Author
Guido Morgenthal
Other affiliations: Hitachi, Weimar Institute, University of Cambridge ...read more
Bio: Guido Morgenthal is an academic researcher from Bauhaus University, Weimar. The author has contributed to research in topics: Aeroelasticity & Aerodynamics. The author has an hindex of 20, co-authored 120 publications receiving 1300 citations. Previous affiliations of Guido Morgenthal include Hitachi & Weimar Institute.
Topics: Aeroelasticity, Aerodynamics, Vortex, Flutter, Aerodynamic force
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the application of UAVs for visual inspection and damage detection on civil structures is discussed and the properties of such flight systems, the factors influencing their movements and the resulting photo quality is discussed.
Abstract: This paper discusses the application of Unmanned Aerial Vehicles (UAV) for visual inspection and damage detection on civil structures. The quality of photos and videos taken by using such airborne vehicles is strongly influenced by numerous parameters such as lighting conditions, distance to the object and vehicle motion induced by environmental effects. Whilst such devices feature highly sophisticated sensors and control algorithms, specifically the effects of fluctuating wind speeds and directions affect the vehicle motion. The nature of vehicle movements during photo and video acquisition in turn affect the quality of the data and hence the degree to which damages can be identified. This paper discusses the properties of such flight systems, the factors influencing their movements and the resulting photo quality. Based on the processed data logged by the high precision sensors on the UAV the influences are studied and a method is shown by which the damage assessment quality may be quantified.
219 citations
TL;DR: A coherent framework for automated unmanned aircraft system based inspections of large bridges to facilitate an automated condition assessment is presented and the application to a large bridge structure showcases how the integration of digital systems and algorithms forms the basis for an intelligent and potentially autonomous safety assessment of very large infrastructures.
108 citations
27 May 2014
99 citations
TL;DR: In this article, a two-dimensional immersed interface technique for the vortex-in-cell (VIC) method for simulation of flows past bodies of complex geometry is presented, which is augmented by a local particle-particle correction term in a Particle-Particle Particle Mesh (P^3M) context to resolve sub-grid scales incurred by the presence of the immersed interface.
69 citations
TL;DR: In this paper, a numerical model of the square RC pier column with fixed base was developed to predict the impact force time-history and dynamic responses of the column subjected to barge impact.
50 citations
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1,604 citations
01 Jan 2009
TL;DR: In this paper, a criterion for the convergence of numerical solutions of Navier-Stokes equations in two dimensions under steady conditions is given, which applies to all cases, of steady viscous flow in 2D.
Abstract: A criterion is given for the convergence of numerical solutions of the Navier-Stokes equations in two dimensions under steady conditions. The criterion applies to all cases, of steady viscous flow in two dimensions and shows that if the local ' mesh Reynolds number ', based on the size of the mesh used in the solution, exceeds a certain fixed value, the numerical solution will not converge.
1,568 citations
TL;DR: In this paper, the authors present a comprehensive review of the literature on footbridges' vibration serviceability, focusing on three key issues: vibration source, path, and receiver.
571 citations
TL;DR: An overview of recent advances in computer vision techniques as they apply to the problem of civil infrastructure condition assessment and some of the key challenges that persist toward the goal of automated vision-based civil infrastructure and monitoring are presented.
500 citations
TL;DR: This article implements the state‐of‐the‐art deep learning technologies for a civil engineering application, namely recognition of structural damage from images with four naïve baseline recognition tasks: component type identification, spalling condition check, damage level evaluation, and damage type determination.
Abstract: This article implements the state‐of‐the‐art deep learning technologies for a civil engineering application, namely recognition of structural damage from images. Inspired by ImageNet Chall...
460 citations