Search Results (468)

Bent-pipe intake distortion restricts the stable flow range (SFR) and degrades the aerodynamic performance of centrifugal compressors. To expand the SFR while minimizing efficiency loss, this study carries out multi-objective optimization on a self-recirculating casing treatment (SRCT). Numerical simulations were performed at 65,000 rpm based on a four-factor, three-level orthogonal test design, focusing on four key geometric parameters: recirculation angle (α), downstream slot width (b_r), axial passage height (h_b), and axial passage width (b_b). The specific effects of these parameters on the SFR, isentropic efficiency (η), and a comprehensive stability index (ΔSFR/Δη) were systematically analyzed. Three optimal designs were obtained through this optimization approach, tailored to different operational requirements, namely Casing_SFR, Casing_η, and Casing_Opt. The results indicate that the comprehensive optimal model (Casing_Opt) achieves an optimal balance between SFR expansion and efficiency retention, extending the SFR by 28.67% with only a 10.84% reduction in isentropic efficiency. Flow field analysis further verifies that the optimized SRCT can effectively modulate tip leakage flow via low-energy fluid suction and reinjection, correct deviated inlet incidence, thereby mitigating the severe leading-edge flow separation and high-entropy generation induced by distorted inflow. Full article

This study analyzes the econometric correlation between resale prices and CO₂ emissions of 832 bulk carriers sold from 2018 to 2025. It uses a cross-sectional hedonic pricing model to look at how environmental performance affects the value of sub-types of dry bulk vessels (Capesize, Panamax, Supramax, and Handysize) and age groups (0–5, 6–10, 11–15, and 16+). The findings show that emission efficiency has a statistically significant and negative effect on second-hand prices for all models. Results indicate that higher emission intensity (higher technical efficiency values) reduces vessel values. The magnitude of this effect varies by ship type and age group. Based on the Technical Efficiency Indicator (TEI), refers to Energy Efficiency Existing Ship Index (EEXI) or Energy Efficiency Design Index (EEDI) coefficients, the Supramax segment appears to be the most price-sensitive, followed by Panamax, Capesize, and Handysize. Age has a consistently negative and significant effect on prices, while vessel size positively affects asset values. Further analysis shows that TEI levels increase with vessel age, whereas they decrease with larger vessel size and more recent measurement years. These results are consistent with tightening regulatory pressures under the International Maritime Organization (IMO) frameworks. The economic implications of IMO’s environmental regulations on carbon intensity indicate that compliance with regulation standards creates a measurable price differential in the second-hand ship market. These findings have important implications for shipowners’ investment strategies, regulatory policy design, and the decarbonization path of the maritime sector. This study contributes to the growing research on environmental economics in maritime transport by providing empirical evidence on how carbon regulations translate into tangible asset value impacts. Full article

To improve the operational efficiency of the park source-load-storage system and reduce operation costs and the wind-solar curtailment rate, this paper establishes a Park Integrated Energy System (PIES) model with multiple energy storage and vehicle-to-grid (V2G) components and proposes an adaptive comprehensive fitness multi-objective particle swarm optimization algorithm. First, each component of the PIES is modeled. Second, electric vehicle (EV) scheduling boundaries, determined by wind and PV output, as well as a dynamic charging-discharging incentive mechanism, are designed to enhance renewable energy accommodation. Finally, an adaptive comprehensive fitness index is defined, and convergence and particle-update strategies are improved to achieve better scheduling performance. Simulation results verify that the proposed PIES model achieves optimal performance in terms of carbon-emission cost, total operation cost, and wind-solar curtailment rate. Meanwhile, the improved algorithm also outperforms traditional multi-objective methods in PIES scheduling. Full article

