Machine learning study on performance prediction of asphalt mixtures under Dutch conditions

The Netherlands is a northwestern European country. The location makes the Netherlands an important entry for trade to the European continent resulting in high traffic intensities [1]. The Netherlands has one of the densest road networks in the world, having over 139.000km of roadways [2, 3]. The understanding of the link between the functional...

Optimal maintenance of deteriorating systems integrating deep reinforcement learning and Bayesian inference

An issue of utmost significance constitutes the maintenance of engineering systems exposed to corrosive environments, e.g. coastal and marine environments, highly acidic environments, etc. The most beneficial sequence of maintenance decisions, i.e. the one that corresponds to the minimum maintenance cost, can be sought as the solution to an...

Optimal condition-based maintenance of asphalt concrete pavements

Maintenance is a necessary measure to keep the asset, in this case a road network, in good condition. Spending too much on maintenance is clearly not efficient, while not spending enough may cause the condition to drop below a desired value; moreover, it will almost always cost more to correct the emerging damages afterwards. <br/>In this report...

Rolling Weight Deflectometer for Stiffer Pavements: Combining Machine Learning and Field Data

Pavement structures are assessed based on its functional and structural capacity in order to evaluate the safety of its use. Structural pavement evaluation is often carried out by road authorities or consulting companies that use non-destructive testing (NDT) methods to assess the remaining life and structural capacity of a road structure at...

Quantifying track condition based on soil properties

Soil is an important part of a railway track structure. It provides the foundation for the structure and distributes the imposed loads. Consequently, soil has an influence on the condition of a track structure and a low quality soil can ultimately cause failure of the track structure. To be able to include the condition of a soil in the...

Hierarchical Model Predictive Control in Building Climate Systems for Passive Energy Sources

There is an urgent need for technical innovations in the construction industry to meet the European Parliament’s qualifications for reducing the energy footprint of buildings. This thesis is devoted to conducting research on control strategies that optimally manage passive energy sources, e.g., natural ventilation and solar irradiance, in...

Bayesian system identification for structures considering spatial and temporal dependencies

Bayesian system identification, including parameter estimation and model selection, is widely used to infer partially known, unobservable parameters of the models of physical systems when measurement data is available. A common assumption in the Bayesian system identification...

Rail Line Detection Based Photogrammetry: Using image content knowledge to improve 3D reconstruction of railway tracks

An increasing load on the Dutch rail network requires new solutions for railway monitoring as increasing wear and tighter schedules limit the possibilities of regular maintenance. UAV (Unmanned Aerial Vehicle) based photogrammetry is such a solution which limits the presence of people near the railway and train hindrance. Photogrammetric feature...

PDDL-Based Task Planning of Survey Missions for Autonomous Underwater Vehicles: A generic planning system, taking into account location uncertainty and environmental properties

Autonomous Underwater Vehicles (AUVs) are unmanned vehicles that give the opportunity to carry out lengthy and dangerous tasks autonomously. This is particularly useful for survey tasks, where the objective is to search the seafloor for objects. In this thesis work a planning system is developed that can plan a path for survey tasks, while...

Deep Learning for Monitoring the Health Condition of RailwayCrossings

In this thesis, a method to monitor the health condition of railway crossings based on vibration data recorded by the accelerometers installed on the crossing is proposed. Due to various types of trains and other exogenous factors, responses obtained from accelerometers vary, even when the crossing has the same state condition. As a consequence,...

Model predictive control approaches for urban traffic networks: A comparison between optimization algorithms

In this thesis, the effect of traffic light control on urban networks is investigated, with the main focus on the optimization algorithms used to solve the optimization problems resulting from a model predictive control approach. This will be done by using a macroscopic traffic flow model (the S-Model) to simulate the real-time traffic flows...