Search Results (57,140)

This paper investigates the dual-functional broadband properties of an asymmetric piezoelectric metamaterial beam for simultaneous vibration reduction and energy harvesting. Firstly, a grading method is proposed, and an asymmetric piezoelectric metamaterial beam structure model with the gradient mode is established. The effects of various gradient modes on the grading parameters of each segment are examined. Subsequently, the band structure and group velocity of each segment are examined to elucidate the propagation and energy harvesting mechanisms for the bending-dominated wave. Furthermore, the evaluation criteria for dual-functional properties in the gradient mode are introduced, revealing the broadening law of the dual-functional band under various gradient modes. Finally, the theoretical results are analyzed and compared with the finite element method (FEM). The results show that in gradient mode, the bending-dominated wave in the asymmetric piezoelectric metamaterial beam generates the spatial frequency division and enhances wave field energy. Compared with the uniform mode, the gradient modes can simultaneously achieve dual-functional effects in both the low-frequency and broadband ranges, significantly improving performance. Parameters such as gradient modes and grading variation ranges significantly impact the dual-functional performance. By reasonably selecting the grading parameters, enhanced dual-functional performance can be achieved. Full article

This work investigates the effect of a bio-based plasticizer derived from used sunflower oil on the crystallization behavior of poly (lactic acid) (PLA), comparing it with that of the conventional plasticizer tributyrin. This study aims to explore biodegradable alternatives to petroleum-based materials and to evaluate their potential in modulating PLA crystallization kinetics without altering the crystalline structure of the resulting sustainable material solutions with tailored performance. PLA-based films containing 5%, 10%, and 15% plasticizer were prepared and characterized by differential scanning calorimetry (DSC), polarized optical microscopy (POM), and X-Ray diffraction (XRD). DSC analysis showed a decrease in the glass transition temperatures upon plasticization, with tributyrin producing a more pronounced effect than the recycled sunflower oil plasticizer. XRD patterns confirmed that the crystalline form of PLA remained unchanged regardless of plasticizer type or content. POM revealed that both plasticizers influenced crystallization kinetics, with the bio-plasticizer promoting larger and more sparsely distributed spherulites than tributyrin, indicating differences in nucleation efficiency and crystal growth. Crystallization kinetics were further analyzed using the Avrami model, the Lauritzen-Hoffman theory, and the isoconversional method. Avrami analysis indicated that nucleation mechanisms were largely unaffected, although the overall crystallization rate increased upon plasticization. Lauritzen-Hoffman analysis confirmed crystallization in Regime III, controlled by nucleation, while isoconversional analysis showed reduced activation energy in plasticized PLA. These findings highlight the ability of bio-derived plasticizers to modulate PLA crystallization, promoting the valorization of a food industry residue as a sustainable plasticizer. This study hopes to contribute relevant knowledge to emerging areas of polymer processing, such as 3D printing, to develop sustainable and high-performance PLA-based materials. Full article

This paper addresses the critical challenge of energy management for autonomous robots in the context of large-scale photovoltaic parks. The dynamic and vast nature of these environments, characterized by dense, structured rows of solar panels, introduces unique complexities, including uneven terrain, varied operational demands, and the need for equitable resource allocation among diverse robot fleets. The presented framework adapts and significantly extends the Affinity Propagation algorithm for strategic charging station placement within photovoltaic parks. The key contributions include: (1) a multi-attribute grid-based environment model that quantifies terrain difficulty and panel-specific obstacles; (2) an extended multi-factor scoring function that incorporates penalties for terrain inaccessibility and proximity to sensitive photovoltaic infrastructure; (3) a sophisticated, energy-aware consumption model that accounts for terrain friction, slope, and rolling resistance; and (4) a novel multi-agent fairness constraint that ensures equitable access to charging resources across heterogeneous robot sub-fleets. Through extensive simulations on synthesized photovoltaic park environments, it is demonstrated that the enhanced algorithm not only significantly reduces travel distance and energy consumption but also promotes a fairer, more efficient operational ecosystem, paving the way for scalable and sustainable robotic maintenance and inspection. Full article

