This paper investigates the combined buckling and bending response of sandwich plates composed of bidirectional functionally graded (BDFG) face sheets and a metallic foam core, resting on a partial elastic foundation. Unlike previous studies limited to single load types, the present work considers simultaneous in-plane axial loads (compressive/tensile) and transverse loads inducing out-of-plane bending deformation. Furthermore, multiple boundary conditions including simply supported, clamped, free, and mixed edge restraints are systematically examined to reflect realistic support scenarios. The BDFG face sheets possess material properties that vary continuously in both in-plane (x,z) directions, while the metallic foam core follows a porosity-dependent mechanical distribution. A quasi-3D shear deformation theory is employed to formulate the governing equations. The principle of virtual work is used to derive the equilibrium equations, which are subsequently solved using an analytical solution method. After validating the present formulation against benchmark results, an extensive parametric study is conducted to assess the influence of key parameters: foam porosity coefficient, bidirectional gradation indices, partial foundation stiffness and location, in-plane to transverse load ratio and the type of boundary support. Results reveal that the interplay between combined loading, foundation partialization, and edge restraints significantly alters the critical buckling load and maximum transverse deflection. The proposed model provides a robust design tool for lightweight sandwich structures in aerospace, civil, and marine engineering applications where non-uniform support and combined loading are prevalent.

The discharge of dye-contaminated wastewater from textile and related industries represents a serious environmental concern due to the persistence, toxicity, and resistance of synthetic dyes to natural degradation. In this study, Lantana camara derived biochar (LCB) was investigated as a sustainable and low-cost adsorbent for the removal of Acid Black 172 (AB172) dye from aqueous solutions. The structural and surface properties of LCB were characterized using BET, FTIR, and HRTEM analyses, revealing a mesoporous structure with a surface area of 12.14 m² g⁻¹, pore diameter of 6.8 nm, and total pore volume of 0.031 cm³ g⁻¹. Batch adsorption experiments were conducted to evaluate the effects of pH, contact time, adsorbent dosage, and temperature. The adsorption process showed strong pH dependence, achieving maximum dye removal at pH 3, with equilibrium reached within 90 min. The Langmuir model predicted a maximum adsorption capacity of 303.03 mg g⁻¹, indicating a strong affinity between AB172 molecules and LCB surface sites. Kinetic analysis revealed that the adsorption followed a pseudo-second-order model, while thermodynamic parameters confirmed that the process is spontaneous and endothermic. In addition to this, the use of statistical physics modeling helped understand more about the adsorption process, such as adsorption orientation, adsorption energy, and the mechanism of surface interaction. These aspects set apart the study from other studies on adsorption. In the case of AB172 adsorption, the process was mainly influenced by electrostatic attraction, pore filling, van der Waals force, and hydrogen bonding interactions. Regeneration studies demonstrated high stability of the adsorbent, maintaining over 91% removal efficiency after five adsorption-desorption cycles. Statistical physics modeling and experimental studies on adsorption help in gaining a better insight into the processes involved in the dye-biochar interactions than traditional adsorption experiments do. These findings highlight LCB as a promising, environmentally sustainable, and economically viable adsorbent for the treatment of dye-contaminated wastewater.

This study investigates the buckling behavior of sandwich plates under various in-plane compressive loads (uniform, linear, and exponential). The plates consist of bidirectional functionally graded (BDFG) face sheets, with material properties graded along both axial and thickness directions, and a porosity-graded metal foam core, all partially supported by an elastic foundation. A quasi-3D shear deformation theory is employed to formulate a high-fidelity model, with governing equations derived via the principle of virtual work and solved analytically. After validation of results of the present study, a comprehensive parametric study is presented to evaluate the effect of foam porosity, gradient index, load distribution and foundation stiffness of the buckling stability. Numerical analysis reveals that the critical buckling load is contingent upon a multitude of factors: the plate typology, its geometric slenderness (a/h ratio), the characteristics of the imposed loading, and the underlying elastic medium. The comprehensive parametric analysis confirms that the proposed model provides an efficient and reliable predictive tool for the optimal design of advanced sandwich structures in demanding aerospace, civil, and marine engineering applications.

