A Finite Element Modeling Method for Transmission Towers Considering Nodal Slip Effect

Abstract

This invention provides a finite element modeling method for transmission towers considering nodal slip effects, belonging to the field of transmission tower simulation technology. The method first generates experimental verification data of bolted nodes of the transmission tower, then constructs a database of bolted node skeleton curves; next, it constructs a finite element model of the transmission tower's spatial rigid frame, and establishes joint stiffness elements considering bolt slip at each rigid node; finally, based on the constructed skeleton curve database, it assigns mechanical behavior parameters to the joint stiffness elements under dynamic loads, completing the establishment of the finite element model of the transmission tower considering nodal slip effects. This method, based on existing finite element models of transmission towers, considers the slip characteristics of nodes under dynamic loads, reducing time, financial, human, and material costs, and yields reliable results.

Description

Technical Field

[0001] This invention relates to the field of transmission tower simulation technology, and in particular to a finite element modeling method for transmission towers that considers node slippage effects. Background Technology

[0002] Transmission tower-line systems, as the physical carriers of electrical energy transmission, are an indispensable intermediate link in the process from power generation to power consumption, and their safe operation has a significant impact on the stable development of society. With the development of computer technology, numerical simulation technology has become increasingly mature and reliable, gradually becoming the third research method besides theory and experiment. Currently, commonly used numerical models for transmission towers include spatial truss models, spatial rigid frame models, and beam-truss hybrid models. The spatial truss model uses rod elements to model and analyze the transmission tower, simplifying all nodes to ideal hinge nodes, and all members only bear axial forces, ignoring bending moments and shear forces. The spatial rigid frame model uses beam elements to simulate the transmission tower entirely, assuming all nodes to be ideal rigid nodes; in this case, the members can withstand the combined effects of axial forces, bending moments, and shear forces. The beam-truss hybrid model uses both beam and rod elements to model the transmission tower; generally, areas with higher stiffness, such as main members and crossbars, are simplified to beam elements, while weaker connections, such as diagonal members, are simplified to rod elements. However, in reality, the bolted connections on transmission towers are semi-rigid, neither hinged nor rigid, and the finite element models described above neglect the influence of node slippage. Existing research has shown that connection slippage at nodes can affect the deformation behavior and failure mode of the transmission tower structure. Therefore, it is necessary to consider bolted connection slippage when performing detailed stress analysis on transmission towers.

[0003] Transmission towers are subjected to loads such as strong winds and earthquakes during their service life, which can cause vibrations that threaten their normal operation and, in severe cases, even lead to collapse. Studies have shown that the failure modes, ultimate bearing capacities, and ultimate bearing deformation capacities of steel structure nodes differ under monotonic and cyclic loading. During vibration, the nodes of a transmission tower are subjected to cyclic loads, and their stress state (magnitude and direction) changes. Mechanical models obtained based on static loading cannot accurately reflect the mechanical characteristics of the nodes during dynamic processes. Therefore, accurately obtaining the hysteretic characteristics of transmission tower nodes under dynamic loads and establishing finite element models of transmission towers that consider node slippage have become a hot topic in the field of transmission tower simulation. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to address the shortcomings of the prior art by providing a finite element modeling method for transmission towers that considers node slippage effects. Based on the existing finite element model of transmission towers, the slippage characteristics of nodes under dynamic loads are considered.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a finite element modeling method for transmission towers considering node slippage effects, comprising the following steps:

[0006] Generate test verification data for bolt joints of transmission towers;

[0007] Construct a database of bolt node skeleton curves;

[0008] A finite element model of the spatial rigid frame of the transmission tower is constructed, and a joint stiffness element considering bolt slippage is established at each rigid node;

[0009] Based on the constructed skeleton curve database, mechanical behavior parameters of the combined stiffness element under dynamic load are assigned, and the finite element model of the transmission tower considering the nodal slip effect is established.

[0010] Preferably, the specific method for generating the bolt node test verification data of the transmission tower is as follows:

[0011] According to the design drawings, the geometric parameter information of typical bolt nodes of transmission towers of different tower types was collected and statistically analyzed. Some nodes were selected to make node specimens, and quasi-static tests were carried out on the bolt node specimens to extract the hysteresis curves and skeleton curves of the bolt nodes. The typical bolt node geometric parameter information includes the number of bolts, bolt grade, bolt diameter and bolt hole diameter.

[0012] Preferably, the quasi-static test on the bolt joint specimen is a low-cycle cyclic load test, and the loading regime adopts a load-displacement dual-control loading regime.

