Search Results (20,733)

This study systematically investigates the high-velocity impact response and energy absorption characteristics of carbon fiber-reinforced plastic (CFRP)—aluminum foam (AlF) hybrid composite structures, aiming to address the growing demand for lightweight yet high-performance energy-absorbing materials in aerospace and protective engineering applications. Particular emphasis is placed on elucidating the influence of key geometric and material parameters, including the aspect ratio of the columns and the relative density of the AlF core. Experimental characterization was first performed using a split Hopkinson pressure bar (SHPB) apparatus to evaluate the dynamic compressive behavior of AlF specimens with four different relative densities (i.e., 0.163, 0.245, 0.374, and 0.437). A finite element (FE) model was then developed and rigorously validated against the experimental data, demonstrating excellent agreement in terms of deformation modes and force–displacement responses. Extensive parametric studies based on the validated FE framework revealed that the proposed CFRP-AlF composite structure achieves a balance between specific energy absorption (SEA) and peak crushing force, showing a significant improvement over conventional CFRP or AlF. The confinement effect of CFRP enables AlF to undergo progressive collapse along designated orientations, thereby endowing the CFRP-AlF composite structure with superior impact resistance. These findings provide critical insight for the design of next-generation lightweight protective structures subjected to extreme dynamic loading conditions. Full article

With the rapid development of energy transformation, the proportion of new energy is increasing, and the efficient trading mechanism of multi-microgrids can realize energy sharing to improve the consumption rate of new energy. A distributed multi-microgrid cooperative energy sharing strategy is proposed based on Nash bargaining. Firstly, by comprehensively considering the adjustable heat-to-electrical ratio, ladder-type positive and negative carbon trading, peak–valley electricity price and demand response, a multi-microgrid system with wind–solar-storage-load and combined heat and power is constructed. Then, a multi-microgrid cooperative game optimization framework is established based on Nash bargaining, and the complex nonlinear problem is decomposed into two stages to be solved. In the first stage, the cost minimization problem of multi-microgrids is solved based on the alternating direction multiplier method to maximize consumption rate and protect privacy. In the second stage, through the established contribution quantification model, Nash bargaining theory is used to fairly distribute the benefits of cooperation. The simulation results of three typical microgrids verify that the proposed strategy has good convergence properties and computational efficiency. Compared with the independent operation, the proposed strategy reduces the cost by 41% and the carbon emission by 18490kg, thus realizing low-carbon operation and optimal economic dispatch. Meanwhile, the power supply pressure of the main grid is reduced through energy interaction, thus improving the utilization rate of renewable energy. Full article

Concrete cracks and sulfate degradation severely compromise structural durability, highlighting the need for sustainable solutions to enhance longevity and minimize environmental impact. This study assesses the efficacy of bacterial self-healing technology utilizing Bacillus megaterium (BM) and Bacillus sphaericus (BS) in enhancing the resistance of concrete to sulfate attacks and improving its mechanical properties. Bacterial suspensions (1% and 2.5% of cement weight) were mixed with concrete containing silica fume or fly ash (10% of cement weight) and cured in freshwater or sulfate solutions (2%, 5%, and 10% concentrations). Specimens were tested for compressive strength, flexural strength, and microstructure using a Scanning Electron Microscope (SEM), Energy-Dispersive X-ray Spectroscopy (EDS), and X-ray diffraction (XRD) at various ages. The results indicate that a 2.5% bacterial content yielded the best performance, with BM surpassing BS, enhancing compressive strength by up to 41.3% and flexural strength by 52.3% in freshwater-cured samples. Although sulfate exposure initially improved early-age strength by 1.97% at 7 days, it led to an 8.5% loss at 120 days. Bacterial inclusion mitigated sulfate damage through microbially induced calcium carbonate precipitation (MICP), sealing cracks, and bolstering durability. Cracked specimens treated with BM recovered up to 93.1% of their original compressive strength, promoting sustainable, sulfate-resistant, self-healing concrete for more resilient infrastructure. Full article

