Search Results (24,267)

Pipe-embedded walls offer a promising approach to reducing winter heating demand by mitigating envelope heat loss while maintaining indoor thermal comfort. However, most existing studies focus on single-pipe systems operating under high-flow conditions, with limited attention to low-flow operation and its implications for energy flexibility. This study investigates a parallel pipe-embedded wall system operating at low flow velocity as a flexible heating strategy. A three-dimensional CFD model was developed to analyze the coupled hydraulic and thermal behavior of the wall, including the effects of connecting columns, and was validated through experiments under identical boundary conditions. Parametric analyses examined the influence of main pipe size, branch spacing, flow velocity, water temperature, and column-induced thermal bridging. The results show that variations in flow velocity and branch spacing lead to flow distribution differences of up to 6%, while causing negligible changes in inner-surface temperature (below 0.1 °C). In contrast, increasing column size significantly intensifies thermal bridging, increasing inner-surface heat flux by approximately 21% as the column edge length increases from 200 mm to 400 mm. Overall, the results demonstrate that parallel pipe-embedded walls can enhance building energy flexibility by enabling stable thermal performance under low-flow operation. Full article

The discharge of untreated paper mill effluent poses significant ecological risks due to its high organic and nutrient loads. This study aimed to assess the phytoremediation potential of Azolla pinnata for treating paper mill effluent. Response Surface Methodology (RSM) and Artificial Neural Network (ANN) modeling approaches were applied and optimization was used for pollutant removal and plant biomass production. Experiments were designed using a Central Composite Design with two independent variables: effluent concentration (0, 50, and 100%) and plant density (10, 20, and 30 g per container). The responses measured were biochemical oxygen demand (BOD), chemical oxygen demand (COD) removal efficiencies, and final biomass yield after 16 days of exposure. RSM produced statistically significant (p < 0.05) second-order regression models for all three responses (coefficient of determination; R² > 0.98), while ANN showed slightly lower prediction errors within the experimental range studied. Maximum observed removal efficiencies were 91.74% for BOD, 80.91% for COD, and 92.66 g biomass yield under 50% effluent concentration and 30 g plant density. Optimization via both models suggested closely comparable operating conditions (79% effluent concentration and 29 g biomass) for optimal performance. The results indicate that A. pinnata demonstrates potential as a low-cost, nature-based treatment system for industrial effluent remediation under controlled conditions. The integration of data-driven optimization with biological treatment contributes to sustainable effluent management strategies by reducing chemical inputs, minimizing energy demand, and enabling biomass generation with potential downstream valorization. Full article

Battery-powered electric unmanned surface vehicles (e-USVs) and electrified surface-cleaning platforms require reliable onboard vision under strict compute and power constraints. In reflective water environments, tiny floating debris is often obscured by specular highlights, reflection bands, ripples, motion blur, and camera jitter, while label noise further degrades training stability. To improve robustness without increasing onboard inference burden, this paper proposes YOLOv11-IMP, a lightweight detector for reflective water-surface scenes and embedded edge inference. The method integrates a transformer-enhanced backbone stage, a Global Channel–Spatial Attention module in the neck, and a median-enhanced channel–spatial module in the neck to improve global-context modeling, cross-scale interaction, and weak-boundary representation. WIoU-v3 is adopted to improve localization, and a train-time-only noise-aware screening strategy based on the small-loss principle is introduced to suppress unreliable labels without extra inference cost. Experiments on the CAS dataset and a self-built debris dataset show gains of 3.3% in AP@0.75 and 6.5% in AP for small objects over YOLOv11, while maintaining 7.3 GFLOPs and real-time inference on Jetson Nano, demonstrating practical potential for energy-constrained onboard missions. Full article

