Search Results (8,225)

This study investigates Project-Based Learning (PBL) to boost student engagement in a Transport Phenomena course at the Federal University of Mato Grosso do Sul (UFMS). Through a hands-on project involving Floating Treatment Islands (FTIs) for water quality improvement, PBL was hypothesized to enhance student involvement and analytical skills. Students designed and optimized FTIs, experimenting with configurations like root length and plant type. Quantitative outcomes reveal a standard deviation of 1.5 in project scores among top performers (course average > 6), reflecting diverse problem-solving strategies, while a standard deviation of 0.8 near the passing threshold (course average ≈ 6) indicates consistent efforts to improve grades. Additionally, 80% of students rated their experience ≥ 4 on a 5-point scale, signaling high satisfaction, although 40% identified data interpretation as a challenge requiring targeted support. Outcomes were assessed by analyzing score variability, revealing higher standard deviations among top performers, indicating diverse problem-solving approaches, while lower deviations near the passing threshold suggested uniform efforts to improve grades. Despite general satisfaction, some students faced data interpretation challenges, highlighting areas for instructional refinement. The results affirm PBL’s effectiveness in fostering engagement and practical skills but suggest that adaptive teaching methods are essential to support comprehension and maintain engagement across different performance levels. Full article

Ensuring the safety of building occupants during emergency evacuations is a critical aspect of building design. The spatial configuration and functional layout of buildings significantly influence overall evacuation efficiency. However, accurately assessing evacuation performance based on spatial characteristics remains challenging. This study proposes a weighted network analysis approach to evaluate the evacuation efficiency of buildings. It establishes the “Space-to-Network” diagram translation principles for converting spatial configurations into graph-based representations, defines analytical indicators for evacuation-weighted networks, and introduces a systematic methodology and workflow. A case study demonstrates the effectiveness of this approach, showing that the average relative deviation from evacuation simulation results is less than 10%. The method is particularly well suited for evaluating designs during the early stages. This research offers a novel perspective for evacuation analysis and provides a concise and reliable tool for the quantitative evaluation and performance optimization of building evacuation space. Full article

To achieve energy conservation, emission reduction, and green low-carbon goals for gas storage facilities, it is crucial to efficiently recover and utilize waste heat during gas injection while maintaining natural gas cooling rates. However, existing sensible and latent heat storage technologies cannot sustain long-term thermal storage or seasonal utilization of waste heat. Thermal chemical energy storage, with its high energy density and low thermal loss during prolonged storage, offers an effective solution for efficient recovery and long-term storage of waste heat in gas storage facilities. This study proposes a novel heat recovery method by combining a moving bed with mixed hydrated salts (CaCl₂·6H₂O and MgSO₄·7H₂O). By constructing both small-scale and full-scale three-dimensional models in Fluent, which couple the desorption and endothermic processes of hydrated salts, the study analyzes the temperature and flow fields within the moving bed during heat exchange, thereby verifying the feasibility of this approach. Furthermore, the effects of key parameters, including the inlet temperatures of hydrated salt particles and natural gas, flow velocity, and mass flow ratio on critical performance indicators such as the outlet temperatures of natural gas and hydrated salts, the overall heat transfer coefficient, the waste heat recovery efficiency, and the mass fraction of hydrated salt desorption are systematically investigated. The results indicate that in the small-scale model (1164 × 312 × 49 mm) the outlet temperatures of natural gas and mixed hydrated salts are 79.8 °C and 49.3 °C, respectively, with a waste heat recovery efficiency of only 33.6%. This low recovery rate is primarily due to the insufficient residence time of high-velocity natural gas (10.5 m·s⁻¹) and hydrated salt particles (2 mm·s⁻¹) in the moving bed, which limits heat exchange efficiency. In contrast, the full-scale moving bed (3000 × 1500 × 90 mm) not only accounts for variations in natural gas inlet temperature during the three-stage compression process but also allows for optimized operational adjustments. These optimizations ensure a natural gas outlet temperature of 41.3 °C, a hydrated salt outlet temperature of 82.5 °C, a significantly improved waste heat recovery efficiency of 94.2%, and a hydrated salt desorption mass fraction of 69.2%. This configuration enhances the safety of the gas injection system while maximizing both natural gas waste heat recovery and the efficient utilization of mixed hydrated salts. These findings provide essential theoretical guidance and data support for the effective recovery and seasonal utilization of waste heat in gas storage reservoirs. Full article

