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: evaluation of DailyDayCent and COUP models

Denitrification is an anaerobic key process by microbes where the NO3- is step-by-step reduced and emitted as NO, N2O and finally N2 gas from the soil. Accurate knowledge on denitrification dynamics is important because the N2O is further reduced to N2 and constitutes the main emission source of this greenhouse gas from agricultural soils. Hence, our understanding and ability to quantify soil denitrification is crucial for mitigating nitrogen fertilizer loss as well as for reducing N2O emissions. Models can be an important tool to predict mitigation effects and help to develop climate smart mitigation strategies. Ideally, commonly used biogeochemical models could provide adequate predictions of denitrification processes of agricultural soils but often simplified process descriptions and inadequate model parameters prevent models from simulating adequate fluxes of N2 and N2O on field scale. Model development and parametrization often suffers from limited availability of empirical data describing denitrification processes in agricultural soils. While in many studies N2O emissions are used to develop and train models, detailed measurements on NO, N2O, N2 fluxes and concentrations and related soil conditions are necessary to develop and test adequate model algorithms. To address this issue the coordinated research unit „Denitrification in Agricultural Soils: Integrated Control and Modelling at Various Scales (DASIM)” was initiated to more closely investigate N-fluxes caused by denitrification in response to environmental effects, soil properties and microbial communities. Here, we present how we will use these data to evaluate common biogeochemical process models (DailyDayCent, Coup) with respect to modeled NO, N2O and N2 fluxes from denitrification. The models are used with different settings. The first approximation is the basic “factory” setting of the models. The next step would show the precision in the results of the modeling after adjusting the appropriate parameters from the result of the measurement values and the “factory” results. The better adjustment and the well-controlled input and output measured parameters could provide a better understanding of the probable scantiness of the tested models which will be a basis for future model improvement

Groundwater N2O emission factors of nitrate-contaminated aquifers as derived from denitrification progress and N2O accumulation

We investigated the dynamics of denitrification and nitrous oxide (N2O) accumulation in 4 nitrate (NO3-) contaminated denitrifying sand and gravel aquifers of northern Germany (Fuhrberg, Sulingen, Thulsfelde and Gottingen) to quantify their potential N2O emission and to evaluate existing concepts of N2O emission factors. Excess N-2 - N-2 produced by denitrification - was determined by using the argon (Ar) concentration in groundwater as a natural inert tracer, assuming that this noble gas functions as a stable component and does not change during denitrification. Furthermore, initial NO3- concentrations (NO3- that enters the groundwater) were derived from excess N-2 and actual NO3- concentrations in groundwater in order to determine potential indirect N2O emissions as a function of the N input. Median concentrations of N2O and excess N-2 ranged from 3 to 89 mu g N L-1 and from 3 to 10 mg N L-1, respectively. Reaction progress (RP) of denitrification was determined as the ratio between products (N2O-N + excess N-2) and starting material (initial NO3- concentration) of the process, characterizing the different stages of denitrification. N2O concentrations were lowest at RP close to 0 and RP close to 1 but relatively high at a RP between 0.2 and 0.6. For the first time, we report groundwater N2O emission factors consisting of the ratio between N2O-N and initial NO3--N concentrations (EF1). In addition, we determined a groundwater emission factor (EF2) using a previous concept consisting of the ratio between N2O-N and actual NO3--N concentrations. Depending on RP, EF(1) resulted in smaller values compared to EF(2), demonstrating (i) the relevance of NO3- consumption and consequently (ii) the need to take initial NO3--N concentrations into account. In general, both evaluated emission factors were highly variable within and among the aquifers. The site medians ranged between 0.00043-0.00438 for EF(1) and 0.00092-0.01801 for EF(2), respectively. For the aquifers of Fuhrberg and Sulingen, we found EF(1) median values which are close to the 2006 IPCC default value of 0.0025. In contrast, we determined significant lower EF values for the aquifers of Thulsfelde and Gottingen. Summing the results up, our study supports the substantial downward revision of the IPCC default EF5-g from 0.015 (1997) to 0.0025 (2006).DF

