Search Results (2,304)

This article is devoted to the design of a real-time gain scheduling (adaptive) proportional–integral (PI) controller for the displacement volume regulation of a swash plate-type axial piston pump. The pump is intended for open circuit hydraulic drive applications without “secondary control”. In this type of pump, the displacement volume depends on the swash plate swivel angle. The swash plate is actuated by a hydraulic-driven mechanism. The classical control device is a hydro-mechanical type, which can realize different control laws (by pressure, flow rate, or power). In the present development, it is replaced by an electro-hydraulic proportional spool valve, which controls the swash plate-actuating mechanism. The designed digital gain scheduling controller evaluates control signal values applied to the proportional valve. The digital controller is based on the new linear parameter-varying mathematical model. This model is estimated and validated from experimental data for various loading modes by an identification procedure. The controller is implemented by a rapid prototyping system, and various real-time loading experiments are performed. The obtained results with the gain scheduling PI controller are compared with those obtained by other classical PI controllers. The developed control system achieves appropriate control performance for a wide working mode of the axial piston pump. The comparison analyses of the experimental results showed the advantages of the adaptive PI controller and confirmed the possibility for its implementation in a real-time control system of different types of variable displacement pumps. Full article

With a high proportion of renewable energy sources connected to the distribution network, traditional optimal power flow (OPF) methods face significant challenges including multi-objective co-optimization and dynamic scenario adaptation. This paper proposes a dynamic optimization framework based on the Dynamic Gravitational Search Algorithm (DynaG) for a multi-energy complementary distribution network incorporating wind power, photovoltaic, and energy storage systems. A multi-scenario OPF model is developed considering the time-varying characteristics of wind and solar penetration (low/medium/high), seasonal load variations, and demand response participation. The model aims to minimize both network loss and operational costs, while simultaneously optimizing power supply capability indicators such as power transfer rates and capacity-to-load ratios. Key enhancements to DynaG algorithm include the following: (1) an adaptive gravitational constant adjustment strategy to balance global exploration and local exploitation; (2) an inertial mass updating mechanism constrained to improve convergence for high-dimensional decision variables; and (3) integration of chaotic initialization and dynamic neighborhood search to enhance solution diversity under complex constraints. Validation using the IEEE 33-bus system demonstrates that under 30% penetration scenarios, the proposed DynaG algorithm reduces capacity ratio volatility by 3.37% and network losses by 1.91% compared to non-dominated sorting genetic algorithm III (NSGA-III), multi-objective particle swarm optimization (MOPSO), multi-objective atomic orbital search algorithm (MOAOS), and multi-objective gravitational search algorithm (MOGSA). These results show the algorithm’s robustness against renewable fluctuations and its potential for enhancing the resilience and operational efficiency of high-penetration renewable energy distribution networks. Full article

This paper presents an automatic oil sampling system designed for vertical cylindrical oil tanks on land, focusing primarily on the structural design and control optimization for oil level measurement and liquid sampling inside the tank. First, the key structure and control architecture of the automatic sampler are introduced, explaining the collaborative working principles of its components to ensure good stability in system structure and motion control. On this basis, an improved Sparrow Search Algorithm (CSSA) is proposed, which integrates the Coati Optimization Algorithm (COA) and the traditional Sparrow Search Algorithm (SSA). This algorithm is used to optimize the parameters of the Proportional–Integral–Derivative (PID) control system in the oil sampler, aiming to address issues such as response delay, large overshoot, and insufficient stability that commonly occur in traditional PID control under complex conditions. This method achieves consistent response behavior over time and adaptiveness in the control process by dynamically adjusting the PID parameters in real time. To verify the effectiveness of the proposed control strategy, system simulations were conducted in the MATLAB 2024B environment, and a physical experimental platform was built for testing. The simulation compares the CSSA-PID controller with traditional PID, COA-PID, and SSA-PID control methods. In addition, a load disturbance was introduced at 300 ms to perform anti-interference comparative simulations. The results show that under CSSA-PID control, the system response time was shortened by up to 112 ms, the convergence speed improved by 72.3%, the global optimization capability was significantly enhanced, and the anti-interference ability was stronger. In the actual tests, the average error was reduced by approximately 45.3%. These results indicate that CSSA-PID can significantly enhance the stability and response speed of the control system. The efficient control of the automatic oil sampler will greatly enhance the intelligence and efficiency of oil level detection in tanks and reduce labor costs, having significant implications for the development of the grain and oil storage industry. Full article

