Search Results (4,396)

The application of dynamic vibration absorbers (DVAs) is a countermeasure to suppress vibrations induced by railway traffic. A key advantage of the DVA application is that it does not require any changes to the path of vibration propagation or the receiver of vibration. A review of the literature reveals the necessity of deriving the optimum properties of DVA to mitigate railway vibrations. To this end, the optimum DVA properties were investigated through the development of a two-dimensional finite element model of the track-tunnel-soil system. The model was validated using the results of a field test. A parametric study was made to obtain the optimum properties of DVA for different soils surrounding the tunnel. The results of the model analysis indicate that the DVA has better vibration reduction for metro tunnels built in soft soils as compared to those surrounded by medium and stiff soils. Also, the results disclose that the DVA reduces vibration radiated on the ground surface when the DVA natural frequency is tuned to a low frequency. Using the results of the parametric study, graphs are suggested to select the optimum properties of the DVA as a function of the soil around the tunnel. Full article

Model predictive control (MPC) has emerged as a favorable control approach for PMSM drives, though its practical deployment is frequently hindered by superior computational complexity and execution burden. This paper presents four finite control set MPC (FCS-MPC) techniques applied to a two-level inverter-fed PMSM drive. Two of the approaches are conventional methods, while the other two are novel developed strategies proposed in this paper. The novel techniques focus on significantly decreasing computational burdens by employing an efficient space-vector selection mechanism that quickly selects the optimum switching vector without exhaustive evaluation. A comprehensive comparative assessment of all four control methods is conducted under various operating conditions, evaluating their dynamic and steady-state performance, computational requirements, and real-time feasibility. Simulation results demonstrate that the proposed techniques achieve a significant reduction in computational effort and faster processing, up to 39.65% faster than conventional full-state evaluation, while maintaining control performances comparable to conventional techniques. These results highlight the potential of the proposed MPC approaches to bridge the gap between advanced control theory and practical implementation in real-time PMSM drive systems, providing effective solutions for installing high-performance PMSM drives on hardware with limited resources. Full article

This study investigates the effect of incorporating an electromagnetic harvester inside the bluff body of a 2-DoF hybrid harvester in comparison to a standalone piezoelectric harvester for various external loads. The harvester is excited through a vortex-induced vibration owing to the resultant wake vortices created behind the bluff body. The coupled dynamics of the two harvester components are modeled, and numerical simulations are conducted to evaluate the system’s performance under varying electrical loads. Numerical results show that at high, optimum electrical load, the standalone piezoelectric harvester outperforms the hybrid harvester. Nevertheless, for small electrical loads, the results show that the hybrid harvester outperforms the standalone PZT harvester by up to 18% in peak power output, while reducing the bandwidth by approximately 10% compared to the standalone piezoelectric harvester. Optimal spring stiffness values were identified, with the hybrid harvester achieving its maximum output power at a spring stiffness of 83.56 N/m. These findings underscore the need for careful design considerations, as the hybrid harvester may not achieve enhanced power output and bandwidth under higher electrical loads. Full article

Protein kinases are important molecules of Alzheimer’s Disease (AD), driving neuronal demise and the emergence of the disease’s destructive hallmarks. Cdk5 has recently been highlighted as a key therapeutic target for AD. This study evaluated the expression levels of Cdk5 and Mcl1 (Cdk5’s substrate) in blood samples of 61 AD, 55 Mild Cognitive Impairment (MCI), and 57 Geriatric Controls (GC), and explored the in vitro inhibition of Cdk5. The serum levels of Cdk5 and Mcl1 were measured by Surface Plasmon Resonance (SPR) and verified by Western blot and RT-PCR. Molecular modeling and simulation studies were used to identify a potent hit targeting Cdk5 and validated by binding studies using SPR. The peptide rescue effect was analyzed by MTT assay in the AD cellular model. SPR analysis revealed a significant change in Cdk5 and Mcl1 levels in the serum samples of AD and MCI compared to GC. Results were validated by Western blot and RT-PCR. Binary logistic regression analysis revealed that the concentration of both Cdk5 and Mcl1 was independently associated with disease after adjusting for certain parameters. ROC analysis established an optimum diagnostic cutoff value for Cdk5 [24.97 ng/µL (AUC-0.90)] and Mcl1 [23.08 ng/µL (AUC-0.94)] with high sensitivity and specificity. The peptide YCWS strongly binds to Cdk5′s ATP binding site, confirmed by molecular modeling and SPR. In the AD cellular model, peptide YCWS rescued neurotoxicity, increased Mcl1 levels, and reduced destructive hallmarks by inhibiting Cdk5. It can be concluded that Cdk5 is a promising molecule as a circulatory biomarker for the diagnosis of the early stages of AD, and its peptide inhibitor YCWS is a potential therapeutic agent. Full article

