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Analytical and Numerical Investigation of Sandwich Beams with Additively Manufactured Lattice Cores and Composite Facesheets
No full textPrediction of Entropy Production and Heat Transfer Characteristics of Al2O3-Cu/Water Hybrid Nanofluid in Convection-Radiation Interaction Flow in a Porous Cavity byMachine Learning Approach
No full textMinimizing entropy production is critically important, particularly in nanofluid flows. Applying this principle to flows with porous cavity structures helps optimize heat transfer applications and enhance system efficiency. In this study, the entropy production and heat transfer characteristics of a hybrid nanofluid composed of Al2O3-Cu particles suspended in water were investigated using machine learning. The nanofluid was analyzed in the context of convection–radiation interaction flow within a porous cavity.An artificial neural networkmodel was developed to predict the average Nusselt number, Bejan number, and entropy production as functions of the Hartmann number and inclination parameters. The Bayesian Regularization algorithm was employed to train the multilayer perceptron network model. Prediction results obtained from the model with 10 neurons in the hidden layer were compared with the target values and showed excellent agreement.The developed artificial neural network model successfully predicted the Nusselt number, Bejan number, and entropy productionwith average deviation rates of−0.007%,−0.11%, and 0.0002%, respectively
Fundamental Design Principles for Tensile Membrane Structures: A Call for Structural Awareness in Architectural Practice
No full textMultisensor Fault Diagnosis Leveraging Reinforced Evidential Jensen-Alpha Divergence under Dempster-Shafer Theory
No full textUncertainty and conflicting information are pervasive in artificial intelligence (AI)-driven engineering systems, especially in multisensor fault diagnosis. Dempster-Shafer theory (DST) has garnered significant interest across various fields as it provides a powerful framework for modeling uncertainty. However, despite its advantages, the application of Dempster’s rule can lead to paradoxical outcomes when it encounters highly conflicting evidence. To address this limitation, this paper first presents a new evidential Jensen-alpha divergence (EJ AD) to quantify the discrepancy between the evidence items based on DST. Furthermore, an advanced version, the reinforced evidential Jensen-alpha divergence (REJ AD) is developed, which takes into account the quantity of potential propositions. We demonstrate thatREJ ADcan be transformed into various divergences such as the χ2divergence, Jensen-Shannon divergence, Hellinger distance, and arithmetic-geometric divergence under certain conditions. Also, we show the key properties ofREJ AD, including non-negativity, non-degeneracy and symmetry. Additionally, we design a new multisensor fault diagnosis method utilizingREJ ADand belief entropy. The superior performance of the proposed method is tested in three distinct fault diagnosis cases, and analysis shows robust performance across a range of its key parameter α, offering a computationally feasible, scalable and interpretable solution for AI-based decision-making in real-world engineering applications.OPEN ACCESS Received: 15/10/2025 Accepted: 17/11/202
The Effects of Trichosanthes Root Extract on Regeneration Rate, Behavior, and Movement of Dugesia tigrina
No full textThis study investigated the effects of Trichosanthes root extract on the regeneration rate of Dugesia tigrina, a freshwater planarian. Planarians were chosen for their regenerative ability and stem cell systems. Traditionally used in Chinese medicine for its anti-inflammatory and antioxidant properties, Trichosanthes root was tested for its unexplored regenerative potential. The goal was to evaluate a cost-effective, biologically based method for enhancing tissue regeneration with potential applications in regenerative medicine and wound healing. Planarians were continuously exposed to varying concentrations of the extract, with locomotor activity recorded before and after treatments. Specimens were then transversely amputated into head and tail fragments, which were observed independently. Regenerative outcomes, including body length, eyespot formation, and indicators of nervous system recovery, were measured at regular intervals. Results demonstrated that in trial 1, group D slightly decreased in head length regeneration compared to our control group A. Although group A had the smallest amount of head regeneration over the course of 11 days, there was no significant difference found between the groups in trial 1. Similarly, group C had the least regenerative ability overall over 11 days, but there was still no statistical difference found between the groups. Ultimately, Trichosanthes root was not significantly effective in the regeneration, locomotor activity, and behavior of Dugesia Tirgrina. These findings suggest that even as planarians remain valuable assets in testing biological compounds, Tricosanthes root may not have benefited tissue regeneration as hypothesized