This study investigates the multi-scale tribo–thermo–viscoelastic performance of a sustainable bio-based FormuLITE epoxy reinforced with single and hybrid carbon nanofillers (0.1 wt.% total loading) under dry sliding up to 50 N. Pin-on-disk tests at 10, 30, and 50 N showed a consistent reduction in contact pressure and wear volume in the order: neat epoxy > 0.1 CNT > 0.1 GNP > 0.1 ND > 0.1 CNT/GNP > 0.1 CNT/ND > 0.1 GNP/ND. At 50 N and 1500 m sliding distance, neat epoxy exhibited a wear volume of 13.43 mm³ and contact pressure of 13.4 N/cm², while the GNP/ND hybrid reduced wear to 4.86 mm³ and contact pressure to 6.2 N/cm², corresponding to reductions of 64% and 54%, respectively. The accelerating wear coefficient decreased from 2.9 × 10⁻⁶ to 8.5 × 10⁻⁷, confirming slower damage accumulation in hybrid systems. Time-dependent contact pressure analysis revealed reduced asymptotic intensity and suppressed mid-cycle pressure spikes, indicating enhanced tribolayer stability. Effective surface hardness increased from 0.18 GPa (neat epoxy) to 0.30 GPa (GNP/ND), while normalized wear decreased from 1.00 to 0.36. Enhanced damping behavior and improved thermal conductivity in hybrid systems promoted stress redistribution and minimized flash-temperature localization. An interfacial energy-partition framework calibrated to experimental wear data quantitatively linked effective driving pressure, tribofilm stabilization, and surface hardness to material removal. The results demonstrate that wear mitigation in sustainable bio-epoxy systems is governed by coupled mechanical, viscoelastic, and thermal energy redistribution, with GNP/ND hybrids providing the most stable tribological interface under severe sliding. The findings contribute to the development of durable and sustainable bio-epoxy composite systems for engineering applications, supporting broader goals of responsible material utilization and sustainable industrial innovation aligned with the United Nations Sustainable Development Goals (SDG 9 and SDG 12). Full article

Ice accretion on aircraft, wind-turbine blades, power networks, civil infrastructure, and exposed sensors poses severe safety risks and economic costs. Passive icephobic surfaces mitigate icing by delaying heterogeneous nucleation, altering droplet impact/solidification and wetting transitions, and/or weakening the ice–substrate bond so that accreted ice sheds under modest aerodynamic, gravitational, or vibrational loads. This review synthesizes recent progress using a unified mechanism framework linking (i) nucleation and early freezing, (ii) droplet dynamics during impact or condensation/frosting, and (iii) ice accretion and removal governed by interfacial fracture. Smooth low-surface-energy coatings, textured (superhydrophobic) surfaces, slippery liquid-infused porous surfaces (SLIPS), and low-interfacial-toughness strategies are critically compared in terms of achievable performance ranges, failure modes, durability limits, fabrication scalability, and test-method dependence. Ice-adhesion measurement approaches (push-off, pull-off/tensile, centrifugal) are assessed and a minimum reporting checklist is provided to improve comparability. Case studies across aviation, wind energy, power infrastructure, sensors, and emerging civil-engineering coatings highlight that durability and scale-dependent failure modes remain the dominant barriers to durable, energy-free icing mitigation. The review concludes with priorities for eco-friendly chemistries, self-healing or renewable layers, standardized testing/reporting, and data-driven (machine learning-assisted) optimization to accelerate translation into durable passive ice-mitigation technologies. Full article

The commercialization of V-based catalysts for the selective catalytic reduction of NOx by NH₃ (NH₃-SCR) is hindered by their narrow operating temperature window, insufficient low-temperature (LT) activity, and severe SO₂-to-SO₃ oxidation. To bridge this gap, we herein introduced Nb and hexagonal BN into a VW/TiO₂ system to simultaneously enhance its LT SCR activity, suppress undesired side reactions, and improve durability. Nb incorporation promoted V⁵⁺/V⁴⁺ redox cycling and enhanced lattice oxygen mobility, thus reducing the apparent activation energy and suppressing SO₂ oxidation at elevated temperatures. However, excessive Nb loading induced NH₃ oxidation and N₂O formation. This drawback was mitigated by introducing BN as a dispersion promoter, which helped secure high catalytic performance at a reduced Nb content. The VWNb/Ti-BN catalyst achieved superior NOx conversion and N₂ selectivity over a wide temperature range and benefited from notably suppressed NH₃ oxidation and SO₂-to-SO₃ oxidation. Kinetic analysis revealed that Nb primarily lowered the reaction energy barrier via redox property enhancement, whereas BN accelerated surface reaction turnover by stabilizing and dispersing active acidic sites, markedly increasing the turnover frequency without reducing the activation energy. In situ spectroscopic analysis confirmed the accelerated consumption of adsorbed NH₃ species and enhanced formation of reactive NOx intermediates, indicating SCR pathway enhancement. After aging in the presence of SO₂ and H₂O, the best-performing honeycomb-type monolithic catalyst retained and NOx conversion of >80%, demonstrating excellent long-term durability under practical conditions. A composition-aware machine learning model based on log-ratio-transformed variables quantitatively identified the synergistic balance among V, Nb, W, BN, and TiO₂ as the dominant factor governing LT SCR performance. Thus, this work provides valuable mechanistic insights and a strategy for designing wide-temperature-window SCR catalysts with improved activity, selectivity, and resistance to sulfur poisoning. Full article

