Search Results (203)

To ensure the safe and reliable operation of hydrogen-blended natural gas (HBNG) pipelines in urban utility tunnels, this study conducted a comprehensive CFD simulation of the leakage and diffusion characteristics of HBNG in confined underground environments. Utilizing ANSYS CFD software (2024R1), a three-dimensional physical model of a utility tunnel was developed to investigate the influence of key parameters, such as leak sizes (4 mm, 6 mm, and 8 mm)—selected based on common small-orifice defects in utility tunnel pipelines (e.g., corrosion-induced pinholes and minor mechanical damage) and hydrogen blending ratios (HBR) ranging from 0% to 20%—a range aligned with current global HBNG demonstration projects (e.g., China’s “Medium-Term and Long-Term Plan for Hydrogen Energy Industry Development”) and ISO standards prioritizing 20% as a technically feasible upper limit for existing infrastructure, on HBNG diffusion behavior. The study also evaluated the adequacy of current accident ventilation standards. The findings show that as leak orifice size increases, the diffusion range of HBNG expands significantly, with a 31.5% increase in diffusion distance and an 18.5% reduction in alarm time as the orifice diameter grows from 4 mm to 8 mm. Furthermore, hydrogen blending accelerates gas diffusion, with each 5% increase in HBR shortening the alarm time by approximately 1.6 s and increasing equilibrium concentrations by 0.4% vol. The current ventilation standard (12 h⁻¹) was found to be insufficient to suppress concentrations below the 1% safety threshold when the HBR exceeds 5% or the orifice diameter exceeds 4 mm—thresholds derived from simulations showing that, under 12 h⁻¹ ventilation, equilibrium concentrations exceed the 1% safety threshold under these conditions. To address these gaps, this study proposes an adaptive ventilation strategy that uses variable-frequency drives to adjust ventilation rates in real time based on sensor feedback of gas concentrations, ensuring alignment with leakage conditions, thereby ensuring enhanced safety. These results provide crucial theoretical insights for the safe design of HBNG pipelines and ventilation optimization in utility tunnels. Full article

Federated Learning (FL) enables privacy-preserving model training across distributed clients. However, its reliance on voluntary client participation makes it vulnerable to strategic behaviors—actions that are not overtly malicious but significantly impair model convergence and fairness. Existing defense methods primarily focus on explicit attacks, overlooking the challenges posed by economically motivated “pseudo-honest” clients. To address this gap, we propose a Reputation-Aware Defense Framework to mitigate strategic behaviors in FL. This framework introduces a multi-dimensional dynamic reputation model that evaluates client behaviors based on gradient alignment, participation consistency, and update stability. The resulting reputation scores are incorporated into both aggregation and incentive mechanisms, forming a behavior-feedback loop that rewards honest participation and penalizes opportunistic strategies. We theoretically prove the convergence of reputation scores, the suppression of low-quality updates in aggregation, and the emergence of honest participation as a Nash equilibrium under the incentive mechanism. Experiments on datasets such as CIFAR-10, FEMNIST, MIMIC-III demonstrate that our approach significantly outperforms baseline methods in accuracy, fairness, and robustness, even when up to 60% of clients act strategically. This study bridges trust modeling and robust optimization in FL, offering a secure foundation for federated systems operating in open and incentive-driven environments. Full article

This paper presents a novel four-dimensional (4D) chaotic system exhibiting parametric symmetry breaking and multistability. Through equilibrium stability analysis, attractor reconstruction, Lyapunov Exponent spectra (LEs), and bifurcation diagrams, we reveal a continuous transition from symmetric period attractors to asymmetric chaotic states and rich dynamical behaviors. Additionally, considering the potential of this system in practical applications, a feedback control simulation circuit is designed and implemented to ensure its stability and effectiveness under real-world conditions. Finally, among various control strategies, this paper proposes an innovative Fixed-Time Sliding Mode Synchronization (FTSMS) strategy, determines its synchronization convergence time, and provides an important theoretical foundation for the practical application of the system. Full article

This paper aims to investigate a Nash equilibrium (NE)-seeking approach for the aggregative game problem of second-order multi-agent systems (MAS) with uncontrollable malicious players, which may cause the decisions of global players to become uncontrollable, thereby hindering the ability of normal players to reach the NE. To mitigate the influence of malicious players on the system, a malicious player detection and disconnection (MPDD) algorithm is proposed, based on the fixed-time convergence method. Subsequently, a predefined-time distributed NE-seeking algorithm is presented, utilizing a time-varying, time-based generator (TBG) and state-feedback scheme, ensuring that all normal players complete the game problem within the predefined time. The convergence properties of the algorithms are analyzed using Lyapunov stability theory. Theoretically, the aggregative game problem with malicious players can be solved using the proposed algorithms within any user-defined time. Finally, a numerical simulation of electricity market bidding verifies the effectiveness of the proposed algorithm. Full article

