T
Thomas Schumacher
Researcher at Portland State University
Publications - 88
Citations - 1044
Thomas Schumacher is an academic researcher from Portland State University. The author has contributed to research in topics: Acoustic emission & Structural health monitoring. The author has an hindex of 16, co-authored 79 publications receiving 796 citations. Previous affiliations of Thomas Schumacher include University of Illinois at Urbana–Champaign & University of Delaware.
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Experimental Setup for a Large-Scale Bridge Superstructure Model Subjected to Waves
TL;DR: In this paper, a series of experiments was conducted on a realistic, 1:5 scale reinforced concrete bridge superstructure, where the stiffness of the horizontal support system can be varied to represent different dynamic properties of the bridge system.
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Monitoring of Structures and Mechanical Systems Using Virtual Visual Sensors for Video Analysis: Fundamental Concept and Proof of Feasibility
Thomas Schumacher,Ali Shariati +1 more
TL;DR: The basic concept and mathematical theory of this proposed so-called virtual visual sensor (VVS) is introduced, a set of initial laboratory experiments are presented to demonstrate the accuracy of this approach, and a practical in-service monitoring example of an in- service bridge is provided.
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A Novel Methodology for Spatial Damage Detection and Imaging Using a Distributed Carbon Nanotube-Based Composite Sensor Combined with Electrical Impedance Tomography
TL;DR: In this paper, a non-destructive evaluation methodology for imaging of damage in composite materials using the electrical impedance tomography (EIT) technique applied to a distributed carbon nanotube-based sensor is described.
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Processing and Characterization of a Novel Distributed Strain Sensor Using Carbon Nanotube-Based Nonwoven Composites.
TL;DR: The development of an innovative carbon nanotube-based non-woven composite sensor that can be tailored for strain sensing properties and potentially offers a reliable and cost-effective sensing option for structural health monitoring (SHM).
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Toward a probabilistic acoustic emission source location algorithm: A Bayesian approach
TL;DR: In this article, a probabilistic source location algorithm was proposed for acoustic emissions analysis using Bayesian analysis methods with Markov Chain Monte Carlo (MCMC) simulation where all source location parameters were described with posterior probability density functions (PDFs).