Search Results (256)

In agricultural systems, excessive application of nitrogen fertilizer often leads to low nitrogen use efficiency and environmental pollution. In order to solve this problem, we studied the synergistic effect of biochar and nitrogen fertilizer on pepper yield, quality and rhizosphere soil health. This study was conducted under a temperate continental monsoon climate in Changchun, China. Using ‘Jinfu 803’ pepper (Capsicum annuum L.) as the test material, biochar was prepared from corn straw under oxygen-limited conditions at 500 °C. the comprehensive effects of the combined application of biochar (0, 0.7% soil mass ratio) and nitrogen fertilizer (0, 75, 375, 675 kg/hm² pure nitrogen) on pepper yield, fruit quality, rhizosphere soil physicochemical properties, and microbial community structure were studied. Redundancy analysis (RDA), high-throughput sequencing, and multivariate statistical methods were used to analyze the association patterns between soil environmental factors and microbial functional groups. The results showed that the combined application of biochar and nitrogen fertilizer significantly improved soil porosity (increased by 12.3–28.6%) and nutrient content, increased yield, and improved quality, among which the treatment of 0.7% biochar combined with 375 kg/hm² nitrogen fertilizer (B1N2) had the best effect. Under this treatment, the pepper yield reached 24,854.1 kg/hm², which was 42.35% higher than that of the control (B0N0). Notably, the nitrogen partial factor productivity (PFPN) of the B1N2 treatment (66.3 kg/kg) was significantly higher than that of the corresponding treatment without biochar and was not significantly lower than that of the high-nitrogen B1N3 treatment. The contents of soluble sugar and vitamin C in fruits increased by 51.18% and 39.16%, respectively. Redundancy analysis (RDA) revealed that the bacterial community structure was primarily shaped by soil pH, organic matter, and porosity, while the fungal community was predominantly influenced by alkaline hydrolyzable nitrogen and total nitrogen. Furthermore, the B1N2 treatment specifically enriched key functional microbial taxa, such as Chloroflexi (involved in carbon cycling) and Mortierellomycota (phosphate-solubilizing), which showed significant positive correlations with improved soil properties. In conclusion, B1N2 is the optimal treatment combination as it improves soil physical conditions, increases nutrient content, optimizes microbial community structure, and enhances pepper yield and quality. Full article

Solar biomass gasification results in reducing CO₂ emissions while saving biomass resources and producing higher-quality syngas when compared with conventional autothermal processes that require partial feedstock combustion for supplying the process heat. However, the solar process suffers from inherent barriers related to the variability of solar energy caused by cloud passages and shutdowns at night. The concept of hybrid solar gasification thus appears attractive for continuous and stabilized operation under intermittent or variable solar irradiation. This study addresses the dynamic simulation and control of hybrid solar–autothermal biomass gasification for continuous and stabilized syngas fuel production. A hybridization path with a constant H₂ + CO production was retained, and this control strategy was implemented in a second-by-second dynamic optimization problem using a model predictive control (MPC) algorithm. Its feasibility was demonstrated both at the small scale and industrial scale, and daily to yearly performance results were provided. For a 10 MW hybrid gasifier, the yearly solar heat share was 22% for a controlled 1000 NL/s production rate of H₂ + CO (corresponding to the complete allothermal gasification of ~2 t/h of wood at 1200 K), and this decreased with increasing H₂ + CO production objectives (17.4% at 1300 NL/s). A total of 24,200 t of wood feedstock and 8290 t of O₂ were required annually to generate 1410 t of H₂ and 19,200 t of CO, with a 1.03 average H₂:CO molar ratio. In addition, solar-only gasification and hybridization with external heating were also assessed. External auxiliary heating might be as efficient as in situ oxy-combustion and would not affect syngas composition by contamination from combustion products throughout hybridization. However, similar to external heat storage, the related thermal efficiency and heat losses must be considered. Full article

