To address the core challenge of achieving optimal risk-return tradeoff under distributional uncertainty, this paper proposes a multi-period distributionally robust portfolio optimization model that integrates Conditional Value at Risk (CVaR) with Wasserstein ambiguity sets. To handle the unknown distribution of asset returns, we employ a stationary block bootstrap method to construct Wasserstein ambiguity sets that preserve temporal dependence structures. By exploiting the piecewise linear structure of the CVaR loss function and leveraging the Wasserstein metric along with Lagrangian duality techniques, we reformulate the tri-level optimization problem into an equivalent tractable linear programming formulation that can be efficiently solved. Furthermore, we introduce an adaptive τ mechanism that maps an EWMA volatility z-score through a bounded sigmoid function to dynamically adjust the CVaR-mean tradeoff weight at each rebalancing date, enabling automatic adaptation to heterogeneous market regimes without manual recalibration. Empirical results based on 30 constituent stocks of the Dow Jones Industrial Average (DJIA) over 2500 trading days demonstrate that the proposed model achieves superior out-of-sample performance in terms of annualized return, Calmar ratio, conditional Sharpe ratio, and maximum drawdown control compared to six benchmark strategies including classical mean-variance, distributionally robust, and passive investment approaches.
Deep coal-rock reservoirs are considered excellent carriers for CO2 sequestration due to their widespread distribution and substantial storage capacity. However, the sealing performance of these reservoirs is compromised by the development of natural fractures and pronounced heterogeneity, making them susceptible to CO2 leakage. To address this challenge, this study developed a novel CO2-enhanced sequestration system specifically designed for deep coal seams. Sodium silicate was selected as the primary agent in the system by using the interaction energy between the agent and the initiator as the screening criterion. The system formulation was then optimized through experimental design. The solidification mechanism was elucidated, revealing the formation of a three-dimensional cross-linked network via dehydration condensation between silanol groups. Silicon-oxygen bonds and the aromatic skeleton serve as key structural units, imparting high strength and adaptability to the system. Injection and plugging experiments demonstrated that the optimized system exhibits excellent and broadly applicable plugging performance. In fractured coal-rock masses with permeability ranging from 60 mD to 1600 mD, the residual resistance coefficient remained high, decreasing only from 31 to 10, indicating that the system effectively blocks seepage channels across a wide permeability range. These results confirm that the developed system can significantly enhance reservoir CO2 sequestration by sealing fractures, provides a promising material approach and theoretical basis for CO2 sequestration in deep coal seams.
Grouting reinforcement is essential for controlling deep fractured surrounding rock. The grout–rock interface constitutes the weak link in the reinforcement system, yet its mesoscopic mechanical properties and damage mechanisms remain poorly understood. This study proposes a heterogeneous parameter characterization method for the interfacial transition zone (ITZ) based on the Weibull distribution. Combined with the finite-discrete element method (FDEM), refined numerical simulation of mesoscopic damage evolution of the grout–rock interface is achieved. Mesoscopic mechanical tests and nanoindentation tests were performed to obtain key mesoscopic mechanical parameters of the grout–rock interface. The mesoscopic mechanical tests contain two loading schemes: mesoscopic three-point bending tension (Meso-TPB) and anti-symmetric four-point bending shear (Meso-ASFPB). Tests cover three rock types (mudstone, sandstone, coal rock) and three water-cement ratios (0.3, 0.4, 0.5). Secondly, a Weibull probability distribution function is adopted to quantify the statistical distribution of interface parameters, and a statistical damage model considering the water-cement ratio effect is established. The damage variable D is introduced to realize cross-scale description from mesoscopic deterioration to macroscopic failure. Based on experimental results, an improved FDEM mesoscopic model of the grout-rock interface is developed to reproduce heterogeneous ITZ structural features. In this model, cohesive elements mechanical parameters follow the Weibull distribution calibrated by experimental data. The simulated crack propagation patterns, load–displacement responses, and probability distribution of peak axial force are in excellent agreement with experimental measurements, with maximum error within 10%. The results demonstrate that the grout-sandstone interface exhibits the best mechanical performance and the lowest parameter dispersion, while the grout-coal rock interface has the weakest mechanical properties and the most prominent randomness. Increasing the water-cement ratio degrades interface mechanical parameters and exacerbates parameter discreteness. The integrated experimental-statistical-simulation framework proposed in this paper provides a mesomechanical foundation and reliable numerical tool for the grouting reinforcement design of deep underground roadway
Designing lubricant additives capable of simultaneously improving lubrication and impact resistance remains a significant challenge in tribological systems operating under complex loading conditions. In this work, hollow mesoporous silica nanoparticles (HMSNs) encapsulating high-viscosity polyethylene glycol (PEG6000) were fabricated and further modified with a polydopamine shell to construct PEG6000@HMSN@PDA nano-additives dispersed in PEG200 base fluid. Rheological measurements revealed pronounced shear-thickening behavior at high particle concentrations, while tribological tests demonstrated a substantial reduction in friction coefficient and wear compared with the base lubricant. The optimized additive concentration produced stable boundary lubrication conditions and reduced peak impact force, indicating enhanced energy dissipation capability under cyclic impact loading. Surface analyses suggest that the improved performance originates from the synergistic effects of nanoparticle deposition, physical surface protection, and pressure-induced release of viscous PEG6000 within the contact zone. These findings provide a feasible strategy for designing multifunctional lubricant additives capable of adapting to both sliding and impact conditions.
Halide salts are widely used to mitigate coal spontaneous combustion (CSC), yet their performance can be compromised under complex industrial conditions. To develop a cost-effective and high-performance alternative, this study systematically evaluates lithium chloride (LiCl) as an inhibitor and examines how application mode affects CSC suppression. Three types of inhibited coal samples with different degrees of metamorphism were prepared using solution soaking and direct mixing methods, with varying amounts of LiCl (5, 10, 15, and 20 wt%) Macro-oxidation indicators, including indicator-gas evolution, crossing point temperature(CPT), inhibition rate, and characteristic temperatures from thermogravimetric analysis(TG), were quantified via temperature-programmed oxidation and TG to elucidate the coupled effects of dosage and application mode. LiCl significantly suppressed coal oxidation under both application modes, and the inhibitory effect increased monotonically with dosage; 20 wt% consistently yielded the strongest suppression across all coal ranks among the tested concentrations (5-20 wt%). Overall efficacy followed lignite > bituminous coal > anthracite, primarily reflecting rank-dependent differences in pore structure . For lignite treated with 20 wt% LiCl solution, CPT increased by 19.1 degrees C, the critical temperature increased by 33.3 degrees C, and the temperature athe temperature of the maximum weight loss rateimum mass-loss rate was delayed by 69.7 degrees C, corresponding to a mean inhibition rate of 60.44 %. Notably, the preferred application mode depends on coal rank: powder blending is more effective for lignite, whereas solution immersion is more suitable for bituminous coal and anthracite. For lignite, powder blending produced critical temperatures up to 4.8 degrees C higher than solution immersion and achieved a peak mean inhibition rate of 63.55 % at 20 wt%. These findings identify LiCl as a promising and economically viable halide inhibitor and provide guidance for optimizing application strategies based on coal-rank properties.
