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Multiscale Extended Finite Element Method for the Simulation of Fractured Geological Formations
No full textIn the prevailing context of the 21st century, characterized by a predominant reliance on oil and gas, or in the promising future where green energy shapes a human society committed to net-zero emissions, the role of underground fractured formations in energy production and storage remains pivotal and irreplaceable. Geological faults typically act as non-permeable sealing boundaries for reservoirs used in storage, including those for hydrogen and carbon dioxide. In contrast, artificial fractures can serve as highly permeable conduits for fluid flow into wellbores, particularly in applications such as enhanced geothermal reservoirs. In the past decade, the hazardous consequences of failing to predict the geomechanics behaviors of fractured formations have led to a pronounced focus on developing simulation strategies that are both accurate and efficient for fractured formations.It is challenging to understand formations riddled with fractures. From a computational perspective, the complex fracture networks typically demand a way finer unstructured grid. However, using such an unstructured grid is impractical for real-world applications due to their high computational load. Conversely, coarser grids paired with strategies such as homogenization could result in loss of crucial details. Heterogeneous properties of geological formations that span on large length sizes require the simulation strategies to be scalable, in order to be relevant.This thesis proposes a novel approach named as multiscale extended finite element method (MS-XFEM) to tackle these challenges. The challenges related to discretization are resolved by applying the extended finite element method (XFEM) which allows for the use of structured grids. This simplified mesh, however, leads to an augmented matrix size due to extra degrees of freedom (DOFs) introduced by enrichments. A multiscale approach is therefore combined with XFEM. The computational process is operated on the larger yet sparser coarse grids and then the coarse scale mesh solutions are interpolated back to fine scale mesh. The novelty of this work is to involve the fractures into basis functions only, thus the coarse scale system is constructed based on a finite element method. More importantly, this construction of basis functions is fully algebraic and can be updated locally and adaptively for the simulation of propagating fractures.This method has been implemented and tested to prove its efficiency and accuracy. All tests results prove the good qualities of solutions computed from MS-XFEM when compared to fine scale XFEM solutions. Basis functions are constructed successfully with the algebraic method. These tests reveal the potential of the MS-XFEM in simulating real-world subsurface fractured formations.Applied Mechanic
From Scroll to Soul: Design Features of Social Media Platforms and Their Impact on Users' Mental Well-Being
No full textThe prevalence of mental health issues among adolescents and young adults is increasing, with social media usage identified as a potential contributing factor. As technology becomes more integral to daily life, the design decisions of social media platforms emerge as significant determinants of users' mental well-being.Despite awareness of social media's general adverse effects, there is a gap in understanding the specific impact of different design features. Academic literature identifies features like likes and direct messaging as having nuanced effects on mental well-being, but lacks a comprehensive overview for developers to reference. This thesis seeks to bridge this gap, focusing on design features and their psychological impacts to propose design interventions for enhancing mental well-being.Employing Value Sensitive Design (VSD) as an analytical framework, this study is the first to apply VSD to social media in the context of mental well-being. It involves a tripartite methodology — conceptual, empirical, and technical investigations — to identify significant design features and values related to mental well-being on social media platforms. A novel social media platform, Dime, designed with mental well-being in mind, serves as a case study for evaluating these features and proposing design requirements.The study identifies 8 key design features affecting mental well-being and outlines 13 values divided into higher and lower levels, facilitating focus on critical values for desired outcomes. It explores value interrelationships and conflicts, particularly noting indirect tensions between values like authenticity and connection, and between personalization, control, and autonomy.Proposed design interventions aim to resolve identified value conflicts, enhancing authenticity to support connection and enhancing personalization and control to support autonomy.Management of Technology (MoT