The excessive use of fossil fuels and the increasing generation of solid waste, driven by population growth, industrialization, and economic development, have led to serious environmental, energy, and public health issues. In light of this problem, it is crucial to adopt sustainable solutions that promote the transition to renewable energy sources, such as biogas. Although progress has been made in optimizing biogas production, there is still no adaptable model for various environments that allows for the determination of optimal quantities of different organic wastes, simultaneously considering their composition, moisture content, and control of critical factors for biogas production, as well as the biodigester’s capacity and other relevant elements. In practice, the dosing of waste is conducted empirically, leading to inefficiencies that limit the potential for biogas production in real scenarios. The objective of this article is to propose a linear optimization model with nonlinear constraints that maximizes biogas production, considering fundamental parameters such as the moisture percentage, pH, carbon/nitrogen ratio (C/N), substrate volume, organic matter, volatile solids (VS), and biogas production potential from different wastes. The model estimates the optimal waste composition based on the biodigester capacity to ensure balanced substrates. The results for the proposed scenarios demonstrate its effectiveness: Scenario 1 achieved 3.42 m³ (3418.67 L) of biogas, while Scenario 2, with a greater diversity of waste, reached 8.06 m³ (8061.43 L). The model maintained pH (6.49–6.50), C/N ratio (20.00), and moisture (60.00%) within optimal ranges. Additionally, a Monte Carlo sensitivity analysis (1000 simulations) validated its robustness with a 95% confidence level. This model provides an efficient tool for optimizing biogas production and waste dosing in rural contexts, promoting clean and sustainable technologies for renewable energy generation. Full article

Addressing the problems of wind power’s anti-peak regulation characteristics, increasing system peak regulation difficulty, and wind power uncertainty causing frequency deviation leading to power imbalance, this paper considers the peak shaving and valley filling function and frequency regulation characteristics of energy storage, establishing a day-ahead and intraday coordinated two-stage optimization scheduling model for research. Stage 1 establishes a deterministic wind power prediction model based on time series Autoregressive Integrated Moving Average (ARIMA), adopts dynamic peak-valley identification method to divide energy storage operation periods, designs energy storage peak regulation working interval and reserves frequency regulation capacity, and establishes a day-ahead 24 h optimization model with minimum cost as the objective to determine the basic output of each power source and the charging and discharging plan of energy storage participating in peak regulation. Stage 2 still takes the minimum cost as the objective, based on the output of each power source determined in Stage 1, adopts Monte Carlo scenario generation and improved scenario reduction technology to model wind power uncertainty. On one hand, it considers how energy storage improves wind power system inertia support to ensure the initial rate of change of frequency meets requirements. On the other hand, considering energy storage reserve capacity responding to frequency deviation, it introduces dynamic power flow theory, where wind, thermal, load, and storage resources share unbalanced power proportionally based on their frequency characteristic coefficients, establishing an intraday real-time scheduling scheme that satisfies the initial rate of change of frequency and steady-state frequency deviation constraints. The study employs improved chaotic mapping and an adaptive weight Particle Swarm Optimization (PSO) algorithm to solve the two-stage optimization model and finally takes the improved IEEE 14-node system as an example to verify the proposed scheme through simulation. Results demonstrate that the proposed method improves the system net load peak-valley difference by 35.9%, controls frequency deviation within ±0.2 Hz range, and reduces generation cost by 7.2%. The proposed optimization scheduling model has high engineering application value. Full article

This paper presents a novel control-based observer (CbO) framework for robust state and disturbance estimation in the longitudinal dynamics of fixed-wing aircraft. In this approach, the observer design problem is recast as an equivalent control problem, enabling the use of advanced control techniques for observer synthesis. Within the proposed framework, the estimation of both system states and unknown disturbance inputs is achieved by integrating disturbance rejection capabilities into the control sub-block of the observer. This integration ensures that the output mismatch between the plant and observer model is minimized, even in the presence of modeling uncertainties and external disturbances. Two observer designs are developed: (i) an ${\mathcal{H}}_{\infty }$-CbO, formulated as an ${\mathcal{H}}_{\infty }$ control problem around a linearized model at a nominal operating point, and (ii) a robust ${\mathcal{H}}_{\infty }$-CbO, which extends the design to account for significant model nonlinearities and variations by incorporating multiple operating points and optimizing for the worst-case estimation error. The longitudinal dynamics of a fixed-wing aircraft are derived and linearized to provide the basis for observer design. The performance of the proposed observers is evaluated through comprehensive simulation studies under three scenarios: operation at the nominal point, operation around neighboring points, and comparison with conventional linear observers. Simulation results demonstrate that the proposed observer offers superior robustness and accuracy in estimating both states and external disturbances, particularly in the presence of model uncertainties and varying flight conditions. Full article

