessary to prevent failure and assesses the total deformation for an optimized stacked [K/K/G/G/K] composite, taking into account various projectile shapes conforming to low-velocity impact applications. The results of this study provide valuable insights into the properties and capabilities of the hybrid composite laminate and may pave the way for the development of more effective materials for impact protection in various applications.

Exceptional mechanical performance by spatial printing with continuous fiber: Curved slicing, toolpath generation and physical verification

This work explores a spatial printing method to fabricate continuous fiber-reinforced thermoplastic composites (CFRTPCs), which can achieve exceptional mechanical performance. For models giving complex 3D stress distribution under loads, typical planar-layer based fiber placement usually fails to provide sufficient reinforcement due to their orientations being constrained to planes. The effectiveness of fiber reinforcement could be maximized by using multi-axis additive manufacturing (MAAM) to better control the orientation of continuous fibers in 3D-printed composites. Here, we propose a computational approach to generate 3D toolpaths that satisfy two major reinforcement objectives: (1) following the maximal stress directions in critical regions and (2) connecting multiple load-bearing regions by continuous fibers. Principal stress lines are first extracted in an input solid model to identify critical regions. Curved layers aligned with maximal stresses in these critical regions are generated by computing an optimized scalar field and extracting its iso-surfaces. Then, topological analysis and operations are applied to each curved layer to generate a computational domain that preserves fiber continuity between load-bearing regions. Lastly, continuous fiber toolpaths aligned with maximal stresses are generated on each surface layer by computing an optimized scalar field and extracting its iso-curves. A hardware system with dual robotic arms is employed to conduct the physical MAAM tasks depositing polymer or fiber reinforced polymer composite materials by applying a force normal to the extrusion plane to aid consolidation. When comparing to planar-layer based printing results in tension, up to 644% failure load and 240% stiffness are observed on shapes fabricated by our spatial printing method. We demonstrate the versatility of our approach through various complex load cases which demonstrate their successful implementation of continuous fiber printing in 3D.

Investigation of the features of destruction of fillers of structures made of reinforced polymer composite materials

The paper presents the results of experimental studies of the destruction of fillers of polymer composite materials (PCM) with the control of acoustic emission (AE) signal parameters. As object of research were considered silica filaments К11С6-180, carbon filaments UKN-M-12K-1-7-380 and aramid technical fiber Rusar-С600 type А. Based on the experimental data obtained, acoustic emission portraits of the destruction processes of various types of PCM fillers were obtained. This allows, when loading a structure made of PCM with AE control, to fix the destruction of the filler, and, consequently, to increase the reliability and safety of operation of products made of PCM.

Tribological properties of CNT-filled epoxy-carbon fabric composites: Optimization and modelling by machine learning

Polymer matrix composites reinforced with fibers/fillers are extensively used in several tribological components of automotive and boating applications. The mechanical performance of polymer composites improves by incorporating nanofillers as secondary reinforcement. The present research work fabricated carbon fabric-reinforced epoxy composites using the hand layup. The carbon fabric-reinforced polymer composites were fabricated with 0.1 wt%, 0.2 wt%, and 0.5 wt% of carbon nanotubes (CNT) fillers as secondary reinforcement. Tribological properties of carbon fabric-reinforced epoxy composites filled with CNT have been carried out using a pin‐on‐disc method. Adding fillers significantly improves the tribological behaviour of the carbon fabric-reinforced epoxy composites by reducing wear rate and coefficient of friction. The large surface area of interaction due to the higher aspect ratio of CNT shows improved adhesion between epoxy matrix and carbon fabrics. It improves the various mechanical and tribological characteristics of composites—also, an analysis of worn surfaces is carried out to analyze the wear mechanisms using scanning electronic microscopy. The research employs a combination of experimental analyses and machine learning (ML) techniques to explore the wear resistance, hardness, and predictive modeling of volume loss in the composites. The hyperparameter fine-tuning of ML algorithms, including Random Forest (RF), k-Nearest Neighbors (KNN), and XGBoost, demonstrates superior predictive capabilities, particularly with RF. The study bridges material science, ML, and practical applications, contributing valuable insights for developing advanced composite materials.

