Search Results (104,546)

To address the problems of closed-loop task organization, strong corridor constraints, and path failure after local disturbances in unmanned aerial vehicle (UAV) inspection of gas-insulated switchgear (GIS) rooms, this paper proposes a topology-and-corridor-guided bias-suppressed D* (TCG-BS-D*) method for closed-loop three-dimensional (3D) path planning and local replanning. The proposed method constructs a structured guidance model based on the inspection-corridor topology, generates local 3D path segments according to a predetermined inspection sequence, and forms a nominal closed-loop inspection path through bias suppression and path regularization. Meanwhile, for local maintenance blockage and dynamic disturbance scenarios, an alternative local replanning strategy is applied to the affected path segments. Simulation results show that, under the static closed-loop inspection condition, the proposed method achieves a total path length of 700.22 m, a total inspection time of 269.32 s, an average safety clearance of 8.18 m, 37 large-angle turns, a corridor adherence rate of 80.73%, and a task completion rate of 100%, showing superior performance in inspection efficiency, safety margin, trajectory regularity, and corridor consistency. Under the local blockage condition, the replanned path introduces path-length and time increments of 71.29 m and 25.88 s, respectively, while maintaining the minimum safety clearance at 1.52 m and increasing the corridor adherence rate to 83.91%. Under dynamic disturbance conditions, the minimum dynamic safety clearance is improved from −2.71 m to 17.84 m, effectively eliminating the local dynamic collision risk. The results demonstrate that the proposed method can balance closed-loop path-generation efficiency, corridor-structure consistency, safety margin, and adaptability to local disturbances, providing an effective solution for UAV inspection path planning in GIS rooms. Full article

Trajectory optimization during the terminal area energy management (TAEM) phase is pivotal for achieving accurate runway alignment and enhancing landing safety in autonomous aircraft operations. In the presence of initial state uncertainties in TAEM phase, conventional pseudo-spectral methods still suffer from robustness limitations and exhibit a strong dependence on the quality of the initial guess. Therefore, this paper proposes the composite African vulture optimization algorithm (CAVOA), a meta-heuristic framework designed to automate trajectory optimization. An in-depth examination of the heading alignment cone (HAC) trajectory model enables effective heading adjustments prior to landing, augmented by a tailored dynamic pressure profile to ensure safe touchdown velocities. By incorporating dynamic opposition learning, intelligent boundary processing, and composite exploration, CAVOA enhances global search efficiency. These enhancements are substantiated through comparisons with benchmark function optimization, Wilcoxon rank sum tests, and convergence analysis. Numerical simulations validate that CAVOA reliably directs autonomous aircraft to predefined touchdown states, demonstrating superior performance in complex aerial environments. Full article

To address the high deployment cost, insufficient local coverage, and limited timeliness of conventional wave-observation methods in onboard real-time applications, this study conducts a comparative investigation of centre-of-gravity-equivalent instantaneous wave-height estimation models based on three-degree-of-freedom ship motion responses under the framework of the wave buoy analogy (WBA). The heave, roll, and pitch responses of a 1:2 scaled Series 62 4667-1 planing craft model in regular head seas are used as inputs, while the synchronous instantaneous wave-height signal measured by a wave probe near the centre of gravity is used as the label. A unified protocol is established with consistent inputs, labels, window construction, data partitioning, and evaluation metrics. Six models, namely SVR, TCN, LSTM, CNN-LSTM, Transformer, and LSTM-MHA, are compared and validated using STAR-CCM+ numerical simulation data and towing-tank experimental data. The results indicate that, in the simulated case of H = 0.10 m and T = 1.5 s, LSTM-MHA achieves the highest estimation accuracy, with RMSE and R² values of 0.001231 and 0.997848, respectively, but it also has the largest model size and computational cost. In comparison, TCN achieves near-optimal accuracy with a smaller parameter count and lower inference latency, and shows stable performance across multiple conditions. The towing-tank experimental results further show that both LSTM-MHA and TCN clearly outperform the SVR baseline. Overall, accuracy in the simulation domain, robustness in the towing-tank experimental domain, and cross-domain generalisation capability are not fully consistent. Therefore, the selection of onboard instantaneous wave-height estimation models should jointly consider estimation error, model complexity, computational latency, window length, and practical deployment requirements. Full article

