PhD Position in Dynamic Planning of Construction and Maintenance Activities on Railway Networks
The Chair of Infrastructure Management lead by Professor Dr. Bryan T. Adey in the Institute of Construction and Infrastructure Management of the Department of Civil, Environmental and Geomatic Engineering has an opening for a PhD student in the field of Dynamic Planning of Construction and Maintenance Activities on Railway Networks.
Railway networks are constructed and maintained to provide service, e.g. to transport persons and goods from A to B in a specified amount of time. The service required from railway networks changes over time, e.g. to transport a greater number of persons and goods from A to B in a specified amount of time. The ability of railway networks to provide service also changes over time due to the deterioration of the infrastructure. Deterioration may lead, for example, to excessive track settlement trains can no longer transport persons and good from A to B in the specified amount of time. In order to ensure that railway networks continue to provide the service expected of them construction and maintenance activities are required.
In order to ensure that there is minimal effect on service when construction and maintenance activities are performed, they are first planned in general far in advance, with general construction activities being first planned between 10 and 7 years before they are to be performed, and maintenance activities being first planned between 7 years and 1 year before they are to be performed. In both cases, the activities are first planned at a relatively high level of abstraction and are worked out in more detail over time. By generally knowing which activities will be performed far in advance, it is possible to, approximate the different ways that they could be performed, and interact with train schedulers to determine the optimal trade-off between how the activities are performed and how the service is provided.
In these early planning phases, it is necessary to have a general 1) understanding of the construction and maintenance activities to be performed, 2) understanding of the different methods that can be used to perform these activities and how they affect service, 3) estimating the costs of performing the construction and maintenance activities using each method, 4) estimating the general effects of the activities on service while they are being performed, keeping in mind that the effect on service can vary throughout the activity, and 5) estimating the lengths of time required to perform the activities.
Although these activities are currently developed by planning experts in a qualitative and iterative fashion, there appears to be potential to improve the planning process through the use of improved computer support. Improved support could greatly increase the ability of planning experts to assess possible combinations of construction and maintenance activities that are possible without affecting the provided service and how they can be modified to minimally affect service, if affecting service is unavoidable.
The goal of this PhD is to propose the first mathematically supported methodology to determine an optimal set of coordinated construction and maintenance activities to be performed on railway networks. Construction activities, e.g. expanding a single-track section to a double track section, are modifications required to ensure infrastructure meets changing demands. Maintenance activities, e.g. track renewal, ensure infrastructure continues to provide the service for which it was originally designed.
The methodology will be based on a mathematical model with an objective function that maximizes net benefit, e.g. making, optimal trade-offs between the costs of performing construction and maintenance activities, and the effects on service. The model will consider economical, structural and topological dependencies, as well as the uncertainties associated with the future condition state of the assets, i.e. due to the environment and traffic loads. It will be developed taking into consideration the how assets of different types function, how they deteriorate over time and how train movements might be affected by the execution of interventions.
The methodology will be demonstrated by generating the optimal set of coordinated construction activities for a railway network at a very preliminary stage, i.e. 10 to 7 years before they are performed, and illustrating how maintenance activities are to be optimally planned from a very preliminary stage, i.e. 7 to 3 years before they are planned, to more detailed stages, e.g. 3 to 1 years before they are planned, given the earlier determined set of coordinated construction and maintenance activities. This work will require consideration of the spatial distribution of the objects in the network as well as their roles in the network. Special attention will be required to ensure that the information on the object level e.g. a power line, a bridge, or a track section is collected and generated in ways that are compatible with the network level analysis.
The successful candidate for this PhD position will have a Master’s degree in civil engineering, geo-spatial engineering, systems engineering or a related field, and will have experience using operations research methods. A good grasp of probability theory, risk assessment, R, python and GIS is beneficial. Good knowledge of English is essential, and good knowledge of German is preferred.
We look forward to receiving your online application until 10 January 2020 including the following documents:
- letter of interest including your understanding of the problem and thoughts on a way forward
- one publication by the author
- curriculum vitae (with list of publications and contact information of at least two referees)
- grades of all university courses taken as well as diplomas
Please note that we exclusively accept applications submitted through our online application portal. Applications via e-mail or postal services will not be considered. Screening of applications starts on 11 January 2020. Applications are accepted until the position is filled.
The preferred start date is 01 March 2020 although others are possible.