Search Results (10,843)

This study investigates the influence of varying water-to-cement (W/C) ratios and fine aggregate compositions on the performance of concrete incorporating expanded perlite aggregate (EPA) as a lightweight alternative to natural sand. A total of eighteen concrete mixes were produced, each with different W/C ratios and fine-to-coarse aggregate (FA/CA) ratios, and evaluated for workability, compressive strength, flexural and tensile strength, water absorption, density, and thermal conductivity. Perlite was used to fully replace natural sand in half of the mixes, allowing a direct assessment of its effects across low-, medium-, and high-strength concrete formulations. The results demonstrate that EPA can improve workability and reduce both density and thermal conductivity, with variable impacts on mechanical performance depending on the W/C and FA/CA ratios. Notably, higher cement contents enhanced the internal curing effect of perlite, while lower-strength mixes experienced a reduction in compressive strength when perlite was used. These findings suggest that expanded perlite can be effectively applied in structural and non-structural concrete with optimized mix designs, supporting the development of lightweight, thermally efficient concretes. Mixture W16-100%EPS was considered the ideal mix because its compressive strength at the age of 65 days 44.2 MPa and the reduction in compressive strength compared to the reference mix 14% and the reduction in density 5.4% compared with the reference mix and the reduction in thermal conductivity 14% compared with the reference mix. Full article

Concrete structures increasingly face dynamic loading conditions, such as seismic events, vehicular traffic, and environmental vibrations, necessitating enhanced energy dissipation capabilities. The damping ratio, a critical parameter quantifying a material’s ability to dissipate vibrational energy, is typically low in conventional concrete, prompting extensive research into strategies for improvement. This review comprehensively explores the impact of advanced concrete types—such as Engineered Cementitious Composites (ECCs), Ultra-High-Performance Concrete (UHPC), High-Performance Concrete (HPC), and polymer concrete—on enhancing the damping behavior. Additionally, key mix design innovations, including fiber reinforcement, rubber powder incorporation, and aggregate modification, are evaluated for their roles in increasing energy dissipation. External factors, particularly curing conditions, are also discussed for their influence on the damping performance. The findings consolidate experimental and theoretical insights into how material composition, mix design, and external treatments interact to optimize dynamic resilience. To guide future research, this paper identifies critical gaps including the need for multi-scale numerical simulation frameworks, standardized damping test protocols, and long-term performance evaluation under realistic service conditions. Advancing work in material innovation, optimized mix design, and controlled curing environments will be essential for developing next-generation concretes with superior vibration control, durability, and sustainability. These insights provide a strategic foundation for applications in seismic-prone and vibration-sensitive infrastructure. Full article

This study investigates the impact of rural digital economy development on agricultural carbon emission efficiency, aiming to elucidate the intrinsic mechanisms and pathways through which digital technology enables low-carbon transformation in agriculture, thereby contributing to the achievement of agricultural carbon neutrality goals. Based on provincial-level panel data from China spanning 2011 to 2022, this study examines the relationship between the rural digital economy and agricultural carbon emission efficiency, along with its underlying mechanisms, using bidirectional fixed effects models, mediation effect analysis, and Spatial Durbin Models. The results indicate the following: (1) A significant N-shaped-curve relationship exists between rural digital economy development and agricultural carbon emission efficiency. Specifically, agricultural carbon emission efficiency exhibits a three-phase trajectory of “increase, decrease, and renewed increase” as the rural digital economy advances, ultimately driving a sustained improvement in efficiency. (2) Industrial integration acts as a critical mediating mechanism. Rural digital economy development accelerates the formation of the N-shaped curve by promoting the integration between agriculture and other sectors. (3) Spatial spillover effects significantly influence agricultural carbon emission efficiency. Due to geographical proximity, regional diffusion, learning, and demonstration effects, local agricultural carbon emission efficiency fluctuates with changes in neighboring regions’ digital economy development levels. (4) The relationship between rural digital economy development and agricultural carbon emission efficiency exhibits a significant inverted N-shaped pattern in regions with higher marketization levels, planting-dominated areas of southeast China, and digital economy demonstration zones. Further analysis reveals that within rural digital economy development, production digitalization and circulation digitalization demonstrate a more pronounced inverted N-shaped relationship with agricultural carbon emission efficiency. This study proposes strategic recommendations to maximize the positive impact of the rural digital economy on agricultural carbon emission efficiency, unlock its spatially differentiated contribution potential, identify and leverage inflection points of the N-shaped relationship between digital economy development and emission efficiency, and implement tailored policy portfolios—ultimately facilitating agriculture’s green and low-carbon transition. Full article

