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The present study investigates the compressive strength performance of polylactic acid (PLA) polymer material parts printed using the Fused Deposition Modelling (FDM) three-dimensional (3D) printing process, with a particular emphasis on various machine input parameters. The face centred central composite design matrix approach was employed for experimental modelling, which was subsequently utilised as a knowledge base for the fuzzy algorithm. A hybrid evolutionary algorithm, i.e., Genetic-Algorithm (GA) assisted with Fuzzy Logic Methodology (FLM), was used to optimize input process parameters and compressive strength of FDM technique fabricated polymer material parts. The study concluded that the maximum compressive strength observed with GA integrated FLM was 49.7303 MPa at input factors (layer thickness-0.16 mm, temperature 208°C, infill-pattern-Honeycomb, infill-density-60% and speed/extrusion velocity-41 mm/s) which is higher than the experimental (47.08 MPa) and fuzzy predicted (47.101 MPa) value. This evolutionary hybrid soft computing methodology has optimized the compressive strength of PLA polymer material parts at optimum parameters combination set.

In this study, the hydrodynamics and thermal behavior in the crossflow of air passing over hybrid tubes in the staggered configuration were numerically investigated. CFD (Computational Fluid Dynamics) study were conducted with the help of the ANSYS Fluent program. In the study, 12 different tube bundle models were created with a combination of circular and wing-shaped tubes. The wing-shaped tubes were placed in the tube bundle at different attack angles (θ: 0° and 180°). Reynolds numbers in the range of 4000 ≤ Re ≤ 12,000 were used. To observe the effects of hybrid tubes and Reynolds numbers on thermal and flow fields, velocity, pressure, and temperature contours were acquired. According to the findings, Nusselt number (Nu) and performance criteria (PC) increased, and friction factor (f) decreased with increasing Re for all tube bundle models. The friction factor of hybrid tube bundles was higher than wing-shaped tube bundles but considerably lower than circular tube bundles. Among the hybrid models, the best heat transfer was obtained in Model 6, the lowest friction factor in Model 11, and the best PC in Model 4. Also, three different stacked ensemble models were created to predict Nu, f, and PC values for CFD analysis. These models are the ensemble of XGBoosts, the ensemble of DNNs, and the ensemble of DNN, XGBoost, and RF. This study revealed that ensemble of XGBoosts is more beneficial than the other in the CFD analysis.

This article is concerned with the existence of a weak asymptotic solution for a (5times 5) system of nonstrictly hyperbolic conservation laws. We provide additional weak asymptotic expansions within the framework of the weak asymptotic approach. Then, with the aid of these weak asymptotic expansions, we establish sufficient conditions for the existence of a weak asymptotic solution for the (5times 5) system with initial data of Riemann type. Combining the Riemann problems allow us to form a weak asymptotic solution for a more general type of initial data.

The objective of this study was to develop a finite element model that explains the drying performance of a hybrid greenhouse dryer equipped with a single-pass solar air heater for drying of bitter gourd flakes. The model utilized the finite element method (FEM) to solve a set of partial differential equations (PDEs) that describe the combined heat and mass transfer process during drying. The 3-dimensional finite element model provided a visual representation of the spatial distribution of moisture within the bitter gourd sample. The mesh used in the model consisted of Lagrange triangle finite elements with small sizes and second-order geometry shapes. A time-dependent analysis was performed to capture changes in moisture content during the 5-hour of drying. The model predicted maximum crop and ground temperatures of 60.10°C and 77.20°C, respectively, with a drying efficiency of 42.91%. The relative humidity inside the drying chamber was 30.4%. The energy and exergy efficiencies were determined to be 80.09% and 53.83%, respectively. The predicted results were validated against experimental data and it was found that the hybrid greenhouse solar dryer, with moderate inside temperatures, is a suitable option for bitter gourd flakes drying while maintaining environmental sustainability.

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A non-linear critical layer analysis of the presence of singular azimuthal neutral modes in density stratified swirling flows is considered. It is shown that finite amplitude neutral modes exist when the basic flow velocity, vorticity, and temperature profiles undergo distortions with the occurrence of jump in them.

In this study, the effectiveness of different wire feed rates, pulsed current, spark gap voltage, pulse on time, and pulse off time was investigated to determine their impact on kerf width. The ideal parameters for wire-EDM machining of aluminum hybrid ceramic composite were determined through experimental investigation and an adaptive neuro-fuzzy inference system (ANFIS). Additionally, five distinct predictive models for influential kerf width parameters were developed as an innovative approach. A hybrid learning methodology combining back propagation and least square estimations was employed to create these predictive models. The prediction ranked the machining parameters affecting kerf width dimensions as wire feed rate, pulsed current, pulse on time, pulse off time, and spark gap voltage. Experimental findings showed that the kerf width of the machined workpiece significantly increased as the wire feed rate increased. This exploratory study suggested a wire feed rate setting of 3 mm/min with a current of 2 A and a pulse on time of 0.6 μs to achieve the best quality machined surface for the aluminum hybrid ceramic composite. Similarly, the proposed optimization model results proved that the experimental findings were near-optimal solutions.

