Search Results (331)

Steel structures operating in demanding environments require instrumentation capable of detecting structural damage and supporting timely intervention. This paper presents a compact wireless system that integrates piezoelectric sensing, decision-making, and localized on-demand repair. A surface-mounted piezoelectric transducer (PZT) transmitter–receiver pair is bonded to a steel plate, while an Arduino controller drives the transmitter with a 5 V, 10 kHz signal and acquires the sampled receiver response. Damage is identified through relative changes from a baseline established for the intact plate. Upon detection, a motor-driven miniature valve releases low-viscosity adhesive from an internal reservoir through a silicone tube for gravity-fed delivery to the damaged region. The system also logs and transmits data for MATLAB R2025b-based post-processing. A 3D-printed PLA/TPU housing integrates the sensing, control, power, and repair components while mechanically separating sensing and actuation functions. Coupled-field harmonic simulations in ANSYS were used to evaluate the electromechanical response of the bonded PZT pair and support the experimental design. Experimental frequency sweeps characterized the intact-system response, while controlled slot-width tests at 10 kHz showed a systematic decrease in the sampled receiver-response index with increasing defect width. Repair performance was further supported by partial recovery of the sampled response, together with morphology and bond-strength evidence showing continuous adhesive filling and mechanically meaningful bonding. The results demonstrate the feasibility of integrating piezoelectric sensing, decision-making, and localized on-demand repair within a single portable system for steel structures. Full article

Permanent-magnet brushless DC motors (PMBLDCMs) are widely used in various industrial applications. This paper proposed a fully analytical dynamic model of PMBLDCMs based on the armature reaction and subsequent commutation phenomenon. First, it introduced the PMBLDCM prototype, including the stator currents, electromagnetic torque, and rotor position calculated via electromotive force balance equations, the Maxwell stress tensor method, and motion formulas. Then, it employed the subdomain method under load conditions to analyze magnetic flux densities in the airgaps and the stator slots. Finally, it established a field-circuit coupling finite-element model (FEM) to verify magnetic flux densities, back-EMF, torque and rotor-position predictions. A 1.5 kW PMBLDCM prototype was built with back-EMF and stator-phase currents validated through experiments. In addition, torque and rotor-position results are validated against FEM instead of physical experiments. Full article

Background: Aviation spare parts management faces unpredictable demand, long lead times, strict airworthiness requirements, and high inventory costs, which drive aircraft-on-ground events and operational disruption. Digital spare parts, enabled by digital warehousing and local on-demand manufacturing, offer a potential response, but no standardized framework exists for selecting items for digital warehousing in aviation. Methods: This study develops a modified Spare Parts Interchangeability Record framework incorporating digital readiness, manufacturability, and production-based lead times, coupled to a stochastic discrete-event simulation. Twenty candidate Airbus A320 components are screened, and three supply configurations are compared over a one-year horizon: physical warehousing with OEM procurement, fully digital warehousing with local production, and a hybrid strategy. Results: The hybrid configuration performs best. Relative to the baseline, total waiting time falls by 67.7%, demand-weighted aircraft-on-ground duration from 1089 to 316 h, operational cost by 19.7%, and transport-related emissions by 50%, while service level rises from 86.5% to 95.8%. A fully stockless configuration proves contingent on production capacity, leaving 32.3% of demand unserved at the capacity assumed; twenty simultaneous production slots are identified as the viability threshold. Conclusions: Technical suitability alone does not establish strategic viability. Results derive from simulation rather than field implementation. Full article

