The traditional two-dimensional design method for the side and front slopes of tunnel
portal projects face some challenges, such as difficulties in quality control,
low parameterization and automation, and a lack of spatial relationship. To
address these problems, a design scheme for tunnel portal slopes based on
parametric, three-dimensional, and intelligent concepts
is proposed. Initially, a database of tunnel portal slope design cases is
established; further, a deep learning algorithm is employed to intelligently
determine the portal boundary mileage and excavation parameters of the tunnel
portal slope. Subsequently, a slope transition mode based on a curved surface
is introduced, a swarm intelligence algorithm is applied to optimize the
selection of controlling transition sections, and excavation control points are
estimated to stitch them into a mesh, thereby establishing a slope excavation
model. Finally, the integrated slope excavation model and terrain model are
subjected to Boolean operations to determine the boundary and quantities of
excavation accurately and automatically. A case study conducted on the Changsha-Ganzhou railway using the proposed method reveals that compared with
the traditional method, the design scheme obtained via intelligent
recommendations exhibits high reliability, a reduction in the excavation
boundaries with notable distortion by 28.0%, and an increase in the average
accuracy rate of excavation quantities by 8.7%. These results confirm that the
proposed method improves the efficiency and quality of the tunnel portal slope
design.
DAI Linfabao
,
CHEN Shaoping
,
YANG Jian
,
SUN Wenhao
,
WU Jiaming
,
YANG Hui
. Intelligent Design Methods
for Tunnel Portal Slopes[J]. Tunnel Construction, 2024
, 44(12)
: 2500
-2509
.
DOI: 10.3973/j.issn.2096-4498.2024.12.017