Solar panel deployment is vital to generate clean energy and reduce carbon emissions, but sustaining energy output requires regular monitoring and maintenance. This is particularly critical in countries with harsh environmental conditions, such as Qatar, where high dust density reduces solar radiation reaching panels, thereby lowering generating efficiency and increasing maintenance costs. This paper introduces a data-driven model that uses the relationship between generated and consumed energy to track changes in solar panel performance. By applying statistical analysis to real and simulated data, the model identifies when efficiency losses are within the parameters of normal variation (e.g., daily fluctuations) and when they are likely caused by dust accumulation or system ageing. The findings demonstrate that the model provides a reliable and cost-effective way to support timely cleaning and maintenance decisions. It offers decision-makers a practical tool to improve residential solar panel management, reducing unnecessary costs, and ensuring more consistent renewable energy generation. Full article

This paper presents a comprehensive analysis of the dynamic properties of low-power current transformers (LPCTs) in the context of their application in both power systems and electromechanical systems. Momentary changes in external loads occurring in the mechanical parts of systems, affecting their correct operation, cause the appropriate monitoring and control systems, including LPCTs, to operate in transient states where dynamic errors are significant. The issues discussed in this article are therefore important from both an electrical and mechanical engineering perspective. The study focuses on the evaluation of dynamic errors using two complementary performance criteria: the mean squared error and the absolute dynamic error. An equivalent circuit model of the LPCT is formulated and employed to investigate its response under transient conditions representative of modern energy networks as well as electromechanical devices, including drives, converters, and rotating machines operating under variable loads. A key contribution of this work is the determination of the upper bounds of dynamic errors, which establish the ultimate accuracy constraints of LPCTs when subjected to rapid current variations. The obtained results provide quantitative evidence of the impact of dynamic properties on the reliability of current measurements, thereby reinforcing the importance of the proposed error evaluation framework. In this context, the study demonstrates that a rigorous assessment of dynamic errors is essential for improving the functional performance of LPCTs, particularly in applications where steady-state accuracy must be complemented by a reliable transient response. Full article

Floating offshore wind–wave hybrid systems, as a novel structural form integrating floating wind turbine foundations and WECs, can effectively enhance the efficiency of renewable energy utilization when properly designed. A numerical model is established to investigate the dynamic responses of a wind–wave hybrid system comprising a semi-submersible FOWT and PA wave energy converters. The optimal damping values of the PTO system for the wind–wave hybrid system are determined based on an NSGA-II. Subsequently, a comparative analysis of dynamic responses is carried out for the PTO system with different states: latching, fully released, and optimal damping. Under the same extreme irregular wave conditions, the pitch motion of the FOWT with optimal damping is reduced to 71% and 50% compared to the latching and fully released states, respectively. The maximum mooring line tension in the optimal damping state is similar to that in the fully released state, but nearly 40% lower than in the latching state. This optimal control strategy not only sustains power generation but also enhances structural stability and efficiency compared to traditional survival strategies, offering a promising approach for cost-effective offshore wind and wave energy utilization. Full article

As large common areas, cruise ship atriums affect passenger comfort and HVAC efficiency. Due to their complexity and high occupancy, maintaining a suitable thermal environment is difficult. Experimental measurements, thermal load analysis, and CFD simulation are used to assess and improve the atrium’s summer thermal climate. Experimental data supported the use of the RNG $k$-$\epsilon$ turbulence model to forecast airflow and temperature. To meet the cooling demand of 28,784 W, a supply air volume of 10,742 m³/h was required. Various air-supply methods were evaluated for temperature distribution, airflow velocity, PMV, and air age. Larger diffusers and better air dispersion increased temperature homogeneity, air age, and comfort. Redistributing airflow to corridors reduced localized overheating but raised core temperatures, whereas adding diffusers without boosting supply volume caused interference. The configuration with larger diffuser areas and equilibrated airflow maintained a temperature of 21–23 $°\mathrm{C}$, a PMV of −0.1 to 0.1, an air velocity of 0–0.3 $\mathrm{m}/\mathrm{s}$, and an average air age of 350 s. The findings provide theoretical and engineering guidance for energy-efficient HVAC systems in cruise ship atriums and other large public spaces. Full article

