Search Results (5,587)

Accurately determining the thermal transmittance (U-value) of glazing systems plays a pivotal role in building energy conservation. This study establishes an explicit analytical model and conducts a systematic parametric analysis to elucidate the heat transfer mechanisms and key influencing factors governing the U-values of both single-pane and insulating glass. Based on fundamental thermodynamic principles and blackbody radiation laws, numerical iterative models are developed and validated against WINDOW and Fluent software simulations, with deviations consistently below 3.8%. A comprehensive parametric analysis quantifies the effects of glass thickness, cavity width, surface emissivity, and indoor/outdoor heat transfer coefficients. The results reveal that: (1) while U-values decrease approximately linearly with increasing glass thickness, they exhibit a non-monotonic relationship with cavity width, identifying an optimal cavity width of approximately 16 mm for air-filled insulating glass units; (2) surface emissivity exerts the most significant influence on the U-value, with cavity-facing surfaces demonstrating the greatest sensitivity (up to 81% variation), whereas outdoor surface emissivity shows negligible impact; (3) the U-value displays greater sensitivity to variations in the indoor heat transfer coefficient compared to outdoor conditions. Based on the parametric analysis under standard winter conditions, a preliminary design hierarchy is proposed for energy optimization: prioritize Low-E coatings on cavity surfaces, followed by cavity width optimization near 16 mm, and finally consider increasing glass thickness. The validated models and quantitative insights establish a benchmark calculation method for U-value analysis. These findings offer theoretical guidance and a prioritized optimization pathway for the preliminary design of energy-efficient glazing systems, particularly under standard winter conditions. Full article

Cotton, a globally significant crop grown in over 100 countries, sustains a $40 billion market and provides employment for over 350 million people worldwide. However, plastic contamination remains a persistent challenge within the industry, degrading cotton fiber quality and disrupting ginning. Manual inspection and optical machine-vision systems struggle when plastic fragments are concealed by fibers or lack sufficient color contrast. To address these challenges, we developed an ultrasonic phased-array imaging system operating at 40 kHz under field-programmable gate array (FPGA) control. Transmitter elements emit pulsed ultrasound along radial paths, separate reflection receivers record echo amplitudes to form acoustic images, and a set of transmission receivers captures signal attenuation, which is overlaid onto the reflection-based image to highlight potential contaminants. In preliminary laboratory-based tests on both seed cotton and lint samples, the system successfully detected visually obscured plastic fragments as small as $2\mathrm{cm}\times 2\mathrm{cm}$ with an angular resolution limit of $\pm 3^{\circ }$. Distinct reflection peaks and corresponding attenuation overlays were produced across the field of view, validating the system’s detection capabilities. These results demonstrate the feasibility of using ultrasonic imaging to reveal concealed plastics in cotton processing. Integrating this approach with existing optical methods could enhance contaminant-removal workflows and improve overall fiber quality and processing efficiency. Full article

Reliable underwater acoustic (UWA) communication is fundamental to marine sensing applications, including environmental monitoring, underwater sensor networks, and autonomous platforms, yet remains severely challenged by multipath propagation, Doppler effects, and limited bandwidth. This paper investigates a memory-based multicarrier modulation framework in which controlled phase continuity is introduced at the symbol-mapping stage to enhance robustness against channel-induced distortions. Unlike conventional memoryless multicarrier schemes, the proposed approach embeds intentional phase memory at the transmitter and exploits it at the receiver, improving reliability in highly dispersive underwater environments. A comprehensive bit-error-rate (BER) evaluation is conducted using extensive simulations over realistic shallow-water acoustic channel models. The analysis examines rational modulation indices, pulse-shaping filters, roll-off factors, transmitter–receiver separation distances, and receiver structures. Both matched-filter and zero-forcing receivers are considered to assess trade-offs between interference mitigation and noise amplification. Results demonstrate consistent and significant BER improvements compared with conventional memoryless multicarrier systems. A modulation index of 7/16 achieves the minimum BER with matched-filter detection, while 3/10 yields optimal performance with zero-forcing detection. The Dirichlet pulse provides the most robust performance across operating conditions. These findings establish phase-memory-aware multicarrier design as a practical strategy for reliable underwater sensing and communication systems. Full article

