Search Results (1,441)

The use of millimeter-wave spectrum in fifth-generation (5G) systems is increasing the need for accurate prediction of received power and coverage in real deployment scenarios. In this context, ray tracing (RT) is a promising approach for site-specific analysis, although its reliability depends on how accurately different tools reproduce measurements in complex urban environments. This work presents a comparative assessment at 27 GHz of three RT tools: in-house Exact tool based on Vertical Plane Launching (VPL), Matlab 5G and open-source Sionna RT based on Shooting and Bouncing Rays (SBR). The comparison relies on a large outdoor walk-test campaign, including about 14,725 measurement points collected in a real urban area around a 27 GHz mMIMO base station, using real operator-provided antenna radiation patterns. Measured and simulated power levels are compared using statistical metrics, including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and a planning-oriented coverage-rate metric. The results show a reasonable agreement between simulations and measurements, with RMSE and MAE values around 10–12 dB, highlighting tool-specific behaviors related to boundary effects, interaction modeling, and high-power overestimation. This work confirms that RT is a flexible support for 5G preliminary network design, reducing the need for extensive drive tests. Full article

Waste electronic components are valuable secondary resources containing various metals. Analyzing their elemental distribution is crucial for developing recycling methods. Micro- X-ray fluorescence (μ-XRF) is commonly used for this purpose, but traditional polychromatic X-ray excitation creates high background scattering. This masks trace element signals, impairing detection limits and accurate identification of minor valuable or hazardous elements. To address this, this study developed a monochromatic μ-XRF spectrometer using a low-power molybdenum-target X-ray tube. The system integrates polycapillary lenses for X-ray regulation and a flat crystal for monochromatization, producing a micron-sized monochromatic X-ray spot with high power density. This design eliminates scattered background from the primary continuous spectrum and enhances excitation efficiency by concentrating photon flux, enabling high-brightness monochromatic beams even at low tube power. The spectrometer was validated by analyzing a waste printed circuit board. High-resolution elemental mapping successfully revealed clear distribution patterns of major elements like copper, nickel, and iron, consistent with their physical structures. These images allowed intuitive differentiation of compositional differences across functional regions. This technique effectively overcomes the background interference caused by polychromatic excitation and is expected to further enhance the quality and reliability of elemental distribution imaging. It provides a powerful tool for formulating precise, scientific recycling strategies for waste electronics. Full article

The design of volume holographic gratings (VHGs) is traditionally based on monochromatic plane waves. However, practical applications often involve light sources with broad wavelength bandwidths and certain emission areas, such as LEDs and MiniLEDs, which cause significant Bragg mismatch and degrade diffraction efficiency. To address this fundamental challenge, this paper proposes a novel, to the best of our knowledge, genetic algorithm (GA)-based optimization method for VHG design. A ray-tracing analysis model that fully incorporates the spectral and spatial characteristics of extended broadband sources is established. The GA optimizes the grating fabrication angles by minimizing a fitness function defined as the residual energy after diffraction, thereby achieving optimal performance under non-ideal illumination conditions. The effectiveness of the proposed method is demonstrated through a case study: suppressing the high-intensity central beam in an ultra-thin MiniLED backlight module (BLM). Simulation and experimental results show that the GA-optimized VHG significantly reduces the peak irradiance from 5.01 W/cm² to 4.14 W/cm² at an optical distance (OD) of 0.5 mm. This work provides a robust and source-adaptive design methodology for VHGs, with potential applications extending beyond backlighting to areas such as augmented reality, holographic displays, and optical communications. Full article

