Search Results (22,008)

Aging populations have intensified the demand for thermally comfortable and energy-efficient housing, particularly for elderly residents whose diminished thermoregulatory capacity renders them disproportionately vulnerable to indoor temperature fluctuations. Existing senior apartments in cold-climate regions frequently fail to meet age-specific thermal comfort standards, yet systematic retrofit optimization frameworks explicitly tailored to elderly occupants remain scarce. This study presents a data-driven multi-objective optimization framework for building envelope retrofitting, which is validated using on-site temperature measurements from a representative 1980s brick–concrete senior apartment building in Beijing. The framework integrates Latin Hypercube Sampling (LHS) for design space exploration, a Long Short-Term Memory (LSTM) surrogate model for simultaneous prediction of three performance objectives, and Non-dominated Sorting Genetic Algorithm II (NSGA-II) for Pareto-optimal solution generation, with final selection performed via a weighted Mahalanobis distance-based Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Optimization targets—annual energy consumption, indoor thermal discomfort hours, and retrofit cost—are parameterized using the age-sensitive comfort thresholds specified in GB 50340-2016. The LSTM surrogate achieved R² values of 0.91–0.93 across all objectives with training–testing differences below 0.02. The optimal retrofit package—Polyvinyl Chloride (PVC) Low Emissivity (Low-E) double-glazed windows (5 + 6A + 5), glass fiber roof insulation (65.25 mm), and Extruded Polystyrene (XPS) external wall insulation (65.39 mm)—reduces annual energy consumption by 47.1% (from 40,867 to 21,626 kWh) and annual thermal discomfort hours by 62.4% (from 2454 °C·h to 923 °C·h). SHapley Additive exPlanations (SHAP)-based sensitivity analysis further identifies wall U-value and roof thickness as the dominant performance drivers. A reproducible and computationally efficient pathway is provided by the proposed framework for evidence-based envelope retrofit decision-making in existing senior residential buildings. Full article

Renewable energy sources, such as solar and biomass, represent sustainable alternatives to meet the growing energy demands of the residential sector. This study evaluated the energy, exergy, and environmental performance of two Brayton configurations using supercritical carbon dioxide: a recompression cycle (SRC) and a recompression cycle with intercooling in the main compression (SMC), both coupled to a dual-loop organic Rankine cycle (DORC) and powered by a hybrid solar-biomass thermal system. Mass, energy, and exergy balances were developed, and a life cycle assessment was performed to quantify the environmental impact. The systems were designed to cover a cooling load of 130 kW corresponding to 200 dwellings constructed with Asbestos cement in the Colombian Caribbean region. The results show that both configurations meet the required demand; the SMC-DORC cycle operates at 650 °C, while the SRC-DORC requires 750 °C. The SRC-DORC exhibits higher thermal efficiency (53.24%), while the SMC-DORC achieves a slightly higher exergy efficiency (28.15%). Environmental analysis shows that the construction phase accounts for the majority of the total impact, exceeding 95% of emissions. Overall, both configurations are technically feasible, with the SRC-DORC standing out for its balance between efficiency and environmental impact. Full article

The field of nanoparticle-based biotechnology has undergone substantial advancement, characterized by progress in targeted drug delivery systems, the development of innovative diagnostic and imaging platforms, the expanded adoption of environmentally sustainable (“green”) synthesis approaches, and an increasing emphasis on the integration of emerging technologies such as artificial intelligence and nanorobotics. Conventional nanoparticle synthesis often involves toxic reducing agents; however, recent advances promote eco-friendly green synthesis methods utilizing biological systems such as bacteria, fungi, algae, yeast, plants, and actinomycetes. These biological approaches are safe, sustainable, cost-effective, and capable of producing highly stable Nanoparticles (NPs). The interaction of nanomaterials with biological systems is crucial for developing intracellular and subcellular drug delivery technologies with minimal toxicity, governed by nano–bio interface mechanisms such as cellular translocation, surface wrapping, embedding, and internal attachment. Key factors influencing NP behavior include morphology, size, surface area, surface charge, and ligand chemistry. Magnetic nanoparticles, particularly iron-based forms, exhibit unique superparamagnetic properties that are strongly influenced by particle size, as explained by the Néel relaxation mechanism, in which thermal energy induces flipping of magnetic moments. Nanoparticles demonstrate diverse modes of action, including antimicrobial activity, reactive oxygen species (ROS)-induced cytotoxicity, genotoxicity, and plant growth promotion. NP performance and biological effects are strongly dependent on their size, shape, dosage, and concentration. This critical review article aims to elucidate evolution, classification, preparation methods, and multifaceted applications of nanoparticles Full article