Dynamic reversible mechanism of phenol-carbamate bonds and their potential for the development of thermo-healing, recyclable and high-performance epoxy thermosets

In this paper, a series of small monomers were synthesized to explore the dynamic reversible properties of phenol-carbamate bonds (PCBs), and the bimolecular exchange mechanism of PCBs was verified. Based on this mechanism, a novel thermo-healing recyclable epoxy resin with high mechanical performance and shape memory function was successfully developed. Meanwhile, the number of reversible phenol-carbamate bonds in this system was increased by molecular structure design, which increased the chance of reversible cleavage and recombination of the dynamic covalent bonds. Compared with our previous work, the thermo-healing efficiency of the epoxy thermosets was greatly increased, and the target polymer achieved an excellent balance between high thermo-healing efficiency and good mechanical performance. Further post-treatment experiments show that the cured epoxy resin can also be well recycled by solvent degradation or hot-pressing process. What's more, a novel carbon fiber (CF) reinforced polymer composite material was synthesized by taking that prepared epoxy thermoset as a matrix, which greatly improve the mechanical properties of epoxy resin, and the CF cloths can be recycled when the epoxy resin is removed by chemical degradation. In addition, due to the existence of reversible crystallizable switching segments in the epoxy resin system, when the temperature is above its Tg, it can be triggered by thermal energy, so that the film can rapidly recover from the temporary shape to the permanent shape. This study also provides a new direction for the development of novel multifunctional intelligent polymers.

Flexible photonics in carbon and glass fiber reinforced polymers for new multifunctionality: Exploring the advances, challenges, and opportunities

Flexible photonics, characterized by their planar design and integrated features, have surfaced as a promising technology to unlock new possibilities for multifunctionality within fiber reinforced polymer composite materials. A comprehensive review of current progress, challenges, and opportunities associated with flexible photonic integration into carbon and glass fiber reinforced polymers is provided. A systematic examination of the literature has revealed several flexible photonic technologies that have demonstrated potential for integration in composite components to monitor performance in manufacture, service, and reuse. The review highlights the advantages and limitations of the current state-of-the-art in flexible integrated photonics for making assessments of compatibility with carbon and glass fiber reinforced polymer structures. By examining proof-of-concept demonstrations, the improved performance and novel functionalities that can be achieved for industrial applications are identified. The challenges associated with the integration process, such as durability and scalability are discussed in the context of the manufacturing processes required to create composite components. The concept of integrating flexible photonics in composite structures is relatively new, hence the paper closes by highlighting opportunities for further research and development in this field.

Fabrication of continuous woven E-glass fiber composite using vat photopolymerization additive manufacturing process

PurposeThe industrial application of continuous glass fabric-reinforced polymer composites (GFRPCs) is growing; however, the manufacturing boundedness of complex structures and the high cost of molds restrict their use. This research proposes a three-dimensional (3 D) printing process for GFRPCs that allows low-cost and rapid fabrication of complex composite parts.Design/methodology/approachThe composite is manufactured using a digital light processing (DLP) based Vat-photopolymerization (VPP) process. For the composites, suitable resin material and glass fabrics are chosen based on their strength, stiffness, and printability. Jacob's working curve characterizes the curing parameters for adequate adhesion between the matrix and fabrics. The tensile and flexural properties were examined using UTM. The fabric distribution and compactness of the cured resin were analyzed in scanning electron microscopy.FindingsThe result showed that the object could print at a glass fabric content of 40 volume%. In DLP-based VPP printing technology, the adequate exposure time was found to be 30 seconds for making a GFRPC. The tensile strength and Young's modulus values were increased by 5.54 and 8.81 times, respectively than non-reinforced cured specimens. The flexural strength and modulus were also effectively increased to 2.8 and 3 times more than the neat specimens. In addition, the process is found to help fabricate the functional component.Originality/valueThe experimental procedure to fabricate GFRPC specimens through DLP-based AM is a spectacular experimental approach.

