Search Results (56)

Transmission towers are particularly vulnerable to extreme wind events, which can lead to structural damage or collapse, thereby compromising the stability of power transmission systems. Enhancing the wind-resistant capacity of these towers is therefore critical for improving the reliability and resilience of electrical infrastructure. This study utilizes finite element analysis (FEA) to evaluate the structural response of a 220 kV transmission tower subjected to fluctuating wind loads, effectively capturing the dynamic characteristics of wind-induced forces. A comprehensive dynamic analysis is conducted to account for uncertainties in wind loading and variations in wind direction. Through this approach, this study identifies the most critical wind angle and local structural weaknesses, as well as determines the threshold wind speed that precipitates structural collapse. To improve structural resilience, a concurrent multi-scale modeling strategy is adopted. This allows for localized analysis of vulnerable components while maintaining a holistic understanding of the tower’s global behavior. To mitigate failure risks, the traditional perforated plate reinforcement technique is implemented. The reinforcement’s effectiveness is evaluated based on its impact on load-bearing capacity, displacement control, and stress redistribution. Results reveal that the critical wind direction is 45°, with failure predominantly initiating from instability in the third section of the tower leg. Post-reinforcement analysis demonstrates a marked improvement in structural performance, evidenced by a significant reduction in top displacement and stress intensity in the critical leg section. Overall, these findings contribute to a deeper understanding of the wind-induced fragility of transmission towers and offer practical reinforcement strategies that can be applied to enhance their structural integrity under extreme wind conditions. Full article

The increasing number of natural and man-made disasters registered at the global level is causing a significant amount of damage. This represents one of the main sustainability challenges at the global level. The collapse of the Twin Towers, Hurricane Katrina, and the nuclear accident at the Fukushima power plant are some of the most representative disaster events that occurred at the beginning of the third millennium. These relevant disasters need an enhanced level of preparedness to reduce the gaps between the plan and its implementation. Among these actions, training and exercises play a relevant role because they increase the capability of planners, managers, and the people involved. By focusing on the exposure risk component, the general objective of the research is to obtain quantitative evaluations of the exercise’s contribution to risk reduction through evacuation. The paper aims to analyze serious games using a set of methods and models that simulate an urban risk reduction plan. In particular, the paper proposes a transparent framework that merges transport risk analysis (TRA) and transport system models (TSMs), developing serious game activities with the support of emerging information and communication technologies (e-ICT). Transparency is possible through the explicitation of reproducible analytical formulations and linked parameters. The core framework of serious games is constituted by a set of models that reproduce the effects of players’ choices, including planned actions of decisionmakers and travel users’ choices. The framework constitutes the prototype of a digital platform in a “non-stressful” context aimed at providing more insights about the effects of planned actions. The proposed framework is characterized by transparency, a feature that allows other analysts and planners to reproduce each risk scenario, by applying TRA and relative effects simulations in territorial contexts by means of TSMs and parameters updated by e-ICT. A basic experimentation is performed by using a game, presenting the main results of a prototype test based on a reproducible exercise. The prototype experiment demonstrates the efficacy of increasing preparedness levels and reducing exposure by designing and implementing a serious game. The paper’s methodology and results are useful for policymakers, emergency managers, and the community for increasing the preparedness level. Full article

This study investigates the stability of high-rise wind turbine tower foundations in collapsible loess regions through finite element analysis. The mechanisms by which wind load, extreme rainfall load, and seismic load interact during the dynamic response of a pile foundation under single-action and intercoupling conditions are analyzed. A comprehensive multi-parameter analytical model is developed to evaluate pile foundation stability, incorporating key indicators including pile skin friction, average axial stress of pile groups, horizontal displacement at pile tops, and pile inclination. The results show that, among single-load conditions, seismic loading has the most pronounced impact on foundation stability. The peak horizontal displacement at the pile top induced by seismic loads reaches 10.07 mm, substantially exceeding the effects of wind and rainfall loads, posing a direct threat to wind turbine tower safety. Under coupled loading conditions, notable nonlinear interaction effects emerge. Wind–earthquake coupled loading amplifies horizontal displacement by 1.85 times compared to single seismic loading. Rainfall–earthquake coupled loading reduces the peak of positive skin friction by 20.17%. Notably, all seismic-involved loading combinations significantly compromise the pile foundation safety margin. The seismic load is the dominant influencing factor in various loading conditions, and its coupling with other loads induces nonlinear superposition effects. These findings provide critical insights for wind turbine foundation design in collapsible loess areas and strongly support the need for enhanced seismic considerations in engineering practice. Full article