Expanded polystyrene (EPS) concrete has broad application potential in energy-efficient buildings due to its low density and excellent thermal insulation performance. However, a significant nonlinear trade-off exists between its compressive strength and thermal conductivity. Existing studies are mainly based on empirical mix design or single-objective optimization, and the employed modeling methods generally lack interpretability. To address this challenge, this study proposes a multi-objective optimization model (MOPIA-RA) based on physics-informed constraints and an intelligent evolutionary algorithm, aiming to solve the nonlinear contradiction among compressive strength, thermal conductivity, and production cost encountered in practical engineering. A comprehensive dataset covering different cementitious materials, EPS contents, and particle sizes was established based on experimental data, and a surrogate model (PIA-RA) was developed using this dataset. Finally, the Shapley additive explanation (SHAP) method was used to quantitatively evaluate the effects of key materials on compressive strength and thermal conductivity. The results show that the proposed PIA-RA model achieved coefficients of determination (R²) of 0.95 and 0.98 for predicting compressive strength and thermal conductivity, respectively; EPS particle size was the main factor affecting performance, with a contribution rate of 69%, while EPS content also played an important regulatory role, with a contribution rate of 29%. Based on the constructed MOPIA-RA model, it is possible to effectively resolve the multi-objective trade-offs among strength, thermal performance, and cost in EPS concrete and achieve precise mix design. The proposed MOPIA-RA model not only realizes multi-objective optimization among compressive strength, thermal performance, and cost, but also establishes a physics-informed and interpretable methodology for concrete material design. This model provides a scientific basis for the mix-design optimization of EPS concrete. Full article

Seawater desalination has emerged as a crucial solution for addressing global freshwater scarcity. However, it generates significant volumes of concentrated brine waste. This brine is rich in dissolved salts and minerals, primarily, chloride (55%), sodium (30%), sulfate (8%), magnesium (4%), calcium (1%), potassium (1%), bicarbonate (0.4%), and bromide (0.2%), which are often discharged into marine environments, posing ecological challenges. This study presents a comprehensive global review of innovative technologies for recovering these constituents as valuable products, thereby enhancing the sustainability and economic viability of desalination. The paper evaluates a range of proven and emerging recovery methods, including membrane separation, nanofiltration, electrodialysis, thermal crystallization, solar evaporation, chemical precipitation, and electrochemical extraction. Each technique is analyzed for its effectiveness in isolating salts (NaCl, KCl, and CaSO₄) and minerals (Mg(OH)₂ and Br₂), with a discussion of process-specific constraints, recovery efficiencies, and product purities. Furthermore, the study incorporates a detailed techno-economic assessment, highlighting revenue potential, capital and operational expenditures, and breakeven timelines. Simulated case studies of a 100,000 m³/day seawater reverse osmosis (SWRO) facility demonstrates that a sequential brine recovery process and associated energy balances, supported by pilot-scale data from ongoing global initiatives, can achieve over 90% total salt recovery while producing marketable products such as NaCl, Mg(OH)₂, and Br₂. The estimated revenue from recovered materials ranges between USD 4.5 and 6.8 million per year, offsetting 65–90% of annual desalination operating costs. The analysis indicates a payback period of 3–5 years, depending on recovery efficiency and product pricing, underscoring the economic viability of large-scale brine valorization alongside its environmental benefits. By transforming waste brine into a source of commercial commodities, desalination facilities can move toward circular economy models and achieve greater sustainability. A practical integration framework is proposed for both new and existing SWRO plants, with a focus on aligning with the principles of a circular economy. By transforming waste brine into a resource stream for commercial products, desalination facilities can reduce environmental discharge and generate additional revenue. The study concludes with actionable recommendations and insights to guide policymakers, engineers, and investors in advancing brine mining toward full-scale implementation. Full article

