Industrial decarbonisation requires the large-scale integration of renewable energy into energy-intensive processes traditionally characterised by limited flexibility, high heat demands, and strong dependence on fossil fuels. In this context, energy storage, encompassing thermal and electrical storage as well as hydrogen as an energy carrier, emerges as a key enabling solution to reconcile variable renewable supply with industrial process demands. This paper proposes a dynamic techno-economic framework linking sectoral energy profiles to storage sizing and economic performance in industrial renewable integration. Storage technologies are assessed with hydrogen emerging as a long-duration buffer and a solution for decarbonising high-temperature heat. A representative industrial plant with 5 GWh/y energy demand and an 80%/20% thermal-to-electric load split is analysed under increasing solar-to-load ratios (20–60%), with storage technologies evaluated both individually and in hybrid configurations. Results demonstrate that hybrid battery–hydrogen configurations systematically outperform single-technology solutions. Yearly energy cost reductions reach 16.6–33.8% at 20% renewable penetration, 30.0–49.6% at 40%, and 43.4–62.8% at 60%, with advantages over the best standalone option increasing on average from 13.5% to 28.0% as renewable availability rises. Overall, the study identifies scale-dependent feasibility thresholds and highlights small and medium-sized industrial plants as the most actionable deployment context under current technological and market conditions.

This study investigates the influence of waste-based materials, namely drinking water treatment sludge (DWTS) and expanded glass production waste (EGPW), on the properties of fine-grained concrete when used as partial Portland cement replacements. Fine-grained concrete mixtures containing different proportions of DWTS and EGPW were evaluated in terms of hydration behavior, microstructural development, mechanical performance, durability, and dimensional stability. Density, ultrasonic pulse velocity, water absorption, flexural and compressive strengths, drying shrinkage, and porosity parameters were determined, while frost resistance was assessed and predicted based on porosity characteristics. Hydration kinetics were analyzed using X-ray diffraction and semi-adiabatic calorimetry. The results showed that increasing EGPW content enhanced cement hydration processes and promoted matrix densification through pozzolanic reactions, resulting in reduced water absorption and improved mechanical properties. In contrast, DWTS exhibited an inhibiting effect on hydration due to its inert nature and high Fe2O3 content, acting primarily as a micro-filler; however, when combined with EGPW at moderate dosages, DWTS contributed positively to flexural strength and slightly reduced drying shrinkage. The combined use of DWTS and EGPW enabled the formation of a balanced pore structure and improved the durability of fine-grained concrete. Among the tested mixtures, ED-3 (7.5% EGPW + 5% DWTS) provided the most favorable balance between hydration activation and binder reduction, while the highest frost resistance was achieved by the ED-4 mixture, reaching approximately 603 predicted freeze–thaw cycles. Overall, the results indicate that properly optimized combinations of EGPW and DWTS can significantly enhance the performance and durability of fine-grained concrete while controlling drying shrinkage.

As global energy demand continues to grow, the inherent safety requirements for natural gas long-distance pipelines are becoming increasingly stringent. Therefore, accurately analyzing the trends in pipeline defects using multi-round internal inspection data is of great significance for enhancing pipeline inherent safety levels and reducing the risk of pipeline medium leakage. However, existing pipeline in-line inspection data alignment methods for long-distance multi-round pipeline data alignment suffer from cumbersome alignment procedures and low computational efficiency. This paper proposes an adaptive threshold dynamic time warping defect alignment method (Adaptive Dynamic Threshold-Dynamic Time Warping, ADTH-DTW) for rapidly matching multi-round in-line inspection data. A new multi-round in-line inspection data alignment framework based on valve-weld-defect is established. By integrating the DTW algorithm into each alignment stage, unnecessary manual effort is avoided, significantly improving data alignment efficiency. First, the ADTH method is used to clean redundant weld seam data in the in-line inspection data. By dynamically generating expected values and combining an intelligent point selection strategy, the method accurately identifies and removes interfering data. Additionally, valve chamber data is used to correct the overall mileage, providing a data foundation for subsequent defect alignment. Second, the dynamic time warping algorithm is used to align weld seam data and establish a data mapping table. Finally, relative displacement methods are employed to achieve defect matching. The validation results from three rounds of in-vehicle inspection data tested on-site indicate that the ADTH-DTW algorithm achieves an average 23.08% improvement in alignment accuracy compared to methods such as DTW, KL divergence, JS divergence, and linear interpolation, with computational efficiency nearly tripled. This effectively addresses the issue of incompatible computational efficiency and accuracy in existing data alignment algorithms, thereby enhancing the intrinsic safety level of natural gas long-distance pipelines.

