Tag: Eigenmodes

When Grain Growth Models Don’t Grow Real Grains

Picture a bustling medieval city: houses of all shapes, roads interweaving unpredictably, and gates that won’t budge because of stubborn gatekeepers. That’s exactly what modeling mesoscale grain growth feels like—chaotic, unpredictable, and utterly maddening. Sure, we have tools like phase-field, Monte‑Carlo Potts, and cellular automata to simulate this thermal dance at the grain level. But each has quirks that make them fall short of mimicking real-world materials.

August 13, 2025 0

When Matrices Bend Reality: Unlocking Waves with Metric Spaces and Pseudo‑Hermitian Algebra

Think of a symphony where each instrument plays in perfect harmony. Now imagine that hall bending and warping the music—notes stretch, shift, harmonics twist. That’s akin to how metric spaces, pseudo-symmetric, and pseudo-Hermitian matrices are transforming how we understand wave dynamics in warped environments—from quantum realms to engineered metamaterials.

August 6, 2025 0

Sparse Wavenumber Recovery in Anisotropic Composites Repository

Guided wave imaging is a cornerstone technique in structural health monitoring (SHM), especially for composite materials. But composites are anisotropic—meaning wave speeds and behaviors vary with direction—which makes interpreting wave propagation challenging.

This CodeOcean capsule presents the algorithm and tools for Sparse Wavenumber Recovery (SWR) developed by Soroosh Sabeti, which leverage compressed sensing and sparse signal processing to efficiently extract anisotropic wavenumber content from limited measurements.

July 15, 2025 0

K-SVD Dictionary Learning for Damage Detection Repository

K-SVD Dictionary Learning for Damage Detection is a baseline-free, data-driven approach for detecting structural damage using guided ultrasonic waves. Developed by Supreet Alguri and Dr. Joel B. Harley, this method eliminates the need for pristine baseline measurements—a major limitation in many real-world Structural Health Monitoring (SHM) systems.

This CodeOcean capsule provides a reproducible implementation of the algorithm, as described in the paper:

June 10, 2025 0

Temporal Sparse Wavenumber Analysis Repository

Temporal Sparse Wavenumber Analysis (TSWA) is a novel technique that reconstructs high-resolution spatiotemporal wavefields using fewer temporal samples than traditional methods typically require. Developed by Soroosh Sabeti and Dr. Joel B. Harley, TSWA makes it possible to retrieve accurate guided wave information from temporally undersampled data, which is crucial in applications where high-speed sensing, data storage, or power consumption are limiting factors.

June 3, 2025 0
Data-driven matched field processing

Data-Driven Matched Field Processing (DDMFP) Repository

Data-Driven Matched Field Processing (DDMFP) is an innovative signal processing framework designed for localizing acoustic sources in complex environments, such as those encountered in structural health monitoring (SHM) using Lamb waves. Traditional matched field processing (MFP) techniques rely heavily on accurate physical models of the propagation medium, which can be challenging to obtain in real-world scenarios. DDMFP circumvents this limitation by constructing localization models directly from measured data, enhancing robustness and accuracy in complex, multimodal propagation environments.

May 17, 2025 0

Listening to the Plate: How Lamb Waves Quietly Reveal the Structure of Materials

Guided waves like Lamb modes are reshaping how we inspect, model, and understand solid materials — all by listening to vibrations within the structure itself.

If you’ve never heard of Lamb waves, you’re not alone. Though they’ve been known to physicists and engineers for over a century, they remain surprisingly underdiscussed outside specialized fields like non-destructive testing, ultrasonics, and solid mechanics. But behind the scenes, Lamb waves are playing a crucial role — helping us understand how materials behave, age, and break, all through the language of wave motion.

May 16, 2025 0

©  2025 SmartDATA Lab. Built using WordPress and OnePage Express Theme.