Search Results (15,379)

Coal is the primary energy source in China and has long dominated energy consumption, serving as both the cornerstone for safeguarding national energy security and the backbone of stable energy supply. Despite the gradual improvement in the level of fully mechanized and intelligent mining in recent years, as well as the remarkable progress achieved in safe and efficient mining technologies, significant challenges are still encountered in the horizontal slicing mining of steeply inclined coal seams. This study was conducted against the engineering backdrop of the steeply inclined extra-thick coal seam in the Yimen Coal Mine, Sichuan Province. A combination of theoretical analysis, FLAC3D numerical simulation, and on-site monitoring was employed to investigate the support technology for mining roadways. Considering the geological occurrence conditions, roadway dimensions, and service life, the bolt (cable) + steel strip + metal mesh system was selected as the basic support method, with shed supports supplemented for reinforcement in areas with special geological structures or fractured surrounding rock. A non-uniform roadway support technology for horizontal slicing mining of steeply inclined extra-thick coal seams was proposed. The optimal support parameters of the roadways were determined through numerical simulation, and favorable support effects were verified by field measurements. Full article

Shock-aware aerodynamic shape optimization of transonic airfoils requires surrogate models that capture both integral aerodynamic trends and shock-relevant pressure distribution features. This study addresses drag-oriented optimization of the RAE2822 transonic airfoil under a lift-targeted condition with baseline relative thickness feasibility, rather than strict target pressure inverse design. Each airfoil is parameterized by a 16-dimensional CST vector and mapped to a two-channel vertical signed distance field representation of the upper- and lower-surface $C_p$ curves, from which shock descriptors, including the shock location indicator $x_s$ and the pressure jump magnitude $\Delta C_p$, are extracted in a deterministic, implementation-consistent manner. To quantify the reliability of surrogate-derived shock metrics, a held-out uncertainty analysis is performed on 500 samples. The surrogate achieves MAE/RMSE values of 0.00474/0.00602 for $C_L$ and $4.66\times {10}^{-4}/6.33\times {10}^{-4}$ for $C_D$, while the recovered shock-related quantities yield 0.00201/0.01598 for $x_s$ and 0.00200/0.00336 for $\Delta C_p$. Scatter plots and error histograms show tight one-to-one trends for most samples, with limited outliers mainly associated with locally ambiguous pressure gradient patterns. Overall, the surrogate is more reliable for capturing shock intensity trends than for prescribing an exact shock location; accordingly, $x_s$ is interpreted as a trend-level descriptor, whereas $\Delta C_p$ is treated as the more stable engineering indicator inside the optimization loop. The trained surrogate is embedded in a differential evolution optimizer with soft penalties on lift deviation and thickness feasibility violation, and selected designs are re-evaluated through closed-loop SU2 RANS simulations. CFD verification shows that the optimized design reduces drag from $C_D=0.01463$ to $C_D=0.01229$ (a 16.0% reduction) and reduces the shock jump from $\Delta C_p=0.239$ to $\Delta C_p=0.046$ (an 80.7% reduction). For the optimized design, the prediction-to-CFD differences are $\Delta C_L=+0.0042$ and $\Delta C_D=+0.00012$. These results support an engineering-oriented and auditable shock-aware closed-loop optimization workflow, with final design conclusions established by CFD verification rather than surrogate-predicted shock location alone. Full article

To address the challenges of difficult feature extraction and suboptimal parameter configuration for cyclotron ion source fault diagnosis in complex environments, this study proposes an intelligent diagnostic framework integrating Kernel Principal Component Analysis (KPCA), an Improved Sparrow Search Algorithm (ISSA), and a Support Vector Machine (SVM). The KPCA algorithm is employed for dimensionality reduction to handle the highly nonlinear nature of fault data. Regarding algorithmic evolution, the basic SSA is enhanced by integrating dynamic weights, opposition-based learning, and Cauchy mutation strategies, which effectively overcome the diagnostic bottlenecks inherent in cyclotron scenarios. Furthermore, the ISSA facilitates the global adaptive optimization of key SVM parameters, eliminating the stochasticity of empirical tuning and fundamentally enhancing the model’s robustness. Experimental results across 30 independent tests demonstrate that the KPCA-ISSA-SVM model achieves an average accuracy of 97.6% in multi-class fault detection. Compared with other classic diagnostic models, the proposed framework exhibits superior precision and stability, providing an effective technical approach with significant engineering value for the precise monitoring of ion source statuses. Full article