[0013] Preferably, the specific method for constructing the bolt node skeleton curve database is as follows:

[0014] First, a refined three-dimensional finite element model of a typical bolt node is established using finite element software, and the load-displacement hysteresis curve of the bolt node and the corresponding skeleton curve are extracted.

[0015] Then, the BP neural network is trained using bolt node geometric parameter information and skeleton curve data, where bolt node geometric parameter information is used as input layer variable of BP neural network and skeleton curve data is used as output layer variable.

[0016] Finally, the trained BP neural network is used to predict the skeleton curves of different types of bolt nodes under dynamic loads, thus forming a bolt node skeleton curve database.

[0017] Preferably, the refined three-dimensional finite element model of the typical bolt node is established using solid elements in finite element software; and the load-displacement hysteresis curve extracted from the three-dimensional finite element model of the bolt node is compared with the test results of the quasi-static test of the bolt node specimen to verify the accuracy of the refined three-dimensional finite element model of the bolt node.

[0018] Preferably, the finite element model of the transmission tower spatial rigid frame is established using beam elements, and the combined stiffness element considering bolt slippage is established using beam elements and nonlinear spring elements;

[0019] The method for establishing a combined stiffness element that considers bolt slippage is to find each rigid node in the finite element model of the spatial rigid frame of the transmission tower, create a new node with geometrically coincident position at each rigid node, and insert a zero-length nonlinear spring element between the original node and the new node.

[0020] Preferably, the mechanical behavior parameters of the combined stiffness unit under dynamic load are obtained through the constructed node skeleton curve database. Specifically, the geometric parameter information of each bolt node is extracted according to the modeled transmission tower drawings, and then the corresponding bolt node skeleton curve is generated in the constructed skeleton curve database.

[0021] The beneficial effects of adopting the above technical solution are as follows: The finite element modeling method for transmission towers that considers the node slip effect provided by the present invention is suitable for dynamic analysis, takes into account the node slip characteristics, reduces the time, financial, human and material costs, and the results are reliable;

[0022] (1) Compared with the traditional finite element modeling method for transmission towers, the method of the present invention considers the reciprocating sliding characteristics of nodes under dynamic loads, which greatly increases the accuracy of the vibration response analysis results of transmission towers.

[0023] (2) Applicable to dynamic analysis of transmission towers under various load conditions, such as earthquakes, strong winds, and icing;

[0024] (3) Applicable to various types of transmission towers, the mechanical behavior of their bolted nodes under dynamic loads can be obtained through the node skeleton curve database.

[0025] (4) The BP neural network is used to predict the skeleton curve of the bolt node under dynamic action. Only a few experiments are required. Compared with the traditional model test method, the time, financial resources, human resources and material resources are reduced. Moreover, the prediction results are verified by experimental comparison to ensure the accuracy of the results. Attached Figure Description

[0026] Figure 1 A flowchart illustrating a finite element modeling method for transmission towers considering node slippage effects, provided in an embodiment of the present invention;

[0027] Figure 2 A schematic diagram of a typical bolt joint quasi-static test device provided in an embodiment of the present invention;

[0028] Figure 3 A detailed three-dimensional finite element model of a typical bolt node provided in an embodiment of the present invention;

[0029] Figure 4 The numerical results and experimental results verification diagram provided in the embodiments of the present invention;

[0030] Figure 5 A schematic diagram of the basic architecture of a BP neural network provided in an embodiment of the present invention;

[0031] Figure 6 This is a comparison and verification diagram between the prediction results of the BP neural network and the experimental results provided in the embodiments of the present invention;

[0032] Figure 7 This is a finite element model of a transmission tower spatial rigid frame provided in an embodiment of the present invention;

[0033] Figure 8 The diagram below shows the creation of a combined stiffness element considering bolt slippage effect, provided for an embodiment of the present invention. In this diagram, (a) is a main material-main material connection node, and (b) is a main material-diagonal material connection node.

[0034] Among them, 1. Nodes at the connection of beam element BEAM189; 2. Nonlinear spring element; 3. New nodes with coincident geometric positions. Detailed Implementation

[0035] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0036] In this embodiment, a finite element modeling method for transmission towers considering node slippage effects is described, such as... Figure 1 As shown, it includes the following steps:

[0037] Step 1: Generate test verification data for bolted joints of the transmission tower;

[0038] According to the design drawings, the geometric parameter information of typical bolt nodes of transmission towers of different tower types was collected and statistically analyzed. Some nodes were selected to make node specimens, and quasi-static tests were carried out on the bolt node specimens to extract the hysteresis curves and skeleton curves of the bolt nodes. The typical bolt node geometric parameter information includes the number of bolts, bolt grade, bolt diameter and bolt hole diameter.

