The fluid dynamics of airflow through a city controls the transport and dispersion of airborne contaminants. This is
urban aerodynamics, not meteorology. The average flow, large-scale fluctuations and turbulence are closely coupled to
the building geometry. Buildings create large "rooster-tail" wakes; there are systematic fountain flows up the backs of
tall buildings; and dust in the wind can move perpendicular to or even against the locally prevailing wind. Requirements
for better prediction accuracy demand time-dependent, three-dimensional CFD computations that include solar heating
and buoyancy, complete landscape and building geometry specification including foliage and, realistic wind fluctuations.
This fundamental prediction capability is necessary to assess urban visibility and line-of-sight sensor performance in
street canyons and rugged terrain.
Computing urban aerodynamics accurately is clearly a time-dependent High Performance Computing (HPC) problem. In
an emergency, on the other hand, prediction technology to assess crisis information, sensor performance, and obscured
line-of-sight propagation in the face of industrial spills, transportation accidents, or terrorist attacks has very tight time
requirements that suggest simple approximations which tend to produce inaccurate results. In the past we have had to
choose one or the other: a fast, inaccurate model or a slow accurate model. Using new fluid-dynamic principles, an
urban-oriented emergency assessment system called CT-Analyst® was invented that solves this dilemma. It produces
HPC-quality results for airborne contaminant scenarios nearly instantly and has unique new capabilities suited to sensor
optimization. This presentation treats the design and use of CT-Analyst and discusses the developments needed for
widespread use with advanced sensor and communication systems.
Modern information systems that are designed to plan for and respond to Chemical, Biological, and Radiological (CBR) attacks are now attempting to include airborne contaminant plume models in their application package. These plume models are a necessary component for the emergency personnel responding to an actual event and to those charged with developing an effective response plan in advance. The capabilities to create a variety of CBR-event scenarios quickly, to determine possible contaminant agent release locations from reports and sensor data, and to predict the path of a plume before it gets there, are functions that many involved in the military and homeland security will find beneficial. For this reason CT-Analyst's ability to generate accurate, time-dependant plumes that can be rendered much faster than real-time and can be adjusted and modified on the screen, is an incredible asset to developers of these civil defense systems. The value of the fast, accurate CT-Analyst computer models for complex urban terrain is greatly increased when the capabilities can be imported into platforms users and developers are already taking advantage of. CT-Analyst's strengths can now be accessed through other applications, GIS tools, and development environments. This process will be described to show how this is possible, to which systems it can be applied, and what benefits can result.
Networked groups of sensors that detect Chemical, Biological, and Radiological (CBR) threats are being developed to defend cities and military bases. Due to the high cost and maintenance of these sensors, the number of sensors deployed is limited. It is vital for the sensors to be deployed in optimal locations for these sensors to be effectively used to analyze the scope of the threat. A genetic algorithm, along with the instantaneous plume prediction capabilities of CT-Analyst has been developed to meet these goals. CT-Analyst’s time dependant plumes, upwind danger zone, and sensor capabilities are used to determine the fitness of sensor networks generated by the genetic algorithm. The optimization and the requirements for the evaluation of sensor networks in an urban region are examined along with the number of sensors required to detect these plumes.
An urban-oriented emergency assessment system for airborne Chemical, Biological, and Radiological (CBR) threats, called CT-Analyst and based on new principles, gives greater accuracy and much greater speed than possible with current alternatives. This paper explains how this has been done. The increased accuracy derives from detailed, three-dimensional CFD computations including, solar heating, buoyancy, complete building geometry specification, trees, wind fluctuations, and particle and droplet distributions (as appropriate). This paper shows how a very finite number of such computations for a given area can be extended to all wind directions and speeds, and all likely sources and source locations using a new data structure called Dispersion Nomographs. Finally, we demonstrate a portable, entirely graphical software tool called CT-Analyst that embodies this entirely new, high-resolution technology and runs effectively on small personal computers. Real-time users don't have to wait for results because accurate answers are available with near zero-latency (that is 10 - 20 scenarios per second). Entire sequences of cases (e.g. a continuously changing source location or wind direction) can be computed and displayed as continuous-action movies. Since the underlying database has been precomputed, the door is wide open for important new real-time, zero-latency functions such as sensor data fusion, backtracking to an unknown source location, and even evacuation route planning. Extensions of the technology to sensor location optimization, buildings, tunnels, and integration with other advanced technologies, e.g. micrometeorology or detailed wind field measurements, will be discussed briefly here.