This study evaluated how the ice dosage and water-to-binder (W/B) ratio affect the uniaxial response of roller-compacted concrete (RCC). Three levels of W/B, 0.40, 0.45, and 0.50, were examined. For every W/B level, five proportions of ice substitution, namely 0%, 25%, 50%, 75%, and 100%, were adopted in the mixing process, producing 15 distinct mixture categories. In each group, three prismatic specimens and three cubic specimens were fabricated for compression testing. Uniaxial compression experiments were conducted to determine the failure characteristics and full stress–strain behavior, whereas scanning electron microscopy (SEM) was used to analyze the internal microstructure. Based on the test data, a constitutive expression describing RCC under uniaxial compression was established. The experimental results showed that, within the investigated range, compressive strength displayed a rise-then-fall trend as the W/B ratio increased from 0.40 to 0.50, and the best overall performance was obtained at W/B = 0.45. Microscopic examination further confirmed that this ratio produced a denser and more integrated internal structure. In addition, the role of ice dosage in governing the mechanical response of RCC varied significantly with the W/B level. The outcomes of this study provide useful support for RCC mix proportion optimization and practical engineering design. Full article

Minimum quantity lubrication (MQL) is a promising green technology for high-speed milling of GH4169. However, the full-chain oil mist penetration mechanism remains unclear, limiting precise parameter regulation. Based on a cross-scale mechanism, this study develops a semi-empirical oil mist penetration efficiency model coupling four key parameters and conducts single-factor and orthogonal high-speed milling experiments to validate the model and analyze the regulation mechanism using milling force and surface roughness. The experimental results show relative deviations below 6%, demonstrating good model validity and robustness. The influence hierarchy is spindle speed > nozzle orientation > nozzle angle > nozzle distance. Spindle speed and nozzle orientation are strongly coupled dominant parameters with a “drive-adaptation” mechanism, while nozzle distance and nozzle angle are weakly coupled, only notable under extreme conditions. The optimal parameters obtained via BP neural network and NSGA-II are nozzle orientation −X, angle 22.43°, distance 14.96 mm, and spindle speed 16,581 rpm. Under this combination, minimum Surface Roughness Ra of 0.17 μm and milling force of 24.27 N are achieved, reducing surface roughness by 85.32% and milling force by 53.52% versus the worst condition and reducing roughness by 28.57% versus the baseline while maintaining milling force within a reasonable range. This study clarifies the physical mechanism of MQL oil mist penetration, extending conventional macroscopic parameter optimization. The proposed cross-scale framework offers theoretical and engineering guidance for MQL parameter design in green precision machining of nickel-based superalloys. Full article

Bacterial cellulose (BC) has emerged as a structurally robust, biologically compatible, and highly adaptable biomaterial with significant potential for next-generation wound-care technologies. Its nanofibrillar, extracellular-matrix-like architecture provides exceptional moisture retention, mechanical stability, and conformability, enabling BC to function as an active scaffold rather than a traditional dressing. Advances in chemical modification, composite engineering, and bioactive functionalization, including antimicrobial metals, chitosan, biosurfactants, enzymes, and growth factors, have expanded BC’s therapeutic capabilities. Emerging smart BC dressings integrate biosensors, stimuli-responsive drug release, and 3D-printed architectures tailored to patient-specific wound geometries. Parallel developments in artificial intelligence (AI) are transforming BC production by optimizing bioprocessing, guiding genetic engineering, reducing culture media costs, and enabling real-time quality control, thereby improving scalability and industrial feasibility. These combined innovations position BC as a multifunctional, immunologically instructive, and digitally integrated platform for advanced regenerative wound care. This review reframes BC within the contemporary pathophysiology of chronic wounds, emphasizing its roles in immunomodulation, macrophage polarization, angiogenesis, mechanotransduction, and the disruption of mixed bacterial–fungal biofilms that characterize diabetic foot ulcers and other non-healing wounds. BC hydrogels typically contain >90–99% water and exhibit tensile strengths exceeding 200 MPa, enabling robust mechanical performance in wound environments. Advances in BC composites have demonstrated antimicrobial reductions of 3–5 log units against common chronic-wound pathogens. Full article