The present article provides an abstract overview of the issue of optimal blank searching for integral parts utilized in complex engineering projects, including those pertaining to the fabrication of machine, ship, and aircraft components. The manufacturing process for these components is intricate and necessitates meticulous precision and strict adherence to the design model. Conventional blank calculation techniques are marred by substantial inaccuracies. The present research proposes and verifies an effective method based on the reverse solution of a mathematical problem. The focal point of this study is the aerodynamic curvature of aluminum alloys belonging to the Al–Mg–Mn family. The formation of the object is achieved through the employment of a hydroelastomer press of the QFC (Quintus Technologies) type. The forming process is simulated using PAM-STAMP software, developed by the French company ESI Group. The objective of the present study is to ascertain the optimal configuration of the blank by optimizing the discrepancy between the dynamic calculations and the design model using sweep contours. The resulting new shape of the part allows for the formation of parts with minimal deviation from their design contours. Full article

Space debris is an increasingly severe problem in the space industry. According to projections, the number of satellites will increase from the current 10,000 to 100,000 by 2030, specially in LEO orbits. This significant rise in the number of satellites threatens space sustainability, forcing satellites to perform more maneuvers to avoid impacts or leading to the production of more and more space debris due to collisions (Kessler Syndrome). Consequently, substantial efforts have been made to detect and track space debris, leading to the development of the current catalogs. However, with existing technology, detecting and tracking small debris remains challenging. In order to improve the current system, several proposals of Space-Based Situational Awareness (SBSA) have been made. These proposals involve satellites equipped with telescopes to detect space debris and determine their orbits. Unlike prior works, focused primarily on detection rates, this research aims to quantify their accuracy in orbit determination as a function of observation duration, the number of observers, and sensor precision. The Unscented Kalman Filter (UKF) is employed as the core estimation algorithm, leveraging both simulated single-case analyses and Monte Carlo simulations to evaluate system performance under various configurations and uncertainties. The results indicate that a constellation of at least three observers with high-precision instruments and sub-kilometer positioning accuracy can reliably estimate debris orbits within an observation period of 4–7 min, with the mean error in position and velocity obtained being 2.2–3 km and 3–4 m/s, respectively. These findings offer critical insights for designing future SBSA constellations and optimizing their operational parameters to address the growing challenge of orbital debris. Full article

Electrochemical sensors have been developed based on polyethylene terephthalate track-etched membranes (PET TeMs) modified by photograft copolymerization of N-vinylformamide (N-VFA) and trimethylolpropane trimethacrylate (TMPTMA). The modification, structure and properties of the modified PET TeMs were thoroughly characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM), thermogravimetric analysis (TGA), Fourier-transform infrared (FTIR) spectroscopy, gas permeability measurements and contact angle analysis. Optimal membrane modification was achieved using C = 10% (N-VFA), 60 min of UV irradiation and a UV lamp distance of 10 cm. Furthermore, the modified membranes were implemented in a two-electrode configuration for the determination of Eu³⁺, Gd³⁺, La³⁺ and Ce³⁺ ions via square-wave anodic stripping voltammetry (SW-ASV). The sensors exhibited a linear detection range from 10⁻⁷ M to 10⁻³ M, with limits of detection of 1.0 × 10⁻⁶ M (Eu³⁺), 6.0 × 10⁻⁶ M (Gd³⁺), 2.0 × 10⁻⁴ M (La³⁺) and 2.5 × 10⁻⁵ M (Ce³⁺). The results demonstrated a significant enhancement in electrochemical response due to the grafted PET TeMs-g-N-PVFA-TMPTMA structure, and the sensor showed practical applicability and consistent performance in detecting rare earth ions in tap water. Full article

