Search

In the entire wind turbine system, the blade acts as the central load-bearing element, with its stability and reliability being essential for the safe and effective operation of the wind power unit. Carbon fiber, known for its high strength-to-weight ratio, high modulus, and lightweight characteristics, is extensively utilized in blade manufacturing due to its superior attributes. Despite these advantages, carbon fiber composites are frequently subjected to cyclic loading, which often results in fatigue issues. The presence of internal manufacturing defects further intensifies these fatigue challenges. Considering this, the current study focuses on carbon fiber composites with multiple pre-existing cracks, conducting both static and fatigue experiments by varying the crack length, the angle between cracks, and the distance among them to understand their influence on the fatigue life under various conditions. Furthermore, this study leverages the advantages of Paris theory combined with the Extended Finite Element Method (XFEM) to simulate cracks of arbitrary shapes, introducing a fatigue simulation method for carbon fiber composite laminates with multiple cracks to analyze their fatigue characteristics. Concurrently, the Particle Swarm Optimization (PSO) algorithm is employed to determine the optimal weight configuration, and the Backpropagation neural network (BP) is used to train and adjust the weights and thresholds to minimize network errors. Building on this foundation, a surrogate model for predicting the fatigue life of carbon fiber composite laminates with multiple cracks under conditions of physical parameter uncertainty has been constructed, achieving modeling and assessment of fatigue reliability. This research offers theoretical insights and methodological guidance for the utilization of carbon fiber-reinforced composites in wind turbine blade applications. [ABSTRACT FROM AUTHOR]

The quality and reliability of wind turbine blades, as core components of wind turbines, are crucial for the operational safety of the entire system. Carbon fiber is the primary material for wind turbine blades. However, during the manufacturing process, manual intervention inevitably introduces minor defects, which can lead to crack propagation under complex working conditions. Due to limited understanding and measurement capabilities of the input variables of structural systems, the distribution parameters of these variables often exhibit uncertainty. Therefore, it is essential to assess the impact of distribution parameter uncertainty on the fatigue performance of carbon-fiber structures with initial cracks and quickly identify the key distribution parameters affecting their reliability through global sensitivity analysis. This paper proposes a sensitivity analysis method based on surrogate sampling and the Kriging model to address the computational challenges and engineering application difficulties in distribution parameter sensitivity analysis. First, fatigue tests were conducted on carbon-fiber structures with initial cracks to study the dispersion of their fatigue life under different initial crack lengths. Next, based on the Hashin fatigue failure criterion, a simulation analysis method for the fatigue cumulative damage life of cracked carbon-fiber structures was proposed. By introducing uncertainty parameters into the simulation model, a training sample set was obtained, and a Kriging model describing the relationship between distribution parameters and fatigue life was established. Finally, an efficient input variable sampling method using the surrogate sampling probability density function was introduced, and a Sobol sensitivity analysis method based on surrogate sampling and the Kriging model was proposed. The results show that this method significantly reduces the computational burden of distribution parameter sensitivity analysis while ensuring computational accuracy. [ABSTRACT FROM AUTHOR]

The fatigue of adhesive joints in offshore wind turbine blades is a critical and widespread challenge, necessitating an urgent focus on adhesive bond reliability. Given the constraints of full-scale testing, this research explores the fatigue endurance of carbon fiber–epoxy adhesive composites, integral to blade construction. Recognizing the fatigue characteristics' sensitivity to environmental factors and joint dimensions, an innovative approach to fatigue modelling and evaluation is introduced. This method incorporates the influence of different environmental stresses and size effects. Specifically, a degradation coefficient and size impact factor (SIF) are introduced into the cyclic cohesive zone model, and a simulation-based analytic approach is proposed for analyzing adhesive fatigue. Furthermore, we introduce a reliability modelling procedure that integrates performance degradation theory to address the deteriorative characteristics inherent in adhesive fatigue. Subsequently, the specimens' damage accumulation increased by 75% because of the stresses and escalated to 85% with adhesive joint size effects, causing carbon fiber Reinforced Polymer/epoxy adhesive joints to fail interfacially rather than in a mixed-mode manner. This study provides valuable insights for the safety analysis and assessment of adhesive joint performance in offshore wind turbine blades. [ABSTRACT FROM AUTHOR]

The energy inside the Earth can not only be released outward through earthquakes and volcanoes but also can be used by humans in the form of geothermal energy. Is there a correlation between different forms of energy release? In this contribution, we perform detailed seismic and geothermal research in the Beijing area. The results show that the geothermal resources in Beijing belong to typical medium-low temperature geothermal resources of the sedimentary basin, and some areas are controlled by deep fault activities (e.g., Xiji geothermal well (No. 17)). The heat sources are upper mantle heat, radioactive heat in granite, and residual heat from magma cooling. The high overlap of earthquakes and geothermal field locations and the positive correlation between the injection water and earthquakes indicate that the exploitation and injection water will promote the release of the earth's energy. The energy releases are partitioned into multiple microearthquakes, avoiding damaging earthquakes (ML ≥ 5) due to excessive energy accumulation. Therefore, the exploitation of geothermal resources may be one way to reduce destructive earthquakes. Furthermore, the use of geothermal resources can also reduce the burning of fossil energy, which is of great significance in dealing with global warming. [ABSTRACT FROM AUTHOR]

Influenza A virus infection induces the production of excessive reactive oxygen species (ROS). Overproduction of ROS can overwhelm the antioxidant defense system, leading to increasing intensive oxidative stress. However, antioxidant defense against oxidative damage induced by influenza A virus infection, and in particular the significance of the SOD3 response in the pathogenesis of influenza virus infection, has not been well characterized. Here, we investigated the potential role of SOD3 in resistance to influenza A virus infection. In this study, SOD3, as an important antioxidant enzyme, was shown to be highly elevated in A549 cells following influenza A virus infection. Furthermore, inhibition of SOD3 impacted viral replication and virulence. We found that SOD3 disrupts IAV replication by impairing the synthesis of vRNA, whereas it did not affect viral ribonucleoprotein nuclear export. In addition, overexpression of SOD3 greatly reduced the levels of ROS caused by influenza A virus infection, regulated the inflammatory response to virus infection by inhibiting the phosphorylation of p65 of the NF-κB signaling pathway, and inhibited virus-induced apoptosis to a certain extent. Taken together, these findings indicate that SOD3 is actively involved in influenza A virus replication. Pharmacological modulation or targeting of SOD3 may pave the way for a novel therapeutic approach to combating influenza A virus infection. [ABSTRACT FROM AUTHOR]

Influenza virus infections and the continuing spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are global public health concerns. As there are limited therapeutic options available in clinical practice, the rapid development of safe, effective and globally available antiviral drugs is crucial. Drug repurposing is a therapeutic strategy used in treatments for newly emerging and re-emerging infectious diseases. It has recently been shown that the voltage-dependent Ca2+ channel Cav1.2 is critical for influenza A virus entry, providing a potential target for antiviral strategies. Nisoldipine, a selective Ca2+ channel inhibitor, is commonly used in the treatment of hypertension. Here, we assessed the antiviral potential of nisoldipine against the influenza A virus and explored the mechanism of action of this compound. We found that nisoldipine treatment could potently inhibit infection with multiple influenza A virus strains. Mechanistic studies further revealed that nisoldipine impaired the internalization of the influenza virus into host cells. Overall, our findings demonstrate that nisoldipine exerts antiviral effects against influenza A virus infection and could serve as a lead compound in the design and development of new antivirals. [ABSTRACT FROM AUTHOR]