Biological Solitons in Biomembranes: Analytical Solutions of a Boussinesq-Type Equation with Amplitude-Dependent Nonlinearity
No full textBoussinesq-type equations (BTE) emerge in various fields of fluid and solid mechanics, particularly where nonlinearities and dispersion are considered. Boussinesq-type equations are used to model wave effects in biomembranes, particularly longitudinal waves. They can account for nonlinear and dispersive effects that are important for characteristic wave behavior in biomembranes, composed of lipids, with distinct nonlinear effects. This provides a realistic description of longitudinal mechanical waves in nerve membranes. In this research, we investigate the Boussinesq-type equation that describes the waves in biomembranes with amplitude-dependent nonlinearities, using the Khater method (KM) and the Jacobi elliptic function method (JEFM). In addition to producing generic biological answers, the proposed methods allow the analysis of single wave solutions. These methods make it easier to derive solutions for solitary waves, which occur in a variety of forms, including bell, antibell, periodic, anti-kink and kink solitons. Each of these waves has a wide range of possible applications in biomathematics. Some of the findings are displayed as contour, 2D, and 3D graphics with particular parameter values applied under the specified conditions in order to highlight the important propagation properties. To the best of our knowledge, the biological solitons of the considered model have not been reported by using the proposed techniques in the literature. These results provide new theoretical insights into wave phenomena in biomembranes and may contribute to biological physics and nonlinear science.OPEN ACCESS Received: 04/11/2025 Accepted: 15/12/2025 Published: 23/01/202
Qualitative Analysis of Nonlinear Systems Involving Hadamard-Type Fractional Derivatives with Nonlocal Boundary Conditions and Stability Properties
No full textThis paper establishes a comprehensive analysis of a coupled system of nonlinear Hadamard-type fractional differential equations subject to generalized nonlocal integral boundary conditions. The distinct logarithmic kernel of the Hadamard derivative makes this framework particularly suitable for modeling scale-invariant processes and ultraslow diffusion phenomena. The existence and uniqueness of solutions are rigorously investigated using fixed point theory: Banach’s contraction principle ensures uniqueness, while the Leray-Schauder nonlinear alternative guarantees existence under more general growth conditions. Furthermore, the system is proven to be Ulam-Hyers stable, ensuring that approximate solutions remain close to exact solutions, which is crucial for the robustness of the model in practical applications. The theoretical findings are effectively validated through two detailed numerical examples, demonstrating the applicability of the established results to different classes of nonlinearities.OPEN ACCESS Received: 22/08/2025 Accepted: 03/11/2025 Published: 23/01/202
Thermomechanical Uncertainty Analysis of Steel PartitionWalls Using Direct FE2 and Polynomial Chaos Expansion
No full textSteel partition walls are essential components in modern civil engineering, providing both structural support and spatial separation. These walls are frequently exposed to combined thermal and mechanical loads, particularly in specialized environments such as high-temperature workshops or fire scenarios, where their thermo-mechanical coupling behavior is critical to building safety and functionality. This study integrates the direct finite element squared (Direct FE2) method with generalized polynomial chaos expansion (PCE) to quantify the uncertainties in key material propertiesnamely, the elastic modulus and the coefficient of thermal expansionand to evaluate their effects on the thermo-mechanical performance of steel partition walls. The proposed approach enables efficient simulation of material uncertainties and their influence on structural behavior under coupled thermal-mechanical conditions. Case studies demonstrate both the accuracy and computational efficiency of the method, while sensitivity analysis highlights the most influential uncertainty factors. The integration of Direct FE2and PCE thus offers a robust framework for assessing the reliability of steel partition walls under uncertain conditions, providing valuable insights for design optimization and enhancing the safety and efficiency of building structures in practical applications.OPEN ACCESS Received: 05/07/2025 Accepted: 17/09/2025 Published: 23/01/202
