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Type: Text × Subject: Stabilization ×

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    Topological boundaries between helical domains as a nucleation source of skyrmions in the bulk cubic helimagnet Cu2OSeO3
    (College Park, MD : APS, 2022) Leonov, A.O.; Pappas, C.
    Cu2OSeO3 represents a unique example in the family of B20 cubic helimagnets with a tilted spiral and a low-temperature skyrmion phase arising for magnetic fields applied along the easy crystallographic (100) axes. Although the stabilization mechanism of these phases can be accounted for by cubic magnetic anisotropy, the skyrmion nucleation process is still an open question, since the stability region of the skyrmion phase displays strongly hysteretic behavior with different phase boundaries for increasing and decreasing magnetic fields. Here, we address this important point using micromagnetic simulations and come to the conclusion that skyrmion nucleation is underpinned by the reorientation of spiral domains occurring near the critical magnetic fields of the phase diagrams: HC1, the critical field of the transition between the helical and conical/tiled spiral phase, and HC2, the critical field between the conical/tiled spiral and the homogenous phase. By studying a wide variety of cases we show that domain walls may have a 3D structure. Moreover, they can carry a finite topological charge stemming from half-skyrmions (merons) also permitting along-the-field and perpendicular-to-the-field orientation. Thus, domain walls may be envisioned as nucleation source of skyrmions that can form thermodynamically stable and metastable lattices as well as skyrmion networks with misaligned skyrmion tubes. The results of numerical simulations are discussed in view of recent experimental data on chiral magnets, in particular, for the bulk cubic helimagnet Cu2OSeO3.
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    Low-stabilisation scenarios and technologies for carbon capture and sequestration
    (Amsterdam : Elsevier, 2009) Bauer, N.; Edenhofer, O.; Leimbach, M.
    Endogenous technology scenarios for meeting low stabilization CO2 targets are derived in this study and assessed regarding emission reductions and mitigation costs. The aim is to indentify the most important technology options for achieving low stabilization targets. The significance of an option is indicated by its achieved emission reduction and the mitigation cost increase, if this option were not available. Quantitative results are computed using a global multi-regional hard-linked hybrid model that integrates the economy, the energy sector and the climate system. The model endogenously determines the optimal deployment of technologies subject to a constraint on climate change. The alternative options in the energy sector comprise the most important mitigation technologies: renewables, biomass, nuclear, carbon capture and sequestration (CCS), and biomass with CCS as well as energy efficiency improvements. The results indicate that the availability of CCS technologies and espec. biomass with CCS is highly desirable for achieving low stabilization goals at low costs. The option of nuclear energy is different: although it could play an important role in the primary energy mix, mitigation costs would only mildly increase, if it could not be expanded. Therefore, in order to promote prudent climate change mitigation goals, support of CCS technologies reduces the costs and-thus-is desirable from a social point of view. © 2009 Elsevier Ltd. All rights reserved.
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    Joint model of probabilistic-robust (probust) constraints with application to gas network optimization
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2018) Adelhütte, Dennis; Aßmann, Denis; Grandón, Tatiana González; Gugat, Martin; Heitsch, Holger; Henrion, René; Liers, Frauke; Nitsche, Sabrina; Schultz, Rüdiger; Stingl, Michael; Wintergerst, David
    Optimization problems under uncertain conditions abound in many real-life applications. While solution approaches for probabilistic constraints are often developed in case the uncertainties can be assumed to follow a certain probability distribution, robust approaches are usually applied in case solutions are sought that are feasible for all realizations of uncertainties within some predefined uncertainty set. As many applications contain different types of uncertainties that require robust as well as probabilistic treatments, we introduce a class of joint probabilistic/robust constraints. Focusing on complex uncertain gas network optimization problems, we show the relevance of this class of problems for the task of maximizing free booked capacities in an algebraic model for a stationary gas network. We furthermore present approaches for finding their solution. Finally, we study the problem of controlling a transient system that is governed by the wave equation. The task consists in determining controls such that a certain robustness measure remains below some given upper bound with high probability.
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    Joint Model of Probabilistic-Robust (Probust) Constraints Applied to Gas Network Optimization
    (Singapore : Springer, 2020) Adelhütte, Dennis; Aßmann, Denis; Grandòn, Tatiana Gonzàlez; Gugat, Martin; Heitsch, Holger; Henrion, René; Liers, Frauke; Nitsche, Sabrina; Schultz, Rüdiger; Stingl, Michael; Wintergerst, David
    Optimization problems under uncertain conditions abound in many real-life applications. While solution approaches for probabilistic constraints are often developed in case the uncertainties can be assumed to follow a certain probability distribution, robust approaches are usually applied in case solutions are sought that are feasible for all realizations of uncertainties within some predefined uncertainty set. As many applications contain different types of uncertainties that require robust as well as probabilistic treatments, we deal with a class of joint probabilistic/robust constraints. Focusing on complex uncertain gas network optimization problems, we show the relevance of this class of problems for the task of maximizing free booked capacities in an algebraic model for a stationary gas network. We furthermore present approaches for finding their solution. Finally, we study the problem of controlling a transient system that is governed by the wave equation. The task consists in determining controls such that a certain robustness measure remains below some given upper bound with high probability.