Who are the value transformers, value co-operators and value gatekeepers? New routes to value preservation in a sufficiency-based circular economy
No full textValue preservation is key for the transition from a linear economy to a sufficiency-based circular economy. However, to keep the value of products and materials at the highest level possible over time, different actors such as businesses, designers, consumers, and policymakers must know when value is reduced during a product's lifetime, and how to capture and preserve this value. This study results in a comprehensive mapping of factors with a negative impact on the perceived value of products from a consumer's perspective and suggests new routes to value preservation, as a way of turning the negative factors into positive changes. Next, the paper presents a conceptual model for value preservation. The model identifies new key actors: value transformers (product developers), value co-operators (consumers), value gatekeepers (businesses), and value accountants (policymakers) and suggests important changes to their linear practices, which are needed for the sufficiency-based circular economy paradigm to flourish.Responsible Marketing and Consumer Behavio
Automating the Insurance Sector - Assessing Technology Acceptance of Emerging Technology
No full textEmerging technologies like artificial intelligence, big data analytics, blockchain, and the internet of things offer interesting opportunities to automate business processes. With the potential to streamline operations like claims management, underwriting, and customer service, these advancements appear to be especially promising for insurance companies. Nevertheless, digital transformation does not come without its barriers, such as IT-system legacies, regulatory demands, and business issues. One challenge for digital transformation is the rejection of innovations. Insurers, therefore, need their internal stakeholders to accept and adapt to technological change.This study investigates this barrier to a successful digital transformation of the insurance industry. Following a literature review on innovations in this realm and technology acceptance, this thesis aims to identify factors influencing the behavioral intention to use technologies within this context....Management of Technology (MoT
Analyzing coastal erosion and sedimentation using Sentinel-1 SAR change detection: An application on the Volta Delta, Ghana
No full textGhana's coastline has been facing erosion and sedimentation phenomena for several decades, resulting in a serious threat to life and property considering that major urban settlements are located on the coast. In this region, there has been a lack of emphasis on comprehensive, large-scale investigations into coastal changes: prior research has predominantly centered on site-specific assessments. These studies have revealed alarming erosion rates, with reports indicating that nearly ten meters are lost annually. The use of high-resolution remotely sensed data can be a consistent support in regions where physical or economic obstacles interfere with collecting in situ information. In particular, the use of continuous all-weather SAR data may facilitate the evaluation of erosion and sedimentation phenomena in coastal areas. In this paper, we apply SAR data over a time period between 2017 and 2021. Sentinel-1 data are pre-processed using the Google Earth Engine platform, and a dedicated algorithm is then applied to identify and quantify erosion and sedimentation processes. Optical images are used as a reference for detecting the location of two areas where consistent sedimentation and erosion phenomena occurred in the considered four years. The results demonstrate that SAR backscattering variations over time offer a reliable method for monitoring coastal changes. This approach enables the identification of the type of phenomena occurring - sedimentation or erosion -, and allows for the quantification of their intensity and dimensions over time. The method can be worldwide applied once the appropriate thresholds are evaluated and help in predictive studies and environmental planning.Mathematical Geodesy and Positionin
Product-ProtoNet: A simple architecture for classifying supermarket products, using just a few example images
No full textAirlab, a collaboration between TU Delft and Ahold Delhaize, is developing Albert, a robot tailored to work in a complex supermarket environment. Key to Albert is a product detection and classification module that tells it what products to grasp and where they are located in a shelf. Albert’s existing YOLO‑based product detector a significant issue: Adding new products without re‑training the whole model is impossible. Especially in a dynamic supermarket environment with an ever‑changing stock, the latter is a major issue.This problem will be the main focus of this paper and is addressed through few‑shot learning, which predicts similarity between query and target products. This simplifies adding new products to just supplying new target images. Few‑shot learning also requires significantly less data to train on. In supermarkets with 300.000 different products, requiring only a few images per product is a major advantage. For this reason, this paper aims to deploy a few‑shot model to classify products as either the target class or non‑target class for Albert’s picking task and defines the following research question: “What few‑shot classifier can identify products in a supermarket environment, is able to detect non‑target classes, and meets the requirements of deployment on a robotic platform like Albert best?