Soy protein isolate (SPI) microgels were produced via heat-set gelation (4, 6, 8, and 10% by mass) followed by ultrasonication (400 W, 70% amplitude, 3 or 6 min) and used as stabilizers of oil–water emulsions (10% oil phase). The SPI concentration and ultrasonication time affected microgel size (236–356 nm) and polydispersity (0.253–0.550). The physical stability of the emulsions stabilized with 6 and 8% SPI microgels (6 min of ultrasonication) was evaluated for 14 d, influencing on the average size, creaming index and instability index of the emulsions, where those with 6% SPI microgels resulted in a major stability. The emulsions produced with these microgels encapsulated beta-carotene and were incorporated into whole yogurt at three concentrations: 5 (YE5), 10 (YE10), and 15% (YE15). The addition of the emulsions did not affect the physicochemical or microbiological quality of the yogurt. Rheological tests revealed that the yogurt behaved as a non-Newtonian and pseudoplastic fluid, with yogurts with more emulsions being less viscous. Sensory evaluation revealed consumer acceptance regarding color and texture; however, the perception of residual flavor was proportional to the amount of emulsion added. SPI microgels are effective stabilizers for β-carotene-loaded emulsions and a promising strategy for this compound delivery in yogurt. Full article

Pressure-sensitive adhesion arises at a specific rheological behavior of polymer systems, which should correlate with their relaxation properties, making them potentially useful for predicting and altering adhesive performance. This work systematically studied the rheology of eco-friendly pressure-sensitive adhesives based on non-crosslinked polyisobutylene ternary blends free of solvents and byproducts, which serve for reversible adhesive bonding. The ratio between individual polymer components differing in molecular weight affected the rheological, relaxation, and adhesion properties of the constituted adhesive blends, allowing for their tuning. The viscosity and viscoelasticity of the adhesives were studied using rotational rheometry, while their adhesive bonds with steel were examined by probe tack and shear lap tests at different temperatures. The adhesive bond durability at shear and pull-off detachments depended on the adhesive composition, temperature, and contact time under pressure. The double differentiation of the continuous relaxation spectra of the adhesives enabled the accurate determination of their characteristic relaxation times, which controlled the durability of the adhesive bonds. A universal linear correlation between the reduced failure time of adhesive bonds and their reduced formation time enabled the prediction of their durability with high precision (Pearson correlation coefficient = 0.958, p-value < 0.001) over at least a four-order-of-magnitude time range. The reduction in the formation/failure times of adhesive bonds was most accurately achieved using the longest relaxation time of the adhesives, associated with their highest-molecular-weight polyisobutylene component. Thus, the highest-molecular-weight polymer played a dominant role in adhesive performance, determining both the stress relaxation during the formation of adhesive bonds and their durability under applied load. In turn, this finding enables the prediction and improvement of adhesive bond durability by increasing the bond formation time (a durability rise by up to 10–100 times) and extending the adhesive’s longest relaxation time through elevating the molecular weight or proportion of its highest-molecular-weight component (a durability rise by 100–350%). Full article

