Search Results (349)

This comprehensive study presents an integrated analysis of NO_x reduction strategies and operational optimization for the HYUNDAI-HiMSEN 7H35DFP dual-fuel marine engine. The optimization scope focuses on selective catalytic reduction control strategies and operational decision-making (fuel mode selection, load management) rather than engine hardware modifications, ensuring practical applicability within certified marine engine operational envelopes. The research employs a multifaceted approach combining experimental investigation, computational fluid dynamics (CFD) modeling, and advanced control algorithms to address the stringent IMO Tier III emission standards. The 3500 kW, 7-cylinder engine achieves IMO Tier III compliance through dual pathways: (1) gas mode operation meeting the 2.4 g/kWh limit inherently with measured emissions of 1.41–2.29 g/kWh across 25–100% load without aftertreatment, and (2) diesel mode achieving compliance via SCR aftertreatment, reducing Tier II baseline emissions (7.68–10.71 g/kWh) by 75–82% to final values of 1.60–1.96 g/kWh. The research quantifies NO_x reduction mechanisms separately for each operating mode and establishes optimal operational strategies for mode selection. A MATLAB v2025a-based SCR optimization model successfully predicts optimal urea injection rates, achieving >75% NO_x reduction efficiency across all operating conditions. Multivariate analysis using principal component analysis identifies the following three primary factors explaining 89.3% of dataset variability: combustion intensity (45.2%), fuel mixing characteristics (28.7%), and thermal management (15.4%). CFD analysis reveals that gas mode combustion produces more uniform temperature distributions (peak ~2000 K) compared to diesel operation (>2200 K), directly explaining NO_x generation differences. The developed digital twin framework with machine learning algorithms achieves 94.2% accuracy in SCR catalyst degradation prediction and 91.8% in fuel injection system performance prediction. Waste heat recovery analysis indicates 25–30% of fuel energy resides in exhaust gases, with theoretical energy recovery potential of 8.5–15.3%. This integrated approach validates dual-fuel technology’s capability to meet current and future maritime environmental regulations while maintaining operational flexibility. Full article

Cu-SSZ-13, the most widely used catalyst in diesel selective catalytic reduction (SCR) systems, often suffers severe deactivation, including hydrothermal aging and ash poisoning. In comparison with traditional impregnation in laboratory work, a more realistic solid-state diffusion method was employed to simulate K₂SO₄ poisoning on a commercial Cu-SSZ-13 catalyst with high aluminum and copper contents. Hydrothermal aging at 650 °C alone induces severe framework dealumination and transformation of isolated Cu²⁺ ions to copper aluminate (CuAlO_x) species. K₂SO₄ poisoning alone is more prone to detached Cu²⁺ ions and aluminum terminal hydroxyl group to form CuSO₄ and Al₂(SO₄)₃. The presence of water vapor during K₂SO₄ poisoning dramatically reduces SCR activity by accelerating the ion-exchange between K⁺ and Cu²⁺ and zeolite dealumination. These synergistic effects promote extensive detachment of active Cu species, resulting in the formation of predominating inert sulfates, along with a small amount of CuO_x clusters. These findings are expected to provide a theoretical basis for designing catalysts with enhanced resistance to both hydrothermal aging and ash poisoning in diesel aftertreatment applications. Full article

The detection of low-altitude slow-small (LSS) targets, such as drones, is challenged by their small radar cross-section (RCS) and low signal-to-clutter ratio (SCR), resulting in short effective range and susceptibility to background clutter in complex environments. To overcome the limitations of conventional radar and electro-optical methods, this paper proposes a novel detection theory based on broadband spectral modulation imaging (BSMI). We analyze the recognition accuracy for drone targets across different zenith angles and detection ranges through numerical simulations. A snapshot-based BSMI detection system was designed and implemented, with experiments conducted under consistent conditions for validation. Results demonstrate that the system achieves over 90% classification accuracy, confirming the theory’s effectiveness. This study significantly enhances detection probability and suppresses false alarms for low-altitude drones, providing a viable technical solution for monitoring unauthorized aerial activities. Full article

Growing renewable penetration increases deep peak-shaving demands, making stable wide-load operation of coal-fired boilers essential. A full-process CFD model of a 660 MW ultra-supercritical boiler was established, covering the furnace, heat-transfer surfaces, rear-pass duct, and selective catalytic reduction (SCR) system. Simulations at 25–100% boiler maximum continuous rating (BMCR) quantified load effects on combustion and emissions. Predicted furnace outlet temperature and major flue-gas species matched field data with deviations within ±6%. Lowering the load from 100% to 25% BMCR contracted the high-temperature core in the furnace and reduced mean temperature and mixing. Furnace nitrogen oxides (NO_x) formation decreased as the load decreased. However, NO_x at 25% BMCR increased because separated over-fire air (SOFA) was not applied. Reduced combustion intensity increased the level of unburned carbon in fly ash, which rose by approximately 3.5% at 25% BMCR, relative to the rated condition. Pronounced flow maldistribution also appeared at 25% BMCR. The SCR-inlet flow analysis indicated that the original guide vane design was not suitable for wide-load operation and that inlet-velocity uniformity deteriorated, especially at low loads. An optimized guide vane scheme is proposed, improving SCR-inlet uniformity over the full load range while mitigating ash deposition and erosion risks. Full article