The utilisation of composite materials has the potential to play a vital role in the development of lightweight structures for future generations of aircraft, with the objective to reduce emissions. Ultrasonic welding is a process that has been proven to exhibit advantageous qualities, including the capacity to achieve welds with a comparatively short process time. Furthermore, its capacity to function as both a static and a continuous process makes it a viable candidate for facilitating the realisation of this objective. The present study investigates the potential of a novel explicit modelling approach for the static ultrasonic welding process to more accurately represent the welding process by incorporating a more precise representation of the hammering effect. The hammering effect describes the partial loss of contact between the sonotrode and the upper adherend. The model’s validation was achieved through a multifaceted approach that incorporates high-speed camera recording, encompassing digital image correlation, laser displacement sensor measurements, and static ultrasonic welding experiments. These experiments encompassed varying welding times, followed by fracture surface analysis. The findings showed that an explicit time-domain model can effectively represent the static welding process of unidirectional materials utilising a film energy director. The experimental validation demonstrated a high degree of correlation between the thermal behaviour of the welding interface and the simulation results. The study demonstrated that the neutral position of the sonotrode exhibited an increase during the initial phase of the welding process due to dynamic stresses. This phenomenon enables reduced constraint movement of the adherends and the energy director, which results in the disconnection of the sonotrode from both the upper adherend and the energy director, as well as the adherends and the anvil. The higher neutral position of the sonotrode was then implemented in an explicit simulation of the static ultrasonic welding process. Full article

This work presents a method to encapsulate plant extracts within a binary polysaccharide carrier and to characterize the physicochemical and rheological performance of the resulting biocomposites in the context of food use. Using a starch/psyllium matrix, extracts from Sambucus nigra (SN), Aronia melanocarpa (AM), and Echinacea purpurea (EP) were effectively protected and incorporated through a stepwise workflow encompassing matrix preparation, encapsulation, structural verification, and functional assessment. SEM revealed a porous network containing uniformly distributed, extract-loaded spherical structures (~800–1500 nm), while FTIR supported the presence of hydrogen bonding and hydrophobic interactions that contributed to system stability. The prepared nanoemulsions showed shear-thinning (pseudoplastic) behavior, indicating favorable processing characteristics, whereas most physicochemical and bioactivity measurements were performed on lyophilized composites. The dried materials preserved extract-specific color signatures (ΔE > 5) and exhibited distinct thermal responses: AM produced a pronounced plasticizing effect (Tg reduced by >20 °C), while the incorporation of extracts generally delayed thermal degradation, consistent with polyphenol–starch interactions. Phase-transition behavior was also altered, with melting peaks suppressed for SN and AM and melting temperatures lowered for EP. Surface analysis indicated increased hydrophobicity and a reduced polar component of surface free energy, suggesting improved moisture barrier potential. Antioxidant capacity closely tracked total phenolic content (r > 0.94), with caffeic acid contributing strongly, particularly in EP-based systems. Antimicrobial activity depended on extract type (broad-spectrum for EP, selective for SN, minimal for AM), and the comparatively higher sensitivity of Gram-negative bacteria points to improved phenolic availability and membrane interactions upon encapsulation. Collectively, these results highlight the starch/psyllium matrix as a flexible platform for stabilizing plant extracts while enabling tunable functional attributes for functional food applications. Full article