Emergency, remote, and infrastructure-constrained environments cannot always rely on cellular networks or continuous Internet connectivity. LoRa offers an alternative for direct, long-range communication between low-power devices without depending on nearby cellular infrastructure, but its low data rate and variable transmission time create new coordination challenges. When multiple LoRa nodes must agree on information, fixed timing can either introduce unnecessary delay or cause missed deadlines as radio conditions change. This paper introduces a cross-layer controller that adapts mesh coordination timing to LoRa time-on-air at runtime. A MAPE-K loop maps estimated airtime into transmission-slot spacing $S\left(c\right)$ and deadlines $D\left(c\right)$, coupled with quorum or full-participation finalisation and a bounded single-retry mechanism. The framework was implemented on four SX1276 nodes at 915 MHz and evaluated over 2514 coordination rounds under crash and omission faults. Three-of-four quorum coordination achieved a median latency of 2.1 s, compared with 5.3 s for full participation. Overall, 88.6% of rounds met the first adaptive deadline, 11.4% required one retry, and none exhausted the retry budget or violated the evaluated safety invariants. A replay-derived fixed-SF12 schedule produced a median completion time of 11.3 s, compared with 3.4 s for adaptive execution. These results show that LoRa airtime can serve as a practical runtime signal for adaptive coordination on constrained mesh nodes. Full article

This paper proposes a physics-informed neural network (PINN)-based design optimization framework for a compact smart actuator motor in physical artificial intelligence (Physical AI) robotic systems, where artificial intelligence is integrated with sensing, actuation, and physical interaction to perceive and act in the real world. To improve integration density and joint compactness, a printed circuit board (PCB) stator axial-flux permanent magnet (AFPM) motor is adopted as a thin and highly integrated topology. Because its performance is strongly affected by coupled design variables, including outer diameter, PCB count, turns per slot, trace width, and magnet thickness, an efficient and physically consistent optimization method is required. The proposed framework constructs a finite element analysis (FEA)-based design database and trains a physics-reconstructed PINN surrogate model to predict torque and loss components. Unlike purely data-driven models, the proposed PINN reconstructs output power and efficiency using physical power-balance relations, thereby improving consistency among torque, loss, output power, and efficiency. The trained surrogate is coupled with the nondominated sorting genetic algorithm II (NSGA-II) to maximize torque and efficiency while minimizing AC loss under dimensional and performance constraints. The optimized candidates are further verified by high-fidelity FEA. The results demonstrate that the proposed framework provides an effective Physical AI-oriented design methodology for compact robotic smart actuators by integrating PCB stator AFPM motor topology, physics-informed learning, and multi-objective optimization. Full article

This paper presents a wideband circularly polarized (CP) stacked patch antenna for 5G Sub-6 GHz applications. A major challenge in wideband dual-feed antennas is the fabrication limit caused by standard chemical etching and mechanical milling processes for extremely narrow high-impedance microstrip lines in two-stage branch-line couplers. To overcome this bottleneck, a Defected Ground Structure (DGS) is utilized. By etching the ground plane, the distributed inductance is increased, allowing the highly sensitive narrow traces to be physically widened while strictly maintaining the 50 Ω impedance. The antenna features an aperture-coupled mechanism via an H-shaped slot to excite the driven and parasitic patches, which are separated by an air gap to maximize bandwidth. The fabricated prototype demonstrates an impedance bandwidth ($\left|S_{11}\right|<-10 \mathrm{dB}$) of 41.6% (2.92–4.37 GHz) and a simulated 3 dB axial ratio bandwidth of 23.14% (3.26–4.07 GHz) with a peak realized gain of 7.54 dBi. Excellent agreement between simulated and measured results validates the robustness of the proposed DGS technique against fabrication tolerances. Full article

In disaster response and other infrastructure-limited settings, UAV-mounted access points can rapidly restore service availability for mobile ground users as demand and fleet availability evolve. Existing single-slot coverage formulations, however, can mask prolonged individual outages and do not jointly represent heterogeneous service priorities, finite battery capacities, and periodic recharging. We study persistent geometricmulti-UAV service coverage, where a user is available for service when it lies inside a UAV footprint. We propose Priority- and Outage-Guided Safe QMIX (POGS-QMIX), a hybrid hierarchical framework in which a centralized online coordinator forms conflict-reduced UAV–user targets from fleet-wide priority and outage information, while parameter-shared QMIX agents independently choose target-conditioned low-level actions. The framework couples class-balanced outage memory, assignment, dense target-progress feedback, and a return-energy action mask. The evaluation includes learning and non-learning baselines, greedy-versus-Hungarian assignment, multi-seed statistics, sensitivity studies, operating-condition studies, and energy-stress tests. In the default scenario, POGS-QMIX obtains high-priority coverage $0.547\pm 0.009$ and maximum high-priority outage $38.0\pm 4.7$ slots over five independent seeds. Full article