The One Health framework highlights the interconnectedness of human, animal, and environmental health, requiring interdisciplinary and multisectoral collaboration to address complex global health challenges. This scoping review protocol aims to guide the systematic mapping on how studies and policy initiatives have incorporated socioecological interconnections within the One Health paradigm, following the Joanna Briggs Institute guidance and the PRISMA Scr checklist. The experimental design includes searches in PubMed, Scopus, Web of Science, LILACS, Health Systems Evidence, Social Systems Evidence, and Google Scholar for the period from 2004 to 2025. The strategy, developed with librarian support and peer reviewed, includes terms in English, Portuguese, and Spanish. Pilot searches retrieved 5333 PubMed and 470 LILACS records. Eligible documents must explicitly present two or more of the six One Health dimensions: policies to strengthen health systems; antimicrobial resistance; food safety; environmental health; emerging and re-emerging zoonotic epidemics and pandemics; endemic zoonotic, neglected tropical and vector-borne diseases. A standardized tool was developed for data extraction, synthesizing in narrative, tabular, and graphical formats. The protocol’s utilization will provide comprehensive mapping of practices and policies, identifying achievements, barriers, and knowledge gaps to inform future strategies and strengthen global health governance. Full article

Unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) systems have been widely applied in various scenarios recently. This paper aims to maximize the total secure communication rate (SCR) of multiple users while ensuring the minimum beamforming gain towards sensing targets under the surveillance of multiple UAV warden swarms. To reduce the risk of detection, a novel type of artificial noise (AN) is introduced to interfere with swarm wardens. We conduct an analysis of the detection error probability (DEP) of these wardens and subsequently establish a mathematical model. In this model, the SCR is maximized subject to power, trajectory, sensing performance, and secure communication constraints. Since the problem is non-convex and the variables to be optimized are numerous and complex, we decompose the problem into three sub-problems. Then, an overall algorithm is proposed to solve these sub-problems separately. Simulation results demonstrate that the proposed scheme leads to a significant increase in the SCR. Moreover, the system exhibits highly stable performance in both communication and sensing tasks over time, indicating its robustness and reliability. Additionally, communication fairness among users is ensured, and energy efficiency is enhanced. Full article

Background: The extraordinary disturbances faced by the hotel industry, ranging from worldwide health problems to political instability and climate change, have highlighted the insistent need for more resilient and agile supply chain (SC) systems. This study explored how artificial intelligence (AI) capabilities can generate competitive advantage (CA) through supply chain agility (SCA) and supply chain resilience (SCR) as mediators and competitive pressure (CP) as a moderator. Methods: Drawing on the resource-based view (RBV) framework, we suggested and empirically tested the study model. Using data collected from 432 hotel managers and analyzed using Partial Least Squares Structural Equation Modelling (SEM-PLS). Results: the results reveal that AI-driven SC can significantly strengthen SCA and SCR. Furthermore, SCA and SCR can act as powerful mediators, and CP can strengthen the tested relationships (the links from AI adoption and CA) as a moderator. Conclusions: The study made several theoretical and practical contributions by integrating AI capabilities into SCR and SCA frameworks in the hotel and tourism context, and by providing practical evidence for professionals aiming to leverage AI-driven SC tools to navigate uncertainty and create sustainable CA. Full article

Currently, factors such as geopolitical conflicts, frequent extreme weather events, and power struggles among major countries are threatening the stability of the global supply chain. Building a more resilient supply chain has received international consensus. Today, new quality productivity (NQP), spawned by disruptive innovation, is an important way for China to enhance its agricultural product supply chain resilience (SCR). However, studies often overlook the “time lag” problem of the panel data adopted, and their empowering paths require further investigation. Therefore, this study firstly constructs NQP and agricultural product SCR indicators. Based on the panel data produced by 31 Chinese provinces from 2011 to 2022, we solved the “time lag” problem by integrating a Backpropagation Neural Network (BPNN) with an Autoregressive Integrated Moving Average (ARIMA) model to predict the NQP level. Subsequently, the empowering paths through NQP-enhancing agricultural product SCR were explored via entropy weight TOPSIS and Fuzzy-Set Qualitative Comparative Analysis (fsQCA) method. Foundations: China’s agricultural product SCR exhibits a spatial differentiation characteristic of “prominent in the central region and weak in the western region”. A single factor is not a necessary condition for high resilience, and its improvement depends on the synergy of multiple factors. Three differentiated driving paths have been identified: “autonomous endogenous driving type”, “environment-enabled driving type”, and “system architecture driving type”. NQMP has become the bottleneck for improving agricultural product SCR, and the threshold of each factor has increased significantly as the resilience target is raised. High resilience stems from the synergy and functional compensation of core factors, while low resilience is mostly caused by the concurrent absence of key conditions or structural mismatch, showing distinct “multiple concurrencies” and “causal asymmetry” characteristics. Full article

