Search Results (14,495)

Offshore wind-farm performance remains constrained by persistent wake deficits and turbulence that compound across intra-farm, intra-cluster, and inter-cluster scales, particularly under atmospheric neutral–stable stratification. A concept is advanced whereby offshore wind-farm yield may be augmented by pairing conventional horizontal-axis wind turbines (HAWTs) with lighter-than-air parafoil systems that entrain higher-momentum air and re-energise wakes, complementing yaw/induction-based wake control and enabling higher array energy density. A concise synthesis of wake physics and associated challenges motivates opportunities for active momentum re-injection, while a review of kite technologies frames design choices for lift generation and spatial keeping. Stability and control, spanning static and dynamic behaviours, tether dynamics, and response to extreme meteorological conditions, are identified as key challenges. System-integration pathways are outlined, including alignment and mounting options relative to turbine rows and prevailing shear. A staged validation programme is proposed, combining high-fidelity numerical simulation with wave-tank testing of coupled mooring–tether dynamics and wind-tunnel experiments on scaled arrays. Evaluation metrics emphasise net energy gain, fatigue loading, availability, and Levelized Cost of Energy (LCOE). The paper concludes with research directions and recommendations to guide standards and investment, and with a quantitative assessment of the techno-economic significance of kite–HAWT integration at scale. Full article

This paper studies optimal dividend and capital injection strategies with active exit options under a jump-diffusion model. We introduce a piecewise terminal payoff function to capture stop-loss exits (for deficits) and profit-taking exits (for surpluses), enabling shareholders to dynamically balance risk and return. Using the dynamic programming principle, we derive the associated quasi-variational inequalities (QVIs) and characterize the value function as the unique viscosity solution. To address analytical challenges, we employ the Markov chain approximation method, constructing a controlled Markov chain that closely approximates the jump-diffusion dynamics. Numerical solutions of the approximated problem are obtained via value iteration. The numerical results demonstrate how the value function and optimal strategies respond to different claim distributions (comparing Exponential and Pareto cases), key model parameters, and exit payoff functions. The numerical study further validates the algorithm’s convergence and examines the stability of solutions with respect to domain truncation in the QVI formulation. Full article

Vibration is a critical issue in aerospace structures, where lightweight design, high flexibility, and complex operational environments often lead to pronounced nonlinear dynamic responses. Excessive vibrations induced by harmonic excitations, aerodynamic loads, or onboard equipment can significantly degrade structural integrity, control accuracy, and service life. Consequently, advanced passive vibration suppression techniques with strong robustness and broadband effectiveness are of great importance in aerospace engineering applications. The bifurcation boundary and vibration suppression performance of Piezoelectric–Monostable Nonlinear Energy Sink (PMNES) are crucial for evaluating its effectiveness on the main structure. To simplify the analysis of flexible aerospace structures, a reduced-order model is derived by modal truncation in the low-frequency range, which is then treated as a two-degree-of-freedom main structure. To focus on the underlying nonlinear dynamic mechanisms, an equivalent two-degree-of-freedom lumped-parameter system is adopted as a generic representation of the dominant low-frequency dynamics of flexible aerospace structures. In this work, the electromechanical coupling control equations of the system of a two-degree-of-freedom main structure coupled with PNES are derived through the application of Newton’s second law and Kirchhoff’s voltage law. The methods of complexification-averaging (CX-A) and Runge–Kutta (RK) are employed to assess the vibration suppression performance and stability characteristics of the system under harmonic excitation. The approximate solution is validated through numerical solutions. The approximate solutions of the system are employed to derive the Saddle Node (SN) bifurcation and codimension-two cusp bifurcation points, while the enhanced algorithm is employed to ascertain the most unfavorable amplitude at each external excitation circular frequency and to determine whether the mark represents a Hopf Bifurcation (HB) point. The generalized transmissibility is utilized to assess the efficacy of vibration suppression. The various vibration suppression efficiency regions are created by superimposing the vibration suppression efficiency maps and bifurcation maps. The influence of PNES parameters on the vibration suppression region is investigated. The results indicate that this method can effectively evaluate the bifurcation boundary and vibration suppression performance of PMNES. Full article

