Search Results (39,385)

The continuous increase in the penetration rate of renewable energy has posed severe challenges to the flexibility of power systems, especially in coastal and island areas where local power supply is insufficient while electricity demand keeps growing. Focusing on the regional water–energy nexus system (WENS), this paper fully taps into the flexibility potential of seawater desalination plants (SWDPs) as adjustable loads, and proposes a bi-level optimal dispatch model. First, the operational characteristics of reverse osmosis (RO) seawater desalination loads are analyzed, and an operational model encompassing water intake equipment, high-pressure pumps, clear water tanks and product water tanks is established. Second, a dispatch framework for the regional WENS incorporating SWDP is designed, on the basis of which a bi-level optimal dispatch model is constructed: the upper-level model takes maximizing wind power accommodation and minimizing wind power output fluctuation as the objectives, so as to determine the wind power output and the charging/discharging strategy of supercapacitors; constrained by the decisions made by the upper-level model, the lower-level model comprehensively takes into account the operation cost of thermal power units (TPUs), the wind curtailment penalty cost of the system, the operation cost of energy storage systems and the operation cost of SWDP, and thus establishes an optimization model with the goal of minimizing the comprehensive operation cost of the system. Finally, a comparative analysis is carried out under different scenarios. The results show that compared with the optimal scheduling scheme in which the seawater desalination load does not participate in regulation, the proposed method can reduce the wind curtailment rate by 43.71%, the energy consumption cost of the seawater desalination load by 50.98%, and the total system operation cost by 22.51%, thus providing a feasible approach for the collaborative optimization of water–energy systems in coastal areas. Full article

The objective was to evaluate the impact of a 3-month comprehensive rehabilitation program on functional outcomes and caregiver burden in a 73-year-old male with end-stage Parkinson’s disease (PD) following pallidotomy. Baseline evaluation included cardiorespiratory, digestive, and neuromusculoskeletal assessments, complemented by a multidomain geriatric assessment: activities of daily living (Barthel Index), cognition (MoCA), nutrition (MNA), mental health (GDS, UCLA Loneliness Scale), sarcopenia (AWGS criteria), frailty (Clinical Frailty Scale), fatigue (FSS), mobility (De Morton Mobility Index), fall risk (Morse Fall Scale), and caregiver burden (Zarit Burden Interview). The patient then underwent a structured 3-month rehabilitation program consisting of strengthening and flexibility training, cardiopulmonary endurance exercise, functional task practice, and psychological and nutritional counseling, with monthly evaluations. At baseline, the patient presented with generalized rigidity, fatigue, low cardiorespiratory endurance, total ADL dependence, malnutrition, sarcopenia, frailty, loneliness, and high caregiver burden, but intact cognition and mood. After rehabilitation, he achieved short distance walking, improved appetite and weight gain, and reduced scores in Zarit Burden, Fatigue Severity Scale, and MNA. Functional independence (Barthel Index) and respiratory capacity (single-breath count) improved, while frailty and sarcopenia remained stable without progression. In advanced PD, comprehensive rehabilitation can yield meaningful gains in mobility, nutrition, and functional independence while alleviating caregiver burden. Frailty and sarcopenia remain strongly associated with disease progression and highlight the need for sustained multidisciplinary care for both patients and caregivers. Full article

The rapid proliferation of electric vehicles (EVs) has introduced significant challenges to the efficient operation of hydrogen-containing integrated energy systems (H-IESs). To cope with these challenges, this paper develops a bi-level optimal scheduling strategy for H-IESs that simultaneously incorporates a ladder-type carbon emission trading mechanism, demand response, and the operational characteristics of EVs. A demand response model is formulated by considering the coupling characteristics of electric and thermal loads. Price-based incentive signals are further designed to coordinate the interactions between the H-IES operator and EV users, enabling flexible resources to actively participate in system scheduling. In the proposed bi-level framework, the upper-level problem aims to minimize the total operating cost of the H-IES, while the lower-level problem seeks to reduce the charging cost of EV users. The resulting bi-level optimization problem is reformulated and solved using the Karush–Kuhn–Tucker (KKT) conditions. Case study results demonstrate that, compared with the single-level benchmark, the proposed bi-level strategy reduces the total operating cost by 34.79% and lowers the EV charging cost by 4.50%. Full article

