159 research outputs found
Information based mobile sensor planning for source term estimation of a non-continuous atmospheric release
This paper presents a method to estimate the
original location and the mass of an instantaneous release of hazardous material into the atmosphere. It is formulated as an inverse problem, where concentration observations from a mobile sensor are fused with meteorological information and a Gaussian puff dispersion model to characterise the
source. Bayesâ theorem is used to estimate the parameters of the release taking into account the uncertainty that exists in the dispersion parameters and meteorological variables. An
information based reward is used to guide an unmanned aerial vehicle equipped with a chemical sensor to the expected most
informative measurement locations. Simulation results compare the performance between a single mobile sensor with various amounts of static sensors
Simulating The Impact of Emissions Control on Economic Productivity Using Particle Systems and Puff Dispersion Model
A simulation platform is developed for quantifying the change in productivity of an economy under passive and active emission control mechanisms. The program uses object-oriented programming to code a collection of objects resembling typical stakeholders in an economy. These objects include firms, markets, transportation hubs, and boids which are distributed over a 2D surface. Firms are connected using a modified Primâs Minimum spanning tree algorithm, followed by implementation of an all-pair shortest path Floyd Warshall algorithm for navigation purposes. Firms use a non-linear production function for transformation of land, labor, and capital inputs to finished product. A GA-Vehicle Routing Problem with multiple pickups and drop-offs is implemented for efficient delivery of commodities across multiple nodes in the economy. Boids are autonomous agents which perform several functions in the economy including labor, consumption, renting, saving, and investing. Each boid is programmed with several microeconomic functions including intertemporal choice models, Hicksian and Marshallian demand function, and labor-leisure model. The simulation uses a Puff Dispersion model to simulate the advection and diffusion of emissions from point and mobile sources in the economy. A dose-response function is implemented to quantify depreciation of a Boidâs health upon contact with these emissions. The impact of emissions control on productivity and air quality is examined through a series of passive and active emission control scenarios. Passive control examines the impact of various shutdown times on economic productivity and rate of emissions exposure experienced by boids. The active control strategy examines the effects of acceptable levels of emissions exposure on economic productivity. The key findings on 7 different scenarios of passive and active emissions controls indicate that rate of productivity and consumption in an economy declines with increased scrutiny of emissions from point sources. In terms of exposure rates, the point sources may not be the primary source of average exposure rates, however they significantly impact the maximum exposure rate experienced by a boid. Tightening of emissions control also negatively impacts the transportation sector by reducing the asset utilization rate as well as reducing the total volume of goods transported across the economy
THE DEVELOPMENT OF A PUFF DISPERSION MODEL FOR USE IN MODELLING SHORT TERM ACCIDENTAL RELEASES, BASED ON THE ADMS 4 MODEL: ADMS-STAR2
To help enable the United Kingdom Food Standards Agency to protect the food chain in the event of an accidental
atmospheric release, it has funded the development of a puff dispersion model, called ADMS-STAR2, based on the existing ADMS
4. The ADMS-STAR2 model can be run using a range of input parameters or defaults within the model, dependant on the
information available following a release. Meteorological inputs include basic surface derived observational data or full 3-D
spatially and temporally varying NWP data. Thermal and explosive releases penetrating the boundary layer can be modelled. The
use of FLOWSTAR within ADMS-STAR2 allows consideration of complex terrain effects, with deposition responsive to spatially
varying surface roughness. Output options include isopleth display on ArcGIS of total ground deposition
Moth-inspired navigation algorithm in a turbulent odor plume from a pulsating source
Some female moths attract male moths by emitting series of pulses of
pheromone filaments propagating downwind. The turbulent nature of the wind
creates a complex flow environment, and causes the filaments to propagate in
the form of patches with varying concentration distributions. Inspired by moth
navigation capabilities, we propose a navigation strategy that enables a flier
to locate a pulsating odor source in a windy environment using a single
threshold-based detection sensor. The strategy is constructed based on the
physical properties of the turbulent flow carrying discrete puffs of odor and
does not involve learning, memory, complex decision making or statistical
methods. We suggest that in turbulent plumes from a pulsating point source, an
instantaneously measurable quantity referred as a "puff crossing time",
improves the success rate as compared to the navigation strategy based on
"internal counter" that does not use this information. Using computer
simulations of fliers navigating in turbulent plumes of the pulsating point
source for varying flow parameters: turbulent intensities, plume meandering and
wind gusts, we obtained trajectories qualitatively resembling male moths
flights towards the pheromone sources. We quantified the probability of a
successful navigation as well as the flight parameters such as the time spent
searching and the total flight time, with respect to different turbulent
intensities, meandering or gusts. The concepts learned using this model may
help to design odor-based navigation of miniature airborne autonomous vehicles
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