This study systematically investigates the velocity characteristics and coupling mechanisms of tunnel flow fields under the interactions of natural wind, traffic wind, mechanical ventilation, and structural factors (such as transverse passages and relative positions between vehicles and fans). Using CFD simulations combined with turbulence model analyses, the flow behaviors under different coupling scenarios are explored. The results show that: (1) Under natural wind conditions, transverse passages act as key pressure boundaries, reshaping the longitudinal wind speed distribution into a segmented structure of “disturbance zones (near passages) and stable zones (mid-regions)”, with disturbances near passages showing “amplitude enhancement and range contraction” as natural wind speed increases. (2) The coupling of natural wind and traffic wind (induced by moving vehicles) generates complex turbulent structures; vehicle motion forms typical flow patterns including stagnation zones, high-speed bypass flows, and wake vortices, while natural wind modulates the wake structure through momentum exchange, affecting pollutant dispersion. (3) When natural wind, traffic wind, and mechanical ventilation are coupled, the flow field is dominated by momentum superposition and competition; adjusting fan output can regulate coupling ranges and turbulence intensity, balancing energy efficiency and safety. (4) The relative positions of vehicles and fans significantly affect flow stability: forward positioning leads to synergistic momentum superposition with high stability, while reverse positioning induces strong turbulence, compressing jet effectiveness and increasing energy dissipation. This study reveals the intrinsic laws of tunnel flow field evolution under multi-factor coupling, providing theoretical support for optimizing tunnel ventilation system design and dynamic operation strategies. Full article

The urgent global challenge of environmental sustainability has intensified interest in integrating Lean Management practices with environmental objectives, particularly within the automotive industry, a sector known for both innovation and high environmental impact. This study investigates the systemic relationships between 16 lean practices and three environmental performance metrics: energy consumption, CO₂ emissions, and waste generation. Using the Fuzzy Decision-Making Trial And Evaluation Laboratory (DEMATEL) methodology, data were collected from seven lean experts in the Italian automotive industry to model the cause–effect dynamics among the selected practices. The analysis revealed that certain practices, such as Total Productive Maintenance (TPM), just-in-time (JIT), and one-piece-flow, consistently act as influential drivers across all environmental objectives. Conversely, practices like Statistical Process Control (SPC) and Total Quality Management (TQM) were identified as highly dependent, delivering full benefits only when preceded by foundational practices. The results suggest a strategic three-step implementation roadmap tailored to each environmental goal, providing decision-makers with actionable guidance for sustainable transformation. This study contributes to the literature by offering a structured perspective on lean and environmental sustainability in the context of the automotive sector in Italy. The research is supported by a data-driven method to prioritize practices based on their systemic influence and contextual effectiveness. Full article

Composite laminates are used in aerospace and wind energy applications, where they are often subjected to low-velocity impact (LVI) that can cause barely visible damage, compromising their structural integrity. The finite element method helps predict the impact behavior of composite laminates under LVI; however, achieving accuracy and computational efficiency remains challenging. Conventional shell elements (CSEs) are efficient alternatives to solid elements due to their reduced degrees of freedom. This study aims to establish modeling guidelines for LVI modeling of composite laminates using CSEs in Abaqus. A mesh convergence study using contact force, displacement, and stress is proposed and evaluated across five experimental case studies. While contact force and displacement converge quickly, stress is sensitive to element size and number of through-the-thickness section points. A parametric study of seven projectile modeling techniques shows that a deformable projectile combined with a kinematic algorithm reliably predicts LVI behavior. Furthermore, comparing artificial strain energy across three hourglass algorithms shows that the enhanced algorithm outperforms in controlling hourglass mode with minimal numerical stiffening. Finally, the applicable thickness range of CSE is quantified, indicating accurate prediction for thickness-to-width ratios below 0.04. These findings highlight the strength and limitations of CSEs in LVI modeling of composite laminates and serve as a benchmark for future analyses. Full article