Mechanically activated pyrite plays an important role in gold extraction and coal utilization, but its reactivity may change markedly during storage. This study investigates how air deactivation during storage affects the crystal structure and subsequent thermal decomposition behavior of mechanically activated pyrite. Pyrite was mechanically activated and then stored in air for 0, 7 and 180 days. X-ray diffraction (XRD) combined with Rietveld refinement was used to characterize variations in lattice parameters and unit-cell-related structural features, while non-isothermal thermogravimetric–differential scanning calorimetry (TG-DSC) under an argon atmosphere, together with the Flynn–Wall–Ozawa (FWO) method, was applied to evaluate the decomposition kinetics. Air deactivation induced a non-monotonic evolution of lattice parameters and unit-cell volume, which is attributed to combined effects of residual stress relaxation and air-induced surface-related modification during storage. All samples exhibited two mass-loss stages during heating, reflecting stepwise thermal decomposition, and their decomposition behavior varied systematically with deactivation time. The apparent activation energy depended on both conversion fraction and deactivation degree, and nucleation-and-growth-type mechanisms were found to dominate the decomposition process, with their relative contributions evolving with storage time. These results clarify how prior air-deactivation history influences the structural evolution and subsequent thermal decomposition behavior of mechanically activated pyrite and provide useful insight for its storage and utilization in related processes. Full article

District heating systems play a critical role in urban energy supply; however, secondary networks suffer from frequent sensor failures that undermine thermal balance control. The development of virtual sensors to estimate return-water temperatures offers a promising solution to this challenge. This study investigates the performance of different feature selection methods for developing virtual sensors. The investigated feature selection methods include two engineering experience-based methods, one embedded method, one wrapped-based method, and two filter methods. Using operational data from a real secondary district heating network over an entire heating season, the embedded method’s performance is investigated, and an appropriate machine learning algorithm, paired with the wrapped and filter methods, is selected. For the filter methods, the paper additionally examines the differences between the rank-based and threshold-based filter implementations. The performance of the wrapped and filter methods on accuracy, computational cost, and sensitivity to data volume was compared. The results indicate that the embedded method exhibits relatively unstable performance under the engineering experience-based baselines, but the gradient tree boosting (GTB) method demonstrates better performance in both accuracy and stability. Further tests combining GTB with wrapped and filter methods revealed that both the filter and wrapped methods show an acceptable performance in terms of accuracy. The mean RMSE of both filter and wrapped methods consistently ranges from 0.75 °C to 0.8 °C when the selected feature is more than 6. However, the wrapped method exhibits a higher computational cost and is more sensitive to data volume. The training time of the wrapped method is approximately 136 times that of the fastest filter method. Considering overall performance, the combination of GTB with an HSIC indicator, employing either the rank-based selection of the top 9 features or the threshold-based feature selection, is recommended. These findings provide methodological guidance for the development of virtual sensors in district heating systems. Full article