Achieving a balance between accuracy and computational efficiency in solar energy flux estimation models remains a key challenge in atmospheric radiative transfer research. Given the high computational cost of spectral models, a widely used simplification strategy consists of parameterizing atmospheric spectral transmittances through wavelength-averaging formulations. This study introduces a Clear-Sky Multivariable (CSMV) broadband parametric model derived from the Leckner spectral model for estimating the three components of solar irradiance under clear-sky conditions: direct normal irradiance (DNI), diffuse irradiance (Gd), and global irradiance (G). The model development follows a two-stage procedure. First, discrete broadband transmittances are obtained by applying an independent spectral integration scheme to the transmittances of the source spectral model. In the second stage, these discrete values are fitted with analytical functions expressed solely in terms of atmospheric state parameters, yielding wavelength-independent broadband formulations. While the overall development framework follows a classical parameterization approach, the calculation of the diffuse component introduces a novel way of estimating the fraction of aerosol scattering directed toward the ground. The model was tested against data collected from eight radiometric stations distributed across six continents and benchmarked against two well-established reference models. Overall, the results indicate a high level of accuracy and demonstrate the practical applicability of the model. Full article

Wireless sensor networks using battery-powered, low-cost sensors, due to their non-rechargeability and strictly limited energy resources, are more sensitive to energy efficiency than other networks of this type. Clustered wireless sensor networks address this problem. In these networks, the most energy-intensive communication, i.e., a long-range one, is carried out via designated nodes, called cluster head nodes, while other cluster nodes communicate with their cluster heads. Cluster head node selection is handled by appropriate routing protocols, and newly designed protocols are first tested in simulations. Among the simulators of cluster head selection protocols, those implemented in a MATLAB environment play an important role, and among these, those implementing a first-order radio model to estimate the energy cost of transmission, both at the transmitter and at the receiver, play a particularly important role. This paper presents and discusses the energy aspects of MATLAB-based open-source wireless sensor network environments that employ the first-order radio model for the simulation of cluster head selection protocols. Current MATLAB-based open-source simulators of cluster head selection protocols were inventoried and analyzed. The review results showed that the first-order radio model had been used in its classic form for years, with the same default parameters. Although the simulators were written using different programming paradigms, precluding simple copy-and-paste, the first-order radio model was generally similar. However, there were exceptions to this rule. A hard exception is the simulator for a body-area wireless sensor network, which only implements a version of the first-order radio model specific to that environment. Soft exceptions are two simulators of the popular cluster head selection protocol, which implemented only half the functionality of the classic first-order radio model. On the one hand, this demonstrates both the widespread use of a conservative approach to the model, which ensures relatively easy repeatability of simulation results, and, on the other hand, the flexibility of the model, which allows its extension to other environments. Finally, the limitations of the model are presented and directions for future research are indicated. Full article

Heat stress is a major challenge for broiler production worldwide and is expected to intensify with more frequent heatwaves. This study focuses on mechanically ventilated broiler houses in South Korea, where heatwaves have become increasingly frequent. Three regression meta-models were developed to predict the indoor temperature–humidity index (THI) directly from weather forecast data, using simulated results from a validated building energy simulation (BES) model. A TRNSYS-based BES model was validated against field measurements from four rearing cycles in a commercial broiler house (RMSE 1.31–2.16; MAPE < 2.00%). Using 3072 simulation cases that combined multiple sites, thermal-transmittance levels, cooling conditions, building sizes, and broiler body weights, three regression meta-model approaches were evaluated: a condition-specific regression meta-model for each condition set, a unified regression meta-model with categorical predictors, and a single variable meta-model using only external THI as a predictor. All three showed strong predictive performance, and the unified regression meta-model achieved R² = 0.978, RMSE = 0.817, and MAPE = 0.829, providing the best balance between accuracy and simplicity. This unified model offers a practical tool to link weather forecasts with broiler-house design and environmental-control decisions for heat-stress risk management. Full article