“This paper first analyses the potential of using TRIDENT and P>M>F, two state‑of‑the‑art few‑shot models, for deployment on Albert, and evaluates them on the requirements of this paper. P>M>F performs better on all requirements, which makes it the preferred model for Albert. However to work well, it still requires adjustments. Its inference time is still too high to work on Albert and it cannot classify query images as not the target product.For this reason, this paper uses P>M>F’s two key ideas to construct Product‑ProtoNet, a new Albert‑suitable few‑shot model: 1) Using a good pre‑trained feature extractor; and 2) Comparing query images to a set of classes and matching only to the likeliest. P>M>F uses a ProtoNet model for classification that essentially does this; Like ProtoNet, Product‑ProtoNet constructs class prototypes from one or multiple examples of class images. Product‑ProtoNet then uses a sigmoid classifier to predict if query images have the same class as those prototypes. It compares query images to a set of similar class prototypes(helper prototypes) and classifies it as the likeliest. Product‑ProtoNet uses a ViT pre‑trained with DINO to extract image features. To bring down inference time, Product‑ProtoNet computes product prototypes before deployment.With an accuracy of 99.1% on product classes seen during training and 99.8% on novel classes in a realistic supermarket setting, a low inference time of 2.89 ms and a memory usage lower than 4GB, Product‑ProtoNet is the only model that passes all requirements of this paper. When deployed on Albert Product‑ProtoNet successfully guides Albert to the right product in 97% of attempts. This makes Product‑ProtoNet the only few‑shot classifier that can identify products in a supermarket environment, is able to detect non‑target classes, and meets the requirements of deployment on a robotic platform like Albert.Mechanical Engineering | Vehicle Engineering | Cognitive Robotic
Strain engineering of nonlinear nanoresonators from hardening to softening
No full textAlthough strain engineering and soft-clamping techniques for attaining high Q-factors in nanoresonators have received much attention, their impact on nonlinear dynamics is not fully understood. In this study, we show that nonlinearity of high-Q Si3N4 nanomechanical string resonators can be substantially tuned by support design. Through careful engineering of support geometries, we control both stress and mechanical nonlinearities, effectively tuning nonlinear stiffness of two orders of magnitude. Our approach also allows control over the sign of the Duffing constant resulting in nonlinear softening of the mechanical mode that conventionally exhibits hardening behavior. We elucidate the influence of support design on the magnitude and trend of the nonlinearity using both analytical and finite element-based reduced-order models that validate our experimental findings. Our work provides evidence of the role of soft-clamping on the nonlinear dynamic response of nanoresonators, offering an alternative pathway for nullifying or enhancing nonlinearity in a reproducible and passive manner.Dynamics of Micro and Nano SystemsQN/Otte LabComputational Design and Mechanic
Enhancing performance of polar InGaN-based thin film solar cells through intrinsic layer impact optimization: Numerical modeling
No full textThe paper deals with the conception and feasibility of the device structure based on the optimized PIN-(In, Ga)N homojunction solar cells. A new and efficient model combining the most realistic ones considering the impacts of band gap narrowing, collection efficiency, Shockley-Read-Hall recombination, and interface polarization is proposed to examine the solar cells' performance numerically. The functioning processes of n-In0.42Ga0.58N/i-(In, Ga)N/p-In0.42Ga0.58N solar cells at room temperature were investigated by calculating their characteristics for the AM1.5D, AM1.5G, and AM0 American Society for Testing and Materials experimental data. Our results show that the indium content, thickness, and defect density of the intrinsic layer strongly influence the characteristics of the InGaN solar cells. As the In-mole fraction increases, Voc, FF and efficiency diminish to reach an independent regime for high In-content. A higher-quality 2μm−In0.43Ga0.57N for 1014cm−3 defect concentration can exhibit as high an efficiency as ≅11.3%, dropping to ≅4.12% for 1016cm−3 one.ImPhys/Esmaeil Zadeh groupDynamics of Micro and Nano System
