Based on the mechanical principle of limit equilibrium, a method for calculating the safety factor for a symmetric three-dimensional slope without assuming the inter-column forces is proposed, and the safety factor expression considering the direction and intensity of blast-induced load is derived. The three classic examples are analyzed to quantify the influence of the direction and intensity of blast-induced load on the safety factor of the slopes. The results show that under the action of blast-induced load, the most dangerous action direction of the three-dimensional symmetric slope is consistent with the resultant force direction of the sliding force; as the pseudo-static coefficient of the blast-induced load gradually increases from 0 to 0.3, the slope safety factor gradually decreases, and the safety factors of the three examples in the most unfavorable direction decrease by up to 38.89%, 29.29%, and 42.83% respectively. The proposed method and analysis results provide a reference for the stability analysis and safety risk assessment of homogeneous slopes under weapon strike conditions.
Structural planes, as weak links in rock masses, often determine the overall stability of the rock mass. To reveal the triggering mechanism of structural plane instability, the mechanical and energy characteristics during the formation of sliding surfaces are analyzed. The energy relationship for the progressive instability of structural planes is established, and an energy criterion for structural plane instability under single disturbance is proposed based on a dimensionless energy factor. The main influencing factors of block stability were quantitatively analyzed with a three-block model and a simplified bilinear shear constitutive relation. The analysis revealed that when adopting the bilinear constitutive relation, the threshold of the instability energy factor can be expressed as a function of the initial state of the structural plane and the constitutive characteristics of the material deformation. Its magnitude is proportional to the square of the nominal ultimate strain and the square of the relative magnitude of the initial shear force to the ultimate resistance, while being independent of disturbance parameters. Under single disturbance, higher disturbance frequencies require greater disturbing forces to induce instability. The main conclusions derived from the energy-based theoretical analysis are consistent with the results obtained from limit equilibrium methods and the general patterns revealed by relevant experimental results. The proposed dimensionless energy factor criterion provides a new perspective for preventing engineering disasters induced by structural plane instability.
To address the severe challenges in rapid repair and reconstruction of protective works under new conditions, this study proposes the application of a fabricated reinforced concrete arch in protective engineering. The blast resistance of the reinforced concrete arch was investigated through field blast tests and numerical simulations. Finite element models of both fabricated reinforced concrete arches and monolithic arches were established to compare and analyze their respective damage characteristics, deformation behavior, energy absorption and dissipation under blast loading. The results indicate that when the scaled distance exceeds 1 m·kg-1/3, the blast resistance of the fabricated arch is comparable to that of the monolithic arch. As the scaled distance decreases further, however, their damage mechanisms begin to differ. The damage of the fabricated arch tends to concentrate on the arch segment closest to the blast source, whereas that of the monolithic arch is distributed more uniformly. Owing to this distinct damage mechanism and the replaceability of its components, the fabricated arch offers significant advantages over the monolithic arch in scenarios requiring rapid repair and reconstruction.
The failure modes of reinforced concrete slabs exhibit dynamic transformation characteristics influenced by factors, such as structural configuration and impact conditions，and the internal damage and failure evolution after impact are difficult to measure directly. Based on the low-velocity impact tests, the numerical simulations of impact failure under multiple working conditions were conducted with the LS-DYNA software. The dynamic responses of reinforced concrete slabs under impact, including impact force, displacement, and failure characteristics, were investigated, and the transformation of failure modes as well as the influence of key factors were analyzed. The results show that simply supported reinforced concrete slabs under low-velocity impact loads exhibit four failure modes: local impact damage, global impact failure, coupled local global failure, and punching shear failure. As the impact velocity increases, the failure mode evolves sequentially from local impact damage to global impact failure, coupled local global failure, and punching shear failure. Increasing the bottom longitudinal reinforcement ratio and slab thickness significantly enhances the global bending resistance compared to the punching shear resistance. Improving concrete strength is more beneficial for enhancing punching shear resistance, thereby inducing a transformation in the failure mode of the slab. The findings can provide references for analyzing the structural safety of reinforced concrete slabs.