This study investigates hydrogen storage enhancement through adsorption in porous materials by coupling the Dubinin–Astakhov (D-A) adsorption model with H₂ conservation equations (mass, momentum, and energy). The resulting system of partial differential equations (PDEs) was solved numerically using the finite element method (FEM). Experimental work using activated carbon as an adsorbent was carried out to validate the model. The comparison showed good agreement in terms of temperature distribution, average pressure of the system, and the amount of adsorbed hydrogen (H₂). Further simulations with different adsorbents indicated that compact metal–organic framework 5 (MOF-5) is the most effective material in terms of H₂ adsorption. Additionally, the pair (273 K, 800 s) remains the optimal combination of injection temperature and time. The findings underscore the prospective advantages of optimized MOF-5-based systems for enhanced hydrogen storage. These systems offer increased capacity and safety compared to traditional adsorbents. Subsequent research should investigate multi-objective optimization of material properties and system geometry, along with evaluating dynamic cycling performance in practical operating conditions. Additionally, experimental validation on MOF-5-based storage prototypes would further reinforce the model’s predictive capabilities for industrial applications. Full article

Tire–road friction is a fundamental factor in vehicle safety, energy efficiency, and environmental sustainability. This narrative review synthesizes current knowledge on the tire–road friction coefficient (TRFC), emphasizing its dynamic nature and the interplay of factors such as tire composition, tread design, road surface texture, temperature, load, and inflation pressure. Friction mechanisms, adhesion, and hysteresis are analyzed alongside their dependence on environmental and operational conditions. The study highlights the challenges posed by emerging mobility paradigms, including electric and autonomous vehicles, which demand specialized tires to manage higher loads, torque, and dynamic behaviors. The review identifies persistent research gaps, such as real-time TRFC estimation methods and the modeling of combined environmental effects. It explores tire–road interaction models and finite element approaches, while proposing future directions integrating artificial intelligence and machine learning for enhanced accuracy. The implications of the Euro 7 regulations, which limit tire wear particle emissions, are discussed, highlighting the need for sustainable tire materials and green manufacturing processes. By linking bibliometric trends, experimental findings, and technological innovations, this review underscores the importance of balancing grip, durability, and rolling resistance to meet safety, efficiency, and environmental goals. It concludes that optimizing friction coefficients is essential for advancing intelligent, sustainable, and regulation-compliant mobility systems, paving the way for safer and greener transportation solutions. Full article

This study proposes a Transformer–NSGA-III multi-objective optimization framework for high-rise residential buildings in Haikou, a coastal city characterized by a hot summer and warm winter climate. The framework addresses four conflicting objectives: Annual Energy Demand (AED), Predicted Percentage of Dissatisfied (PPD), Global Cost (GC), and Life Cycle Carbon (LCC) emissions. A localized database of 11 design variables was constructed by incorporating envelope parameters and climate data from 79 surveyed buildings. A total of 5000 training samples were generated through EnergyPlus simulations, employing jEPlus and Latin Hypercube Sampling (LHS). A Transformer model was employed as a surrogate predictor, leveraging its self-attention mechanism to capture complex, long-range dependencies and achieving superior predictive accuracy (R² ≥ 0.998, MAPE ≤ 0.26%) over the benchmark CNN and MLP models. The NSGA-III algorithm subsequently conducted a global optimization of the four-objective space, with the Pareto-optimal solution identified using the TOPSIS multi-criteria decision-making method. The optimization resulted in significant reductions of 28.5% in the AED, 24.1% in the PPD, 20.6% in the GC, and 18.0% in the LCC compared to the base case. The synergistic control of the window solar heat gain coefficient and external sunshade length was identified as the central strategy for simultaneously reducing energy consumption, thermal discomfort, cost, and carbon emissions in this hot and humid climate. The TOPSIS-optimal solution (C = 0.647) effectively balanced low energy use, high thermal comfort, low cost, and low carbon emissions. By integrating the Energy Performance of Buildings Directive (EPBD) Global Cost methodology with Life Cycle Carbon accounting, this study provides a robust framework for dynamic economic–environmental trade-off analyses of ultra-low-energy buildings in humid regions. The work advances the synergy between the NSGA-III and Transformer models for high-dimensional building performance optimization. Full article