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Responsible mission governance: An integrative framework and research agenda
No full textGovernance lies at the heart of instigating, steering, and creating the conditions for mission-oriented transitions that potentially help resolve some of our grand societal challenges. In doing so, policymakers will need to navigate both epistemic and normative considerations to develop, implement, and evaluate missions responsibly. A number of scholars have therefore expressed the need for a better conceptualization of responsible mission governance as a procedural approach, particularly with the aim of coping with the complexity, uncertainty, and contestation that render these wicked problems intractable. In this paper we develop an integrative framework for responsible mission governance by taking wickedness dimensions as our entry point. Accordingly, we argue that responsible mission governance should integrate various complementary governance responsibilities (e.g., reflexivity) and modes (e.g., reflexive governance) that potentially improve the effectiveness and desirability of missions.Values Technology and Innovatio
Design Study on the Feasibility of a Self-closing Flood Barrier: A Case Study of the City of Arcen, Limburg
No full textFlood risks and its consequences become more and more challenging and are demanding for the currently present dike systems and hydraulic structures in the Netherlands. This automatically raises the question for the possibility of adjustable temporary deployable flood defences that work autonomously. Nowadays it is more likely that a standard earthen dike will not be possible everywhere, due to site-specific characteristics such as available space or protected townscape. At these specific locations, a self-closing flood barrier can offer a solution, in view of minimally affecting the spatial quality with a reliable solution. The goal of this design study is to gain insight in the feasibility of applying a self-closing flood barrier in areas where spatial quality plays an important role and where the hydraulic boundary conditions demand for heavier structures. With the increase of densely built areas nowadays, the concept of an autonomously closing barrier is promising and an interesting alternative to consider.In this thesis the objective is to develop a customised design of an adaptive self-closing flood barrier in the upper river region of the Netherlands. The city of Arcen in this case study is characterised by its cultural-historical values and its strong connection to the Meuse. This makes it difficult to construct conventional earthen dikes.For the design purpose software with statistical data such as Hydra-NL is used to provide site characteristics, hydraulic and geotechnical boundary conditions and literature for information on currently applied barrier types and drive mechanisms. Furthermore, the design process has been completed with the help of the Design Guide Hydraulic Structures of Rijkswaterstaat and the Eurocode, from which a design originated in which stability and strength requirements have been met. The design resulted in a floating flat barrier of steel, which does not involve a complex design and is in line with integrating the structure in the area with minimal hindrance. In the design the focus lies on the functionality and the structural integrity with an in-depth look at adaptability and integrability. The result shows that the design of a floating flat barrier is feasible as a self-closing structure in the city of Arcen. However, because of the location of the structure with the requirement of no townscape obstructing elements, a heavy support structure is needed for a design water level of 2.5 m above the ground surface. Furthermore, the applied boundary conditions leads to a large floater, even though the structure is slender. In order to develop a complete design, it is recommended to make a detailed design on the concrete foundation, to do a cost analysis on the construction and materials and investigate how a certain structure is received by the residents of Arcen. This will gain insight in areas to optimise the design furthermore.Civil Engineerin
Macrolitter budget and spatial distribution in a groyne field along the Waal river
No full textCurrent research on riverine macrolitter does not yet provide a theoretic framework on the dynamics behind its accumulation and distribution along riverbanks. In an attempt to better understand these dynamics a detailed field survey of three months was conducted in which location of macrolitter items within a single groyne field along the Waal riverbanks was tracked. The data provided insight into the daily changing patterns of spatial item distribution with respect to the waterline. Furthermore, the rates of item uptake and deposition were monitored and related to hydrologic fluctuations. Uptake was initiated by rising water levels and was generally higher when the water level increased faster. Deposition occurred continuously, despite hydrologic fluctuations. This caused the riverbank macrolitter budget to be positive during stable or dropping water levels and negative during rising water levels. Although the results show clear patterns an extended monitoring duration is required to fully understand the fate of plastic objects.Sanitary EngineeringWater Resource
Noise-robust latent vector reconstruction in ptychography using deep generative models