Printed spark ablation nanoparticle films for microelectronic applications
No full textThis thesis is about the application and characterisation of spark ablation generated nanoparticles in microelectronics. It opens in chapter 1 with a general motivation of the need for advanced materials and for nanotechnology in particular. It then describes what nanoparticles are and why they are promising materials. Some of their advantages are a high chemical reactivity, a high specific surface area, and the display of quantum effects at that scale. The chapter ends by presenting the research questions and giving the thesis structure.Chapter 2 provides a technological background for the rest of the thesis based. It describes several applications of nanoparticles within microelectronics not researched during this PhD project: as die-attach materials, chemical sensors, or catalysts. It continues with the description and discussion of several competing nanoparticle synthesis methods and goes in-depth on the theory of spark ablation generation. It describes the effects of various parameters that govern the mass generation rate, particle size, and composition. This theory is important to be able to interpret the results in the other chapters. Impaction deposition is then described in this chapter since it is the method of printing all samples in this thesis. It explains how this method prints dots or lines of nanoparticles, that they have a Gaussian cross-section profile, and how specific deposition parameters affect the deposit. Lastly, the chapter gives a detailed description of the spark ablation synthesis and deposition equipment with which all the experiments in this thesis are performed. The generator, components, gasses, pressures, and materials are all described with diagrams and specifications. Typical synthesis and deposition settings for the generation of Au nanoparticle deposits are given (1 kV, 5 mA, 1.5 L min.¡1 Ar or N2 and 1mmnozzle distance).The first chapter with results, chapter 3, presents a method to measure the mass deposition rate of the nanoparticle printer. Measuring the mass of microgram scale deposits is challenging due to the high sensitivity required for an accurate measurement. Balances are sensitive to changes in pressure, temperature or humidity that can already give too big errors. One solution already applied in thin film deposition methods is the use of quartz crystal microbalances (QCMs). Their resonance frequency is dependent on their mass, and thus, we can use the frequency shift during deposition to measure a mass change. The Sauerbrey equation that is used for that conversion must be valid, so a special method was developed to comply to all of its conditions. A concentric circular pattern of Au nanoparticles was printed on 10 MHz QCMs to measure the mass deposition rate. It was found that the deposition rate scales linearly with the generation current of the spark, as expected from theory, but also showing the losses in the system are either constant or scale linearly too. The film density was surprisingly constant for all tested synthesis and deposition settings, at 15.95 g cm¡3, or a porosity of £p Æ 0.18. The density was compared to models presented in literature, and it is proposed that the impaction energy likely compacts the porous structure during deposition until this density is reached. The QCM method can be applied for process monitoring using commercially available equipment and open-source software.The first applications of printed conducting nanoparticle films are discussed in chapter 4. It describes the conductive properties of such films and the effect of annealing on their conductivity. It was found that an untreated Au film conducts 22 times worse than bulk Au. Several applications are then discussed. Here it was demonstrated that printed Au nanoparticle lines can be applied as interconnect materials as an alternative to wire bonding. Next, a method was presented to miniaturize the deposits even further by using lithography and lift-off. This reached a line width at the minimum of the lithography equipment available, at 1.2 ¹m, without significantly changing the nanostructure.Chapter 5 deals with the application of spark ablation generated nanoparticles as thermoelectric materials. It describes in detail the synthesis and characterization of Bi2Te3 nanoparticles and their thermoelectric properties. The main finding was that the thermal conductivity was drastically lower than bulk Bi2Te3 and comparable to the state of the art for Bi2Te3 nanostructured materials, reaching a minimum of 0.2Wm¡1 K¡1 at room temperature. Unfortunately, the electrical conductivity was reduced by at least a factor 1000, easily undoing any efficiency gains from reduced thermal conductivity. Suggestions are given to possibly improve this trade-off. Additionally, this chapter shows how quickly nanostructured materials like the ones in this thesis oxidize after synthesis. From the moment the sample is printed, it gains mass and loses conductivity, so this must be counteracted