Benchmarking of Flatness-based Control of the Heat Equation

Flatness-based control design is a well established method to generate open-loop control signals. Several articles discuss the application of flatness-based control design of (reaction-) diffusion problems for various scenarios. Beside the pure analytical derivation also the numerical computation of the input signal is crucial to yield a reliable trajectory planning. Therefore, we derive the input signal step-by-step and describe the influence of system and controller parameters on the computation of the input signal. In particular, we benchmark the control design of the one-dimensional heat equation with Neumann-type boundary actuation for pure aluminum and steel 38Si7, and discuss the applicability of the found input signals for realistic scenarios.Comment: 9 Pages, 13 Figure

Eine universelle Erfahrung? Rezension zu "Flucht. Eine Menschheitsgeschichte" von Andreas Kossert

Andreas Kossert: Flucht: Eine Menschheitsgeschichte. München: Siedler 2020. 978-3-8275-0091-

SU(2) chiral perturbation theory low-energy constants from 2+1 flavor staggered lattice simulations

We extract the next-to-leading-order low-energy constants \bar\ell_3 and \bar\ell_4 of SU(2) chiral perturbation theory, based on precise lattice data for the pion mass and decay constant on ensembles generated by the Wuppertal-Budapest Collaboration for QCD thermodynamics. These ensembles feature 2+1 flavors of two-fold stout-smeared dynamical staggered fermions combined with Symanzik glue, with pion masses varying from 135 to 435 MeV, lattice scales between 0.7 and 2.0 GeV, while m_s is kept fixed at its physical value. Moderate taste splittings and the scale being set through the pion decay constant allow us to restrict ourselves to the taste pseudoscalar state and to use formulas from continuum chiral perturbation theory. Finally, by dropping the data points near 135 MeV from the fits, we can explore the range of pion masses that is needed in SU(2) chiral perturbation theory to reliably extrapolate to the physical point.Comment: 40 pages, 22 figures, 3 tables; v2: expanded discussion, matches published versio

Determination of SU(2) ChPT LECs from 2+1 flavor staggered lattice simulations

By fitting pion masses and decay constants from 2+1 flavor staggered lattice simulations to the predictions of NLO and NNLO SU(2) chiral perturbation theory we determine the low-energy constants l_3 and l_4. The lattice ensembles were generated by the Wuppertal-Budapest collaboration and cover pion masses in the range of 135 to 435 MeV and lattice scales between 0.7 and 2.0 GeV. By choosing a suitable scaling trajectory, we were able to demonstrate that precise and stable results for the LECs can be obtained from continuum ChPT to NLO. The pion masses available in this work also allow us to study the applicability of using ChPT to extrapolate from higher masses to the physical pion mass.Comment: 8 pages, 8 figures, 1 table, talk presented at Xth Quark Confinement and the Hadron Spectrum, Munich, October 201

Targeted Adversarial Attacks on Wind Power Forecasts

In recent years, researchers proposed a variety of deep learning models for wind power forecasting. These models predict the wind power generation of wind farms or entire regions more accurately than traditional machine learning algorithms or physical models. However, latest research has shown that deep learning models can often be manipulated by adversarial attacks. Since wind power forecasts are essential for the stability of modern power systems, it is important to protect them from this threat. In this work, we investigate the vulnerability of two different forecasting models to targeted, semitargeted, and untargeted adversarial attacks. We consider a Long Short-Term Memory (LSTM) network for predicting the power generation of a wind farm and a Convolutional Neural Network (CNN) for forecasting the wind power generation throughout Germany. Moreover, we propose the Total Adversarial Robustness Score (TARS), an evaluation metric for quantifying the robustness of regression models to targeted and semi-targeted adversarial attacks. It assesses the impact of attacks on the model's performance, as well as the extent to which the attacker's goal was achieved, by assigning a score between 0 (very vulnerable) and 1 (very robust). In our experiments, the LSTM forecasting model was fairly robust and achieved a TARS value of over 0.81 for all adversarial attacks investigated. The CNN forecasting model only achieved TARS values below 0.06 when trained ordinarily, and was thus very vulnerable. Yet, its robustness could be significantly improved by adversarial training, which always resulted in a TARS above 0.46.Comment: 20 pages, including appendix, 12 figure

Leptonic decay-constant ratio fK/fπf_K/f_\pi from lattice QCD using 2+1 clover-improved fermion flavors with 2-HEX smearing

We present a calculation of the leptonic decay-constant ratio $f_K/f_\pi$ in 2+1 flavor QCD. Our data set includes five lattice spacings and pion masses reaching down below the physical one. Special emphasis is placed on a careful study of all systematic uncertainties, especially the continuum extrapolation. Our result is perfectly compatible with the first-row unitarity constraint of the Standard Model.Comment: 19 pages, 6 figures, 3 tables; v2: added supplementary analysis, version published in Phys. Rev.

Research on Gas Hydrate Plug Formation under Pipeline-Like Conditions

Hydrates of natural gases like methane have become subject of great interest over the last few decades, mainly because of their potential as energy resource. The exploitation of these natural gases from gas hydrates is seen as a promising mean to solve future energetic problems. Furthermore, gas hydrates play an important role in gas transportation and gas storage: in pipelines, particularly in tubes and valves, gas hydrates are formed and obstruct the gas flow. This phenomenon is called “plugging” and causes high operational expenditure as well as precarious safety conditions. In this work, research on the formation of gas hydrates under pipeline-like conditions, with the aim to predict induction times as a mean to evaluate the plugging potential, is described