Search Results (645)

Carbon fiber-reinforced polymer (CFRP) composites are widely used in aerospace due to their excellent strength-to-weight ratio and tailorable properties. However, these properties critically depend on the CFRP curing cycle. The commonly adopted manufacturer-recommended curing cycle (MRCC), designed to accommodate the most conservative conditions, involves prolonged curing times and high energy consumption. To overcome these limitations, this study proposes an efficient and adaptable method to determine the optimal curing cycle. The effects of varying heating rates on resin dynamic and isothermal–exothermic behavior were characterized via reaction kinetics analysis using differential scanning calorimetry (DSC) and rheological measurements. The activation energy of the reaction system was substituted into the modified Sun–Gang model, and the parameters were estimated using a particle swarm optimization algorithm. Based on the curing kinetic behavior of the resin, CFRP compression molding process orthogonal experiments were conducted. A weighted scoring system incorporating strength, energy consumption, and cycle time enabled multidimensional evaluation of optimized solutions. Applying this curing cycle optimization method to a commercial epoxy resin increased efficiency by 247.22% and reduced energy consumption by 35.7% while meeting general product performance requirements. These results confirm the method’s reliability and its significance for improving production efficiency. Full article

Bi₆Fe₂Ti₃O₁₈ (BFTO) ceramics were synthesized via a solid-state reaction route using stoichiometric amounts of Bi₂O₃, TiO₂, and Fe₂O₃ powders. A thermal analysis of the powder mixture was conducted to optimize the heat treatment parameters. Energy-dispersive X-ray spectroscopy (EDS) confirmed the conservation of the chemical composition following calcination. Final densification was achieved through hot pressing. The crystal structure of the sintered samples, examined via X-ray diffraction at room temperature, revealed a tetragonal symmetry for BFTO ceramics sintered at 850 °C. Electron backscatter diffraction (EBSD) provided detailed insight into the crystallographic orientation and microstructure. Broadband dielectric spectroscopy (BBDS) was employed to investigate the dielectric response of BFTO ceramics over a frequency range of 10 mHz to 10 MHz and a temperature range of −30 °C to +200 °C. The temperature dependence of the relative permittivity (ε_r) and dielectric loss tangent (tan δ) were measured within a frequency range of 100 kHz to 900 kHz and a temperature range of 25 °C to 570 °C. The impedance data obtained from the BBDS measurements were validated using the Kramers–Kronig test and modeled using the Kohlrausch–Williams–Watts (KWW) function. The stretching parameter (β) ranged from ~0.72 to 0.82 in the impedance formalism within the temperature range from 200 °C to 20 °C. Full article

Enhancing the real-world performance of sustainably designed and certified green buildings remains a significant challenge, particularly in hot climates where efforts to improve thermal comfort often conflict with energy efficiency goals. In the United Arab Emirates (UAE), even newly constructed facilities with green building certifications present opportunities for retrofitting and performance optimization. This study investigates the energy and thermal comfort performance of a LEED Gold-certified, mixed-use university campus in Dubai through a calibrated digital twin developed using IES thermal modelling software. The analysis evaluated existing sustainable design strategies alongside three retrofit energy conservation measures (ECMs): (1) improved building envelope U-values, (2) installation of additional daylight sensors, and (3) optimization of fan coil unit efficiency. Simulation results demonstrated that the three ECMs collectively achieved a total reduction of 15% in annual energy consumption. Thermal comfort was assessed using operative temperature distributions, Predicted Mean Vote (PMV), and Predicted Percentage of Dissatisfaction (PPD) metrics. While fan coil optimization yielded the highest energy savings, it led to less favorable comfort outcomes. In contrast, enhancing envelope U-values maintained indoor conditions consistently within ASHRAE-recommended comfort zones. To further support energy reduction and progress toward Net Zero targets, the study also evaluated the integration of a 228.87 kW rooftop solar photovoltaic (PV) system, which offset 8.09% of the campus’s annual energy demand. By applying data-driven thermal modelling to assess retrofit impacts on both energy performance and occupant comfort in a certified green building, this study addresses a critical gap in the literature and offers a replicable framework for advancing building performance in hot climate regions. Full article

The sustainable development of Chinese cities is of long-term significance. Multiple environmental regulatory instruments aim to promote the parallel advancement of environmental conservation and economic growth. This study examines three batches of low-carbon city pilot (LCCP) programs, employing eco-efficiency as the outcome variable. Using conventional difference-in-differences (DID) models, time-varying DID models, and period-by-period propensity score matching DID (PSM-DID) models with city and time fixed effects, we investigate the comprehensive impact of pilot policies on both economic and environmental performance. Eco-efficiency, measured through the Data Envelopment Analysis (DEA) model, exhibits a strong correlation with energy consumption patterns, as carbon emissions and air pollutants predominantly originate from non-clean energy utilization. The analysis reveals that LCCP policies significantly enhance eco-efficiency. These findings demonstrate robustness across placebo tests, endogeneity treatments, and alternative outcome variable specifications. The first and third LCCP batches significantly improve eco-efficiency, whereas the second batch demonstrates no statistically significant effect. Significant impacts emerge in regions where cities hold pilot status while provinces do not; conversely, regions where both cities and provinces participate in pilot programs show no significant effects. Finally, from an energy consumption perspective, policy recommendations are proposed to further enhance eco-efficiency through regulatory instruments. Full article

