Search Results (1,278)

The performance of large-scale photovoltaic (PV) power plants is strongly influenced by array layout parameters including module tilt angle, azimuth angle, and row spacing. These geometric variables jointly determine solar irradiance geometry, shading losses, and land-use efficiency, affecting annual energy yield and levelized cost of electricity. To achieve multi-objective comprehensive optimization of array layout parameters for a PV power generation system, a collaborative optimization strategy for PV array layout based on the lemur optimization (LO) algorithm is proposed in this paper. The method couples the Perez anisotropic irradiance model with a dynamic shading irradiance geometric model to simulate the effective insolation, incorporating land availability, shading thresholds, and maintenance access requirements. In addition, the LO algorithm is employed to solve resulting nonlinear and constrained problems, enabling an efficient global search across large parameter spaces. The case studies in Lianyungang, Dalian, and Fuzhou City show that the proposed scheme based on the LO algorithm improves annual energy yield compared with the existing optimization schemes, providing new theoretical methods and engineering application paths for the optimal layout of PV arrays. Full article

The heart is the body’s core pump. Heart failure impairs the heart’s ability to pump blood, leading to circulatory disorders. The artificial heart (blood pump) is an important mechanical circulatory support device that can partially or completely substitute cardiac pumping function, potentially improving hemodynamic performance and alleviating symptoms of heart failure. A combination of computational fluid dynamics simulation and hydraulic performance testing was used to study key parameters of the impeller, including blade count, blade wrap angle, impeller flow path, and diversion cone height. The goal was to reduce hemolysis risk and enhance pumping efficiency. Increasing the blade count raised the head, with optimal efficiency achieved at seven blades. A larger blade wrap angle decreased the head but improved efficiency. Synchronizing the flow path and diversion cone height at 4.1 mm maximized the head. Under various rotational speeds, the studied hemolysis index remained well below 0.1 g/100 L. Both experimental and simulation data were validated against each other, meeting the required error tolerances. The studied blood pump meets the design specifications. At an operating condition of 5 L/min flow rate and 2800 rpm, the pump achieves the required head and hemolysis criteria with a margin of safety. Full article

This study investigates jet plume deflection in underexpanded supersonic rectangular nozzles with aft-decks. To determine the underlying mechanism, 117 two-dimensional, Reynolds-averaged Navier–Stokes simulations were performed across a nozzle pressure ratio (NPR) range of $1.9\le \mathrm{NPR}\le 5.0$ and aft-deck length ($L_{\mathrm{aft}}/D_h$) range of $1.36\le L_{\mathrm{aft}}/D_h\le 3.37$. For each simulation, the first shock reflection $S_1$, the wall-pressure field, the vertical force $F_y$, and the presence of any separation bubble were recorded to characterize the relationships among $\mathrm{NPR}$, $L_{\mathrm{aft}}$, and $\theta$. Accordingly, a cause-and-effect path was delineated as $(\mathrm{NPR},L_{\mathrm{aft}})\to S_1\to F_y\to \theta$. A weighted regression captured 96% of the variance in the deflection angle and revealed that shifts in shock position set the wall-pressure imbalance. The imbalance fixes the vertical force and the force ultimately rotates the jet plume. Downward deflection arises when the shock reflects near the deck edge, whereas upstream reflection initiates a shock–boundary-layer interaction that forms a separation bubble and drives the jet plume upward. Between these extremes, a narrow operating band allows either outcome, explaining the divergent trends reported in prior work. The quantitative model assumes steady, two-dimensional flow and the regression prioritises illuminating the underlying physics over exact prediction of $\theta$. Nevertheless, under these assumptions, the analysis establishes a physics-based framework that reconciles earlier observations and offers a basis for understanding how nozzle pressure ratio and aft-deck length govern jet plume deflection. Full article

In the whole-angle mode of a hemispherical resonator gyro (HRG), the external input rotation angle is obtained by detecting the standing-wave rotation angle through electrodes. Due to this operational principle and manufacturing constraints of HRGs, the gyro output in an HRG inertial navigation system exhibits angle-dependent errors that are highly sensitive to temperature variations. To address this issue, this paper proposes a system-level calibration scheme to characterize and compensate for these correlated errors. Angle-dependent bias models were established through multi-temperature point experiments. A Kalman filter was subsequently designed, and a calibration path satisfying observability requirements was developed. System-level calibration experiments were conducted to determine and compensate for the identified errors. Finally, navigation experiments demonstrated the effectiveness of the proposed method, showing that the navigation accuracy of the HRG inertial navigation system was improved by up to 94.35%. Full article

