@article{ValeroVitiGualtieri2019, author = {Valero, Daniel and Viti, Nicolo and Gualtieri, Carlo}, title = {Numerical Simulation of Hydraulic Jumps. Part 1: Experimental Data for Modelling Performance Assessment}, series = {Water}, volume = {11}, journal = {Water}, number = {1}, publisher = {MDPI}, address = {Basel}, issn = {2073-4441}, doi = {10.3390/w11010036}, pages = {Art. Nr. 36}, year = {2019}, language = {en} } @inproceedings{ValeroKramerBungetal.2019, author = {Valero, Daniel and Kramer, Matthias and Bung, Daniel B. and Chanson, Hubert}, title = {A stochastic bubble generator for air-water flow research}, series = {E-proceedings of the 38th IAHR World Congress, September 1-6, 2019, Panama City, Panama}, booktitle = {E-proceedings of the 38th IAHR World Congress, September 1-6, 2019, Panama City, Panama}, doi = {10.3850/38WC092019-0909}, pages = {5714 -- 5721}, year = {2019}, language = {en} } @article{ValeroChansonBung2019, author = {Valero, Daniel and Chanson, Hubert and Bung, Daniel B.}, title = {Robust estimators for turbulence properties assessment}, pages = {1 -- 24}, year = {2019}, language = {en} } @article{ValeroBungCrookston2019, author = {Valero, D. and Bung, Daniel B. and Crookston, B. M.}, title = {Closure to "Energy Dissipation of a Type III Basin under Design and Adverse Conditions for Stepped and Smooth Spillways"}, series = {Journal of Hydraulic Engineering}, volume = {146}, journal = {Journal of Hydraulic Engineering}, number = {2}, publisher = {ASCE}, address = {Reston, Va.}, doi = {10.1061/(ASCE)HY.1943-7900.0001669}, year = {2019}, language = {en} } @inproceedings{UlmerBraunLaietal.2019, author = {Ulmer, Jessica and Braun, Sebastian and Lai, Chow Yin and Cheng, Chi-Tsun and Wollert, J{\"o}rg}, title = {Generic integration of VR and AR in product lifecycles based on CAD models}, series = {Proceedings of The 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019}, booktitle = {Proceedings of The 23rd World Multi-Conference on Systemics, Cybernetics and Informatics: WMSCI 2019}, year = {2019}, language = {en} } @article{TurlybekulyPogrebnjakSukhodubetal.2019, author = {Turlybekuly, Amanzhol and Pogrebnjak, Alexander and Sukhodub, L. F. and Sukhodub, Liudmyla B. and Kistaubayeva, A. S. and Savitskaya, Irina and Shokatayeva, D. H. and Bondar, Oleksandr V. and Shaimardanov, Z. K. and Plotnikov, Sergey V. and Shaimardanova, B. H. and Digel, Ilya}, title = {Synthesis, characterization, in vitro biocompatibility and antibacterial properties study of nanocomposite materials based on hydroxyapatite-biphasic ZnO micro- and nanoparticles embedded in Alginate matrix}, series = {Materials Science and Engineering C}, volume = {104}, journal = {Materials Science and Engineering C}, number = {Article number 109965}, publisher = {Elsevier}, address = {Amsterdam}, doi = {10.1016/j.msec.2019.109965}, year = {2019}, language = {en} } @inproceedings{TullisCrookstonBung2019, author = {Tullis, Blake P. and Crookston, Brian M. and Bung, Daniel B.}, title = {Weir head-discharge relationships: A multi-lab exercise}, series = {E-proceedings of the 38th IAHR World Congress September 1-6, 2019, Panama City, Panama}, booktitle = {E-proceedings of the 38th IAHR World Congress September 1-6, 2019, Panama City, Panama}, pages = {1 -- 15}, year = {2019}, language = {en} } @phdthesis{Tran2019, author = {Tran, Ngoc Trinh}, title = {Limit and Shakedown analysis of structures under stochastic conditions}, publisher = {Technische Universit{\"a}t Braunschweig}, address = {Braunschweig}, doi = {10.24355/dbbs.084-201902121135-0}, pages = {166 S.}, year = {2019}, language = {en} } @incollection{TippkoetterMoehringRothetal.2019, author = {Tippk{\"o}tter, Nils and M{\"o}hring, Sophie and Roth, Jasmine and Wulfhorst, Helene}, title = {Logistics of lignocellulosic feedstocks: preprocessing as a preferable option}, series = {Biorefineries}, booktitle = {Biorefineries}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-97117-9}, doi = {10.1007/10_2017_58}, pages = {43 -- 68}, year = {2019}, abstract = {In comparison to crude oil, biorefinery raw materials are challenging in concerns of transport and storage. The plant raw materials are more voluminous, so that shredding and compacting usually are necessary before transport. These mechanical processes can have a negative influence on the subsequent biotechnological processing and shelf life of the raw materials. Various approaches and their effects on renewable raw materials are shown. In addition, aspects of decentralized pretreatment steps are discussed. Another important aspect of pretreatment is the varying composition of the raw materials depending on the growth conditions. This problem can be solved with advanced on-site spectrometric analysis of the material.}, language = {en} } @article{ThomaRavi2019, author = {Thoma, Andreas and Ravi, Sridhar}, title = {Significance of parallel computing on the performance of Digital Image Correlation algorithms in MATLAB}, pages = {1 -- 17}, year = {2019}, abstract = {Digital Image Correlation (DIC) is a powerful tool used to evaluate displacements and deformations in a non-intrusive manner. By comparing two images, one of the undeformed reference state of a specimen and another of the deformed target state, the relative displacement between those two states is determined. DIC is well known and often used for post-processing analysis of in-plane displacements and deformation of specimen. Increasing the analysis speed to enable real-time DIC analysis will be beneficial and extend the field of use of this technique. Here we tested several combinations of the most common DIC methods in combination with different parallelization approaches in MATLAB and evaluated their performance to determine whether real-time analysis is possible with these methods. To reflect improvements in computing technology different hardware settings were also analysed. We found that implementation problems can reduce the efficiency of a theoretically superior algorithm such that it becomes practically slower than a suboptimal algorithm. The Newton-Raphson algorithm in combination with a modified Particle Swarm algorithm in parallel image computation was found to be most effective. This is contrary to theory, suggesting that the inverse-compositional Gauss-Newton algorithm is superior. As expected, the Brute Force Search algorithm is the least effective method. We also found that the correct choice of parallelization tasks is crucial to achieve improvements in computing speed. A poorly chosen parallelisation approach with high parallel overhead leads to inferior performance. Finally, irrespective of the computing mode the correct choice of combinations of integerpixel and sub-pixel search algorithms is decisive for an efficient analysis. Using currently available hardware realtime analysis at high framerates remains an aspiration.}, language = {en} }