Search Results (4,511)

Coal gangue concrete (CGC), a recycled cementitious material derived from industrial solid waste, presents both opportunities and challenges for structural applications due to its heterogeneous composition and variable mechanical behavior. This study develops an ensemble learning framework—incorporating XGBoost, LightGBM, and CatBoost—to predict four key constitutive parameters based on experimental data. The predicted parameters are subsequently incorporated into an ABAQUS finite element model to simulate the compressive–bending response of CGC columns, with simulation results aligning well with experimental observations in terms of failure mode, load development, and deformation characteristics. To enhance model interpretability, a hybrid approach is adopted, combining permutation-based global feature importance analysis with SHAP (SHapley Additive exPlanations)-derived local explanations. This joint framework captures both the overall influence of each feature and its context-dependent effects, revealing a three-stage stiffness evolution pattern—brittle, quasi-ductile, and re-brittle—governed by gangue replacement levels and consistent with micromechanical mechanisms and numerical responses. Coupled feature interactions, such as between gangue content and crush index, are shown to exacerbate stiffness loss through interfacial weakening and pore development. This integrated approach delivers both predictive accuracy and mechanistic transparency, providing a reference for developing physically interpretable, data-driven constitutive models and offering guidance for tailoring CGC toward ductile, energy-absorbing structural materials in seismic and sustainability-focused engineering. Full article

Background/Objectives: Stroke survivors with dysphagia are usually fed with different feeding routes ranging from oral to percutaneous endoscopic gastrostomy (PEG). However, the impact of the feeding route on the gastric myoelectric activity (GMA) is little-studied. This work examined the effect of feeding route on GMA changes in stroke survivors with dysphagia. Methods: This study included 50 patients (20% women) who were divided into three groups based on their feeding route: an oral group (n = 20), a nasogastric group (NGT) (n = 20), and a PEG group (n = 10). For all participants, a nutritional assessment was conducted, and the GMA was measured using a transcutaneous multichannel electrogastrogram (EGG) with a water load satiety test before and after water loading. The EGG-related parameters used in the analysis included the average power distribution by frequency region and the average dominant frequency (ADF). Results: The study sample experienced ischemic stroke (66%) or hemorrhagic stroke (34%). At the baseline phase, the PEG group exhibited significantly longer periods of normogastria compared to the NGT and oral groups. Moreover, protein intake was significantly higher in the PEG tube feeding group compared to the other groups. Based on the type of stroke, the ischemic stroke group showed significantly higher tachygastria periods during postprandial EGG recording (p = 0.022). The energy and protein consumptions were significantly higher in the hemorrhagic stroke group (p = 0.001, p = 0.028, respectively). Conclusions: The GMA pattern is distinctive for the type of stroke. The PEG feeding route showed more periods with normogastria and the best protein intake. Full article

Retrotransposons exhibit increased activity in cancer cells. One possible approach to anticancer therapy is to use this activity to influence the energy balance in cells. Abnormal distribution of retrotransposons in the genome requires additional energy consumption, which can lead to a significant decrease in the total amount of free ATP molecules in the cell. A decrease in ATP levels below a certain threshold can in turn trigger a cell death program. To investigate the possibility of such a scenario, we developed a mathematical model of the cellular energy balance that describes the dynamics of energy consumption by the main cellular processes, including costs of retrotransposon activity. The model considers changes in the concentrations of ATP, active retrotransposons (LINE-1 and SINE) in the human genome, as well as mRNAs and proteins that are expression products of retrotransposon and constitutive genes. We estimated the parameter values in the model based on literature data and numerical optimization. We found a single stable stationary solution, characterized by low retrotransposon activity, and used it as the reference steady state for further analysis. Parametric sensitivity analysis revealed the parameters whose changes had the greatest impact on cellular ATP levels. The LINE-1 deactivation rate constant and the maximum LINE-1 transcription rate were the most sensitive among the transposon-related parameters. Perturbation of these parameters led to a decrease in the number of free ATP to 30% of the reference value and below. Transcription of retrotransposons under perturbed parameters became comparable to the translation of constitutive genes in terms of energy costs. The presented results indicate that cancer cell death can be initiated by increasing the load on the energy balance due to the activation of transposons. Full article

