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            Assessment of least-cost pathways for decarbonising Europe's power supply : a model-based long-term scenario analysis accounting for the characteristics of renewable energies 

            Pfluger, Benjamin (2013)
            This work analyses technological least-cost pathways for deep emission reductions in the European power sector. It seeks a better understanding of the role renewable energies play in the transformation process up to 2050. ...
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            Biaxial Characterization and Mean-field Based Damage Modeling of Sheet Molding Compound Composites 

            Schemmann, Malte (2018)
            The focus of this work lies on the microstructure-based modeling and characterization of a discontinuous fiber-reinforced thermoset in the form of sheet molding compound (SMC). A microstructure-based parameter identification ...
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            Basissoftware für drahtlose Ad-hoc- und Sensornetze 

            Zitterbart, MartinaBaumung, Peter [Hrsg.] (2009)
            Mit dem Titel ""Basissoftware für selbstorganisierende Infrastrukturen für vernetzte mobile Systeme"" vereint das Schwerpunktprogramm 1140 der DFG Forschungsvorhaben zum Thema drahtloser Ad-hoc- und Sensornetze. Durch die ...
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            Begriffliche Situationsanalyse aus Videodaten bei unvollständiger und fehlerhafter Information 

            Münch, David (2017)
            This work addresses the automatic detection of complex situations in image sequences in the video surveillance context. There are difficulties when dealing with data from natural environments. This work expands the formalism ...
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            CAE - PROCESS AND NETWORK : A methodology for continuous product validation process based on network of various digital simulation methods 

            Syal, Gagan (2013)
            CAE ProNet methodology is to develop CAE network considering interdependencies among digital validations. Utilizing CAE network and considering industrial requirements, an algorithm is applied to execute a product, vehicle ...
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              This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871069.

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