The complex propagation behavior of hydraulic fractures (HFs) in strongly heterogeneous conglomerate reservoirs poses significant challenges for effective reservoir stimulation. In particular, the interaction between fractures and gravel-induced heterogeneity often leads to highly tortuous fracture networks and uneven stimulation efficiency. To address this issue, a series of laboratory true triaxial hydraulic fracturing experiments were conducted on artificially prepared conglomerate specimens with controlled gravel size and distribution. A quantitative evaluation index, termed the Fracture Complexity Index (FCI), was proposed to characterize the tortuosity and complexity of fracture networks by integrating multiple geological and engineering factors. The effects of cluster spacing and fracturing fluid viscosity on multi-fracture propagation behavior were systematically investigated. The results show that increasing cluster spacing enhances inter-fracture interaction and promotes fracture tortuosity, while lower fluid viscosity facilitates fracture branching but may limit effective propagation distance due to energy dissipation. To further quantify the trade-off between fracture complexity and propagation extent, a dimensionless fracture length was introduced and combined with FCI to establish a fracture morphology evaluation framework. This framework enables the classification of fracture patterns and reveals the coupling relationship between engineering parameters and fracture geometry. The findings provide new insights into the mechanisms of fracture propagation in conglomerate reservoirs and offer a quantitative basis for optimizing fracturing design, particularly in balancing fracture complexity and effective stimulation range in strongly heterogeneous formations. Full article

Today, microfluidics has become a revolutionary field of engineering due to its wide range of applications, including lab-on-a-chip devices, microscale biochemical reactors, drug delivery systems, and disease diagnostics. Efficient fluid mixing has been a significant challenge in these systems due to the dominance of laminar flow and low-Reynolds number conditions, where mixing relies primarily on slow molecular diffusion. It is very difficult to achieve rapid mixing and homogeneous mixing within a limited length. In this study, a bioinspired passive micromixer is developed based on the cristae architecture of mitochondria, which is known for maximizing surface area and transport efficiency in biological systems. The micromixer incorporates cristae-like microstructures within a straight microchannel to produce continuous flow deflection, stretching, and folding, thereby promoting chaotic advection without relying on external energy sources. It also includes mitochondrial granules, such as micropillars, within the channel to disrupt streamline flow. Thus, a numerical investigation was conducted to design four different micromixer geometries: conventional T-channel, and T-channels with a single, double and triple matrix of cristae. The analysis was performed in COMSOL Multiphysics, in which “Laminar flow” and “Transport of diluted species” physics were used, and a stationary study was executed. Simulations were conducted at different Reynolds numbers (Re = 0.1–100) to observe the feasibility of the proposed designs. For analysis, the mixing index and concentration profiles at the outlet and along the length were also examined. The results showed that the high cristae density channel performed well, achieving a mixing index of 95.85% at Re = 0.1 and 85.84% at Re = 100, proving that the proposed mitochondria-inspired cristae Mito-mixer delivers efficient mixing over a broad Reynolds-number range while maintaining a compact, length-efficient design. Full article

Functionally graded multi-material thermoplastic architectures provide a promising route for tailoring viscoelastic energy dissipation through controlled phase contrast and interfacial interactions. However, rational selection of optimal material compositions remains challenging due to competing requirements among stiffness, damping efficiency, thermal stability, and processability. The absence of a quantitative decision framework often limits systematic design of architected polymer systems. This study proposes an Analytic Hierarchy Process (AHP)-based multi-criteria decision model to identify the optimal rigid–elastic thermoplastic composition for enhanced damping performance. Nine performance criteria were considered, including storage modulus, loss factor, damping bandwidth, interfacial adhesion strength, elongation at break, impact resistance, glass transition temperature, thermal stability, and printability. Fourteen alternative material configurations combining different rigid phases, elastomeric interlayers, filler contents, and layer thickness ratios were evaluated. Pairwise comparison matrices were constructed based on experimentally measured thermomechanical data and literature-reported values, and consistency ratios were maintained below 0.1 to ensure decision reliability. Numerical results indicate that a graded PLA/soft-TPU/PLA architecture with optimized layer thickness ratio achieved the highest global priority weight (0.431), outperforming the baseline PLA/TPU system by approximately ~25–30% in overall performance index. Sensitivity analysis confirmed ranking robustness across variations in damping and stiffness weighting factors. The proposed framework establishes a systematic methodology for polymer material selection and multi-material architectural optimization, enabling data-driven design of thermoplastic systems with tunable viscoelastic performance. Full article