Combustion instability poses a significant challenge in aerospace propulsion systems, particularly in afterburners that employ bluff-body flame stabilizers. The flame transfer function (FTF) is essential for characterizing the dynamic response of flames to perturbations, which is critical for predicting and controlling these instabilities. This study experimentally investigates the effect of varying the number of fuel injection holes (N = 3, 4, 5, 6) on the FTF and flame dynamics in a model afterburner combustor. Using acoustic excitations, the FTF was measured across a range of frequencies, with flame behavior analyzed via high-speed imaging and chemiluminescence techniques. Results reveal that the FTF gain exhibits dual-peak characteristics, initially decreasing and then increasing with higher N values. The frequencies of these gain peaks shift to higher values as N increases, while the time delay between velocity and heat release rate fluctuations decreases, indicating a faster flame response. Flame morphology analysis shows that higher N leads to shorter, taller flames due to enhanced fuel distribution and mixing. Detailed examination of flame dynamics indicates that different pulsation modes dominate at various frequencies, elucidating the observed FTF behavior. This research provides novel insights into the optimization of fuel injection configurations to enhance combustion stability in afterburners, advancing the development of more reliable and efficient aerospace propulsion systems. Full article

This paper proposes a harmonic source localization method for power systems, combining voltage difference features with a random forest classifier. The method captures harmonic propagation patterns and optimizes network topology handling to ensure accurate and efficient identification across various configurations. Validated on IEEE standard transmission networks, it achieves high accuracy and scalability. While effective in transmission systems, distribution networks pose challenges due to complex topologies and high impedance. Future enhancements will focus on advanced feature engineering, data augmentation, and real-time processing to improve adaptability in diverse power system environments. Full article

Cost-effective procedures usually cannot achieve complete removal of priority contaminants present in water at very low concentrations (as pesticides or pharmaceuticals). Advanced oxidation processes (AOPs) represent promising technologies for removing priority contaminants from water at trace concentrations, yet practical implementation remains limited due to technical and economic constraints. This study presents an innovative flow-through photodegradation device designed to overcome current limitations while achieving efficient contaminant removal at industrial scale. The device integrates a UVC 254 nm lamp-equipped flow chamber with automated dosing pumps for hydrogen peroxide and/or solid catalyst suspensions, coupled with a 30 nm porous membrane filtration system for catalyst recirculation. This configuration optimizes light–catalyst–pollutant contact while enabling combined catalytic processes. Performance evaluation using acesulfame (ACE) and iohexol (IHX) as model contaminants demonstrated rapid and effective removal. IHX degradation with UVC and 75 μM H₂O₂ achieved complete removal with t₉₅% = 7.23 ± 1.21 min (pseudo-order 0.25, t₁/₂ = 3.27 ± 0.39 min), while ACE photolysis (with UVC only) required t₉₅% = 14.88 ± 2.02 min (pseudo-order 1.27, t₁/₂ = 2.35 ± 0.84 min). The introduction of t₉₅% as a performance metric provides practical insights for near-complete contaminant removal requirements. Real-world efficacy was confirmed using tertiary wastewater treatment plant effluents containing 14 μg/L IHX, achieving complete removal within 8 min. However, carbamazepine degradation proved slower (t₉₅% > 74 h), highlighting the need for combined catalytic approaches for recalcitrant compounds. Spiking experiments (1000 μg/L) revealed concentration-dependent kinetics and synergistic effects between co-present contaminants. Analysis identified degradation byproducts consistent with previous studies, including tri-deiodinated iohexol (474.17 Da) intermediates. This scalable system, constructed from commercially available components, demonstrates potential for cost-effective industrial implementation. The modular design allows adaptation to various contaminants through adjustable AOP combinations (UV/H₂O₂, photocatalysts, ozone), representing a practical advancement toward addressing the gap between laboratory-scale photocatalytic research and full-scale water treatment applications. Full article