Power batteries are one of the important components of electric vehicles, but the manufacturing process of vehicle power batteries is complex and diverse. Traditional scheduling methods face challenges such as low production efficiency and inadequate quality control in complex production environments. To address these issues, a multi-objective optimization model with makespan, total machine load, and processing quality as the established objectives, and a Multi-objective Particle Swarm Energy Valley Optimization (MPSEVO) is proposed to solve the problem. MPSEVO integrates the advantages of Multi-objective Particle Swarm Optimization (MOPSO) and Energy Valley Optimization (EVO). In this algorithm, the particle stability level is combined in MOPSO, and different update strategies are used for particles of different stability to enhance both the convergence and diversity of the solutions. Furthermore, a local search strategy is designed to further enhance the algorithm to avoid the local optimal solutions. The Hypervolume ($HV$) and Inverted Generational Distance ($IGD$) indicators are often used to evaluate the convergence and diversity of multi-objective algorithms. The experimental results show that MPSEVO’s $HV$ and $IGD$ indicators are better than other algorithms in 10 computational experiments, which verifies the effectiveness of the proposed strategy and algorithm. The proposed method is also applied to solve the actual battery workshop scheduling problem. Compared with MOPSO, MPSEVO reduces the total machine load by 7 units and the defect rate by 0.05%. In addition, the effectiveness of each part of the improved algorithm was analyzed by ablation experiments. This paper provides some ideas for improving the solution performance of MOPSO, and also provides a theoretical reference for enhancing the production efficiency of the vehicle power battery manufacturing workshop. Full article

The refined aerodynamic design optimization of multistage compressors is a typical high-dimensional and expensive optimization problem. This study proposes an integrated surrogate model-assisted evolutionary algorithm combined with a Directly Manipulated Free-Form Deformation (DFFD)-based parametric dimensionality reduction method, establishing a high-precision and efficient global parallel aerodynamic optimization platform for multistage axial compressors. The DFFD method achieves a balance between flexibility and low-dimensional characteristics by directly controlling the surface points of blades, which demonstrates a particular suitability for the aerodynamic design optimization of multistage axial compressors. The integrated surrogate model enhances prediction accuracy by simultaneously identifying optimal solutions and the most uncertain solutions, effectively addressing highly nonlinear design space challenges. A three-stage axial compressor in a heavy-duty gas turbine is selected as the optimization object. The results demonstrate that the optimization task takes less than 48 h and achieves an improvement of 0.6% and 4% in the adiabatic efficiency and surge margin, respectively, while maintaining a nearly unchanged flow rate and pressure ratio at the design point. The proposed approach provides an efficient and reliable solution for complex aerodynamic optimization problems. Full article

Weeds are one of the main problems in cultivation of medicinal and aromatic plants (MAPs); they negatively affect yield (herba and essential oil), and the overall quantity and quality of biomass, flowers, roots, seeds, and secondary metabolites. This review evaluates mulching as a sustainable, non-chemical method for weed management in the cultivation of MAPs and examines how effectively organic, synthetic, and living mulches reduce weeds and increase yields. Regarding different mulch materials such as straw, sawdust, bark, needles, compost, polyethylene, and biodegradable films, the basic processes of mulch activity, including light interception, physical suppression, and microclimate adjustment, are examined. The review further analyzes the impact of mulching on soil parameters (moisture, temperature, pH, chlorophyll content) and the biosynthesis of secondary metabolites. The findings consistently indicate that mulching substantially reduces weed biomass, improves crop performance, and supports organic farming practices. However, there are still issues with cost, material availability, and possible soil changes, and the efficacy is affected by variables including cultivated plant species, mulch type, and application thickness. The review highlights the importance of further research to optimize the selection of mulch and MAPs and their application across various agroecological conditions, and indicates that mulching is a potential, environmentally friendly technique for weed control in MAP cultivations. Full article

When desalinated water enters the existing drinking water distribution systems (DWDSs), the balance between water and scale will be destroyed, resulting in the release of iron and water quality problems, causing “yellow water”. This study investigated the inhibitory effects of pH, alkalinity, and phosphate on iron release and the optimal control condition using pipe section reactors with a response surface. For steel pipe, the optimal condition for iron release control was pH = 8.5, alkalinity = 250 mg/L CaCO₃, and phosphate = 0.1 mg/L. For cast iron pipe, the optimal condition was pH = 8.0, alkalinity = 250 mg/L CaCO₃, and phosphate = 0.1 mg/L. This study can provide theoretical support for subsequent water supply safety and lay a foundation for the water supply safety of the municipal pipe network. Full article