The efficient and rational development of hydropower in the Lancang–Mekong River Basin can promote green energy transition, reduce carbon emissions, prevent and mitigate flood and drought disasters, and ensure the sustainable development of the entire basin. In this study, based on publicly available hydrometeorological observation data and satellite remote sensing monitoring data from 2001 to 2020, a machine learning model of the Lancang–Mekong Basin was developed to reconstruct the basin’s hydrological processes, and identify the occurrence patterns and influencing mechanisms of water-related hazards. The results show that, against the background of climate change, the Lancang–Mekong Basin is affected by the increasing frequency and intensity of extreme precipitation events. In particular, Rx1day, Rx5day, R10mm, and R95p (extreme precipitation indicators determined by the World Meteorological Organization’s Expert Group on Climate Change Monitoring and Extreme Climate Events) in the northwestern part of the Mekong River Basin show upward trends, with the average maximum daily rainfall increasing by 1.8 mm/year and the total extreme precipitation increasing by 18 mm/year on average. The risks of flood and drought disasters will continue to rise. The flood peak period is mainly concentrated in August and September, with the annual maximum flood peak ranging from 5600 to 8500 m³/s. The Stung Treng Station exhibits longer drought duration, greater severity, and higher peak intensity than the Chiang Saen and Pakse Stations. At the Pakse Station, climate change and hydropower development have altered the non-drought proportion by −12.50% and +15.90%, respectively. For the Chiang Saen Station, the fragmentation degree of the drought index time series under the baseline, naturalized, and hydropower development scenarios is 0.901, 1.16, and 0.775, respectively. These results indicate that hydropower development has effectively reduced the frequency of rapid drought–flood transitions within the basin, thereby alleviating pressure on drought management efforts. The regulatory role of the cascade reservoirs in the Lancang River can mitigate risks posed by climate change, weaken adverse effects, reduce flood peak flows, alleviate hydrological droughts in the dry season, and decrease flash drought–flood transitions in the basin. The research findings can enable basin managers to proactively address climate change, develop science-based technical pathways for hydropower dispatch, and formulate adaptive disaster prevention and mitigation strategies. Full article

This study investigates the influence of vacancy engineering and nitrogen doping on the structural, electronic, and optical properties of T-graphene fragments (TFs) using density functional theory (DFT) and time-dependent DFT (TD-DFT). A central vacancy and five pyridinic nitrogen doping configurations are explored to modulate the optoelectronic behavior. All systems are thermodynamically stable, exhibiting tunable HOMO–LUMO gaps, orbital distributions, and charge transfer characteristics. Optical absorption spectra show redshifts and enhanced oscillator strengths in doped variants, notably v-NTF2 and v-NTF4. Nonlinear optical (NLO) analysis reveals significant enhancement in both static and frequency-dependent responses. v-NTF2 displays an exceptionally high first-order hyperpolarizability (⟨β⟩ = 1228.05 au), along with a strong electro-optic Pockels effect (β (−ω; ω, 0)) and second harmonic generation (β (−2ω; ω, ω)). Its third-order response, γ (−2ω; ω, ω, 0), also exceeds 1.2 × 10⁵ au under visible excitation. Conceptual DFT descriptors and energy decomposition analysis further supports the observed trends in reactivity, charge delocalization, and stability. These findings demonstrate that strategic nitrogen doping in vacancy-engineered TFs is a powerful route to tailor electronic excitation, optical absorption, and nonlinear susceptibility. The results offer valuable insight into the rational design of next-generation carbon-based materials for optoelectronic, photonic, and NLO device applications. Full article

