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August 15, 2007
By DE Editors
A suite of efficient algorithms for solution of Electrical Impedance Tomography (EIT) problems has been developed by Dynaflow, Inc. (Jessup, MD). DYNAEIT, which uses the boundary element method, provides an accurate and efficient set of algorithms for identification of container contents.
These EIT algorithms can be applied for medical imaging, multiphase flows encountered in chemical, oil and gas, energy, and aerospace industries, nondestructive evaluation of structures and materials, imaging of underground water paths and container leakage, archaeology, detection of buried objects, chemical reactive flows, and more.
In EIT, the distribution of conductivity inside a container is sought by applying specified currents (or voltages) at portions of the container surface and performing measurements of the voltage (or currents) at other locations along the surface. The equations for the electric field then provide relationships between the conductivity distribution inside the domain and the measured voltages and currents. Different types of materials have different conductivities resulting in a conductivity map that provides an image of the material distribution in the container.
CPU-efficient methods, such as a Dipole Approximation method, and a Singular Boundary Element Method are used to rapidly solve the “forward” problem of determination of voltage and current distributions for a known conductivity distribution in the imaged domain in 2D and 3D. The inverse problem is the problem of image reconstruction using the measured voltages and/or currents. This is solved by application of multi-dimensional minimization procedures, such as Powell’s Direction Set Method, the Downhill Simplex Method, Genetic Algorithms, and multi-objective minimization based on Pareto sets.
Initial efforts to develop DYNAEIT were funded by two Small Business Innovation Research (SBIR) awards from the National Science Foundation (NSF).
For additional information, please go to Dynaflow, Inc.
Sources: Press materials received from the company and additional information gleaned from the company’s website.
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