Solid polymer electrolytes (SPEs) hold great potential in high-safety energy storage but face two key bottlenecks: low room-temperature ionic conductivity and insufficient mechanical strength. This study proposes a synergistic optimization strategy of “long-carbon-chain regulation of polymer microstructure combined with porous polyimide (PI) support”. A linear random copolyester, poly(1,3-propylene-co-1,4-butylene succinate-co-sebacate) (PBPSS), was synthesized via melt polycondensation using 1,3-propanediol, 1,4-butanediol, succinic acid, and sebacic acid as monomers. Subsequently, the PBPSS-75 composite electrolyte was prepared with this copolyester as the matrix and porous PI as support. Results show that long-carbon-chain sebacic acid effectively regulates polymer segment flexibility and free volume, synergistically enhancing ionic conductivity and interfacial mechanical stability with lithium metal. Experimental data indicate that PBPSS-75 composite electrolyte exhibits an ionic conductivity of up to 4.25 × 10⁻⁵ S cm⁻¹ (30 °C), a lithium-ion transference number of 0.81, and an electrochemical stability window of 4.48 V (vs. Li/Li⁺). In LiFePO₄//Li batteries, it maintains nearly 100% capacity retention after 300 cycles at 0.5 C, and achieves stable cycling for over 800 h in lithium symmetric cells. This study confirms that the combined strategy effectively addresses the conductivity-mechanical property trade-off of SPEs, providing theoretical guidance and technical reference for high-performance solid-state battery material design. Full article

This study investigates hybridization of a solid oxide fuel cell with a gas turbine (SOFC–GT) for application in an ATR 72 regional aircraft. Several challenges hinder its viability, including the low gravimetric power density of SOFC stacks and stringent heat integration constraints. A steady-state model sweeps the cell voltage, overall pressure ratio (OPR), and a bounded turbine inlet temperature (TIT). This study introduces a new corrected power-share metric. This metric accounts for operating-point-dependent SOFC power density. It also enables weight-relevant comparisons. We analyze two types of coupling: direct and indirect. In the direct coupling, SOFC cooling fixes the core airflow and a TIT ceiling imposes a minimum power share. In the indirect coupling, a bypass decouples SOFC and gas turbine operation, incurring an efficiency penalty. We compare two heat-integration architectures: preheating with SOFC cathode exhaust versus low-pressure turbine (LPT) exhaust. Results show that direct coupling achieves efficiencies above 65% at high-corrected power shares, whereas indirect coupling offers greater operational flexibility but lower efficiency. Cathode exhaust preheating improves feasibility and outperforms LPT recuperation by more than 15% efficiency at low-to-mid-corrected power shares. However, LPT recuperation attains higher peak efficiency only at high-corrected power shares and within a narrow OPR window, which is limited by recuperator pinch. Full article

The coupling of electricity, heat, and hydrogen subsystems together with carbon capture technologies introduces complex operational interactions in modern multi-energy systems. Existing game-based scheduling studies mainly focus on electricity–heat or electricity–heat–gas coupling, often neglecting hydrogen blending, carbon capture integration, and strategic coordination among heterogeneous stakeholders. To address these gaps, this study develops a game-theoretic hierarchical optimization framework for electricity–heat–hydrogen integrated energy systems incorporating carbon capture. Compared with conventional multi-energy game models, the proposed framework integrates hydrogen blending and carbon capture into a unified electricity–heat–hydrogen–carbon coupling structure, enabling coordinated low-carbon operation. A Stackelberg leader–follower structure is adopted, where the upper-level operator determines electricity and heat prices, and lower-level participants optimize generation dispatch and demand response accordingly. The bi-level model is transformed into an equivalent single-level formulation using Karush–Kuhn–Tucker conditions and solved through a hybrid particle swarm optimization–mathematical programming approach. Simulation results based on an extended IEEE 30-bus system demonstrate improved coordination, enhanced scheduling flexibility, and reduced operating costs and carbon emissions. Compared with centralized optimization, the proposed framework enables the integrated energy operator and energy supplier to achieve revenues of 3.18 × 10⁵ CNY and 3.95 × 10⁵ CNY, respectively, while reducing the load aggregator’s cost by 41.71%, confirming its effectiveness for coordinated low-carbon IES scheduling. Full article

