activity
20192025
most citedA Look into Chaos Detection through Topological Data Analysis

45 citations · 89 across the 11 of their papers we have counts for

collaborators

11 papers

cs.LG2025

Machine Learning-Based Ultrasonic Weld Characterization Using Hierarchical Wave Modeling and Diffusion-Driven Distribution Alignment

Joshua R. Tempelman, Adam J. Wachtor, Eric B. Flynn

Automated ultrasonic weld inspection remains a significant challenge in the nondestructive evaluation (NDE) community to factors such as limited training data (due to the complexit…

cond-mat.stat-mech2025

Spectral Characterization of Wave Scattering at a Granular-Elastic Solid Interface: From Hyperbolic Wave Propagation to Near-Parabolic Diffusion

Joshua R. Tempelman, Chongan Wang, Alexander F. Vakakis

We present a method based on acoustic wavenumber imaging algorithms to quantify the spectral content of strongly nonlinear energy scattering of a propagating wavefront across the d…

cs.LG2025

Probabilistic Emissivity Retrieval from Hyperspectral Data via Physics-Guided Variational Inference

Joshua R. Tempelman, Kevin Mitchell, Adam J. Wachtor +1

Recent research has proven neural networks to be a powerful tool for performing hyperspectral imaging (HSI) target identification. However, many deep learning frameworks deliver a…

physics.app-ph2024

Subwavelength topological interface modes in a multilayered vibroacoustic metamaterial

Majdi O. Gzal, Joshua R. Tempelman, Kathryn H. Matlack +1

We present a systematic and rigorous analytical approach, based on the transfer matrix methodology, to study the existence, evolution, and robustness of subwavelength topological i…

eess.SP2024

Physics-Informed Machine Learning for the Inverse Design of Wave Scattering Clusters

Joshua R. Tempelman, Tobias Weidemann, Eric B. Flynn +2

Clusters of wave-scattering oscillators offer the ability to passively control wave energy in elastic continua. However, designing such clusters to achieve a desired wave energy pa…

math.DS2023★ 12 cited

A Topological Framework for Identifying Phenomenological Bifurcations in Stochastic Dynamical Systems

Sunia Tanweer, Firas A. Khasawneh, Elizabeth Munch +1

Changes in the parameters of dynamical systems can cause the state of the system to shift between different qualitative regimes. These shifts, known as bifurcations, are critical t…

physics.app-ph2023

Wavenumber Scattering and Inter-band Targeted Energy Transfer in Phononic Lattices with Local Vibro-Impact Nonlinearities

Joshua R. Tempelman, Kathryn H. Matlack, Alexander F. Vakakis

We propose a method for manipulating wave propagation in phononic lattices by employing local vibro-impact (VI) nonlinearities to \textit{scatter} energy across the underling linea…

physics.app-ph2022

A Modal Decomposition Approach to Topological Wave Propagation

Joshua R Tempelman, Alexander F Vakakis, Kathryn H Matlack

The characteristics of topologically protected wave propagation is typically predicted via the band structure of the primitive unit cell, using Berry curvature to predict localized…

physics.app-ph2021★ 32 cited

Topological Protection in a Strongly Nonlinear Interface Lattice

Joshua R. Tempelman, Kathryn H. Matlack, Alexander F. Vakakis

Mechanical topological insulators are well understood for linear and weakly nonlinear systems, however traditional analysis methods break down for strongly nonlinear systems since…

eess.SP2020

Effects of Correlated Noise on the Performance of Persistence Based Dynamic State Detection Methods

Joshua Tempelman, Audun Myers, Jeffrey Scruggs +1

The ability to characterize the state of dynamic systems has been a pertinent task in the time series analysis community. Traditional measures such as Lyapunov exponents are often…

nlin.CD2019★ 45 cited

A Look into Chaos Detection through Topological Data Analysis

Joshua R. Tempelman, Firas A. Khasawneh

Traditionally, computation of Lyapunov exponents has been the marque method for identifying chaos in a time series. Recently, new methods have emerged for systems with both known a…