(1) Background: This study aimed to determine the optimum parameters for the treatment of Streptococcus mutans biofilm on clear dental aligners. (2) Methods: A 24-h-old S. mutans biofilm was grown on polyurethane (PU) and poly(ethylene terephthalate glycol) (PETG) aligners. These samples were treated with three chlorhexidine digluconate (CHX)-based antiseptic solutions, manual brushing, and a combination of both, with varying exposure times. The number of adhered bacteria was determined in both untreated and treated samples after sonication. Materials were analyzed with atomic force and scanning electron microscopy, and surface free energy (SFE) values were determined using three different models. (3) Results: Our findings indicated that control strategies do not depend on the type of material. PU and PETG surfaces exhibited similar SFE values (41–45 mJ/m²). Differences in surface roughness were insufficient to cause significant changes in S. mutans behavior. The highest efficacy of all three tested antiseptics was established for the exposure time of 1 min, with efficacy deteriorating just after 3 min. (4) Conclusions: The efficacy of CHX against S. mutans early biofilm is material-independent and time-dependent. The optimal exposure time of 1 min should be combined with brushing, with a general recommendation of the antiseptic-first approach. Full article

Additively manufactured thermoplastic polyurethane (TPU 95A) is widely used in engineering, yet its machining behavior remains insufficiently explored. This study investigates the post-processing machinability of FDM-fabricated TPU 95A using CNC milling, with a particular focus on material removal rate (MRR) and surface roughness (Ra). A full factorial design of experiments (81 runs) is conducted, considering four input parameters such as spindle speed (N; 2000, 4000, 6000 rpm) and feed rate (F; 100, 200, 300 mm/min) on the CNC vertical machining center, together with infill density (ϕ; 33%, 66%, 100%) and layer thickness (LT; 1.0, 1.5, 2.0 mm). MRR is modeled and optimized across all densities, achieving strong fit (R² = 0.94; Adj-R² = 0.93). The optimum conditions are found to be MRR ≈ 1251 mm³/min at F = 300 mm/min, ϕ = 100%, N ≈ 3500 rpm and LT ≈ 1.05 mm. Ra can only be measured for 100% infill specimens, as lower infill surfaces violate profile measurement requirements. Its regression model shows weak explanatory power (R² = 0.14; Adj-R² = 0.03) and is excluded from optimization. Instead, Ra is reported descriptively: milling reduced roughness from ≈25–30 μm (as-printed) to ≈13.8 μm under favorable conditions. Overall, the study highlights machining’s role in the hybrid manufacturing practice. Full article

With the continuous growth of air transportation demand, air traffic congestion in the Terminal Area has become increasingly serious. In order to assist controllers in efficiently alleviating the traffic congestion situation in the Terminal Area, this paper takes aircraft trajectory adjustment and flow control from the perspective of the Terminal Area as a starting point and proposes a congestion relief strategy based on a complex network and multi-objective optimization theory. First, a Terminal Area traffic network model is established with the approach point, departure point, waypoint, and navigation station as nodes and the flight path as edges. Next, a multi-objective optimization model that takes into account both congestion relief and reduced operating costs is constructed. Finally, an improved ant colony optimization is proposed to solve this optimization model and provide a unified approach to path planning for multiple aircraft. Finally, simulation experiments were conducted based on the airspace structure and operation of the Beijing Terminal Area. At the same time, ablation experiments were designed to compare the method in this paper with other ant colony optimizations. The experimental results show that the path planning results of the improved ant colony optimization can better alleviate the traffic congestion situation in the Terminal Area, converge faster, and reduce the risk of falling into a local optimum. Full article

Composite breakwater is a commonly employed structure for coastal and harbor protection. However, strong hydrodynamic impact can lead to failure and instability of these protective structures. In this study, a two-dimensional fluid-porous-solid coupling model is developed to investigate the stability of composite breakwaters. The fluid-porous model is based on the Volume-Averaged Reynolds-Averaged Navier-Stokes equations, in which the nonlinear Forchheimer equations are added to describe the porous layer. The solid model employs the Nodal-based Discontinuous Deformation Analysis (NDDA) method to analyze the displacement of the caisson. NDDA is a nodal-based method that couples FEM and DDA to improve non-linear processes. This proposed coupled model permits the examination of the influence of the thickness and porosity of the porous layer on maximum impacting wave height (${\mathrm{IWH}}_{\max }$) and the turbulent kinetic energy (TKE) generation. The results show that high porosity values lead to the dissipation of TKE and reduce the ${\mathrm{IWH}}_{\max }$. However, the reduction in the ${\mathrm{IWH}}_{\max }$ is not monotonic with increasing porous layer thickness. We observed that ${\mathrm{IWH}}_{\max }$ reaches an optimum value as the porous layer thickness continues to increase. These results can contribute to improve the design of composite breakwaters. Full article