Experimental and hydrodynamic methods to determine aqueous dispersion of discontinuous reclaimed carbon fibres

In this study, the dispersion of reclaimed carbon fibres following cost-effective surface treatment is explored with a hydrodynamic fibre moving model, and a practical fibre dispersion effect is investigated through various physical dispersion methods. To utilise reclaimed carbon fibres for a desired composite product, our proposed low-cost surface treatment is shown to be beneficial to the physical and chemical properties of the reclaimed carbon fibres and to yield polar-hydrophilic characteristics. Single fibre tensile testing is performed to explore the effect of surface treatment on the reclaimed carbon fibres (a higher tensile strength was observed). A computational hydrodynamic fibre moving model based on a moving particle semi-implicit method is newly designed to perform hydrodynamic simulation to determine aqueous dispersion of discontinuous reclaimed carbon fibres. This simulation helps understanding fibre flocculation phenomena from the perspective of fibre stiffness, which should not be disregarded for the fibre dispersion. Fibre surface analyses including morphology and functional groups are carried out to investigate the effect of surface treatment. The hydrodynamic simulation and proposed fibre dispersion methods with a cost-effective surface treatment approach can be widely applicable to any type of reclaimed carbon fibres to produce recycled fibre reinforced polymer composite materials.

Physico-Mechanical Property Evaluation and Morphology Study of Moisture-Treated Hemp–Banana Natural-Fiber-Reinforced Green Composites

The development of many engineered product applications for automobiles and aircraft parts has initiated the search for novel materials as alternatives to metal matrix composites (MMCs). Natural-fiber-reinforced polymer composites offer distinct advantages such as biodegradability, eco-friendliness, flexibility, low density, and higher specific strengths, etc. This study focuses on natural-fiber (hemp and banana)-fabric-reinforced polymer composites suitable for exterior-engineered parts. The hand lay-up process is used to fabricate these hybrid composites. Exterior-engineered products are highly susceptible to moisture, which can deteriorate their mechanical performances, including their tensile and flexural strength, thereby affecting the durability of the hybrid composites. Therefore, the hybrid composites are subjected to water absorption tests, where samples are immersed in distilled water for week-long intervals. After each interval, the water-absorbed specimens are tested for their tensile and flexural characteristics as per ASTM D-3039 and ASTM D-790, respectively. The moisture treatment had a notable impact on the composite materials, causing a slight decrease in the tensile strength by 2% due to the diminished lateral strength in the interlaminar fibers. Contrary to expectations, the flexural strength of the composites improved by 2.7% after the moisture treatment, highlighting the potential of the moisture treatment process to enhance the elastic properties of such composites. The dimensions of the specimens changed after the water immersion test, resulting in increased longitudinal and decreased lateral dimensions. The surface morphologies of the composite failure samples showed fiber delamination, fiber breakage, voids, and matrix fractures.

Effect of hybridization on natural fiber reinforced polymer composite materials – A review

AbstractThis review explores the hybridization effect of natural fiber‐reinforced composites (NFRCs) to reduce energy consumption and environmental pollution. Although natural fibers offer several advantages over synthetic fibers, such as biodegradability, lightweight, and low cost, their application in NFRCs is challenging due to inherent issues such as variable fiber quality, constrained mechanical properties, water absorption, and poor thermal stability. However, recent research has made significant progress in addressing these issues, resulting in better NFRCs. This article surveys the latest developments in plant‐based NFRCs, focusing on methods and innovations to enhance their performance through fiber modification, hybridization, incorporation of lignocellulosic fillers, and fabrication techniques for mechanical, sound absorption, and wear performance. It also discusses the expanding uses of NFRCs in various industrial sectors and the sustainability of plant‐based NFRCs using life‐cycle assessment.

Study of the physical and mechanical characteristics of modified epoxy matrices and reinforced plastics using modern computer systems for calculations

For the first time, calculations of a reinforced polymer composite material (ArPCM) based on T-25 fabric (VMP) and developed modified epoxy matrices with an active diluents (AR) of different nature, structure and characteristics (laproxides and laprolate), a complex of physical and mechanical characteristics were performed using a generalized 3D models of the elementary structural cell of the anisotropic material ArPKM and computational engineering systems (CAE). Calculations and experiments have shown that all the studied modified epoxy matrices can be used in the design of products from ArPKM, however, preference should be given to matrices with E-181 and DEG-1 grade Laproxides, which fully meet the strength requirements for designing products subjected to forces during operation.