Traditional energy conservation policies have primarily relied on economic incentives and informational campaigns. However, recent insights from behavioral and social sciences indicate that subtle behavioral interventions, particularly social nudges, can significantly influence household electricity use. This paper presents a structured review of 23 recent field studies examining how social nudging strategies, such as peer comparison, group identity, and normative messaging, have contributed to measurable reductions in electricity consumption. By analyzing intervention outcomes across different regions and formats, we identify key success factors, limitations, and policy implications. Special attention is given to ethical considerations, fairness in implementation, and potential challenges in sustaining behavior change. This study offers a framework for integrating social nudges into future energy policies, emphasizing their role as low-cost, scalable tools for promoting sustainable energy behavior. Full article

In the aluminum electrolysis production process, the traditional cell control method based on cell voltage and series current can no longer meet the goals of energy conservation, consumption reduction, and digital-intelligent transformation. Therefore, a new digital cell control technology that is centrally dependent on various process parameters has become an urgent demand in the aluminum electrolysis industry. Among them, the real-time online measurement of alumina concentration is one of the key data points for implementing such technology. However, due to the harsh production environment and limitations of current sensor technologies, hardware-based detection of alumina concentration is difficult to achieve. To address this issue, this study proposes a soft-sensing model for alumina concentration based on a long short-term memory (LSTM) neural network optimized by a weighted average algorithm (WAA). The proposed method outperforms BiLSTM, CNN-LSTM, CNN-BiLSTM, CNN-LSTM-Attention, and CNN-BiLSTM-Attention models in terms of predictive accuracy. In comparison to LSTM models optimized using the Grey Wolf Optimizer (GWO), Harris Hawks Optimization (HHO), Optuna, Tornado Optimization Algorithm (TOC), and Whale Migration Algorithm (WMA), the WAA-enhanced LSTM model consistently achieves significantly better performance. This superiority is evidenced by lower MAE and RMSE values, along with higher R² and accuracy scores. The WAA-LSTM model remains stable throughout the training process and achieves the lowest final loss, further confirming the accuracy and superiority of the proposed approach. Full article

Heritage building conservation plays a special role in addressing modern sustainability challenges by preserving the cultural identity, retrofitting, restoring, and renovating these structures to improve energy performance, which is crucial for revitalisation. This research aims to use Heritage Building Information Modelling (HBIM) to increase energy efficiency and environmental sustainability in historic buildings. Retrofitting heritage buildings presents unique challenges and opportunities to simultaneously reduce energy consumption and carbon emissions while maintaining historical integrity. Traditional approaches are often insufficient to meet heritage structures’ energy needs. Modern technologies such as information building modelling and energy simulations can offer solutions. HBIM is a vigorous digital framework that facilitates interdisciplinary collaboration and offers detailed insights into building restoration and energy modelling. HBIM supports the integration of thermal and energy efficiency measures while maintaining the authenticity of heritage architecture by creating a comprehensive database. Using a case study heritage building, this research demonstrates how retrofitting the different aspects of heritage buildings can improve energy performance. Evaluating the preservation of heritage buildings’ cultural and architectural values and the effectiveness of using HBIM to model energy performance offers a viable framework for sustainable retrofitting of heritage buildings. Full article

This study analyzes the evolution of Pakistan’s energy policies from 1990 to 2024, documenting their transition from a singular focus on generation capacity to an integrated approach prioritizing renewable energy and efficiency. Through a systematic literature review of 110 initially screened studies, with 50 meeting the inclusion criteria and 22 selected for in-depth analysis, we evaluated policy effectiveness and identified implementation barriers. Our methodology employed predefined criteria focusing on energy efficiency, environmental sustainability, and climate impact, utilizing the Web of Science and Scopus databases. Early policies like the National Energy Conservation Policy (1992) and the Energy Policy (1994) emphasized energy security through generation capacity expansion while largely neglecting renewable sources and efficiency improvements. The policy landscape evolved in the 2000s with the introduction of renewable energy incentives and efficiency initiatives. However, persistent challenges include short-term planning, inconsistent implementation, and fossil fuels dependence. Recent framework like the Alternative and Renewable Energy Policy (2019) and the National Energy Efficiency and Conservation Plan (2020–2025) demonstrate progress toward sustainable energy practices. However, institutional, financial, and regulatory barriers continue to constrain effectiveness. We recommend that Pakistan’s energy strategy prioritize the following: (1) long-term planning horizon; (2) enhanced fiscal incentives; and (3) strengthened institutional support to meet global energy security and climate resilience standards. These measures would advance Pakistan’s sustainable energy transition while supporting both energy security and environmental objectives. Full article