Early and accurate detection of mechanical damage in prunes is crucial for preserving postharvest quality and enabling automated sorting. This study proposes a practical and reproducible method for identifying cumulative bruising in prunes using visible–near-infrared (Vis–NIR) reflectance spectroscopy coupled with machine learning techniques. A self-developed impact simulation device was designed to induce progressive damage under controlled energy levels, simulating realistic postharvest handling conditions. Spectral data were collected from the equatorial region of each fruit and processed using a hybrid modeling framework comprising continuous wavelet transform (CWT) for spectral enhancement, uninformative variable elimination (UVE) for optimal wavelength selection, and support vector machine (SVM) for classification. The proposed CWT-UVE-SVM model achieved an overall classification accuracy of 93.22%, successfully distinguishing intact, mildly bruised, and cumulatively damaged samples. Notably, the results revealed nonlinear reflectance variations in the near-infrared region associated with repeated low-energy impacts, highlighting the capacity of spectral response patterns to capture progressive physiological changes. This research not only advances nondestructive detection methods for prune grading but also provides a scalable modeling strategy for cumulative mechanical damage assessment in soft horticultural products. Full article

The use of pressure-sensitive paints (PSPs), an optical oxygen sensing technique, to visualise and measure the surface pressure on vehicle models in wind tunnel testing is becoming increasingly prevalent. Porphyrins have long been the standard luminophore for PSP formulations, with the majority employing the red-emitting platinum(II)-5,10,15,20-tetrakis-(2,3,4,5,6-pentafluorphenyl)-porphyrin. nIR-emitting luminophores, such as Pt(II) tetraphenyl tetrabenzoporphyrins, possess distinct advantages over visible emitting luminophores. In particular, they have wider spectrally useful ‘windows’, facilitating the insertion of a secondary visible emitting temperature-sensitive luminophore to be used for internal calibration without spectral crosstalk that detrimentally impacts PSP performance. In this work, we explore the effect of changing the loading quantity of an nIR-emitting para-CF₃ Pt(II) benzoporphyrin luminophore on the performance of PSP formulations. An optimal luminophore loading of 1.28% wt/wt benzoporphyrin luminophore to polystyrene binder was identified, resulting in a low temperature sensitivity at 100 kPa of 0.61%/K and a large pressure sensitivity at 293 K of 0.740%/kPa. These strong performance metrics, for a polystyrene-based PSP, demonstrate the efficacy of benzoporphyrin luminophores as an attractive luminophore option for the development of a new generation of high-performance PSP formulations that outperform current commercially available ones. Full article

The internal combustion process in a boiler in power plants has a direct impact on boiler efficiency and NOx generation. The objective of this study is to propose an intelligent deep learning modeling and multi-objective optimization approach that considers NOx emission concentration and boiler thermal efficiency simultaneously for boiler combustion in power plants. Firstly, a hybrid deep learning model, namely, convolutional neural network–bidirectional gated recurrent unit (CNN-BiGRU), is employed to predict the concentration of NOx emissions and the boiler thermal efficiency. Then, based on the hybrid deep prediction model, variables such as primary and secondary airflow rates are considered as controllable variables. A single-objective optimization model based on an improved flow direction algorithm (IFDA) and a multi-objective optimization model based on NSGA-II are developed. For multi-objective optimization using NSGA-II, the average NOx emission concentration is reduced by 5.01%, and the average thermal efficiency is increased by 0.32%. The objective functions are to minimize the boiler thermal efficiency and the concentration of NOx emissions. Comparative analysis of the experiments shows that the NSGA-II algorithm can provide a Pareto optimal front based on the requirements, resulting in better results than single-objective optimization. The effectiveness of the NSGA-II algorithm is demonstrated, and the obtained results provide reference values for the low-carbon and environmentally friendly operation of coal-fired boilers in power plants. Full article

With the intensification of urbanization, resulting in the growing building stock, building operations have become the main contributors to greenhouse gas emissions. However, the relationship between urban form and carbon emissions remains unclear, which limits the sustainable development of cities. This study reviews the definition of carbon sources, data characteristics, and evaluation methods of carbon emissions. In addition, the impact of urban form on building carbon emissions at the macro, meso, and micro scales is reviewed, and low-carbon design strategies for urban form are discussed. Finally, the existing problems in this field are pointed out, and future research directions are proposed. Our review found that small and medium-sized compact cities tend to have less carbon emissions, while large cities and megacities with compact urban forms have more carbon emissions. The carbon reduction design of urban form at the meso scale is often achieved by improving the microclimate. Developing a research framework for the impact mechanism of building carbon emissions in a coordinated manner with multi-scale urban forms can effectively promote the development of low-carbon sustainable cities. This review can assist urban planners and energy policymakers in selecting appropriate methods to formulate and implement low-carbon city analysis and planning projects based on limited available resources. Full article