This study presents a comprehensive quasi-three-dimensional (3D) theoretical formulation investigation into the static bending and stress analysis of advanced sandwich plates resting on an elastic foundation. The plate features a lightweight, homogeneous foam core sandwiched between two face sheets made of bidirectional functionally graded (BDFG) materials, where the material properties vary continuously along both the thickness and axial directions according to a power-law distribution. This sophisticated material design allows for tailored performance under multiphysical loads. A quasi-3D displacement field is employed that provides a more realistic representation of the plate's deformation, especially under moisture and temperature gradients. The governing equations and associated boundary conditions are rigorously derived using the principle of virtual work (PVW). The constitutive equations are obtained with the effects of moisture concentration and temperature rise. The resulting system of coupled partial differential equations is solved analytically for simply-supported plates using a Navier-type solution for the spatial domain. A detailed numerical analysis examines the influences of key parameters, including the BDFG power-law indices, foam core stiffness, foundation parameters, and hygro-thermal environmental conditions, on the non-dimensional deflections, in-plane stresses, and transverse shear/normal stresses. The results demonstrate that the BDFG gradation pattern, combined with the elastic foundation, offers significant control over the plate's structural response. This work establishes a reliable and efficient computational framework for the design and optimization of next-generation sandwich structures in severe hygro-thermal environments, such as those found in aerospace and marine engineering applications.

This study presents a comprehensive vibration analysis of isotropic porous functionally graded material (FGM) spherical shells using a refined higher-order shear deformation theory (HSDT). Four distinct porosity distribution patterns even, uneven, logarithmic-uneven, and mass-density based are investigated to determine their influence on the dynamic behavior of FGM shells. The material gradation is modeled using power-law, trigonometric, and Viola-Tornabene four-parameter functions, while five different micromechanics models (Voigt, Reuss, Tamura, Mori-Tanaka, and LRVE) are employed to calculate effective material properties. Analytical solutions are obtained using Navier's technique for simply supported boundary conditions. The effects of gradient index, porosity coefficient, radius of curvature, and vibration mode numbers on the fundamental frequencies are systematically analyzed. Results reveal that each porosity distribution pattern uniquely affects the dynamic response, with mass-density porosity showing the strongest positive correlation to frequency enhancement. The findings provide valuable insights for designing FGM shell structures with tailored dynamic characteristics for various engineering applications.

A quasi-3D higher-order shear deformation theory (QHSDT) with five unknowns is here employed to analyze the vibrational behavior of the honeycomb sandwich cylindrical shells reinforced with graphene nanoplatelets /polymer coatings, which consider effects of both shear and normal deformation. The equations of motion of the sandwich cylindrical shell are obtained via the Hamilton principle. Navier’s technique is applied to obtain the closed-form solution for the simply-supported sandwich cylindrical shell. The accuracy and applicability of the proposed quasi-3D model are validated by comparison with existing results in the literature. Additionally, a parametric study is conducted to examine the effects of different geometrical properties of the honeycomb cells and the reinforcing GNP on the vibration response of the sandwich cylindrical shell, which is of significant interest for many modern engineering applications and their optimal design.

Concrete blocks made from waste aggregates have become a promising way to reduce waste and conserve natural resources while still offering good mechanical performance in both solid and hollow concrete blocks. This is especially relevant as more sustainable construction projects increasingly use recycled and alternative materials. This research develops a series of novel hybrid machine learning (ML) models to accurately predict compressive strength, using a dataset of 544 concrete samples from various sources. The six novel hybrid ML frameworks are designed as Hybrid Stacked Ensemble (HSE), Hybrid Residual Learning (HRL), Hybrid Weighted Ensemble (HWE), Hybrid Meta-Learning (HML), Hybrid Bayesian Stacking (HBS), and Hybrid Feature Fusion (HFF). Results show that novel Hybrid Bayesian Stacking (HBS) algorithms deliver excellent predictive accuracy across all evaluation metrics, with (R2 = 0.998, RMSE = 0.665) during training and (R2 = 0.987, RMSE = 1.836) during testing. Furthermore, Individual Conditional Expectation (ICE) and SHapley Additive exPlanations (SHAP) analyses identified important input features and their effects on compressive strength. A graphical user interface (GUI) was developed to make predictive models accessible for practical engineering