Amid escalating climate challenges, China’s carbon neutrality objectives necessitate energy electrification as a pivotal strategy. As a critical load hub, East China demonstrates significant trends toward cleaner energy—marked by growing renewable energy penetration and accelerated cross-regional direct current (DC) transmission deployment. Ensuring stable and efficient grid operation requires rigorous assessment of the impacts of ultra-high voltage DC (UHVDC) integration on grid stability. This study introduces the transient multi-feed-in short circuit ratio (TMSCR), a novel metric for evaluating new DC transmission systems’ influence on grid performance. We systematically investigate UHVDC integration within the East China power grid, emphasizing strategic DC landing point placement. Using TMSCR, the effects of diverse DC incorporation methods are analyzed. Furthermore, this research examines impacts of new DC connections on local and main grids, proposing targeted mitigation measures to enhance grid resilience. This comprehensive UHVDC impact analysis addresses a critical literature gap, providing actionable insights for East China power grid planning and establishing a foundation for subsequent grid planning and DC project feasibility studies during the ‘15th Five-Year Plan’ period. Full article

This paper aims to explore Virtual Power Plants (VPPs) in combination with Demand Response (DR) concepts, integrating solar power generation, Electric Vehicle (EV) charging and discharging, and user loads to establish an optimal energy management scheduling system. Willingness curves for load curtailment are derived based on the consumption patterns of industrial, commercial, and residential users, enabling VPPs to design DR mechanisms under Time-of-Use (TOU), two-stage, and critical peak pricing periods. An energy management model for a VPP is developed by integrating DR, EV charging and discharging, and user loads. To solve this model and optimize economic benefits, this paper proposes an Improved Wolf Pack Search Algorithm (IWPSA). Based on the original Wolf Pack Search Algorithm (WPSA), the Improved Wolf Pack Search Algorithm (IWPSA) enhances the key behaviors of detection and encirclement. By reinforcing the attack strategy, the algorithm achieves better search performance and improved stability. IWPSA provides a parameter optimization mechanism with global search capability, enhancing searching efficiency and increasing the likelihood of finding optimal solutions. It is used to simulate and analyze the maximum profit of the VPP under various scenarios, such as different seasons, incentive prices, and DR periods. The verification analysis in this paper demonstrates that the proposed method can not only assist decision makers in improving the operation and scheduling of VPPs, but also serve as a valuable reference for system architecture planning and more effectively evaluating the performance of VPP operation management. Full article

This study evaluated the feasibility of reusing abandoned copper mine tailings (Cu tailings) as a precursor in the production of fly-ash-based alkali-activated materials (FA-AAMs). Two formulations were developed by combining FA and Cu tailings with a mixture of sodium silicate and sodium hydroxide as alkaline activators at room temperature (20 °C). Formulation G1 consisted of 70% Cu tailings and 30% fly ash (FA), whereas G2 included the same composition with an additional 15% ordinary Portland cement (OPC). The materials were characterized using X-ray fluorescence (XRF), -X-ray diffraction (XRD), field emission scanning electron microscopy with energy-dispersive spectroscopy (FESEM-EDS), and particle size analysis. While FA exhibited a high amorphous content (64.4%), Cu tailings were largely crystalline and acted as inert fillers. After 120 days of curing, average compressive strength reached 24 MPa for G1 and 41 MPa for G2, with the latter showing improved performance due to synergistic effects of geopolymerization and OPC hydration. Porosity measurements revealed a denser microstructure in G2 (35%) compared to G1 (52%). Leaching tests confirmed the immobilization of hazardous elements, with arsenic concentrations decreasing over time and remaining below regulatory limits. Despite extended setting times (24 h for G1 and 18 h for G2) and the appearance of surface efflorescence, both systems demonstrated good chemical stability and long-term performance. The results support the use of Cu tailings in FA-AAMs as a sustainable strategy for waste valorization, enabling their application in non-structural and moderate-load-bearing construction components or waste encapsulation units. This approach contributes to circular economy goals while reducing the environmental footprint associated with traditional cementitious systems. Full article