Underground coal-mine equipment operates under broadband noise, high dust, humidity, and methane. Acoustic sensing is uniquely suited to this environment: it captures vibration, friction, and airflow signatures without physical contact, incurs low sensor-deployment cost, responds at millisecond speed, and remains effective in low-light, high-dust conditions where optical and vibration alternatives fail. Acoustic fault perception is therefore critically important in underground coal-mine operations. Three unresolved challenges remain: (i) motor whine, material-collision impacts, and ventilation-fan roar compound into a low-SNR soundscape where conventional models lose noise robustness; (ii) acoustic signatures vary widely across equipment types and fault-development stages; and (iii) existing supervised classifiers, trained on imbalanced data, exhibit limited generalization and output only binary judgments, lacking the semantic descriptions that maintenance crews actually need. To address all three, we propose a domain-adaptive audio LLM coupling a BEATs encoder (frozen during Stage II, adapted via Low-Rank Adaptation (LoRA) during Stage I), a Querying Transformer (Q-Former) alignment layer with Dynamic Acoustic Token Compression (DATC), a LLaMA-3.1-8B decoder adapted via LoRA, and Constrained Decoding for Structured Fault Description (CD-SFD) enforcing a three-slot output of fault type, danger level, and handling recommendation. DATC allocates query budget by signal energy to suppress noise-dominated frames; CD-SFD is a state-machine decoder that guarantees the three-slot schema. We release CMEASD: 1200 recordings comprising 24 physical machines (4 per equipment type, 12/6/6 machine-disjoint split). Under machine-disjoint evaluation, the model reaches Macro Accuracy 84.6 ± 1.5% and Macro F1 82.9 ± 1.6%, outperforming the strongest discriminative baseline (PANNs-Transformer, 81.7%) by +2.9 pp and SALMONN-LoRA by +2.5 pp. Ablations attribute +2.4/+1.4/+0.9 pp to DATC, CD-SFD, and the domain prompt. A 30-day mine trial achieves 7.0 s end-to-end latency with 21/30 days of stable, zero-false-shutdown operation. Full article

Immersive media services increasingly rely on edge-cloud rendering to deliver interactive visual content under dynamic network, computing, and mobility conditions. Rendering an entire scene as a single service couples interaction-sensitive foreground content with context-oriented background content, making it difficult to jointly control latency, quality, synchronization, and migration overhead. This paper studies sense-driven edge-cloud foreground–background split rendering for immersive media services. We formulate an online decision problem in which foreground and background rendering layers can be independently controlled under long-term system and migration cost budgets. The formulation turns structural scene separation into a coupled layer-state control problem by preserving asymmetric QoE roles and a common composition requirement. We propose SEELE, a Lyapunov-guided online control algorithm that represents accumulated budget pressure with two virtual queues and converts the long-term constrained problem into lightweight per-slot decisions. The resulting per-slot rule balances immediate QoE loss against queue-weighted system and migration costs. Under sustained resource and network stress, SEELE provides steady-state QoE statistically comparable to a pretrained PPO policy while significantly reducing synchronization violations and improving composition stability. It also improves steady-state QoE and system debt over deterministic and QoE-prioritized baselines. A prototype implementation and controlled characterization further validate split-stream deployment, runtime observability, practical control hooks, and the latency–capacity tradeoff of layered rendering. Full article