The transition toward carbon neutrality is accelerating the deployment of renewable energy sources (RES), creating new challenges for power balance, stability, and renewable generation curtailment. In the Baltic States, this RES growth coincides with synchronization with the Central European Synchronous Area, which poses additional technical and operational challenges. This paper evaluates the integration of offshore wind farms (OWFs) into the Lithuanian power system for 2027 and 2035, focusing on their impact on system operation, transmission loading, power balance and power system strength. A methodology based on extrapolated historical hourly data is applied to assess Lithuanian power system security under large-scale RES penetration, identifying critical contingencies and lines most prone to overloading. Results indicate that in 2027, network overloads may occur under N–1 contingencies when OWF capacity reaches 1400 MW; higher capacities require curtailment to maintain the generation–load balance. In 2035, planned grid reinforcements eliminate N–1 overloads. However, in both years, system strength remains the limiting factor. With an admissible short-circuit ratio (SCR) of 3, the maximum allowable OWF capacity is 1141 MW in 2027 and 1582 MW in 2035 under N–1, and 562 MW and 1039 MW under N–2 conditions. Full article

The increasing global demand for cleaner transportation has intensified the importance of efficient AdBlue^® (AUS32) production, a key chemical in selective catalytic reduction (SCR) systems that reduces nitrogen oxides (NOx) emissions from diesel engines. This work presents a computational fluid dynamics (CFD) simulation study of the urea–water mixing process within a high shear mixer (HSM), aiming to enhance the sustainability of AdBlue^® manufacturing. The model evaluates the hydrodynamic characteristics critical to optimising the dissolution of urea pellets in deionised water, which conventionally requires significant preheating. Experimental validation was conducted by comparing pressure drop simulation results with operational data from an active industrial facility in the United Kingdom. Therefore, this study validates the CFD model against an industrial two-stage Rotor–stator under real operating conditions. The computational framework combines a refined mesh with the k-ω SST turbulent model to resolve flow structures and capture near-wall effects and shear stress transport in complex flow domains. The results reveal opportunities for process optimisation, particularly in reducing thermal energy input without compromising solubility, thus offering a more sustainable pathway for AdBlue^® production. The main contribution of this work is to close existing gaps in industrial practice and propose and computationally validate strategies to improve the numerical design of HSM for solid dissolution. Full article

Enhancing system strength to ensure voltage security has become a critical challenge for power systems with high penetration of renewable energy (RE). As China accelerates its clean-energy transition, the conventional grid dominated by synchronous generators is evolving into a dual-high system characterized by both high shares of wind–solar generation and extensive power-electronic interfaces. This shift fundamentally alters the mechanisms of voltage support, rendering traditional short circuit ratio (SCR) index inadequate for describing grid strength. To address this gap, this study proposes a multi-renewable-station short circuit ratio (MRSCR) index that quantitatively evaluates the voltage support strength of RE-dominated systems, and further analyzes the mechanism by which multiple agents on the generation and grid sides affect MRSCR, enhancing the generality and applicability of the proposed index. The MRSCR is further formulated as a voltage security constraint and integrated into an energy storage planning model considering multi-agent collaborative optimization. The proposed model jointly optimizes the siting and capacity configuration of grid-forming energy storage under voltage security constraints. Case studies on the IEEE 14-bus system and a real provincial grid show that incorporating the MRSCR indicator effectively enhances the system’s voltage support performance and operational resilience, achieving these improvements with only a 5.45% increase in daily operating cost compared with baseline planning results. The framework provides a practical offline tool for energy storage planning, enabling both enhanced renewable integration and improved voltage security. Full article

The selective catalytic reduction (SCR) system is a key component for addressing NOx emissions from internal combustion engines. To resolve the issues of modeling distortion in SCR systems and the difficulty in characterizing the local reaction mechanism, a multi-dimensional SCR reaction model based on the coupling of Eley-Rideal (E-R) and Langmuir-Hinshelwood (L-H) dual mechanisms was established and conducted by experiment. The SCR catalytic characteristics and the dual-mechanism reaction process were systematically investigated. Additionally, based on the combined analysis of species concentration distribution coupled with temperature characteristics, a calculation method for the synergy of concentration-temperature fields was developed, and the synergistic characteristics of the concentration-temperature fields were explored. The results showed that high load accelerated the light-off speed, but this effect was counteracted by the negative impact of high flow rate. A strong negative correlation was maintained between temperature and NOx concentration across the full load range, and the axial consistency increased with load increasing. The results provide important theoretical support for the mechanism analysis of diesel engine SCR reactions and the optimization of thermal management. Full article