Transmission towers in coastal and industrial areas have experienced significant corrosion due to prolonged exposure to atmospheric pollutants and saline moisture, which poses a risk to structural safety. To evaluate the impact of corrosion depth on wind-induced collapse performance of an angle steel transmission tower, a survey of 18 angle steel towers in Ningbo, China, was conducted. Finite element models (FEMs) incorporating observed corrosion patterns were developed to analyze natural vibration characteristics and progressive collapse. The collapse modes of both corroded and uncorroded towers were identified, and high-risk failure member was determined. The results indicate that the corrosion depth below the lower cross-arm can be considered representative of the overall corrosion condition of the tower. Torsional natural frequency of the angle steel tower is particularly sensitive to corrosion due to the critical role of diagonal members. Collapse analysis further reveals that moderate corrosion levels can reduce the tower’s wind resistance to below the design threshold, potentially compromising safety under extreme weather conditions. The diagonal member below the lower cross-arm is identified as a high-risk failure component. Strengthening this member, by up-grading from L75×6 to L90×6, can significantly enhance the tower’s tolerance to corrosion. Full article

The excessive vibration or collapse of a transmission tower-line (TTL) system under seismic excitation can result in significant losses. Viscoelastic material dampers (VMDs) have been recognized as an effective method for structural vibration mitigation. Most existing studies have focused solely on the dynamic analysis of TTL systems with control devices under deterministic seismic excitations. Studies focusing on the nonstationary stochastic control of TTL systems with VMDs have not been reported. To this end, this study proposes a comprehensive analytical framework for the nonstationary stochastic responses of TTL systems with VMDs under stochastic seismic excitations. The analytical model of the TTL system is formulated using the Lagrange equation. The six-parameter model of VMDs and the vibration control method are established. Following this, the pseudo-excitation method (PEM) is applied to compute the stochastic response of the controlled TTL system under nonstationary seismic excitations, and a probabilistic framework for analyzing extreme value responses is developed. A real TTL system in China is selected to verify the validity of the proposed method. The accuracy of the proposed framework is validated based on the Monte Carlo method (MCM). A detailed parametric investigation is conducted to determine the optimal damper installation scheme and examine the effects of the service temperature and site type on stochastic seismic responses. VMDs can effectively suppress the structural dynamic responses, with particularly stable control over displacement. The temperature and site type have a notable influence on the stochastic seismic responses of the TTL system. The research findings provide important references for improving the seismic performance of VMDs in TTL systems. Full article

The growing significance of wind energy in supplying renewable electricity underlines the increasing importance of wind turbine efficiency. Hybrid towers, integrating steel and pre-stressed concrete in a stacked structure, address traditional limitations in nacelle height but face new vulnerabilities, exemplified by a collapse in September 2021. This highlights the crucial need for continuous monitoring, particularly of the tower structure’s tendons. This study introduces acoustic emission monitoring as a novel approach for the early detection of wire breaks within the highly stressed tendons of hybrid towers. The investigations described focus on evaluating the suitability of this method for the specific use case and developing a generalized monitoring approach. Accordingly, background noise in an operating wind turbine tower was recorded and analyzed over a year-long operational period. Correlation analyses of these data unveiled intricate relationships between operational parameters and noise levels, with wind speed, rotor speed, and blade pitch angle exerting influence. Laboratory experiments were conducted on a full-scale specimen, and wire breaks were artificially provoked to characterize the damage signal and assess its attenuation in relevant structural components. The experimental results were integrated into a stochastic model to determine feasible sensor distances, aiming for a 90% probability of detection at a 95% confidence level. Low attenuation along the tendon was identified, enabling reliable detection over significant distances. Nevertheless, practical considerations suggest a focus on tendon anchorages, with the potential for grouped monitoring in specific areas to optimize sensor deployment. The study proposes a sensor network configuration to enhance the safety and reliability of wind turbine structures. Full article