Mechanical sand-control screens are core completion components for maintaining sand retention and flow conductivity in oil, gas, geothermal, hydrate, and underground gas storage wells. This review summarizes recent progress in the plugging mechanisms, diagnostic indicators, and plugging-removal technologies of mechanical sand-control screens. The reviewed studies show that screen plugging is a multi-mechanism process controlled by external sand bridging, internal fines invasion, drilling/completion fluid residues, chemical scaling, organic deposition, and their coupled cementation effects. External plugging is mainly associated with slot- or pore-entrance bridging and filter-cake compaction, whereas internal plugging is controlled by fines retention in mesh layers, prepacked gravel, or tortuous porous media. Pressure drop, permeability damage/recovery, produced-sand particle-size distribution, and microstructural characterization are key indicators for evaluating plugging severity and treatment effectiveness. Hydraulic jetting, mechanical vibration, ultrasonic treatment, acidizing, oxidizing systems, thermochemical treatment, and physical–chemical combined methods are compared in terms of mechanisms and applicability. The analysis indicates that single treatments are usually insufficient for strongly cemented multicomponent plugging; a sequential strategy of chemical weakening followed by physical stripping and flowback is more suitable for complex field conditions. Future work should focus on green and selective chemical systems, downhole diagnosis-guided treatment selection, and integrated sand-control designs combining plugging prevention, monitoring, and removal. Full article

This paper proposes an efficient analytical modeling method for the air-gap flux density in hydro-generators under eccentricity faults. The method specifically addresses the multi-factor coupling characteristics induced by the combined effects of stator slotting, salient-pole rotor structure, and eccentricity. Based on geometric analytical derivation, individual models for air-gap length considering stator slotting, rotor salient-pole structure, and eccentricity are established, and an analytical expression for the air-gap length under coupled conditions is derived. By incorporating the spatial distribution characteristics of the magnetomotive force, a mathematical model for no-load air-gap flux density is constructed, enabling the rapid calculation of air-gap magnetic field distribution. Finite element verification conducted on an 84-slot, 10-pole hydro-generator demonstrates that the proposed method accurately reflects the periodic fluctuations and amplitude variations in the magnetic flux density under both normal and eccentric conditions. Compared with the finite element method (FEM), the analytical approach significantly enhances computational efficiency while maintaining high accuracy, providing effective theoretical support for the structural optimization and eccentricity fault diagnosis of hydro-generators. Full article

Driven by the engineering requirement for high acoustic stealth of unmanned underwater vehicles (UUVs), this paper investigates the electromagnetic vibration of an 8-pole, 48-slot, surface-mounted permanent magnet synchronous motor (SPMSM) employed in the propulsion system through multi-physics coupling analysis and experimental testing. First, analytical calculations of electromagnetic force waves are performed based on the Maxwell stress tensor method and the magnetomotive force–permeance method to analyze the spatial orders, temporal orders, and sources of the harmonics. Then, a two-dimensional motor model is established using ANSYS electromagnetic field simulation software to investigate the temporal and spatial characteristics of electromagnetic force waves under both no-load and on-load conditions. Fourier decomposition is applied to obtain the amplitude-frequency characteristics, thereby verifying the correctness of the analytical results. Subsequently, three-dimensional models of the stator core and the complete stator assembly are constructed in the physical field, and their modal frequencies and mode shapes are obtained through simulation. On this basis, harmonic response analysis is conducted by applying electromagnetic force waves to the stator teeth, and vibration simulations are performed in ANSYS Workbench to acquire vibration characteristics. Vibration experiments are then carried out at multiple rotational speeds, and the experimental results are compared with the simulation results to validate the feasibility and accuracy of the finite element modeling approach. Since the measured motor vibration results are influenced not only by electromagnetic excitation forces, but also by various factors such as mechanical structure, instrument installation, and fixture conditions, while the simulation model in this paper inevitably simplifies damping, housing details, inverter control effects, and considers only the effect of radial electromagnetic forces, there exists a certain discrepancy between the simulated and measured motor vibration acceleration results. However, the main vibration trends in the low-frequency range below 800 Hz are basically consistent, particularly at the second and fourth harmonic frequencies, where the vibrations are electromagnetic vibrations caused by radial electromagnetic force waves, with relative errors between the measured and simulated values of 18% and 25%, respectively. This finite element model can be used for preliminary design evaluation of PMSMs and rapid prediction of electromagnetic vibration, providing researchers with a convenient and practical research approach and methodology. Finally, by analyzing factors that may influence motor vibration, this paper proposes design modifications to the stator structure and air-gap width, providing an optimized solution for reducing electromagnetic vibration of the permanent magnet synchronous motor and avoiding resonance. Full article

