Computational Inversion and Algorithms

"Explores the mathematical development of inversion models used to infer density, porosity, and elastic moduli from observed wave dispersion."

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How Sound Waves Keep Our Bridges from Falling Computational Inversion and Algorithms
Julian Halloway June 27, 2026 5 min read

How Sound Waves Keep Our Bridges from Falling

Surface Wave Hub researchers are using sound waves and seismic sensors to 'listen' to bridges and tunnels, finding hidden cracks and weak spots without ever having to drill a hole.

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Checking Bridges Without Breaking Them Computational Inversion and Algorithms
Elias Thorne June 13, 2026 4 min read

Checking Bridges Without Breaking Them

Researchers at the Surface Wave Hub are using seismic surface waves to look inside bridges and tunnels without ever drilling a hole, saving time and keeping our roads safer.

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Finding the Hidden Voids Beneath Our Cities Computational Inversion and Algorithms
Julian Halloway June 9, 2026 4 min read

Finding the Hidden Voids Beneath Our Cities

Hidden sinkholes and forgotten pipes are a major risk in aging cities, but researchers are using the ground's natural hum to find them before they cause trouble.

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Computational Inversion and Algorithms
Julian Halloway June 9, 2026 4 min read

Listening to Our Bridges Before They Break

Engineers are using seismic surface waves to listen to the health of our bridges and tunnels, catching hidden cracks before they turn into major disasters.

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The Secret Map Under the Sidewalk Computational Inversion and Algorithms
Gareth Kemp June 1, 2026 4 min read

The Secret Map Under the Sidewalk

Researchers are using the natural 'hum' of the city to create underground maps, finding hidden pipes and dangerous sinkholes without digging a single hole.

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The Hidden World Under the Sidewalk Computational Inversion and Algorithms
Selene Mercer May 25, 2026 2 min read

The Hidden World Under the Sidewalk

Cities are full of hidden pipes and old tunnels. Scientists are now using the natural hum of city traffic to map these underground spaces and prevent sinkholes.

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Sensitivity Kernels in Surface Wave Tomography: A Computational Review Computational Inversion and Algorithms
Gareth Kemp April 11, 2026 6 min read

Sensitivity Kernels in Surface Wave Tomography: A Computational Review

Sensitivity kernels or Fréchet derivatives are the mathematical tools used in surface wave tomography to map observable seismic data to subsurface physical properties. This review explores their role in iterative inversion and their frequency-dependent depth sensitivity.

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