This study investigates the underwater transient vibro-acoustic response of double-layered stiffened cylindrical shells through an integrated experimental-numerical approach. Initially, vibration and noise responses under transient impact loads were experimentally characterized in an anechoic water tank, establishing benchmark datasets. Subsequently, based on the theory of transient structural dynamics, a numerical framework was developed by extending the time-domain finite element/boundary element (FEM/BEM) method, enabling comprehensive analysis of the transient vibration and acoustic radiation characteristics of submerged structures. Validation through experimental-simulation comparisons confirmed the method’s accuracy and effectiveness. Key findings reveal broadband features with distinct discrete spectral peaks in both structural vibration and acoustic pressure responses under transient excitation. Systematic parametric investigations demonstrate that: (1) Reducing the load pulse width significantly amplifies vibration acceleration and sound pressure levels, while shifting acoustic energy spectra toward higher frequencies; (2) Loading position alters both vibration patterns and noise radiation characteristics. The established numerical methodology provides theoretical support for transient impact noise prediction and low-noise structural optimization in underwater vehicle design. Full article

Integrating renewable energy, particularly wind power, into modern power systems introduces challenges concerning stability and reliability. These issues require enhanced regulation to balance power supply with load demand. Flexible loads and energy storage provide viable solutions to stabilize the grid without relying on new resources. This paper proposes building thermostatically controlled loads (BTLs), such as heating, ventilation, and air conditioning (HVAC) systems, as flexible demand-side management tools to address the challenges of intermittent energy sources. A new concept is introduced, portraying BTLs as a stochastic battery with losses, offering a compact representation of their dynamics. BTLs’ thermal characteristics, user-defined set points, and ambient temperature changes determine the power limits and energy capacity of this stochastic battery. The model is simulated using DIgSILENT Power Factory, which includes thermal power plants, gas turbines, wind power plants, and BTLs. A dynamic dispatch strategy optimizes power generation while utilizing BTLs to balance grid fluctuations caused by variable wind energy. Performance analysis shows that integrating BTLs with conventional thermal plants can reduce variability and improve grid stability. The study highlights the dual role of simulating overall flexibility and applying dynamic dispatch strategies to enhance power systems with high renewable energy integration. Full article

This study investigates the energy consumption characteristics of individual and clustered thermal storage electric heating systems, focusing on their sustainability implications for regional load distribution and user energy consumption patterns. Simulation results show that thermal storage electric heating shifts peak energy demand from daytime to nighttime low-price hours, reducing electricity costs and optimizing grid load balancing. As the proportion of thermal storage electric heating increases from 10% to 30%, the daytime minimum load reduction rate rises from 7% to 22%, while the nighttime maximum load increase rate increases from 16% to 63%. This operational mode supports sustainable energy usage by alleviating daytime grid peak pressure and leveraging low-cost, off-peak electricity for heat storage. The findings highlight the potential of thermal storage electric heating to enhance energy efficiency, integrate renewable energy, and promote grid stability, contributing to a more sustainable energy system. Full article

Sustainable product development demands components that last longer, consume less energy, and can be refurbished within circular supply chains. This study introduces a digital replica-based predictive prototyping workflow for industrial crusher blades that meets these goals. Six commercially used blade geometries (A–F) were recreated as high-fidelity finite-element models and subjected to an identical 5 kN cutting load. Comparative simulations revealed that a triple-edged hooked profile (Blade A) reduced peak von Mises stress by 53% and total deformation by 71% compared with a conventional flat blade, indicating lower drive-motor power and slower wear. To enable fast virtual prototyping and condition-based maintenance, deformation was subsequently predicted using a data-efficient machine-learning model. Multi-view image augmentation enlarged the experimental dataset from 6 to 60 samples, and an XGBoost regressor, trained on computer-vision geometry features and engineering parameters, achieved R² = 0.996 and MAE = 0.005 mm in five-fold cross-validation. Feature-importance analysis highlighted applied stress, safety factor, and edge design as the dominant predictors. The integrated method reduces development cycles, reduces material loss via iteration, extends the life of blades, and facilitates refurbishment decisions, providing a foundation for future integration into digital twin systems to support sustainable product development and predictive maintenance in heavy-duty manufacturing. Full article