With increasingly stringent greenhouse gas emission regulations in the shipping industry, there is an urgent need for an efficient energy management strategy for new energy ship power systems. However, existing dispatch models often overlook the dynamic energy-saving potential of active drag reduction technologies and lack effective optimization algorithms capable of handling high-dimensional, multi-constrained problems. To address these problems, this paper proposes a novel integrated dispatch framework for hybrid energy ship power systems that incorporates air lubrication systems. First, a unified multi-energy dispatch model is established, coupling the dynamic operation of air lubrication systems with electrical, thermal, and propulsion energy flows. Second, an Improved Traffic Jam Optimizer algorithm is proposed, which enhances global exploration and local exploitation through a nonlinear parameter adaptation mechanism, differential mutation strategy, and dynamic hybrid search architecture. Convergence analysis based on Markov chain theory is provided to guarantee algorithmic reliability. Simulation results demonstrate that the proposed algorithm outperforms existing methods in terms of convergence speed, solution accuracy, and stability. Furthermore, integrating air lubrication systems into the ship power system reduces total operating costs and greenhouse gas emissions by up to 20.569% and 6.310%, respectively. Full article

Accurate prediction of energy consumption is essential for the operation and charging management of battery-electric buses. Existing prediction studies are often constrained by incomplete or low-resolution input data, limiting their robustness under real-world operating conditions. This paper presents a high-resolution, sensor-rich energy consumption modeling framework using second-by-second operational data and tests on an electric bus fleet operating on Route 49 in Jinan, China. The dataset integrates synchronized measurements of vehicle kinematics, powertrain variables, and thermal conditions, providing a substantially more complete description of bus operation against previous studies. Boosting-based machine learning models are developed to predict the instantaneous power demand, and their performance is evaluated in comparison with a physics-based energy model and other variants of machine learning models. Results show that the data-driven boosting models demonstrate excellent explanatory power ($R^2$ values of up to 0.99 (training) and 0.95 (test)) and remain reliable under nonlinear operating conditions. Feature and SHAP analyses identify physically consistent energy drivers, supporting the applicability of the approach to real-world public transport operations. Full article

This paper describes the thermal and energy performance of three roof configurations: a conventional concrete slab, a BIPV system, and a BIPV system equipped with passive aluminum fins. Three-dimensional transient finite element simulations were carried out under field-measured 24 h meteorological boundary conditions characteristic of hot climates. The objective of this study is to quantify the impact of PV integration and passive cooling strategies on heat transfer behavior and building energy performance. The BIPV roof achieved a 38.4% lower residual temperature than the concrete slab at 19:00, indicating superior heat dissipation. The addition of passive fins reduced module temperature by up to 10–12 °C and decreased peak roof temperature by up to 12%. This temperature reduction decreased electrical losses from 13.2% to 10.4%, resulting in a 21% relative reduction in temperature-induced losses. The predicted temperature ranges (≈60–75 °C under peak conditions) are consistent with values reported in experimental and numerical studies of BIPV systems in hot climates, supporting the physical realism of the model. Convective heat transfer was represented using effective coefficients, providing a computationally efficient engineering approximation of air-side heat exchange. Despite construction cost increases of up to 38%, PV integration achieved competitive payback periods of approximately 8.5–9 months under hot climate conditions. This economic assessment is based on a simple payback approach using an incremental cost formulation, where the photovoltaic system replaces the conventional concrete roof, reducing the effective investment. This study introduces a reproducible 3D transient FEM methodology for evaluating BIPV roofs under field-measured climatic boundary conditions. The framework explicitly couples geometry-resolved passive cooling, full-day thermal evolution, and temperature-dependent electrical losses, providing a physically consistent basis for assessing BIPV design alternatives in hot climates. Full article