High-power laser diodes (LDs) inherently generate considerable heat during current loading, which presents substantial challenges to the stable operation of laser systems. This study reports a machine learning-based approach that is to be applied to LD temperature control systems, in which a fuzzy neural network (FNN) algorithm is integrated with a proportional-integral-derivative (PID) controller to create an FNN-PID control architecture. The proposed algorithms synergistically integrate fuzzy rule-based systems with neural network learning frameworks, and, furthermore, facilitate adaptive parameter optimization while preserving the interpretability of the decision-making process. Applying the optimized algorithm temperature controller to the LD with output optical power of 110 W @ 888 nm, compared with the conventional PID, the FNN-PID algorithm has shortened the temperature settling time by 77% during 100 W heat generation in LD, the long-term temperature fluctuation is decreased from ±0.126% to ±0.06%, the corresponding optical power steady-state precision is decreased from ±0.09% to ±0.04%, and the step response time of temperature and corresponding power are reduced by 73.4% and 70% from 25 °C to 27 °C, respectively. The FNN-PID outperforms conventional methods (the PID algorithm and the Fuzzy-PID algorithm) in managing thermal fluctuations, and it offers potential for precise laser control applications to enhance beam quality and stability. Full article

Hydrogen-induced steel embrittlement imposes a technical difficulty in facilitating effective and safe hydrogen transportation via pipelines. This investigative study assesses the potency of polyvinylidene fluoride (PVDF)–graphene-based composite coatings in the inhibition of hydrogen permeation. Spin coating was the method selected for this study, and varying graphene concentrations ranging from 0.1 to 1wt% were selected and applied to 306 stainless steel substrates. A membrane permeation cell was used in the evaluation of hydrogen permeability, while the impact of graphene loading on coating performance was analyzed using the response surface methodology (RSM). The outcomes showed an inversely proportional relationship between the graphene concentration and hydrogen ingress. The permeation coefficient for pure PVDF was recorded as 16.74, which decreased to 14.23, 12.10, and 11.46 for 0.3, 0.5, and 1.0 wt% PVDF-G, respectively, with the maximum reduction of 31.6% observed at 1.0 wt%. ANOVA established statistical significance, along with indications of strong projection dependability. However, the inhibition reduction stabilized with increasing graphene concentrations, likely caused by nanoparticle agglomeration. The results support the notion of PVDF–graphene’s potential as a suitable coating for the transformation of pipelines for hydrogen transport infrastructure. This research will aid in the establishment of suitable contemporary barrier coating materials, which will enable the safe utilization of hydrogen energy in the current energy transportation grid. Full article

Alkali-activated fly ash and slag binders are regarded as environmentally friendly building materials. However, the creep properties of the alkali-activated materials differ from ordinary Portland cement-based materials. Currently, predicting the creep properties of alkali-activated materials is difficult. This study tested the creep properties of alkali-activated materials with various strengths and loading ages, exploring the similarities and differences in the creep properties between alkali-activated and cement-based materials. The result shows that the creep development of alkali-activated materials still conforms to the law of the hyperbolic power function commonly used to describe that of cement-based materials. Nevertheless, the proportion of the basic creep increases to about 70% of the drying creep in alkali-activated materials at 90 days. By modifying the parameters related to the relative humidity in the model of CEB-FIP MC2010, the creep behavior of alkali-activated fly ash and slag concrete could be well predicted. Full article

This study investigates the energy consumption characteristics of individual and clustered thermal storage electric heating systems, focusing on their sustainability implications for regional load distribution and user energy consumption patterns. Simulation results show that thermal storage electric heating shifts peak energy demand from daytime to nighttime low-price hours, reducing electricity costs and optimizing grid load balancing. As the proportion of thermal storage electric heating increases from 10% to 30%, the daytime minimum load reduction rate rises from 7% to 22%, while the nighttime maximum load increase rate increases from 16% to 63%. This operational mode supports sustainable energy usage by alleviating daytime grid peak pressure and leveraging low-cost, off-peak electricity for heat storage. The findings highlight the potential of thermal storage electric heating to enhance energy efficiency, integrate renewable energy, and promote grid stability, contributing to a more sustainable energy system. Full article