Transmission lines are usually located outdoors and are subjected to wind loads year-round. When a fire occurs, transmission towers are exposed to the combined effects of fire and wind loads. This paper investigates the impact of high temperatures on the bearing capacity of transmission tower-line systems under wind load and explores the effects of uneven horizontal spacing distribution and changes in the elevation of the target tower on the bearing capacity of the tower-line system. The failure criteria for transmission tower components at high temperatures were determined by considering the constitutive relationship of steel at ambient temperature and the variation patterns in material strength and elastic modulus with temperature. A finite element model of the transmission tower-line system was established using ABAQUS (2023). This paper studied the effects of temperature, uneven horizontal spacing distribution, and changes in the elevation of the target tower on the response of the transmission tower-line system by comparing collapse-resisting wind speeds and collapse processes under various conditions. The research indicates that the load-bearing capacity of the transmission tower-line system decreases as temperature increases. When the temperature exceeds 400 °C, the collapse-resisting wind speed of the transmission tower drops sharply. At temperatures above 600 °C, the transmission tower may collapse even at the annual average wind speed. In addition, the uneven horizontal spacing distribution and changes in the elevation of the target tower have an adverse effect on the stability of the transmission tower-line system. It is recommended to choose steel materials with higher fire resistance or apply fire-resistant coatings to existing steel, and to avoid extremely uneven spacing distributions and excessively high target tower elevations. Full article

Natural calamities have historically impacted operational mountainous power transmission towers, including high winds and ice accumulation, which can result in pole damage or diminished load-bearing capability, compromising their structural integrity. Consequently, developing a safety state prediction model for transmission towers may efficiently monitor and evaluate potential risks, providing early warnings of structural dangers and diminishing the likelihood of bending or collapse incidents. This paper presents a safety state prediction model for transmission towers utilizing improved coati optimization-based SVM (ICOA-SVM). Initially, we optimize the coati optimization algorithm (COA) through inverse refraction learning and Levy flight strategy. Subsequently, we employ the improved coati optimization algorithm (ICOA) to refine the penalty parameters and kernel function of the support vector machine (SVM), thereby developing the safety state prediction model for the transmission tower. A finite element model is created to simulate the dynamic reaction of the transmission tower under varying wind angles and loads; ultimately, wind speed, wind angle, and ice cover thickness are utilized as inputs to the model, with the safe condition of the transmission tower being the output. The predictive outcomes indicate that the proposed ICOA-SVM model exhibits rapid convergence and high prediction accuracy, with a 62.5% reduction in root mean square error, a 59.6% decrease in average relative error, and a 75.0% decline in average absolute error compared to the conventional support vector machine. This work establishes a scientific foundation for the safety monitoring and maintenance of transmission towers, effectively identifying possible dangers and substantially decreasing the likelihood of accidents. Full article

The probability of accidents, including conductor breakage and tower collapse, for the transmission tower-line system significantly increases under combined ice and wind loads. The existing research on the failure probability of the tower-line system under combined ice and wind loads is limited to static calculation, ignoring the fluctuating effect of wind. In addition, uncertainty in the material strength and geometric dimensions of the structure due to the production process and other pertinent factors could affect the bearing capacity of the tower. To accurately assess the failure probability of transmission lines under combined ice and wind loads, this paper first established numerical models of the transmission tower-line system considering structural uncertainty based on the Latin Hypercube Sampling method. And then, the limit performance indexes of the uncertain models were determined by Pushover analysis. Subsequently, considering the joint probability distributions of ice thickness–wind speed and wind speed–wind direction, the failure probability of the tower-line system under ice and wind loads was calculated. Finally, the influence of structural uncertainty and fluctuating wind on the failure probability was discussed. The results showed that, compared with structural uncertainty, the fluctuating effect of wind had a more significant influence on the failure probability of the tower-line system under combined ice and wind loads. After considering the fluctuating effect of wind, the smaller ice loads can potentially lead to the failure of the transmission tower-line system. Full article

