Parallel Three-Dimensional Distance Transform for Railway Alignment Optimization Using OpenMP

et al. 2021

Sustainability

Self Cite

Sustainable railway construction and operation are threatened by densely occurring geological hazards in complex mountainous regions. Thus, during the alignment optimization process, it is vital to reduce the harmful impacts of geological hazards to a railway. However, current alignment-related studies solely consider such threats in existing geological hazard regions and, outside these regions, slight attention has been devoted to the assessment of potential hazardous impacts along the alignment. To this end, this paper proposes a novel railway alignment optimization model considering both existing and potential geological hazards based on quantitative geological hazard evaluation criteria from a sustainable safety perspective. More specifically, a geohazard zone classification method, within which an energy–slope model is integrated, is first developed. Three geohazard regions, namely the geohazard outbreak region, buffer region and fuzzy region, can then be obtained. Afterward, a spatial geological hazard assessment model is constructed considering the geological danger of three kinds of geohazards (debris flows, landslides and rockfalls) and railway construction vulnerability. This model is incorporated into a previous cost–hazard bi-objective alignment optimization model. Finally, the effectiveness of the proposed model is verified by applying it to a real-life case of the Sichuan–Tibet railway. The results show that this method can effectively optimize mountain railway alignments by concurrently reducing geological hazards and costs, which is beneficial to railway safety and sustainable construction and operation.

Section: Geological Hazard Energy-slope Modelmentioning

confidence: 99%

Railway Alignment Optimization in Mountainous Regions Considering Spatial Geological Hazards: A Sustainable Safety Perspective

Xie

et al. 2021

Sustainability

Self Cite

“…Lastly, identify all railway constructions according to the relations between E g and E d , with details shown in T. Song, Pu, Schonfeld, Li et al. (2020). Evaluate the seismic fragility of each bridge.…”

Section: Optimization Modelmentioning

confidence: 99%

“…However, alignment design is known as a quite difficult and time‐consuming process due to the large‐scale study area (T. Song, Pu, Schonfeld, Li et al., 2020), complicated geographical conditions (Bosurgi, Pellegrino, & Sollazzo, 2013; T. Song, Pu, Schonfeld, Zhang et al., 2020), multiple conflicting design objectives (Yang, Kang, Schonfeld, & Jha, 2014), and many constraints (Easa & Mehmood, 2008; W. Li et al., 2019). Moreover, there exist theoretically unlimited possible alignment solutions in the study area (Hirpa, Hare, Lucet, Pushak, & Tesfamariam, 2016).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Bi‐objective mountain railway alignment optimization incorporating seismic risk assessment

Song

Computer aided Civil Eng

et al. 2020

Self Cite

Mountain railway alignment optimization is known as a very complex engineering problem that should consider many factors, such as drastically undulating terrain, geological hazard impacts, and additional constraints. Moreover, many mountain railway projects are located in earthquake‐prone regions and hence are greatly threatened by seismic activity. Thus far, most alignment optimization studies aim at finding the least‐cost solutions within budget but slight attention has been paid to reducing the complex seismic risk through optimization. In this paper, the first known quantitative seismic risk assessment model for railway alignment optimization is presented, which combines probabilistic seismic fragility analysis and probabilistic seismic loss analysis. Three methods for fragility analysis of bridge, tunnel, and earthwork sections are designed and a specific event tree is developed for seismic loss analysis. Moreover, multiple preliminary constraints are specified for alignments traversing active faults. Afterwards, the seismic risk assessment model is combined with a least‐cost model to formulate a bi‐objective optimization model. To solve it, a particle swarm optimization algorithm is improved by blending the crowding distance computation (CDC) and, especially, a novel marginal benefit analysis (MBA) to search for pareto‐optimal solutions during optimization. A prescreening and repairing operator is also designed to handle the fault constraints. Finally, when applying the proposed procedure to a complex realistic railway case, the results show that the hybrid CDC+MBA bi‐objective solver can find better pareto‐optimal solutions than the generic CDC method. Besides, detailed data analysis shows that the present method can produce less expensive as well as safer solutions than the best alignment designed by experienced human engineers.

“…To solve these problems, we have proposed a two‐stage optimization strategy (Li et al., 2017). In the first stage (Li et al., 2016; Pu et al., 2018; Pu, Song, Schonfeld, Li, Zhang, Wang et al, 2019; Song et al, 2020), we determined several promising railway paths from the broad study area using distance transform (DT) algorithms, which are shortest‐path algorithms. Then, these paths were used as centerlines to generate a set of railway corridors (Area‐corridor stage).…”

Section: Introductionmentioning

confidence: 99%

Mountain railway alignment optimization considering geological impacts: A cost‐hazard bi‐objective model

Song

Computer aided Civil Eng

et al. 2020

Self Cite

Railways are greatly threatened by geological hazards whose disastrous effects include severe economic losses as well as serious casualties. It is vital to properly account for such geological hazardous impacts during a railway alignment optimization process. However, geological factors are complex, especially in mountainous regions. Besides, economic factors are also crucial in railway alignment design. Therefore, railway alignment optimization can be termed as a cost-hazard bi-objective decision-making process. So far, least-cost railway alignment optimization has been studied quite thoroughly while the complicated geological hazard factors have received relatively little attention. In this study, a bi-objective alignment optimization model considering cost and geological hazard is developed. A novel geological railway alignment optimization model is proposed, which includes spatial geological constraints and geological hazard evaluations, after geological railway alignment design criteria are presented and analyzed for three kinds of typical geological hazards: debris flows, landslides, and rockfalls. The geological hazard evaluation includes geological susceptibility and vulnerability assessments. Then, this model is integrated with a previous least-cost alignment optimization model to construct a cost-hazard bi-objective model. The alignment searching processes are also improved to solve the proposed model by integrating geological-constraints-handling and bi-objective alignment optimization approaches. Finally, the effectiveness of the proposed method is verified by applying it to a complicated real-world case. The results show that the proposed method can produce less expensive and safer solutions than the best alignment designed by experienced human designers while satisfying all required design standards. Moreover, the method's applicability for solving actual problems is further demonstrated through the sensitivity analysis. 1 INTRODUCTION Geological hazards greatly threaten the construction and operation of railways. Their disastrous effects include not