In thick coal seam conditions, the surrounding rock deformation in the longwall mining faces’ along-the-goal roadway is severe, and the support strength struggles to meet roadway retention requirements. A coordinated control strategy, termed “pressure-relief and support,” is proposed, which includes an “Optimization of Roof Cutting in Surrounding Rock Structure, Reinforcement of surrounding rock support, high-strength temporary support, and roadside gangue-blocking support.” A numerical model for roof-cutting pressure relief in thick-seam caving mining gob-side entries was established to simulate various roof-cutting heights and angles. This model analyzes the evolution patterns of stress and displacement under different cutting parameters to identify optimal values. The study presents a coordinated “pressure-relief and support” control scheme for gob-side entries in thick-seam caving mining, with its feasibility validated through numerical simulation analysis and field industrial tests. The findings demonstrate that the selection of the roof-cutting height and angle exerts a significant influence on the deformation behavior of the retained roadway roof. By severing the roof strata, this technique disrupts the load-transfer path from the goaf to the entry, thereby mitigating the adverse effects of overlying strata fracturing and facilitating more effective ground control. As a result, roof-cutting and pressure relief substantially reduce the stress imposed on the supporting structures. The coordinated “pressure-relief & support” control strategy employed in gob-side entry retaining for thick-seam longwall top-coal caving faces notably improves the surrounding rock stress regime and effectively restrains roadway convergence. Full article

This paper concentrates on fractional-order fuzzy cellular neural networks (FOFCNNs) with bounded uncertainties and transmission delays. To better capture real-world dynamic behaviors, the fuzzy AND and OR operators are employed to construct drive-response systems. For the fixed-time synchronization task of the systems, a novel multi-module feedback controller incorporating three functional terms is designed. These terms aim to eliminate delay effects, ensure fixed-time convergence, and reduce parameter conservativeness. Leveraging the properties of fractional-order operators and our multi-module control scheme, new synchronization criteria of the studied drive-response systems can be established within a predefined time. An upper bound on the settling time is derived, depending on the system size and control parameters, but independent of the initial conditions. A significant corollary is derived for the case of no uncertainties under the nonlinear controller. Numerical experiments discuss the impact of uncertainties and delays on synchronization, and confirm the validity of the results presented in this study. Full article

Small-scale two-phase flows are subject to intense capillary accelerations that must be treated with care in order to avoid artifacts often associated with the numerical methodologies used, such as excessive fragmentation of structures. This analysis proposes a formulation of capillary actions for compressible viscous two-phase flows within the framework of discrete mechanics, where the concept of mass is abandoned in favor of a law of motion that describes the conservation of accelerations, one related to inertia and the other to external actions. With the introduction of the capillary term, the sum of a capillary potential gradient and the dual curl of a vector potential is consistent with the other terms of the law of motion, a formal Helmholtz–Hodge decomposition. This fully compressible formulation reproduces the capillary waves generated by the source terms and the contact and shock discontinuities in the two immiscible fluids. This methodology completely eliminates parasitic currents due mainly to the presence of residual curl in the capillary source terms. Several classic examples demonstrate the validity of this approach. Full article

Corrugated insect wings inspire biomimetic aerodynamic design, yet their behaviour at low and transitional Reynolds numbers remains not fully understood. This study presents a three-dimensional computational analysis of flow over an infinite corrugated wing across Reynolds numbers from 10 to 10,000 and angles of attack from −5 to 20°, with emphasis on spanwise effects. An expanded verification and validation procedure ensured numerical reliability. At the lowest Reynolds numbers, the flow is steady and largely two-dimensional, with localised recirculation zones. As Reynolds numbers or angles of attack increase, the flow transitions to periodic vortex shedding, and three-dimensional structures appear. At a Reynolds number of ten thousand, periodic shedding occurs at zero degrees incidence, indicating a shift toward turbulent or bluff body-like behaviour. The examined corrugated profile does not exhibit a lift-to-drag benefit over smooth aerofoils in steady gliding, although root section corrugation helps delay separation in transitional regimes. This behaviour reflects mechanisms used by dragonflies to maintain stable gliding despite textured wings. By extending flow regime classification, the study identifies conditions where two-dimensional assumptions fail and highlights the influence of spanwise flow structures. These findings deepen understanding of insect wing aerodynamics and support biomimetic design of future wings. Full article

