CN-121980875-A - Multi-scale test evaluation method for pavement performance of steel bridge deck

CN121980875ACN 121980875 ACN121980875 ACN 121980875ACN-121980875-A

Abstract

The application provides a multi-scale test evaluation method for steel bridge deck pavement performance, which comprises the steps of obtaining test data of steel bridge deck pavement, extracting a multi-scale performance parameter set from the test data, establishing a scale conversion function for mapping local performance parameters to an overall structure state based on the multi-scale performance parameter set, constructing an initial digital model based on the scale conversion function and the multi-scale performance parameter set, carrying out parameter reverse calibration on the initial digital model by combining actual measurement response data in full-scale segment scale data to obtain the multi-scale performance digital model, and carrying out simulation on service environment data of an obtained target pavement structure based on the multi-scale performance digital model to obtain performance evaluation data of the target pavement structure, wherein the performance evaluation data comprises a predicted performance degradation value and a predicted residual service life. By adopting the method, more reliable technical support can be provided for the performance management and control of the steel bridge deck pavement.

Inventors

NING JIKANG
ZHANG ZHIXIANG
YANG YANG
ZHANG HUI
YIN YUAN
Cheng Shufan
CUI LEI
LIN KANG
ZHOU FAN

Assignees

湖北省路桥集团有限公司

Dates

Publication Date: 20260505
Application Date: 20260203

Claims (9)