Design and Analysis of FRP Composite Drive Shaft for Light Motor Vehicle

To make light vehicles such as cars fuel-efficient, which in turn cars make economical, the vehicle should have a lighter weight. The composite materials are lightweight with extra strength as well as stiffness; the replacement of FRP composite materials to conventional metal (SM45C) materials applied in automotive car components can cut back the weight and enhance the mechanical properties of those components. This task deals with the power shaft of MARUTI OMNI to design the shaft for its minimal dimensions and fulfil modern-day disadvantages with specification then replace traditional metallic material with Carbon/Epoxy FRP composite material. Then a component version created for individual dimensions in CATIA V5R19 software. As soon as modeling, Torsional buckling evaluation and Modal analysis could be carried out for propeller shafts the use of ANSYS R14.5 to validate the theoretical calculations and analytical outcomes. The received outcomes are compared and Carbon/Epoxy Fiber Reinforced Polymer composite material is selected as a better alternative material for normal steel material in terms of many mechanical properties for light motor cars.

Aluminum and Carbon Fiber Reinforced Polymer Composite Material Comparative Strength Analysis of a Structural Part in F-16 Fighter Aircraft Landing Gear

In this study, the geometric structure, weight and boundary conditions of the aluminum alloy main landing gear FS 34.180 structural part currently used in F-16 fighter aircraft are determined. Finite element (FE) analysis is performed considering the forces that the existing part is exposed to in four different scenarios with Ansys Workbench software. Then, a FE model of the same part is created from carbon fiber reinforced polymer (CFRP) composite material. The loading conditions applied in the four scenario are also applied to the new CFRP composite material model. Equivalent stress, equivalent total strain, maximum shear stress and total deformation values in the models created with both materials are calculated.
 The results obtained for both materials are compared. As a result of the comparison, it is observed that there is a decrease of approximately 0.8% in the equivalent stress, 12% in the equivalent total strain, 0.7% in the maximum shear stress and 11.8% in the total deformation values for the same loading and boundary conditions. In addition, the total mass of the part is reduced from 31.17 kg to 20.77 kg, which corresponds to a reduction of 33.37%. 
 This development is expected to reduce the weight of the aircraft as well as extend the fatigue life and maintenance period.

A Novel Hierarchical Extreme Machine-Learning-Based Approach for Linear Attenuation Coefficient Forecasting.

The development of reinforced polymer composite materials has had a significant influence on the challenging problem of shielding against high-energy photons, particularly X-rays and γ-rays in industrial and healthcare facilities. Heavy materials' shielding characteristics hold a lot of potential for bolstering concrete chunks. The mass attenuation coefficient is the main physical factor that is utilized to measure the narrow beam γ-ray attenuation of various combinations of magnetite and mineral powders with concrete. Data-driven machine learning approaches can be investigated to assess the gamma-ray shielding behavior of composites as an alternative to theoretical calculations, which are often time- and resource-intensive during workbench testing. We developed a dataset using magnetite and seventeen mineral powder combinations at different densities and water/cement ratios, exposed to photon energy ranging from 1 to 1006 kiloelectronvolt (KeV). The National Institute of Standards and Technology (NIST) photon cross-section database and software methodology (XCOM) was used to compute the concrete's γ-ray shielding characteristics (LAC). The XCOM-calculated LACs and seventeen mineral powders were exploited using a range of machine learning (ML) regressors. The goal was to investigate whether the available dataset and XCOM-simulated LAC can be replicated using ML techniques in a data-driven approach. The minimum absolute error (MAE), root mean square error (RMSE), and R2score were employed to assess the performance of our proposed ML models, specifically a support vector machine (SVM), 1d-convolutional neural network (CNN), multi-Layer perceptrons (MLP), linear regressor, decision tree, hierarchical extreme machine learning (HELM), extreme learning machine (ELM), and random forest networks. Comparative results showed that our proposed HELM architecture outperformed state-of-the-art SVM, decision tree, polynomial regressor, random forest, MLP, CNN, and conventional ELM models. Stepwise regression and correlation analysis were further used to evaluate the forecasting capability of ML techniques compared to the benchmark XCOM approach. According to the statistical analysis, the HELM model showed strong consistency between XCOM and predicted LAC values. Additionally, the HELM model performed better in terms of accuracy than the other models used in this study, yielding the highest R2score and the lowest MAE and RMSE.