The LDCM actuator for vibration suppression

A linear dc motor (LDCM) has been proposed as an actuator for the COFS I mast and the COFS program ground test Mini-Mast. The basic principles of operation of the LDCM as an actuator for vibration suppression in large flexible structures are reviewed. Because of force and stroke limitations, control loops are required to stabilize the actuator, which results in a non-standard actuator-plant configuration. A simulation model that includes LDCM actuator control loops and a finite element model of the Mast is described, with simulation results showing the excitation capability of the actuator

Approximation of Bayesian inverse problems for PDEs

Inverse problems are often ill posed, with solutions that depend sensitively on data. In any numerical approach to the solution of such problems, regularization of some form is needed to counteract the resulting instability. This paper is based on an approach to regularization, employing a Bayesian formulation of the problem, which leads to a notion of well posedness for inverse problems, at the level of probability measures. The stability which results from this well posedness may be used as the basis for quantifying the approximation, in finite dimensional spaces, of inverse problems for functions. This paper contains a theory which utilizes this stability property to estimate the distance between the true and approximate posterior distributions, in the Hellinger metric, in terms of error estimates for approximation of the underlying forward problem. This is potentially useful as it allows for the transfer of estimates from the numerical analysis of forward problems into estimates for the solution of the related inverse problem. It is noteworthy that, when the prior is a Gaussian random field model, controlling differences in the Hellinger metric leads to control on the differences between expected values of polynomially bounded functions and operators, including the mean and covariance operator. The ideas are applied to some non-Gaussian inverse problems where the goal is determination of the initial condition for the Stokes or Navier–Stokes equation from Lagrangian and Eulerian observations, respectively

Existence and uniqueness for four-dimensional variational data assimilation in discrete time

Variational techniques for data assimilation, i.e., estimating orbits of dynamical models from observations, are revisited. It is shown that under mild hypotheses a solution to this variational problem exists. Using ideas from optimal control theory, the problem of uniqueness is investigated and a number of results (well known from optimal control) are established in the present context. The value function is introduced as the minimal cost over all feasible trajectories starting from a given initial condition. By combining the necessary conditions with an envelope theorem, it is shown that the solution is unique if and only if the value function has a derivative at the given initial condition. Further, the value function is Lipschitz and hence has a derivative for almost all (with respect to the Lebesgue measure) initial conditions. Several examples are studied which demonstrate that points of nondifferentiability of the value function (and hence nonuniqueness of solutions) are nevertheless to be expected in practice

Between redeemer and work of the devil: The transnational Brazilian biofuel discourse

Biofuels have been the subject of heated political discussions, but also of a growing literature on discourses and environmental policies. Previous studies on the issue have, however, neglected the fact that the different discourses about on biofuels are increasingly crossing national boundaries, i.e., that there is a tendency toward transnationalization. In the light of this development the present article analyzes the transnational Brazilian biofuel discourse in the period 2005–2011 with a special emphasis on actors from Brazil, the EU and the USA. By conducting a discourse analysis along the lines of Hajer, five discourse coalitions can be distinguished, each providing a different view on the opportunities, problems and perspectives of biofuel production in Brazil. It is observed that the long-established hegemony of the discourse coalition of biofuel supporters was successfully challenged by a more critical position during the food crisis of 2007/2008. As a result, the discourse coalition of critical supporters—which was committed to sustainable biofuel production via political regulation—prevailed in the transnational Brazilian biofuel discourse and its position was translated into policy measures

Advancing research on climate change, conflict and migration

Policy makers across the entire globe have repetitively expressed concern about climate change as a trigger of mass migration and increased political instability. Recent research on both climate-conflict and climatemigration linkages has gained significant attention in the scientific and public debate. Both research fields are deeply intertwined and share some common characteristics. They also have been rapidly evolving during the past years with major achievements being made. Perhaps most importantly, an improved understanding of the role of (potential) climate change impacts in migration and conflicts has been achieved, which has been essential for moving beyond environmental determinism toward a more nuanced exploration of the interlinkages between climate, conflict and migration. Yet, significant conversations and uncertainties continue to exist, hence indicating the urgent need for further advances in these fields. Here, we debate cross-cutting and common pitfalls in both research fields and their implications for policy and research. These pitfalls include (i) insufficient attention to context factors and causal chains, (ii) underestimation of complex spatio-temporal patterns, (iii) discrepancies between quantitative and qualitative evidence, (iv) the non-consideration of adaptation strategies, and (v) a narrow spectrum of methods. We illustrate best practices and suggest ways to move the debate forward

Earthquake forecasting based on data assimilation: sequential Monte Carlo methods for renewal point processes

Data assimilation is routinely employed in meteorology, engineering and computer sciences to optimally combine noisy observations with prior model information for obtaining better estimates of a state, and thus better forecasts, than achieved by ignoring data uncertainties. Earthquake forecasting, too, suffers from measurement errors and partial model information and may thus gain significantly from data assimilation. We present perhaps the first fully implementable data assimilation method for earthquake forecasts generated by a point-process model of seismicity. We test the method on a synthetic and pedagogical example of a renewal process observed in noise, which is relevant for the seismic gap hypothesis, models of characteristic earthquakes and recurrence statistics of large quakes inferred from paleoseismic data records. To address the non-Gaussian statistics of earthquakes, we use sequential Monte Carlo methods, a set of flexible simulation-based methods for recursively estimating arbitrary posterior distributions. We perform extensive numerical simulations to demonstrate the feasibility and benefits of forecasting earthquakes based on data assimilation

Successive phase transitions to antiferromagnetic and weak-ferromagnetic long-range orders in quasi-one-dimensional antiferromagnet Cu3_3Mo2_2O9_9

Investigation of the magnetism of Cu$_3$Mo$_2$O$_9$ single crystal, which has antiferromagnetic (AF) linear chains interacting with AF dimers, reveals an AF second-order phase transition at $T_{\rm N} = 7.9$ K. Although weak ferromagnetic-like behavior appears at lower temperatures in low magnetic fields, complete remanent magnetization cannot be detected down to 0.5 K. However, a jump is observed in the magnetization below weak ferromagnetic (WF) phase transition at $T_{\rm c} \simeq 2.5$ K when a tiny magnetic field along the a axis is reversed, suggesting that the coercive force is very weak. A component of magnetic moment parallel to the chain forms AF long-range order (LRO) below $T_{\rm N}$, while a perpendicular component is disordered above $T_{\rm c}$ at zero magnetic field and forms WF-LRO below $T_{\rm c}$. Moreover, the WF-LRO is also realized with applying magnetic fields even between $T_{\rm c}$ and $T_{\rm N}$. These results are explainable by both magnetic frustration among symmetric exchange interactions and competition between symmetric and asymmetric Dzyaloshinskii-Moriya exchange interactions.Comment: 7 pages, 7 figure