Currently, a wide variety of food contaminants pose a threat to public health [...]

Green communities play a critical role in advancing sustainable development; however, evaluating their performance and identifying appropriate improvement strategies remain challenging due to uncertain, incomplete, and multidimensional information. This study formalizes three key processes essential to green community governance—sustainability evaluation, attribute reduction, and decision-rule generation—and proposes a rough set-based decision framework that integrates quantitative indicators, expert knowledge, and rule-based reasoning. Using empirical assessment data from Nantou County, the framework identifies the most influential determinants of community performance, including accessibility-related facilities, remote-area status, and socioeconomic conditions. The results reveal clear drivers of sustainable community performance. Remote villages lacking community hubs face structural barriers to participation. Communities without facilities supporting vulnerable groups tend to stall at the registration stage, while bronze-level villages require equity-focused engagement despite possessing stronger resource endowments. Notably, silver-level performance is consistently associated with moderate income levels and moderate income disparity, underscoring socioeconomic balance—rather than economic extremes—as a key precondition for stable sustainability advancement. Together, these findings provide interpretable, evidence-based guidance for policymakers and community managers to identify performance gaps and allocate resources more effectively.

The flow field regulation and medium migration characteristics during aggregate slurry grouting in rough fractures are directly related to the grouting repair engineering in various geotechnical projects. The selected three grouting velocities (0.5, 0.55, 0.6 m/s) are within the typical range of 0.3–0.8 m/s for high-pressure jet grouting in geothermal reservoirs. This study uses the Hurst exponent method to construct a 3D rough fracture model and simulates cement slurry flow and aggregate migration based on Fluent–EDEM two-way coupling, analyzing flow field characteristics and their impact on aggregate migration. Results show that differences in flow field pressure and viscosity affect rough fracture flow field distribution and aggregate migration, leading to segmented non-uniform velocity—higher in the ascending section (Up-leg) and Down-leg (Down-leg) and stable in the gentle section (Flat-leg) of the rough fracture—coupled with wall morphology. Particle motion is controlled by the flow field, consistent with the pattern shown in velocity contours, verifying that geometry, pressure and shear characteristics collectively govern fluid and particle movement. Pressure contours show that the pressure distribution in rough fractures is coupled with wall morphology: high pressure occurs at abrupt sections, while pressure is stable in Flat-leg. Viscosity contours indicate that the proportion of high-viscosity regions at abrupt sections is lower than that in Flat-leg. This provides theoretical support for optimizing aggregate slurry migration, improving flow field uniformity, reducing grout waste, and enhancing the construction quality and efficiency of underground engineering

To address the problems of rapid water cut increases and severe interlayer interference in offshore composite rhythmic edge-water reservoirs, this paper aims to reveal the three-dimensional spatiotemporal evolution laws of water-flooding fronts under complex heterogeneous conditions. A systematic study was carried out using a combination of three-dimensional large-scale physical simulation, mathematical derivation, and orthogonal numerical simulation. The results indicate that under composite rhythmic conditions, the dynamic interplay between the interlayer permeability differential and gravity segregation exacerbates bottom-water channeling, while a bottom low-permeability zone and a large formation dip angle effectively inhibit water underride. Crude oil viscosity and liquid production rate are the core factors affecting the recovery factor. Furthermore, the constructed water breakthrough time prediction model, which considers additional gravity potential energy, demonstrates a stable calculation error within 4.6%. The study confirms that promoting the longitudinally balanced advancement of multilayer oil–water fronts is the key to improving macroscopic sweep efficiency, and the optimized balanced sweep mode improves the ultimate recovery factor by up to 8.57% compared to the extreme channeling mode, providing scientific guidance for water control well selection and the optimization of liquid production schedules in offshore edge-water reservoirs.