In the Philippines’ agricultural setup, pre-harvest cacao (Theobroma cacao) fruits are wrapped with low-density polyethylene (LDPE) for moisture retention and damage protection. Responding to the growing concern for its waste volume and scarcity of treatment, this research explores the co-hydrothermal carbonization (co-HTC) of cacao shells (CS) and LDPE as a method to convert agricultural waste with plastic into hydrochar for potential energy applications. Thus, observations on the thermal, physicochemical, and morphological changes from feedstocks to hydrochar are carried out. Optimal conditions of 200 °C for 60 min resulted in hydrochar with 21.11 MJ/kg and appreciable thermal properties. SEM micrographs show that hydrochar had increased surface area, a good fuel characteristic, and surface flaking on oversized LDPE film, suggesting relative LDPE degradation. EDX analysis reveals C, K, Ca, and Zn metals that affect chemical pathways. FTIR analysis further supports chemical synergy by preservation of functional groups innate from both parent materials. Kinetic and thermal evolutions are also investigated to reveal the influence of pretreatment on the stability of cacao shell-dominated hydrochar and the effectivity of biomass integration to facilitate relatively easier cracking of LDPE. The findings support co-HTC as a viable technology to enhance the circular economy by valorizing LDPE and cacao shells while promoting energy recovery and solid fuel production. Full article

This study investigates the thermal and vibration-attenuation performance of a novel 7-inch FPV drone frame manufactured from cast AZ31 magnesium alloy (MG), compared to 6061-T6 aluminum (AL) and carbon fiber (CF) composite structures under an extreme payload of 2 kg. Using quantitative spectral analysis of Blackbox flight logs, the research demonstrates that the MG frame provides superior system-level vibration damping, particularly under high-stress conditions. Under a 2 kg payload, the MG frame exhibited a 49% reduction in vibration power compared to the AL frame. Spectral data identified primary resonance peaks for the MG frame at 147 Hz (0 kg) and 204 Hz (2 kg), whereas the AL frame showed significantly higher frequency peaks at 179.5 Hz (0 kg) and 239.4 Hz (2 kg). Comparative modal hammer tests further validated these findings, with the magnesium design exhibiting lower impulse energy (0.22 mW/Hz) and faster decay than aluminum (0.24 mW/Hz). Thermal imaging analysis showed better motor cooling for the metallic frames; average motor temperatures on the magnesium frame (51.8 °C) and AL frame (50.3 °C) were significantly lower than on the CF structure (77.5 °C). The findings establish that AZ31 magnesium alloy offers an excellent synergy of lightweight stiffness and damping capacity, making it a viable alternative for heavy-duty FPV platforms requiring high signal integrity. Full article

The significant heat generated during the refueling of hydrogen pressure tanks may exceed the permissible 85 °C temperature limit for type IV tanks. Common countermeasures such as hydrogen pre-cooling or long filling times are energy- and time-consuming; hence, in this paper, passive means through thermally better-suited materials are examined. State-of-the-art and alternative materials are first characterized and finally compared using a transient heat model. Different material combinations are compared in terms of the maximum temperature and weight in a typical filling scenario. As alternative liner materials, thermoplastics filled with short carbon fibers, minerals, and graphite were selected to improve thermal properties. For the composite overwrap, copper-coated carbon fibers were chosen. The findings show that the liner is the bottleneck while transferring heat from the inner to the outer tank surface. Using graphite-filled thermoplastics as the liner material shows the greatest potential regarding thermal optimization with only a slight weight increase. Using copper-coated carbon fibers additionally further reduces the maximum temperature but results in a significant weight increase. Full article

Mesophase pitch (MP) is a high-performance precursor for carbon materials. However, its conventional preparation process is limited by stringent conditions and high costs. In this study, heavy coal tar (HCT) was used as a low-cost carbon source, and polyethylene (PE) was introduced as a modifier to induce MP formation under relatively mild conditions, thereby promoting the thermal polycondensation of HCT. Characterization results show that the addition of different types of PE facilitates the condensation of aromatic molecules and significantly enhances the conversion efficiency of HCT to MP. Among the tested PE types, HDPE exhibits the best performance, with an optimal addition of 6 wt.% at 400 °C, yielding the highest number of uniform mesophase carbon microspheres and the most ordered structure. Based on comprehensive characterization data, an average molecular structure model of the product was constructed, addressing a research gap regarding the role of PE in the thermal polycondensation of HCT. This work provides a new pathway for the energy-efficient preparation and property regulation of MP. Full article