Traditional educational assessment systems suffer from inefficient question selection strategies that fail to optimally probe student knowledge while requiring extensive testing time. We present a novel hierarchical probabilistic neural framework that integrates Bayesian inference with symmetric deep neural architectures to enable adaptive, efficient knowledge assessment. Our method models student knowledge as latent representations within a graph-structured concept dependency network, where probabilistic mastery states, updated through variational inference, are encoded by symmetric graph properties and symmetric concept representations that preserve structural equivalences across similar knowledge configurations. The system employs a symmetric dual-network architecture: a concept embedding network that learns scale-invariant hierarchical knowledge representations from assessment data and a question selection network that optimizes symmetric information gain through deep reinforcement learning with symmetric reward structures. We introduce a novel uncertainty-aware objective function that leverages symmetric uncertainty measures to balance exploration of uncertain knowledge regions with exploitation of informative question patterns. The hierarchical structure captures both fine-grained concept mastery and broader domain understanding through multi-scale graph convolutions that preserve local graph symmetries and global structural invariances. Our symmetric information-theoretic method ensures balanced assessment strategies that maintain diagnostic equivalence across isomorphic concept subgraphs. Experimental validation on large-scale educational datasets demonstrates that our method achieves 76.3% diagnostic accuracy while reducing the question count by 35.1% compared to traditional assessments. The learned concept embeddings reveal interpretable knowledge structures with symmetric dependency patterns that align with pedagogical theory. Our work generalizes across domains and student populations through symmetric transfer learning mechanisms, providing a principled framework for intelligent tutoring systems and adaptive testing platforms. The integration of probabilistic reasoning with symmetric neural pattern recognition offers a robust solution to the fundamental trade-off between assessment efficiency and diagnostic precision in educational technology. Full article

Thermocouples can be combined into thermopiles to sense heat differences or achieve localized heating and cooling. However, integrating them into textiles using yarns is not straightforward, and chemical methods face challenges like complex processing, poor scalability, and voltage non-uniformity. This study employs conventional weaving to fabricate textile-based thermocouples and thermopiles for wearable sensing and potential cooling applications, with a focus on protective clothing. Using stainless steel and nickel-coated carbon yarns, we demonstrate a more stable thermocouple than those made with chemical or welded methods, with minimal fabric damage. Four conductive yarns, stainless steel, carbon fiber (CF), and nickel-coated carbon fiber (NiFC), were woven and laser-cut to form thermocouples using three different binding types to connect them. Inox1–NiFC was the most efficient thermocouple, achieving the highest Seebeck coefficient of 21.87 µV/K with Binding 3. Binding 3 also reduced contact resistance by 66% across all configurations. Slightly lower but comparable performance was seen with Inox1–NiFC/Binding 2 (21.83 µV/K) and Inox2–NiFC/Binding 1 (15.79 µV/K). In contrast, FC-based thermocouples showed significantly lower Seebeck values: 5.67 µV/K (Inox2–FC/Binding 2), 5.43 µV/K (Inox1–FC/Binding 3), and 5.06 µV/K (Inox2–FC/Binding 1). A woven thermopile with three junctions made with the optimal binding and thermocouple combination generated an average of 55.54 µV/K and about 500 µV at small temperature differences (4–5 °C), with a linear voltage response suitable for sensing. While thermal sensing proved effective, Peltier cooling needs further optimization. This method offers a stable, low-cost, and scalable platform for textile-integrated thermoelectric systems, with strong potential for use in uniforms and other protective garments. Full article

Shared energy storage (SES) systems, operating alongside microgrid clusters, can effectively mitigate power fluctuations and reduce the operational costs of independently constructed energy storage systems. Consequently, capacity allocation planning for SES in microgrid clusters has emerged as a crucial technology for achieving the system’s economical and efficient operation. This paper presents a two-layer optimal allocation model utilizing the Alternating Direction Method of Multipliers (ADMMs) to characterize system operation precisely. By establishing a refined mathematical model of a microgrid cluster with SES and analyzing the energy flow interaction mechanisms inside the cluster, along with the configuration scheme for SES capacity. The upper layer optimization of the model minimizes operational and maintenance investment costs associated with designing the capacity of SES, while the lower layer model optimizes the operation scheduling with the goal of the lowest operation cost. To illustrate the efficacy and benefits of the proposed method, case studies are conducted in different scenarios comparing the proposed method with the conventional method to analyze the power distribution features of the microgrid and the allocation planning of shared energy storage capacity. Full article

