Search Results (2,188)

A square patch metasurface is designed, simulated, fabricated, and experimentally tested to investigate polarization characteristics quantitatively. The metasurface consists of one layer unit cell in the form of a square patch with one via and a lumped resistor, which is used for harvesting RF (radio frequency) energy. FR4 dielectric is used as a substrate supported by a metal ground plane. Polarization-dependent properties with specific surface current patterns and voltage dip are obtained when simulating under normal incidence of a plane wave. This characteristic results from changes in surface current conditions when the polarization angle is varied. A voltage dip appears at a specific polarization angle when the surface current pattern is symmetrical. This condition occurs when the position of the lumped resistor from the center of the patch is perpendicular to the linearly polarized incident electric field. A couple of 10 × 10 arrays with different resistor positions are fabricated and tested. The experimental results are in good agreement with the simulated results. The proposed design demonstrates a symmetric unit cell structure with one via and a resistor that exhibits polarization-dependent behavior for linear polarization. An asymmetric patch design is explored through both simulation and measurement to mitigate polarization dependence by suppressing the dip behavior, albeit at the expense of reduced absorption efficiency. This study provides a complete polarization analysis for both symmetric and asymmetric patch metasurfaces with a single via and a single lumped resistor, and introduces a predictive relation between the position of the resistor relative to the center of the patch and the resulting voltage dip behavior. Full article

Over three decades of research has been undertaken on point cloud registration algorithms, resulting in mature theoretical frameworks and methodologies. However, among the numerous registration techniques used, the impact of point cloud scanning quality on registration outcomes has rarely been addressed. In most engineering and industrial measurement applications, the accuracy and density of LiDAR point clouds are highly dependent on laser scanners, leading to significant variability that critically affects registration quality. Key factors influencing point cloud accuracy include scanning distance, incidence angle, and the surface characteristics of the target. Notably, in short-range scanning scenarios, incidence angle emerges as the dominant error source. Building on this insight, this study systematically investigates the relationship between scanning incidence angles and point cloud quality. We propose an incident-angle-dependent weighting function for point cloud observations, and further develop an improved weighted Iterative Closest Point (ICP) registration algorithm. Experimental results demonstrate that the proposed method achieves approximately 30% higher registration accuracy compared to traditional ICP algorithms and a 10% improvement over Faro SCENE’s proprietary solution. Full article

We investigate the temperature evolution in the three-dimensional skin tissue exposed to a millimeter-wave electromagnetic beam that is not necessarily perpendicular to the skin surface. This study examines the effect of the beam’s incident angle. The incident angle influences the thermal heating in two aspects: (i) the beam spot projected onto the skin is elongated compared to the intrinsic beam spot in a perpendicular cross-section, resulting in a lower power per skin area; and (ii) inside the tissue, the beam propagates at the refracted angle relative to the depth direction. At millimeter-wavelength frequencies, the characteristic penetration depth is sub-millimeter, whereas the lateral extent of the beam spans at least several centimeters in applications. We explore the small ratio of the penetration depth to the lateral length scale in a nondimensional formulation and derive a leading-term asymptotic solution for the temperature distribution. This analysis does not rely on a small incident angle and is therefore applicable to arbitrary angles of incidence. Based on the asymptotic solution, we establish scaling laws for the three-dimensional skin temperature, the skin surface temperature, and the skin volume in which thermal nociceptors are activated. Full article

Forest structure parameters are critical for understanding and managing forest ecosystems, yet sparse forests have received limited attention in previous studies. To address this research gap, this study systematically evaluates and compares the sensitivity of active Synthetic Aperture Radar (SAR) and passive optical remote sensing to key forest structure parameters in sparse forests, including Diameter at Breast Height (DBH), Tree Height (H), Crown Width (CW), and Leaf Area Index (LAI). Using the novel computer-graphics-based radiosity model applicable to porous individual thin objects, named Radiosity Applicable to Porous Individual Objects (RAPID), we simulated 38 distinct sparse forest scenarios to generate both SAR backscatter coefficients and optical reflectance across various wavelengths, polarization modes, and incidence/observation angles. Sensitivity was assessed using the coefficient of variation (CV). The results reveal that C-band SAR in HH polarization mode demonstrates the highest sensitivity to DBH (CV = −6.73%), H (CV = −52.68%), and LAI (CV = −63.39%), while optical data in the red band show the strongest response to CW (CV = 18.83%) variations. The study further identifies optimal acquisition configurations, with SAR data achieving maximum sensitivity at smaller incidence angles and optical reflectance performing best at forward observation angles. This study addresses a critical gap by presenting the first systematic comparison of the sensitivity of multi-band SAR and VIS/NIR data to key forest structural parameters across sparsity gradients, thereby clarifying their applicability for monitoring young and middle-aged sparse forests with high carbon sequestration potential. Full article

