Search Results (2,135)

The issue of working face stability in shield tunnels crossing inclined layered soil is addressed by a modified version of the Mohr–Coulomb strength criterion. This model considers spatial nonhomogeneity and anisotropy of the soil layer, and enables a 3D tunnel stability analysis. It derives the energy equation using virtual work, finds the ultimate support stress at the working face, and solves for its optimal upper bound using an algorithm. This research examined the impact of soil nonhomogeneity, anisotropy, and reduced tensile strength parameters on the stability of tunnel working faces. The results demonstrate the validity of the model, as the findings are consistent with existing research when only tensile strength is considered. The ultimate support force decreases with the nonhomogeneous coefficient and increases with the nonhomogeneously directional angle. The ultimate support force decreases first, and then increases with the soil layer’s inclined angle. Soil layers between 10° and 30° have the lowest ultimate support force. This ultimate support force gets stronger with an increasing anisotropic coefficient. Case studies show that using a method that accounts for soil tensile strength to calculate tunnel working face support force results in a relative error of only 1.92%, improving tunnel stability assessment accuracy. Full article

With the global climate warming, the temperature conditions in permafrost regions have changed significantly, and the stability of permafrost slopes is facing serious threats. This paper focuses on the construction of the instability mechanism and prediction model of permafrost slopes considering the influence of temperature. By analyzing the thermokarst collapse process of permafrost slopes, the characteristics and causes of stages such as the soil loosening period and the surface sloughing period were studied. Based on the Mohr–Coulomb strength criterion, combined with the simplified Bishop method and the Morgenstern–Price method, a mechanical analysis of the critical state was carried out, and a safety factor formula applicable to the critical state of permafrost slopes was derived. From the curves of the total cohesion and effective internal friction angle of the experimental soil changing with temperature, an influence model of temperature on the strength parameters was fitted. Considering the factor of freeze–thaw cycles, a safety factor model for permafrost slopes was constructed. Through a large amount of data calculation and analysis of the model, the reliability of the model was verified. This model can be used to predict slope states in practical assessments and optimize slope support structure design parameters in cold regions, providing important references for ensuring engineering safety, reducing geological disasters, and promoting sustainability in cold regions. Finally, potential mitigation measures for frozen soil slope instability based on the findings are briefly discussed. Full article

Metal-oxide surge arresters (MOSAs) are critical devices for overvoltage protection in power systems, and the aging characteristics of their zinc oxide (ZnO) varistors under impulse and power-frequency voltages exhibit significant differences. However, traditional methods for monitoring the aging state of surge arresters suffer from limitations such as insufficient sensitivity and vulnerability to harmonic interference. Therefore, this study conducted accelerated aging experiments on ZnO varistor samples under negative-polarity impulse currents. Key parameters were measured, including the DC reference voltage, the DC leakage current, nonlinear coefficients, and the full current under harmonic-containing power-frequency voltage at a voltage ratio of 0.6. The resistive component was accurately extracted from the full current using a separation method based on the Levenberg–Marquardt (LM) optimization algorithm. Spectral analysis was then performed on both the full current and the extracted resistive current components. The experimental results demonstrate a significant polarity effect in the aging of ZnO varistors under unipolar impulse currents. The LM optimization algorithm enables precise extraction of the resistive current component from the full current. Furthermore, compared to the fundamental and third harmonic components, the amplitude of the DC component within the resistive current exhibits the highest sensitivity to aging, establishing it as a viable aging criterion. Full article

Unmanned Aerial Vehicles (UAVs) are widely used in meteorology and logistics due to their unique advantages nowadays. During their lifecycle, uncertainties—such as flight condition variations—can significantly affect both design and performance, making Robust Aerodynamic Design Optimization (RADO) essential. However, existing RADO methodologies face high computational cost of uncertainty analysis and inefficiency of conventional optimization algorithms. To address these challenges, this paper proposed a novel RADO methodology integrating a Stochastic Kriging (SK) surrogate model with the PPO-Clip reinforcement learning algorithm, targeting atmospheric uncertainties encountered by turbojet-powered UAVs in transonic cruise. The SK surrogate model, constructed via Maximin Latin Hypercube Sampling and refined using the Expected Improvement infill criterion, enabled efficient uncertainty quantification. Based on the trained surrogate model, a PPO-Clip-based RADO framework with tailored reward and state transition functions was established. Applied to the RAE2822 airfoil under Mach number perturbations, the methodology demonstrated superior reliability and efficiency compared with L-BFGS-B and PSO algorithms. Full article