This study implemented and validated View Factor (VF) and Ray Tracing (RT) simulation models against four-season field-measured data to evaluate the accuracy of energy yield prediction in bifacial PV systems under three installation configurations: (1) Single-row tilted, (2) Multi-row tilted, and (3) Vertical East–West facing. Front-side and rear-side irradiance and electrical energy yield were evaluated using nRMSE and nMBE metrics, and the relationship between irradiance component ratios (direct, diffuse, reflected) derived from RT results and error trends was analyzed. For front-side irradiance prediction, VF and RT methods showed similar performance in Single-row tilted and Multi-row tilted systems (nRMSE difference within 1 percentage point), while the RT method generally showed lower error than the VF method for rear-side irradiance prediction across the evaluated systems. Notably, in the Multi-row tilted system with high structural complexity, RT achieved nRMSE of 13.3%, which was 14.4 percentage points lower than VF (27.7%). Critically, the performance difference between the two methods was maximized under diffuse-dominant conditions. During shaded periods of the Vertical East–West facing system (diffuse ratio 76–81%), VF method’s nRMSE increased to 14.1–33.5%, while RT method maintained a stable level of 8.8–14.3%. This difference is likely related to differences in diffuse-radiation treatment between the two approaches, including the anisotropic sky representation used in the RT workflow and simplified assumptions in the VF-based rear-side model. In the temporal resolution analysis, the 1 h interval showed the lowest nRMSE for cumulative energy prediction, while the 5 min interval more accurately reproduced peak timing and rapid power fluctuations. This study suggests that the RT method can improve rear-side irradiance prediction accuracy, particularly under conditions of increased structural complexity and higher diffuse radiation ratios. It also indicates that simulation temporal resolution should be selected according to research objectives, such as long-term energy yield estimation or short-term power fluctuation analysis. Full article

Pulse repetition frequency (PRF) controls pulse off-time and, therefore, the extent of thermal accumulation, melt expulsion, and dielectric recovery in finishing electrical discharge machining (EDM). This study clarifies how PRF modifies crater evolution and surface integrity in finishing EDM of 4Cr13 martensitic stainless steel, a corrosion-resistant mold steel used in precision dies and molds. A 2D axisymmetric electro-thermo-fluid model was established in COMSOL, where Gaussian current density, heat-flux, and plasma pressure were periodically imposed at PRFs of 25–100 kHz, while pulse-on time (6 μs) and peak current (8 A) were kept constant. The simulations tracked the transient pressure, heat-flux, velocity, and temperature fields over a common elapsed time of 25 μs. Finishing experiments were then carried out on flat 4Cr13 coupons at 50, 75, and 100 kHz using a copper electrode and deionized water, followed by characterization by laser confocal microscopy, SEM/EDS, and X-ray diffraction using the cosα method. Increasing PRF localized the coupled pressure-heat-flow fields near the crater rim, but shortened off-time and intensified inter-pulse heat accumulation. Accordingly, the surface roughness decreased from Ra = 1.18 μm at 50 kHz to 0.63 μm at 75 kHz, and then slightly increased to 0.71 μm at 100 kHz because of crater overlap, re-melting, and incomplete gap recovery. SEM observations confirmed large irregular craters with cracks at 50 kHz, more uniform fine craters at 75 kHz, and overlapping re-solidified traces at 100 kHz. The residual stress remained compressive for all tested conditions (−341 to −409 MPa). Overall, 75 kHz offers the best compromise between crater uniformity, roughness, and compressive stress for finishing EDM of 4Cr13 steel. Full article

Heating gases to high temperatures is essential for supplying energy to thermal and thermochemical processes. This study presents the optical–thermal design of a mini heliostat field coupled with a tubular solar receiver equipped with second optics, aiming to heat nitrogen to approximately 850 K. The secondary optical system redistributed up to 40% of the incident solar flux from the front to the rear surface of the receiver, improving radial temperature uniformity and significantly reducing thermal gradients along the tube wall. An overall optical efficiency of 65.25% was achieved, accounting for atmospheric attenuation, shading, blocking, and the cosine effect. A coupled computational model was developed by solving the conservation equations of mass, momentum, and energy, with the spatially resolved solar flux distribution obtained via ray tracing used as a thermal boundary condition. The simulation results, validated with an empirical correlation, include solar flux contours, nitrogen temperature distributions, surface temperatures, and heat transfer coefficients. The configuration with a 12 mm vertex spacing between secondary reflectors demonstrated the best thermal performance, reducing the maximum tube surface temperature by 11% and improving radial symmetry, while maintaining nitrogen outlet temperatures near the design target of 850 K. These results confirm the suitability of the system for high-temperature applications such as solar pyrolysis using nitrogen as the heat transfer fluid to deliver the required thermal energy. Full article