The efficiency decline of Francis turbines, a key component of hydroelectric power generation, presents a multifaceted challenge influenced by interconnected factors such as water quality, incidence angle, erosion, and runner wear. This paper is structured into two main sections to address these issues. The first section applies the Buckingham π theorem to establish a dimensional analysis (DA) framework, providing insights into the relationships among the operational variables and their impact on turbine wear and efficiency loss. Dimensional analysis offers a theoretical basis for understanding the relationships among operational variables and efficiency within the scope of this study. This understanding, in turn, informs the selection and interpretation of features for machine learning (ML) models aimed at the predictive maintenance of the target variable and important features for the next stage. The second section analyzes an extensive dataset collected from a Francis turbine in Colombia, a country that is heavily reliant on hydroelectric power. The dataset consisted of 60,501 samples recorded over 15 days, offering a robust basis for assessing turbine behavior under real-world operating conditions. An exploratory data analysis (EDA) was conducted by integrating linear regression and a time-series analysis to investigate efficiency dynamics. Key variables, including power output, water flow rate, and operational time, were extracted and analyzed to identify patterns and correlations affecting turbine performance. This study seeks to develop a comprehensive understanding of the factors driving Francis turbine efficiency loss and to propose strategies for mitigating wear-induced performance degradation. The synergy lies in DA’s ability to reduce dimensionality and identify meaningful features, which enhances the ML models’ interpretability, while ML leverages these features to model non-linear and time-dependent patterns that DA alone cannot address. This integrated approach results in a linear regression model with a performance (R²-Test = 0.994) and a time series using ARIMA with a performance (R²-Test = 0.999) that allows for the identification of better generalization, demonstrating the power of combining physical principles with advanced data analysis. The preliminary findings provide valuable insights into the dynamic interplay of operational parameters, contributing to the optimization of turbine operation, efficiency enhancement, and lifespan extension. Ultimately, this study supports the sustainability and economic viability of hydroelectric power generation by advancing tools for predictive maintenance and performance optimization. Full article

Nonlinear photocurrents (NPs) are electrical currents expected to be measured at the electrodes of a device consisting of an active area, sensitive to light, with a higher-order in-electric field where light-impinging geometry (LIG) is the determining factor in the experimental observation. Although the phenomenology of this light–matter interaction is clear for light directed on a lateral device plane with well-defined azimuthal and incidence angles, as well as light polarization angle, it can be quite complicated for a vertical device structure and reconsideration of the expected NP contributions is necessary in the latter case. In this study, we used a visual approach to describe the LIG for vertical device structures using a specific example of a photodiode, and showed that these angles must be redefined, namely, the interchangeability of azimuthal and incidence angles. The influence of device geometry-dependent optical illumination is reflected on the behavior of NP; therefore, the NPs that are known to be forbidden in certain LIGs can be allowed and vice versa. These results pave the way for the utilization of NPs in flexible optoelectronic applications. Full article

Ubiquitous digital array radar (UDAR) extends the integration time of moving targets by deploying a wide transmitting beam and multiple narrow receiving beams to cover the entire observed airspace. By exchanging time for energy, it effectively improves the detection ability for weak targets. Nevertheless, target motion introduces severe across-range unit (ARU), across-Doppler unit (ADU), and across-beam unit (ABU) effects, dispersing target energy across the range–Doppler-beam space. This paper proposes a beam domain angle rotation compensation and keystone-matched filtering (BARC-KTMF) algorithm to address the “three-crossing” challenge. This algorithm first corrects ABU by rotating beam–domain coordinates to align scattered energy into the final beam unit, reshaping the signal distribution pattern. Then, the KTMF method is utilized to focus target energy in the time-frequency domain. Furthermore, a special spatial windowing technique is developed to improve computational efficiency through parallel block processing. Simulation results show that the proposed approach achieves an excellent signal-to-noise ratio (SNR) gain over the typical single-beam and multi-beam long-time coherent integration (LTCI) methods under low SNR conditions. Additionally, the presented algorithm also has the capability of coarse estimation for the target incident angle. This work extends the LTCI technique to the beam domain, offering a robust framework for high-speed weak target detection. Full article

