Optimizing the pump schedule of water distribution systems using a deep learning meta-model: To what extent can algorithm unrolling optimize the pump schedule of an urban water distribution system?

This thesis investigates the integration of algorithm unrolling and genetic algorithms (GA) for optimizing pump scheduling in water distribution systems (WDS), a critical component for ensuring energy-efficient water delivery. In the context of modern civilization’s reliance on clean, affordable water for diverse uses, the operation of a WDS,...

Integral Probabilistic Reliability Assessment for Flood Defences: The Impact of Correlations

Since 2017, Dutch flood defences are assessed according to new safety standards. These standards are based on flooding probabilities and rely on several assumptions and approximations. There are concerns that the combination of these assumptions leads to conservative results. Recently computed probabilities of failure are...

An integrated approach for efficient and resilient airport management

Application of Conditional Random Fields and Sparse Polynomial Chaos Expansions to Geotechnical Problems

In geotechnical applications, mechanical properties of soil vary spatially within the soil mass and they are often represented by random fields. When data at certain locations of the soil mass are available, conditional random fields may be used to incorporate them. In this paper, we combine conditional random fields with sparse polynomial chaos...

Development of a fast aerodynamic tool using meta-modeling techniques

There is a need for a wave drag method that combines the speed of handbook methods with the accuracy of computational methods. Especially determining the onset of wave drag as well as the initial drag rise is important in initial design stages. Meta-models allow this by capturing the trends present in previously computed data, providing an...

Stochastic Surrogates for Measurements and Computer Models of Fluids

Both measurements and computer simulations of fluids introduce a prediction problem. A Particle Image Velocimetry (PIV) measurement of a flow field results in a discrete grid of velocity vectors, from which we aim to predict the velocity field or related quantities. In Computational Fluid Dynamics (CFD), the output of the computer code depends...

The activity package of the DNO in 2050: An explorative research of the future activities of Dutch DNOs in 2050, within multiple technical and institutional landscapes of the Dutch electricity system

Business Process Modelling for Measuring Quality

Business process modelling languages facilitate presentation, communication and analysis of business processes with different stakeholders. This paper proposes an approach that drives specification and measurement of quality requirements and in doing so relies on business process models as representations of business processes. The approach is...

MAIA: A framework for developing agent-based social simulations

Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty

There is increasing interest in long-term plans that can adapt to changing situations under conditions of deep uncertainty. We argue that a sustainable plan should not only achieve economic, environmental, and social objectives, but should be robust and able to be adapted over time to (unforeseen) future conditions. Large numbers of papers...

An environment to support flexible information modeling