This study investigates the shear behavior of glass fiber-reinforced polymer (GFRP)-reinforced concrete (RC) beams to address challenges associated with their low elastic modulus, absence of yielding, and reduced stirrup efficiency in bending regions. GFRP bars are increasingly adopted as an alternative to steel due to their superior corrosion resistance, durability, and cost-effectiveness. This study focuses on the effects of stirrup type, stirrup spacing, and shear span-to-effective depth ratio on the structural performance of GFRP RC beams. Twelve full-scale beams were tested under four-point bending, incorporating three GFRP shear reinforcement configurations: fabricated closed stirrups, integrated straight bar systems, and discrete vertical bars. Experimental observations were analyzed in terms of failure modes, load-carrying capacity, energy absorption, and deformation characteristics. Results indicate that fabricated F-type stirrups provide the highest shear performance, though their effectiveness is limited by premature rupture at bending points. Site-integrated S- and T-type configurations offer practical alternatives, maintaining structural integrity while mitigating bend-related stress concentrations, but with slightly lower energy absorption and load capacity. Increasing stirrup spacing significantly reduces shear resistance and shifts failure from flexural to shear-dominated modes. Comparisons with widely used design codes and analytical models show that CSA S806-12 provisions offer the most reliable predictions, while other guidelines tend to over- or underestimate shear capacity depending on configuration and a/d ratio. The study highlights the importance of optimizing stirrup type and spacing to enhance the shear performance of GFRP RC beams. Findings provide valuable insights for improving current design methodologies, offering guidance for engineers seeking durable, corrosion-resistant alternatives to steel reinforcement in aggressive environments. This research demonstrates that innovative site-integrated stirrup configurations can bridge practical fabrication constraints without compromising overall shear performance, promoting more efficient and resilient GFRP RC structures. Full article

Plating on Plastics (PoP) requires specific surface pre-treatment steps to enable metallization. The conventional PoP industry utilizes hexavalent chromium (toxic, carcinogenic) and palladium (critical raw material) for surface etching and activation, respectively, raising significant health, environmental, and economic concerns. This work is based on a new Cr⁶⁺-free and Pd-free PoP technology that uses piranha (H₂O₂-H₂SO₄) solutions for surface etching, nickel salts for activation, and NaBH₄ for reduction, ultimately forming metallic nucleation sites for downstream electroless plating and electroplating. A comprehensive modeling approach was developed to simulate and predict unit operation performance (reaction kinetics and yields) and material properties (contact angle and adhesion) across processing stages of the new technology. State-of-the-art and data-driven modeling revealed the combinatorial relationships among process performance, the achieved properties and the different settings of process operating conditions. The results also highlighted capabilities for tuning all processes over a range of conditions, reaching desired product specifications (adhesion and thickness). The models were constructed as a Decision Support Tool (DST) serving economic, environmental, safety and Safe and Sustainable by Design (SSbD) objectives. The DST can be used through a user-friendly interface that enables the insertion of user-defined inputs and monitoring of optimization results. Full article

Chitin-based hydrogels have emerged as a versatile and sustainable material with significant potential in biomedical, environmental, and energy applications. Derived from the abundant biopolymer chitin, these hydrogels exhibit exceptional biocompatibility, biodegradability, and tunable physicochemical properties. This review highlights advances in chitin-based hydrogels, focusing on solvent systems, crosslinking strategies, and structural modifications to enhance mechanical strength, swelling, and stimuli responsiveness. Key applications include wound healing, drug delivery, tissue engineering, and environmental remediation, where their high-water retention, enzymatic degradability, and eco-friendly nature are particularly advantageous. Furthermore, innovations such as nanoparticle incorporation and chemical derivatization (e.g., carboxymethylation, hydroxypropylation) have expanded their utility in energy devices and smart sensors. Despite these advances, challenges remain in optimizing the energy efficiency of production methods for industrial scalability. This review provides a comprehensive overview of the current state of chitin-based hydrogels, offering insights into future directions for research and development in this promising field. Full article