In Time Division Duplex (TDD) Direct-Sequence Code Division Multiple Access (DS/CDMA) architectures, Pre-Rake filtering serves as a powerful transmitter-side strategy to alleviate receiver hardware constraints by leveraging channel reciprocity. Nevertheless, rapid channel fluctuations induced by high Doppler spreads critically undermine this reciprocity assumption. This failure is primarily driven by the unavoidable latency between uplink reception and downlink transmission, leading to severe performance deterioration. To address these challenges and enhance system robustness in modern high-speed scenarios, we propose an improved hybrid transceiver architecture. This scheme integrates multiplexed Pre-Rake processing with a Matched Filter-based Rake receiver and employs a Minimum Mean Square Error (MMSE) equalizer to suppress the severe Inter-Symbol Interference (ISI) and Multi-User Interference (MUI). Furthermore, we conduct a comparative analysis of channel estimation methods tailored for a 10 Mbps high-speed transmission environment.Our investigation reveals that while complex quadratic interpolation is often prioritized in low-data-rate studies, simple averaging is sufficient and even superior in high-speed communications. This is because the shortened slot duration allows simple averaging to effectively track channel variations while avoiding the noise overfitting associated with higher-order interpolation. The simulation results demonstrate that the proposed MMSE-optimized architecture achieves superior Bit Error Rate (BER) performance, providing a practical and computationally efficient solution for next-generation mobile networks. Full article

This study employs a TVP-VAR-BK-DY framework to examine volatility spillovers between China’s financial markets and strategic metal assets. To capture retail investor sentiment, we construct a sentiment index using an LLM knowledge distillation framework. Building on this index, the analysis further incorporates economic policy uncertainty to investigate the joint effects of retail investor sentiment and economic policy uncertainty on cross-market volatility spillovers. The results show that: (1) Price movements in certain assets exhibit leading effects, while metals with stronger financial characteristics generate more pronounced spillover effects. (2) The spillover structure between China’s financial markets and strategic metal assets displays substantial heterogeneity across time horizons and frequency bands. In the 1–5-day frequency band, the stock market serves as a net transmitter of volatility to the banking sector, gold, and copper. In the frequency band exceeding five days, these three assets exert reverse net spillover effects on the stock market. (3) The effects of retail investor sentiment and economic policy uncertainty on volatility spillovers differ significantly. The impact of retail investor sentiment is primarily concentrated in the 1–5-day frequency band, whereas economic policy uncertainty exhibits significant spillover effects in the frequency band exceeding six months. Full article

This study presents a deterministic geospatial methodology for the alignment of directional television receiving antennas using publicly available broadcast-sector parameters. The proposed approach relies exclusively on geometric computations derived from user geolocation (WGS84 coordinates) and transmitter site information, including sector azimuth and beamwidth characteristics. By computing the geodesic bearing between receiver and transmitter locations, the method evaluates angular deviation relative to sector orientation and provides an interpretable alignment assessment framework. The methodology operates without requiring empirical signal measurements, propagation modeling, or machine-learning techniques, thereby ensuring transparency, reproducibility, and low computational complexity. The approach is particularly suitable for scenarios where line-of-sight conditions dominate signal propagation. Under such assumptions, the proposed framework offers a lightweight and explainable solution for antenna pointing and orientation guidance while explicitly acknowledging the limitations imposed by simplified geometric modeling. Full article