if a non-noble metal is to be applied.The final chapter before the conclusions, chapter 6, showcases another application of printed nanoparticles: as UV-sensing material. It shows the results obtained using ZnO nanoparticles to create a UV sensor that is insensitive to visible light. The nanoparticles were deposited over electrodes to fabricate a resistor that has two orders of magnitude electrical resistance reduction when exposed to 265 nm UV light. The response was slow, with 79 seconds to reach 90% of the maximum response and 82 seconds to get back to 10% again. This is attributed to the adsorption and desorption of oxygen under the influence of UV light and can be prevented by packaging the sensor. The contact behaviour between the metal electrodes and ZnO nanoparticles proved to be too unpredictable to reliably create a Schottky diode, which would have had a higher response. This dissertation ends with a list of the conclusions, the answers to the research questions, and finally, some suggestions for future work. Electronic Components, Technology and Material
The assessment of flood mitigation measures applied in Cartagena de Indias: A case study approach about investigating types of flood mitigation measures in Cartagena de Indias
No full textUrban areas of coastal cities are increasingly susceptible to the consequences of climate change. In particular, the threat of increasing floods due to sea level rise and heavier rainfall is growing. Cartagena de Indias in Colombia is such a coastal city, where flooding is a significant issue, with floods becoming more frequent in recent decades. Arcadis, together with the ConAgua consortium, is currently investigating and designing mitigation strategies for the city’s water-related issues. The thesis focuses on defining and quantifying the sources of urban flood problems and assessing the impact of potential mitigation measures for reducing these flooding problems.The study consists of four parts:1. Identifying the main causes of floods using a data analysis;2. Quantifying these findings with a numerical D-Hydro model;3. Investigating suitable kind of mitigation measures and quantifying the impact of the best feasible mitigation options;4. Evaluating the investigated mitigation options based on several criteria with the help of a multicriteria analysis.Parts 1 and 2 focus on understanding the system. Parts 3 and 4 of the study focus on finding the best option to reduce floods.The data analysis allows the development of a system description identifying the main causes of flooding. The analysis reveals that the limited capacity of the drainage system, high topographic variations, and extreme rainfall are the main causes of flooding in Cartagena. Extreme rainfall flows quickly from steep upstream areas to milder slope lower-lying areas, particularly those at the edge of the Ciénaga de la Virgen. It is hypothesised that downstream water level plays a role in the accumulation of runoff water, thereby influencing the frequency and intensity of floods in the neighbourhoods at the southern edge of the Ciénaga de la Virgen, especially with a relative sea level increase of approximately half a meter factored in. This hypothesis is checked by quantifying the impact of different scenarios with a numerical model.A numerical D-Hydro model is used to quantify the impact of different meteorological conditions and downstream water levels on floods. The model’s simulation results show that rainfall intensity is a more dominant factor in flood generation than downstream water levels. Even with a return period of two years, rainfall causes significant flooding of almost 25% in the study area. The model also indicates an increasing influence of tidal conditions due to relative sea level rise. Still, the increased influence is mainly visible in the borders of the Ciénaga de la Virgen with minimal residential impact. These conclusions highlight the need for mitigation efforts to focus primarily on improving the areas influenced by the rainfall, especially for short return period rainfall events.Various flood mitigation measures are considered for the southern border of the Ciénaga de la Virgen to reduce floods caused by the dominant intense rainfall. Wetland creation and evaporation measures are ruled out due to the dominant influence of rainfall-induced floods and the inability to prevent floods caused by extreme rainfall events respectively. After investigating the scale required, considering feasibility, the three types of measures that are converted into mitigation options are:• Mitigation Option 1: Increasing channel dimensions,• Mitigation Option 2: Increasing infiltration,• Mitigation Option 3: Constructing retention areas.These mitigation options are assessed for their impact on reducing flooded areas and flood levels. The three mitigation options are evaluated to recommend the best-preferred mitigation design. This evaluation employs a Multi-Criteria Analysis (MCA)...Civil Engineerin
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