This paper proposes a rolling bearing fault diagnosis method based on HFMD and a dual-branch parallel network, aiming to address the issue of diagnostic accuracy being compromised by the disparity in data quality across different source domains due to sparse feature separation in rolling bearing acoustic signals. Traditional methods face challenges in feature extraction, sensitivity to noise, and difficulties in handling coupled multi-fault conditions in rolling bearing fault diagnosis. To overcome these challenges, this study first employs the HawkFish Optimization Algorithm to optimize Feature Mode Decomposition (HFMD) parameters, thereby improving modal decomposition accuracy. The optimal modal components are selected based on the minimum Residual Energy Index (REI) criterion, with their time-domain graphs and Continuous Wavelet Transform (CWT) time-frequency diagrams extracted as network inputs. Then, a dual-branch parallel network model is constructed, where the multi-scale residual structure (Res2Net) incorporating the Efficient Channel Attention (ECA) mechanism serves as the temporal branch to extract key features and suppress noise interference, while the Swin Transformer integrating multi-stage cross-scale attention (MSCSA) acts as the time-frequency branch to break through local perception bottlenecks and enhance classification performance under limited resources. Finally, the time-domain graphs and time-frequency graphs are, respectively, input into Res2Net and Swin Transformer, and the features from both branches are fused through a fully connected layer to obtain comprehensive fault diagnosis results. The research results demonstrate that the proposed method achieves 100% accuracy in open-source datasets. In the experimental data, the diagnostic accuracy of this study demonstrates significant advantages over other diagnostic models, achieving an accuracy rate of 98.5%. Under few-shot conditions, this study maintains an accuracy rate no lower than 95%, with only a 2.34% variation in accuracy. HFMD and the dual-branch parallel network exhibit remarkable stability and superiority in the field of rolling bearing fault diagnosis. Full article

Shape memory alloy dampers (SMADs) are widely applied in structural vibration control due to their excellent superelastic properties. However, there has been no research on the random wind-induced vibration control of transmission tower-line (TTL) systems with added SMADs. To address this gap, this paper proposes an analytical framework for the wind-induced vibration control of TTL systems with SMADs under random wind loads. An analytical model for the coupled TTL system is developed. The constitutive relationship of the SMAD is derived using the statistical linearization method, and a vibration control approach for the TTL-coupled system with SMADs is proposed. The vibration response of the TTL–SMAD system under random wind loads is derived, and an extreme response analysis framework based on the first exceedance failure criterion is established. The results show that the optimal installation scheme for the SMAD achieves a vibration reduction of more than 30%. When the damper’s stiffness coefficient is approximately 1, the SMAD effectively controls the vibrations. Moreover, a service temperature of 0 °C is found to be the optimal control temperature for the SMAD. These findings provide important references for the application of SMADs in the vibration control of TTL systems. Full article

The performance of passive target localization is significantly influenced by the positions of unmanned aerial vehicle swarms (UAVs). In this paper, we investigate the problem of UAV path optimization to enhance the localization accuracy. Firstly, a passive target localization signal model based on the time difference of arrival (TDOA) algorithm, which is then improved by the Chan method and Taylor series expansion, is established. Secondly, the Cramer–Rao lower bound (CRLB) of the modified TDOA algorithm is derived and adopted as the evaluation criterion to optimize the UAVs’ positions at each time step. Different from the existing works, in this paper, we consider the UAVs to have variable speed; therefore, the feasible region of the UAVs’ positions is changed from a circle into an annular region, which will extend the feasible region, enhancing the localization accuracy while increasing the computation complexity. Thirdly, to improve the efficiency of the UAV path optimization algorithm, the particle swarm optimization (PSO) algorithm is applied to search for the optimal positions of the UAVs for the next time step. Finally, numerical simulations are conducted to verify the validity and effectiveness of the proposals in this paper. Full article

This article introduces a computational tool for Bayesian estimation of the expected time until the next event occurs in both homogeneous Poisson processes (HPPs) and non-homogeneous Poisson processes (NHPPs), following a truncated time. The estimation utilizes the linear exponential (LINEX) asymmetric loss function and incorporates both gamma and non-informative priors. Furthermore, it presents a minimax-type criterion to ascertain the optimal sample size required to achieve a specified percentage reduction in posterior risk. Simulation studies indicate that estimators employing gamma priors for both HPP and NHPP demonstrate greater accuracy compared to those based on non-informative priors and maximum likelihood estimates (MLE), provided that the proposed data-driven method for selecting hyperparameters is applied. Full article