We present a thermodynamically consistent energetic variational model for active nematics driven by ATP hydrolysis. Extending the classical Toner–Tu framework, we introduce a chemo-mechanical coupling mechanism in which the self-advection and polarization dynamics are modulated by the ATP hydrolysis rate. The model is derived using an energetic variational approach that integrates both chemical free energy and mechanical energy into a unified energy dissipation law. The reaction rate equation explicitly incorporates mechanical feedback, revealing how active transport and alignment interactions influence chemical fluxes and vice versa. This formulation not only preserves consistency with non-equilibrium thermodynamics but also provides a transparent pathway for modeling energy transduction in active systems. We also present numerical simulations demonstrating the positive energy transduction under a specific choice of model parameters. The new modeling framework offers new insights into energy transduction and regulation mechanisms in biologically related active systems. Full article

This article concerns a Cournot duopoly game with homogeneous expectations. The cost functions of the two players are assumed to be asymmetric to capture possible asymmetries in firms’ technologies or firms’ input costs. Large values of the speed of adjustment of the players destabilize the Nash Equilibrium (N.E.) and cause the appearance of a chaotic trajectory in the Discrete Dynamical System (D.D.S.). The scope of this article is to control the chaotic dynamics that appear outside the stability field, assuming asymmetric cost functions of the two players. Specifically, one player uses linear costs, while the other uses nonlinear costs (quadratic or cubic). The cubic cost functions are widely used in the Economic Dispatch Problem. The delayed feedback control method is applied by introducing a new control parameter at the D.D.S. It is shown that larger values of the control parameter keep the N.E. locally asymptotically stable even for higher values of the speed of adjustment. Full article

This study develops a dynamic IS-LM macroeconomic model that incorporates delayed taxation and a memory-dependent income effect, and calibrates it to quarterly data for Romania (2000–2023). Within this framework, fiscal policy lags are modelled using a “memory” income variable that weights past incomes, an approach grounded in distributed lag theory to capture how historical economic conditions influence current dynamics. The model is analysed both analytically and through numerical simulations. We derive stability conditions and employ bifurcation analysis to explore how the timing of taxation influences macroeconomic equilibrium. The findings reveal that an immediate taxation regime yields a stable adjustment toward a unique equilibrium, consistent with classical IS-LM expectations. In contrast, delayed taxation, where tax revenue depends on past income, can destabilise the system, giving rise to cycles and even chaotic fluctuations for parameter values that would be stable under immediate collection. In particular, delays act as a destabilising force, lowering the threshold of the output-adjustment speed at which oscillations emerge. These results highlight the critical importance of policy timing: prompt fiscal feedback tends to stabilise the economy, whereas lags in fiscal intervention can induce endogenous cycles. The analysis offers policy-relevant insights, suggesting that reducing fiscal response delays or counteracting them with other stabilisation tools is crucial for macroeconomic stability. Full article

Vibration control has long been a key concern in engineering, with low-frequency vibration isolation remaining particularly challenging. Traditional linear isolators are limited in their ability to provide high load-bearing capacity and effective low-frequency isolation simultaneously. In contrast, quasi-zero stiffness (QZS) isolators offer low dynamic stiffness near equilibrium while maintaining high static stiffness, thereby enabling superior isolation performance in the low and ultra-low frequency range. This paper proposes a novel vibration isolation system that combines a grounded dynamic absorber with a QZS isolator, incorporating time-delay feedback control to enhance performance. The dynamic equations of the system are derived using Newton’s second law. The harmonic balance method combined with the arc-length continuation technique is employed to obtain steady-state responses under harmonic force excitation. The influence of feedback gain and time delay on vibration isolation effectiveness and dynamic behavior is analyzed, demonstrating the ability of time-delay feedback to modulate system responses and suppress primary resonance peaks. To further enhance performance, a genetic algorithm is used to optimize the control parameters under harmonic force excitation. The force transmissibility is defined as fitness functions, and the effects of control parameters on these metrics are examined. The results show that the optimized time-delay feedback parameters significantly reduce the transmitted force, improving the overall isolation efficiency. The proposed system provides a promising approach for achieving high-performance vibration isolation in low-frequency environments. Full article

