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Der Beitrag fokussiert die Frage nach dem Stand des durch die Bologna-Reform angestoßenen Kulturwandels im Hinblick auf Kompetenzorientierung am Beispiel der Technischen Universität Hamburg (TUHH). An der TUHH wird bereits seit einigen Jahren daran gearbeitet, die Lehre grundlegend neu auszurichten. Hierfür setzt das hochschuldidaktische "Zentrum für Lehre und Lernen" (ZLL) verschiedene Maßnahmen ein, wie z.B. eine finanzielle und didaktische Unterstützung von Lehrenden bei der Umstellung ihrer Veranstaltungen, Weiterqualifizierungsangebote und Informationsmaterial. Die Maßnahmen ebenso wie die innovierten Veranstaltungen werden von Lehrenden und Studierenden gut evaluiert. Nach dem Ansatz des Constructive Alignments lässt sich jedoch davon ausgehen, dass der Bereich der Prüfungen für eine Einschätzung des Status Quo der Kompetenzorientierung besonders relevant ist. Dieser wird deshalb anhand der beiden Kriterien Prüfungsformate und Schwierigkeitsstufen von Prüfungsaufgaben näher beleuchtet, die eng mit der Kompetenzorientierung zusammen hängen. Ergebnisse hierzu aus einer universitätsweiten Datenbank zur Studienorganisation sowie aus einer Online-Umfrage unter Studierenden weisen darauf hin, dass das Prüfungsformat "Klausur" nach wie vor am stärksten verbreitet ist; zugleich sind die Studierenden nach einer Selbsteinschätzung in Prüfungen vorrangig mit Aufgaben auf den Taxonomieniveaus "Wiedergeben" und "Anwenden" konfrontiert. Dies lässt sich als Hinweis darauf interpretieren, dass es im Hinblick auf eine Kompetenzorientierung in den Prüfungen noch weiteren Veränderungsbedarf gibt.
Digitalisierung bezeichnet die Nutzung großer Datenmengen, die zu einer umfassenden Vernetzung aller Bereiche der Wirtschaft und Gesellschaft führen wird (BMWi, 2015 und ähnlich Köhler/Wollschläger, 2014: 79). Sie umfasst die Erhebung von analogen Informationen („Big Data“ in einem engen Sinne; z.B. O´Leary, 2013), ihre Speicherung in einem digitaltechnischen System (lokale Speicherung oder „Cloud Computing“ durch die Weiterentwickelung des Internets; z.B. Hashem et al., 2015: 101), die Analyse und Interpretation sowie den Transfer in andere Systeme („Internet der Dinge“ bzw. „Internet of Things“; z.B. Ashton, 2009).
The potential of SMART climbing robot combined with a weatherproof cabin for rotor blade maintenance
(2016)
The Dry-Low-NOx (DLN) Micromix combustion technology has been developed originally as a low emission alternative for industrial gas turbine combustors fueled with hydrogen. Currently the ongoing research process targets flexible fuel operation with hydrogen and syngas fuel.
The non-premixed combustion process features jet-in-crossflow-mixing of fuel and oxidizer and combustion through multiple miniaturized flames. The miniaturization of the flames leads to a significant reduction of NOx emissions due to the very short residence time of reactants in the flame.
The paper presents the results of a numerical and experimental combustor test campaign. It is conducted as part of an integration study for a dual-fuel (H2 and H2/CO 90/10 Vol.%) Micromix combustion chamber prototype for application under full scale, pressurized gas turbine conditions in the auxiliary power unit Honeywell Garrett GTCP 36-300.
In the presented experimental studies, the integration-optimized dual-fuel Micromix combustor geometry is tested at atmospheric pressure over a range of gas turbine operating conditions with hydrogen and syngas fuel. The experimental investigations are supported by numerical combustion and flow simulations. For validation, the results of experimental exhaust gas analyses are applied.
Despite the significantly differing fuel characteristics between pure hydrogen and hydrogen-rich syngas the evaluated dual-fuel Micromix prototype shows a significant low NOx performance and high combustion efficiency. The combustor features an increased energy density that benefits manufacturing complexity and costs.
This work presents a methodology for automated
damage-sensitive feature extraction and anomaly
detection under multivariate operational variability
for in-flight assessment of wings. The
method uses a passive excitation approach, i. e.
without the need for artificial actuation. The
modal system properties (natural frequencies and
damping ratios) are used as damage-sensitive
features. Special emphasis is placed on the use
of Fiber Bragg Grating (FBG) sensing technology
and the consideration of Operational and
Environmental Variability (OEV). Measurements
from a wind tunnel investigation with a composite
cantilever equipped with FBG and piezoelectric
sensors are used to successfully detect an impact
damage. In addition, the feasibility of damage
localisation and severity estimation is evaluated
based on the coupling found between damageand
OEV-induced feature changes.
The impact of wake model effects is investigated for two highly
non-planar lifting systems. Dependent on the geometrical
arrangement of the configuration, the wake model shape is found
to considerably affect the estimation. Particularly at higher angles
of attack, an accurate estimation based on the common linear wake
model approaches is involved.
Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions.