SEAMLESS-WAVE is a developing “SoftwarE infrAstructure for Multi-purpose fLood modElling at variouS scaleS” based on "WAVElets" and their versatile properties. The vision behind SEAMLESS-WAVE is to produce an intelligent and holistic modelling framework, which can drastically reduce iterations in building and testing for an optimal model setting, and in controlling the propagation of model-error due to scaling effects and of uncertainty due statistical inputs.

View the Project on GitHub ci1xgk/Fellowship_Webpage

Food-pedestrian simulator

The flood-pedestrian simulator is implementend within FLAMEGPU, a computational platform for the simulation of multiple agent interactions on CUDA Cores for parallel processing on Graphical Processing Units (GPUs). It involves dynamic and bidirectional coupling across pedestrian-agents and flood-agents (Shirvani et al. 2021).

Pedestrian-agents are continuous so they can change their coordinates and their population. Their walking patterns are based on the social force model that accounts for the movements of each individual and by modelling the interaction between individuals to derive forces that avoid collisions with neighbours. The motion of pedestrian-agents is also governed by a global path planning model represented by a grid of discrete agents, navigation-agents, forming a navigation map. The navigation map encodes the features of the walkable area necessary for the individuals’ way-finding decision, e.g. terrain obstacles and walls that need to be avoided as the individuals navigate and vector fields providing navigation to key destinations. Multiple pedestrian agents can be present at the same time over one mutual navigation agent as they are of continuous type (Shirvani et al. 2021).

Flood-agents are discrete agents that are coincident with the grid of navigation agents. Each flood-agent stores its position, terrain properties in terms of height and Manning’s roughness parameter, and the states of the floodwater variables in terms of water depth and velocity components. A non-sequential computation for a hydrodynamic model is used to allow all flood-agents to dynamically updates the states of floodwater variables at the same time. The information stored in the pedestrian-agents and in the flood-agents is dynamically passed between them through the navigation-agents that act as shared communication interfaces (see Section 2.5 in Shirvani et al. 2021).

Verification of the simualtor’s two-way coupling capability

The two-way coupling ability of the simulator has been evaluated for a hypothetical case study of a flooded shopping centre (Shirvani et al. 2021), for an evacuation scenario of 1000 pedestrians to a safe emergency exit, with with/without an advanced flood warning; and an intervention scenario to find out the miminum responder pedestrians and height of a flood-fighting barrier for safe and robust deployment.

In addition to the demonstration provided in Shirvani et al. (2021), simulation demos are provided in this video for five modelling cases. ‘Model 1’ to ‘Model 3’ simulate people evacuating during a flood; whereas, ‘Model 4’ and ‘Model 5’ simulate people intervening to deploy a flood-fighting barrier upstream of the emergency exit. More specifically:

The flood-pedestrian simulator has been augmented with more sophisticated behaviour rules for governing pedestrians’ variable walking speeds and instability states in floodwater, and considering age groups, gender and body sizes (Shirvani et al 2020).

Work is underway to explore the perforamce of the simulator for a real-case study, of a flood-prone and congested area in Sheffield, and to enable it with a dynamic 4D visulaisation tool to stimulate more effective engagement with the general public (Festival of the Mind, 2020).

Accessing the simualtor

The flood-pedestrian simualtor has been ported to the compute facility of DAFNI, where it can be used from a user-friendly graphical interface and informed by a detailed user guide. We are very grateful for the portability support provided by DAFNI to make the simulator available to the wider community and easy-to-use by non-experts. The project of porting the simulator to DAFNI was smooth, timely and stress-free. Also, upon project completion, DAFNI provided us with a demonstration of how the simulator can be run from their user-friendly graphical interface. Thanks DAFNI!

A more detailed run guide is also available for those wishing to setup and run the simualtor on a personal computer for new case studies.