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A Comprehensive Analysis of Urban Flooding Under Different Rainfall Patterns:A Full-Process Perspective in Haining, China
No full textUrban flooding, driven by extreme rainfall events and urbanization, poses substantial risks to urban safety and infrastructure. This study employed a neighborhood-scale InfoWorks ICM model to analyze the full-process impacts of urban flooding under six rainfall return periods in Haining, China. The results reveal distinct non-linear responses from the 3-year to 50-year rainfall return period: (1) the surface runoff volume increases by 64.3%, with peak timing advancing by about one minute; (2) the overflow nodes rise from 37.35% to 63.24%, with durations over 30 min increasing by 78.6%; (3) the inundation areas expand by 164.9%, with maximum depths increasing by 0.31 m, showing significant regional disparities; and (4) high-risk zones, such as Haining People’s Square and Railway Station, require targeted interventions due to severe surface overflow and inundation. This comprehensive analysis emphasizes the need for tailored and phased flood prevention measures that address each stage of urban flooding. It provides a strong framework to guide urban planning and enhance resilience against rainfall-induced urban flooding.</p
Overview and Challenges of Computer Vision-Based Visual Inspection for the Assessment of Bridge Defects
No full textVisual inspection remains the most fundamental and widely used method for assessing the condition of bridges. This process involves observation of structural surfaces at a close distance to identify visible signs of deterioration such as cracking, spalling, corrosion, and delamination. Traditionally, human inspectors perform visual inspections manually. This labour-intensive process is associated with many limitations, for example, subjectivity to an inspector’s interpretation, difficulty accessing structural components, management of large volumes of unstructured data and the lack of consistent historical records. Recent advancements in computer vision and artificial intelligence have enabled considerable progress toward automating visual inspections. However, the full automation of visual inspections in practical, real-world scenarios remains constrained by several challenges: (i) the continued need for human intervention, (ii) the limited availability of high-quality labelled datasets, (iii) the generalizability of existing models, and (vi) the lack of standardized inspection protocols. In this positioning paper, we present an overview of the current state of automated visual inspection for defects identification in bridges. It reviews key open-source datasets of defects and state-of-the-art deep learning models. We give our forward-looking perspective on fully automated defects identification systems that align with standardized visual inspection guidelines
Federated causal discovery with missing data in a multicentric study on endometrial cancer
No full textObjectives: Establishing causal dependencies is crucial in applied domains, such as medicine and healthcare, where decision-making must be explainable. In these settings, small sample sizes and missing data call for federated approaches to maximise the amount of information we can use. Methods: We propose a novel federated causal discovery algorithm capable of pooling information from multiple sources with heterogeneous missing data to learn a graph representing cause–effect relationships. In particular, we learn a causal graph on a centralised server while taking into account both prior knowledge and missingness mechanism specific to each client. Results: We applied the proposed algorithm to synthetic data and real-world data from a multicentric study on endometrial cancer, validating the obtained causal graph through quantitative analyses and a clinical literature review. Conclusion: Our approach learns an accurate model despite data missing not-at-random.</p
Circular (De)Construction Matchmaking:Towards a Morphological Matrix
No full textShifting from recycling toward reuse can accelerate the transition to a Circular Economy (CE) in the built environment. However, the large-scale implementation of reuse remains challenging. This research frames circular (de)construction reuse as a matchmaking problem, where supply and demand for reusable materials need to be matched. Currently, there is a lack of understanding of what fundamental dimensions that constitute matchmaking, and what options within each dimension are available to formulate a coherent matchmaking strategy. To address this gap, this research proposes a morphological matrix that tailors decision-making processes for circular (de)construction matchmaking across different assets and buildings. The matrix is grounded in literature insights and its functionality is illustrated through a user case. Different combinations of options can be selected from each dimension, widening the search for possible matchmaking strategies, and leading to innovative strategies that have not previously been identified. The study advances theoretical knowledge of matchmaking mechanisms and offers decision-support guidance for practitioners, bridging the gap between CE theory and implementation in the built environment
Impacts from low-frequency, high-consequence volcanic eruptions (e.g., calderaforming VEI 7–8 events and large igneous provinces)
No full textThis chapter addresses the potential impacts and catastrophic risk posed by explosive caldera-forming eruptions (VEI 7–8) and flood basalt volcanism associated with large igneous provinces (LIPs). The potential consequences include climate disruption, destruction of many thousands of square kilometres around the vent, systemic risks to globally-connected critical infrastructure, and cascading socio-economic crises. A key contribution of the chapter is linking understanding of past events, with current risk assessment, disaster risk reduction, and need for development and maintenance of international policy and coordination
Mapping canopy phenolics in European mixed temperate forests using air- and space-borne imaging spectroscopy