To address the collaborative demand for low-frequency vibration control and energy recovery, this paper proposes a dual-functional structure integrating low-frequency vibration isolation and broadband energy harvesting. The structure consists of two core components: one is a quasi-zero stiffness (QZS) vibration isolation module composed of a linkage-horizontal spring (negative stiffness) and a vertical spring; the other is an energy-harvesting component with an array of parameter-differentiated piezoelectric cantilever beams. Aiming at the conflict between the structural dynamic stiffness approaching zero and broadening the effective working range, this paper establishes a dual-objective optimization function based on the Pareto principle on the basis of static analysis and uses the grid search method combined with actual working conditions to determine the optimal parameter combination. By establishing a multi-degree-of-freedom electromechanical coupling model, the harmonic balance method is used to derive analytical solutions, which are then verified by numerical simulations. The influence laws of external excitations and system parameters on vibration isolation and energy-harvesting performance are quantitatively analyzed. The results show that the optimized structure has an initial vibration isolation frequency below 2 Hz, with a vibration isolation rate exceeding 60% in the 3 to 5 Hz ultra-low frequency range and a minimum transmissibility of the order of 10⁻² (vibration isolation rate > 98%). The parameter-differentiated piezoelectric array effectively broadens the energy-harvesting frequency band, which coincides with the vibration isolation range. Synergistic optimization of both performances can be achieved by adjusting system damping, parameters of piezoelectric vibrators, and load resistance. This study provides a theoretical reference for the integrated design of low-frequency vibration control and energy recovery, and its engineering implementation requires further experimental verification. Full article

Hybrid AC/DC microgrids (HADCMGs), which integrate renewable energy sources and battery storage systems, often face significant stability challenges due to their inherently low inertia and highly variable power inputs. To address these issues, this paper proposes a novel, robust composite controller based on backstepping fast terminal sliding mode control (BFTSMC). This controller is further enhanced with a virtual capacitor to emulate synthetic inertia and with a fractional power-based reaching law, which ensures smooth and finite-time convergence. Moreover, the proposed control strategy ensures the effective coordination of power sharing between AC and DC sub-grids through bidirectional converters, thereby maintaining system stability during rapid fluctuations in load or generation. To achieve optimal control performance under diverse and dynamic operating conditions, the controller gains are adaptively tuned using the marine predators algorithm (MPA), a nature-inspired metaheuristic optimization technique. Furthermore, the stability of the closed-loop system is rigorously established through control Lyapunov function analysis. Extensive simulation results conducted in the MATLAB/Simulink environment demonstrate that the proposed controller significantly outperforms conventional methods by eliminating steady-state error, reducing the settling time by up to 93.9%, and minimizing overshoot and undershoot. In addition, real-time performance is validated via processor-in-the-loop (PIL) testing, thereby confirming the controller’s practical feasibility and effectiveness in enhancing the resilience and efficiency of HADCMG operations. Full article