Islanded DC microgrids face challenges in voltage stability and communication overhead due to renewable energy variability. A novel enhanced distributed coordinated control framework, based on adaptive event-triggered mechanisms, is developed for the efficient management of multiple hybrid energy storage systems (HESSs) in islanded DC microgrids (MGs). We propose a hierarchical distributed control framework integrating ANN-based controllers and adaptive event-triggered mechanisms to dynamically regulate power flow and minimise communication. This system utilises a hierarchical coordinated control method (HCCM) with primary virtual resistance droop control integrated with state-of-charge (SoC) management and secondary control for voltage regulation and proportional current distribution through optimised communication networks. The integration of artificial neural network (ANN)-based controllers alongside traditional PI control leads to an improvement in system responsiveness. The control approach dynamically adjusts the trigger parameters to minimise communication overhead with tight voltage regulation. An extensive simulation using MATLAB/Simulink shows how the system can effectively manage variability in renewable energy sources and maintain stable voltage profiles with precise power distribution and minimal bus voltage fluctuations. Simulations confirm enhanced voltage regulation (±0.5% deviation), proportional current sharing (98% accuracy), and 60% communication reduction under load transients (outcomes). Full article

Staggered floor frame structures with good spatial adaptability are widely used in large-space civil buildings such as conference halls and terminal buildings. However, the short columns formed by staggered floor slabs significantly affect load transfer, which is unfavorable to the seismic performance of the structure. To address this issue, based on a practical project, this paper establishes a finite element analysis model, sets up steel-tube-reinforced concrete (ST-RC) columns at staggered floors to improve the insufficient ductility of short columns, and adopts the dynamic time–history analysis method combined with performance-based evaluation methods to study the effects of different seismic input angles (0°, 30°, 60°, 90°) on the seismic performance of local staggered floor frame structures at both the overall and member levels. The research results show that at the overall level, the fourth floor of the staggered floor frame structure is the weak floor, and the most unfavorable seismic input angle is 60°; additionally, at the member level, the damage of each member meets the performance objectives. Frame beams are more severely damaged under 0° and 90° seismic input, frame columns are more severely damaged under 30° and 60° seismic input, and the damage degree of ST-RC columns is similar in the four directions. As energy-dissipating members, frame beams have a significantly higher proportion of nonlinear strain energy than frame columns and ST-RC columns, which can effectively consume a large amount of seismic energy and enable the structure to retain more safety reserves. Therefore, for irregular buildings such as staggered floor frame structures that are prone to damage due to insufficient ductility of short columns, setting ST-RC columns at staggered floors can effectively reduce structural damage. The adoption of evaluation methods at both the overall structural and member levels enables a comprehensive understanding of the damage status of staggered floor structures. Full article

The microcrack initiation and evolution behavior of Fe-C alloy under uniaxial tensile loading are investigated using molecular dynamics (MD) simulations. The model is stretched along the z-axis at a strain rate of 2 × 10⁹ s⁻¹ and temperatures ranging from 300 to 1100 K, aiming to elucidate the microscopic deformation mechanisms during crack evolution under varying thermal conditions. The results indicate that the yield strength of Fe-C alloy decreases with a rising temperature, accompanied by a 25.2% reduction in peak stress. Within the temperature range of 300–700 K, stress–strain curves exhibit a dual-peak trend: the first peak arises from stress-induced transformations in the internal crystal structure, while the second peak corresponds to void nucleation and growth. At 900–1100 K, stress curves display a single-peak pattern, followed by rapid stress decline due to accelerated void coalescence. Structural evolution analysis reveals sequential phase transitions: initial BCC-to-FCC and -HCP transformations occur during deformation, followed by reversion to BCC and unidentified structures post-crack formation. Elevated temperatures enhance atomic mobility, increasing the proportion of disordered/unknown structures and accelerating material failure. Higher temperatures promote faster potential energy equilibration, primarily through accelerated void growth, which drives rapid energy dissipation. Full article

