Robust and real-time control of magnetic bearings for space engines

Currently, NASA Lewis Research Center is developing magnetic bearings for Space Shuttle Main Engine (SSME) turbopumps. The control algorithms which have been used are based on either the proportional-intergral-derivative control (PID) approach or the linear quadratic (LQ) state space approach. These approaches lead to an acceptable performance only when the system model is accurately known, which is seldom true in practice. For example, the rotor eccentricity, which is a major source of vibration at high speeds, cannot be predicted accurately. Furthermore, the dynamics of a rotor shaft, which must be treated as a flexible system to model the elastic rotor shaft, is infinite dimensional in theory and the controller can only be developed on the basis of a finite number of modes. Therefore, the development of the control system is further complicated by the possibility of closed loop system instability because of residual or uncontrolled modes, the so called spillover problem. Consequently, novel control algorithms for magnetic bearings are being developed to be robust to inevitable parametric uncertainties, external disturbances, spillover phenomenon and noise. Also, as pointed out earlier, magnetic bearings must exhibit good performance at a speed over 30,000 rpm. This implies that the sampling period available for the design of a digital control system has to be of the order of 0.5 milli-seconds. Therefore, feedback coefficients and other required controller parameters have to be computed off-line so that the on-line computational burden is extremely small. The development of the robust and real-time control algorithms is based on the sliding mode control theory. In this method, a dynamic system is made to move along a manifold of sliding hyperplanes to the origin of the state space. The number of sliding hyperplanes equals that of actuators. The sliding mode controller has two parts; linear state feedback and nonlinear terms. The nonlinear terms guarantee that the systems would reach the intersection of all sliding hyperplanes and remain on it when bounds on the errors in the system parameters and external disturbances are known. The linear part of the control drives the system to the origin of state space. Another important feature is that the controller parameter can be computed off-line. Consequently, on-line computational burden is small

Validating soil denitrification models based on laboratory N2 and N2O fluxes and underlying processes derived by stable isotope approaches: concept, methods and regulation of measured fluxes

Robust denitrification data suitable to validate soil N2 fluxes in denitrification models are scarce due to methodical limitations and the extreme spatio-temporal heterogeneity of denitrification in soils. Numerical models have become essential tools to predict denitrification at different scales. Model performance could either be tested for total gaseous flux (NO + N2O + N2), individual denitrification products (e.g. N2O and/or NO) or for the effect of denitrification factors (e.g. C-availability, respiration, diffusivity, anaerobic volume, etc.). While there are numerous examples for validating N2O fluxes, there are neither robust field data of N2 fluxes nor sufficiently resolved measurements of control factors used as state variables in the models. Here we present the concept, methods and first results of collecting model validation data. This is part of the coordinated research unit “Denitrification in Agricultural Soils: Integrated Control and Modelling at Various Scales” (DASIM). Novel approaches are used including analysis of stable isotopes, microbial communities, pore structure and organic matter fractions to provide denitrification data sets comprising as much detail on activity and regulation as possible. This will be the basis to validate existing and calibrate new denitrification models that are applied and/or developed by DASIM subprojects. To allow model testing in a wide range of conditions, denitrification control factors are varied in the initial settings (pore volume, plant residues, mineral N, pH) but also over time, where moisture, temperature, and mineral N are manipulated according to typical time patterns in the field. This is realized by including precipitation events, fertilization (via irrigation), drainage (via water potential) and temperature in the course of incubations. Moreover, oxygen concentration is varied to simulate anaerobic events. The 15N gas flux method is employed to quantify N2 and N2O emissions from various pools and processes

Psychosocial stress impairs working memory at high loads: an association with cortisol levels and memory retrieval.

De samenhang tussen somatische en psychische (dys)functie

Charged Particles in a 2+1 Curved Background

The coupling to a 2+1 background geometry of a quantized charged test particle in a strong magnetic field is analyzed. Canonical operators adapting to the fast and slow freedoms produce a natural expansion in the inverse square root of the magnetic field strength. The fast freedom is solved to the second order. At any given time, space is parameterized by a couple of conjugate operators and effectively behaves as the `phase space' of the slow freedom. The slow Hamiltonian depends on the magnetic field norm, its covariant derivatives, the scalar curvature and presents a peculiar coupling with the spin-connection.Comment: 22 page

Phase-transformation and precipitation kinetics in vanadium micro-alloyed steels by in-situ, simultaneous neutron diffraction and SANS

In-situ Neutron Diffraction and Small-Angle Neutron Scattering (SANS) are employed for the first time simultaneously in order to reveal the interaction between the austenite to ferrite phase transformation and the precipitation kinetics during isothermal annealing at 650 and at 700 °C in three steels with different vanadium (V) and carbon (C) concentrations. Austenite-to-ferrite phase transformation is observed in all three steels at both temperatures. The phase transformation is completed during a 10 h annealing treatment in all cases. The phase transformation is faster at 650 than at 700 °C for all alloys. Additions of vanadium and carbon to the steel composition cause a retardation of the phase transformation. The effect of each element is explained through its contribution to the Gibbs free energy dissipation. The austenite-to-ferrite phase transformation is found to initiate the vanadium carbide precipitation. Larger and fewer precipitates are detected at 700 than at 650 °C in all three steels, and a larger number density of precipitates is detected in the steel with higher concentrations of vanadium and carbon. After 10 h of annealing, the precipitated phase does not reach the equilibrium fraction as calculated by ThermoCalc. The external magnetic field applied during the experiments, necessary for the SANS measurements, causes a delay in the onset and time evolution of the austenite-to-ferrite phase transformation and consequently on the precipitation kinetics