Smart monitoring of local electricity systems (LESs) with sources based on renewable energy resources (RESs) from the point of view of the requirements of the functions of an intelligent system are hardware and software systems that can solve the tasks of both analysis (optimization) and synthesis (design, planning, control). The article considers the following: a functional scheme of smart monitoring of LESs, describing its main components and scope of application; an assessment of the state of the processes and the state of the equipment of generators and loads; dynamic pricing and a dynamic assessment of the state of use of primary fuel and/or current costs of generators; economic efficiency of generator operation and loads; an assessment of environmental acceptability, in particular, the volume of CO₂ emissions; provides demand-side management, managing maximum energy consumption; a forecast of system development; an assessment of mutual flows of electricity; system resistance to disturbances; a forecast of metrological indicators, potential opportunities for generating RESs (wind power plants, solar power plants, etc.); an assessment of current costs; the state of electromagnetic compatibility of system elements and operation of electricity storage devices; and ensures work on local electricity markets. The application of smart monitoring in the formation of tariffs on local energy markets for transactive energy systems is shown by conducting a combined comprehensive assessment of the energy produced by each individual power source with graphs of the dependence of costs on the generated power. Algorithms for the comprehensive assessment of the cost of electricity production in a transactive system for calculating planned costs are developed, and the calculation of the cost of production per 1 kW is also presented. A visualization of the results of applying this algorithm is presented. Full article

This study investigates the influence of hybrid filler systems comprising carbon black (CB), mica, and surface-modified mica (SM) on the properties of ethylene–propylene–diene monomer (EPDM)/butadiene rubber (PB) composites. To reduce the environmental issues associated with CB, mica was incorporated as a partial substitute, and its compatibility with the rubber matrix was enhanced through surface modification using ureidopropyltrimethoxysilane (URE). The composites with hybrid filler systems and surface modification were evaluated in terms of curing behavior, crosslink density, mechanical and elastic properties, and dynamic viscoelasticity. Rheological analysis revealed that high mica loadings delayed vulcanization due to reduced thermal conductivity and accelerator adsorption, whereas SM composites maintained comparable curing performance. Swelling tests showed a reduction in crosslink density with increased unmodified mica content, while SM-filled samples improved the network density, confirming enhanced interfacial interaction. Mechanical testing demonstrated that the rubber compounds containing SM exhibited average improvements of 17% in tensile strength and 20% in toughness. In particular, the CB20/SM10 formulation achieved a well-balanced enhancement in tensile strength, elongation at break, and toughness, surpassing the performance of the CB-only system. Furthermore, rebound resilience and Tan δ analyses showed that low SM content reduced energy dissipation and improved elasticity, whereas excessive filler loadings led to increased hysteresis. The compression set results supported the thermal stability and recovery capacity of the SM-containing systems. Overall, the results demonstrated that the hybrid filler system incorporating URE-modified mica significantly enhanced filler dispersion and rubber–filler interaction, offering a sustainable and high-performance solution for elastomer composite applications. Full article

Butyric acid is one of the main volatile fatty acids (VFAs) in Maotai-flavor liquor wastewater (MFLW), and its degradation process exhibits a positive Gibbs free energy, making it prone to accumulation during high-load anaerobic digestion (AD), which can lead to system instability or even failure. In this study, hydrochar (HTC) was prepared from rice husk obtained from distiller’s grains, and butyrate-degrading microbiomes were selectively enriched under acidic conditions with butyric acid as the sole carbon source. Through co-incubation, the butyrate-degrading microbiomes were successfully pre-coupled with HTC, forming a “hydrochar–microbe” composite, which was then applied to the AD of MFLW. The experimental results demonstrated that this composite enhanced system performance. The hydrochar–butyrate pre-coupling group (HBA-C) showed a 15.48% increase in methane yield compared to the control group (CK), with a soluble chemical oxygen demand (sCOD) removal rate of 75.02%, effectively mitigating VFA accumulation. Microbial community analysis indicated higher bacterial and archaeal diversity indices in the HBA-C group. qPCR results showed that the bacterial and archaeal copy numbers in the HBA-C group were 22.06-times and 13.80-times higher than those in the CK group, respectively. Moreover, the relative abundance of the genes for the key enzymes methylmalonyl-CoA carboxyltransferase (EC: 2.1.3.1) and succinate dehydrogenase (EC: 1.3.5.1) was significantly increased, indicating that the “hydrochar–microbe” coupling enhanced carbon flow distribution efficiency and energy metabolism by optimizing metabolic pathways. This study provides an innovative strategy for MFLW treatment and offers practical value for anaerobic digestion optimization and high-strength wastewater management. Full article