Owing to the recent attention towards the growing issue of global warming, the automotive industry is shifting towards more capable and eco-friendly vehicles with longer ranges than conventional vehicles. Although the transition to eco-friendly vehicles faces several challenges, including component failures due to mechanical wear, electrical voltage fluctuations, motor damage from overloads, infrastructure, and external environmental disturbances. The four-wheel independent drive electric vehicle (4WID-EV) is often used as an alternative to the single-drive electric vehicle, providing improved traction control and reducing the increased load on the individual motors. This study proposes an optimally enhanced controller to control the linear and nonlinear trajectories of four independent motors to evaluate the electric vehicle’s speed and address challenges involved in torque distribution to the independent drive, especially under various motor failure conditions. The computed results reveal that the proposed optimal linear quadratic regulator (LQR) controller accurately predicts better than the conventional proportional integral derivative (PID) controller in terms of the vehicle’s speed under various motor failures. Specifically, the optimal LQR controller achieves a faster settling time of 2.5 s, a lower overshoot of 0.8%, a mean error of 0.0441 rad/s, and a mean squared error (MSE) of 0.0820 (rad/s²). These results indicate that the proposed controller enhances stability and accuracy, improving adaptability even under motor failure conditions in 4WID-EVs. Full article

In the pursuit of sustainable and circular energy sources, this study examines the potential of tire pyrolysis oil (TPO) as a diesel fuel substitute when combined with hydrotreated vegetable oil (HVO), a second-generation biofuel. At varying TPO-HVO blend percentages, this investigation evaluates engine performance and emissions in relation to critical fuel parameters, including density, viscosity, and lubricity. The high-frequency reciprocating rig (HFRR) method was employed to examine tribological aspects, and a single-cylinder diesel engine was tested under various load conditions. The findings indicated that blends containing up to 30% TPO maintained sufficient lubrication and engine performance to comply with diesel standards, concurrently reducing carbon monoxide and smoke emissions. The increase in TPO proportion resulted in a decrease in cetane number, an increase in NOx emissions, and a rise in viscosity, particularly under full engine load conditions. The utilization of TPO is crucial for converting tire waste into fuel, as it mitigates the accumulation of tire waste and reduces dependence on fossil fuels, despite existing challenges. This study provides critical insights into the efficacy of blending methods and underscores the necessity of additional fuel refining processes, such as cetane enhancement and desulfurization, to facilitate their integration into transportation energy systems. Full article

Pt/TiO₂ and Pt-Eu₂O₃/TiO₂ catalysts were prepared via the impregnation method for catalytic oxidation of CO. The Pt-2Eu₂O₃/TiO₂ catalyst exhibited better CO oxidation activity as well as greater SO₂ resistance than the Pt/TiO₂ catalyst. For the inlet gas consisting of 0.8% CO, 5% O₂, and balanced N₂, the lowest complete conversion temperatures (T₁₀₀) of CO were 120 °C and 140 °C for the Pt-2Eu₂O₃/TiO₂ and Pt/TiO₂ catalysts, respectively. During the 72 h SO₂-resistance test at 200 °C under an inlet gas composition of 0.8% CO, 5% O₂, 15% H₂O, 50 ppm SO₂, and balanced N₂, the CO conversion on the Pt-2Eu₂O₃/TiO₂ catalyst remained >99%, while that on the Pt/TiO₂ catalyst gradually decreased to 77.8%. Pre-loading 2 wt% Eu₂O₃ on TiO₂ enhanced the dispersion of Pt, increased the proportion of Pt⁰, and facilitated the adsorption and dissociation of H₂O, all of which promoted CO oxidation. SO₂ preferentially occupied the Eu₂O₃ sites by forming stable sulfates on the Pt-2Eu₂O₃/TiO₂ catalyst, which protected the Pt active sites from poisoning. The OH* species produced from the dissociation of H₂O played a significant role in promoting CO oxidation through the formation of COOH* as the key reaction intermediate. The developed Pt-2Eu₂O₃/TiO₂ catalyst has great application potential in terms of the removal of CO from industrial flue gases. Full article