In response to the escalating global energy demands, the optimization of energy efficiency has emerged as a linchpin for sustainable development. This study considers the potential of energy conservation and emission reduction in one of the most economically vibrant and resource-intensive regions in China, the Yangtze River Economic Belt, encompassing 11 provinces and cities. The SBM-Undesirable model is used to measure the energy efficiency and analyze the temporal-spatial distribution. Moran’s I is employed to analyze the overall spatial pattern and local regional differences in energy efficiency. The systematic analysis shows that the temporal fluctuation exists in the development of energy efficiency, and the average of the Yangtze River Economic Belt exhibits a development pattern of “downstream > midstream > upstream” from the spatial perspective. The upstream region would require way more effort than others to decarbonize and improve efficiency. At the municipal level, the overall energy efficiency of 11 provinces and cities fails to reach an efficient state, and potential for improvement exists. Moreover, the potential model of energy conservation and emission reduction is constructed. We further explore the pathways of energy efficiency improvement for each region in the Yangtze River Economic Belt, including pathways of “High-Efficiency Type”, “High Emission Reduction Potential”, and “Extensive Development Type”. Full article

A maximum entropy (ME) methodology was used to infer the Hubble constant from the temperature anisotropies in cosmic microwave background (CMB) measurements, as measured by the Planck satellite. A simple cosmological model provided physical insight and afforded robust statistical sampling of a parameter space. The parameter space included the spectral tilt and amplitude of adiabatic density fluctuations of the early universe and the present-day ratios of dark energy, matter, and baryonic matter density. A statistical temperature was estimated by applying the equipartition theorem, which uniquely specifies a posterior probability distribution. The ME analysis inferred the mean value of the Hubble constant to be about 67 km/sec/Mpc with a conservative standard deviation of approximately 4.4 km/sec/Mpc. Unlike standard Bayesian analyses that incorporate specific noise models, the ME approach treats the model error generically, thereby producing broader, but less assumption-dependent, uncertainty bounds. The inferred ME value lies within 1σ of both early-universe estimates (Planck, Dark Energy Signal Instrument (DESI)) and late-universe measurements (e.g., the Chicago Carnegie Hubble Program (CCHP)) using redshift data collected from the James Webb Space Telescope (JWST). Thus, the ME analysis does not appear to support the existence of the Hubble tension. Full article

The existence of echoes in an acoustic event can ruin the capture of a spoken message and the perception of a piece of music. Likewise, in the performers’ area, clear hearing is essential for the coordination and execution of the ensemble. Bullrings are buildings with a circular plan in which echo-encouraging focalisations can occur. Since bullrings lack a roof, the density of reflections is lower than that in a closed area, and therefore strong isolated reflections perceived by the audience as an echo can be created. In this work, calculations of the echo parameter (Echo Criterion EK) and inspection of impulse responses and energy decay curves are obtained in an on-site measurement campaign in the audience zones and in arena areas where the EK parameter exceeds the thresholds. To this end, four bullrings very emblematic of the Iberian Peninsula together with a very prominent Roman amphitheatre in a relatively good state of conservation in the Roman province of Hispania comprise the study cases. Experimental results of the EK parameter and from acoustic simulation in two of the bullrings present good concordance and show that there is no echo for music in any of the venues in the spectator zones and that the most critical area is when source and receiver are both in the arena, where even double and triple echoes appear. Full article

Aeroponics efficiently conserves water and fertilizer but faces energy sustainability challenges in maintaining high productivity and quality. This study aimed to identify critical growth phases of lettuce affected by management modes and assess resource/energy efficiency (cost per unit yield) to inform the development of sustainability strategies for lettuce production in a lettuce-dominant aeroponics system integrated with radish. Three management modes were tested: M1 (constant nutrient solution concentrations), M2 (variable nutrient solution concentrations), and M3 (combined variable nutrient solution concentrations and preharvest short-duration continuous light for 48 h). Plant parameters were dynamically measured in a 30-day cultivation cycle. The results showed that the intercropped lettuce exhibited peak growth at 15–25 days after transplanting, and nutrient solution adjustment enhanced the shoot weight and quality, with synergistic quality improvements under M3. However, preharvest lighting reduced the net photosynthetic rate via stomatal closure and lowered the effective quantum yield of photosystem II, preventing biomass increase. The preharvest short-duration continuous light elevated the soluble protein, ascorbic acid, and soluble sugar contents. For yield-focused systems, M2 alone achieved comparable shoot weight to M3 with higher energy efficiency. However, when simultaneously considering lettuce quality enhancement and the yield boost of radish in the intercropping system, M3 demonstrated potential for greater marginal benefits. Full article

