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High spin states in ¹³⁶ Ce
(1975)
High spin states in ¹³⁶ Ce
(1975)
In-beam study of ¹⁴⁴ Gd
(1978)
In-beam study of ¹⁴⁴ Gd
(1978)
In-beam study of ¹⁴⁴ Gd
(1977)
Isomeric states in ¹³⁴ Ba
(1980)
Isomeric states in ¹³⁴ Ba
(1980)
High-spin states in ¹³³ La
(1982)
High-spin states in ¹³³ La
(1980)
Isomeric state in ¹³⁴ La
(1981)
Isomeric state in ¹³⁶ La
(1981)
Band structure in ¹⁹⁴ Au
(1979)
High-spin states in ¹⁸⁰ Os
(1979)
High spin states in ¹⁸⁸ Au
(1982)
Side-bands in ¹⁸⁰ Os
(1981)
Yrast states up to spin 18 have been identified in ¹³²Ce. The energies and spins of the levels suggest the existence of two fairly well-behaved collective bands. The results are compared with those obtained in the rare-earth deformed region.
In-beam study of ¹⁴³ Eu
(1988)
Unsteady flow measurements in the wake behind a wind-tunnel car model by using high-speed planar PIV
(2015)
This study investigates unsteady characteristics of the wake behind a 28%-scale car model in a wind tunnel using highspeed planar particle image velocimetry (PIV). The car model is based on a hatchback passenger car that is known to have relatively high fluctuations in its aerodynamic loads. This study primarily focuses on the lateral motion of the flow on the horizontal plane to determine the effect of the flow motion on the straight-line stability and the initial steering response of the actual car on a track. This paper first compares the flow fields in the wake behind the above mentioned model obtained using conventional and high-speed planar PIV, with sampling frequencies of 8 Hz and 1 kHz, respectively. Large asymmetrically coherent flow structures, which fluctuate at frequencies below 2 Hz, are observed in the results of highspeed PIV measurements, whereas conventional PIV is unable to capture these features of the flow owing to aliasing. This flow pattern with a laterally swaying motion is represented by opposite signs of cross-correlation coefficients of streamwise velocity fluctuations for the two sides of the car model. Effects of two aerodynamic devices that are known to reduce the
fluctuation levels of the aerodynamic loads are then extensively investigated. The correlation analyses reveal that these devices indeed reduce the fluctuation levels of the flow and the correlation values around the rear combination-lamp, but it is found that the effects of these devices are different around the c-pillar.
Aachen: Colourdome
(2002)
Digital forensics of smartphones is of utmost importance in many criminal cases. As modern smartphones store chats, photos, videos etc. that can be relevant for investigations and as they can have storage capacities of hundreds of gigabytes, they are a primary target for forensic investigators. However, it is exactly this large amount of data that is causing problems: extracting and examining the data from multiple phones seized in the context of a case is taking more and more time. This bears the risk of wasting a lot of time with irrelevant phones while there is not enough time left to analyze a phone which is worth examination. Forensic triage can help in this case: Such a triage is a preselection step based on a subset of data and is performed before fully extracting all the data from the smartphone. Triage can accelerate subsequent investigations and is especially useful in cases where time is essential. The aim of this paper is to determine which and how much data from an Android smartphone can be made directly accessible to the forensic investigator – without tedious investigations. For this purpose, an app has been developed that can be used with extremely limited storage of data in the handset and which outputs the extracted data immediately to the forensic workstation in a human- and machine-readable format.
Operational Modal Analysis (OMA) is a promising candidate for flutter testing and Structural Health Monitoring (SHM) of aircraft wings that are passively excited by wind loads. However, no studies have been published where OMA is tested in transonic flows, which is the dominant condition for large civil aircraft and is characterized by complex and unique aerodynamic phenomena. We use data from the HIRENASD large-scale wind tunnel experiment to automatically extract modal parameters from an ambiently excited wing operated in the transonic regime using two OMA methods: Stochastic Subspace Identification (SSI) and Frequency Domain Decomposition (FDD). The system response is evaluated based on accelerometer measurements. The excitation is investigated from surface pressure measurements. The forcing function is shown to be non-white, non-stationary and contaminated by narrow-banded transonic disturbances. All these properties violate fundamental OMA assumptions about the forcing function. Despite this, all physical modes in the investigated frequency range were successfully identified, and in addition transonic pressure waves were identified as physical modes as well. The SSI method showed superior identification capabilities for the investigated case. The investigation shows that complex transonic flows can interfere with OMA. This can make existing approaches for modal tracking unsuitable for their application to aircraft wings operated in the transonic flight regime. Approaches to separate the true physical modes from the transonic disturbances are discussed.