Three-dimensional UAV operations require path planning methods that can jointly maintain route efficiency, threat avoidance, and trajectory smoothness under spatially distributed and time-varying constraints. To address this problem, this paper develops an integrated Dual-Layer Adaptive T-perturbation and Opposition-based Multi-Objective Particle Swarm Optimization framework, termed DATO-MOPSO, for 3D UAV path planning in complex threat environments. The method integrates a dual-layer adaptive inertia-weight and velocity-regulation mechanism with symmetric T-perturbation, an elite quasi-opposition-based learning strategy for diversity recovery and feasible local exploitation, and an archive-driven simulated annealing rule for stagnation-aware personal-best updating. A three-objective model minimizing path length, threat exposure, and path smoothness is established, and comparative experiments against MOPSO, ZAMOPSO, NSGA-II, and SPEA2 are conducted in both static and dynamic environments, together with statistical and ablation analyses. In the static scenario, DATO-MOPSO achieved the highest mean HV and stable repeated-run performance, but its IGD was comparable to ZAMOPSO with higher computational cost. In the dynamic scenario, DATO-MOPSO showed its main advantage, achieving the highest mean HV and the lowest mean IGD with statistically significant HV and IGD improvements over all baselines. Overall, DATO-MOPSO is most advantageous in time-varying complex threat environments, whereas its static-scenario advantages are accompanied by higher computational cost. Full article

Decarbonization of existing buildings is obstructed by the performance gap between intended and operational energy consumption. Smart energy management and monitoring of existing buildings through digital twins pose significant attributes towards decarbonization efforts. However, there is limited research that transforms digital twins’ monitored performance into actionable retrofitting strategies. Hence, this research develops a framework that bridges the digital twin concept with standards-based IEQ analytics, guiding retrofit decision-making in existing buildings. The framework offers a low-code workflow that uses Autodesk Tandem to develop a digital twin integrating indoor environmental quality (IEQ) data, including thermal comfort and air quality. IEQ is monitored since inefficient management of its parameters often results in excessive HVAC demand, contributing to the performance gap. The framework structures IEQ parameter evaluations against benchmarks guided by ASHRAE to identify deviations indicative of operational inefficiencies in energy consumption. The digital twin model positions live IEQ tracking and analysis as diagnostic measures, leading to targeted fabric-oriented retrofit prioritization. The framework was tested on a case study in a hot arid climate, where its results indicate that the integration of digital twin-based IEQ analysis with building characteristics effectively identified the need for targeted envelope improvements, including high-performance glazing, external shading elements, and sound isolation, as key factors for eliminating overheating and high noise levels. Validating the proposed retrofits’ effectiveness, energy simulations examines the whole building to find an 11.52% annual reduction in energy use intensity from 145.61 kWh/m²·year to 128.84 kWh/m²·year through shading elements and low-E films for glazing. Full article

Local impedance variations in structural waveguides partially reflect and absorb incident
flexural waves, motivating wave-based strategies for passive vibration control. This study
develops and experimentally validates a wave-energy framework to quantify and optimize
flexural wave absorption by Kelvin–Voigt attachments on a finite Timoshenko beam.
A finite element model is validated against Scanning Laser Doppler Vibrometry measurements
from a clamped–clamped aluminum beam with a passive damper mounted near
one end, with dashpot parameters identified through two independent approaches and
the discrepancies attributed to parameter uncertainty. Wave decomposition of the simulated
and measured velocity fields yields the power reflection coefficient ρ(ω) and power
absorption coefficient α(ω) over the 0–15.3 kHz band. The spring stiffness and damping
coefficient exhibit frequency-dependent optima and act as complementary, jointly tuned design
variables. Expressing dashpot location in wavelength-normalized coordinates reveals
a recurring spatial pattern in which absorption minima cluster around half-wavelength
multiples, while multiple spanwise positions yield near-peak absorption at any given
frequency. This pattern is governed primarily by the flexural wavelength, decoupling
placement from parameter tuning, and persists across clamped–clamped, clamped–free,
and free–free boundary conditions. Two independently tuned dampers further broaden the
effective absorption band by suppressing local minima in α(ω). These results demonstrate
that measurement-driven wave decomposition provides compact, physically grounded
guidelines for passive damper placement in beam structures. Full article