To improve environmental sustainability and operational safety in maritime industries, the development of efficient methods for removing biofouling from submerged surfaces is critical. This study investigates the erosion mechanisms of cavitation jets as a non-contact, high-efficiency method for detaching marine organisms, including bacteria and larvae, from ship hulls and underwater infrastructure. Through erosion experiments on coated specimens, variations in jet morphology, and flow visualization using the Schlieren method, we examined how factors such as jet incident angle and nozzle configuration influence removal performance. The results reveal that erosion occurs not only at the direct jet impact zone but also in regions where cavitation bubbles exhibit intense motion, driven by pressure fluctuations and shock waves. Notably, single-hole jets with longer potential cores produced more concentrated erosion, while multi-jet interference enhanced bubble activity. These findings underscore the importance of understanding bubble distribution dynamics in the flow field and provide insight into optimizing cavitation jet configurations to expand the effective cleaning area while minimizing material damage. This study contributes to advancing biofouling removal technologies that promote safer and more sustainable maritime operations. Full article

We propose a single-phase chiral elastic metamaterial capable of simultaneously exhibiting negative effective mass density and negative bulk modulus in the ultrasonic frequency range. The unit cell consists of a regular hexagonal frame connected to a central circular mass through six obliquely oriented, slender aluminum beams. The design avoids the manufacturing complexity of multi-phase systems by relying solely on geometric topology and chirality to induce dipolar and rotational resonances. Dispersion analysis and effective parameter retrieval confirm a double-negative frequency region from 30.9 kHz to 34 kHz. Finite element simulations further demonstrate negative refraction behavior when the metamaterial is immersed in water and subjected to 32 kHz and 32.7 kHz incident plane wave. Equifrequency curves (EFCs) analysis shows excellent agreement with simulated refraction angles, validating the material’s double-negative performance. This study provides a robust, manufacturable platform for elastic wave manipulation using a single-phase metallic metamaterial design. Full article

In classic all-dielectric one-dimensional photonic crystals, transparent bands exhibit strong angular dispersion. Herein, we realize an angle-dispersion-free near-infrared transparent band in a one-dimensional photonic hypercrystal containing hyperbola-dispersion metamaterials. As the incident angle increases from 0° to 80°, the relative shifts of the wavelengths of four transmittance peaks within the transparent band are smaller than 1.5% and the bandwidth of the transparent band marginally fluctuates from 1098.2 to 1132.5 nm. Particularly, the angle-dispersion-free property of the transparent band is quite robust with respect to the layer thickness disturbance. Our work not only offers a viable method of achieving angle-dispersion-free transparent bands but also facilitates the development of transparency-based optical devices. Full article

Low-altitude drones, which are unimpeded by traffic congestion or urban terrain, have become a critical asset in emergency rescue missions. To address the current lack of emergency rescue data, UAV aerial videos were collected to create an experimental dataset for action classification and localization annotation. A total of 5082 keyframes were labeled with 1–5 targets each, and 14,412 instances of data were prepared (including flight altitude and camera angles) for action classification and position annotation. To mitigate the challenges posed by high-resolution drone footage with excessive redundant information, we propose the SlowFast-Traffic (SF-T) framework, a spatio-temporal sequence-based algorithm for recognizing traffic accident rescue actions. For more efficient extraction of target–background correlation features, we introduce the Actor-Centric Relation Network (ACRN) module, which employs temporal max pooling to enhance the time-dimensional features of static backgrounds, significantly reducing redundancy-induced interference. Additionally, smaller ROI feature map outputs are adopted to boost computational speed. To tackle class imbalance in incident samples, we integrate a Class-Balanced Focal Loss (CB-Focal Loss) function, effectively resolving rare-action recognition in specific rescue scenarios. We replace the original Faster R-CNN with YOLOX-s to improve the target detection rate. On our proposed dataset, the SF-T model achieves a mean average precision (mAP) of 83.9%, which is 8.5% higher than that of the standard SlowFast architecture while maintaining a processing speed of 34.9 tasks/s. Both accuracy-related metrics and computational efficiency are substantially improved. The proposed method demonstrates strong robustness and real-time analysis capabilities for modern traffic rescue action recognition. Full article