Efficient mixing is a persistent bottleneck in agricultural and agrochemical processing, where rapid and uniform mixing must be achieved under laminar flow with low energy input and gentle shear. Inspired by peristaltic transport in biological systems, this study investigates a bio-inspired flexible-wall squeezing mixer and establishes a two-dimensional computational framework to quantify how periodic wall deformation governs scalar homogenization in a flexible conduit. An Arbitrary Lagrangian–Eulerian dynamic mesh approach is implemented to resolve moving boundaries and to prescribe actuation, enabling the systematic evaluation of the separate and coupled effects of peak wall-normal velocity amplitude A and actuation frequency f on mixing performance. Mixing effectiveness is quantified using a variance-based mixing index MI and a sustained-threshold mixing time ts, and response surface methodology is employed to map the A–f design space and interpret the roles of time-dependent shear, interfacial stretching and folding, and vortex intensification. Relative to a non-actuated baseline, a peak wall-normal velocity amplitude of 3 × 10⁻³ m s⁻¹ at 2 Hz reduces t_s by 21.3%. At fixed f = 3 Hz, increasing A from 1 × 10⁻³ to 4 × 10⁻³ m s⁻¹ shortens t_s by 10.2%, while at fixed A = 3 × 10⁻³ m s⁻¹, raising f from 1 to 5 Hz further decreases t_s by 6.6% with diminishing gains at the lowest frequencies. The response surface identifies an operating optimum at A = 4 × 10⁻³ m s⁻¹ and f = 5 Hz, achieving a peak MI of 0.9557 and a minimum t_s of 7.81 s. A periodically squeezed physical mixing loop was further examined using fluorescence imaging to assess outlet homogeneity trends. The stabilized outlet coefficient of variation (CV) decreased from about 0.65 without squeezing to 0.60 at 1 Hz and 10 mm s⁻¹, 0.58 at 2 Hz and 10 mm s⁻¹, and 0.54 at 2 Hz and 30 mm s⁻¹, indicating that stronger and faster actuation improves outlet uniformity. The numerical and experimental results are therefore interpreted jointly as mechanistic and trend-level evidence, while a rigorous quantitative prediction for the cylindrical compliant device will require future three-dimensional, compliance-resolved simulations and broader experimental benchmarking. Full article

With the deployment and application of the Fifth-Generation (5G) mobile communication technologies and the ongoing research and development of the Sixth-Generation (6G) mobile communication technologies, the space–air–ground–sea integrated network has become the core development vision for future communications. As aerial nodes, Unmanned Aerial Vehicles (UAVs) can be applied in a wide range of scenarios, including emergency rescue, surveying and mapping, environmental monitoring, and communication coverage enhancement. In terms of communication coverage enhancement, the space–air–ground integrated network, with UAVs as a key component, can provide seamless communication coverage for the full-domain three-dimensional space such as remote areas, deserts, and oceans. Benefiting from advantages such as low cost and high flexibility, UAVs have become a critical research focus, and the one-hop Base Station (BS)–relay UAV–slave UAV architecture for communication coverage enhancement has emerged as an important development direction. However, the high mobility and wide coverage characteristics of UAVs also pose significant synchronization challenges. Aiming at the uplink synchronization problem on the sidelink between slave UAVs and the relay UAV, a two-step random-access scheme based on Asynchronous Non-Orthogonal Multiple Access (A-NOMA) is designed to mitigate the Doppler Frequency Offset (DFO), improve access efficiency, reduce resource consumption, and accommodate the asynchrony among different users. This scheme leverages the existing preamble sequences of the Physical Random Access Channel (PRACH) and realizes DFO estimation in combination with the pairing index. On this basis, a Successive Interference Cancellation (SIC) algorithm based on DFO and phase compensation is designed to complete the demodulation of user data. For the downlink synchronization problem on the sidelink between slave UAVs and the relay UAV, the frequency offset estimation performance is improved by redesigning the resource allocation scheme of the Sidelink Synchronization Signal Block (S-SSB). Meanwhile, considering the energy constraint of UAVs, a downsampling-based detection scheme is designed to reduce UAV power consumption, and a full-link algorithm is developed to support the practical implementation of the proposed scheme. Full article