An in-depth investigation into the evolutionary characteristics, transmission mechanisms, and optimization pathways of electricity consumption linkages across China’s industrial sectors highlights their substantial theoretical and practical significance in achieving the “dual carbon” goals and advancing high-quality economic development. This study investigates the structural characteristics and developmental trends of electricity consumption linkages across China’s industrial sectors using an enhanced hypothetical extraction method. The analysis draws on national input–output tables and sector-specific electricity consumption data during the period from 2002 to 2020. Key transmission routes between industrial sectors are identified through path analysis and average path length calculations. The findings reveal that China’s industrial electricity consumption structure is marked by notable scale expansion and differentiation. The magnitude of inter-sectoral electricity flows continues to grow steadily. The evolution of these linkages exhibits clear phase-specific patterns, while the intensity of electricity consumption connections across sectors shows pronounced heterogeneity. Furthermore, the transmission path analysis revealed differentiated characteristics of electricity influence transmission, with generally shorter internal paths within sectors, significant cross-sectoral transmission differences, and manufacturing demonstrating good transmission accessibility with moderate path distances to major sectors. These insights provide a robust foundation for designing differentiated energy conservation policies, as well as for optimizing the overall structure of industrial electricity consumption. Full article

Addressing climate change and advancing clean energy transitions demand holistic approaches that capture complex, interconnected system behaviors. This review focuses on the application of causal loop diagrams (CLDs) as a core systems-thinking methodology to understand and manage dynamic feedback within environmental, social, and technological domains. CLDs visually map the reinforcing and balancing loops that drive climate risks, clean energy adoption, and sustainable development, offering intuitive insights into system structure and behavior. Through a synthesis of empirical studies and case examples, this paper demonstrates how CLDs help identify leverage points in renewable energy policy, carbon management, and ecosystem resilience. Despite their strengths in simplifying complexity and enhancing stakeholder communication, challenges remain—including data gaps, model validation, and the integration of diverse knowledge systems. The review also examines recent innovations that improve CLD effectiveness, such as hybrid modeling approaches and digital tools that enhance transparency and decision support. By emphasizing CLDs’ unique capacity to reveal feedback mechanisms critical for climate action and energy planning, this study provides actionable recommendations for researchers, policymakers, and practitioners seeking to leverage systems thinking for transformative, sustainable solutions. Full article

Under the background of “dual-carbon” strategy and global energy transition, the metallurgical industry, which accounts for 15–20% of industrial energy consumption, urgently needs to reduce the energy consumption and emission of DC power supply of electric furnaces. Aiming at the existing 400–800 V/≥3000 A industrial-frequency transformer-rectifier system with low efficiency, large volume, heat dissipation difficulties and other bottlenecks, this thesis proposes and realizes a high-frequency integrated DC power supply scheme for high-power electric furnaces: high-frequency transformer core and rectifier circuit are deeply integrated, which breaks through and reduces the volume of the system by more than 40%, and significantly reduces the iron consumption; multiple cores and three windings in parallel are used for the system. The topology of multiple cores and three windings in parallel enables several independent secondary stages to share the large current of 3000 A level uniformly, eliminating the local overheating and current imbalance; the combination of high-frequency rectification and phase-shift control strategy enhances the input power factor to more than 0.95 and cuts down the grid-side harmonics remarkably. The authors have completed the design of 100 kW prototype, magneto-electric joint simulation, thermal structure coupling analysis, control algorithm development and field comparison test, and the results show that the program compared with the traditional industrial-frequency system efficiency increased by 12–15%, the system temperature rise reduced by 20 K, electrode voltage increased by 10–15%, the input power of furnace increased by 12%, and the harmonic index meets the requirements of the traditional industrial-frequency system. The results show that the efficiency of this scheme is 12–15% higher than the traditional IF system, the temperature rise in the system is 20 K lower, the voltage at the electrode end is 10–15% higher, the input power of the furnace is increased by 12%, and the harmonic indexes meet the requirements of GB/T 14549, which verifies the value of the scheme for realizing high efficiency, miniaturization, and reliable DC power supply in metallurgy. Full article

