为解决隧道洞口工程的边仰坡设计在传统二维方式中面临精度控制困难、参数化与自动化程度低以及缺乏空间关系等问题，提出一种基于参数化、三维化和智能化理念的隧道洞口边仰坡三维智能设计方案。首先，建立隧道洞口边仰坡设计案例数据库，利用深度学习算法智能确定洞口明暗分界里程与边仰坡开挖参数；其次，引入基于弧面的边仰坡过渡方式，应用群体智能算法优化控制性过渡断面的选择，通过计算开挖控制点并进行曲面缝合，构建边仰坡整体开挖模型；最后，将该模型与周边地形进行布尔运算，以实现开挖边界、工程量等设计成果的精确计算和自动输出。以长赣铁路为实例进行应用分析的结果表明：
相比于传统设计方式，由智能推荐得到的设计方案具备较高可信度，且显著失真的开挖线减少28.0%，工程量计算准确率平均提升8.7%，能够有效改善隧道洞口边仰坡设计的效率和质量。
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.
