Abstract. We present an approach for the computation of singleobject velocity statistics in a noisy fluorescence image series. The algorithm is applied to molecular imaging data from an in vitro actinmyosin motility assay. We compare the relative efficiency of wavelet and curvelet transform denoising in terms of noise reduction and object restoration. It is shown that while both algorithms reduce background noise efficiently, curvelet denoising restores the curved edges of actin filaments more reliably. Noncrossing spatiotemporal actin trajectories are unambiguously identified using a novel segmentation scheme that locally combines the information of 2-D and 3-D segmentation. Finally, the optical flow vector field for the image sequence is computed via the 3-D structure tensor and mapped to the segmented trajectories. Using single-trajectory statistics, the global velocity distribution extracted from an image sequence is decomposed into the contributions of individual trajectories. The technique is further used to analyze the distribution of the x and y components of the velocity vectors separately, and it is shown that directed actin motion is found in myosin extracts from single skeletal muscle fibers. The presented approach may prove helpful to identify actin filament subpopulations and to analyze actin-myosin interaction kinetics under biochemical regulation.
The wings of passenger aircrafts are constantly vibrating due to various loads. There are transient low-frequency vibrations caused by gust loads. But there are also higher-frequency vibrations caused by the vibration load of the jet engines. The higher-frequency stationary vibrations
of the wing are partially introduced as a power flow into the fuselage and radiated there as sound, which is then perceived as noise. In this work, which is part of the EU CleanSky2 framework, this chain of effects is being investigated in more detail aiming for the quantification of the vibrational
power flow input into the fuselage by utilizing structural intensity. In this paper, numerical investigations are carried out on FEM models of an Airbus A320 wing generated with a parametric model generator. First, the structural components mainly responsible for the power transmission are
identified, and second, the magnitude of the power input into the fuselage is determined in dependence of the pylon position along the wing. The engine vibrations are approximated by a custom-developed model. In the further course of the project, these numerical results will be validated by
a test campaign. For this purpose, a real wing of an A320 is available as a test structure.
Aircraft engines, especially when mounted directly to the fuselage, inject a considerable amount of tonal vibrations into the airframe causing audible and comfort reducing cabin noise. Reducing this noise requires the development of specialised noise reduction systems. This is a time
consuming and expensive endeavour. To speed up and ease this process a sufficiently detailed numerical model of the aircraft structure and the force injected by the engines is required. The DLR ISTAR, a Dassault Falcon 2000, was used for an extensive vibration measurement campaign. The goal
of this campaign was twofold: Getting spatially dense information about the aircrafts vibro-acoustic behaviour to later update a finite element model for calculations in the mid-frequency range and to analyse the vibration injected by running engines into the fuselage structure. The measurements
include the vibrational response to both shaker excitation and engine vibration of the DLR ISTAR at about 1400 positions acquired by a rowing grid of sensors. The results are presented in the form of operational deflection shapes and energy transfer paths calculated using structural intensity
analysis.
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