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Publikationen von Professorinnen und Professoren der HAW Hamburg

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Zeitschriftenbeiträge:

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Bernd Baumann, Jörg Schwieger, Ulrich Stein, Sarah Hallerberg und Marcus Wolff
High-intensity discharge lamp and Duffing oscillator--Similarities and differences
Journal of Applied Physics, 122(21):16
6 Dezember 2017
E

Marker: TI-MP

Zusammenfassung: The processes inside the arc tube of high-intensity discharge lamps are investigated by finite element simulations. The behavior of the gas mixture inside the arc tube is governed by differential equations describing mass, energy and charge conservation as well as the Helmholtz equation for the acoustic pressure and the Reynolds equations for the flow driven by buoyancy and Reynolds stresses. The model is highly nonlinear and requires a recursion procedure to account for the impact of acoustic streaming on the temperature and other fields. The investigations reveal the presence of a hysteresis and the corresponding jump phenomenon, quite similar to a Duffing oscillator. The similarities and, in particular, the differences of the nonlinear behavior of the high-intensity discharge lamp to that of a Duffing oscillator are discussed. For large amplitudes the high-intensity discharge lamp exhibits a stiffening effect in contrast to the Duffing oscillator. It is speculated on how the stiffening might affect hysteresis suppression.

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Thomas Kletschkowski und Florian Albrecht
A quasi-axisymmetric lattice model applied to analyze the vibrational contact between a PTFE shaft seal and a rotor
88th Annual Meeting of the International Association of Applied Mathemathics and Mechanics (GAMM), Volume 17, Issue 1:357-358
Dezember 2017

Marker: TI-FF

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Walter Leal Filho, A. Q. Al-Amin, N. M. Habib und A. H. Chowdhury
Assessing climate change mitigation proposals for Malaysia: Implications for emissions and abatement costs
Journal of Cleaner Production, Vol 167, :163-173
20 November 2017

Marker: LS

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Jutta Abulawi
Brauchen Hochschuldozierende heute andere Tugenden als früher?
Bulletin VSH-AEU, 43. Jahrgang, Nr. 3/4:7-11
1 November 2017
ISSN: 1663–9898
Deutsch

Schlüsselwörter: Hochschullehre, Haltung von Lehrenden, Spannungsfeld von Lehre und Forschung, Gute Lehre

Marker: TI-FF

Zusammenfassung: Gute Lehre und gute Forschung scheinen wie Zielkonflikte in der Hochschulwelt. Tatsächlich sind sie aber sehr gut miteinander vereinbar, denn beiden sollte eine offene Haltung, Neugier, Selbstkritik, Offenheit für Feedback und der Diskurs mit Fachleuten, Fachfremden und Novizen zugrunde liegen.

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Wolfgang Willaschek
Essay: Eine unaufhörliche Odyssee - Spurensicherungen historischer und theatralischer Art zu „Il ritorno d´Ulisse in patria“
Claudio Monteverdis Oper, Hamburgische Staatsooper,
November 2017

Marker: DMI-Mt

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Michael Röther
"Der anfängliche Mehraufwand lohnt sich"
Transnationale Bildung made in Germany; Beilage zur duz - Deutsche Universitätszeitung, :19
20 Oktober 2017

Marker: TI

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Günther Gravel und Thies Kahnenbley
Welligkeiten auf Zahnflanken und ihre Ursachen
Antriebstechnik,
20 September 2017

Marker: TI-MP

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Vera Schorbach, Peter Dalhoff und Peter Gust
Teeter design for lowest extreme loads during end impacts
Wind Energy,
19 September 2017
ISSN: 1099-1824

Marker: TI-MP

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Birgit Haase
Footwear – Shoes and Boots from the Hopkins Collection. (Rezension)
netzwerk mode textil,
19 August 2017

Marker: DMI-D

pdf
Mike Gerdes, Diego Galar und Dieter Scholz
Genetic Algorithms and Decision Trees for Condition Monitoring and Prognosis of A320 Aircraft Air Conditioning
Insight - Non-Destructive Testing and Condition Monitoring, 59(8):424 - 433
August 2017
ISSN: 1354-2575

Marker: TI-FF

Zusammenfassung: Unscheduled maintenance is a large cost driver for airlines, but condition monitoring and prognosis can reduce the number of unscheduled maintenance actions. The paper shows condition monitoring can be introduced into most system by adopting a data-driven approach and using existing data sources. The goal is to forecast the remaining useful life (RUL) of a system based on various sensor inputs. We use decision trees to learn the characteristics of a system. The data for the decision tree training and classification are processed by a generic parametric signal analysis. To obtain the best classification results for the decision tree, the parameters are optimized by a genetic algorithm. A forest of three different decision trees with different signal analysis parameters is used as classifier. The proposed method is validated with data from an A320 aircraft from ETIHAD Airways. Validation shows condition monitoring can classify the sample data into ten predetermined categories, representing the total useful life (TUL) in 10 percent steps. This is used to predict the RUL. There are 350 false classifications out of 850 samples. Noise reduction reduces the outliers to nearly zero, making it possible to correctly predict condition. It is also possible to use the classification output to detect a maintenance action in the validation data.

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Letzte Änderung: 23.01.15

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