To address the complexity of tensile mechanical behavior in fissured rock masses, this study conducted Brazilian splitting tests and numerical simulations on yellow sandstone containing randomly distributed fissures. Based on secondary development of the ABAQUS platform, a numerical model considering the spatial distribution of mineral components was established. A random fissure network was generated using the Weibull distribution, and crack propagation was characterized by employing cohesive elements. The influence mechanisms of the fissure inclination angle (θ = 0°~90°) and fissure ratio (R = 3~15%) on Brazilian tensile strength, failure mode, and crack propagation were systematically analyzed. The research demonstrates the following: (1) Brazilian tensile strength exhibits an overall decreasing trend with an increasing fissure ratio, while the effect of the fissure inclination angle is non-monotonic: at a low fissure ratio (R = 3%), Brazilian tensile strength shows a “decrease–increase–decrease” characteristic; at a medium to high fissure ratio (R ≥ 9%), Brazilian tensile strength continuously increases with an increasing fissure inclination angle. (2) The fissure ratio dominates the deviation of the failure path (deviation intensifies when θ ≤ 67.5° and is minimal at θ = 90°). At the mesoscale, the proportion of tensile cracks increases with an increasing R, while the contribution of shear cracks significantly enhances with an increasing θ (sharply increasing after θ > 45°). (3) Crack propagation is controlled by the spatial interaction of initial cracks. Under the combined action of a high inclination angle (θ = 90°) and high fissure ratio (R = 15%), a tensile–shear composite failure pattern forms, characterized by dual-source crack initiation and central coalescence. This study provides a mesoscale mechanical basis for the stability assessment of engineering structures in fissured rock masses. Full article

This paper addresses the issue of existing research that fails adequately capture the spatiotemporal nonstationarity caused by the building of occlusion and flight dynamics in air-to-ground channels from unmanned aerial vehicles (UAVs) in urban scenarios. This study focuses on the angular-altitude correlations of three key metrics: path loss (PL), shadow fading, and the Ricean K-factor. A dynamic path-loss model incorporating the look-down angle is proposed, an exponential decay model for the shadow-fading standard deviation is constructed, and a model for the angle-dependent variation of the Ricean K-factor is established based on line-of-sight probability. Simulations were conducted in two urban-geometry scenarios using WinProp to evaluate the combined effects of flight altitude and elevation angle. The results indicate that path loss decreases and subsequently stabilizes with increasing elevation angle, the shadow-fading standard deviation decreases significantly, and the Ricean K-factor increases with angle and saturates at high angles, in agreement with theoretical predictions. These models are more adaptable to UAV mobility scenarios than traditional fixed exponential models and provide a useful basis for UAV link planning and system optimization in urban environments. Full article

Terrestrial laser scanners (TLS) are widely used for deformation monitoring due to their ability to rapidly generate 3D point clouds. However, high-precision deliverables are increasingly required in TLS-based remote sensing applications to distinguish between measurement accuracies and actual geometric displacements. This study addresses the impact of atmospheric refraction, a primary source of systematic error in long-range terrestrial laser scanning, which causes laser beams to deviate from their theoretical path and intersect different object points on the target surface. A comprehensive study of two physical refractive index models (Ciddor and Closed Formula) is presented here, along with further developments on 3D spatial gradients of the refractive index. Field experiments were conducted using two long-range terrestrial laser scanners (Leica ScanStation P50 (Leica Geosystems, Heerbrugg, Switzerland) and Maptek I-Site 8820 (Maptek, Adelaide, Australia)) with reference back to a control network at two monitoring sites: a mine site for long-range measurements and a dam site for vertical angle measurements. The results demonstrate that, while conventional physical atmospheric models provide moderate improvement in accuracy, typically at the centimeter- or millimeter-level, the proposed advanced physical model—incorporating refractive index gradients—and the hybrid physical model—combining validated field results from the advanced model with a neural network algorithm—consistently achieve reliable millimeter-level accuracy in 3D point coordinates, by explicitly accounting for refractive index variations along the laser path. The robustness of these findings was further confirmed across different scanners and scanning environments. Full article

Vision navigation systems provide significant advantages in agricultural scenarios such as pesticide spraying, weeding, and harvesting by interpreting crop row structures in real-time to establish guidance lines. However, the delay introduced by image processing causes the path and pose information relied upon by the controller to lag behind the actual vehicle state. In this study, a hierarchical delay-compensated cooperative control framework (HDC-CC) was designed to synergize Model Predictive Control (MPC) and Sliding Mode Control (SMC), combining predictive optimization with robust stability enforcement for agricultural navigation. An upper-layer MPC module incorporated a novel delay state observer that compensated for visual latency by forward-predicting vehicle states using a 3-DoF dynamics model, generating optimized front-wheel steering angles under actuator constraints. Concurrently, a lower-layer SMC module ensured dynamic stability by computing additional yaw moments via adaptive sliding surfaces, with torque distribution optimized through quadratic programming. Under varying adhesion conditions tests demonstrated error reductions of 74.72% on high-adhesion road and 56.19% on low-adhesion surfaces. In Gazebo simulations of unstructured farmland environments, the proposed framework achieved an average path tracking error of only 0.091 m. The approach effectively overcame vision-controller mismatches through predictive compensation and hierarchical coordination, providing a robust solution for vision autonomous agricultural machinery navigation in various row-crop operations. Full article