This study evaluates the performance and energy trade-offs of three popular data processing libraries—Pandas, PySpark, and Polars—applied to GreenNav, a CO₂ emission prediction pipeline for urban traffic. GreenNav is an eco-friendly navigation app designed to predict CO₂ emissions and determine low-carbon routes using a hybrid CNN-LSTM model integrated into a complete pipeline for the ingestion and processing of large, heterogeneous geospatial and road data. Our study quantifies the end-to-end execution time, cumulative CPU load, and maximum RAM consumption for each library when applied to the GreenNav pipeline; it then converts these metrics into energy consumption and CO₂ equivalents. Experiments conducted on datasets ranging from 100 MB to 8 GB demonstrate that Polars in lazy mode offers substantial gains, reducing the processing time by a factor of more than twenty, memory consumption by about two-thirds, and energy consumption by about 60%, while maintaining the predictive accuracy of the model (R² ≈ 0.91). These results clearly show that the careful selection of data processing libraries can reconcile high computing performance and environmental sustainability in large-scale machine learning applications. Full article

Fintech and government effectiveness are encouraged to be considered in the campaign towards renewable energy transition. However, the literature on these factors is tilted towards their impact on carbon emissions and less on fintech and energy transition. To address this significant gap in the literature, this current study employs the Cross-Sectional Autoregressive Distributed Lag (CS-ARDL) to estimate the influence of fintech and government effectiveness on renewable energy transition and carbon emissions in selected Asian countries. The results reveal that in the long and short terms, government effectiveness encourages the transition to renewable energy; however, government effectiveness effect on carbon emissions is insignificant in both terms. Nevertheless, fintech is statistically not significant in affecting the renewable energy transition and carbon emissions. Based on the study findings, it is recommended that a strong governance system is required to achieve a clean energy transition. Full article

Traditional forced-air cooling systems suffer from excessive energy consumption and noise pollution. This study proposes an innovative passive cooling strategy through developing aqueous radiative cooling coatings made from a combination of TiO₂-decorated carbon nanotube (TiO₂-CNT) hybrids and polyacrylic acid (PAA), designed to simultaneously enhance the heat dissipation and improve the mechanical strength of the coating films. Based on CNTs’ exceptional thermal conductivity and record-high infrared emissivity, bead-like TiO₂-CNT architectures have been prepared as the filler in PAA. The TiO₂ nanoparticles were in situ grown on CNTs, forming a rough surface that can produce asperity contacts and enhance the strength of the TiO₂-CNT/PAA composite. Moreover, this composite enhanced heat dissipation and achieved remarkable cooling efficiency at a small fraction of the filler (0.1 wt%). The optimized coating demonstrated a temperature reduction of 23.8 °C at an operation temperature of 180.7 °C, coupled with obvious mechanical reinforcement (tensile strength from 13.7 MPa of pure PAA to 17.1 MPa). This work achieves the combination of CNT and TiO₂ nanoparticles for strong radiative cooling coating, important for energy-efficient thermal management. Full article

Hydrogen offers an effective pathway for the large-scale storage of renewable energy. For a tourist city located in a plateau region rich in renewable energy, hydrogen shows great potential for reducing carbon emissions and utilizing uncertain renewable energy. Herein, the wind–solar–hydrogen stand-alone and grid-connected systems in the plateau tourist city of Lijiang City in Yunnan Province are modeled and techno-economically evaluated by using the HOMER Pro software (version 3.14.2) with the multi-criteria decision analysis models. The system is composed of 5588 kW solar photovoltaic panels, an 800 kW wind turbine, a 1600 kW electrolyzer, a 421 kWh battery, and a 50 kW fuel cell. In addition to meeting the power requirements for system operation, the system has the capacity to provide daily electricity for 200 households in a neighborhood and supply 240 kg of hydrogen per day to local hydrogen-fueled buses. The stand-alone system can produce 10.15 × 10⁶ kWh of electricity and 93.44 t of hydrogen per year, with an NPC of USD 8.15 million, an LCOE of USD 0.43/kWh, and an LCOH of USD 5.26/kg. The grid-connected system can generate 10.10 × 10⁶ kWh of electricity and 103.01 ton of hydrogen annually. Its NPC is USD 7.34 million, its LCOE is USD 0.11/kWh, and its LCOH is USD 3.42/kg. This study provides a new solution for optimizing the configuration of hybrid renewable energy systems, which will develop the hydrogen economy and create low-carbon-emission energy systems. Full article