Electromobility is central to urban decarbonisation, but its charging infrastructure must be sized under substantial uncertainty about user behaviour that varies across stations, time of day and user type. This study couples a hierarchical Bayesian model with an agent-based, discrete-event simulation of a charging network. It is fitted by Markov chain Monte Carlo to the public ACN-Data dataset (13,694 sessions across 52 stations; 16,468 user requests), with partial pooling across stations. Posterior parameters drive a 24 h simulation of 500 vehicles across nine configurations and 30 to 180 slots. Service success rises from 19% to 81% and mean waiting falls from 110 to 62 min; long workplace dwell times limit turnover, so capacity rather than energy binds. TOPSIS with a paired bootstrap selects 160 slots under balanced weighting, but that optimum holds for only a tenth of the weight simplex, and the recommendation spans 140–180 slots. Spreading the arrival peak at fixed hardware raises service from 67% to 83%, matching a 29% expansion. Spatially explicit assignment costs three percentage points when stations are evenly sited, and six when clustered. The framework makes the cost of over-provisioning explicit and preference-conditional rather than naming a single optimum, giving a reproducible basis for sustainable capacity planning. Full article

Compact sub-6 GHz and wireless local area network (WLAN) multiple-input multiple-output (MIMO) antennas require broad impedance coverage and low inter-port coupling within limited footprints. This work presents a two-port Koch-fractal U-slot antenna with a defected ground structure (DGS) on RT/duroid 5880. The design evolves from a rectangular monopole through Koch-edge shaping, U-slot loading, and ground-plane defects. The fabricated two-port prototype exhibits a measured −10 dB impedance bandwidth of 3.07–6.02 GHz, covering n78, n79, and WLAN, while the measured inter-port isolation exceeds 18.13 dB. The fabricated single-element prototype provides measured realized gains of 1.92, 2.34, and 2.05 dBi at 3.5, 4.7, and 5.5 GHz, respectively. Measurement-derived MIMO metrics yield an envelope correlation coefficient not exceeding 0.002, diversity gain close to 10 dB, channel capacity loss of 0.07–0.10 bits/s/Hz, mean effective gain near −3.1 dB with zero port imbalance, and acceptable in-phase total active reflection coefficient behavior. WLAN-band quadrature phase-shift keying tests at 5.18, 5.50, and 5.825 GHz produce error vector magnitude values of 5.4–9.1%, with derived bit error rate estimates below 10⁻⁶ under an additive white Gaussian noise assumption. The design provides wide measured bandwidth, good isolation, low correlation, and WLAN-band signal-domain validation in a simple printed structure. Full article

Off-highway vehicle electrification requires traction motors combining high torque density with reliable performance across demanding duty cycles, yet finite-element-based optimization remains computationally demanding for broad design-space exploration. This study addresses the gap with a sensitivity-analysis-based, surrogate-assisted multi-objective optimization framework for a 12-pole/72-slot, 120 kW Interior Permanent-Magnet Synchronous Motor (IPMSM) for a compact wheel-loader drivetrain, coupling Ansys Motor-CAD with Ansys OptiSLang. A Latin Hypercube sensitivity study of thirteen geometric parameters identifies the dominant design drivers, and an evolutionary algorithm operating on the validated surrogate produces a Pareto-optimal set, from which the final design is selected using the CRITIC–TOPSIS method applied to finite-element-validated feasible designs. Relative to the baseline, the validated performance shows a 7.4% increase in continuous torque, a 4.0% increase in peak torque, a 4.0% increase in efficiency, and a 53.5% reduction in torque ripple, with mass essentially unchanged, while also revealing that surrogate predictions were markedly optimistic relative to the finite-element results. These findings demonstrate an efficient, reliable route to high-performance IPMSM design for off-highway applications. Full article