No full textComputational imaging is increasingly vital for a broad spectrum of applications, ranging from biological to material sciences. This includes applications where the object is known and sufficiently sparse, allowing it to be described with a reduced number of parameters. When no explicit parameterization is available, a deep generative model can be trained to represent an object in a low-dimensional latent space. In this paper, we harness this dimensionality reduction capability of autoencoders to search for the object solution within the latent space rather than the object space. We demonstrate what we believe to be a novel approach to ptychographic image reconstruction by integrating a deep generative model obtained from a pre-trained autoencoder within an automatic differentiation ptychography (ADP) framework. This approach enables the retrieval of objects from highly ill-posed diffraction patterns, offering an effective method for noise-robust latent vector reconstruction in ptychography. Moreover, the mapping into a low-dimensional latent space allows us to visualize the optimization landscape, which provides insight into the convexity and convergence behavior of the inverse problem. With this work, we aim to facilitate new applications for sparse computational imaging such as when low radiation doses or rapid reconstructions are essential.ImPhys/Coene grou
Real-time reconstruction of indoor ground surfaces in occluded environments filled with smoke based on point clouds obtained using LiDAR
No full textWith the current transition towards renewable and high-tech solutions, the world is becoming increasingly complex. Consequently, the challenges faced by firefighters also intensify. For that reason, firefighting robots are rising in popularity despite being far from perfect. An important area of improvement is the perception capabilities of those robots, given the fact that firefighting robots suffer from occluded camera views in environments filled with smoke. To overcome this challenge a LiDAR sensor may be used but experiments in this work show that even those point clouds are adversely affected by smoke. Consequently, this work presents a method for real-time reconstruction of ground surfaces in occluded environments filled with smoke. The developed method functions in ROS Noetic and merges segmented ground points, when available, with ground surfaces which are reconstructed based on information from segmented wall points. In this way, the method works even without the presence of ground points. To achieve this, a combination of established techniques from scientific literature, along with newly developed techniques were implemented. Doing so gives the robot’s operator an improved representation of the ground surface within environments filled with smoke. Ultimately the developed method may allow for autonomous navigation based on LiDAR data within environments filled with smoke. This research shows that a method consisting of techniques which tackle the independent sub-challenges arising from the use of LiDAR in indoor environments filled with smoke can effectively reconstruct the ground surfaces within those environments. Furthermore, the developed method has the potential to do so in a real-time manner.Mechanical Engineering | Vehicle Engineering | Cognitive Robotic
Reducing journey times for en-route charging using V2X communication
No full textThis thesis project explores how V2X communication between electric vehicles (EV) and charging stations can be used to reduce en-route charging times. This is done using standardized V2X messages for EV charging, as well as proposing an extension to these messages to include data on the intentions of other vehicles. As individual vehicles can have significant effects on the total waiting time at EV charging stations, knowing the intentions of other vehicles will allow drivers to better avoid congested charging stations and achieve a lower total journey time. The performance of the system is evaluated using state-of-the-art traffic and communications simulators showing that using V2X can reduce journey times by 70%. Aside from demonstrating the performance using simulation the system has also been implemented on a real life test vehicle using functional V2X hardware to show that the system is viable for implementation.Electrical Engineering | Embedded System
Fuel consumption prediction for pre-departure flights using attention-based multi-modal fusion
No full textImproper fuel loading decision results in carrying excessive dead weight during flight operation, which will burden the airline operation cost and cause extra waste emission. Existing works mainly focused on the post-event fuel consumption based on flight trajectory. In this work, a novel deep learning model, called FCPNet, is proposed to achieve the fuel consumption prediction (FCP) before the flight departure. Considering the influential factors for aircraft performance, the multi-modal information sources, including the planned route, weather information, and operation details, are selected as the model input to predict fuel consumption. Correspondingly, three modules are innovatively proposed to learn embedding features from multi-modal inputs. Based on the planned route, the graph convolutional network is proposed to mine the spatial correlations in the non-Eulerian route network. Considering the grid attributes of the weather information, the ConvLSTM is applied to learn abstract representations from both the temporal and spatial dimensions, in which the three-dimensional convolution neural networks are also designed to fine-tune intermediate feature maps. The fully connected layer is also proposed to learn informative features from operation details. Finally, an attention-based fusion network is presented to generate the final embedding by considering the unique contributions of the multi-modality sources, which are further applied to predict flight fuel consumption. A binary encoding representation is proposed to formulate the FCP task as a multi-binary classification problem. The proposed model is validated on a real-world dataset, and the results demonstrate that it outperforms other baselines, i.e., achieving a 6.50% mean absolute percentage error, which can practically support the airline operation and global emission control before flight departure.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Air Transport & Operation