Temperature forecasting is critical for public safety, environmental risk management, and energy conservation. However, reliable forecasting becomes challenging in regions where governmental institutions lack adequate measurement infrastructure. To address this limitation, the present study aims to improve temperature forecasting by collecting temperature, pressure, and humidity data through IoT sensor networks. The study further seeks to identify the most effective method for the real-time processing of large-scale datasets generated by sensor measurements and to ensure data reliability. The collected data were pre-processed using Discrete Wavelet Transform (DWT) to extract essential features and reduce noise. Subsequently, three wavelet-processed deep-learning models were employed: Wavelet-processed Artificial Neural Networks (W-ANN), Wavelet-processed Long Short-Term Memory Networks (W-LSTM), and Wavelet-processed Bidirectional Long Short-Term Memory Networks (W-BiLSTM). Among these, the W-BiLSTM model yielded the highest performance, achieving a test accuracy of 97% and a Mean Absolute Percentage Error (MAPE) of 2%. It significantly outperformed the W-LSTM and W-ANN models in predictive accuracy. Forecasts were validated using data obtained from the Turkish State Meteorological Service (TSMS), yielding a 94% concordance, thereby confirming the robustness of the proposed approach. The findings demonstrate that the W-BiLSTM-based model enables reliable temperature forecasting, even in regions with insufficient governmental measurement infrastructure. Accordingly, this approach holds considerable potential for supporting data-driven decision-making in environmental risk management and energy conservation. Full article

The increasing penetration of distributed energy resources (DERs) and power electronic loads challenges the modeling and control of modern distribution networks (DNs). The traditional models often fail to capture the complex aggregate dynamics required for advanced control strategies. This paper proposes a novel framework for DN power regulation based on Neural Ordinary Differential Equations (NODEs) and Model Predictive Control (MPC). NODEs are employed to develop a data-driven, continuous-time dynamic model capturing the aggregate relationship between the voltage at the point of common coupling (PCC) and the network’s power consumption, using only PCC measurements. Building upon this NODE model, an MPC strategy is designed to regulate the DN’s active power by manipulating the PCC voltage. To ensure computational tractability for real-time applications, a local linearization technique is applied to the NODE dynamics within the MPC, transforming the optimization problem into a standard Quadratic Programming (QP) problem that can be solved efficiently. The framework’s efficacy is comprehensively validated through simulations. The NODE model demonstrates high accuracy in predicting the dynamic behavior in a DN against a detailed simulator, with maximum relative errors below 0.35% for active power. The linearized NODE-MPC controller shows effective tracking performance, constraint handling, and computational efficiency, with typical QP solve times below 0.1 s within a 0.1 s control interval. The validation includes offline tests using the NODE model and online co-simulation studies using CloudPSS and Python via Redis. Application scenarios, including Conservation Voltage Reduction (CVR) and supply–demand balancing, further illustrate the practical potential of the proposed approach for enhancing the operation and efficiency of modern distribution networks. Full article

Background/Objectives: Additive manufacturing (AM) enables the production of cementless acetabular cups with porous surfaces that facilitate early osseointegration. Directed energy deposition (DED), a form of AM, allows the direct welding of porous structures onto metal substrates without requiring a vacuum environment, offering advantages over conventional powder bed fusion methods. Despite growing interest in DED, no prospective clinical studies evaluating DED-based acetabular components have been published to date. This study assessed short-term outcomes of a DED-based 3D-printed acetabular cup in total hip arthroplasty (THA). Methods: A total of 120 patients who underwent primary cementless THA using the Corentec Mirabo Z^® acetabular cup were prospectively enrolled. Among them, 124 hips from 100 patients who had completed a minimum of 24 months of follow-up were included in the analysis. Clinical outcomes were assessed using the Harris hip score (HHS), WOMAC, EQ-5D-5L, and pain NRS. Radiographic evaluation included measurements of cup position, osseointegration, and detection of interfacial or polar gaps on CT and plain radiographs. Implant-related complications were also recorded. Results: At a mean follow-up of 34.6 months, the implant survival rate was 99.3%, with one revision due to suspected osseointegration failure. The HHS improved from 56.6 to 91.4 at 24 months, and the NRS decreased from 6.2 to 1.1 (both p < 0.001). Interfacial gaps were observed in 58.1% of cases on CT, though most were <1 mm and not clinically significant. Common postoperative issues included greater trochanteric pain syndrome, squeaking, and iliotibial band tightness, all of which were resolved with conservative treatment. Conclusions: DED-based 3D-printed acetabular cups demonstrated favorable short-term clinical and radiographic outcomes, with high survivorship and reliable early osseointegration in cementless THA. Full article