The escalating security risks associated with unauthorized unmanned aerial vehicles (UAVs) in advancing smart cities necessitate the development of robust active countermeasures. This work presents a novel approach centered on a UAV-borne flexible net system and provides a rigorous investigation into its complex nonlinear dynamics. This study establishes a lumped-mass, semi-spring–damper dynamic model of the flexible capture net, characterizing its key dynamic properties, including deployment performance, aerodynamic attitude, and the high-impact phenomena of collision and entanglement with the target UAV. To verify the reliability of the proposed method, numerical simulations are combined with field tests for systematic validation. Comparative analysis reveals excellent quantitative agreement, with over 80% conformity in the net’s spatial configuration between simulated and experimental results. This paper illuminates the fundamental principles governing energy dissipation and transient tension dynamics pre- and post-capture. This study provides preliminary evidence for the feasibility of the proposed method and identifies key directions for future investigation. The findings offer guidance for the design and optimization of future systems intended to neutralize low, slow, and small (LSS) aerial threats. Full article

Background: Effective strategies for delivering neuroprotective agents to the brain remain a major challenge due to the poor solubility, rapid metabolism, and low bioavailability of promising molecules, such as 7,8-dihydroxyflavone (7,8-DHF). This small-molecule TrkB receptor agonist exhibits significant antioxidant, neuroprotective properties, and additional effects on metabolic regulation, but its therapeutic potential is limited by unfavorable pharmacokinetic characteristics. Nanotechnology-based delivery systems are increasingly explored to improve drug stability, enhance bioavailability, and facilitate direct nose-to-brain transport following intranasal administration. In this study, lipid nanoparticles encapsulating 7,8-DHF were developed using a fish-oil-based lipid core enriched with ω-3 polyunsaturated fatty acids (DHA and EPA) and naturally derived excipients, including soybean lecithin and ε-polylysine. Methods: The formulation was optimized using a Design of Experiments (DoE) approach based on a 2³ full factorial design, evaluating drug concentration, lecithin concentration, and surfactant type (Pluronic^® F127 or Tween^® 80). The main formulation responses considered were particle size, polydispersity index (PDI), zeta potential, and encapsulation efficiency. Results: The optimized nanoparticles exhibited nanometric dimensions (<250 nm); spherical morphology, confirmed by TEM; low polydispersity (PDI < 0.3); and adequate encapsulation efficiency. Stability studies in simulated biological fluids indicated good physicochemical stability for up to 48 h, while interaction studies with mucin suggested a good interaction within the mucus environment. ROS scavenging capacity was confirmed through the DPPH chemical assay, and in vitro experiments on olfactory ensheathing cells, selected as a biologically relevant model for their anatomical localization along the olfactory pathway, showed reduced cytotoxicity of the encapsulated drug compared with the free form. Conclusions: Collectively, these results support the potential application of the developed nanoformulation in the intranasal delivery of 7,8-DHF. Full article

As augmented reality head-up display (AR-HUD) becomes increasingly integrated into intelligent vehicles, inappropriate interface designs may increase drivers’ cognitive workload and delay hazard responses. This study investigates how cognitive style, driving task type, and AR-HUD navigation design jointly influence drivers’ behavioral performance and visual attention. A total of 55 participants were recruited and screened using the Group Embedded Figures Test, with 38 drivers finally selected for a 2 × 4 × 2 driving-simulation experiment comparing world-fixed (WF) and screen-fixed (SF) interfaces across goal-directed and stimulus-driven tasks. Reaction times and eye-tracking indicators were analyzed using generalized linear models. Results show that stimulus-driven tasks significantly increased reaction times, with rear-vehicle scenarios producing the longest responses (mean = 1.420). During lane-change tasks, WF displays significantly reduced fixation duration (p < 0.001) and fixation counts (p < 0.001), whereas SF displays improved attentional efficiency during pedestrian-warning tasks. In addition, field-dependent drivers exhibited significantly larger pupil diameters, indicating higher cognitive workload. These findings provide sensor-based evidence for AR-HUD systems that dynamically optimize interface presentation according to task context and workload conditions. Full article