The liquid spreading on structured packings plays an essential role in affecting gas–liquid mass transfer in separation columns, yet the synergistic mechanism of surface wettability and textured geometries remains insufficiently understood. This study integrates experimental and computational methods to systematically investigate the liquid spreading characteristics on textured surfaces. The synergistic combination of hydrophilic modification and surface textures markedly enhances liquid spreading performance. Compared with the hydrophilic plane surface, the spherical cap texture increases the interface area and wetted area by 25.2% and 49.6%, respectively, while the pyramid-shaped texture leads to improvements of 24.5% and 48.9%, respectively. Based on Weber number analysis, it is identified that the competition between inertial force and surface tension governs the evolution of liquid spreading regimes. In addition, the results suggest that variations in liquid viscosity and density may further influence spreading behavior by modifying the balance among inertial, viscous, and surface tension forces. The geometric parameters of spherical cap textures are systematically examined, and it is revealed that a spherical cap with a non-uniform staggered configuration (Mode III) enables the efficient liquid spreading. A new non-uniform spherical cap texture is designed to enhance liquid spreading, which enhances spreading performance compared with the original plate, increasing the interface area by 27.3% and the wetted area by 47.4%. Although the liquid film thickness increases slightly, the wetted area ratio is significantly improved, indicating enhanced effective surface coverage. Both simulations and experiments confirm that the new textured structure further enhances liquid spreading performance on the textured surface. This research unveils a strategy to improve liquid spreading through tailored surface textures, opening up new possibilities for the design of efficient packings.

This study presents a detailed colorimetric evaluation using the CIEL*a*b* system for a novel series of symmetrically structured disazo-stilbene dyes. The synthesis utilized the non-genotoxic 4,4’-diaminostilbene-2,2’-disulfonic acid as the diazotizing component, with the coupling components being N-substituted acetoacetanilide derivatives. The purity of the obtained dyes was confirmed by HPLC analysis. The color analysis was initially conducted on the dyes in solid state (powder) to investigate potential structure–color correlations. Subsequently, these parameters were applied to analyze the performance of the dyes incorporated into acrylic resin films. Titanium dioxide (P.W.6; C.I. 77891) served as the white standard, along with mixtures of dyes in different concentrations that were applied to a cellulosic substrate. The results characterize these compounds as eco-friendly dyes possessing high tinctorial strength and a significant metamerism effect.

Characterizing multiscale fracture networks in shale gas reservoirs remains challenging, while the limited applicability of conventional continuum-based models and insufficient multi-objective coordination often lead to low efficiency in development optimization. To address these issues, this study proposes a production history matching and multi-objective collaborative optimization framework for shale gas horizontal wells based on an equivalent fractal fracture (EFF) model. By integrating fractal theory with intelligent optimization techniques, a multiscale equivalent fractal permeability tensor is constructed, forming a hybrid machine-learning framework that combines physics-based fractal constraints with data-driven learning for efficient representation of complex fracture networks. Microseismic event clouds were converted into continuous fracture-density and fractal-geometry descriptors through denoising, temporal alignment, and spatial interpolation, and these descriptors were mapped to the equivalent fractal fracture model to dynamically update key flow parameters for history matching and parameter inversion. On this basis, a multi-objective collaborative optimization strategy is developed to achieve simultaneous time-varying fracture characterization and dynamic regulation of development parameters. Comparative results indicate that the EFF-based approach yields a production prediction error of 6.8%, slightly higher than the 4.2% obtained using discrete fracture network (DFN) models, while requiring only one-eighteenth of the computational time. Using the net present value (NPV) as the unified objective function, constraints are imposed on bottom-hole flowing pressure, flowback rate and system switching time for optimization. With the optimized pressure drop being more uniform and the gas saturation distribution being more balanced, it is verified that “EFF + NPV” can achieve the coordinated optimization of “production capacity—decline—cost” and enhance the development efficiency.