The extraction of geothermal energy is of great significance for sustainable energy development. The destruction of hard rock masses during geothermal well exploitation generates seismic waves that can compromise wellbore stability and operational sustainability. Seismic waves are known to be affected by rock structures like cracks and interfaces. However, a quantitative understanding of these effects on wave parameters is still lacking. This study addresses this gap by experimentally investigating the effect of crack geometry (angle and width) and rock interfaces on seismic wave propagation. Using a synchronous system for rock loading and seismic wave acquisition, we analyzed wave propagation through carbonate rock samples with pre-defined cracks and interfaces under unconfined, dry laboratory conditions. Key wave parameters (amplitude, frequency, and energy) were extracted using the fast Fourier transform (FFT) and the Hilbert–Huang transform (HHT). Our primary findings show the following: (1) Increasing the crack angle from 35° to 75° and the width from 1 mm to 3 mm leads to significant attenuation, reducing peak amplitude by up to 94.0% and energy by over 99.8%. (2) A tightly pressed rock interface also causes severe attenuation (94.2% in amplitude and 99.9% in energy) but can increase the main frequency by up to 8.5%, a phenomenon attributed to a “boundary effect”. (3) Seismic wave parameters exhibit significant spatial variations depending on the propagation path relative to the source and rock structures. This study provides a fundamental, quantitative baseline for how rock structures govern seismic wave attenuation and parameter shifts, which is crucial to improving microseismic monitoring and wellbore integrity assessment in geothermal engineering. Full article

As the intelligent transformation of manufacturing accelerates, Unmanned Aerial Vehicles are increasingly being deployed for workshop operations, making efficient obstacle avoidance path planning a critical requirement. This paper introduces a parameter-optimized path planning method for the Unmanned Aerial Vehicle, termed the Artificial Potential Field A* algorithm, which enhances the standard A* approach through the integration of an artificial potential field and a variable step size strategy. The variable step size mechanism allows dynamic adjustment of the search step size, while potential field values from the artificial potential field are embedded into the cost function to improve planning accuracy. Key parameters of the hybrid algorithm are subsequently optimized using response surface methodology, with a regression model built to analyze parameter interactions and determine the optimal configuration. Simulation results across multiple performance indicators confirm that the proposed Artificial Potential Field A* algorithm delivers superior outcomes in path length, attitude angle variation, and flight altitude stability. This approach provides an effective solution for enhancing Unmanned Aerial Vehicle operational efficiency in production workshops. Full article

Robot navigation in confined spaces has gained popularity in recent years, but offline planning assumes static obstacles, which limits its application to online path-planning. Several methods have been introduced to perform an efficient robot navigation process. However, various existing methods mainly depend on pre-defined maps and struggle in a dynamic environment. Also, diminishing the moving costs and detour percentages is important for real-world scenarios of robot navigation systems. Thus, this study proposes a novel perceptron-Q learning fusion (PQLF) model for Robot Navigation to address the aforementioned difficulties. The proposed model is a combination of perceptron learning and Q-learning for enhancing the robot navigation process. The robot uses the sensors to dynamically determine the distances of nearby, intermediate, and distant obstacles during local path-planning. These details are sent to the robot’s PQLF Model-based navigation controller, which acts as an agent in a Markov Decision Process (MDP) and makes effective decisions making. Thus, it is possible to express the Dynamic Robot Navigation in a Confined Indoor Environment as an MDP. The simulation results show that the proposed work outperforms other existing methods by attaining a reduced moving cost of 1.1 and a detour percentage of 7.8%. This demonstrates the superiority of the proposed model in robot navigation systems. Full article

This paper introduces a method for estimating the Downlink Angle of Departure (DL-AoD) of 5G User Equipment (UE) from measured signal strengths of directionally transmitted synchronization signals. Based on estimated DL-AoD values, from two or more anchor nodes, the position of the UE was estimated. Unlike most prior work, which is simulation-based or relies on custom testbeds, this study uses real measurements from an operational 5G network in an industrial factory environment. A deterministic estimator was derived, but multipath and unknown beam characteristics limit its accuracy. To address this, machine learning was applied to automatically adapt to the environment. Previous simulation studies reported 90th-percentile DL-AoD estimation errors below 2°, while experimental works achieved best-case accuracies of 5–6°. In this study, the experimental DL-AoD estimation error remained below 4° for 90% of the measurements, indicating improved real-world performance. Reported positioning errors in the literature range from 3.8 m to 140 m, whereas the 13.2 m error obtained here lies near the midpoint of this range, confirming the practicality of the proposed method in industrial environments. Compared to existing approaches, this work demonstrates high angular accuracy using only sub-6 GHz beams in a realistic industrial scenario without detailed knowledge of antenna beam patterns and channel state. The findings demonstrate that standard 5G signals can provide accurate indoor localization without additional infrastructure, offering a practical path toward cost-effective positioning in industrial IoT and automation. Full article