The global market for production organizations is becoming increasingly dynamic and complex. To address this development, production organizations develop strategies to become smarter in their operations, aiming at more flexibility and just-in-time mechanisms. These strategies imply advanced levels of digitization of the tactical decision making for and operational control of the primary production processes, both within individual organizations and at the level of supply networks. To embody this digitization, a spectrum of advanced digital technologies is available, such as artificial intelligence, blockchain, end-to-end process control, internet-of-things, and augmented reality. The realization of the strategies through digitization with these technologies is, however, severely hindered by two typical problems. Firstly, a large gap often exists between the high-level, abstract intentions formulated in strategies and the detailed, concrete embodiment in digital technology. Secondly, classes of digital technologies often are considered in isolation in projects resulting from a digital strategy, making synergies between technologies almost impossible and thus heavily reducing the added value of digitization efforts. This short commentary paper argues that the effective use of digital architecture in smart production system design is the path to effectively addressing these two problems. The observations and suggested architecture approach are illustrated by experiences with large international research and development projects in the smart production domain. Full article

We propose a comprehensive rotation-minimizing (RM) Darboux framework for the study of curve theory and relativistic ruled surfaces in Minkowski three-space ${\mathbb{E}}_1^3$. The construction merges the adaptability of the classical Darboux frame to surface geometry with the reduced rotational behavior characteristic of RM frames, yielding a natural geometric description of curves in a Lorentzian environment. For unit speed non-null curves, the governing equations of the RM Darboux frame are derived, and precise connections between the RM curvature functions and the classical Frenet and Darboux invariants are obtained, thereby elucidating the geometric significance of RM curvatures in Lorentzian geometry. Within this setting, multiple classes of ruled surfaces are generated using RM Darboux frame vector fields. Necessary and sufficient conditions for developability, minimality, and flatness are formulated exclusively in terms of RM curvature quantities. The role of the causal character of the generating curve is analyzed in detail, revealing distinct geometric behaviors for space-like and time-like cases. These findings indicate that the RM Darboux framework constitutes a flexible and effective approach for modeling curve-induced surface geometries in Minkowski space, with potential relevance to relativistic kinematics, world sheet constructions, and geometric problems arising in mathematical physics. Full article

The hollow fiber membrane humidification modules are used for indoor humidification in hot–dry regions and heating in winter. The module is composed of several flexible hollow fiber membranes, which are bent and displaced by gravity and fluid forces. This paper is a further study of previous work that reveals the internal relationship between the forces generated by vortex shedding and fiber vibration. The central trajectories of fibers in the flow field are described for various pulsating flow and fiber structure parameters. The effects of fiber displacement on fluid flow, heat transfer, and mass transfer performance at different parameters are discussed. The results show that the fiber displacement in the flow field consists of two components: (i) deformation caused by fluid drag force and gravity and (ii) periodic vibration caused by periodic lift and drag force as vortices shed at the fiber surface. The fiber vibration facilitates the vortex shedding on the fiber surface, which enhances the convective heat and mass transfer performance on the fiber surface. The average friction factor (f_m,v), Nusselt number (Nu_m,v), and Sherwood number (Sh_m,v) increased by 12.9%, 39.3%, and 20.0%, respectively, when the fiber vibrated compared to non-vibration. This implies that inducing fiber vibration can optimize the heat and moisture transfer performance. Full article