Bacterial chromosome organization by ParB proteins
No full textThis thesis explores the mechanisms that underlie chromosome organization in bacteria. Bacteria are considered amongst the simplest living organisms on our planet. They lack the cellular organization found in other domains of life (Archaea or Eukaryotics) and often have simpler life cycles. Over the past decade, we gained increasing knowledge pointing to the fact that bacteria allocate a lot of resources to precisely organize their genome within the cell, and to segregate two genomes after DNA replication to daughter cells.In this thesis, I investigated DNA organization and segregation systems in a model system bacterium Bacillus subtilis. I approached this feat both from the in vivo aspect – imaging in a live bacterium, and from the in vitro aspect – observing isolated proteins and DNA molecules. This holistic approach allowed me to gain deep insight into the proteins and mechanisms needed for DNA organization and segregation....BN/Cees Dekker La
Navigating complexity: agent-based simulations for climate-resilient economies
No full textAmid the Anthropocene, the escalating threat of flooding, driven by extreme rainfall and sea-level rise, challenges societies worldwide. In the last two decades, floods have impacted billions and inflicted colossal economic losses. Concurrently, the global trend towards urbanization predicts that by 2050, about 70\% of the global population will inhabit urban areas. This demographic trend, heavily influenced by agglomeration forces, further underscores the vulnerability of these urban centers, many of which are precariously situated in flood-prone areas. Given the confluence of escalating climate risks and the surge in populations settling in vulnerable zones, a pressing question emerges: How will rapidly urbanizing coastal societies adapt to intensifying flood risks in the face of escalating climate-induced shocks and changing regional economic landscapes?To address this multifaceted issue, this dissertation delves into the complex nexus between climate shocks, regional economic dynamics, and societal responses. Central to this exploration is the creation of innovative simulation tools tailored to incorporate the autonomous adaptation strategies of various actors within a regional economic framework. This thesis stands at the forefront of a new wave of computational models that encompass risk and embed resilience into complex adaptive systems.I commence by examining the current advancements and gaps in employing Agent-Based Models to unravel the dynamics of flood risk and adaptation assessments. In this exploration, I underscore the pivotal role of human actions in shaping risks and resilience within flood-prone urban settings.Building on this foundation, I introduce the Climate-Economy Regional Agent-Based (CRAB) model. The CRAB model employs an evolutionary perspective to provide a comprehensive view of the balances struck between the driving forces of economic agglomeration and the counteracting pressures of climate hazards. It focuses on the decision-making of heterogeneous agents, representing households and firms, as they navigate the choice of relocation between safer inland regions and hazard-exposed coastal zones.Venturing further, I enhance the CRAB model to embody autonomous household adaptation behaviors, drawing from empirical data. Here, I challenge the traditional reliance on rational agents in sustainability models, unveiling a notable adaptation deficit when juxtaposed against boundedly-rational choices gleaned from real-world surveys. This nuanced exploration uncovers how varied adaptive capacities can potentially accentuate inequality and impede resilience.Subsequently, I include in the CRAB model a layered risk strategy that encompasses an array of climate change adaptation measures. This refined model, enriched by extensive behavioral and flood data, bridges existing gaps in the current understanding of feedback loops and cascading effects triggered by flood shocks within a socio-economic system of boundedly-rational agents.In conclusion, this dissertation pioneers a unique trajectory in understanding societal responses to the specter of flooding, offering invaluable insights and frameworks for devising future climate-resilient strategies.Policy Analysi
Oil Spaces: Extended Urbanization from Sea to Land
No full textFlows of petroleum have shaped buildings, cities and landscape around the world on sea and land. This paper shows how industrially drilled petroleum and its refined products have played a major role in transforming the built environment over the last century and a half, in ways that are often not visible or recognized. Understanding the multiple links between refineries, gas stations, headquarters or cities around the world, and acknowledging the path dependencies that these flows have created, provides a concrete example for extended urbanization and its role in fueling ways of life and visions of progress, modernity, and disaster.Through detailed international case studies the paper considers petroleum’s role in the development of the built environment and the imagination. It explores how petroleum and its infrastructure have served in shaping extended urbanization as a source of military conflict and political and economic power, inspiring efforts to create territories and reshape geographies and national boundaries. The paper explores ruptures and continuities between colonial and postcolonial frameworks through diverse case studies with diverse functions from around the world, including heritage sites.By revealing petroleum’s role in organizing and imagining space globally, this paper takes up a key task in imagining the possibilities of a post-oil future. It explores diverse contributions made by students in courses at Delft University of Technology to show visualize them.History, Form & Aesthetic