The seismic assessment of historical masonry bell towers is of significant interest, particularly in Italy, due to their widespread presence and inherent vulnerability given by their slenderness. According to technical codes and standard practice, the seismic evaluation of masonry bell towers can be conducted using a range of methodologies that vary in their level of detail. This paper presents a case study of a historical masonry bell tower located in the Caserta Province (Italy). Extensive investigative efforts were undertaken to determine the tower’s key geometric and structural characteristics, as well as to document ongoing damage phenomena. The dynamic behavior of the tower was assessed through ambient vibration testing, which enabled the identification of the principal modal shapes and corresponding frequencies, also highlighting peculiar dynamical characteristics caused by the damage conditions. Subsequently, the seismic assessment was carried out using both Level 1 (simplified mechanical) and Level 2 (kinematic limit analysis) methodologies. This assessment helped identify the most probable collapse mechanisms and laid the foundation for employing more advanced methodologies to design necessary retrofitting interventions. The study emphasizes the importance of Level 2 analyses for structures where out-of-plane failure mechanisms are likely due to pre-existing cracking. Both approaches provide less-than-unity acceleration factors, ranging from 0.45 for Level 1 (assuming non-ductile behavior) to 0.59 for Level 2, in this case specifically using the information available about existing cracking pattern. Full article

Although the wind load is usually adopted as the governing lateral load in the design of transmission towers, many tall transmission towers may be damaged or even collapse in high seismic intensity areas, especially under near-fault pulse-like ground motions. To study the seismic vibration control effect of a tuned mass damper (TMD) attached to transmission tower, parametric analyses are conducted in SAP2000 through CSI OAPI programming, including TMD parameters such as the mass ratio μ from 0.5% to 10%, the frequency ratio f from 0.7 to 1.2, and the damping ratio ξ from 0.01 to 0.2. Based on the obtained analysis results, artificial neural network (ANN) is trained to predict the vibration reduction ratios of peak responses and the corresponding vibration reduction cost. Finally, the NSGA-III algorithm is adopted to perform the multi-objective optimization of a transmission tower equipped with TMD. Results show that the vibration reduction ratios first increase and then decrease with the increase of frequency ratio, but first increase and then remain stable with the increase of mass ratio and damping ratio. In addition, ANN fitting can accurately predict the nonlinear relationship between TMD parameters and objective functions. Through multi-objective optimization with the NSGA-III algorithm, TMD can simultaneously and significantly reduce different peak responses of transmission towers under near-fault pulse-like ground motions in a cost-effective manner. Full article

Power transmission line icing (PTLI) poses significant threats to the reliability and safety of electrical power systems, particularly in cold regions. Accumulation of ice on power lines can lead to severe consequences, such as line breaks, tower collapses, and widespread power outages, resulting in economic losses and infrastructure damage. This study proposes an enhanced image processing pipeline to accurately detect and match key points in PTLI images for 3D monitoring of ice thickness using binocular vision. The pipeline integrates established techniques such as multiscale retinex (MSR), oriented FAST and rotated BRIEF (ORB) and scale-invariant feature transform (SIFT) algorithms, further refined with m-estimator sample consensus (MAGSAC)-based random sampling consensus (RANSAC) optimization. The image processing steps include automatic cropping, image enhancement, feature detection, and robust key point matching, all designed to operate in challenging environments with poor lighting and noise. Experiments demonstrate that the proposed method significantly improves key point matching accuracy and computational efficiency, reducing processing time to make it suitable for real-time applications. The effectiveness of the pipeline is validated through 3D ice thickness measurements, with results showing high precision and low error rates, making it a valuable tool for monitoring power transmission lines in harsh conditions. Full article