This paper presents a novel design strategy for outlier-robust, three-element non-uniform linear array (NULA) configurations optimized for multiple-input multiple-output (MIMO) radar systems aimed at target direction of arrival (DoA) estimation. The occurrence of outliers, i.e., ambiguous estimates, is a well-known issue in DoA estimation based on the maximum likelihood (ML), which is caused by the local maxima of the likelihood function. Specifically, we study how the positioning of both transmitters and receivers affects both presence of outliers and accuracy of ML DoA estimation. By leveraging a theoretical prediction of the DoA mean squared error (MSE), we propose a design strategy to jointly optimize the positions of NULA array of three transmitting and receiving elements, only inside a subspace which guarantees that the outlier probability remains below a specified threshold. Compared to NULA configurations with a single transmitter, the proposed designs achieve superior estimation accuracy due to two key factors: improved asymptotic performance resulting from a narrower mainlobe, and enhanced robustness against outliers due to reduced sidelobes. Furthermore, the proposed approach is well-suited for practical implementation in low-cost radars using only 3 × 3 or 2 × 3 MIMO configurations, as it also incorporates practical design constraints such as minimum inter-element spacing to account for the physical dimensions of the antennas, and tolerance in the installation accuracy. Full article

The thermal insulation performance of liquid hydrogen (LH₂) storage tanks is critical for long-distance transportation. The active cooled shield (ACS) technologies, such as the liquid nitrogen cooled shield (LNCS) and the vapor hydrogen cooled shield (VHVCS) are important thermal insulation methods. Many researchers installed the VHVCS inside the multilayer insulation (MLI) and obtained the optimal position. However, the MLI layer is often thinner than the vacuum interlayer between the inner and outer tanks, and there is a large vacuum interlayer between the outermost side of MLI and the inner wall of the outer tank. It is unknown whether the insulation performance can be improved if we install ACS in the mentioned vacuum interlayer and separate a portion of the MLI to be installed on the outer surface of ACS. In this configuration, the number of inner MLI (IMLI) layers and the ACS position are interdependent, a coupling that has not been thoroughly investigated. Therefore, thermodynamic models for MLI, MLI-LNCS, and MLI-VHVCS schemes were developed based on the Layer-by-Layer method. By applying Robin boundary conditions, the temperature distribution and heat leakage of the MLI scheme were predicted. Considering the coupled effects of IMLI layer count and ACS position, a co-optimization strategy was adopted, based on an alternating iterative search algorithm. The results indicate that for the MLI-LNCS scheme, the optimal number of IMLI layers and LNCS position are 36 layers and 49%, respectively. For the MLI-VHVCS scheme, the optimal values are 21 layers and 39%, respectively. Compared to conventional MLI, the MLI-LNCS scheme achieves an 88.09% reduction in heat leakage. However, this improvement involves increased system complexity and higher operational costs from LN₂ circulation. In contrast, the MLI-VHVCS scheme achieves a 62.74% reduction in heat leakage, demonstrating that using sensible heat from cryogenic vapor can significantly improve the thermal insulation performance of LH₂ storage tanks. The work of this paper provides a reference for the design and optimization of the insulation scheme of LH₂ storage tanks. Full article

The advancement of wearable technologies has resulted in significant interest in GNSS-integrated textile antenna development. Although existing literature surveys predominantly concentrate on flexible non-textile antenna systems operating within UHF and 5G frequency spectra, systematic investigations of textile-based antenna configurations in the 1–2 GHz GNSS band have been relatively scarce. Contemporary GNSS textile antenna architectures primarily target GPS frequency coverage, while the global proliferation of BeiDou Navigation Satellite System (BDS) infrastructure necessitates urgent development of BDS-compatible textile antenna solutions. This review methodically examines the structural configurations and radiation characteristics of 1–2 GHz textile antennas, bandwidth enhancement techniques, miniaturization methodologies, and gain optimization approaches, along with material selection criteria and manufacturing processes. Technical challenges persist in simultaneously achieving broadband operation, compact dimensions, and elevated gain performance. Primary manufacturing approaches encompassing laminated fabric assemblies, printed electronics, and embroidered conductive patterns are analyzed, while existing methodologies exhibit limited capacity for seamless garment integration. Despite remarkable progress in conductive material engineering, dielectric property modification studies demonstrate insufficient theoretical depth. Comprehensive mitigation strategies for multifaceted operational environments involving human proximity effects, mechanical deformation, and variable meteorological conditions remain notably underdeveloped. This comprehensive analysis aims to establish a foundational framework for next-generation BDS-oriented textile antenna development. Full article