Filament-Based Atmospheric Dispersion Model to Achieve Short Time-Scale Structure of Odor Plumes

Abstract

Abstract. This article presents the theoretical motivation, implementation approach, and example validation results for a computationally efficient plume simulation model, designed to replicate both the short-term time signature and long-term exposure statistics of a chemical plume evolving in a turbulent flow. Within the resulting plume, the odor concentration is intermittent with rapidly changing spatial gradient. The model includes a wind field defined over the region of interest that is continuous, but which varies with location and time in both magnitude and direction.The plume shape takes a time varying sinuous form that is determined by the integrated effect of the wind field.Simulated and field data are compared. The motivation for the development of such a simulation model was the desire to evaluate various strategies for tracing odor plumes to their source, under identical conditions. The performance of such strategies depends in part on the instantaneous response of target receptors; therefore, the sequence of events is of considerable consequence and individual exemplar plume realizations are required. Due to the high number of required simulations, computational efficiency was critically important.

Understanding the Potential Impact of Multiple Robots in Odor Source Localization

“…The odor propagation model closely resembles the filament-based model proposed by Farrell et al [3]. This model is easy to implement and requires only a very limited amount of CPU power.…”

A 3-D bio-inspired odor source localization and its validation in realistic environmental conditions

“…An odor dispersion simulator plugin [27] has also been developed which allows a realistic simulation of wind and odor plume, based on the filament-based atmospheric dispersion model proposed in [28], as well as using olfaction and anemometry sensors on robots. Using these tools, we have been able to simulate a realistic odor plume in a large environment of 20 × 4 × 2 m 3 (see Fig.…”

“…The main challenges in Odor Source Localization (OSL) are related to the intermittent structure of odor dispersion in the air [1]. Understanding how odor molecules disperse through an environment under naturally turbulent flow is the key to design and development of efficient olfactory search strategies.…”

“…Odor molecules move downwind due to mean flow velocity, forming an odor plume, while their net 3D motion is almost random, due to small-scale turbulence curls. As the flow carries patches of odor away from the source, the average concentration within a patch decreases and the average time between successive patches increases [1]. Due to the turbulent structure (over large scales) of the air flow, the plume has an irregular packet-like structure, whereby high and low concentrations are close in both time and space.…”

A Graph-Based Formation Algorithm for Odor Plume Tracing

“…The odor propagation implementation is based on the the filament-based model proposed by Farrell et al [7], and generates an intermittent plume similar to the one observed in the wind tunnel. Odor is simulated as a set of filaments (i = 0, ..., N), each containing a constant amount s = 8.3 × 10 9 of molecules.…”