Improving carbon emission efficiency (CEE) is crucial for coordinating economic development and reducing carbon emissions. Drawing on panel data for 30 provinces in China from 2013 to 2022, this paper selects six key antecedent conditions guided by the Technology–Organization–Environment (TOE) framework. Then the dynamic qualitative comparative analysis (DQCA) is employed to explore CEE improvement pathways from a configurational perspective, and regression analysis is used to compare the driving effects of different pathways. The findings reveal that (1) single factors cannot independently achieve high CEE; instead, multiple factors must work synergistically to form various improvement pathways, including “technology–organization dual-driven”, “environment-dominated”, and “multi-equilibrium” pathways, with industrial structure upgrading as the core factor for improving CEE; (2) temporally, these improvement pathways demonstrate universality, while, spatially, they exhibit significant provincial heterogeneity; and (3) in terms of marginal effects, the “multi-equilibrium” pathway has the strongest driving effect on CEE. The findings provide valuable policy implications for developing targeted CEE enhancement strategies across provinces at different developmental stages. Full article

The transition to smart, zero-carbon cities relies on advanced, sustainable energy solutions, with artificial intelligence (AI) playing a crucial role in optimizing renewable energy management. This study evaluates state-of-the-art AI models for solar power forecasting, emphasizing accuracy, reliability, and environmental sustainability. Using operational data from Benban Solar Park in Egypt and Sakaka Solar Power Plant in Saudi Arabia, two of the world’s largest solar installations, the research highlights the effectiveness of hybrid AI techniques. The hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model outperformed other models, achieving a Mean Absolute Percentage Error (MAPE) of 2.04%, Root Mean Square Error (RMSE) of 184, Mean Absolute Error (MAE) of 252, and R² of 0.99 for Benban, and an MAPE of 2.00%, RMSE of 190, MAE of 255, and R² of 0.98 for Sakaka. This model excels at capturing complex spatiotemporal patterns in solar data while maintaining low computational CO₂ emissions, supporting sustainable AI practices. The findings demonstrate the potential of hybrid AI models to enhance the accuracy and sustainability of solar power forecasting, thereby contributing to efficient, resilient, and zero-carbon urban environments. This research provides valuable insights for policymakers and stakeholders aiming to advance smart energy infrastructure. Full article

LPG fuel supply systems are increasingly important for improving energy efficiency and reducing carbon emissions in the shipping industry. The primary objective of this research is to investigate the heat transfer phenomena to enhance the thermal performance of double-pipe heat exchangers (DPHEs) in LPG fuel supply systems. This study investigates the heat transfer performance of a glycol–steam double-pipe heat exchanger (DPHE) within an LPG fuel supply system under varying operating conditions. A computational model and methodology were developed and validated by comparing the numerical results with experimental data obtained from commissioning tests. Additionally, the effects of turbulence models and parametric variations were evaluated by analyzing the glycol–water mixing ratio and flow direction—both of which are critical operational parameters for DPHE systems. Numerical validation against the commissioning data showed a deviation of ±2% under parallel-flow conditions, confirming the reliability of the proposed model. With respect to the glycol–water mixing ratio and flow configuration, thermal conductance (UA) decreased by approximately 11% in parallel flow and 13% in counter flow for every 20% increase in glycol concentration. Furthermore, parallel flow exhibited approximately 0.6% higher outlet temperatures than counter flow, indicating superior heat transfer efficiency under parallel-flow conditions. Finally, the heat transfer behavior of the DPHE was further examined by considering the effects of geometric characteristics, pipe material, and fluid properties. This study offers significant contributions to the engineering design of double-pipe heat exchanger systems for LPG fuel supply applications. Full article