The integration of Building Information Modeling [BIM] and Digital Twins [DT] has emerged as a central driver of digital transformation in the architecture, engineering, and construction sector. Yet, its systemic impact remains constrained by conceptual fragmentation and uneven institutional adoption. This study synthesizes contemporary BIM–DT scalability and each to identify dominant technological and application dimensions, examine the governance conditions shaping scalability, and develop an analytical framework that advances understanding beyond technology-centered syntheses. A two-stage analytical design was employed, combining bibliometric keyword co-occurrence analysis of 1295 Scopus-indexed records with systematic qualitative synthesis of 56 peer-reviewed journal articles published between 2020 and 2025, following PRISMA guidelines. Six interrelated analytical dimensions characterize the current BIM–DT research landscape: BIM–DT integration advancements and applications; interoperability and visualization; safety enhancement; energy efficiency; data-driven decision making; and stakeholder collaboration. Across these dimensions, a persistent misalignment emerges between technological capability and organizational readiness, with deficiencies in standards, governance, and sociotechnical coordination constituting the principal barriers to large-scale deployment. The findings reframe BIM–DT convergence not as a discrete technological upgrade but as the emergence of a coordinated socio-technical information ecosystem spanning the full building lifecycle. By foregrounding governance conditions, data stewardship, and institutional coordination, this study extends understanding of how digital twins expand BIM from design coordination to operational governance and establishes a foundation for more systematic implementation of intelligent, resilient, and sustainable built-environment systems. Full article

The energy-intensive nature of primary aluminum production necessitates advanced computational tools for process optimization. This study presents a coupled electro-thermal model of an aluminum reduction cell, developed within the framework of smart manufacturing. Using the finite difference method (FDM) implemented in MATLAB R2025b, the model resolves the three-dimensional configuration of a cell with eight prebaked anodes across four distinct physical domains (electrolyte, anodes, cathode, and gas phase). The computational grid comprises approximately 45,000 nodes with refined vertical resolution (Δz = 0.025 m) in the interelectrode gap. The electrostatic solution converges within 150–200 iterations using successive over-relaxation (SOR, ω = 1.5), with a total runtime under 15 min for 30,000 s of simulated physical time on a standard desktop workstation. Simulation results reveal characteristic temperature profiles with maxima reaching 1150 °C and a thermal uniformity index of approximately 130 °C across the central cross-section. The predicted specific energy consumption of 14.0 MWh/t Al aligns with industrial benchmarks. This computationally accessible virtual testbed enables rapid assessment of design modifications and process parameters, supporting the goals of energy efficiency and enhanced operational stability in primary aluminum production. Full article

This paper presents an analytical framework for the preliminary design of stringer-stiffened composite panels subjected to low-velocity impact. The formulation combines First-Order Shear Deformation Theory with a two-degree-of-freedom spring–mass model, while the super-stringer is represented as a Euler–Bernoulli beam whose bending contribution is transferred to the skin mid-surface through the parallel axis theorem. This provides a computationally efficient tool for rapid parametric assessment of stiffened configurations at the early design stage. To support laminate selection, a Specific Impact Energy Index (SIEI) is introduced to rank configurations according to their elastic energy storage efficiency relative to the product of skin and stringer thicknesses. The tool is validated against both published experimental results and a finite element dynamic explicit model, demonstrating a good approximation of the impact response. It is then applied to identify the optimum laminate configuration for a super-stringer case study within the design space considered. Full article

Rising temperatures and increasing evaporative demand accelerate soil moisture loss (SML) during the sowing-to-emergence phase of cotton (Gossypium hirsutum L.), constraining crop establishment under water-limited Mediterranean conditions. Conventional tillage (CT) involves intensive tillage operations with higher fuel and energy requirements, whereas strip tillage (ST) limits tillage to the crop row while preserving inter-row residues. This study evaluated ST and CT across two consecutive growing seasons (2024 and 2025) under a wheat–cotton rotation system. A field experiment was conducted using a replicated design (n = 8), in which emergence parameters, SML (0–10 cm), yield, and fuel-derived energy use and CO₂ emissions were quantified. SML was significantly lower under ST than CT (43% in 2024 and 52% in 2025; p < 0.001), leading to earlier emergence (0.98–1.17 days) and higher emergence rate index (ERI) values. Cotton yield was slightly higher under CT (3–4%); however, this difference, although statistically significant (p = 0.001), remained limited and consistent across years. In contrast, ST resulted in a 66–69% reduction in operational fuel use, with proportional reductions in energy use and CO₂ emissions on an area basis. Yield-scaled indicators, defined as energy use (MJ kg⁻¹) and CO₂ emissions (kg CO₂ kg⁻¹) per unit yield, further revealed substantially greater resource-use efficiency under ST compared with CT. These findings demonstrate that strip tillage enhances hydrothermal conditions during crop establishment while markedly reducing energy demand and carbon intensity, providing a resource-efficient mechanization strategy for cotton production under increasing climatic stress. Full article

