Mitigation of urban storm water runoff through application of computational fluid dynamics
Doctoral thesis, 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.

microstructure

infiltration

Green roof

CFD

wind-driven rain

building facade.

lattice Boltzmann

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

Author

Kaj Pettersson

Chalmers, Architecture and Civil Engineering, Building Technology

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.

Potentials of using existing roofs for mitigation of storm water flooding risks in urban areas

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

Formas (2015-173), 2015-09-01 -- 2018-12-31.

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

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

City of Gothenburg, 2016-01-11 -- 2019-01-11.

Driving Forces

Sustainable development

Areas of Advance

Building Futures (2010-2018)

Subject Categories

Computational Mathematics

Oceanography, Hydrology, Water Resources

Roots

Basic sciences

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

ISBN

978-91-7905-500-4

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4967

Publisher

Chalmers

Online

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

More information

Latest update

3/23/2022