To meet the requirements for radar echo acquisition and feature extraction from stratified media and rough-surfaced targets, a vehicle was geometrically modelled in CAD. Monte Carlo techniques were applied to generate the rough interfaces at air–snow and snow–soil boundaries and over the vehicle surface. Soil complex permittivity was characterized with a four-component mixture model, while snow permittivity was described using a mixed-media dielectric model. The composite electromagnetic scattering from a rough-surfaced vehicle on snow-covered soil was then analyzed with the finite-difference time-domain (FDTD) method. Parametric studies examined how incident angle and frequency, vehicle orientation, vehicle surface root mean square (RMS) height, snow liquid water content and depth, and soil moisture influence the composite scattering coefficient. Results indicate that the coefficient oscillates with scattering angle, producing specular reflection lobes; it increases monotonically with larger incident angles, higher frequencies, greater vehicle RMS roughness, and higher snow liquid water content. By contrast, its dependence on snow thickness, vehicle orientation, and soil moisture is complex and shows no clear trend. Full article

The proliferation of electromagnetic wave applications has accentuated electromagnetic pollution concerns, highlighting the critical importance of electromagnetic wave absorbers (EMA). This study proposes innovative I-Wrapped Package Lattice electromagnetic wave absorbers (IWP–EMA) based on the triply periodic minimal surface (TPMS) lattice structure. Through a rational design of porous gradient structures, broadband wave absorption was achieved while maintaining lightweight characteristics and mechanical robustness. The optimized three-dimensional configuration features a 20 mm thick gradient structure with a progressive relative density transition from 10% to 30%. Under normal incidence conditions, this gradient IWP–EMA basically achieves broadband absorption with a reflection loss below −10 dB across the 2–40 GHz frequency band, with absorption peaks below −19 dB, demonstrating good impedance-matching characteristics. Additionally, due to the complex interactions of electromagnetic waves within the structure, the proposed IWP–EMA achieves a wide-angle absorption range of 70° under Transverse Electric (TE) polarization and 70° under Transverse Magnetic (TM) polarization. The synergistic integration of the TPMS design and additive manufacturing technology employed in this study significantly expands the design space and application potential of electromagnetic absorption structures. Full article

In recent years, there has been an increasing transition from 1D point-based to 3D point-cloud-based data acquisition for monitoring applications and deformation analysis tasks. Previously, many studies relied on point-to-point measurements using total stations to assess structural deformation. However, the introduction of terrestrial laser scanning (TLS) has commenced a new era in data capture with a high level of efficiency and flexibility for data collection and post processing. Thus, a robust understanding of both data acquisition and processing techniques is required to guarantee high-quality deliverables to geometrically separate the measurement uncertainty and movements. TLS is highly demanding in capturing detailed 3D point coordinates of a scene within either short- or long-range scanning. Although various studies have examined scanner misalignments under controlled conditions within the short range of observation (scanner calibration), there remains a knowledge gap in understanding and characterizing errors related to long-range scanning (scanning calibration). Furthermore, limited information on manufacturer-oriented calibration tests highlights the motivation for designing a user-oriented calibration test. This research focused on investigating four primary sources of error in the generic error model of TLS. These were categorized into four geometries: instrumental imperfections related to the scanner itself, atmospheric effects that impact the laser beam, scanning geometry concerning the setup and varying incidence angles during scanning, and object and surface characteristics affecting the overall data accuracy. This study presents previous findings of TLS calibration relevant to the four error sources and mitigation strategies and identified current challenges that can be implemented as potential research directions. Full article

A turboprop aircraft is exposed to the risk of bird strikes during flight, which may have a serious impact on flight safety once the bird is sucked into the engine. In this study, the aerodynamic and bird exclusion characteristics of a branched turboprop inlet were tested on a branched turboprop inlet–bird striking experiment system under ground suction conditions. The ingestion processes of the bird were captured by a high-speed camera system. The static pressure at the inner wall of the inlet during the ingestion process was measured. The results indicate that when a low-speed bird at a large incident angle impacts on the wall of the inlet near the lower lip under ground suction conditions, the bird is easily sucked into the core duct. Conversely, it is more likely to be excluded by the bypass duct. Moreover, when the bird moves into the inlet, the static pressure on the wall of the area where it passes through increases significantly. Full article