Mitigation of urban storm water runoff through application of computational fluid dynamics
Doktorsavhandling, 2021

This thesis covers computational methods for improving the ability of green roofs to mitigate storm water runoff in urban environments. Roofs with living vegetation, known as green roofs, have been used for this purpose however quantification of their ability to slow and stop rainfall runoff has not been undertaken to a large degree. In this work two different approaches are taken: i) to improve green roof performance by optimizing their location on a building facade; and ii) to optimize the design of the growth substrate by examining the impact of the porous microstructure on infiltrating flow. The approach for optimization by placement makes use of traditional computational fluid dynamics and applies a full turbulence model to an Eulerian multiphase system consisting of a steady-state wind phase and a set of transient rainfall phases. The rainfall phases are determined by droplet size and the quantity incident upon the building facade is calculated and compared to experimental results. The analysis shows that the accuracy varies widely dependent upon location upon the structure and several sources of error are discussed. The second approach makes use of the lattice Boltzmann technique to aid in the deisgn of the growth substrate. Several representative porous media are generated using monodisperse randomly packed particles and gravity-driven infiltration is tracked from an initialized standing water height above the porous subdomain. Many aspects of the flow and properties of the microstructure are analyzed and conclusions are drawn based upon such factors as interfacial area, saturation rate, capillary pressure, and pore size distribution. Guidelines are drawn to aid in the design of thin homogeneous growth substrates based upon the findings. These ideal cases are compared to simulations performed on XMT scans of real growth substrate material and some conclusions are drawn on the observed differences.

lattice Boltzmann

building facade.

infiltration

wind-driven rain

CFD

microstructure

Green roof

Opponent: Prof. Dr. Jan Carmeliet, ETH Zürich, Switzerland

Författare

Kaj Pettersson

Chalmers, Arkitektur och samhällsbyggnadsteknik, Byggnadsteknologi

Simulating wind-driven rain on building facades using Eulerian multiphase with rain phase turbulence model

Building and Environment,; Vol. 106(2016)p. 1-9

Artikel i vetenskaplig tidskrift

This thesis describes numerical approaches to aid in reducing urban flooding due to excess storm water by utilizing green roofs. The work is divided into two parts: i) optimization of the placement of a green roof for maximum impact on reducing storm water; and ii) optimization of the soil growth substrate design and composition to control water infiltration. Different techniques within computational fluid dynamics are applied to solve these problems. A continuum approach is used to solve the wind profile around and wind-driven rainfall on a building façade to predict where green roofs should be placed. A statistical approach, the lattice Boltzmann method, is used to solve water infiltration of an unsaturated soil at the microscopic scale to determine how the soil microstructure impacts the flow profile. The results are used to provide rudimentary tools to predict how different microstructures will behave under extreme rainfall conditions.

Användning av tak för att minska risken för översvämning orsakade av skyfall i urbana områden

Formas, 2015-09-01 -- 2018-12-31.

Göteborgs Stad, 2016-01-11 -- 2019-01-11.

Sintef Byggforsk, 2016-01-11 -- 2019-01-11.

Framtiden, 2016-01-11 -- 2019-01-11.

Veg Tech, 2016-01-11 -- 2019-01-11.

Drivkrafter

Hållbar utveckling

Styrkeområden

Building Futures (2010-2018)

Ämneskategorier

Beräkningsmatematik

Oceanografi, hydrologi, vattenresurser

Fundament

Grundläggande vetenskaper

Infrastruktur

C3SE (Chalmers Centre for Computational Science and Engineering)

ISBN

978-91-7905-500-4

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4967

Utgivare

Chalmers tekniska högskola

Online

Opponent: Prof. Dr. Jan Carmeliet, ETH Zürich, Switzerland

Mer information

Senast uppdaterat

2021-05-07