This paper addresses the challenge of determining optimal parameters in chaotic systems used for image encryption algorithms based on chaos theory. A baseline algorithm employing a third-order Lorenz chaotic system is examined, incorporating core procedures such as permutation (shuffling) and diffusion. Graphical results are presented to illustrate the variation of image entropy in relation to changes in system parameters. The analysis reveals a distinct region in the parameter space where entropy reaches its highest values. Based on these observations, an optimality criterion is formulated, defining an objective function that captures the entropy’s sensitivity to two key system parameters, including the bifurcation parameter. A complex objective function is derived, and the optimization problem is solved using a modified version of the Price algorithm enhanced with artificial intelligence techniques. The proposed modification demonstrates superior performance in locating the global extremum of the objective function, resulting in enhanced security of the encrypted image. Numerical and graphical results for various images are provided, along with a comparative analysis between the standard and the modified Price method. Full article

In order to study the influence of rock mechanical behavior under different saturation conditions on the stability of deep caverns, this paper establishes a mechanical model for bottom drum failure in deep chambers based on Pratt’s pressure arch theory and the upper bound theorem of limit analysis, comprehensively considering the effect of rock saturation. An analytical solution for the surrounding rock pressure under the nonlinear Hoek–Brown criterion is derived, and the optimal upper bound solution is obtained. The study systematically investigates the influence of rock saturation, geostress, and Hoek–Brown parameters (GSI, σ_c0, σ_c100, m_i, D) on the surrounding rock pressure and the characteristics of potential failure surfaces. The results indicate that the surrounding rock pressure exhibits two-stage variation with saturation degree (S_r): when S_r = 0~0.6, the surrounding rock pressure increases significantly, and the growth rate slows and tends to stabilize when S_r exceeds 0.6. Increases in ground stress field parameters (σ_v, λ) significantly raise the surrounding rock pressure and expand the potential failure zone. Among the Hoek–Brown parameters, increases in GSI, σ_c0, σ_c100, and m_i enhance the stability of the surrounding rock, while an increase in the disturbance factor D reduces its bearing capacity. The results of this paper can provide theoretical guidance for the stability evaluation of deep underground chambers. Full article

Background/Objectives: The optimal protein dose for critically ill cancer patients, especially for muscle mass preservation and survival, remains unclear. This study evaluated whether a higher protein intake, compared to usual intake, was associated with improved clinical outcomes in this population. Methods: This was a prospective analysis of critically ill adult cancer patients admitted to an oncological intensive care unit (ICU). Patients were initially assigned to receive protein prescriptions of either 1.5 or 2.0 g per kilogram per day (g/kg/day), but due to common limitations in achieving prescribed targets in this setting, a prespecified per-protocol analysis was conducted. After three days of exclusive nutritional therapy, patients were reclassified into two groups based on actual protein intake: >1.5 g/kg/day (higher intake group, IG) and ≤1.5 g/kg/day (usual intake group, CG). The primary outcome was muscle mass preservation, measured by quadriceps muscle thickness (QMT) via ultrasound on days 1, 7, and 14. Secondary outcomes included ICU survival, hospital and ICU length of stay, mechanical ventilation duration, dialysis requirement, and 60-day survival. Results: From June 2019 to September 2023, 117 patients were included. Following the planned interim analysis, the study was stopped after meeting the Pocock criterion for ICU survival (p = 0.0013). After reclassification, 68.4% (n = 80) were in the IG and 31.6% (n = 37) in the CG. ICU stay was similar (both medians 13 days), but the IG had shorter hospital stays [21.0 vs. 27.5 days, p = 0.020], less QMT loss, and improved ICU (HR = 0.31, 95% CI 0.15–0.64), hospital (HR = 0.43, CI 0.23–0.80), and 60-day survival (HR = 0.43, CI 0.23–0.80), along with shorter ventilation duration (HR = 0.54, CI 0.30–0.99). Conclusions: Higher protein intake (>1.5 g/kg/day) was associated with better muscle mass preservation and improved clinical outcomes in critically ill cancer patients. Full article

