Recent Submissions 

  1. Applying Machine Learning Methods to the Assessment of Tropical Cyclone Impacts 

    Lüthi, Samuel (2019)
    Tropical cyclones are among the most disastrous natural catastrophes worldwide and pose a major threat to societies in the affected regions. Thus, governments and private companies have strong interests in improving the understanding of impacts from tropical cyclones in order to better prepare societies for possible disastrous impacts. This led to the development of natural catastrophe models that allow the quantification of expected ...
    Master Thesis
  2. On the Approximation of Rough Functions with Artificial Neural Networks 

    De Ryck, Tim (2020)
    Deep neural networks and the ENO procedure are both efficient frameworks for approximating rough functions. We prove that at any order, the stencil shifts of the ENO and ENO-SR interpolation procedures can be exactly obtained using a deep ReLU neural network. In addition, we construct and provide error bounds for ReLU neural networks that directly approximate the output of the ENO and ENO- SR interpolation procedures. This surprising fact ...
    Master Thesis
  3. Channels with a Helper 

    Marti, Gian (2019)
    Master Thesis
  4. Double-pump x-ray probe experiments on the charge density wave-compound K0.3MoO3 

    Neugebauer, Martin J. (2015)
    The ultrafast structural dynamics of the periodic lattice distortion in K0.3MoO3 asso- ciated with its CDW ground state were reported recently. The dynamics show the behavior of a displacively excited coherent phonon for pump fluences significantly below 1 mJ/cm2 . Above 2mJ/cm2 a transient recovery of the periodic lattice distortion after a delay time of 0.35 ps occurs. The system is successfully modeled by a high-symmetry potential ...
    Master Thesis
  5. Industrial Investment and Operation of Energy Storage for Mitigating the Risk of Power Outage 

    Lonergan, Katherine Emma (2019)
    The addition of decentralised, renewable energy generation to the electric power system helps reduce the overall carbon intensity of electricity; however, the variability in energy supply also creates operational challenges within the electricity network and can increase the risk of power outage if not properly managed. Electrical energy storage has the potential to provide back-up supply as well as other electricity services. Here, the ...
    Master Thesis
  6. Profiling Symbolic Execution 

    Arquint, Linard (2019)
    Master Thesis
  7. Multiple Address Spaces in a Distributed Capability System 

    Hossle, Nora (2019)
    Master Thesis
  8. Sketch-Based 4D Prototyping for Smoke Simulations 

    Huang, Xingchang (2019)
    Master Thesis
  9. Construction Scheduling: Potential for improvement using productivity data and new technologies 

    Mendoza Salinas, Paola A. (2019)
    A construction schedule is one of the most essential documents to manage and measure a project’s performance. Its completeness and correctness have a direct impact on the project’s success. However, the traditional methodology to create the schedules presents several flaws; such that statistics show that more than 75% of the projects worldwide do not finish in the duration predicted by their original plan. This dissertation researched ...
    Master Thesis
  10. Optimization of heat extraction within sedimentary reservoirs for CO2 Plume Geothermal (CPG) electricity generation 

    Ravilov, Marat (2019)
    The primary goal of the present work is evaluation and comparison of vertical and horizontal well placements and their impact on the power output of a CPG (CO2 Plume Geothermal) system. Performances of vertical and horizontal wells are evaluated for a repeated five-spot pattern. Six numerical models were developed in MOOSE (Multiphysics Object Oriented Simulation Environment), tested and compared against each other and a benchmark study. ...
    Master Thesis
  11. Learning-based Approximate Model Predictive Control with Guarantees 

    Nubert, Julian (2019)
    In this work, we present a model predictive control (MPC) method for applications in complex constrained physical systems. We base our work on a novel robust model predictive control (RMPC) scheme guaranteeing constraint satisfaction and recursive feasibility under disturbances. The used scheme keeps the computational complexity comparable to the nominal case. We adopt this approach and extend it by practical useful additions, such as ...
    Master Thesis
  12. Shaping species richness: ecological filtering in native and non-native plants along elevation gradients in the Swiss Alps 

    Righetti, Damiano (2012)
    Ecological filtering, imposed by climatic constraints or competitive interactions, might shape distribution patterns of native and non-native plants differently along elevation gradients. However, patterns of species richness that might reflect these processes have rarely been compared between native and non-native plants. All angiosperms and gymnosperms were recorded along and away from three road-corridors that vertically extended >1100 ...
    Master Thesis
  13. Optimizing the size of a fully renewable power system to meet energy demand 

    van Brummen, Anna (2019)
    In electricity grids, demand and generation must be balanced at all times. Modern electricity is primarily generated by baseload power sources, such as nuclear and coal, and quickly dispatchable sources, such as gas fired power plants. As anthropogenic total CO2 emissions already make up almost 75% of the atmosphere's total carbon content, governments are increasingly implementing renewable energy mandates. Therefore future electricity ...
    Master Thesis
  14. The Impact of Self-consumption Regulation on Individual and Community Solar PV Adoption in Switzerland: an Agent-Based Model 

    Mehta, Prakhar (2019)
    Historically, Swiss solar PV adoption has been slow but Switzerland's Energy Strategy 2050 requires electricity production from renewables to increase 4.5 times by 2035 compared to 2017. The new Energy Act in Switzerland came into force in January 2018 with investment subsidies for practically all PV system sizes and very encouraging provisions for community solar PV systems – clearer financial and legal structures under the `Zusammenschluss ...
    Master Thesis
  15. End-to-End Collision Avoidance from Depth Input with Memory-based Deep Reinforcement Learning 

    Kang, Dongho (2019)
    The main goal of this work is learning a local path planning policy for mobile robots from a single depth camera input. We formulate the end-to-end local plan- ning problem as a Partially Observable Markov Decision Process and solve it using a Deep Reinforcement Learning algorithm. The main challenges of this setting comes from 1) the short-sightedness of reaction-based planners, and 2) the limited field-of-view of depth camera that ...
    Master Thesis
  16. Linear Induction Motor (LIM) for Hyperloop Pod Prototypes 

    Timperio, Christopher (2018)
    Mobility is one of the main dilemmas facing a sustainable, clean-energy future. How can people and cargo be transported over long distances, without expending large amounts of fossil fuel energies or producing a large carbon footprint? How can this be done quickly and efficiently? Finding a mode of transportation which is energy-efficient, inexpensive, and even offers passenger transport is the task which the Swissloop team is striving ...
    Master Thesis

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