Complex feedback mechanisms and interdependencies exist among the water–energy–food–ecosystems (WEFE) nexus. In water-scarce regions, fluctuations in the supply or demand of any single subsystem can destabilize the others, with water shortages intensifying conflicts among food production, energy consumption, and ecological sustainability. Balancing the synergies and trade-offs within the WEFE system is therefore essential for achieving sustainable development. This study adopts the natural–social water cycle as the core process and develops a coupled simulation model of the WEFE (CSM-WEFE) system, integrating food production, ecological water replenishment, and energy consumption associated with water supply and use. Based on three performance indices—reliability, coupling coordination degree, and equilibrium—a coordinated sustainable development index (CSD) is constructed to quantify the performance of WEFE system under different scenarios. An integrated evaluation framework combining the CSM-WEFE and the CSD index is then proposed to assess the sustainability of WEFE systems. The framework is applied to the Beijing–Tianjin–Hebei (BTH) region, a representative water-scarce area in China. Results reveal that the current balance between water supply and socio-economic demand in the BTH region relies heavily on excessive groundwater extraction and the appropriation of ecological water resources. Pursuing food security goals further exacerbates groundwater overexploitation and ecological degradation, thereby undermining system coordination. In contrast, limiting groundwater use improves ecological conditions but increases regional water scarcity and reduces food self-sufficiency. Even with the full operation of the South-to-North Water Diversion Project (Middle Route), the region still experiences a 16.4% water shortage. By integrating the CSM-WEFE model with the CSD evaluation approach, the proposed framework not only provides a robust tool for assessing WEFE system sustainability but also offers practical guidance for alleviating water shortages, enhancing food security, and improving ecological health in water-scarce regions. Full article

This study investigates the evolutionary game dynamics of medical knowledge sharing (KS) among Chinese hospitals under government regulation, focusing on the strategic interactions between general hospitals, community health service centers, and governmental bodies. Leveraging evolutionary game theory, we construct a tripartite evolutionary game model incorporating replicator dynamics to characterize the strategic evolution of the involved parties. Our analysis examines the regulatory decisions of the government and the strategic choices of Chinese hospitals, considering critical factors such as KS costs, synergistic benefits, government incentives and penalties, and patient evaluations. The model is analyzed using replicator dynamic equations to derive evolutionary stable strategies (ESSs), complemented by numerical simulations for sensitivity analysis. Key findings reveal that the system’s equilibrium depends on the balance between KS benefits and costs, with government regulation and patient evaluations significantly influencing Chinese hospital behaviors. The results highlight that increasing government incentives and penalties, alongside enhancing patient feedback mechanisms, can effectively promote KS. However, excessive incentives may reduce willingness to regulate, suggesting the need for balanced policy design. This research provides novel theoretical insights and practical recommendations by (1) pioneering the application of a tripartite evolutionary game framework to model KS dynamics in China’s hierarchical healthcare system under government oversight, (2) explicitly integrating the dual influences of government regulation and patient evaluations on hospital strategies, and (3) revealing the non-linear effects of policy instruments. These contributions are crucial for optimizing Chinese medical resource allocation and fostering sustainable collaborative healthcare ecosystems. Full article

Water scarcity has become a critical global challenge, particularly in rapidly developing regions where water demand often exceeds sustainable supply capacities. Traditional “demand-driven” water management approaches have proven inadequate to address this imbalance, necessitating the development of more sophisticated “supply-driven” solutions. This study presents a groundbreaking System Dynamics (SD)-Feedback-Hierarchical Water Demand (SD-F-HWD) model that advances water resources management through three contributions. First, the model substantially extends conventional water demand hierarchy methods by developing a comprehensive classification framework with enhanced sector-specific criteria for industrial, agricultural, and ecological needs. Second, the innovative feedback regulation mechanism resolves persistent challenges from previous studies, including ambiguous control parameters and system instability. Third, the model establishes a unified analytical platform that effectively integrates these components for robust supply–demand equilibrium analysis. Validation in Wu’an City, Hebei Province—a representative water-stressed industrial region in northern China—demonstrated the model’s effectiveness. Under low-flow conditions (P = 75%), total water demand decreased by 11.24% while rigid demand was reduced by 8.50%. For normal flow conditions (P = 50%), corresponding reductions reached 9.88% and 6.99%, respectively. Crucially, all adjustments remained within practical policy implementation boundaries, demonstrating the model’s real-world applicability. The SD-F-HWD model offers a practical and scalable solution for sustainable water allocation in water-stressed regions through its integrated methodological framework. Full article