Lithium (Li) ion sieve is considered to have great potential in the selective extraction of Li⁺ from complex Li⁺-containing brine owing to its cost-effectiveness, excellent adsorption performance, and environmental friendliness. Nevertheless, the defects of complex regulation and control of technological parameters in the preparation process of Li ion sieve and poor recycling efficiency limit its application. In this study, spinel-type H₄Ti₅O₁₂ ion sieves (HTO) were successfully prepared through a high-temperature solid-state method for recovering Li⁺ from aqueous resources. Through the experiment of optimizing the key preparation process parameters of HTO, it was found that the optimum preparation conditions were as follows: lithium ion source of CH₃COOLi‧H₂O, calcination temperature of 800 °C, and acid (HCl) washing concentration of 0.3 mol/L. The uptake of Li⁺ by HTO aligned with the pseudo-second-order kinetic model, which was a chemical adsorption process controlled by reversible Li–H ion exchange reaction. HTO exhibited extremely high regeneration cycle characteristics, and after five cycles, it retained 96.06% of its initial adsorption capacity. The present work highlighted that spinel-type HTO has high industrial application potential in the field of Li⁺ recovery from oilfield brine. Full article

This study explores the use of a novel heterogeneous CoZnFe₄O₈ nanocatalyst for biodiesel production from a sustainable and innovative blend of waste cooking oil and neem oil feedstock. Utilizing waste cooking oil and inedible neem oil feedstock to produce biodiesel provides a green and economical way to produce renewable and environmentally friendly fuel while simultaneously reducing waste and valorizing inedible oils. Additionally, this feedstock blend does not threaten food or land resources as opposed to feedstocks obtained from edible resources. To fulfill the rising demand for biodiesel and address issues related to lower ester yields, particularly when utilizing waste cooking oils with high free fatty acid concentration, there is an urgent need for more effective processes, including two-stage transesterification. The novel CoZnFe₄O₈ nanocatalyst employed in this study demonstrated high efficiency in biodiesel production thanks to its high surface area, mesoporous structure, and catalytic properties. The effect of key process parameters, including catalyst concentration, reaction time, alcohol-to-oil molar ratio, and oil blend ratio, was investigated to evaluate the performance of the nanocatalyst and optimize the biodiesel yield with the help of Response Surface Methodology (RSM). The optimized process achieved a yield of 94.23% under optimum parameters of 2.13 wt% catalyst, 6.80:1 methanol-to-oil ratio, 4 h, and a ratio of waste cooking oil to neem oil of 98.32:1.68. The predicted and experimental values were in close agreement, indicating that the model was adequate. Additionally, detailed catalyst characterization, including analysis of the surface area, structure, and thermal stability, was carried out. Similarly, the biodiesel was characterized to assess its quality through heating value, density, Fourier Transform Infrared (FTIR) spectroscopy, and ultimate analysis. The recovery and reusability of the nanocatalyst were also investigated, highlighting its potential for multiple reaction cycles. The novel CoZnFe₄O₈ nanocatalyst and innovative feedstock blend demonstrated high efficiency in biodiesel production comparable to other nanocatalysts and feedstocks reported in the literature, highlighting their potential as an efficient and sustainable method to produce biofuels. Full article

In this study, the synergistic effects of a combination of nano additives (nano-clay (NC) and nano-silica (NS)) on the compressive strength (CS) of concrete exposed to temperatures ranging between 25 °C and 800 °C were modeled with two machine learning (ML) techniques: extreme gradient boosting (XGB) and random forest (RF) algorithms. A dataset comprising 169 compressive strength results (using four input parameters: NC dose, NS dose, temperature, and duration) was utilized for the raw data for the prediction models. The results indicated the superior performance of the XGB model in terms of the high accuracy attained in the prediction and the few errors present. Furthermore, SHAP analysis demonstrated that temperature has the highest negative impact on the prediction of the CS of nano-modified concrete. The individual conditional expectation (ICE) with partial dependence plots (PDPs) demonstrated that the optimum doses of NS and NC, leading to maximum compressive strength, were (2~3%) and (5~6%) by weight of cement. The developed models can be used as tools for optimizing mix designs to enhance fire resistance, thereby contributing to more durable and sustainable concrete construction and reducing the need for costly experimental trials. Full article