Monitoring atmospheric turbulence data of the near-surface sublayer presents a difficult challenge on complex and heterogeneous terrain such as mixed land areas where weather facilities are not always available. This study uses tilt data derived from the flight logs of two hovering unmanned aerial vehicles (UAVS) as portable probes (DJI Mavic 2 and DJI Mavic 3 Classic) to compare the turbulence spectral characteristics of two adjacent contrasting surfaces; a built open courtyard and an open grass field. Turbulence spectra were divided into three ranges: $E_1$ (0.05–0.2 Hz), $E_2$ (0.2–1 Hz), and $E_3$ (1–5 Hz). A 30 s moving mean and welch methods were used to filter out noise to ensure that the resulting spectra only showed the small tilts that were derived to show atmospheric turbulence. Normalization was applied to compare spectral shapes. Comparisons were made within platform (M2 vs. M2, M3 vs. M3). Observations show that spectral shapes generally agree. Contrasts were systematic within the energy bands and were not global. The study concludes on the notion that the unobstructed surfaces produce stronger fluctuations at the largest scales, whereas the built environments intensify turbulence at smaller scales. Full article

With the growing significance of renewable energy resources and energy storage systems, the number of grid-connected inverters has been rising at an increasingly rapid pace. Generally, these inverters are directly integrated with the distribution network by synchronizing with the grid voltage at the point of common coupling. However, the low grid strength and varying R/X ratios, as the common characteristics of most distribution networks or weak grids, can lead to dynamic interactions that comprise stability and limit the power transfer capacity of grid-connected inverters. To ensure stable operation of the inverters, researchers must determine the stability boundary, described as the maximum power transfer capacity of grid-connected inverters under the premise of maintaining system small-signal stability. For this purpose, we propose to formulate a state-space model of the system in the synchronously rotating dq-frame of reference and perform eigenvalue analysis to determine the stability boundary. With a detailed model of the control structure and parameters of the grid-connected inverters, the stability boundary is identified as a surface with respect to different grid strengths and R/X ratios. Case study results of proposed eigenvalue analysis are compared with those of admittance model-based stability analysis as well as time-domain simulation using a switching model in Matlab/Simulink, validating the effectiveness and accuracy of the proposed eigenvalue analysis for stability boundary identification. Full article

To enhance the performance of high-speed solenoids (HSSs) in control systems, two improved structural designs incorporating a permanent magnet (PM) and an annular flange (AF) are proposed based on the parallel magnetic circuit principle. Their static electromagnetism performances were thoroughly investigated by the finite element method. Furthermore, multi-objective optimization combined with the response surface method and NSGA-II was carried out. The results indicate that the electromagnetic energy conversion efficiency and electromagnetic force of HSSs can be promoted by applying a PM and an AF: for the first improvement design just employing a PM, increasing the PM height improves energy conversion efficiency and mitigates magnetic saturation within the main pole, and for the second improvement design employing both a PM and an AF, the electromagnetic energy conversion efficiency and electromagnetic force of HSS can be further promoted. In the end, based on the Pareto optimal solution set, the optimized design increases the net electromagnetic force by 18.8% and reduces the peak current by 18.8%. This is the result of applying the optimization scheme, which is beneficial for increasing the dynamic response speed of the HSS valve and reduce its energy loss. Full article

The high-efficient utilization technology of organic waste can alleviate the dual pressures of energy and the environment. The study investigated the effects of substrate ratio, substrate concentration, and temperature on biohydrogen yield, and further optimized the process conditions for co-digestion of food waste and fecal sludge as substrates for biological hydrogen production. The results of batch mode experiments show that when the ratio of food waste to fecal sludge is 5:1, substrate concentration is 60 g/L, and fermentation temperature is 40 °C, the system achieves maximum cumulative hydrogen production of 183 mL (equivalent to 32 mL/g VS). The response surface methodology (RSM) indicates that substrate ratio, substrate concentration, and temperature all exert remarkably significant effects on hydrogen yield (p < 0.01). In addition, the synergistic interaction between substrate ratio and temperature significantly influences hydrogen production performance (p < 0.05). This study elucidates the synergistic mechanism of key process factors in the co-digestion of food waste and fecal sludge for biohydrogen production. The findings provide a theoretical basis for the engineering application of organic waste to hydrogen technologies. Full article

