This student project investigates numerical simulation of wave propagation in simplified urban environments using the shallow water equations. The work focuses on developing a Runge-Kutta
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Category: Gothenburg
Gothenburg. Optimizing investments in and operation of Positive Energy Districts for emissions reductions
In recent years there has been an increased interest in finding cost efficient strategies to reduce the emissions of the building stock, in the effort
Read moreGothenburg. Making Sense of Lung Function Variability with Hidden Markov Models
Respiratory diseases like asthma and chronic obstructive pulmonary disease (COPD) lowers quality of life and increases mortality. Much of this burden comes from exacerbations, acute
Read moreGothenburg: Business-oriented vehicle routing for electric trucks
In order to reduce the climate impact of the transportation industry, fossil fuel-driven trucks are being replaced by more sustainable alternatives, like electric trucks. Electric
Read moreGothenburg: Simulation-based inference for complex models
Most models for real-life applications, e.g., stochastic models for systems biology, finance and population dynamics, have an intractable likelihood-function, that is, the likelihood is not
Read moreGothenburg: Efficient evaluation of micro-mechanical paper models
The paper and pulping industries account for a substantial amount of global industrial energy use, which means that small improvements in the process result in
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Heidelberg Laureate Forum
My name is Julia Jansson and I am a PhD student at the division of Applied Mathematics and Statistics at Chalmers University of Technology. This
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GENERATION OF RANDOM SURFACES BY STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS
Imagine a moving biological cell as recorded and published in a movie by Johns Hopkins Medicineor an ice crystal in a cloud that starts to
Read moreDiscretization by quantization
My name is Erik Jansson and I am a PhD student in Professor Klas Modin’s group at the Department of Mathematical Sciences at Chalmers University
Read moreSimulation-based inference for complex models
Most models for real-life applications, e.g., stochastic models for systems biology, finance and population dynamics, have an intractable likelihood-function, that is, the likelihood is not
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