Virtual reality can support the preparation and rehearsal of assembly tasks by providing a safe and repeatable digital representation of workstations. This study presents the development and laboratory feasibility validation of a geometry- and procedure-oriented VR simulation model for the assembly and disassembly of end-effectors on an industrial robot. The workflow was implemented using the Almega AX-V6 robotic workstation as a case study and included geometric acquisition of the real robot, CAD modelling in SolidWorks, redesign of the original end-effector connection using a quick-change flange concept, creation of two alternative end-effector models, modelling of the laboratory workspace in SketchUp, and scene enhancement in Twinmotion. The resulting robot and environment models were integrated in Pixyz Review and deployed through an Oculus Rift-based VR setup. Compared with the original flange concept, which required twelve screws, the redesigned training concept used two screws and two nuts, reducing the number of fastening elements by 66.7% and the number of screw positions by 83.3%. The VR implementation supported visual inspection, controller-based placement and alignment, and symbolic confirmation of fastening steps; it did not include force feedback, threaded fastening physics, automatic error scoring, or quantified transfer-of-training evaluation. Laboratory feasibility validation confirmed correct asset integration, spatial correspondence with the physical workplace, and functional executability of the target exchange sequence. The results show that the workflow is useful as a case-study pipeline for CAD-to-VR modelling and assembly rehearsal, while controlled user studies are still required before claims about training effectiveness can be made. Full article

Horticultural intensification in Mediterranean areas has increased the risk of nitrate pollution due to inefficient irrigation and nitrogen fertilisation management. The availability of simulation models aimed at rational nitrogen management in outdoor crops is limited. The objective of this study is to adapt the VegSyst model, initially developed for greenhouse vegetables, for use in open-field conditions in relevant crops, such as processing peppers and broccoli in Extremadura. VegSyst simulates dry matter production and nitrogen uptake by incorporating the influence of evaporative demand (TUE approach) in addition to the effect of radiation (RUE approach). Experimental field data obtained in five campaigns (peppers: 2020–2022; broccoli: 2020 and 2022) under different nitrogen doses were used. The model was calibrated, and critical N dilution curves were developed for each crop. Subsequently, the simulation of fi-PAR, dry matter production (DMP) and N uptake was validated using statistical indices (RMSE, RE, d, EF) and regression analysis. The model showed a high predictive capacity for N uptake in both crops, with values of d ≥ 0.98 and EF ≥ 0.90 in the validation campaigns. The fi-PAR simulation was acceptable in peppers and excellent in broccoli. In contrast, the DMP prediction showed notable deviations in peppers, especially in 2022, attributable to interannual variations in weather conditions and physiological limitations not considered by the model. In both crops, the TUE-based strategy was a better fit for the measurements than the RUE-based strategy, indicating that under semi-arid Mediterranean conditions, transpiration is the limiting factor for biomass production. The adaptation of the VegSyst-Outdoors model proved to be robust for simulating N uptake and sufficiently accurate to be integrated into decision support tools aimed at efficient fertilisation and irrigation management. Full article

We propose a fractional-order cancer virotherapy model based on Caputo derivatives to investigate the temporal interactions among tumor cells, viruses, and immune response components. The existence and uniqueness of the solutions for the proposed model are rigorously studied. The proposed model is capable of tracking the temporal dynamics of uninfected and infected cancer cells, free oncolytic virus, and several components of the immune response. To determine the analytical solutions of the resulting nonlinear fractional-order system, we utilize the Temimi–Ansari method (TAM). The convergence and accuracy of the method are confirmed via error analysis and numerical simulation carried out in MATHEMATICA. It is observed that the fractional order plays a prominent role in controlling the temporal dynamics of the cancer–virus–immune system, leading to a reduction in the number of infected cancer cells due to virotherapy. On the other hand, the immune response is vital for controlling cancer growth. Full article