Effluents from industries, manufacturing companies, textile looms, and floodwater contaminate the surface water reservoirs. This endangers the quality of water for use by humans. Wastewater remediation is one of the ways to recycle the dirty water and make it suitable for use. Photocatalysis is the most common method for wastewater remediation, especially using Titanium dioxide (TiO₂) nanoparticles. However, chemical synthesis and direct addition of nanoparticles may cause toxicity to the flora and fauna present in the water body. To address this limitation, we have green-synthesized TiO₂ nanoparticles using a horticulture waste, Calendula officinalis dried flower extract and entrapped them in a natural polymer, chitosan (CTS-TiO₂-CO nanocomposite). The polymer entrapment ensures biocompatibility as well as reduced aggregation of nanoparticles. The synthesized CTS-TiO₂-CO nanocomposite was characterized using UV-visible spectrophotometry, dynamic light scattering, zeta potential, Fourier Transformed Infrared Spectroscopy (FTIR), X-ray diffractometry (XRD), scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDAX) analysis. The absorption peak was found at 302 nm, and the hydrodynamic diameter at 490 nm. SEM images show flower-like morphology with 326 nm average particle diameter. The non-toxic dose of the nanoparticles was estimated by MTT assay and zebrafish embryo developmental studies. More than 82% fibroblast cells were viable after treatment with 100 μg/mL of CTS-TiO₂-CO nanocomposite. 85% embryos hatched after treatment with 50 μg/mL of CTS-TiO₂-CO nanocomposite. Further, the textile dye remediation assessment was done using the dye crystal violet, exhibiting 69.19% dye degradation after 4 h of sunlight exposure. Altogether, the results demonstrate that the CTS-TiO₂-CO nanocomposite was effective in the remediation of crystal violet without causing any toxicity up to a dose of 100 μg/mL. Full article

Arsenic (As) contamination of soils is a critical environmental and geochemical concern, with its mobility and bioavailability largely controlled by molecular-scale interactions with soil minerals. This study investigates the adsorption behavior of arsenate [As(V)] and arsenious acid [As(III)] on major clay minerals to elucidate fundamental controls on As retention in soil and sediment systems. Molecular modeling approaches were employed to investigate these interactions. Density functional theory (DFT) calculations were performed on cluster models of illite, chlorite, montmorillonite, and kaolinite to evaluate adsorption configurations and binding energies of arsenate and arsenious acid. In addition, semiempirical (PM6) and classical force-field (UFF) methods were used to examine the influence of vermicompost-derived organic matter on arsenate-mineral interactions. Multiple adsorption configurations, including atop atom, bridge, three-fold filled, and three-fold hollow sites, were evaluated, and binding energies were calculated with correction for basis set superposition error. The results indicate that three-fold hollow sites are the most favorable, with As(V) binding energies of 60–65 kcal mol⁻¹ on illite, chlorite, and montmorillonite, reaching 75 kcal mol⁻¹ on kaolinite at a surface distance of 2.7 Å. In contrast, As(III) shows weaker and energetically flatter adsorption, with binding energies of 28–54 kcal mol⁻¹ and larger equilibrium distances of 3.2–4.0 Å. Modeling of vermicompost addition suggests a substantial reduction in arsenate binding on most clay minerals, except illite, indicating competitive or disruptive interactions at mineral surfaces. These findings provide quantitative, atomistic insight into mineral- and amendment-specific controls on As stabilization and mobility in soil and sediment systems. Full article

This paper presents a hybrid control strategy for robust voltage regulation of a DC–DC boost converter used in a renewable-rich DC microgrid. The DC microgrid may comprise batteries, photovoltaic, and wind energy sources connected to a common DC bus, where voltage fluctuations arise due to variable generation and dynamic load profiles. To ensure optimal and efficient output voltage regulation under these conditions, a novel Linear Quadratic Regulator (LQR) driven self-regulating Sliding Mode Control (SMC) approach is developed. The proposed scheme is realized by combining the optimal performance of an LQR voltage-reference tracking controller with the robustness of a tangent-hyperbolic-based-sliding-mode reaching law defined over an LQR-driven sliding surface. To reduce chattering and improve adaptability to bounded disturbances, the waveform of the hyperbolic switching function in the reaching law is adaptively modulated via an online indirect supervised learning law. The control parameters are tuned offline using numerical optimization. Simulation results under different scenarios, including input voltage disturbances, load variations, and model uncertainties, show that the proposed method achieves superior voltage regulation, reduced chattering, and enhanced dynamic response compared to conventional controllers. The framework ensures reliable EV integration into intelligent DC microgrids. Full article