Page 77 - 2025年第56卷第11期
P. 77
报,2024,55(8):966-976,989.
[ 43] 任 炳 昱 , 吴 斌 平 , 苏 哲 , 等 . 基 于 BIM 的 土 石 坝 施 工 进 度 动 态 可 视 化 仿 真 方 法 : CN2020108927 96. 1
[P] 2022-09-30.
.
.
[ 44] 钟登华,王飞,吴斌平,等 . 从数字大坝到智慧大坝[J] 水力发电学报,2015,34(10):1-13.
[ 45] WANG T C, LIU M Y, ZHU J Y, et al. High-resolution image synthesis and semantic manipulation with condi‐
/
tional gans[C]/ Proceedings of the IEEE conference on computer vision and pattern recognition. 2018.
[ 46] RONNEBERGER O, FISCHER P, BROX T. U-net: Convolutional networks for biomedical image segmentation
[C]/Medical image computing and computer-assisted intervention-MICCAI 2015:18th international conference. 2015.
/
[ 47] 任炳昱,卢逊,王晓玲,等 . 基于 SLAM 优化的高拱坝施工仿真移动 AR 可视化[J] 水力发电学报,2021,
.
40(11):115-128.
[ 48] 中华人民共和国住房和城乡建设部 . 水工建筑物抗震设计标准:GB 51247—2018 [S].北京:中国计划出版
社,2018.
[ 49] FAN G,LI J,HAO H,et al. Data driven structural dynamic response reconstruction using segment based genera‐
.
tive adversarial networks[J] Engineering Structures,2021,234:111970.
[ 50] WOLDESELLASSE H, TESFAMARIAM S. Prediction of lateral spreading displacement using conditional Genera‐
.
tive Adversarial Network (cGAN)[J] Soil Dynamics and Earthquake Engineering,2022,156:107214.
[ 51] SU Z,YU J,XIAO X,et al. Deep learning seismic damage assessment with embedded signal denoising consider‐
.
ing three-dimensional time-frequency feature correlation[J] Engineering Structures,2023,286:116148.
Study on spatiotemporal analysis system of earth-rockfill dam seismic dynamic response
under the digital twin framework
1 1 1 1 2 1
SU Zhe ,WANG Xiaoling ,YU Jia ,WANG Jiajun ,YU Hongling ,ZHANG Jun
(1. State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation,Tianjin University,Tianjin 300072,China;
2. College of Water Resources and Civil Engineering,China Agricultural University,Beijing 100083,China)
Abstract:To address the shortcomings of current dam seismic dynamic response analysis systems,which often fail
to consider the impact of construction quality on the physical and mechanical parameters of dam materials and
struggle with rapid analysis and visualization of the temporal and spatial distribution of dynamic responses,this study
proposed a method for constructing a spatiotemporal analysis system for dam seismic dynamic response under the digi‐
tal twin framework. This approach leveraged the strengths of digital twins,such as virtual-real mapping and rapid
analysis. The system′s data foundation integrated high-fidelity geometric models,material parameters of the dam
body,and seismic motion information through parameterized modeling,intelligent monitoring of construction qual‐
ity,and virtual sensors. A novel heterogeneity analysis model for dam material parameters based on transfer learning
and ResNet was introduced to accurately analyze the spatial distribution of material parameters across the entire dam,
considering the effects of construction quality. For specialized modeling,a pix2pixHD-based surrogate model for spa‐
tiotemporal analysis of dam seismic response is developed. This model used multi-layer generative adversarial net‐
works to learn the temporal distribution characteristics of seismic response data and local enhancers to improve the
authenticity of spatial distribution features in the analysis results,thereby overcoming the limitations of existing surro‐
gate models that can only predict a few points and fail to characterize the overall spatiotemporal distribution of seismic
dynamic responses. For system visualization,a CUDA-accelerated 3D physical field calculation method was proposed
for visualizing dam seismic dynamic responses,addressing the issue of using pre-made animations for earthquake pro‐
cess visualization in current research. Using an earth-rockfill dam project in southwestern China as case study,a dam
seismic analysis system was developed within the digital twin framework. The system achieved rapid analysis and visu‐
alization of the entire dam′s seismic dynamic response in just 148 ms,providing strong support for dam seismic safety
assessment and decision-making.
Keywords:dam seismic dynamic response analysis;digital twin;material parameters heterogeneity;spatiotemporal
global surrogate model;3D physical field visualization
(责任编辑:王 婧)
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