In this work, we present an experimental validation of a modified Halbach array magnet configuration for passive electrodynamic suspension (EDS) systems. The study builds upon previous research that indicated improved lift-to-drag performance and reduced power consumption by altering the span (fill factor) of horizontally magnetised magnets in a Halbach array. A custom rotating test rig was developed to measure both magnetic field distributions and levitation/braking forces for several Halbach array configurations with varying magnet width ratios. Six magnet array packs were tested, featuring different fill factors (0.125, 0.5, 0.875), magnet lengths, and wavelengths. The experimental results show good agreement with 3D finite-element simulations across a range of speeds (0–85 m/s) and air gaps, confirming that non-classical Halbach arrays (with a fill factor ≠ of 0.5) can achieve higher energy efficiency. In particular, configurations with extreme fill factors produced lower magnetic drag for the same lift force, yielding a higher lift-to-drag ratio and a reduced magnetic friction coefficient. These findings validate the proposed modified Halbach arrangement and demonstrate that adjusting the horizontal magnet span can indeed reduce the power requirements of EDS maglev systems. The novelty of this work lies in the combined numerical–experimental assessment of mixed-length Halbach array configurations, revealing previously unreported scaling effects between magnet width ratio and force stability in short-stroke applications. Full article

The rapid expansion of tunnel construction in mountainous regions faces significant challenges due to the heterogeneity of surrounding rocks caused by faults, fractures, and karst features, which strongly affect groundwater seepage. Traditional homogeneous assumptions are inadequate for accurately predicting tunnel water inflow, while current heterogeneous assumptions primarily focus on the permeability of the medium near a single tunnel. This study employs 2D numerical modeling based on the Kexuecheng Tunnel in Chongqing, China, to investigate the effects of geological heterogeneity on tunnel discharge and groundwater drawdown. A methodological advancement of this work lies in the quantification of the impact of non-permeability heterogeneity, stratigraphic continuity, and dip angles on groundwater under multi-tunnel conditions. Four stratigraphic continuities (R = 60 m, 120 m, 180 m, 240 m) and four dip angles (θ = 0°, 30°, 60°, 90°) are considered for permeability variations. Results demonstrate that heterogeneous formations produce irregular discharge and non-uniform groundwater drawdown, closely reflecting field conditions. Increased stratum continuity intensifies discharge and drawdown at smaller dip angles, while combined variations yield complex hydraulic responses. In multi-tunnel settings, reduced spacing amplifies discharge and drawdown, exacerbating groundwater impacts. Compared with homogeneous conditions, heterogeneous formations yield higher water inflow and uneven drawdown. The findings underscore the necessity of accounting for geological heterogeneity and tunnel interactions in hydrogeological evaluations and design. In addition to permeability, stratigraphic continuity and dip angles during simulation validation, especially in multi-tunnel configurations, enhance safety and reduce engineering risks. Full article

The district heating system (DHS) can provide flexibility to the electrical power system (EPS) in the coordinated dispatch of an integrated power and heat system (IPHS). To exploit the energy storage capacity of the DHS and support the flexible IPHS operation, it is essential to characterize the flexible operation region (FOR) of the DHS. This paper proposes an FOR characterization method for the DHS, based on a Farkas-cut outer approximation algorithm (FCOAA). The FOR characterization is formulated as a polyhedral projection problem. Within the FCOAA-based framework, the feasible cut generation model is constructed as a bilinear programming problem, which is relaxed by using the normalized multiparametric disaggregation technique (NMDT) and converted into a mixed-integer linear programming (MILP) problem. Numerical simulations on a 6-bus/6-node IPHS are carried out to validate the proposed method, and key factors influencing the flexibility of the DHS are analyzed. Full article

In this study, we address a coupled system of nonlinear fractional delay differential equations subject to cross-coupled multi-point boundary conditions. By utilizing the generalized power Caputo fractional derivative, we present a unified theoretical framework that encompasses several operators—including the Atangana–Baleanu, Caputo–Fabrizio, and weighted Hattaf derivatives—as special cases. This generality ensures that our results remain applicable across a broad family of fractional kernels. We transform the complex delay system into an equivalent integral form to derive sufficient criteria for the existence and uniqueness of solutions via fixed-point theory. Furthermore, we rigorously establish the Ulam–Hyers stability of the system, a critical property for ensuring robustness in the presence of perturbations. Finally, the theoretical findings are validated through a detailed numerical study employing a predictor–corrector scheme adapted for fractional delay systems. The simulations highlight the sensitivity of solutions to the memory kernel and fractional orders and include a systematic exploration of delay effects. Full article

