TU Delft Repository

We seek to quantify bulk viscoelastic flow, afterslip, and locking, within a rheological framework that is consistent over the entire earthquake cycle. We address this using an ensemble smoother. We construct a 2D finite element seismic cycle model with a power-law rheology in the asthenosphere. A priori information, such as a realistic temperature field and a coseismic slip distribution, is integrated into the model. Model pre-stresses are initialized during repeated earthquake cycles wherein the accumulated slip deficit is released entirely. We tailor the last earthquake to match the observed co-seismic slip of the 2011 Tohoku earthquake. The heterogeneous rheology structure is derived from the temperature field and experimental flow laws. Additionally, we simulate afterslip using a thin viscoelastic shear zone. We focus on constraining power-law flow parameters for the asthenosphere and the shear zone. We assimilate 3D GEONET GNSS displacement time series acquired before and after the 2011 Tohoku earthquake. Power-law viscosity parameters are successfully retrieved for all domains. The data require separate viscoelastic domains in the mantle wedge above and below ~50 km depth. The sub-slab asthenosphere has viscoelastic properties that are distinctly different from the mantle wedge. The trade-off between the power-law activation energy and water fugacity hinders their individual estimation. The wedge viscosity is >10^19 Pa·s during the interseismic phase. Postseismic afterslip and bulk viscoelastic relaxation can be individually resolved from the surface deformation data. Afterslip is substantial between 40-50 km depth and extends to 80 km depth. Bulk viscoelastic relaxation in the wedge concentrates above 150 km depth with viscosities <10^18 Pa·s. Landward motion of the near-trench region occurs during the early postseismic period without the need for a separate low-viscosity channel below the slab.

To ensure transport models are effective tools for planning, they must not only adequately explain current travel choices but also maintain predictive accuracy over forecast horizons while being computationally feasible for practical use. One simple approach to achieving this is by including behavioral theories in transport models to improve the behavioral representation of models.
One such theory is Spatial Competition and Agglomeration Effects (SC&AE). This theory examines how opportunities present nearby influence the attractiveness of a destination. This influence can be either positive (Agglomeration) or negative (Spatial Competition). Although SC&AE is widely recognized in the literature for enhancing the explanatory power of computationally simple Multinomial Logit (MNL) destination choice models, its impact on the temporal transferability of these models remains unexplored.
This study assesses the impact of SC&AE on MNL destination choice models for home-based maintenance, work, and education trips in the Metropolitan Region of Amsterdam on a 5-year short-term forecast horizon (2018-2022) using Dutch National Travel Survey Data (ODiN). The findings indicate that SC&AE has a positive but limited effect on the temporal transferability of these models. This impact decreases with decreasing traveler autonomy and ease of switching to alternate destinations. In terms of percentage improvement, Transfer index metric shows an exaggerated impact (35.2% - 286.36%) while the other performance indicators, such as Fitting Factor (1.1% 3.6%) and % Correct predictions (0.14%-2.05%) confirm that the impact is limited.

In line with the growing trend of satellite miniaturization, Delft University of Technology has developed advanced micropropulsion systems such as micro electro mechanical systems (MEMS) vaporizing liquid micro-resistojet (VLM) using water as propellant. These systems play a crucial role in enabling small satellites to achieve functions like maneuverability and attitude control. The objective of this research is to evaluate the performance of next-generation MEMS VLM by creating a numerical simulation model for the VLM heater microchannel and micronozzle and validating the model using existing experimental data. To this end, numerical simulations were conducted for the VLM microchannel and micronozzle using computational fluid dynamics (CFD) models. The microchannel simulation captured flow boiling characteristics, including bubble nucleation, growth, and heat transfer. Micronozzle simulations validated against experimental data showed deviations of less than 10% in key metrics like thrust and specific impulse and confirms the enhanced performance of next-generation designs.

This doctoral thesis stands on three pillars that emerged from following my scientific interests: i) biophysics, ii) synthetic biology, and iii) biosecurity. The former, biophysics, reflects my desire for deep understanding of biological systems and my affinity for experimental work. The latter, synthetic biology and biosecurity, were born from the conviction that the understanding obtained in pursuing science offers the most fulfillment when applied to the benefits of society.

The main part of this thesis explores methodologies for the extraction, and characterization of large-scale DNA, with a particular focus on the megabase-pair length DNA from bacterial sources. The research aims to bridge the gap between in vivo chromosome studies and in vitro single-molecule techniques by developing approaches that enable the investigation of chromosome structure and dynamics at a more relevant genomic scale. The following chapters detail the experimental approaches, results, and conclusions drawn from this work.

Glioblastoma is one of the deadliest types of brain cancer with patients having a poor prognosis. The development of effective treatments requires physiologically relevant disease model systems. Although there are a variety of 3D glioblastoma culture models available, they fail to capture a key characteristic, namely core and edge tumour regions. The tumour core refers to the central region of the tumour distinguished by densely packed quiescent cells. The edge is located at the periphery of the tumour, where infiltrating/proliferating tumour cells interact with normal tissue. In this study, we successfully designed and fabricated a two-photon polymerized 3D printed scaffold and developed a microinjection-based protocol for guiding the growth of biomechanically constrained glioblastoma spheroids. The formation of the spheroid was achieved by injecting nL-volumes of cells on the scaffolds either functionalized with an extracellular matrix (ECM) coating or embedded in Collagen hydrogel. An alignment protocol based on the use of fiducial cross-shaped markers was employed to align the microinjector needle to the desired position. The culture model was tested by examining cell colonization with a commercial glioblastoma cell line (U87) as well as with patient-derived glioblastoma cells. Immunofluorescence (IF) staining and scanning electron microscopy (SEM) were employed to characterize the model. Two core and two edge-specific immunofluorescence markers were tested to analyse the core and edge formation further. IF and SEM imaging revealed a dense core and protruding edge-like cells both in the ECM-coated scaffold and the collagen-embedded ones. Further, we observed a remarkable difference in terms of F-actin expression between the core and edge region. We compared these results with those obtained in a scaffold-free model, which showed that the presence of the scaffold influences the behaviour of glioblastoma cells, resulting in guided growth, along the microfabricated structures. The developed 3D culture model paves the way for further investigation of core and edge dynamics as well as for prospective in-vitro drug screening.