Chiller systems account for a substantial proportion of building energy consumption, where their operational efficiency and start–stop cycling frequency directly influence overall system energy use and equipment lifespan. In practical applications, load fluctuations and improper control settings often cause chillers to experience frequent cycling, leading to decreased efficiency and increased mechanical wear. While existing studies predominantly focus on real-time control or model predictive approaches, fewer investigations systematically identify stable operating regions and optimal control thresholds using historical operational data. This study proposes a data-driven method for identifying an operational threshold. Long-term historical data are analyzed to establish a start–stop event detection mechanism. A normalized power index is introduced, and multi-scenario classification—incorporating seasonal conditions and peak/off-peak periods—is employed to evaluate system behavior across different contexts. Furthermore, a quantile scanning approach combined with hysteresis simulation is utilized to identify optimal operational threshold intervals. Stability evaluation indices, based on cycling frequency, power variation rate, and load deviation magnitude, are constructed to quantify stability performance. To verify the robustness of these thresholds, K-fold cross-validation is performed. Results indicate that the identified thresholds effectively reduce cycling frequency and power fluctuations, thereby enhancing system stability. Specifically, the start–stop cycling frequency is reduced by approximately 75–90%, and the power variation rate decreases by up to 85% across various scenarios. This study provides an offline decision-support framework to assist operators in optimizing control parameters and strategies. These outcomes serve as a reference for chiller energy management and provide empirical evidence for the future design of control strategies. Full article

This study presents a comprehensive thermo-energetic and exergetic assessment of a 250 MW steam boiler in a Cuban thermal power plant, operating under partial load conditions (plant: 62–66%; boiler: 58–61%). An integrated diagnostic methodology was developed and implemented in Mathcad 15 to evaluate key performance indicators, including thermal efficiency (η_tGV); exergetic efficiency (η_ExGV); exergy destruction ratio (γ_ExGV); steam generation index (IG_v); and specific fuel consumption (B_Esp). The methodology was applied to two fuels with contrasting thermophysical and chemical properties: fuel oil and Enhanced Crude Oil 650. The results indicate superior performance with fuel oil due to its higher heating value; however, efficiency losses were mainly attributed to operational factors such as excessive air supply (22.7–26.4%), heat transfer surface fouling, and inadequate maintenance. The analysis revealed significant deviations from design values—thermal efficiency (90.27–90.59%) and exergetic efficiency (<60%)—highlighting an untapped potential for energy savings. Quantitative estimates indicate potential annual fuel cost savings of approximately 1.2 million USD through optimized combustion and maintenance practices. The proposed framework enables accurate diagnostics of complex boiler systems and provides actionable indicators to support combustion optimization and energy efficiency strategies in conventional thermal power plants. Full article

Improving energy efficiency and reducing the carbon footprint of crop production are critical for sustainable agriculture, particularly in semi-arid regions where resource use efficiency is essential. This study evaluated the effects of different fertilization strategies on energy use efficiency and carbon footprint in maize production. A field experiment was conducted during the 2023 growing season in Konya Province, Türkiye, using a randomized block design with three treatments and three replications. The treatments included an unfertilized control (U1), inorganic fertilizer application (U2), and liquid animal manure application (U3). The results showed that the highest grain yield was obtained in the liquid manure treatment, which was 2.08 times higher than the unfertilized treatment and 1.18 times higher than the inorganic fertilizer treatment. The highest total energy input was recorded in the inorganic fertilizer treatment (26,235.12 MJ ha⁻¹), while the highest total energy output was observed in the liquid manure treatment (203,154 MJ ha⁻¹). The liquid manure treatment also showed higher net energy efficiency, output–input ratio, carbon efficiency, and carbon sustainability index, while producing the lowest carbon footprint per unit of product. These findings indicate that liquid animal manure can improve maize productivity while enhancing energy efficiency and reducing carbon emissions in semi-arid agroecosystems. Full article