Acoustic propagation in stratified shallow seas is governed by finite-depth waveguiding, impedance contrasts at the seawater–seabed interface, and coupled space–time wave dynamics. Conventional numerical solvers are accurate but often require detailed environmental priors, mesh generation, and explicit time marching, increasing the cost of simulations involving complex boundaries or repeated evaluations. This study proposes a physics-informed residual network (ResNet-PINN) for continuous simulation of two-dimensional acoustic fields in shallow-sea stratified media. The framework embeds a variable-density, variable-sound-speed acoustic pressure wave equation, initial and boundary constraints, and interface-focused collocation into network training. A Gaussian initial wave packet and temporal gating are incorporated through the output transformation to improve early-time physical consistency. The model is validated against SPECFEM2D simulations and a stratified semi-analytical modal benchmark. The results show that it captures source-region spreading, main wavefront evolution, and transmission–reflection structures near the seawater–seabed interface at an equivalent frequency of approximately 477 Hz. Supplementary tests with sloping and arched interfaces and modified boundary conditions indicate adaptability to smooth interface variations. Overall, the framework provides a physically consistent neural network strategy for continuous shallow-sea acoustic field simulation and a complementary basis for future extensions to higher-frequency propagation, more complex environments, and dynamically varying ocean conditions. Full article

Two reconstruction methods for constraint and load parameters of aero-engine pipelines based on intelligent optimization algorithms are proposed in this paper. First, a simplified finite element model (FEM) of the aero-engine pipeline structure is established, and its reliability is validated by comparing simulation data with experimental data. Second, a reconstruction algorithm for spring constraint parameters and pipeline load parameters based on the improved particle swarm optimization (IPSO) algorithm is developed on the MATLAB data analysis and ANSYS simulation platforms, which completes the reconstruction calculation of parameters such as spring constraint stiffness and applied harmonic excitation. For harmonic excitation parameter reconstruction, the maximum error of this algorithm reaches 24.9%, revealing its significant inapplicability to load parameter reconstruction. To solve this problem, a load reconstruction method based on the conjugate gradient method (CGM) is further proposed to achieve accurate reconstruction of pipeline load parameters, which mitigates the large reconstruction error of the IPSO algorithm under working conditions with multiple loads. Under 5% noise interference, the maximum error of the CGM is merely 5.16%. Finally, experimental verification of harmonic excitation amplitude reconstruction is performed using the CGM with lower reconstruction errors. Experimental results indicate that the maximum error is 14.24% for harmonic excitation amplitude reconstruction, which verifies the high applicability of the conjugate gradient algorithm to load reconstruction of aero-engine pipelines. Full article

To investigate the early-stage flame propagation and pressure response of premixed H₂-O₂ combustion under ultra-high-pressure constant-volume conditions, a transient CFD model was developed for a large-volume confined chamber. The numerical framework combines a density-based solver, the Peng–Robinson real equation of state, large eddy simulation, and a reduced H₂-O₂ chemical kinetic mechanism. Simulations were conducted at initial pressures of 30 and 40 MPa, H₂/O₂ molar ratios of 8:1 and 12:1, and three-, four-, and five-point ignition configurations. The results show that increasing the initial pressure from 30 MPa to 40 MPa advances the pressure rise onset from approximately 1.65 ms to 1.28 ms and increases the maximum pressure rise rate from 18.6 MPa·ms⁻¹ to 27.4 MPa·ms⁻¹ under the H₂/O₂ = 8:1 and three-point ignition condition. Under the investigated fuel-rich conditions, increasing the H₂/O₂ molar ratio from 8:1 to 12:1 delays the pressure rise onset from approximately 1.28 ms to 1.46 ms and reduces the maximum pressure rise rate from 27.4 MPa·ms⁻¹ to 21.1 MPa·ms⁻¹. For the 30 MPa and H₂/O₂ = 8:1 cases, the four-point ignition case produces the largest pressure rise rate of approximately 23.5 MPa·ms⁻¹, whereas the five-point ignition case shows a lower pressure fluctuation amplitude of approximately 3.6 MPa. The present conclusions are based on CFD quantitative engineering predictions and should be further validated using quantitative experimental measurements. Full article