The building-integrated photovoltaic (BIPV) system has advantages in construction and energy, but due to the use of flammable polymer packaging materials, it introduces complex fire safety-related challenges. Although polymer backboards are traditionally considered to be the main combustible components in photovoltaic modules, recent studies have shown that ethylene–vinyl acetate (EVA) packaging materials play a key role in the development of fires. This study investigated the fire behavior, optical properties and system-level fire effects of montmorillonite (MMT) nano-clay-modified EVA packaging materials. Through the 50 kW/m² conical calorimeter test, optical transmittance measurement and the accelerated aging test, pure EVA and EVA containing 3% MMT were evaluated, and the measured fire parameters were further incorporated into the simplified BIPV cavity fire model. The results show that MMT modification reduces the peak heat release rate of EVA by about 30%, delays the ignition time, and increases the formation of carbides, while maintaining the optical transmittance of more than 88%. At the system level, the reduction in heat release leads to a decrease in the cavity temperature and delays the ignition of adjacent insulation materials. These findings establish a direct link between material-level fire behavior and the fire performance of BIPV systems, indicating that nano-clay-modified EVA is a feasible strategy that can improve the fire safety of BIPV systems integrated into the facade without compromising optical or durability requirements. Full article

Some windowless semiconductor photodiodes can detect not only photons but also charged particles, cover a wide spectral range including a part of the ionizing radiation region and, thus, play important roles for synchrotron radiation experiments. To understand the spectral, angular and polarizing properties of semiconductor photodiodes, complex amplitude coefficients of transmittance or reflectance are calculated based on rigorous formulation using Fresnel equations with complex optical constants of the composing materials, whose validity was verified by comparison with experiments. Concrete examples of the behavior on the complex plane are shown as a function of complex optical constants, film thickness, angle of incidence and the wavelength. The results show that the optical properties of the layered system are sensitive to its layer thickness, the angle of incidence and the wavelength in the ultraviolet region where optical indices of the composing materials steeply change. It has been shown that oblique incidence photodiodes are useful as polarization-sensitive devices, and that the graphical technique using the amplitude coefficients expressed on the complex plane is effective and powerful to search for optimal conditions for complex optical constants, film thickness and/or angle of incidence. Full article

To accurately quantify the intrinsic absorption efficiency of bamboo leaves to the solar spectrum, we measured the reflectance and transmittance of leaves from 55 bamboo species cultivated at the same site, and developed a mathematical model to calculate the annual cumulative photon absorption of photosynthetically active radiation (PAR) per leaf. The results showed the following: (1) Bamboo leaf optical properties exhibited high instrumental and spatial measurement consistency, with transmittance not significantly fluctuating with changes in incident light intensity or quality. (2) Bamboo leaves exhibited significant spectral selective absorption characteristics, with stronger absorption of blue and red light and weaker absorption of green light; Phyllostachys vivax had the highest mean absorptance per unit area, while Chimonobambusa tumidinoda had the lowest. (3) The annual photon absorption per unit leaf area ranged from 1.83 × 10⁵ to 9.86 × 10⁵ μmol, with Phyllostachys iridescens being the lowest and Chimonobambusa marmorea the highest. The annual photon absorption per single leaf ranged from 1.84 × 10⁶ to 5.13 × 10⁷ μmol, with Indocalamus decorus achieving the highest total absorption due to its largest leaf area (114.9 cm²), while Bambusa multiplex var. riviereorum was the lowest. (4) All tested bamboo species showed consistent seasonal dynamics in photon absorption, with the highest in summer and lowest in winter. Although unit-area absorptance reflects the intrinsic light interception efficiency, leaf morphology has a substantial influence (explaining 99.56% of the variance) in determining total light acquisition per leaf. Full article