Aerogels represent an extraordinary class of materials characterized by remarkable properties, including an exceptionally high porosity (approximately 99.8%), minimal weight, extraordinarily low density, low thermal conductivity, a diminished dielectric constant, and a reduced refractive index. These attributes arise from their extensive micro-meter-sized pores. In recent years, there has been a notable surge of interest in carbon or carbon nanotube (CNT) based aerogels due to their compelling potential across various applications, encompassing sensors, energy systems, and catalysis, among others. In the context of our ongoing investigation, we have successfully synthesized lightweight aerogels by incorporating copper and carbon nanotubes (Cu-CNT) through electrospinning. Intriguingly, these aerogels exhibit an electrical conductivity of approximately 0.5 × 103 S/cm, positioning them within the realm of semiconductors. Concurrently, their density measures approximately 1.669 g/c.c (similar to CNTs), underscoring their notably low mass. These semi-conductive aerogels, uniquely characterized by their lightweight nature and expansive surface area (approximately 442 m²/g), manifest considerable potential across a spectrum of applications. This includes catalytic processes, energy storage mechanisms, bio-sensing technologies, thermoelectric systems, and the burgeoning domains of micro and wearable electronics. The distinctive combination of properties within these aerogels augments their suitability for these diverse applications, offering the prospect of innovative and impactful advancements in various scientific and technological arenas. Full article

The Janus monolayers have recently attracted substantial interest due to their unique asymmetric structures and intriguing physical properties. In this work, we explore the thermoelectric properties of the Janus monolayer ZrBrI, using first-principles calculations and Boltzmann transport theory. We demonstrate that the system maintains good dynamic and thermal stability, as evidenced by the absence of imaginary phonon modes and small lattice fluctuation at a higher temperature of 600 K. The hybrid functional calculations reveal that the monolayer exhibits a relatively small indirect gap of 1.22 eV, and the energy bands near the conduction band minimum exhibit double degeneracy with weak dispersions, which is very beneficial for enhancing the n-type power factor. Meanwhile, a relatively lower lattice thermal conductivity is found due to strong lattice anharmonicity caused by the antibonding state and the symmetry breaking of the structure. Collectively, a larger ZT value of 3.9 at 600 K can be realized for the n-type Janus monolayer ZrBrI at an optimal concentration of $1.89\times {10}^{13} {\mathrm{cm}}^{-2}$, highlighting its promising thermoelectric application in the intermediate temperature region. Full article

Electric energy metering cabinets serve as critical nodes in power grid operations, providing essential protection for key components in distribution networks. Under environmental stressors, the non-metallic casings of electric energy metering cabinets are susceptible to aging-induced performance degradation, which may result in electrical safety hazards. However, rapid and precise methods for evaluating the performance of these non-metallic casings are still lacking. Laser-induced breakdown spectroscopy (LIBS), capable of rapid multi-element detection with non-contact analytical advantages, was employed in this study. Thermal aging experiments were conducted to investigate the performance degradation mechanisms of sheet molding compound (SMC)—a representative non-metallic cabinet material. The research analyzed time-dependent trends in material performance and microstructural evolution during aging. By integrating LIBS with multi-analytical techniques, this study further explored the feasibility of quantitatively evaluating the bending strength of thermally aged SMC, which has rarely been reported in previous studies. Based on LIBS spectral data, bending strength characterization revealed its attenuation patterns with aging duration. The relationships between bending strength and plasma temperature, as well as the characteristic line intensity ratios of K, Al, and Ca, were systematically examined. A multivariate linear regression model incorporating these key variables was subsequently developed, yielding a high coefficient of determination (R² = 0.9657) between the predicted and measured bending strength values. This model represents a promising initial step, but further validation with a larger dataset is necessary to enhance its reliability and generalizability. Full article