tower model
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2022 ◽  
Vol 2148 (1) ◽  
pp. 012046
Author(s):  
Xiancai Ren ◽  
Zhaobo Meng ◽  
Xin Wang ◽  
Feifei Gao ◽  
Ting Zhang

Abstract In order to study the seismic performance of ancient wooden structures with single eaves and beam lifting in China, the finite element model of the upper floor of the south gate of Jiangzhang town in Shanxi Province was established by using ANSYS. Through modal analysis, the main frequencies and modes of the south gate of Jiangduan were obtained. Through the seismic response analysis of the south gate tower model, the displacement and acceleration response curves of the top nodes of the outer eaves column, golden column and through column under various working conditions of the South gate tower are obtained. The results show that the first and second order frequencies of the South Gate tower model are 1.830Hz and 1.855Hz, and the first two order modes are mainly transitional. With the increase of seismic excitation, the displacement and acceleration response of the top joints of the outer eave column, golden column and through column increase.


Author(s):  
Vahid Saberi Nasrabad ◽  
Ali Hajnayeb ◽  
Qiao Sun

The deflection of the wind turbine tower can provide us with rich information about the effective wind speed. In this paper, a new method for effective wind speed estimation is proposed based on tower deflection. The tower vibration model is derived and a subspace identification method is used to identify the model parameters. An online estimator of aerodynamic thrust force based on the identified tower model is designed and then implemented using a Kalman filter together with a recursive least squares algorithm. The estimated aerodynamic thrust force is then used as an input to a neural network estimator, which is trained to invert the aerodynamic thrust force equation and estimate the effective wind speed. In order to show the performance of the proposed estimator, the estimated thrust force and wind speed are compared and verified with a third-party simulation data of a 1.5 MW wind turbine. The comparison shows close agreement between their values.


Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 695
Author(s):  
Björn Nienborg ◽  
Marc Mathieu ◽  
Alexander Schwärzler ◽  
Katharina Conzelmann ◽  
Lena Schnabel

Fouling is a permanent problem in process technology and is estimated to cost 0.25% of the gross national product. Evaporative cooling systems are especially susceptible to air-side fouling: as they work with untreated outside air, they are exposed to both natural (e.g., pollen) and human-made (e.g., industrial dust) contaminants. In addition, suspended solid particles and dissolved salts in the spray water are an issue. In this study we analyzed an approach for fouling detection based on a semi-physical (grey-box) cooling tower model which we calibrated with measurement data. A test series with reliable laboratory data indicates good applicability of the model. In three datasets, the performance decreases due to fouling (scaling, which was provoked intentionally) in the range of 5–11% were clearly detected. When applied to measurement data of two cooling towers in real applications, the model also proved to be well calibratable with relatively little data (two to four operating days). For two data sets, the model yielded reasonable results when applied to long term data: a cooling tower cleaning could be retraced and nominal operation was verified during the remaining time. During the analysis of a third data set a temporary performance deviation was found, which could not be explained with the recorded data. Thus, the approach turned out to be generally applicable but requires further verification and refinement in order to increase the robustness. If successful, it can be transferred to a commercial product for need-oriented maintenance in order to reduce cooling tower operating costs and environmental impact.


2021 ◽  
Author(s):  
Suhrid Deshmukh ◽  
Leon R. Glicksman ◽  
Leslie Norford
Keyword(s):  

Author(s):  
Z. Wu ◽  
H. Wang ◽  
W. Yu ◽  
J. Xi ◽  
W. Lei ◽  
...  

Abstract. Constructing the transmission tower from LiDAR point clouds is a fundamental step for smart grid. However, currently the transmission tower construction method relies heavily on manual editing, which is far from the practical industrial application. This paper proposes a model-driven based method to realize 3D construction of transmission tower fast and accurately. This method first generates different types of 3D tower models. Then, it calculates the direction characteristic of point clouds distribution using the obtained transmission towers point clouds. While finding the principal direction of transmission towers, the local coordinates of the transmission towers are settled. And then the key points are captured in a semi-automatically way. According to these key points, the transmission tower model that best matches the point clouds is selected using the model matching algorithm. Comparing with the existing traditional manual editing methods, the method proposed in this paper can ensure the integrity and accuracy of the reconstructed tower model using the model-driven based strategy. The proposed method makes a trade-off between manual editing and efficiency, which guarantees the quality of tower modelling. And the feasibility and practicability of the proposed method are verified by the experiments on real-world point clouds data.


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