The global shift towards the use of renewable energy is essential to ensure sustainable development, and geothermal energy stands out as a suitable option that can support various cascading projects. Spent geothermal water (SGW) requires proper treatment to ensure that it does not become an environmental burden. Typically, companies often face the dilemma of choosing between discharging spent geothermal water (SGW) into surface waters or injecting it into rock masses, and the economic and environmental impacts of the decision made determines the feasibility of geothermal plant development. In this study, we aimed to comprehensively assess the technical, economic, and environmental feasibility of SGW injection into rock masses. To this end, we employed a comprehensive analytical approach using the Chochołów GT-1 geothermal injection borehole in Poland as a reference case. We also performed drilling and hydrogeological testing, characterized rock samples in the laboratory, and corrected hydrodynamic parameters for thermal lift effects to ensure accurate aquifer characterization. The results obtained highlight the importance of correcting hydrogeological parameters for thermal effects, which if neglected can lead to a significant overestimation of the calculated hydrogeological parameters. Based on our analysis, we developed a framework for assessing SGW injection feasibility that integrates detailed hydrogeological and geotechnical analyses with environmental risk assessment to ensure sustainable geothermal resource exploitation. This framework should be mandatory for planning new geothermal power plants or complexes worldwide. Our results also emphasize the need for adequate SGW management so as to ensure that the benefits of using a renewable and zero-emission resource, such as geothermal energy, are not compromised by the low absorption capacity of rock masses or adverse environmental effects. Full article

Against the backdrop of global energy transition and strict environmental regulations, supercritical carbon dioxide (scCO₂) fracturing and oil displacement technologies have emerged as pivotal green approaches in shale gas exploitation, offering the dual advantages of zero water consumption and carbon sequestration. However, the inherent low viscosity of scCO₂ severely restricts its sand-carrying capacity, fracture propagation efficiency, and oil recovery rate, necessitating the urgent development of high-performance thickeners. The current research on scCO₂ thickeners faces a critical trade-off: traditional fluorinated polymers exhibit excellent philicity CO₂, but suffer from high costs and environmental hazards, while non-fluorinated systems often struggle to balance solubility and thickening performance. The development of new thickeners primarily involves two directions. On one hand, efforts focus on modifying non-fluorinated polymers, driven by environmental protection needs—traditional fluorinated thickeners may cause environmental pollution, and improving non-fluorinated polymers can maintain good thickening performance while reducing environmental impacts. On the other hand, there is a commitment to developing non-noble metal-catalyzed siloxane modification and synthesis processes, aiming to enhance the technical and economic feasibility of scCO₂ thickeners. Compared with noble metal catalysts like platinum, non-noble metal catalysts can reduce production costs, making the synthesis process more economically viable for large-scale industrial applications. These studies are crucial for promoting the practical application of scCO₂ technology in unconventional oil and gas development, including improving fracturing efficiency and oil displacement efficiency, and providing new technical support for the sustainable development of the energy industry. This study innovatively designed an amphiphilic modified amino silicone oil polymer (MA-co-MPEGA-AS) by combining maleic anhydride (MA), methoxy polyethylene glycol acrylate (MPEGA), and amino silicone oil (AS) through a molecular bridge strategy. The synthesis process involved three key steps: radical polymerization of MA and MPEGA, amidation with AS, and in situ network formation. Fourier transform infrared spectroscopy (FT-IR) confirmed the successful introduction of ether-based CO₂-philic groups. Rheological tests conducted under scCO₂ conditions demonstrated a 114-fold increase in viscosity for MA-co-MPEGA-AS. Mechanistic studies revealed that the ether oxygen atoms (Lewis base) in MPEGA formed dipole–quadrupole interactions with CO₂ (Lewis acid), enhancing solubility by 47%. Simultaneously, the self-assembly of siloxane chains into a three-dimensional network suppressed interlayer sliding in scCO₂ and maintained over 90% viscosity retention at 80 °C. This fluorine-free design eliminates the need for platinum-based catalysts and reduces production costs compared to fluorinated polymers. The hierarchical interactions (coordination bonds and hydrogen bonds) within the system provide a novel synthetic paradigm for scCO₂ thickeners. This research lays the foundation for green CO₂-based energy extraction technologies. Full article