Background: Dental caries is a prevalent dental problem affecting primary and permanent teeth. Early demineralization of enamel lesions can be reversed through remineralization. Many studies have focused on caries prevention and disease progression arrest using silver diamine fluoride (SDF). No in vitro studies have compared the remineralization effects of different 38% SDF solutions on artificially demineralized enamel lesions. This study aimed to compare the remineralization potential of three commercial 38% silver diamine fluoride formulations on artificial enamel lesions in primary teeth using a pH cycling model. The hypothesis was as follows: different commercial SDF formulations would exhibit varying remineralization effects, as measured by surface microhardness, due to potential differences in their compositions. Materials and Methods: In this study, 75 primary molars were randomized into five groups (N = 15): I: baseline, II: SDF Riva Star Aqua^® 38%, III: Riva Star^® 38%, IV: SDF Advantage Arrest^® 38%, and V: control. Artificial caries were created by submerging teeth in 10 mL of demineralization solution (pH 4.5) for three days in a light-resistant container, ensuring distinct visual changes in the enamel as per the International Caries Detection and Assessment System (ICDAS level 2). After pH cycling, all samples underwent a standardized Vickers microhardness test (VMHT) with a 50 g load for 15 s. Data were analyzed using one-way ANOVA and Tukey’s post hoc test, with a significance level set at p ≤ 0.05. Results: The one-way ANOVA test indicated a significant difference in microhardness among the groups (SDF Riva Star Aqua, SDF Riva Star, and SDF Advantage Arrest), with an F-value of 167.73 and p < 0.001. The post hoc Scheffé test showed that SDF Riva Star Aqua and SDF Riva Star were not significantly different (p = 0.388). However, SDF Advantage Arrest had a significantly higher mean microhardness compared to both groups (p < 0.001). Overall, these results show that SDF Advantage Arrest leads to greater microhardness than SDF Riva Star Aqua or SDF Riva Star. Conclusions: SDF Advantage Arrest showed superior performance among the SDF-treated groups, significantly increasing microhardness compared to SDF Riva Star Aqua and SDF Riva Star. This suggests that SDF Advantage Arrest offers enhanced remineralization and structural strengthening, making it the most effective option for managing demineralized primary teeth. Future research should investigate the long-term performance and mechanisms of these treatments to optimize clinical protocols for preserving primary tooth integrity. Full article

This paper proposes a novel Guidance and Control architecture for close-range rendezvous and final approach of a chaser spacecraft towards a non-cooperative and tumbling space target. In both phases, reference trajectory generation relies on a Sequential Convex Programming algorithm which iteratively solves a non-linear optimization problem accounting for propellant consumption, relative dynamics, collision avoidance and navigation sensor pointing constraints. At close range, trajectory tracking is entrusted to a translational H-infinity controller, coupled with a quaternion-feed-back regulator for target pointing. In the final approach phase, an attitude-pointing strategy is adopted, requiring a six degree-of-freedom H-infinity controller to follow a reference roto-translational trajectory generated to ensure target-chaser motion synchronization. Performance is evaluated in a high-fidelity simulation environment that includes environmental perturbations, navigation errors, and actuator (i.e., cold gas thrusters and reaction wheels) modelling. In particular, the latter aspects are also addressed by integrating the proposed solution within a complete Guidance, Navigation and Control pipeline including a state-of-the-art LIDAR-based relative navigation filter and a dispatching function for the distribution of commanded control actions to the actuation system. A statistical analysis on 1000 simulations shows the robustness of the proposed approach, achieving centimeter-level position accuracy and sub-degree attitude accuracy near the docking/berthing point. Full article

