ABSTRACT
We propose a generative design workflow that integrates a stochastic multi-agent simulation with the intent of helping building designers reduce the risk posed by COVID-19 and future pathogens. Our custom simulation randomly generates activities and movements of individual occupants, tracking the amount of virus transmitted through air and surfaces from contagious to susceptible agents. The stochastic nature of the simulation requires that many repetitions be performed to achieve statistically reliable results. Accordingly, a series of initial experiments identified parameter values that balanced the trade-off between computational cost and accuracy. Applying generative design to a case study based on an existing office space reduced the predicted transmission by around 10% to 20% compared with a baseline set of layouts. Additionally, a qualitative examination of the generated layouts revealed design patterns that may reduce transmission. Stochastic multi-agent simulation is a computationally expensive yet plausible way to generate safer building designs.
ABSTRACT
Presynaptic nerve terminals are located at the ends of nerve cells; a signal propagating through a nerve cell reaches one of these compartments before being transmitted to an adjacent nerve cell. A tethered particle system (TPS) is a type of impulse-based model recently developed for the simulation of deformable biological structures. In a TPS, collisions can cause approaching particles to rebound outwards, as one would expect, but they can also caused separating particles to retract inwards. This paper demonstrates how a TPS can be used to simulate biological systems by presenting its application to a presynaptic nerve terminal. The model captures the clustering of sacs called vesicles in the presence of protein called synapsin. Both rigid and deformable membranes are also described. The simulated presynaptic nerve terminal may be used, for example, to predict how a change in synapsin concentration affects the size of vesicle clusters.