The increase in pore water pressure, directly associated with the compressibility of loose sands under seismic loading, induces liquefaction, resulting in a decrease in effective stresses and, consequently, a loss of soil strength and stiffness in saturated sandy soils. For a long time, geotechnical engineers have found it difficult to understand the phenomenon of soil liquefaction. It is crucial to look into the factors influencing the liquefaction and/or softening of soil as well as the production and evolution of pore water pressure to have a deeper knowledge of the liquefaction phenomena. The size of the particles is one of the important factors. The purpose of this work is to examine how sand particle size, repetitive loading, and undrained circumstances affect the development of excessive pore water pressure. SEM and EDX imaging were conducted to determine the characteristics of three different sands. To ascertain the parameters of shear resistance, three sands with varying gradations were chosen and subjected to direct shear tests. For each of the three sands with varying particle sizes, cylindrical triaxial test specimens were made, and a set of dynamic triaxial tests under stress control were performed. The specimens were tested at various repeated stress ratios (CSR) using loading frequency of 0.1 Hz after being isotropically consolidated under an effective stress of 100 kPa. Experiments on three different sands with varying grain sizes and shapes revealed increased liquefaction potential with a reduction in grain diameter. It was observed that as the cyclic shear strain increased, the sand samples reached liquefaction at lower cycles. Additionally, it was noted that incorporating empirical coefficients that consider grain size and shape into the prediction of pore water pressure improved compatibility with models commonly used in the literature, leading to better results.

Localization in sensor communication is considered one of the most foundational concepts that facilitates targeted monitoring, optimized deployment, and real-time navigation. The localization algorithms have several applications, including asset tracking, environmental monitoring, industrial automation, and other location-based services. This drives the need for continually refining and enhancing localization techniques for three-dimensional sensor networks. The DV-Hop is a widely used localization technique owing to its lesser range requirements, easy to implement, and suitable for large-scale network of sensors. In this research, we have proposed an enhanced group learning optimization-based three-dimensional DV-Hop algorithm, termed as GL-3DDVHop. The proposed method overcomes the limitations of the original variant of DV-Hop and extended it to three-dimensional environment. In the proposed approach, the communication ring partitioning-based location aware node selection approach is developed to calculate the hopsize of location aware node. The correction factor for hopsize refinement is also added to obtain the corrected distances between location unaware node and location aware nodes in terms of the modified hopsize and hop count. Finally, group learning optimization technique is used to estimate the position coordinates of location unaware nodes. According to our experimentation conducted for 3D wireless sensor network, the localization accuracy of GL-3DDVHop surpassed its existing counterparts, namely 3DDV-Hop and PSO-3DDVHop techniques by 9% and 3%, respectively.

The stability of an overburdened mine dump is a significant challenge due to limited space and increasing mineral demand. Stability analysis often assumes uniform shear strength parameters, potentially leading to unprecedented slope failure. This study investigates the effect of overburden pressure on the shear strength parameters through direct shear tests under various normal loading conditions. Results show that with increased normal pressure, cohesion increases while friction angle decreases. Shear tests were conducted on dump samples with varying compositions, which were created by combining different ratios of medium, fine, and coarse particles. Numerical simulations in FLAC were performed using Mohr–Coulomb (constant shear strength parameters and varying shear strength parameters) and Hoek–Brown failure criterion, based on laboratory and field-testing results. It was observed that using the uniform value of shear strength parameters can lead to the production of a higher factor of safety (around 10% for coarse particle mix dump and 5% for finer particle mix dump) as compared to models prepared with the non-uniform value of shear strength parameters along the depths of the dump. Also, the huge overburden pressure leads to a decrease in shear strength at the location deep inside the dump body resulting in a deeper depth of failure surface. The effect of Hoek–Brown parameters ‘m_i’ and ‘GSI’ on the factor of safety of a high overburden dump slope has also been determined.

The Industrial IoT system often struggles to identify malignant traffic and may cause disruption in the flow of work or even hazardous situations. The previously described techniques to identify such intrusions work well but not enough to be implemented in such environments where it is very difficult to identify malignant traffic in loads of benign ones. Hence, an intrusion detection system is needed that works well with very highly unbalanced datasets. Therefore, we developed a transformer model that gives a high accuracy and combined it with a boosting module that decreases false negatives, which is highly required. This model is applied to the UNSW-2018-IoT-Botnet dataset, which is publicly available in the cloudstor network. Thus, the classified traffic identified as malignant is eliminated from the system using prevention techniques. The paper also extends the model to classify among five different traffics for the same dataset, in which some of the traffics are very difficult to distinguish, such as DoS and DDoS traffic. The experiments on such data sets have shown much better results, which proves that the model classifies well and can be implemented practically as well.