Productive and healthy soils are essential in agriculture and other economic uses of land which depend on plant growth, and are under increasing pressure globally. The physical properties of soil, its porosity and pore structure, also have a significant impact on a wide range of environmental factors, such as surface water runoff and greenhouse gas exchange. Methods exist for evaluating soil porosity that are applied in a laboratory environment or by inserting sensors into soil in the field. However, such methods do not readily sample adequately in space or time and are labour-intensive. The purpose of the current study is to investigate the potential for estimation of soil porosity and pore size using the strength of reflection of audio pulses from natural soil surfaces. Estimation of porous material properties using acoustic reflections is well established. But because of the complex, viscous interactions between sound waves and pore structures, these methods are generally restricted to transmissions at low audio frequencies or at ultrasonic frequencies. In contrast, this study presents a novel design for an integrated broad band sensing system, which is compact, inexpensive, and which is capable of rapid, non-contact, and in situ sampling of a soil structure from a small, moving, farm vehicle. The new system is shown to have the capability of obtaining soil parameter estimates at sampling distances of less than 1 m and with accuracies of around 1%. In describing this novel design, special care is taken to consider the challenges presented by real agriculture soils. These challenges include the pasture, through which the sound must penetrate without significant losses, and soil roughness, which can potentially scatter sound away from the specular reflection path. The key to this new integrated acoustic design is an extension of an existing theory for acoustic interactions with porous materials and rigorous testing of assumptions via simulations. A configuration is suggested and tested, comprising seven audio frequencies and three angles of incidence. It is concluded that a practical, new operational tool of similar design should be readily manufactured. This tool would be inexpensive, compact, low-power, and non-intrusive to either the soil or the surrounding environment. Audio processing can be conducted within the scope of, say, mobile phones. The practical application is to be able to easily map regions of an agricultural space in some detail and to use that to guide land treatment and mitigation. Full article

Cardiovascular disease (CVD) remains the leading cause of global mortality, highlighting the need for continuous vital sign monitoring. Photoplethysmography (PPG) is well suited for wearable devices. Smart rings, benefiting from dense capillary distribution and minimal tissue interference, can capture high-quality PPG signals with comfort, making them a promising next-generation wearable. However, ring rotation relative to the finger alters the optical path, especially for multi-wavelength light, thus reducing accuracy. This paper proposes a rotation-robust PPG sensor for smart rings. Monte Carlo simulations analyze photon transmission under different LED–photodiode (PD) angles, showing that at ±60°, green, red, and infrared light achieve optimal penetration into the microcirculation layer. Considering non-ideal conditions, the green-light angle is adjusted to ±30°, and a symmetrical sensor design is adopted. A prototype smart ring is developed, capable of recording 4-channel PPG, 3-axis acceleration, and 4-channel temperature signals at 100, 25, and 0.2 Hz, respectively. The system achieves reliable PPG acquisition with only 0.59 mA average current consumption. In continuous testing, heart rate estimation reached mean absolute errors of 0.82, 0.79, and 0.78 bpm for green, red, and IR light. The results provide a reference for future smart ring development. Full article

For the combination of finite elements and control circuits, the calculation is complex and time-consuming, making direct optimization impractical. In this paper, a new distributed node and magnetic circuit model is proposed to simulate the spatial and temporal variation of the distributed air-gap magnetic density with the current and rotor angle and solve the electromagnetic force wave variation. Compared to other distributed flux-linkage models, the proposed model not only considers the radial magnetic path but also connects adjacent magnetic paths tangentially. The inclusion of this tangential path enhances the mutual interaction between magnetic circuits, leading to a more accurate model. Based on the control circuit model, the electromagnetic force wave changes caused by the harmonic currents under various circuits and operating conditions are calculated, the topology is analyzed and optimized to mitigate critical harmonics, the electromagnetic force wave is reduced, and finally, the model accuracy is verified experimentally. While most distributed flux-linkage models are applied to the optimization of motor performance metrics such as the magnetomotive force (MMF), power, and torque, this paper applies the model to the optimization of the magnetic field strength, the harmonic content, and the corresponding noise, vibration, and harshness (NVH), demonstrating a broader range of applications. This method can be coupled with the control circuit to analyze the changes in electromagnetic force waves and quickly optimize them, improving the accuracy and efficiency of research and development. Full article