Interactive reinforcement learning innovation to reduce carbon emissions in railway infrastructure maintenance

Carbon emission is one of the primary contributors to global warming. The global community is paying great attention to this negative impact. The goal of this study is to reduce the negative impact of railway maintenance by applying reinforcement learning (RL) by optimizing maintenance activities. Railway maintenance is a complex process that may not be efficient in terms of environmental aspect. This study is the world's first to use the potential of RL to reduce carbon emission from railway maintenance. The data used to create the RL model are gathered from the field data between 2016–019. The study section is 30 km long. Proximal Policy Optimization (PPO) is applied in the study to develop the RL model. The results demonstrate that using RL reduces carbon emission from railway maintenance by 48%, which generates a considerable amount of carbon emission reduction and reduces railway defects by 68%, which also improves maintenance efficiency significantly

Sustainability-based lifecycle management for bridge infrastructure using 6D BIM

A number of bridge infrastructures are rising significantly due to economic expansion and growing numbers of railway and road infrastructures. Owing to the complexity of bridge design, traditional design methods always create tedious and time-consuming construction processes. In recent years, Building Information Modelling (BIM) has been developed rapidly to provide a faster solution to generate and process the integration of information in a shared environment. This paper aims to highlight an innovative 6D BIM approach for the lifecycle asset management of a bridge infrastructure by using Donggou Bridge as a case study. This paper adopts 6D modelling, incorporating 3D model information with time schedule, cost estimation, and carbon footprint analysis across the lifecycle of the bridge project. The results of this paper reveal that raw materials contribute the most embodied carbon emissions, and as the 6D BIM model was developed in the early stage of the lifecycle, stakeholders can collaborate within the BIM environment to enhance a more sustainable and cost-effective outcome in advance. This study also demonstrates the possibility of BIM applications to bridge infrastructure projects throughout the whole lifecycle. The 6D BIM can save time by transforming 2D information to 3D information and reducing errors during the pre-construction and construction stages through better visualisation for staff training. Moreover, 6D BIM can promote efficient asset and project management since it can be applied for various purposes simultaneously, such as sustainability, lifecycle asset management and maintenance, condition monitoring and real-time structural simulations. In addition, BIM can promote cooperation among working parties and improve visualisation of the project for various stakeholders