The process of slip instability of deep rock masses along a structural plane is closely related to energy conversion. To investigate the evolution law of pre-peak elastic strain energy during the shear process of structural planes, regular serrated structural planes of red sandstone with undulation angles of 15°, 30°, and 45° were selected. Direct shear tests and stepwise loading-unloading shear tests were carried out under different normal stress conditions.The variation laws of elastic strain energy and energy storage efficiency of red sandstone structural planes at different shear stress levels in the pre-peak stage were obtained. The test results show that as normal stress increases, the pre-peak input energy, elastic strain energy, and dissipated strain energy all continuously increase; under different undulation angle and normal stress conditions, the elastic strain energy and dissipated energy of red sandstone structural planes have a good linear relationship with the square of shear stress; under different undulation angle and normal stress conditions, the elastic strain energy of red sandstone structural planes conforms to the linear energy storage law, and the elastic strain energy at the peak shear stress moment can be estimated based on this. The research results can provide data support for revealing the failure behavior of rock structural planes from the perspective of energy.
To investigate the energy absorption characteristics of foam-cored composite fenders reinforced with trapezoidal webs, the full-scale quasi-static compression tests were carried out on the composite fenders of the Yongning Bridge. Based on a hybrid criterion, the theoretical models were derived for the equivalent compressive modulus, strength, and web relative density of a 45° trapezoidal unit cell.The results show that the specimens mainly exhibit three failure modes: web buckling, web-foam debonding, and interlaminar delamination. The ultimate load-bearing capacity reaches 705.68 kN, with an average compressive load of 627.38 kN. In the 10%-20% compression stage, the absorbed energy increases by 116.09%, and the maximum absorbed energy is 2.76×105 J, indicating a stable, stage-wise energy dissipation behavior. The deviation between the theoretical predictions and experimental results is less than 15%, demonstrating that the proposed model has good accuracy and engineering applicability.
Urban civil air defense engineering serves as a critical means for safeguarding the lives and property of urban residents and preserving war potential during wartime. This study aims to conduct a scientific assessment of the protective effectiveness of the urban civil air defense engineering. Based on the constituent factors of the urban civil air defense engineering's overall efficacy, an evaluation index system was established around the five key dimensions: fundamental protection, peacetime-to-wartime conversion, system connectivity, spatial layout, and supporting facilities. The fuzzy comprehensive evaluation method was utilized to perform the assessment. By evaluating the protective effectiveness of three typical urban civil air defense engineering, the operability of the proposed index system and method were successfully validated. The findings of this research can serve as a valuable reference for the future planning and construction of urban civil air defense engineering.
To address the challenges of reliable communication path selection and transmission rate maximization for unmanned aerial vehicle (UAV) swarms in malicious interference environments, an anti-jamming communication path selection model is established based on the dynamic multi-armed bandit (DMAB) under the condition of unknown jammer channel state information. The dynamically updated "arms" are used to represent the set of available paths, and worse paths are dynamically eliminated. The intelligent anti-jamming path selection algorithms, Dyn-UCB and Dyn-ε-greedy, are proposed to balance the trade-off between exploration and exploitation, so as to obtain the optimal transmission path. The simulation results show that the Dyn-UCB algorithm has a faster convergence speed, while the Dyn-ε-greedy algorithm has better performance after convergence. The two proposed algorithms have low computational complexity, and the performance is better than other path selection algorithms such as the shortest hop algorithm and the shortest transmission distance algorithm, and can still maintain good performance under severe jamming conditions.
This paper proposes an emotion-multi-objective particle swarm optimization (EMMOPSO) algorithm to address the issues of low efficiency and poor coordination in task allocation and path planning for unmanned aerial vehicle （UAV） swarms operating in complex dynamic environments. Based on the classical multi-objective particle swarm optimization framework, a quantitative emotional state model is established, and dynamic emotion propagation equations are formulated to describe inter-individual emotional interactions, enabling the dynamic election and coordinated control of leading UAVs within the swarm. An emotion-benefit game mechanism is introduced, which incorporates task priority and emotional state utility functions to effectively mitigate task overlap and resource competition. Additionally, an emotion-objective coupled evaluation function is designed, integrating factors such as path length, safety, and curvature variation. Emotional factors are utilized to adjust the inertia weight of the particle swarm, balancing global exploration and local optimization. The simulation results show that in scenarios involving 10 to 15 UAVs, compared with the algorithms such as multi-objective particle swarm optimization, artificial bee colony, dung beetle optimization, and ant colony optimization, the proposed algorithm achieves average improvements of approximately 32% in task completion time, 11% in path length, and 70% in convergence speed. By enhancing the adaptability of swarm intelligence systems through emotion modeling, this method provides a novel optimization paradigm for UAV cooperative decision-making.