Efficient energy harvesting from open-channel flows offers a sustainable solution for powering distributed sensing systems in water infrastructure. This study investigates a piezoelectric wake-excited membrane vortex-induced vibration (VIV) energy harvester through a combined numerical and mechanical approach. The device features an upstream cylindrical bluff body that generates a periodic vortex street, exciting a downstream flexible membrane equipped with surface-mounted piezoelectric patches. A one-way coupled CFD–FEM framework implemented in ANSYS was employed to assess the effects of membrane length, material stiffness, and flow conditions on hydrodynamic loading, structural deformation, and deformation power. Results show that membrane length mainly affects oscillation amplitude and force levels, whereas material stiffness has a stronger influence on membrane deformation and RMS mechanical power. Among the investigated materials, low-stiffness polyethylene yields the highest deformation power, while none of the analysed configurations reaches a full lock-in condition within the explored parameter range. Complementary mechanical analysis revealed that the stiffness of commercial piezoelectric patches significantly reduces local strain, thereby constraining the practically harvestable energy in the present baseline configuration. Spectral power density analysis identified the dominant shedding frequency and its harmonics, confirming that the flow response is governed by a coherent periodic excitation. These findings highlight key design trade-offs in wake-excited membrane harvesters and provide useful guidance for the future optimisation of self-powered hydraulic monitoring systems. Full article

As industrial internet platforms increasingly play a central role in the digital transformation of manufacturing, they have become crucial areas for manufacturing enterprises to pursue digital innovation. Current academic research has paid relatively little attention to the digital innovation of participating enterprises within industrial internet platforms, failing to fully reveal the driving mechanisms of such innovation in this context. Based on the TOE framework and adopting a platform participant perspective, this study employs fuzzy set qualitative comparative analysis (fsQCA). By surveying 169 manufacturing enterprises participating in industrial internet platforms, it integrates seven key antecedents—technology availability, technology fit, digital leadership, organizational structural flexibility, resource orchestration, policy support, and competitive pressure—to systematically explore the complex influence pathways of multi-factor concurrent interactions on digital innovation. The research results show that the high digital innovation of manufacturing enterprises on the industrial internet platform includes precise implementation type, exploration-oriented type and co-evolution type, while the non-high digital innovation paths include technology blocking type, dual-core absence type and system disorder type. These conclusions expand the theoretical framework for digital innovation in manufacturing enterprises within industrial internet platforms and offer practical recommendations for their digital innovation practices. Full article

The convergence of climate change, migration, and health represents a critical global challenge, with the Middle East and North Africa (MENA) region illustrating acute vulnerabilities while offering insight relevant beyond the region. Increasing exposure to extreme heat, droughts, and floods drives displacement, constrained mobility, and adaptive migration, placing additional pressure on already stretched health systems. This paper proposes an integrated Nexus Action Framework for Climate Change, Migration, and Health (NAF-CMH) to address these interlinked dynamics and move beyond fragmented, sector-specific responses. The framework conceptualizes human mobility both as a potential resilience strategy and as a determinant of health, encompassing climate-affected migrants, displaced populations, and those experiencing involuntary immobility across diverse pathways and settings. It promotes systematic integration of health considerations into climate adaptation and migration governance and situates these interventions within the broader agenda of climate-resilient health systems. Drawing on a non-systematic narrative review of peer-reviewed and grey literature, complemented by the authors’ expertise, the paper identifies seven interrelated pillars for coordinated policy and operational action. While grounded in MENA-specific vulnerabilities, the framework is flexible and adaptable to other regions facing climate-driven mobility challenges. By providing an operational architecture for multisector collaboration, the NAF-CMH supports policymakers, public health authorities, and migration actors in strengthening resilience, reducing vulnerability and safeguarding health amid accelerating climate impacts and evolving mobility patterns. Full article