The prevailing approach to the wind resistance design of transmission towers is rooted in the quasi-static method. However, this methodology faces criticism for neglecting tower-line coupling dynamics. Despite efforts to boost structural wind resilience, the research on tower failure mechanisms, especially under extreme winds considering tower-line coupling, is limited. To address this gap, the wind-induced dynamic failure modes of the transmission tower-line system are investigated in this paper. The consistent discrete random flow generation method is employed to simulate the fluctuating wind field for transmission lines. Incorporating the compressive buckling mode of angle steel, the plastic hinge model of the frame element is employed to simulate mechanical nonlinearity. A typical transmission tower-line system is concerned, with a finite element model established for a three-tower, four-line coupled configuration. The findings reveal that the wind-induced collapse of the transmission tower is directly triggered by the buckling failure of the compressed main members, with the vulnerable section located beneath the lower cross-arm. The transmission tower experiences bidirectional bending and compression instability under an unfavorable wind direction. In contrast, the traditional pushover collapse modes of the transmission tower cannot fully capture the characteristics of the collapse failure, mainly due to the ignorance of the transverse wind force action induced by the coupling effect. This research underscores the importance of incorporating lateral dynamic considerations into transmission tower designs and advocates for optimizing strategies to mitigate wind-induced collapse modes. Full article

Icing on transmission lines may cause damage to tower components and even lead to structural failure. Aiming at the lack of research on predicting mechanical characteristic parameters of weak components of transmission towers, and the cumbersome steps of building a finite element model (FEM), the study of prediction for mechanical characteristic parameters of weak components of towers based on a finite element simulation and machine learning is proposed. Firstly, a 110 kV transmission tower in a heavily iced area is taken as an example to establish its FEM. The locations of the weak components are analyzed, and the accuracy of FEM is verified. Secondly, meteorological and terrain parameters are considered as input parameters of the prediction model. The axial stresses and nodal displacements of four weak components are selected as output parameters. The FEM of the 110 kV transmission tower is used to obtain input and output datasets. Thirdly, five machine learning algorithms are considered to establish the prediction models for mechanical characteristic parameters of weak components, and the optimal prediction model is obtained. Finally, the accuracy of the prediction method is verified through an actual tower collapse case. The results show that ACO-BPNN is the optimal model that can accurately and quickly predict the mechanical characteristic parameters of the weak components of the transmission tower. This study can provide an early warning for the failure prediction of transmission towers in heavily iced areas, thus providing an important reference for their safe operation and maintenance. Full article

This paper delves into the impact of the damage accumulation effect, which leads to the degradation of material strength and stiffness, on the seismic resistance of transmission towers. Building upon the elastic–plastic finite element theory, a mixed hardening constitutive model is derived for circular steel tubes, standard elements in transmission towers, incorporating the damage accumulation effect. A user material subroutine, UMAT, is created within the LS–DYNA framework. The program’s validity and reliability are established through axial constant–amplitude loading tests on single steel tubes. The subroutine is employed to conduct the incremental dynamic analysis (IDA) of an individual transmission tower and to contrast it with the structure utilizing the Plastic Kinematic material model, assessing the discrepancies in tower top displacements and segment damage indices (SDIs) at both macroscopic and microscopic scales. The results shows that the Plastic Kinematic model inflates the seismic performance of the transmission tower. When considering the damage accumulation effect in structural failure, the damage index of the members increases, leading to a reduction in both the structural strength and stiffness. The dynamic response in the plastic phase becomes more pronounced, and the onset of structural failure is accelerated. Consequently, structural analysis under seismic conditions should account for the damage accumulation process. Through the delineation of member and segment damage, the extent of damage to transmission tower segments can be quantitatively assessed. Subsequently, the ultimate load–bearing capacity and the most vulnerable location of the transmission tower can be ascertained. Finally, this paper provides a detailed analysis of the transmission tower collapse process under seismic action and summarizes the mechanism of collapse for the structure. Full article