In the field of task planning and spectrum resources allocation for multiple unmanned aerial vehicle (UAV) formations, traditional approaches often face challenges in effectively coordinating task planning and spectrum resources allocation across UAV formations, resulting in inefficient task execution and underutilization of spectrum resources. To address this issue, a mixed-integer nonlinear programming model is formulated, which consists of UAV formation sizes, task execution sequences, and bandwidth allocation strategies. In addition, a multi-start joint optimization algorithm integrating a genetic algorithm with the gradient projection method is proposed. The genetic algorithm is employed to generate candidate solutions for discrete variables, while the gradient projection method efficiently optimizes continuous variables. The proposed algorithm can effectively handle multi-start multi-UAV formation planning scenarios, which explores the solution space from multiple initial points to avoid falling into local optimum, thereby enhancing solution diversity and robustness. The simulation results validate the superiority of the proposed algorithm over the traditional methods in terms of the rationality of task allocation, utilization efficiency of UAV resources and overall task yield. Furthermore, the algorithm demonstrates enhanced convergence and significantly higher task rewards in complex scenarios.
Blockchain technology is crucial for ensuring data security, trustworthiness, and transparency in the Industrial Internet of Things (IIoT), facilitating the trust and secure interactions among Internet of Things (IoT) devices, and accelerating the development of industrial automation and intelligence. However, the blockchain deployment in IIoT is facing issues such as the dynamic complex network topology and the limited energy of wireless nodes. This paper proposes a wireless node transmission power determination framework using graph convolutional neural network (GCN). The relationship between transmission power and delay is first analytically obtained by fitting sufficient experimental data. Then, the system utility optimization problem is formulated by taking the energy consumption, fork rate, delay, and hash computing power into account. After training, the GCN can quickly determine the optimal transmission power for wireless blockchain nodes using information such as node hash power, network topology graphs, blockchain block intervals, and block sizes, thereby enhancing the system energy efficiency and deployment timeliness of IIoT blockchains.The experimental results show that the proposed method can efficiently obtain the desired transmission power value of wireless blockchain nodes in the complex wireless IoT environment, with an average relative deviation from the optimal value of less than 1.81%.
To address vehicle entrapment and pavement instability caused by soft ground in tidal flat areas, this research focuses on overcoming key technical bottlenecks in current physical reinforcement methods，namely low construction efficiency, high costs of chemical modification, and insufficient durability of composite materials. A systematic study was conducted by integrating field tests with numerical simulations. Based on time-history data of earth pressure, strain, and displacement measured in a 60-ton tracked vehicle loading test site, combined with parametric modeling in ABAQUS, the load-bearing performance of a composite structure comprising a chemically stabilized layer and an aluminum alloy deck plate was validated. The results demonstrate that the aluminum alloy deck plate maintains an elastic working state under load and, synergistically interacting with a 20 cm-thick chemically stabilized layer, forms a composite foundation solution with low additional stresses. This effectively meets the traffic requirements of heavy-duty vehicles. The findings not only enhance the theoretical framework of layered foundation synergistic bearing mechanisms but also provide a time-efficient and cost-effective engineering solution for military mobility support through the engineering practice of "chemical stabilization combined with aluminum alloy deck paving".
Aiming at the continuous rotation of principal stress axis of subgrade soil element induced by traffic load, a series of vertical-torsional coupled shear tests were conducted on solidified lightweight soil of soda residue with GCTS hollow cylindrical torsional apparatus. The tests aimed to reveal the evolution of dynamic strength and stiffness degradation under varying major principal stress direction angles, intermediate principal stress coefficients, vibration frequencies, and densities. The results show that the dynamic strength decreases significantly as the major principal stress direction angle α increases, with a reduction of 21.5% to 26.7% observed at α= 90°. As the intermediate principal stress coefficient varies from 0 to 0.75, the dynamic strength initially increases and then decreases. Under the same number of cycles to failure, the dynamic strength increases with both vibration frequency and density. The tangent stiffness development of solidified lightweight soil of soda residue can be divided into three stages: hardening, degradation, and stabilization. A critical yield strain exists between 0.25% and 0.5%, which remains unaffected by the initial stress state and the vibration frequency of cyclic loading. The influence of different factors on tangent stiffness varies, and a stiffness degradation model reflecting its nonlinear relationship with generalized shear strain was established. The findings provide data support for improving the long term service performance of road engineering.