Expanded polystyrene (EPS) waste is a major environmental concern, yet practical routes to upgrade it into higher value-added materials remain limited. Here, post-consumer EPS was dissolved in ethyl acetate and solvent-cast into films containing cellulose nanocrystals (CNCs) and a sunflower oil. Three formulations were produced: F-EPS (100% EPS), F-EPS + CEL (80% EPS/20% CNC), and F-EPS + CEL + OIL (80% EPS/15% CNC/5% oil). CNC markedly enhanced optical shielding, reducing transmittance at 400 nm from ≈58% (F-EPS) to ≈18% (CNC containing films). All films remained hydrophobic, showed negligible water uptake, and exhibited low mass loss after 30 days of accelerated weathering ($\Delta M=1$–$3\%$). Tensile testing showed that F-EPS had the highest UTS and elongation at break (10.0 ± 0.6 MPa and 10.5 ± 0.4%), whereas adding cellulose increased the elastic modulus (249.5 ± 29.0 MPa to 358.4 ± 64.8 MPa) but reduced UTS and elongation (8.2 ± 0.2 MPa and 5.4 ± 2.5%). Oil addition led to a further reduction in UTS and elongation (6.2 ± 0.4 MPa and 3.6 ± 0.0%), while the modulus returned to a value statistically similar to neat F-EPS. FTIR and XRD confirmed preservation of the EPS chemical fingerprint and a predominantly amorphous structure ($2\theta \approx 20$–30°). Overall, EPS + CNC + OIL films combine hydrophobicity, UV-screening, and elastic modulus similar to neat F-EPS, supporting their use as moisture-resistant, UV screening protective topcoats for non-food-contact paperboard packaging. Full article

Thermal bridges at window installations significantly influence the energy performance and indoor comfort of buildings, particularly in nearly zero energy buildings (nZEB). This study investigates the impact of window mounting-position on thermal-bridge intensity at window-to-wall junctions using finite element method (FEM) simulations of representative junction configurations. Mounting depth, frame alignment relative to the insulation layer, and junction detailing were systematically varied to quantify their effect on linear thermal transmittance (ψ-values) and internal-surface temperatures. The results show that relatively small changes in mounting position can markedly reduce thermal-bridge effects; the most effective strategy combines installing the window within the insulation layer at an optimal depth of 7–12 cm. Across the studied configurations, ψ decreased from traditional installation values of 0.27 W/(m·K) to 0.02 W/(m·K) for installation in the insulation layer, and with frame overlap and frame extenders, the ψ-value can be further reduced, reaching 0.005 W/(m·K) in the best case. Applying external insulation increases the minimum internal-surface temperature by at least 2 °C compared with cases without frame covering. In the case study of a historical building retrofitted to Passive House (PH) standard, installing windows in the insulation layer reduced annual heating demand from 32 kWh/m² to 24 kWh/m². The additional investment is economically justified, with a simple payback period of about 25 years, decreasing to around 20 years assuming a 3% annual increase in energy prices. These findings demonstrate that optimised window positioning is an effective and economically viable measure to improve the energy performance, durability, and sustainability of high-performance buildings. Full article

Airborne electromagnetic (AEM) surveys map subsurface electrical structures by deploying transmitter and receiver coils on an airborne platform. However, platform-induced vibrations are transmitted to the sensors, generating strong motion-induced noise that severely degrades signal quality. To mitigate such noise, this study proposed the use of granular materials as a cushioning medium. An impact model based on the Discrete Element Method (DEM) was developed and validated against drop-weight experiments. Both granular material properties and impactor characteristics were investigated. The study examined the cushioning effects on both the base plate and the impactor under impact loading, and the sensitivity of key parameters was evaluated. The results showed that granular properties had minimal influence on the impactor peak force. Increasing particle Young’s modulus, density, or friction coefficient led to higher peak forces on the base plate, with Young’s modulus and density having significantly stronger effects than friction coefficient. Additionally, both the impactor size and velocity correlate positively with the peak forces transmitted to the base plate and experienced by the impactor. Under thin layer conditions, the impactor force was more sensitive to impact parameters, while in thick layers it was mainly determined by particle rearrangement and energy dissipation mechanisms. These findings reveal the mechanisms governing granular cushioning and provide a theoretical basis for vibration isolation design in AEM systems to preserve high-fidelity signals. Full article