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search.filters.applied.f.access: openAccess × End date: 2019 × Start date: 2014 × Type: Report ×

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Now showing 1 - 10 of 821
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    Direct transfer of magnetic sensor devices to elastomeric supports for stretchable electronics
    (Hoboken, NJ : Wiley, 2015) Melzer, Michael; Karnaushenko, Daniil; Lin, Gungun; Baunack, Stefan; Makarov, Denys; Schmidt, Oliver G.
    A novel fabrication method for stretchable magnetoresistive sensors is introduced, which allows the transfer of a complex microsensor systems prepared on common rigid donor substrates to prestretched elastomeric membranes in a single step. This direct transfer printing method boosts the fabrication potential of stretchable magnetoelectronics in terms of miniaturization and level of complexity, and provides strain‐invariant sensors up to 30% tensile deformation.
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    Biomimetic microelectronics for regenerative neuronal cuff implants
    (Hoboken, NJ : Wiley, 2015) Karnaushenko, Daniil; Münzenrieder, Niko; Karnaushenko, Dmitriy D.; Koch, Britta; Meyer, Anne K.; Baunack, Stefan; Petti, Luisa; Tröster, Gerhard; Makarov, Denys; Schmidt, Oliver G.
    Smart biomimetics, a unique class of devices combining the mechanical adaptivity of soft actuators with the imperceptibility of microelectronics, is introduced. Due to their inherent ability to self‐assemble, biomimetic microelectronics can firmly yet gently attach to an inorganic or biological tissue enabling enclosure of, for example, nervous fibers, or guide the growth of neuronal cells during regeneration.
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    Self‐assembled on‐chip‐integrated giant magneto‐impedance sensorics
    (Hoboken, NJ : Wiley, 2015) Karnaushenko, Daniil; Karnaushenko, Dmitriy D.; Makarov, Denys; Baunack, Stefan; Schäfer, Rudolf; Schmidt, Oliver G.
    A novel method relying on strain engineering to realize arrays of on‐chip‐integrated giant magneto‐impedance (GMI) sensors equipped with pick‐up coils is put forth. The geometrical transformation of an initially planar layout into a tubular 3D architecture stabilizes favorable azimuthal magnetic domain patterns. This work creates a solid foundation for further development of CMOS compatible GMI sensorics for magnetoencephalography.
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    High-performance magnetic sensorics for printable and flexible electronics
    (Hoboken, NJ : Wiley, 2014) Karnaushenko, Daniil; Makarov, Denys; Stöber, Max; Karnaushenko, Dmitriy D.; Baunack, Stefan; Schmidt, Oliver G.
    High‐performance giant magnetoresistive (GMR) sensorics are realized, which are printed at predefined locations on flexible circuitry. Remarkably, the printed magnetosensors remain fully operational over the complete consumer temperature range and reveal a giant magnetoresistance up to 37% and a sensitivity of 0.93 T−1 at 130 mT. With these specifications, printed magnetoelectronics can be controlled using flexible active electronics for the realization of smart packaging and energy‐efficient switches.
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    Mathematical modeling and numerical simulations of diode lasers with micro-integrated external resonators
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2016) Radziunas, Mindaugas
    This report summarizes our scientific activities within the project MANUMIEL (BMBF Program “Förderung der Wissenschaftlich-Technologischen Zusammenarbeit (WTZ) mit der Republik Moldau”, FKZ 01DK13020A). Namely, we discuss modeling of external cavity diode lasers, numerical simulations and analysis of these devices using the software package LDSL-tool, as well as the development of this software.
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    Calibration methods for gas turbine performance models
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2016) Borchardt, Jürgen; Mathé, Peter; Printsypar, Galina
    The WIAS software package BOP is used to simulate gas turbine models. In order to make accurate predictions the underlying models need to be calibrated. This study compares different strategies of model calibration. These are the deterministic optimization tools as nonlinear least squares (MSO) and the sparsity promoting variant LASSO, but also the probabilistic (Bayesian) calibration. The latter allows for the quantification of the inherent uncertainty, and it gives rise to a surrogate uncertainty measure in the MSO tool. The implementation details are accompanied with a numerical case study, which highlights the advantages and drawbacks of each of the proposed calibration methods.
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    Type II singular perturbation approximation for linear systems with Lévy noise
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2017) Redmann, Martin
    When solving linear stochastic partial differential equations numerically, usually a high order spatial discretisation is needed. Model order reduction (MOR) techniques are often used to reduce the order of spatially-discretised systems and hence reduce computational complexity. A particular MOR technique to obtain a reduced order model (ROM) is singular perturbation approximation (SPA), a method which has been extensively studied for deterministic systems. As so-called type I SPA it has already been extended to stochastic equations. We provide an alternative generalisation of the deterministic setting to linear systems with Lévy noise which is called type II SPA. It turns out that the ROM from applying type II SPA has better properties than the one of using type I SPA. In this paper, we provide new energy interpretations for stochastic reachability Gramians, show the preservation of mean square stability in the ROM by type II SPA and prove two different error bounds for type II SPA when applied to Lévy driven systems.
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    Towards time-limited H2-optimal model order reduction
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2017) Goyal, Pawan; Redmann, Martin
    In order to solve partial differential equations numerically and accurately, a high order spatial discretization is usually needed. Model order reduction (MOR) techniques are often used to reduce the order of spatially-discretized systems and hence reduce computational complexity. A particular class of MOR techniques are H2-optimal methods such as the iterative rational Krylov subspace algorithm (IRKA) and related schemes. However, these methods are used to obtain good approximations on a infinite time-horizon. Thus, in this work, our main goal is to discuss MOR schemes for time-limited linear systems. For this, we propose an alternative time-limited H2-norm and show its connection with the time-limited Gramians. We then provide first-order optimality conditions for an optimal reduced order model (ROM) with respect to the time-limited H2-norm. Based on these optimality conditions, we propose an iterative scheme which upon convergences aims at satisfying these conditions. Then, we analyze how far away the obtained ROM is from satisfying the optimality conditions.We test the efficiency of the proposed iterative scheme using various numerical examples and illustrate that the newly proposed iterative method can lead to a better reduced-order compared to unrestricted IRKA in the time interval of interest.