[0039] Among them, the quasi-static test, namely the low-cycle cyclic load test, was conducted on the bolt joint specimens, and the loading regime adopted a load-displacement dual-control loading regime.

[0040] This embodiment collects geometric parameter information of typical bolted nodes based on the design drawings of the transmission tower, including the number of bolts, bolt grade, bolt diameter, and bolt hole diameter. For example, the bolted node parameters are 1 bolt of grade 4.8 M16 bolt with a bolt hole diameter of 17.5mm.

[0041] Adopting such Figure 2 The 500kNMTS servo hydraulic testing machine shown is used as the testing device to fabricate the node specimen and conduct a quasi-static test on it, namely a low-cycle reciprocating load test, with a load-displacement dual-control loading regime.

[0042] Step 2: Construct a database of bolt node skeleton curves;

[0043] First, a refined three-dimensional finite element model of a typical bolt node is established using finite element software. The load-displacement hysteresis curve of the bolt node and the corresponding skeleton curve are extracted. Then, the geometric parameter information of the bolt node and the skeleton curve data are used to train the BP neural network. The geometric parameter information of the bolt node is used as the input layer variable of the BP neural network, and the skeleton curve data is used as the output layer variable.

[0044] Finally, the trained BP neural network is used to predict the skeleton curves of different types of bolt nodes under dynamic loads, forming a bolt node skeleton curve database.

[0045] The refined three-dimensional finite element model of a typical bolt node was established using solid elements in finite element software. The accuracy of the refined three-dimensional finite element model of the bolt node was verified by comparing the load-displacement hysteresis curve extracted from the three-dimensional finite element model of the bolt node with the test results of the quasi-static test of the bolt node specimen.

[0046] Meanwhile, the accuracy of the prediction results of the trained BP neural network was also verified by the experimental data of the quasi-static test conducted on the bolt node specimen.

[0047] In this embodiment, the refined three-dimensional finite element model of a typical bolt node is established as follows: Figure 3 As shown, the finite element method used was the large-scale commercial software ANSYS, with SOLID185 for three-dimensional solid elements, CONTA173 and TARGE170 for contact elements, and PRETS179 for bolt preload elements. The nodal load-displacement hysteresis curves extracted from the finite element model were compared with the experimental results of quasi-static tests on bolted joint specimens. The results are as follows: Figure 4 As shown.

[0048] The BP neural network is then trained using the number of bolts, bolt grade, bolt diameter, and bolt hole diameter as input layer variables, and the skeleton curve data as output layer variables. In this embodiment, the skeleton curve data is obtained through a refined three-dimensional finite element model, with 30,000 training iterations and an error of 0.001. The algorithm also performs data normalization and denormalization. The basic architecture of the BP neural network is as follows: Figure 5 As shown.

[0049] Finally, a BP neural network was used to quickly predict the skeleton curves of typical bolt nodes of transmission towers of different tower types, and a database of skeleton curves of nodes under dynamic loads was constructed.

[0050] Simultaneously, the skeleton curve predicted by the trained BP neural network was compared with the experimental results of the quasi-static test on the bolt node specimen. This demonstrates that the BP neural network can effectively predict the skeleton curve of the node under dynamic load. In this embodiment, the node parameters are three 4.8 grade M12 bolts with a bolt hole diameter of 16.5 mm. The comparison between the BP neural network prediction results and the experimental results verifies the results. Figure 6 As shown.

[0051] Step 3: Construct a finite element model of the transmission tower's spatial rigid frame, and establish a combined stiffness element considering bolt slippage at each rigid node (without considering slippage effect). Based on the constructed skeleton curve database, assign mechanical behavior parameters to the combined stiffness element under dynamic loads to complete the establishment of the finite element model of the transmission tower considering node slippage effect.

[0052] The spatial rigid frame finite element model of the transmission tower is established using beam elements, and the combined stiffness element considering bolt slippage is established using beam elements and nonlinear spring elements.

[0053] One method for establishing a joint stiffness element that considers bolt slippage is to find each rigid node of the finite element model of the transmission tower spatial rigid frame, create a new node with geometrically coincident position at each rigid node, and insert a zero-length nonlinear spring element between the original node and the new node.