This paper investigates the quality of mobile network coverage along the Riga–Tukums railway corridor with a focus on the performance of 4G and 5G technologies. Ensuring reliable mobile connectivity along suburban railway corridors remains a significant technical challenge due to mixed forest–urban propagation conditions, macro-cell-dominated LTE infrastructure, mobility-induced channel variability, and fluctuating passenger density. Unlike high-speed railway environments that are extensively studied in dedicated 5G-R scenarios, suburban railway systems often rely on existing macro-cell deployments, where coverage continuity, signal quality stability, and capacity constraints must be addressed simultaneously. This study presents a measurement-based evaluation of 4G and 5G radio performance along the Riga–Tukums railway corridor under real operational conditions (50–90 km/h). Classical propagation models (Okumura–Hata and COST231-Hata) are quantitatively validated using MAE and RMSE metrics, followed by correlation analysis between RSSNR and QoS indicators. A theoretical Doppler sensitivity assessment (80–200 km/h) is conducted to evaluate mobility robustness across LTE and 5G frequency bands. Mobility transition regions and handover-related time windows are geometrically estimated, and passenger density-based capacity modeling is applied to assess throughput degradation under peak occupancy scenarios. Based on these results, a multi-layer network planning strategy integrating 700 MHz macro coverage, 1700 MHz capacity enhancement, and 3500 MHz 5G NR deployment is proposed. The optimization strategy resulted in an estimated 22–28% increase in stable service coverage in previously weak-signal zones and demonstrated that propagation model deviations remain within ranges comparable to recent railway studies (≈15–25 dB RMSE). These findings provide a structured framework for suburban railway communication optimization and support the gradual modernization of railway infrastructure toward FRMCS-ready architectures. The study illustrates the applicability of modern modelling tools for assessing and improving mobile communication systems and contributes to the broader development of digital infrastructure within Latvia’s transport sector. Full article

Accurate modeling of outdoor wireless propagation in dense urban environments is essential for smart city connectivity. Deterministic ray-tracing techniques provide high-fidelity multipath insight; however they suffer from high computational cost and limited scalability in large 3D environments. This work proposes a hybrid framework combining MATLAB-based (MATLAB 2024b 24.2.0.2773142, 64-bit, 22 October 2024) ray tracing and Machine Learning for scalable Wi-Fi 7 channel analysis. A large dataset is generated over a realistic university campus across multiple frequency bands, transmit powers, and reflection/diffraction configurations. Several regression models are evaluated, with emphasis on transformer-based architectures. The FT-Transformer achieves a Mean Absolute Error (MAE) of $3.49$ dB, RMSE of $5.36$ dB, and an $R^2$ of $99.63\%$ for validation, reducing computation time from months of simulation to seconds at inference. The framework enables accurate and efficient surrogate modeling for network planning and digital twin applications. Full article

Both the Lower Silurian Longmaxi Formation and the Upper Permian Dalong Formation shales in southern China are organic-rich with well-developed nanoscale reservoir pores, demonstrating significant shale gas exploration potential. However, the current lack of in-depth research on the differential depositional and reservoir evolution characteristics of these two shale sequences has left the main controlling factors of the reservoirs unclear, thereby constraining breakthroughs in shale gas development. Focusing on the Longmaxi and Dalong formation shales in the Sichuan Basin, this study employed various analytical methods, including major and trace element analyses, X-ray diffraction (XRD), high-pressure mercury intrusion (HPMI), nitrogen adsorption, CO₂ adsorption, and scanning electron microscopy (SEM). Investigations into the depositional paleoenvironment, paleoproductivity, organic matter enrichment, and microscopic difference mechanisms of nanoscale reservoirs reveal that the Longmaxi Formation shale represents a passive continental margin shelf facies. It is characterized by strong terrigenous input, a predominance of quartz and clay minerals, and consists mainly of siliceous and argillaceous shale facies with high organic matter abundance. In contrast, the Dalong Formation shale was deposited in an intra-platform basin under the influence of intra-platform rifting. It features weak terrigenous input, highly reducing conditions, and strong paleoproductivity. Dominated by quartz and carbonate minerals, its lithofacies are primarily siliceous and calcareous shales. Within the Dalong Formation, the diagenetic dissolution of carbonate minerals promotes the development of micrometer-scale pores larger than 100 μm, while the extensive thermal evolution of organic matter fosters the formation of honeycomb- and embayment-like nanoscale micropores and mesopores, rendering it a relatively superior shale reservoir. Ultimately, the high-TOC shales in the lower part of the Longmaxi Formation and the upper part of the Dalong Formation are identified as the primary sweet spot intervals for future shale gas development. Full article