Oyster shells, though rich in calcium, are mostly discarded and contribute to environmental issues. Developing calcium-based materials with antimicrobial functionality offers a promising solution. However, their low bioavailability limits their direct use, requiring processing to enhance their applicability. Therefore, this study aims to evaluate the physicochemical properties and antimicrobial activity of thermally processed pulverized oyster shells (TPOS) and citric acid-treated TPOS (TPOSc) compared with those of fibrous calcium carbonate (FCC) and coral-derived calcium product (CCP), which are used as reference materials. The solubility values were 0.7 mg/g for FCC, 0.5 mg/g for TPOS, 0.4 mg/g for TPOSc, and 0.05 mg/g for CCP. The average particle sizes were 476 (FCC), 1000 (TPOS and TPOSc), and 1981 nm (CCP). Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD) analyses revealed calcium ion release and structural changes in TPOS and TPOSc. Antibacterial testing further confirmed that these samples exhibited significant antimicrobial activity. Furthermore, to assess their practical applicability, TPOS and TPOSc samples with antimicrobial properties were incorporated into rice cakes. All samples retained antimicrobial activity at 0.3 wt%, while higher concentrations led to deterioration in their textural properties. These findings support the potential of thermally processed oyster shell powders for food applications that require microbial control with minimal impact on product quality. Full article

Green construction in infrastructure projects has emerged as a crucial approach for reducing environmental impacts, yet its implementation is fraught with numerous uncertainties. To assess the capacity to maintain and restore green construction performance in complex environments, this study proposes the concept of Green Construction Performance Resilience (GCPR) for infrastructure projects and develops methodologies for its management and optimization. This study constructs a project network based on the labeled property graph (LPG) technique and demonstrates its dynamic evolution throughout the entire project lifecycle. A series of indicators for quantifying GCPR are constructed and applied, enabling the quantification of green construction performance resilience in infrastructure projects. An optimization method for GCPR based on genetic algorithms is proposed. Finally, the applicability and effectiveness of the proposed methodologies are validated through the analysis of real-world infrastructure project cases. The results demonstrate that the project network model can comprehensively capture the complexity of large-scale infrastructure projects, and that the GCPR indicators effectively measure green construction performance resilience, providing valuable decision-making support for project managers. The optimization algorithm has been validated and shown to improve the GCPR level of the project. This study enriches interdisciplinary research on project resilience and project complexity theory and provides project managers with quantitative analysis and visualization tools to facilitate the attainment of green construction performance objectives in infrastructure projects and accelerate the transition towards low-carbon practices. Full article

Volcanic ash from explosive eruptions can significantly alter lake water chemistry through ash–water interactions, potentially influencing primary productivity. Alkaline (soda) lakes, mostly found in volcanic regions, are particularly sensitive due to their unique geochemical properties. However, the effects of volcanic ash on the biogeochemistry and phytoplankton dynamics of soda lakes remain poorly understood. This study presents the first nutrient release experiments using natural alkaline water from Lake Van (Türkiye) and volcanic ash from four volcanoes (Hekla, Arenal, Sakurajima, Rabaul-Tavurvur) with different compositions. Sixteen abiotic leaching experiments were conducted over contact durations ranging from 1 to 24 h. Results show rapid increases in pH (~0.4–0.5 units), enhanced silica and phosphate concentrations, and elevated levels of Na, K, Ca, Sr, and S. Nitrate and Mg were generally depleted. The low N:P ratio (~0.06) in Lake Van water indicated nitrogen limitation, partially mitigated by ash-derived inputs. Cyanobacteria dominated the phytoplankton community (95%), consistent with nitrogen fixation under low-nitrate conditions. Elevated silica may promote diatom growth, while changes in Mg/Ca ratios suggest possible impacts on carbonate precipitation and microbialite development. These findings highlight the biogeochemical and ecological relevance of volcanic ash inputs to soda lakes. Full article