The Hejaz region of Saudi Arabia was previously considered seismically inactive, but the recent earthquake in the Jeddah region has raised concerns. Therefore, the safety of the holy cities (Madinah and Makkah) must incorporate seismic effects in design. This research focuses on the performance of multi-story office buildings under lateral loads in the Madinah region. Furthermore, the SWOT (strength, weakness, opportunities, threats) analysis has been carried out to pinpoint the detailed scenario of the retrofitting ideology. The study showed that retrofitting systems can highly increase the lateral strength of the existing structures. It has been proved that a non-earthquake-resistant building can be transferred to an earthquake-resistant facility by following solutions with a level arrangement. The mechanism appears to increase the lateral strength resistance of the seismically vulnerable building. The bracing system exhibits the highest increase in strength. Such retrofitting approaches demonstrate their potential to be applied to vulnerable structures.

This article proposes a new type of aluminum-wood composite beam that reduces material weight and enhances lightweight construction. The beam is reinforced by composite material plates, providing additional rigidity. The beam has three cross-sections: I-shape, U-shape, and rectangular tube, with adhesive connection for both interfaces. The interfacial stresses in aluminum-wood composite beams reinforced by composite laminates are analyzed using nonlinear elastic theory and strain compatibility approach. The model considers shear deformations of the interface and is intended to be applied to all types of bonded materials. Theoretical predictions are compared with existing solutions, contributing to understanding the mechanical behavior of the interface and designing aluminum-wood structures reinforced by composite materials.

Lightweight high-strength concrete (LWHSC) is increasingly used as a sustainable material that reduces structural weight while maintaining performance. Promoting sustainability involves using less high-carbon cement and more supplementary cementitious materials (SCMs) like fly ash, silica fume, and slag. However, testing LWHSC’s mechanical behavior is costly and time-consuming, highlighting the need for reliable prediction tools. To address this, this study employs machine learning models multi-expression programming (MEP) and random forest (RF) to forecast the mechanical properties of LWHSC containing SCMs using a large dataset with eight key parameters, including water-to-binder ratio, cement, fly ash, slag, silica fume, aggregate, lightweight aggregate, and basalt fiber. Performance was evaluated with R2, MAE, RMSE, and MSE. Both models captured strength trends, but MEP was more accurate, especially for compressive strength (R2 = 0.98–0.99) versus RF (0.87–0.91), and similarly for tensile and flexural strengths. Errors mostly stayed below 3 MPa for CS, 0.5 MPa for TS, and 2 MPa for FS. Taylor diagrams confirmed MEP predictions closely matched experimental data. Additionally, SHapely Additive ExPlanations (SHAP) investigation demonstrated that the water-to-binder ratio and lightweight aggregate had a favorable impact on the mechanical properties of the LWHSC. The study highlights MEP as a robust, dependable tool for designing sustainable LWHSC by effectively combining SCMs with machine learning.

This study presents a systematic comparative analysis of homogenization models for free vibration behavior in isotropic porous functionally graded material (FGM) spherical shells, addressing critical research gaps through rigorous evaluation of five micromechanical schemes Voigt, Reuss, Mori-Tanaka, Tamura, and LRVE coupled with power-law and trigonometric material gradations. A refined higher-order shear deformation theory (HSDT) incorporating five shear functions governs the analytical formulation, solved via Navier's technique for simply supported boundaries. Comprehensive parametric studies quantify the coupled effects of thickness-to-span ratio, aspect ratio, porosity coefficient, and radius of curvature on non-dimensional fundamental frequencies. Results demonstrate that homogenization model selection critically influences vibrational response, with Voigt and LRVE predicting frequencies 12-15% higher than Reuss models. Porosity distribution dominates stiffness reduction, where mass-density and logarithmic-uneven configurations cause 20-25% greater frequency suppression than even distributions, while trigonometric gradation amplifies curvature sensitivity by 30% versus power-law. These insights provide validated design guidelines for optimizing vibration performance in civil engineering dome structures and pressure vessels, aerospace components, and automotive acoustic enclosures.