The ongoing decarbonisation of power systems is displacing synchronous generators (SGs) with converter-based plants, requiring a consistent assessment of grid-following inverters (GFLIs) and grid-forming inverters (GFMIs). Using an openly available four-bus root-mean-square (RMS) benchmark modelled in DIgSILENT PowerFactory, this work compares three generation configurations: (i) a single local SG connected at the point of common coupling; (ii) the same generator combined with a GFLI; and (iii) the generator combined with a GFMI. These configurations are evaluated under three disturbance scenarios: (1) a balanced load step, (2) an unbalanced double line-to-ground fault at low short-circuit ratio (SCR) with temporary islanding and single-shot auto-reclose, and (3) full islanding with under-frequency load shedding (UFLS), partial resynchronisation, and staged restoration. For the tested tuning ranges and within this RMS benchmark, the grid-forming configuration behaves as a low-impedance source at the point of common coupling in the phasor sense, yielding higher frequency nadirs during active-power disturbances and faster positive-sequence voltage recovery under weak and unbalanced conditions than the SG-only and SG+GFLI cases. During islanding, it supports selective UFLS, secure resynchronisation, and orderly load restoration. Rather than introducing new control theory, this work contributes a reproducible RMS benchmarking framework that integrates low-SCR operation, unbalance, and restoration sequences with a documented cross-technology tuning procedure. The findings indicate system-level improvements in frequency resilience and voltage recovery for the tested benchmark relative to the alternative configurations, while recognising that instantaneous device-level effects and broader generality will require electromagnetic-transient (EMT) or hybrid EMT/RMS validation in future work. Full article

Ultra-high-voltage direct current (UHVDC) transmission serves as a vital method for long-distance transmission of renewable energy in China. Commutation failure represents a common fault type in UHVDC transmission systems, causing the sending-end bus voltage to exhibit a “low-to-high” characteristic. This phenomenon poses a high-voltage disconnection risk for renewable energy units at the sending end. The high-voltage ride-through criteria for renewable energy incorporate both time and voltage peak factors. However, existing research relies solely on the voltage peak metric to assess disconnection risks for renewable units, failing to determine the specific stability level of the voltage. Therefore, this paper considers the cumulative effect of voltage transients over time, constructing a mathematical model of transient voltage during the entire fault process of a UHVDC transmission system at the sending end under commutation failure. Subsequently, a transient voltage rise stability margin metric based on a multi-binary table is proposed to evaluate the system’s transient voltage rise stability margin from both time and voltage peak dimensions. Finally, the accuracy of the proposed mathematical model and evaluation metric is validated using the PSCAD/EMTDC simulation platform. Results indicate that following a commutation failure in a UHVDC system, under the scenario of overvoltage instability alone, a higher short-circuit ratio (SCR) correlates with a lower system rated voltage. This configuration enhances the voltage stability margin of the sending end grid, improves its transient voltage stability, and helps mitigate the risk of renewable energy units disconnecting from the sending end grid. Full article

Growing efforts to reduce air pollution have accelerated the development of advanced flue gas treatment technologies for coal-fired power plants. This study presents the design, development, and industrial-scale implementation of a microwave-assisted non-thermal plasma reactor, powered by a 75 kW, 915 MHz magnetron, for simultaneous sulfur dioxide (SO₂) removal and fly ash agglomeration. The reactor was installed on the outlet line of the selective catalytic reduction (SCR) system of a 22 MW_e pulverized-coal-fired boiler and evaluated under real flue gas conditions. The flue gas stream, extracted by an induced-draft fan, was supplied to the reactor through two configurations—radial and axial injection—to investigate the influence of gas flow rate and microwave power on SO₂ abatement performance. Under radial injection, the system achieved a maximum SO₂ removal efficiency of 99.0% at 5194 Nm³/h and 75 kW, corresponding to a specific energy consumption of 14.4 Wh/Nm³. Axial injection resulted in a removal efficiency of 97.5% at 4100 Nm³/h. Beyond SO₂ mitigation, exposure of flue gas to the microwave-assisted plasma environment significantly enhanced particle agglomeration, as confirmed by means of SEM imaging and particle size distribution analyses. Notably, the proportion of fine particles smaller than 2.5 µm (PM_2.5) decreased from 70.25% to 18.63% after plasma treatment, indicating improved capture potential in the downstream electrostatic precipitator (ESP). Overall, microwave-assisted plasma provides efficient SO₂ removal and enhanced particulate capture, offering a compact and potentially waste-free alternative to conventional systems. Full article