Modern aerospace engineering places increasing emphasis on materials that combine low weight with high mechanical performance. Fiber metal laminates (FMLs), which merge metal layers with fiber-reinforced composites, meet this demand by delivering improved fatigue resistance, impact tolerance, and environmental durability, often surpassing the performance of their constituents in demanding applications. Despite these advantages, inspecting such thin, layered structures remains a significant challenge, particularly when they are difficult or impossible to access. As with any new invention, they always come with challenges. This study examines the effectiveness of the fundamental anti-symmetric Lamb wave mode (A0) in detecting weak interfacial defects within Carall laminates, a type of hybrid fiber metal laminate (FML). Delamination detectability is analyzed in terms of strong wave dispersion observed downstream of the delaminated sublayer, within a region characterized by acoustic distortion. A three-dimensional finite element (FE) model is developed to simulate mode trapping and full-wavefield local displacement. The approach is validated by reproducing experimental results reported in prior studies, including the author’s own work. Results demonstrate that the A0 mode is sensitive to delamination; however, its lateral resolution depends on local position, ply orientation, and dispersion characteristics. Accurately resolving the depth and extent of delamination remains challenging due to the redistribution of peak amplitude in the frequency domain, likely caused by interference effects in the acoustically sensitive delaminated zone. Additionally, angular scattering analysis reveals a complex wave behavior, with most of the energy concentrated along the centerline, despite transmission losses at the metal-composite interfaces in the Carall laminate. The wave interaction with the leading and trailing edges of the delaminations is strongly influenced by the complex wave interference phenomenon and acoustic mismatched regions, leading to an increase in dispersion at the sublayers. Analytical dispersion calculations clarify how wave behavior influences the detectability and resolution of delaminations, though this resolution is constrained, being most effective for weak interfaces located closer to the surface. This study offers critical insights into how the fundamental anti-symmetric Lamb wave mode (A0) interacts with delaminations in highly attenuative, multilayered environments. It also highlights the challenges in resolving the spatial extent of damage in the long-wavelength limit. The findings support the practical application of A0 Lamb waves for structural health assessment of hybrid composites, enabling defect detection at inaccessible depths. Full article

Selenium nanoparticles (SeNPs), with their high absorption and antioxidant properties, hold promise as feed additives in aquaculture, enhancing growth and reproductive health in fish. This review evaluates how selenium nanoparticles influence growth and reproductive traits in Asian seabass (L. calcarifer). Using the PRISMA approach, we examined the impacts of selenium nanoparticles (SeNPs) on the growth performance and gonadal development of Asian seabass (L. calcarifer) by synthesizing findings from the existing literature. Meta-analysis explored that selenium nanoparticles (SeNPs) supplementation significantly improved specific growth rate (SGR) (pooled effect size = 3.97; 95% CI: 3.68–4.26) and feed conversion ratio (FCR) (pooled effect size = 0.81; 95% CI: 0.75–0.86), with low heterogeneity. Regarding reproductive outcomes, SeNPs enhanced gonadal development, sperm quality, and steroidogenesis. Significant improvements were observed in gonadosomatic index (effect size = 0.5), fertilization rate (0.6), and testosterone levels (0.5), along with a reduction in abnormal embryogenesis (−0.3) (p < 0.05). While an optimal level of SeNPs is effective for enhancing aquaculture performance, excessive use may lead to toxicity; therefore, their economic viability, environmental impact, and sustainability in large-scale aquaculture warrant further investigation. This review provides insights for researchers, policymakers, and industry stakeholders on the potential of SeNPs in advancing sustainable aquaculture through fish productivity and reproductive performance. Full article

Driven by stringent emission regulations, advanced combustion modes utilizing turbulent jet ignition technology are pivotal for enhancing the performance of marine low-speed natural gas dual-fuel engines. This review focuses on three novel combustion modes, yielding key conclusions: (1) Compared to the conventional DJCDC mode, the TJCDC mode exhibits a significantly higher swirl ratio and turbulence kinetic energy in the main chamber during initial combustion. This promotes natural gas jet development and combustion acceleration, leading to shorter ignition delay, reduced combustion duration, and a combustion center (CA50) positioned closer to the Top Dead Center (TDC), alongside higher peak cylinder pressure and a faster early heat release rate. Energetically, while TJCDC incurs higher heat transfer losses, it benefits from lower exhaust energy and irreversible exergy loss, indicating greater potential for useful work extraction, albeit with slightly higher indicated specific NOx emissions. (2) In the high-compression ratio TJCPC mode, the Liquid Pressurized Natural Gas (LPNG) injection parameters critically impact performance. Delaying the start of injection (SOI) or extending the injection duration degrades premixing uniformity and increases unburned methane (CH₄) slip, with the duration effects showing a load dependency. Optimizing both the injection timing and duration is, therefore, essential for emission control. (3) Increasing the excess air ratio delays the combustion phasing in TJCPC (longer ignition delay, extended combustion duration, and retarded CA50). However, this shift positions the heat release more optimally relative to the TDC, resulting in significantly improved indicated thermal efficiency. This work provides a theoretical foundation for optimizing high-efficiency, low-emission combustion strategies in marine dual-fuel engines. Full article