High-speed railway corridors operating under dense traffic conditions often face capacity limitations and operational conflicts caused by minimum headway constraints and heterogeneous train services. Differences in running times and stopping patterns between fast and slow trains may lead to overtaking conflicts and inefficient infrastructure utilization. This study investigates a multi-objective timetable optimization problem for high-speed railways under minimum headway constraints. A timetable optimization framework is established for high-speed railways under dense heterogeneous operations. The core mathematical formulation explicitly models timetable variables and basic temporal bounds, including sectional running-time limits, dwell-time bounds, and operating time-window constraints. Additional engineering feasibility requirements, such as minimum headway, station-capacity restrictions, and in-station overtaking feasibility, are enforced through the BS-FGS feasibility-scheduling procedure and the repair-based constraint-handling mechanism in the improved MOPSO stage. A hierarchical solution framework is proposed in which a Binary Search–Feasibility-Guided Greedy Scheduling (BS-FGS) method first evaluates the maximum feasible train number and generates an initial feasible timetable, followed by an improved Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to obtain Pareto-optimal solutions within the feasible region. A case study on the Shanghai–Hangzhou High-Speed Railway corridor shows that system utilization can reach approximately 0.93–0.94 when in-station overtaking is allowed. Robustness simulations further demonstrate that the optimized timetables maintain stable train intervals and exhibit strong disturbance resistance. These results indicate that the proposed framework provides effective support for capacity evaluation and timetable optimization in high-density high-speed railway operations. Full article

Coal gangue (CG), a bulk solid waste produced during coal mining, is rich in active components such as silicon and aluminum oxides, making it a high-quality raw material for the production of cementitious materials. Its utilization represents a significant pathway for achieving high-value applications of CG and facilitating the low-carbon transformation of the cement industry. Owing to advantages such as low carbon emissions, environmental friendliness, cost-effectiveness, and tunable performance, CG-based cementitious materials have been extensively investigated by researchers worldwide. Studies have focused on various aspects, including cementitious backfill materials, CG solid waste-based cement, geopolymers, concrete, and composite materials derived from CG. This paper systematically reviews the regional distribution, mineral composition, chemical constituents, and reactivity characteristics of CG. It further summarizes recent advances in activation techniques, performance optimization, and engineering applications of CG-based cementitious materials. Current challenges, such as insufficient activation efficiency, ambiguous hydration mechanisms, and limitations in large-scale application, are critically analyzed. Finally, future research directions and development trends are outlined to provide a theoretical foundation for further investigation and industrial implementation of CG-based cementitious materials. Full article

The rational design of electrode materials with tailored composition and architecture is crucial for advancing high-capability electrochemical energy storage systems. This study reports that gadolinium-modified NiFe₂O₄ nanosheet electrodes were effectively synthesized on nickel foam via a hydrothermal approach followed by thermal treatment. A series of compositions (NiFe, NiFe–Gd1, NiFe–Gd2, and NiFe–Gd3) were prepared to systematically examine the effect of Gd incorporation on structural features and electrochemical properties. X-ray diffraction (XRD) analysis confirmed the formation of the cubic spinel NiFe₂O₄ phase without detectable secondary phases, indicating that the crystal structure remains intact after Gd introduction. X-ray photoelectron spectroscopy (XPS) further verified the presence of Ni²⁺, Fe³⁺, and Gd³⁺ species within the lattice environment. Morphological analysis using field-emission scanning electron microscopy (FESEM) revealed a nanosheet-based architecture, where the optimized NiFe–Gd2 electrode exhibited a porous and interconnected nanosheet framework with abundant exposed edges. This structural configuration improves electrolyte penetration and facilitates efficient ion transport during charge storage processes. Electrochemical measurements demonstrated that the NiFe–Gd2 electrode delivers an areal capacitance of 5235 mF cm⁻² at 10 mA cm⁻², along with improved reaction kinetics and low internal resistance. An asymmetric supercapacitor assembled using NiFe–Gd2 as the positive electrode and activated carbon as the negative electrode operated stably within a 0–1.5 V potential window, achieving an energy density of 0.136 mWh cm⁻² and a power density of 3.14 mW cm⁻², while retaining 86.55% of its initial capacitance after 7000 cycles. These results highlight the potential of rare-earth engineering as a viable strategy for designing advanced spinel ferrite electrodes and pave the way for the development of high-performance, durable, and scalable supercapacitor systems for practical energy storage applications. Full article