Bone remodeling is a dynamic biological process that preserves bone strength and structure through the coordinated actions of osteoblasts, osteoclasts, osteocytes, and bone mass density. Traditional models based on ordinary differential equations often fail to capture the memory-dependent nature of these interactions. In this study, we propose a novel mathematical model of bone remodeling using the Atangana–Baleanu–Caputo fractional derivative, which accounts for the non-local and hereditary characteristics of biological systems. The model introduces fractional-order dynamics into a previously established ODE framework while maintaining the intrinsic symmetry between bone-forming and bone-resorbing mechanisms, as well as the balance mediated by porosity-related feedback. We establish the existence, uniqueness, and positivity of solutions, and analyze the equilibrium points and their global stability using a Lyapunov function. Numerical simulations under various fractional orders demonstrate symmetric convergence toward equilibrium across all biological variables. The results confirm that fractional-order modeling provides a more accurate and balanced representation of bone remodeling and reveal the underlying symmetry in the regulation of bone tissue. This work contributes to the growing use of fractional calculus in modeling physiological processes and highlights the importance of symmetry in both mathematical structure and biological behavior. Full article

This paper introduces a functional framework for modeling cyclical and feedback-driven information flow using a generalized family of derangetropy operators. In contrast to scalar entropy measures such as Shannon entropy, these operators act directly on probability densities, providing a topographical representation of information across the support of the distribution. The proposed framework captures periodic and self-referential aspects of information evolution through functional transformations governed by nonlinear differential equations. When applied recursively, these operators induce a spectral diffusion process governed by the heat equation, with convergence toward a Gaussian characteristic function. This convergence result establishes an analytical foundation for describing the long-term dynamics of information under cyclic modulation. The framework thus offers new tools for analyzing the temporal evolution of information in systems characterized by periodic structure, stochastic feedback, and delayed interaction, with potential applications in artificial neural networks, communication theory, and non-equilibrium statistical mechanics. Full article

The exploration of the coupling trend between urban agglomeration development (UAD) and land surface temperature (LST) expansion is of great significance, and it is of scientific value for the regulation of the thermal environment of urban agglomerations, the optimization of urban spatial planning, and the achievement of sustainable urban development. This study employs an array of remote sensing datasets from multiple sources—employing a multi-faceted approach encompassing an overall coupling situation analysis model, a coordination and evaluation system, a geographically weighted spatial autocorrelation algorithm, and landscape pattern quantification indicators—to explore the mutual feedback mechanism and spatial coupling characterization of LST and UAD in the Guanzhong Plain Urban Agglomeration (GZPUA). The results of the study can provide data support for urban spatial planning and thermal environment regulation. The results indicate the following findings: (1) In the GZPUA, the nighttime light (NTL) and land surface temperature (LST) centroids show a significant tendency toward approaching one another, with a spatial offset decreasing from 45.0 km to 9.1 km at the end, indicating a strengthening trend in the photothermal system’s coupling synergy. (2) The coordination of light and heat in the study area exhibits significant non-equilibrium development, with a dynamic trend of urban development space shifting towards the southwest. It confirms the typical regional response law of rapid urbanization. (3) The Moran’s I index of the photothermal system in the study area increased from 0.289 to 0.335, an increase of 15.9%. The proportion of “high–high” (H-H)/“low–low” (L-L)-type regions with clustering distribution of cold and hot spots reaches 58.01%, and their spatial continuity characteristics are significantly enhanced, indicating a significant trend of spatial structural integration between urban heat island effect and construction land expansion. Full article

Equilibrium Propagation (EP) offers a biologically inspired alternative to backpropagation for training recurrent neural networks, but its reliance on symmetric feedback connections and stability limitations hinders practical adoption. The DirEcted EP (DEEP) model relaxes the symmetry constraint, yet suffers from convergence issues and lacks a principled learning guarantee. In this work, we generalize DEEP by incorporating neuronal leakage, providing new convergence criteria for the network’s dynamics. We additionally propose a novel local learning rule closely linked to the objective function’s gradient and establish sufficient conditions for reliable learning in small networks. Our results resolve longstanding stability challenges and bring energy-based learning models closer to biologically plausible and provably effective neural computation. Full article