As critical components of wind energy systems, the structural integrity of wind turbine blades is directly tied to the operational safety and economic performance of wind turbines. With blade designs trending toward larger and more flexible structures and operating environments becoming increasingly harsh, maintenance strategies must urgently shift from reactive approaches to predictive maintenance paradigms. From an engineering application perspective, this study conducts a systematic and critical review of non-destructive testing (NDT) and structural health monitoring (SHM) technologies for wind turbine blades. Drawing on the literature published over the past decade, we examine the field applicability, limitations, and engineering challenges of core NDT techniques—including vision-based methods, acoustic approaches, vibration analysis, ultrasound, and infrared thermography. Particular emphasis is placed on the integration of data-driven approaches with engineering practice, evaluating the role of machine learning in fault classification and anomaly diagnosis, as well as the contributions of deep learning to automated defect detection in image and signal data. Moreover, this paper critically discusses the growing use of robotic inspection platforms, such as unmanned aerial vehicles and climbing robots, as multi-sensor carriers enabling rapid and comprehensive blade assessment. By comparatively analyzing detection performance, cost, and automation levels across technologies, we identify key engineering barriers, including environmental noise robustness, signal attenuation within complex blade structures, and the persistent gap between laboratory methods and field deployment. Finally, we outline forward-looking research directions, encompassing multi-modal sensor fusion, edge computing for real-time diagnostics, and the development of standardized SHM systems aimed at supporting full lifecycle blade management. Full article

Space–air–ground integrated networks (SAGINs) enable flexible content delivery through satellite–UAV–ground cooperation, yet time-varying user demand and dynamic backhaul conditions pose significant challenges to efficient UAV caching. To address these challenges, this paper proposes PCICaching, a backhaul-aware and prediction-driven UAV caching framework that integrates LSTM-based popularity forecasting, cache-aware user association, and conditionally activated cooperative caching. Under normal satellite backhaul conditions, PCICaching operates in a latency-oriented mode and reduces average content delivery latency by up to 33.9% and 38.9% compared with representative GTGA-based and history-based baselines, respectively. When backhaul connectivity degrades, the proposed C3 mechanism enlarges cluster-level content coverage and maintains service continuity with only a moderate latency increase of approximately 14.2%. Moreover, the proposed sequential decomposition enables scalable online operation with per-update execution time below 100 ms. These results demonstrate that PCICaching provides a structurally adaptive and computationally efficient solution for UAV-assisted caching in SAGINs, effectively balancing latency efficiency and content availability under time-varying demand and infrastructure uncertainty. Full article

Renewable hydrogen is increasingly promoted as a key component of sustainable low-emission energy systems; however, its realistic role remains highly dependent on national system conditions. This review examines under what circumstances renewable hydrogen can effectively contribute to Poland’s low-emission energy transition, given its coal-dominated electricity mix, energy-intensive industrial structure, and evolving regulatory environment. The article adopts a system-oriented review approach that integrates recent European Union and national policy developments, including RED III and related delegated acts, with technological pathways, infrastructure readiness, safety considerations, and sectoral demand. Particular attention is given to electricity–hydrogen–industry coupling and the system-level conditions that determine the technical feasibility, efficiency losses, and economic viability of renewable hydrogen deployment. The review demonstrates that renewable hydrogen in Poland is unlikely to become a universal decarbonization solution. Its effective deployment is conditional on accelerated renewable electricity expansion, coordinated development of hydrogen transport and storage infrastructure, and regulatory alignment with EU frameworks. In the short and medium term, the highest system value lies in substituting fossil-based hydrogen in existing industrial applications, while in the longer-term hydrogen may support system flexibility and the decarbonization of hard-to-electrify sectors. Technology-neutral policy approaches may facilitate early market formation but risk reinforcing technology lock-in effects if maintained in the long term. These findings suggest that renewable hydrogen should be positioned as a complementary element of Poland’s low-emission energy system, requiring targeted, system-integrated policy and investment strategies rather than broad, technology-neutral deployment. Full article