To explore the spectral characteristics of near-field vibration signals from multi-hole millisecond-delay blasting in open-pit mines and the modulation effect of delay time on blasting energy distribution, field blasting vibration tests with multi-gradient delays were conducted taking an open-pit coal mine in Xinjiang as the engineering background. Particle Swarm Optimization (PSO) optimized Variational Mode Decomposition (VMD) and Hilbert-Huang Transform (HHT) were introduced for the refined processing and frequency band energy ratio analysis of the measured signals, and field vibration control tests were subsequently carried out. The results show that compared with the traditional Empirical Mode Decomposition (EMD), the PSO-optimized VMD can effectively overcome the mode aliasing phenomenon. By extracting the high-frequency Intrinsic Mode Function (IMF7) that characterizes the instantaneous detonation impulse, the actual delay time was successfully inverted to be 10.47 ms. The inter-hole delay time significantly affects the time-frequency distribution of vibration energy. Under the 25 ms delay condition, the energy ratio of the high-frequency band is the highest, and the low-frequency energy accumulation degree is the lowest, which is most conducive to shortening the vibration duration and accelerating energy attenuation. Control tests further confirmed that adopting a 17 ms delay in the near-slope area can effectively control the peak particle velocity (PPV) in the near field, while adopting a 23 ms delay in the middle and far areas can further reduce the low-frequency energy concentration. The research results demonstrate a dynamic matching strategy for millisecond delays based on spatial distance differences, which has important guiding significance for realizing safe and efficient blasting vibration control in open-pit mines. Full article

The challenge of substituting bone defects necessitates the search for effective biomaterials based on biopolymer composites with biocompatible fillers. A promising approach in bone tissue engineering is the use of regenerative scaffolds based on polyhydroxyalkanoates (PHAs), specifically poly(3-hydroxybutyrate)—P(3HB), which are characterized by high biocompatibility and osteoinductive potential. In this study, we evaluate the changes in the mechanical, thermal, and morphological properties of P(3HB) within P(3HB)-copolymers/HA, P(3HB)/CS, P(3HB)/PLA/CS, and P(3HB)/PLA/HA composites. These materials, containing various filler contents (up to 70 wt.% of HA–hydroxyapatite or CS–chitosan), were obtained using melt extrusion compounding. It is shown that the modification of biopolymer matrices promotes a decrease in melting temperature, improvement of mechanical characteristics, and an increase in material elasticity. At high filler concentrations, nanoparticle agglomeration and a deterioration of physical-mechanical properties were observed. It was established that a content of 10–20 wt.% of nano-hydroxyapatite and chitosan is optimal, as these composites most closely match the mechanical properties of bone tissue. The results obtained indicate the high potential of the developed nanocomposites for the creation of biodegradable implants in reconstructive orthopedics. Full article

Steel–UHPC composite beams are widely used in bridge engineering due to their high strength, durability, and suitability for prefabricated construction. However, the mechanical performance of shear connectors in UHPC differs significantly, and the uniform use of a single connector type along the beam span may result in a mismatch between connector mechanical characteristics and regional force demands, leading to suboptimal force transfer and inefficient utilization of connector capacity along the beam span. While previous studies have mainly focused on the local behavior of individual connectors, a system-level design strategy considering regional force demands is still limited. This study proposes a system-level design method for combined shear connectors in steel–UHPC composite beams, in which headed stud connectors and trapezoidal composite dowel connectors are arranged according to bending moment distribution and interface shear demand, thereby integrating connector mechanical characteristics with the spatial variation in internal forces along the beam span. The design procedure includes shear span division, longitudinal interface shear calculation, and resistance verification of different connector types. The method is applied to a practical steel–UHPC composite beam in a long-span approach bridge. Results show that headed studs provide reliable uplift resistance and ductile behavior in negative bending regions, whereas composite dowel connectors are shown to be more suitable for shear-dominated positive bending regions due to their higher shear capacity and stiffness. The combined system ensures effective composite action under different stress states and reduces total connector steel consumption compared with a stud-only layout. The proposed approach advances connector design toward performance-oriented and system-level structural optimization, providing a practical framework for connector arrangement in steel–UHPC composite beams. Full article