1. The multi-scale test evaluation method for the pavement performance of the steel bridge deck is characterized by comprising the following steps of: Acquiring test data of steel bridge deck pavement, and extracting a multi-scale performance parameter set from the test data, wherein the test data comprises raw material scale data, mixture scale data, scale combined structure scale data and full-scale segment scale data; establishing a scale conversion function for mapping the local performance parameters to the overall structure state based on the multi-scale performance parameter set; Constructing an initial digital model based on the scale conversion function and the multi-scale performance parameter set, and carrying out parameter reverse calibration on the initial digital model by combining actual measurement response data in the full-scale segment scale data to obtain a multi-scale performance digital model; based on the multi-scale performance digital model, simulating the acquired service environment data of the target paving structure to obtain performance evaluation data of the target paving structure, wherein the performance evaluation data comprises a predicted performance degradation value and a predicted residual service life.
2. The method of claim 1, wherein the obtaining test data for steel deck pavement and extracting a set of multi-scale performance parameters from the test data comprises: Performing viscoelastic constitutive model fitting on paving key materials in the raw material scale data, and extracting to obtain a material constitutive parameter vector representing the basic mechanical behavior of the material; extracting a mixture macroscopic performance parameter vector comprising a dynamic modulus characteristic parameter and a fatigue equation coefficient by analyzing a dynamic modulus main curve and a four-point bending fatigue life curve of the mixture in the mixture scale data; Performing model inversion analysis based on a force-displacement curve of the scale data of the scaled composite structure, and extracting to obtain an interface behavior parameter vector representing interface bonding sliding behavior; based on the full-scale segment scale data, separating load and temperature time sequence data applied to the structure in the acceleration loading process as external input vectors, and separating structural strain and displacement response time sequence data obtained by monitoring as system response vectors; And integrating the material constitutive parameter vector, the mixture macro performance parameter vector, the interface behavior parameter vector, the external input vector and the system response vector to form the multi-scale performance parameter set.
3. The method of claim 2, wherein the establishing a scaling function for mapping local performance parameters to overall structural states based on the set of multi-scale performance parameters comprises: Calculating to obtain a difference parameter representing geometric dimension and boundary constraint between the scale combination structure scale data and the full-scale segment scale data based on a mechanical similarity principle; based on the difference parameter and the interface behavior parameter vector, constructing a first mapping function taking the interface behavior parameter vector as input and taking the equivalent interface parameter under the full-scale condition as output, wherein the first mapping function comprises undetermined coefficients; Selecting loading working condition data corresponding to a reduced scale combined structure test mechanical mode from the full scale segment scale data; Extracting corresponding local area actual measurement response data from the full-scale segment scale data according to the loading working condition data; Calculating to obtain an uncalibrated equivalent interface parameter vector according to the interface behavior parameter vector, the difference parameter and the first mapping function currently containing the undetermined coefficient; Constructing a local full-scale finite element analysis model corresponding to the loading working condition data according to the uncalibrated equivalent interface parameter vector; Carrying out mechanical simulation calculation on the local full-scale finite element analysis model to generate prediction response data; Constructing a loss function related to the undetermined coefficient according to the predicted response data and the local area actual measurement response data, and carrying out minimization solving processing on the loss function by adopting a regression analysis algorithm to obtain a calibrated undetermined coefficient, wherein the calibrated undetermined coefficient is used for replacing the undetermined coefficient in the first mapping function so as to obtain the scale conversion function.
4. The method of claim 2, wherein constructing an initial digital model based on the scale transfer function and the set of multi-scale performance parameters, and performing parameter inverse calibration on the initial digital model in combination with measured response data in the full-scale segment scale data, to obtain the multi-scale performance digital model, comprises: establishing a parameterized finite element analysis model according to the actual geometric construction of the full-scale segment scale data; endowing the material constitutive parameter vector and the mixture macroscopic performance parameter vector in the multi-scale performance parameter set with material properties of a paving layer in the parameterized finite element analysis model; Processing the interface behavior parameter vector based on the scale conversion function to generate full-scale equivalent interface parameters, and endowing the full-scale equivalent interface parameters to the attribute of interlayer contact in the parameterized finite element analysis model to obtain the initial digital model; Inputting the external input vector in the multi-scale performance parameter set as a load condition into the initial digital model for simulation calculation to obtain a theoretical system response vector; Constructing an error evaluation function based on the theoretical system response vector and the system response vector in the multi-scale performance parameter set; And reversely adjusting a preset parameter to be calibrated in the initial digital model by adopting an optimization algorithm with the aim of minimizing the error evaluation function value until the error evaluation function value meets a preset convergence condition, and outputting the model in the parameter state at the moment as the multi-scale performance digital model.
5. The method of claim 2, wherein simulating the acquired service environment data of the target paving structure based on the multi-scale performance digital model to obtain performance evaluation data of the target paving structure comprises: acquiring historical traffic load data, forecast period traffic load data and environmental time sequence data of the target pavement structure as the service environment data; Inputting the service environment data as load into the multi-scale performance digital model to simulate the full-period service process; in the simulation process, the stress strain time course, the interlayer interface damage state and the integral structure rigidity index time course of each unit of the pavement layer are extracted and recorded in real time; based on the stress-strain time course and the fatigue equation coefficient in the mixture macroscopic performance parameter vector, calculating the fatigue damage distribution of the pavement layer by adopting a linear accumulated damage rule; Based on the interlayer interface damage state time course, the area evolution of the interface void area is counted; predicting a first residual life according to the time when the fatigue damage distribution reaches a critical threshold value, predicting a second residual life according to the time when the area of the interface void area exceeds an allowable threshold value, and comprehensively obtaining the predicted residual service life; And generating the predicted performance degradation value according to the integral structure rigidity index time course.
6. A method according to claim 3, wherein the loss function for the undetermined coefficients is expressed as: Wherein, the As a function of the loss in question, For the undetermined coefficients of the first mapping function, To be the total number of response data points for comparison, To use the undetermined coefficient The local full-scale finite element analysis model is at the first time The predicted response value calculated from the data points, Actual measurement of response data for the local region is at The actual values of the data points are calculated, Representing the norm of the vector.
7. A steel deck pavement performance multi-scale test evaluation system for implementing the method of any one of claims 1 to 6, the system comprising: The data acquisition module is used for acquiring test data of the steel bridge deck pavement and extracting a multi-scale performance parameter set from the test data, wherein the test data comprises raw material scale data, mixture scale data, scale composite structure scale data and full-scale segment scale data; The scale conversion module is used for establishing a scale conversion function for mapping the local performance parameters to the overall structure state based on the multi-scale performance parameter set; The model construction module is used for constructing an initial digital model based on the scale conversion function and the multi-scale performance parameter set, and carrying out parameter reverse calibration on the initial digital model by combining actual measurement response data in the full-scale segment scale data to obtain a multi-scale performance digital model; The performance evaluation module is used for simulating the acquired service environment data of the target pavement structure based on the multi-scale performance digital model to obtain performance evaluation data of the target pavement structure, wherein the performance evaluation data comprises a predicted performance degradation value and a predicted residual service life.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the method of any one of claims 1 to 6 when executing the computer program.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the method of any one of claims 1 to 6.

