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Piotr Omenzetter

Researcher at University of Aberdeen

Publications -  127
Citations -  1947

Piotr Omenzetter is an academic researcher from University of Aberdeen. The author has contributed to research in topics: Structural health monitoring & Bridge (interpersonal). The author has an hindex of 19, co-authored 127 publications receiving 1664 citations. Previous affiliations of Piotr Omenzetter include University of Auckland & Nanyang Technological University.

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Assessment of highway bridge upgrading by dynamic testing and finite-element model updating

TL;DR: In this article, a short-span bridge taking a busy main road across a coastal inlet near a major port facility was assessed before and after highway bridge upgrading works including strengthening, and the utility of the combined experimental and analytical process in direct identification of structural properties has been proven.
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Application of time series analysis for bridge monitoring

TL;DR: The reported study formulates a vector seasonal autoregressive integrated moving average (ARIMA) model for the recorded strain signals and uses it for analysis of the signals recorded during the construction and service life of the bridge.
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A spectral density approach for modelling continuous vertical forces on pedestrian structures due to walking

TL;DR: In this paper, a walking model used for vibration serviceability assessment of structures carrying pedestrians is presented, which is typically based on measurements of single footfalls replicated at precise intervals, and the model is used to assess the serviceability of a structure carrying pedestrians.
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Prediction of seismic-induced structural damage using artificial neural networks

TL;DR: In this paper, a general method for predicting seismic-induced damage using Artificial Neural Networks (ANNs) is presented, which describes both the structure and ground motion using a large number of structural and ground-motion properties.
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Particle Swarm Optimization with Sequential Niche Technique for Dynamic Finite Element Model Updating

TL;DR: A methodology based on particle swarm optimization (PSO), a GOA, with sequential niche technique (SNT) for FE model updating is proposed and explored and considerably increases the confidence in finding the global minimum.