The increasing difficulty of handling industrial and agricultural wastes has generated interest in reusing materials such as Cement Kiln Dust (CKD) and Rice Husk Ash (RHA) for sustainable soil stabilization. This study examined the enhancement of lateritic soil with the incorporation of CKD (0–12%) and RHA (0–25%) by weight. An integrated experimental and Artificial Neural Network (ANN) methodology was utilized to evaluate and forecast geotechnical features. Laboratory assessments were conducted to measure Atterberg limits, Maximum Dry Density (MDD), Optimum Moisture Content (OMC), and Unconfined Compressive Strength (UCS) at 0, 7, and 28 days of curing. The results indicated significant enhancements in soil characteristics with CKD-RHA combinations. Artificial Neural Network models, including GELU, LOGSIG-3, and Leaky ReLU activation functions, accurately predicted the UCS, MDD, and OMC, achieving R² values as high as 0.980. This work underscores the efficacy of CKD-RHA mixtures in improving soil stability and the promise of ANN models as excellent prediction instruments, fostering sustainable and economical construction methodologies. Full article

Acid pickling is a vital stage in metal manufacturing during which the material is susceptible to corrosion if the process is not appropriately managed. Adding green corrosion inhibitors to the acidic solution used is one solution to this critical problem that the industry faces today. This paper examines the application of two organic substances, tea tree essential oil and the expired drug Sinecod, as green corrosion inhibitors for carbon steel in concentrated chlorohydric acid. Corrosion behavior is evaluated using the weight loss method, potentiodynamic polarization, and electrochemical impedance spectroscopy for three inhibitor concentrations (1%, 2%, 3%, and 4%) and a Blank sample. SEM analysis was performed for surface analysis. The mechanism of inhibition was also investigated by fitting the electrochemical data to adsorption isotherms such as the Langmuir and the Freundlich models. The optimum concentration proved to be 4% for both substances, with inhibition efficiencies up to 90% in the case of tea tree essential oil and up to 60% in the case of expired Sinecod, showing that the inhibitor concentration and inhibitor efficiency are directly correlated in this case. The findings of this study show the possibility of using expired pharmaceutical compounds or natural extracts as corrosion inhibitors for the concentration of acid solutions used for industrial processing. Full article

Gliders are engineless aircraft capable of maintaining altitude for extended periods and achieving long ranges. This paper presents an optimal aerodynamic design method for flying wing gliders, leveraging a combination of artificial neural networks (ANNs) as a surrogate model and genetic algorithms (GAs) for optimization. Data for training the ANN is generated using the vortex-lattice method (VLM). The study identifies optimal aerodynamic shapes for two objectives: maximum flight endurance and maximum range. A key finding is the inherent conflict between aerodynamic performance and static stability in tailless designs. By introducing a stability constraint via a penalty function, we successfully generate stable and high-performance configurations. For instance, the stabilized RG15 airfoil design achieves a maximum glide ratio of 24.1 with a robust 5.1% static margin. This represents a calculated 11.5% performance reduction compared to its unstable theoretical optimum, quantitatively demonstrating the crucial trade-off between stability and performance. The methodology provides a computationally efficient path to designing practical, high-performance, and inherently stable flying wing gliders. Full article

Improvements in the aerodynamic performance of the H-Darrieus turbine are crucial to address future energy requirements. This work aims to optimize the behavior of two adjacent turbines through the addition of a dual H-Darrieus rotor. The first rotor is composed of three NACA 0021 blades, while the second comprises a single Eppler 420 blade. This study focuses on 2D CFD simulation based on the solution of the unsteady Reynolds-averaged Navier–Stokes (URANS) equations, using the sliding mesh method and $k-\omega$ SST turbulence model. The simulation results indicate a 17% improvement in the efficiency of the two turbines integrating dual rotors, compared to the two isolated turbines, for $\alpha$ = 0°. Moreover, the power coefficient ${ (C}_P)$ reaches maximum values of 0.49, 0.42, and 0.40 for angles of attack of 30°, 25°, and 20°, respectively, at TSR = 2.51. Conversely, the selection of an optimal angle of attack allows the efficiency of the two H-Darrieus turbines to be increased. It is also shown by the results that the effect of stagnation is reduced and lift is maximized when the optimum distance between two adjacent turbines is chosen. Moreover, the overall aerodynamic performance of the system is enhanced by the potential of a dual-rotor configuration, and the wake between the two turbines is disrupted, which can result in a decrease in energy production within wind farms. Full article