Description

Multi-scale test evaluation method for pavement performance of steel bridge deck Technical Field The invention belongs to the technical field of steel bridge deck pavement performance evaluation, and particularly relates to a multi-scale test evaluation method for steel bridge deck pavement performance. Background With the development of bridge engineering, in particular to a large-span steel bridge construction technology, the steel bridge deck pavement is used as a key functional layer for directly bearing the load of vehicles and the environmental effect, and the long-term performance and the durability of the steel bridge deck pavement become core problems affecting the operation safety and the economy of the full bridge. The traditional evaluation mode obtains relevant performance parameters to support evaluation conclusion by carrying out targeted tests on paving materials or structures, and provides a certain reference for the design and maintenance of steel bridge pavement. However, in the conventional technology, the evaluation work is mostly focused on the performance analysis of a single scale, or only the basic performance of the paving material is detected, or the local stress performance of a specific structural form is focused, the system consideration of the performance association between different scales is lacking, the service performance of the steel bridge pavement is the result of the combined action of multiple factors such as material characteristics, structural synergism, engineering actual working conditions and the like, the overall stress and deformation rule of the paving system are difficult to be comprehensively reflected by the evaluation data of the single scale, the deviation exists between the evaluation result and the actual service state of the real bridge due to the data fracture between the scales, and the accurate and reliable technical support cannot be provided for the durability design optimization and the full life cycle performance management and control of the paving structure. Disclosure of Invention Based on the above, it is necessary to provide a multi-scale test evaluation method for the performance of steel bridge deck pavement, which can improve the evaluation accuracy of the overall durability of steel bridge deck pavement and provide more reliable technical support for the performance management and control of steel bridge deck pavement. In a first aspect, the application provides a multi-scale test evaluation method for pavement performance of a steel bridge deck, comprising the following steps: Acquiring test data of steel bridge deck pavement, and extracting a multi-scale performance parameter set from the test data, wherein the test data comprises raw material scale data, mixture scale data, scale combined structure scale data and full-scale segment scale data; establishing a scale conversion function for mapping the local performance parameters to the overall structure state based on the multi-scale performance parameter set; constructing an initial digital model based on a scale conversion function and a multi-scale performance parameter set, and carrying out parameter reverse calibration on the initial digital model by combining actual measurement response data in full-scale segment scale data to obtain the multi-scale performance digital model; Based on the multi-scale performance digital model, simulating the acquired service environment data of the target pavement structure to obtain performance evaluation data of the target pavement structure, wherein the performance evaluation data comprises a predicted performance degradation value and a predicted residual service life. In one embodiment, obtaining test data for steel deck pavement and extracting a set of multi-scale performance parameters from the test data includes: Performing viscoelastic constitutive model fitting on paving key materials in raw material scale data, and extracting to obtain a material constitutive parameter vector representing the basic mechanical behavior of the material; extracting a mixture macroscopic performance parameter vector comprising a dynamic modulus characteristic parameter and a fatigue equation coefficient by analyzing a dynamic modulus main curve and a four-point bending fatigue life curve of the mixture in the mixture scale data; performing model inversion analysis on a force-displacement curve based on scale data of the scaled composite structure, and extracting to obtain an interface behavior parameter vector representing interface bonding sliding behavior; based on full-scale segment scale data, separating load and temperature time sequence data applied to a structure in an acceleration loading process as external input vectors, and separating structural strain and displacement response time sequence data obtained by monitoring as system response vectors; Integrating the material constitutive parameter vector, the mixture macro performance parameter ve