One of the most significant advancements in basalt fiber (BF) technology is its application in Basalt fiber reinforced polymers (BFRP). The production of BFRP utilizes basalt rock, a naturally abundant resource, resulting in a composite that generates approximately 74% less carbon emissions compared to traditional steel, aligning with global sustainability goals. This study employs previously published experimental datasets on basalt fiber-reinforced concrete (BFRC) to statistically predict compressive strength (CS) and splitting tensile strength (STS) using advanced machine learning. The dataset includes 270 CS and 267 STS samples, split into 70% training and 30% testing, enabling accurate, data-driven predictions without the need for new laboratory experiments. In addition to the parametric analysis of Shapley additive explanation (SHAP), machine learning models were used, namely support vector regression (SVR), random forest regression (RFR), decision tree (DT), bagging regressor (BR), and gradient boosting regression (GBR) with grid search hyper-tuning. Additionally, the model generated SHAP interaction plots to show the impact of each characteristic on an individual prediction. The results found that GBR model performance is the most precise prediction of compressive strength compared to other models, achieving an R2 of 0.99 for training phase and R2 of 0.86 for testing phase. But SVR model outperforms the other four models in STS prediction, with the coefficient of determination (R2) value of 0.99 during the training stage and R2 of 0.97 for the testing stage. The Shapley additive explanations (SHAP) method was used to display the effect of each input parameters on model prediction. The cement and silica fume were found to have the highest positive influence on BFRC compressive and tensile strength. The basalt fiber (BF) diameter as an input parameter was found to have the highest effect on STC. Finally, the concrete designers can now easily and affordably predict CS and STS using a graphical user interface, without conducting expensive computations or experiments.

The North Gyeongsang region in South Korea has demonstrated significant seismic activity over the past two decades. This study assessed the zone-specific performance and vulnerability of lined tunnels, incorporating structural material properties and surrounding geological conditions as primary influential parameters, along with variations in tunnel lining, to develop intensity-response relationships. For Zone E, the seismic fragility curves (SFCs) generated for minor, moderate, and extensive damage levels for both shallow and deep tunnels indicate a high level of catastrophic risk. These proposed SFCs are employed to assess tunnels planned for a proposed road network in Pohang. The findings revealed that Route P2 represents the optimal choice, whereas Route P3 is the least suitable for ensuring the safest design. This analysis includes the formulation of a tunnel-specific risk matrix, which is utilized to define the functionality of each route in post-seismic scenarios within the study area. The combined use of SFCs, risk matrices, and road functionality maps provides a valuable engineering resource for professionals engaged in the earthquake-resistant design and assessment of underground structures in South Korea. This methodology will assist disaster management authorities in risk mitigation and ensuring safe traffic flow on transportation networks.

This paper leverages data from February 6, 2023, Kahramanmaras (Turkiye) Earthquake (Mw 7.8) to evaluate seismic risk and assess bridge damage through a fuzzy synthetic approach (FSA). A novel hierarchical damage classification framework is introduced, integrating critical factors such as ground conditions, structural characteristics, and seismic intensity. By analyzing data from 331 bridges affected by eight major historical earthquakes, the study underscored the influence of foundation depth, construction quality, and distance to fault rupture on structural resilience. Notably, 65% of damaged bridges were within 40 km of the distance to fault rupture, with oblique span orientations (45° to 65°) showing heightened susceptibility to seismic forces. To enhance resilience against earthquakes, the findings advocated for the adoption of deep foundations, advanced materials, and optimized structural designs. Consistent with field observations, the study reinforces the utility of FSA in enabling informed decision-making for disaster risk mitigation and is also beneficial for future seismic resilience design of bridges.

A p-version finite element method (p-FEM) based on First-Order Shear Deformation Theory (FSDT) is utilized to investigate the dynamic behavior of functionally graded porous sandwich plates reinforced with carbon nanotubes (FG-CNTR). The plate comprises three layers, with the core layer as FG-CNTR, accounting for several types (Uniform, FG-X, and FG-O distributions). Both the bottom and top surfaces consist of a porous, functionally graded material (FGM) employing five different porosity models (Perfect, Imperfect I, & mldr;, V). The obtained numerical results have converged and are compared with published data to demonstrate the validity and accuracy of the present formulation. For the response under dynamic conditions, the solution obtained from the p-version of FEM using the mode superposition method is compared with a novel developed analytical solution used Classical Plate Theory (CPT). The effects of various parameters, including the carbon nanotube distribution pattern, porosity model, CNT volume fraction, geometric characteristics, mechanical load, volume fraction exponent, damping coefficient, and boundary conditions, are illustrated and analyzed in depth. These findings provide important guidance for the efficient design and optimization of FGM structures in various engineering applications.