Carbon fiber reinforced polymer (CFRP) composites are prone to developing localized material loss defects during long-term service, which can severely degrade their mechanical properties and structural reliability. To address this issue, this study proposes a multi-sensor synchronous monitoring method combining embedded fiber Bragg grating (FBG) sensors and surface-mounted electrical resistance strain gauges. First, finite element simulations based on the three-dimensional Hashin damage criterion were performed to simulate the damage initiation and propagation processes in CFRP laminates, revealing the complete damage evolution mechanism from initial defect formation to progressive failure. The simulations were also used to determine the optimal sensor placement strategy. Subsequently, tensile test specimens with prefabricated defects were prepared in accordance with ASTM D3039, and multi-sensor monitoring techniques were employed to capture multi-parameter, dynamic data throughout the damage evolution process. The experimental results indicate that embedded FBG sensors and surface-mounted strain gauges can effectively monitor localized material loss defects within composite laminate structures. Strain gauge measurements showed uniform strain distribution at all measuring points in intact specimens (with deviations less than 5%). In contrast, in defective specimens, strain values at measurement points near the notch edge were significantly higher than those in regions farther from the notch, indicating that the prefabricated defect disrupted fiber continuity and induced stress redistribution. The combined use of surface-mounted strain gauges and embedded FBG sensors was demonstrated to accurately and reliably track the damage evolution behavior of defective CFRP laminates. Full article

Cilantro (Coriandrum sativum L.) is a popular annual culinary herb grown for its leaves or seeds. With the increase in hydroponic herb production in controlled environments, a need exists for leaf tissue nutrient standards specific to this production system. The objective of this study was to develop comprehensive foliar mineral nutrient interpretation ranges for greenhouse-grown cilantro. Cilantro plants were grown in a hydroponic sand culture system to induce and document nutritional disorders. Plants were supplied with a modified Hoagland’s solution, which was adjusted to individually add or omit one nutrient per treatment while holding all others constant. Deficiency and toxicity symptoms were photographed, after which the plant tissue was collected to determine plant dry weight and critical tissue nutrient concentrations. Nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulfur (S), boron (B), iron (Fe), and zinc (Zn) deficiencies, as well as B toxicity, were induced. Deficiencies of copper (Cu), manganese (Mn), and molybdenum (Mo) were not observed during the experiment. Additional foliar tissue analysis data (n = 463) were compiled to create nutrient interpretation ranges for 12 essential elements based on a hybrid meta-analysis Sufficiency Range Approach (SRA). This approach defines ranges for deficient, low, sufficient, high, and excessive values. For each element, the optimal distribution was selected according to the lowest Bayesian Information Criterion (BIC) value. A Normal distribution best represented K and S. A Gamma distribution best represented P, Ca, Mn, and Mo, whereas a Weibull distribution best represented N, Mg, B, Cu, Fe, and Zn. These interpretation ranges, along with descriptions of typical symptomology and critical tissue nutrient concentrations, provide useful tools for both diagnosing nutritional disorders and interpreting foliar nutrient analysis results of greenhouse-grown cilantro. Full article

Synergizing soil quality improvement and greening for increased yields are essential to ensuring grain security and developing sustainable agriculture, which has become a key issue in agricultural cultivation. This study considers a contract farming supply chain composed of a risk-averse farmer and a risk-neutral firm making green and efficient technology (GET) investments, which refers to the use of technology monitoring to achieve fertilizer reduction and yield increases with yield uncertainty. Based on the CvaR (Conditional value at Risk) criterion, the Stackelberg game method is applied to construct a two-level supply chain model and analyze different cooperation mechanisms. The results show that when the wholesale price is moderate, both sides will choose the cooperative mechanism of cost sharing to invest in technology; the uncertainty of yield and the degree of risk aversion have a negative impact on the agricultural inputs and GET investment, and when yield fluctuates greatly, the farmer invests in GET to make higher utility but lowers profits for the firm and supply chain. This study provides a theoretical basis for GET investment decisions in agricultural supply chains under yield uncertainty and has important practical value for promoting sustainable agricultural development and optimizing supply chain cooperation mechanisms. Full article

To meet the demands of deep grid integration of renewable energy and long-distance power transmission, this paper presents a hybrid multi-infeed DC system architecture that includes an AC power source (AC), a voltage source converter (VSC), and a modular multilevel converter (MMC). Addressing the limitations of traditional differential protection—such as insufficient sensitivity under high-resistance grounding and susceptibility to false operations under out-of-zone disturbances—this paper introduces an enhanced current differential criterion based on dynamic phasor analysis. By effectively decoupling DC bias and load current components and optimizing the calculation of action and braking quantities, the proposed method enables the rapid and accurate identification of typical faults, including high-resistance grounding, three-phase short circuits, and out-of-zone faults. A multi-scenario simulation platform is built using MATLAB to thoroughly validate the improved criterion. Simulation results demonstrate that the proposed method offers excellent sensitivity, selectivity, and resistance to false operations in multi-infeed complex systems. It achieves fast fault detection (~2.0 ms), strong sensitivity to high-resistance internal faults, and low false tripping under a variety of test scenarios, providing robust support for next-generation DC protection systems. Full article