Background: The release study is a standard tool for the development, evaluation, and control of dosage forms. In the case of traditional drug delivery systems, it is conducted in accordance with the established principles available in the European and American Pharmacopoeias or guidelines proposed by registration agencies. The problem is the study of modern carriers, not yet described in compendia, which require adjustments to traditionally used methods. Objectives: The present study focuses on developing an optimal method for testing the release of cyclosporine (Cs, 0.5–4%) incorporated in solid lipid microparticles (SLM) dispersions (10%) intended for administration in the form of eye drops. This is a multicompartment lipid carrier that provides prolonged release of the active substance. Methods: Three methods of testing the release were compared: the dialysis bag method, the horizontal cells technique, and a method without a membrane. Results: During the analyses, the proper membrane was selected and the effect of the lysozyme enzyme on the release profile was analyzed. The effect of the composition of the acceptor fluid on the obtained results was also assessed. In the model without a membrane, up to 60% of the Cs was released within 30 min due to the burst effect. In horizontal chambers, no formulation released more than 14% of the Cs over 96 h, while at the same time, 60–70% of the Cs was released from the dialysis bag. Conclusions: Based on the obtained results, the dialysis bag method was selected to study the release of Cs from SLM without the need to use multicomponent artificial tear fluid as an acceptor medium. Full article

The usage of fossil fuels has resulted in increasingly severe environmental problems, such as climate change, air pollution, water pollution, etc. Hydrogen energy is considered one of the most promising clean energies to replace fossil fuels due to its pollution-free and high-heat properties. However, the oxygen evolution reaction (OER) remains a critical challenge due to its high overpotential and slow kinetics during water electrolysis for hydrogen production. Electrocatalysts play an important role in lowering the overpotential of OER and promoting the kinetics. Co₃O₄-based electrocatalysts have emerged as promising candidates for the oxygen evolution reaction (OER) due to their favorable catalytic activity and good compatibility compared with precious metal-based electrocatalysts. This review presents a summary of the recent developments in the synthesis strategies and mechanisms of Co₃O₄-based electrocatalysts for the OER. Various synthesis strategies have been explored to control the size, morphology, and composition of Co₃O₄ nanoparticles. These strategies enable the fabrication of well-defined nanostructures with enhanced catalytic performance. Additionally, the mechanisms of OER catalysis on Co₃O₄-based electrocatalysts have been elucidated. Coordinatively unsaturated sites, synergistic effects with other elements, surface restructuring, and pH dependency have been identified as crucial factors influencing the catalytic activity. The understanding of these mechanisms provides insights into the design and optimization of Co₃O₄-based electrocatalysts for efficient OER applications. The recent advancements discussed in this review offer valuable perspectives for researchers working on the development of electrocatalysts for the OER, with the goal of achieving sustainable and efficient energy conversion and storage systems. Full article

The varying characteristics of grid-connected energy resources necessitate a clear and effective approach for managing and scheduling generation units. Without proper control, high levels of renewable integration can pose challenges to optimal dispatch, especially as more generation sources, like wind and solar PV, are introduced. As a result, conventional power sources require an advanced management system, for instance, a virtual power plant (VPP), capable of accurately monitoring power supply and demand. This study thoroughly explores the dispatch of battery energy storage systems (BESSs) and diesel generators (DGs) through a distributionally robust joint chance-constrained optimization (DR-JCCO) framework utilizing the conditional value at risk (CVaR) and heuristic-X (H-X) algorithm, structured as a bilevel optimization problem. Furthermore, Binomial expansion (BE) is employed to linearize the model, enabling the assessment of BESS dispatch through a mathematical program with equilibrium constraints (MPECs). The findings confirm the effectiveness of the DRO-CVaR and H-X methods in dispatching grid network resources and BE under the MPEC framework. Full article

This paper investigates the well-posedness of the inverse problem for the time-fractional Burgers equation, which aims to reconstruct initial conditions from terminal observations. Such equations are crucial for the modeling of hydrodynamic phenomena with memory effects. The inverse problem involves inferring initial conditions from terminal observation data, and such problems are typically ill-posed. A framework based on optimal control theory is proposed, addressing the ill-posedness via $H^1$ regularization. Three substantial results are achieved: (1) a rigorous mathematical framework transforming the ill-posed inverse problem into a well-posed optimization problem with proven existence of solutions; (2) theoretical guarantee of solution uniqueness when the regularization parameter is $\alpha >0$ and the stability is of order O($\delta$) with respect to observation noise ($\delta$); and (3) the discovery of a “super-stability” phenomenon in numerical experiments, where the actual stability index (0.046) significantly outperforms theoretical expectations (1.0). Finally, the theoretical framework is validated through comprehensive numerical experiments, demonstrating the accuracy and practical effectiveness of the proposed optimal control approach for the reconstruction of hydrodynamic initial conditions. Full article