Wood ash from biomass power plants and coarse, low-grade sheep wool from farming are underutilized biowastes that are often landfilled. Their valorization could reduce waste and emissions, decrease reliance on virgin materials, and support the circular economy and European Green Deal targets. However, both materials may contain naturally occurring radionuclides, primarily ⁴⁰K, as well as trace uranium and thorium isotopes, with higher concentrations typically found in wood ash due to combustion processes. Assessing their activity concentrations and bioavailability is therefore essential to ensure regulatory compliance and protect public health. This study quantified radionuclide levels in wood ash and sheep wool samples collected in Croatia and evaluated their suitability for agricultural applications. Natural radionuclides (⁴⁰K, ²³²Th, ²³⁸U, ²¹⁴Pb, ²¹⁴Bi, ²²⁶Ra, ²¹⁰Pb, ²¹⁰Po) and ¹³⁷Cs were determined using high-resolution gamma-ray and alpha spectrometry. The influence of different factors on radionuclide content was discussed, and transfer factors within the soil–hay–wool pathway were calculated to assess bioavailability. Measured activity concentrations were consistently low, and transfer factors indicated minimal radionuclide mobility. The results support the safe agricultural reuse of these materials and provide baseline data for radiological safety assessments in sustainable waste management practices. Full article

Prompt 3D mapping of grain storage is essential for effective management. However, standard mapping algorithms encounter a number of challenges, with the typical granary environment containing dust, grain piles, and narrow aisles. A single robotic agent is not able to provide complete area coverage, and most multi-robot approaches involve re-scanning the same areas due to a lack of explicit viewpoint-based task allocation processes. In order to overcome the above issues, we propose an air–ground collaborative exploration system for complex multi-grain pile scenarios. Exploration redundancy can be reduced by estimating the advantages of viewpoints through ray tracing and assigning the tops of the grain piles to aerial robots with ground vehicles in lower regions and narrow aisles. In order to manage dense dust (5–15 mg/m³), the quality-aware fusion strategy evaluates the reliability of the distance and point density of the sensing to reduce the influence of degraded aerial depth data. Moreover, mapping relies on LiDAR data to ensure mapping quality. A mechanism for re-scanning to enable coverage-driven exploitation of insufficiently explored regions is subsequently proposed. The simulation results show that the design achieved a grain pile coverage of 97.2%, with the total exploration time reduced by 20.1% over single-robot baselines. The results indicate that viewpoint-aware task allocation and dust-sensitive perception fusion can offer a practical solution for autonomous inspection in GPS-restricted, dust-rich industrial environments, such as granary facilities. Full article

The growing demand for offshore oil and gas production in deep waters has motivated the development of technologies to enable the continuous, reliable, and cost-effective monitoring of subsea equipment. Traditional inspection techniques rely on ROVs and AUVs, leading to delays between data acquisition and recovery and high operational costs. Underwater acoustic communication systems represent an attractive alternative for transmitting monitoring data to the surface in real time. This work evaluates the feasibility of implementing an underwater acoustic communication link for data transmission in deep-water environments, considering environmental conditions and acoustic channel characteristics. Using the BELLHOP ray-tracing model, simulations were performed to predict transmission loss, multipath effects, ambient noise, and the resulting signal-to-noise ratio (SNR) for different modem configurations and operating frequencies. The results demonstrate that the performance of the underwater link is strongly dependent on frequency, distance, and environmental variability. The study identifies optimal frequency–range relationships, quantifies the limitations imposed by transmission loss and ambient noise, and provides guidance for selecting acoustic modem parameters for real subsea monitoring applications. The SNR for three modem models operating at different frequencies illustrates the signal detection capability in the marine environment. The differences between modems A, B, and C are defined by their technical specifications and how they perform within the underwater acoustic channel of the Campos Basin. The data transmission capacity is supported by the data rates provided by the analyzed modems. The low frequencies of modem A (9.75 kHz) achieve the highest SNR, enabling long-range monitoring. At higher frequencies, modem C (78 kHz) allows short-distance communication. Modem B (35 kHz) offers a good balance between the data rate and power consumption, consuming only 1 W, making it highly viable for monitoring systems that rely on batteries and require long-term operation. The findings support the feasibility of integrating underwater acoustic communication into subsea monitoring architectures, enabling a more efficient oversight of deep-water production systems. The analysis concludes that project viability depends on selecting a system where the SNR and range meet the specific monitoring requirements. Full article