No full textPhenolics are a rarely quantified plant biochemical trait that plays a vital role in plant physiology and ecosystem functioning, contributing to plant's chemical defence and influencing nutrient cycling and soil microbial compositions. Spatially continuous information on foliar phenolics is essential for assessing plant health and ecosystem functional diversity. However, previous efforts to predict and map phenolics have been confined to aircraft-based hyperspectral data in limited biomes. The potential of next-generation imaging spectroscopy, whether airborne- or spaceborne-based, for mapping phenolics remains underexplored, particularly in structurally complex and heterogeneous ecosystems such as European mixed temperate forests. Furthermore, much is still unknown about the consistency and uncertainties of predicting forest canopy phenolics across different acquisition levels (airborne vs. spaceborne), limiting our ability to generalise and upscale local trait estimates to broader spatial extents. In this study, we sampled sunlit top-of-canopy leaves from three dominant tree species across mixed temperate forests in southeast Germany. Leveraging next-generation airborne (AVIRIS-NG) and spaceborne (PRISMA) imaging spectroscopy (400–2400 nm), we modelled two ecologically important phenolics (total phenol and tannin) expressed in three forms (foliar mass-based, foliar area-based, and canopy-based). The predictive accuracy of two data-driven approaches, partial least squares regression (PLSR) and Gaussian processes regression (GPR), was compared to assess performance across different spatial scales. Our results demonstrate that phenolics in sunlit canopy leaves can be accurately estimated from both airborne and spaceborne data, with foliar area-based phenolics showing the strongest relationship with spectral reflectance (total phenol: R2 = 0.64–0.69, NRMSE = 13.28%–15.65%; tannin: R2 = 0.49–0.65, NRMSE = 15.86%–21.29%). We observed several similar patterns in model coefficients across airborne and satellite levels, with informative wavelengths aligning with known phenolic features. While the model accuracy declined slightly when scaling from canopy to landscape scale, phenolic maps derived from AVIRIS (aggregated to 30 m) and PRISMA showed good spatial agreement and linearity (GPR: r = 0.68, slope = 0.86; PLSR: r = 0.57, slope = 0.49). These maps successfully captured inter- and intra-species phenolic variability across the test site with low prediction uncertainty. Our findings provide valuable insights into mapping canopy traits across different observational scales, demonstrating how next-generation imaging spectroscopy can characterize the spatial and temporal dynamics of plant phenolics. This research paves the way for improved global monitoring of ecosystem functioning, as well as the pattern of phenolics across forested landscapes and trees' potential ‘chemical’ defences against herbivory and other environmental stressors
Thickness-dependent mechanical properties of epitaxial PMN-PT thin films studied by Nano-indentation
No full textThis study examines the thickness-dependent structural and mechanical properties of epitaxial [Pb(Mg1/3Nb2/3)O3]0.67-(PbTiO3)0.33 thin films, a high-performance piezoelectric material, deposited on (001)-oriented SrTiO3 substrates with a 100 nm SrRuO3 bottom electrode layer and a 25 nm Pb(Zr0.5Ti0.5)O3 interfacial layer. Structural characterization confirms phase-pure, (001)-oriented PMN-PT films with very slight in-plane tensile strain. The out-of-plane lattice constant evolves with thickness in the range of 300–1000 nm, shifting from values below the bulk value in thinner films to the bulk value for the thickest film. This indicates strain relaxation and defect accumulation. The XRD analysis indicates a transition from a tetragonal to a more bulk-like, rhombohedral lattice symmetry for the thickest PMN-PT layer, which is ascribed to the strain relaxation. Nanoindentation results show that the hardness and elastic modulus exceed those of bulk values, with the thickest film (1000 nm) standing out with the highest modulus (217 ± 17.7 GPa) and hardness (12.04 ± 0.84 GPa) values. This is attributed to the rhombohedral lattice symmetry for this sample. The observed correlation between deeper pop-in events and PMN-PT film thickness signify the strong effect of strain relaxation and structural defects on mechanical failure mechanisms. These findings highlight the potential to optimize mechanical response of PMN-PT thin films through thickness control, paving the way for advanced applications in piezoelectric devices.</p
Controlling the reflection and emission of light via photonic crystals and quasicrystals
No full textLight is essential for most forms of life on our planet. It has interesting properties: our hands can move objects like stones, but light cannot just be grabbed and placed somewhere else. Instead, to get light at a particular spot, you need to steer it in that direction (e.g., via reflection) or produce it at that spot (i.e., via emission).Photonic crystals and quasicrystals are periodic and quasiperiodic structures designed to control light. To achieve this control, they exploit the wave nature of light, namely by using constructive and destructive interference. Possibly counterintuitively, despite being made from transparent materials, the control of light that these structures offer is very strong.In this PhD thesis, I explore the control of light by photonic crystals and quasicrystals in an experimental setting with the goal of finding new ways to control light. We manufacture the photonic crystals and quasicrystals ourselves using silicon lithography. To study their optical properties, we develop and modernize complex optical setups. These include custom-built angle-resolved reflection and time-resolved emission setups upgraded using new objectives and detectors. Our reflectivity and emission setups provide large datasets with detailed information about how light interacts with these photonic structures. Every experimental chapter compares experimental data with theoretical calculations and numerical simulations computed using open-source simulation packages. The agreement between experiment and theory is often excellent, and from the discrepancies, we learn about the differences between theoretical and experimental nanostructures. More specifically on the reflectivity, we extract the bands of 2D photonic crystals in the plane of periodicity, find new and exciting properties of 2D photonic quasicrystals, study a backward propagating surface defect wave on a 3D photonic band gap crystal, and observe a band-gap-like reflectivity on a 3D photonic crystal outside the band gap. For emission, we calculate the radiative local density of states to model decay curves of quantum emitters in photonic crystals, and study spontaneous emission in 3D photonic band gap crystals. Overall, our results form an up-to-date basis for the control of light by photonic crystals and quasicrystals
