@incollection{StadlerBauerBudtetal., author = {Stadler, Ingo and Bauer, Franz and Budt, Marcus and Heindl, Eduard and Wolf, Daniel}, title = {Mechanical Energy Storage}, series = {Handbook of Energy Storage}, booktitle = {Handbook of Energy Storage}, editor = {Sterner, Michael and Stadler, Ingo}, publisher = {Springer Berlin Heidelberg}, address = {Berlin, Heidelberg}, isbn = {978-3-662-55503-3}, doi = {10.1007/978-3-662-55504-0_9}, pages = {483 -- 561}, abstract = {Chemical-energy storage systems use caverns, porous storage facilities, tanks, and storage rooms to store chemical energy sources. Caverns, caves, and reservoirs can also be used to store gaseous media such as air, liquid media such as water, and solid media such as rock. The principles of mechanical energy storage are based on classical Newtonian mechanics, or in other words on fundamental physics from the eighteenth and nineteenth centuries. As a result, these types of storage are typically divided into two categories; storage of kinetic and potential energy, or storage of 'pressure energy'. In this chapter, storage media is categorized by its aggregate state, and described by its function and application: first compressed air energy storage and then conventional electricity storage—pumped-storage plants. The chapter continues with a discussion of innovative methods of storing potential energy using water as a medium. These include artificially constructed pumped storage, pumped storage in the open sea, dam storage on rivers, pumped storage on heaps in repurposed mining areas, underfloor or underground pumped storage, and surface mine storage. The chapter concludes with a description of classical and modern flywheel energy storage systems. This age-old technology is then compared with a new concept: mechanical stored energy exploiting both pumped storage and change in the potential energy of rocks or large boulders.}, language = {en} } @incollection{StadlerBauerBudtetal., author = {Stadler, Ingo and Bauer, Franz and Budt, Marcus and Heindl, Eduard and Wolf, Daniel}, title = {Mechanische Energiespeicher}, series = {Energiespeicher - Bedarf, Technologien, Integration}, booktitle = {Energiespeicher - Bedarf, Technologien, Integration}, edition = {2. Auflage}, publisher = {Springer Vieweg}, address = {Berlin ; Heidelberg}, isbn = {978-3-662-48893-5}, doi = {10.1007/978-3-662-48893-5_9}, pages = {495 -- 577}, language = {de} } @article{FranzWolfPeriyasamyetal., author = {Franz, Maja and Wolf, Lucas and Periyasamy, Maniraman and Ufrecht, Christian and Scherer, Daniel D. and Plinge, Axel and Mutschler, Christopher and Mauerer, Wolfgang}, title = {Uncovering Instabilities in Variational-Quantum Deep Q-Networks}, series = {Journal of the Franklin Institute}, journal = {Journal of the Franklin Institute}, edition = {In Press, Corrected Proof}, publisher = {Elsevier}, issn = {0016-0032}, doi = {10.1016/j.jfranklin.2022.08.021}, abstract = {Deep Reinforcement Learning (RL) has considerably advanced over the past decade. At the same time, state-of-the-art RL algorithms require a large computational budget in terms of training time to converge. Recent work has started to approach this problem through the lens of quantum computing, which promises theoretical speed-ups for several traditionally hard tasks. In this work, we examine a class of hybrid quantumclassical RL algorithms that we collectively refer to as variational quantum deep Q-networks (VQ-DQN). We show that VQ-DQN approaches are subject to instabilities that cause the learned policy to diverge, study the extent to which this afflicts reproduciblity of established results based on classical simulation, and perform systematic experiments to identify potential explanations for the observed instabilities. Additionally, and in contrast to most existing work on quantum reinforcement learning, we execute RL algorithms on an actual quantum processing unit (an IBM Quantum Device) and investigate differences in behaviour between simulated and physical quantum systems that suffer from implementation deficiencies. Our experiments show that, contrary to opposite claims in the literature, it cannot be conclusively decided if known quantum approaches, even if simulated without physical imperfections, can provide an advantage as compared to classical approaches. Finally, we provide a robust, universal and well-tested implementation of VQ-DQN as a reproducible testbed for future experiments.}, language = {en} } @incollection{ScholzKrenkelTerekhovetal., author = {Scholz, Alexander-Wigbert K. and Krenkel, Lars and Terekhov, Maxim and Friedrich, Janet and Rivoire, Julien and K{\"o}brich, Rainer and Wolf, Ursula and Kalthoff, Daniel and David, Matthias and Wagner, Claus and Schreiber, Laura Maria}, title = {Magnetic Resonance Imaging and Computational Fluid Dynamics of High Frequency Oscillatory Ventilation (HFOV)}, series = {Fundamental Medical and Engineering Investigations on Protective Artificial Respiration}, volume = {116}, booktitle = {Fundamental Medical and Engineering Investigations on Protective Artificial Respiration}, editor = {Hirschel, Ernst Heinrich and Schr{\"o}der, Wolfgang and Fujii, Kozo and Haase, Werner and Leer, Bram and Leschziner, Michael A. and Pandolfi, Maurizio and Periaux, Jacques and Rizzi, Arthur and Roux, Bernard and Shokin, Yurii I. and Klaas, Michael and Koch, Edmund and Schr{\"o}der, Wolfgang}, publisher = {Springer}, address = {Berlin, Heidelberg}, isbn = {978-3-642-20325-1}, doi = {10.1007/978-3-642-20326-8_7}, pages = {107 -- 128}, abstract = {In order to better understand the mechanisms of gas transport during High Frequency Oscillatory Ventilation (HFOV) Magnetic Resonance Imaging (MRI) with contrast gases and numerical flow simulations based on Computational Fluid Dynamics(CFD) methods are performed. Validation of these new techniques is conducted by comparing the results obtained with simplified models of the trachea and a first lung bifurcation as well as in a cast model of the upper central airways with results achieved from conventional fluid mechanical measurement techniques like e.g. Laser Doppler Anemometry (LDA). Further it is demonstrated that MRI of experimental HFOV is feasible and that Hyperpolarized 3He allows for imaging the gas re-distribution inside the lung. Finally, numerical results of oscillatory flow in a 3rd generation model of the lung as well as the impact of endotracheal tubes on the flow regime development in a trachea model are presented.}, language = {en} }