The automotive augmented reality head-up display (AR-HUD) system projects critical driving information directly into the driver’s line of sight, enhancing driving safety, user experience, and navigation efficiency. However, due to the intrinsic asymmetry of vehicle windshields, existing optical configurations are difficult to use as effective design starting points. The asymmetric transmission region of the windshield causes the AR-HUD optical system to deviate significantly from the YOZ plane, increasing the complexity of system design and optimization. To address these challenges, this paper proposes an automated design method for automotive AR-HUD optical systems. Given the windshield geometry and system design specifications, a normal-guided iterative construction method is first employed to generate a high-performance initial optical structure with low distortion. Subsequently, differentiable ray tracing combined with optimization algorithms is employed to further improve system performance. Based on the proposed method, an AR-HUD optical system with a 130 mm × 50 mm eye-box and a 13° × 4° field of view was designed. The design results indicate that the maximum optical distortion is 0.51%. At five sampled eye positions within the eye-box, the MTF exceeds 0.5 at the spatial frequency of 6 lp/mm, and the dynamic distortion remains below 5.36′. Finally, a complete experimental prototype was established, and the experimental results verified the feasibility and effectiveness of the proposed automated design method. Full article

Polarized side-scattering techniques are widely used in aerosol detection, oceanographic optics, and biomedical sensing due to their high sensitivity to weak optical signals in low-scattering coefficient media. Conventional polarized Monte Carlo methods face significant challenges in such regimes due to geometric mismatch, where photon exit positions deviate substantially from the detector plane. This study addresses the geometric mismatch issue in polarized Monte Carlo simulations for side scattering in low-scattering media (scattering coefficient ${\mu }_s=$ 1 cm⁻¹), where photon exit positions often deviate from the detector plane. We propose a novel algorithm incorporating backward ray tracing with geometric projection correction to enhance simulation accuracy. Experimental validation was conducted using 532 nm laser illumination on both 500 nm polystyrene microspheres (${\mu }_s=$ 0.21 cm⁻¹) and 5 nm TiO₂ nanoparticles (${\mu }_s=$ 1.06 × 10⁻⁶–1.06 × 10⁻⁵ cm⁻¹). The results demonstrate excellent agreement between simulations and experiments, confirming the algorithm’s capability to accurately capture the polarization characteristics of side-scattered light. This work provides a high-fidelity simulation tool for designing optical sensors in low-scattering media and holds direct applicability in nanoparticle concentration sensing and aerosol monitoring. Full article

Virtual plant models combined with ray-tracing simulations are an established tool for evaluating plant–light interactions. Current approaches often simplify leaf surface properties by assuming diffuse reflectance behavior, despite experimental evidence that leaf reflectance is direction-dependent across much of the visible spectrum. This study investigates whether incorporating measured, spectrally resolved and direction-dependent (BRDF) reflectance properties into these models affects simulation outcomes. Using virtual 3D cucumber (Cucumis sativus) plant models with PhongShader-based optical leaf characteristics for BRDF consideration, light absorption and local photon flux densities were simulated under a wide range of lighting conditions, including diffuse and directed sunlight scenarios. While total light absorption at the leaf level is only marginally affected (mean absolute percentage error, MAPE < 2%), spectral distortions in leaf surroundings, especially under direct light, exceeded 8% in the blue wavelength range. Beyond their relevance for estimating photosynthetic rates, such distortions directly affect the spectral composition within the canopy, which is particularly critical in greenhouse applications where optical sensors are used to monitor spectral ratios and, therefore, require the accurate prior simulation of canopy light conditions. This is particularly relevant for setups with directional artificial lighting. The findings suggest that BRDF modeling is not critical for calculating photosynthetic rates under most conditions, but is required in spectral analyses or for optimizing artificial lighting designs. Full article