[0054] The mechanical behavior parameters of the combined stiffness element under dynamic load are obtained through the constructed node skeleton curve database. The specific method is as follows: based on the modeled transmission tower drawings, the geometric parameter information of each bolt node is extracted, and then the corresponding bolt node skeleton curve is generated in the constructed skeleton curve database.

[0055] In this embodiment, the large-scale commercial software ANSYS is used. Through steps such as establishing material properties, defining element physical characteristics, and generating finite element meshes, a finite element model of the transmission tower spatial frame is created using the beam element BEAM189. The spatial frame model of the transmission tower in this embodiment is as follows: Figure 7 As shown.

[0056] The creation of a combined stiffness element considering bolt slippage effect is as follows: Figure 8 As shown, based on the finite element model of the transmission tower spatial frame, the self-developed ANSYS APDL program is used to find node 1 at the connection of beam element BEAM189. A new node 3 with geometrically coincident position is created at node 1. Then, a nonlinear spring element 2 is introduced to simulate the slippage behavior of bolts under dynamic loads. Combined stiffness elements considering bolt slippage are created at all nodes of the transmission tower spatial frame model. In this embodiment, the nonlinear spring element COMBIN39 is used.

[0057] In this example, the parameter information of each bolt node is extracted based on the modeled transmission tower drawings; then, the node skeleton curves corresponding to the node parameters are obtained by querying the node skeleton curve database; finally, the mechanical behavior parameters of the combined stiffness element under dynamic load are assigned by real constants, thus completing the establishment of the finite element model of the transmission tower considering the node slip effect.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the claims of the present invention.

Claims

1. A finite element modeling method for transmission towers considering nodal slip effects, characterized in that: Includes the following steps: According to the design drawings, the geometric parameter information of typical bolt nodes of transmission towers of different tower types was collected and statistically analyzed. Some nodes were selected to make node specimens. Quasi-static tests were carried out on the bolt node specimens, and the hysteresis curves and skeleton curves of the bolt nodes were extracted. The geometric parameter information of the typical bolt nodes includes the number of bolts, bolt grade, bolt diameter and bolt hole diameter, and the bolt node test verification data of the transmission tower is generated. Based on finite element simulation and BP neural network, a database of bolt node skeleton curves is constructed. First, a refined three-dimensional finite element model of a typical bolt node is established using finite element software, and the load-displacement hysteresis curves of the bolt node and the corresponding skeleton curves are extracted. Then, the BP neural network is trained using the bolt node geometric parameters and skeleton curve data, with the bolt node geometric parameters as the input layer variables and the skeleton curve data as the output layer variables. Finally, the trained BP neural network is used to predict the skeleton curves of different types of bolt nodes under dynamic loads, thus forming a bolt node skeleton curve database. A finite element model of the spatial rigid frame of the transmission tower is constructed, and a joint stiffness element considering bolt slippage is established at each rigid node; Based on the constructed skeleton curve database, mechanical behavior parameters of the combined stiffness element under dynamic load are assigned, and the finite element model of the transmission tower considering the nodal slip effect is established.

2. The finite element modeling method for transmission towers considering node slippage effect according to claim 1, characterized in that: The quasi-static test on the bolt joint specimen is a low-cycle cyclic load test, and the loading regime adopts a load-displacement dual-control loading regime.

3. The finite element modeling method for transmission towers considering node slippage effect according to claim 2, characterized in that: The refined three-dimensional finite element model of the typical bolt node was established using solid elements in finite element software. The load-displacement hysteresis curve extracted from the three-dimensional finite element model of the bolt node was compared with the test results of the quasi-static test of the bolt node specimen to verify the accuracy of the refined three-dimensional finite element model of the bolt node.

4. The finite element modeling method for transmission towers considering node slippage effect according to claim 1, characterized in that: The finite element model of the spatial rigid frame of the transmission tower is established using beam elements, and the combined stiffness element considering bolt slippage is established using beam elements and nonlinear spring elements. The method for establishing a combined stiffness element that considers bolt slippage is to find each rigid node in the finite element model of the spatial rigid frame of the transmission tower, create a new node with geometrically coincident position at each rigid node, and insert a zero-length nonlinear spring element between the original node and the new node.

5. The finite element modeling method for transmission towers considering node slippage effect according to claim 4, characterized in that: The mechanical behavior parameters of the combined stiffness element under dynamic load are obtained through the constructed node skeleton curve database. Specifically, the geometric parameter information of each bolt node is extracted based on the modeled transmission tower drawings, and then the corresponding bolt node skeleton curve is generated in the constructed skeleton curve database.

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