TU Delft Repository

This study investigates the mechanical properties of cementitious composites with 3D-printed auxetic lattices, featuring negative Poisson's ratios (auxetic behavior) in multiple directions. These lattices were fabricated using vat photopolymerization 3D printing, and three base materials with varying stiffness and deformation capacities were analyzed to determine their impact on the composites’ mechanical behavior. To unravel the reinforcing mechanisms of multidirectional auxetic lattices, which exhibit auxetic behavior in both planar and out-of-plane directions, X-ray computed tomography (X-ray CT) was utilized to analyze composite damage evolutions under different strain levels. The micro-CT characterization reveals that auxetic lattices more effectively constrain crack growth and dissipate energy by distributing stress evenly within the cement matrix. In contrast, due to lack of lateral confinement, the non-auxetic lattice reinforced composites primarily dissipate energy through extensive crack propagation and interfacial damage, leading to lower peak strength. When strain exceeding 5%, although the confinement from the auxetic behavior diminished with crack propagation, the lattice can still maintain the composite's structural integrity, resulting in 1.7 times higher densification energy than conventional cement-based materials. These findings provide valuable insights for designing auxetic lattice-reinforced cementitious composites with enhanced load-bearing capacity and improved dissipation capabilities.

The statistical treatment of random weakly nonlinear interactions between waves, called wave turbulence (WT), is fundamental to understanding the development of the ocean surface. For gravity waves, wave turbulence predicts a dual (direct and inverse) cascade of energy and wave action, which yield power-law solutions for the energy spectrum. While energy cascades were predicted more than 50 years ago, observing them in the laboratory with mechanical forcing remains a challenge. Here, we present experiments in which we attempted to reproduce both direct and inverse cascades in a large circular wave tank. The geometry of the wave tank allows for the creation of isotropically spread surface waves, which is an assumption that underlies WT theory. Although we did see evidence of a direct cascade of energy, we did not observe an inverse cascade of wave action. We discuss the competing effects of dissipation and intermittency, which may dominate or obscure the weakly nonlinear dynamics.

The repeat period of SAR data and its side-looking characteristics make InSAR time series analysis useful for water level monitoring applications. The standard approach determines corresponding scatterers by focusing the study area on the multipath radar reflections that include the water level. This paper introduces an alternative approach to identifying such signals using two metrics: cosine similarity and temporal differential coherence. The results show that temporal differential coherence can detect phase variations similar to water level by constantly returning high values even when there is an offset, while cosine similarity yields low scores. Within an urban environment, this approach finds point scatterers corresponding to water level changes in or near water, such as permanent floating objects, bridges, and buildings adjacent to water, where the highest differential coherence value was acquired from a permanent floating restaurant in open water.

InSAR enables the estimation of spatio-temporal displacements, relative to a reference point and a reference epoch, here defined as the mother image. When dealing with time series, there are several options to treat the mother image in computing and plotting the temporal phase differences, producing distinctly different results, in terms of the estimated displacement parameters and their precision. Here we review the three approaches mostly encountered in literature, discuss the implications of the different approaches, and recommend the 'embracing mother' approach for standard InSAR analyses and visualizations.

User comfort in higher-level Automated Vehicles (AVs, SAE Level 4+) is crucial for public acceptance. AV driving styles, characterised by vehicle kinematic and proxemic factors, affect user comfort, with “human-like” driving styles expected to provide natural feelings. We investigated a) how the kinematic and proxemic factors of an AV's driving style affect users' evaluation of comfort and naturalness, and b) how the similarities between automated and users' manual driving styles affect user evaluation. Using a motion-based driving simulator, participants experienced three Level 4 automated driving styles: two human-like (defensive, aggressive) and one machine-like. They also manually drove the same route. Participants rated their comfort and naturalness of each automated controller, across twenty-four varied UK road sections. We calculated maximum absolute values of the kinematic and proxemic factors affecting the AV's driving styles in longitudinal, lateral, and vertical directions, for each road section, to characterise the automated driving styles. The Euclidean distance between AV and manual driving styles, in terms of kinematic and proxemic factors, was calculated to characterise the human-like driving style of the AV. We used mixed-effects models to examine a) the effect of AV's kinematic and proxemic factors on the evaluation of comfort and naturalness, and b) how similarities between manual and automated driving styles affected the evaluation. Results showed significant effects of lateral and rotational kinematic factors on comfort and naturalness, with longitudinal kinematic factors having a less prominent effect. Similarities in vehicle metrics, such as speed, longitudinal jerk, lateral offset, and yaw, between manual and automated driving styles, enhanced user comfort and naturalness. This research facilitates an understanding of how control features of AVs affect user experience, contributing to the design of user-centred controllers and better acceptance of higher-level AVs.