Validation of ICON model configurations optimized over a limited domain is essential before accepting new semi-empirical parameters that influence the behavior of subgrid-scale schemes. Because such parameters can modify the dynamics of a numerical weather prediction (NWP) model in highly nonlinear ways, we analyze one season of forecasts (December 2022, January and February 2023) generated with the NWP ICON-LAM through the lens of machine learning–based diagnostics as a complement to traditional evaluation metrics. The goal is to extract physically interpretable information on the model behavior induced by the optimized parameters. This work represents the first part of a wider study exploring machine learning tools for model validation, focusing on two specific approaches: Empirical Orthogonal Functions (EOFs), which are widely used in meteorology and climate science, and autoencoders, which are increasingly adopted for their nonlinear feature extraction capability. In this first part, EOF analysis is used as the primary tool to decompose weather fields from observed reanalysis and forecast datasets. Hourly 2-m temperature forecasts for winter 2022–2023 from multiple regional ICON configurations are compared against downscaled ERA5 data and in situ observations from ground station. EOF analyses revealed that the optimized configurations demonstrate a high skill in predicting surface temperature. From the signal error decomposition, the fourth EOF mode is effective particularly during night-time hours, and contributes to enhancing the performance of ICON. Analyses based on autoencoders will be presented in a companion paper (Part II). Full article

Thermo-hydrodynamic (THD) lubrication is a key mechanism in injection pumps, where frictional heating and heat transfer strongly influence lubrication performance. Accurate numerical modeling remains challenging due to the nonlinear coupling of temperature- and pressure-dependent fluid properties and the high computational cost of iterative solvers. The rising relevance of bio-hybrid fuels, however, demands the investigation of a great number of fuel mixtures and conditions, which is currently infeasible with traditional solvers. Physics-informed neural networks (PINNs) have recently been applied to lubrication problems; existing approaches are typically restricted to stationary cases or rely on data to improve training. This work presents a novel, purely physics-based PINN framework for solving coupled, transient THD lubrication problems in injection pumps. By embedding the Reynolds equation, energy conservation laws, and temperature- and pressure-dependent fluid models directly into the loss function, the proposed approach eliminates the need for any simulation or experimental data. The PINN is trained solely on physical laws and validated against an iterative solver for 16 transient test cases across two fuels and eight operating scenarios. The good agreement of PINN and iterative solver demonstrates the strong potential of PINNs as efficient, scalable surrogate models for transient THD lubrication and iterative design applications. Full article

We present a theoretical and numerical investigation of a far-field super-resolution dark-field microscopy technique based on longitudinal nano-optical field excitation and detection. This method is implemented by integrating vector optical field modulation into a back-scattering confocal laser scanning microscope. A complete forward theoretical imaging framework that rigorously accounts for light–matter interactions is adopted and validated. The weak interaction model and general model are both considered. For the weak interaction model, e.g., multiple discrete dipole sources with a uniform or modulated responding intensity are utilized to fundamentally demonstrate the relationship between the sample and the imaging information. For continuous nanostructures, the finite-difference time-domain simulation results of the interaction-induced optical fields in the imaging model show that the captured image information is not determined solely by system resolution and sample geometry, but also arises from a combination of sample-dependent factors, including material composition, the local density of optical states, and intrinsic physical properties such as the complex refractive index. Unlike existing studies, which predominantly focus on system design or rely on simplified assumptions of weak interactions, this paper achieves quantitative characterization and precise regulation of nanoscale vector optical fields and samples under strong interactions through a comprehensive analytical–numerical imaging model based on rigorous vector diffraction theory and strong near-field coupling interactions, thereby overcoming the limitations of traditional methods. Full article

This paper presents a reduced-order Legendre–Galerkin extrapolation (ROLGE) method combined with the scalar auxiliary variable (SAV) approach (ROLGE-SAV) to numerically solve the time-fractional Allen–Cahn equation (tFAC). First, the nonlinear term is linearized via the SAV method, and the linearized system derived from this SAV-based linearization is time-discretized using the shifted fractional trapezoidal rule (SFTR), resulting in a semi-discrete unconditionally stable scheme (SFTR-SAV). The scheme is then fully discretized by incorporating Legendre–Galerkin (LG) spatial discretization. To enhance computational efficiency, a proper orthogonal decomposition (POD) basis is constructed from a small set of snapshots of the fully discrete solutions on an initial short time interval. A reduced-order LG extrapolation SFTR-SAV model (ROLGE-SFTR-SAV) is then implemented over a subsequent extended time interval, thereby avoiding redundant computations. Theoretical analysis establishes the stability of the reduced-order scheme and provides its error estimates. Numerical experiments validate the effectiveness of the proposed method and the correctness of the theoretical results. Full article