Modelling of an imaging beamline at the ISIS pulsed neutron source

A combined neutron imaging and neutron diffraction facility, IMAT, is currently being built at the pulsed neutron spallation source ISIS in the U.K. A supermirror neutron guide is required to combine imaging and diffraction modes at the sample position in order to obtain suitable time of flight resolutions for energy selective imaging and diffraction experiments. IMAT will make use of a straight neutron guide and we consider here the optimization of the supermirror guide dimensions and characterisation of the resulting beam characteristics, including the homogeneity of the flux distribution in space and energy and the average and peak neutron fluxes. These investigations take into account some main design criteria: to maximise the neutron flux, to minimise geometrical artefacts in the open beam image at the sample position and to obtain a good energy resolution whilst retaining a large neutron bandwidth. All of these are desirable beam characteristics for the proposed imaging and diffraction analysis modes of IMAT

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

Developments in Agricultural Soil Quality and Health: Reflections by the Research Committee on Soil Organic Matter Management

The North Central Education and Research Activity Committee (NCERA-59) was formed in 1952 to address how soil organic matter formation and management practices affect soil structure and productivity. It is in this capacity that we comment on the science supporting soil quality and associated soil health assessment for agricultural lands with the goal of hastening progress in this important field. Even though the suite of soil quality indicators being applied by U.S. soil health efforts closely mirrors the “minimum data set” we developed and recommended in the mid-1990s, we question whether the methods or means for their selection and development are sufficient to meet current and emerging soil health challenges. The rush to enshrine a standard suite of dated measures may be incompatible with longer-term goals. Legitimate study of soil health considers soil change accrued over years to decades that influence on- and off-site function. Tailoring of methods to local conditions is needed to effectively apply and interpret indicators for different soil resource regions and land uses. Adherence to a set suite of methods selected by subjective criteria should be avoided, particularly when we do not yet have adequate data or agreed upon interpretive frameworks for many so-called “Tier 1” biological indicators used in soil health assessment. While pooling data collected by producer-groups is one of the most exciting new trends in soil health, standardizing methods to meet broad inventory goals could compromise indicator use for site or application-specific problem solving. Changes in our nation’s research landscape are shifting responsibility for soil stewardship from national and state government backed entities to public-private partnerships. As a result, it is critical to ensure that the data needed to assess soil health are generated by reproducible methods selected through a transparent process, and that data are readily available for public and private sector use. Appropriate methods for engagement need to be applied by public-private research partnerships as they establish and expand coordinated research enterprises that can deliver fact-based interpretation of soil quality indicators within the type of normative soil health framework conceived by USDA over 20 years ago. We look to existing examples as we consider how to put soil health information into the hands of practitioners in a manner that protects soils’ services

Developments in Agricultural Soil Quality and Health: Reflections by the Research Committee on Soil Organic Matter Management

The North Central Education and Research Activity Committee (NCERA-59) was formed in 1952 to address how soil organic matter formation and management practices affect soil structure and productivity. It is in this capacity that we comment on the science supporting soil quality and associated soil health assessment for agricultural lands with the goal of hastening progress in this important field. Even though the suite of soil quality indicators being applied by U.S. soil health efforts closely mirrors the “minimum data set” we developed and recommended in the mid-1990s, we question whether the methods or means for their selection and development are sufficient to meet current and emerging soil health challenges. The rush to enshrine a standard suite of dated measures may be incompatible with longer-term goals. Legitimate study of soil health considers soil change accrued over years to decades that influence on- and off-site function. Tailoring of methods to local conditions is needed to effectively apply and interpret indicators for different soil resource regions and land uses. Adherence to a set suite of methods selected by subjective criteria should be avoided, particularly when we do not yet have adequate data or agreed upon interpretive frameworks for many so-called “Tier 1” biological indicators used in soil health assessment. While pooling data collected by producer-groups is one of the most exciting new trends in soil health, standardizing methods to meet broad inventory goals could compromise indicator use for site or application-specific problem solving. Changes in our nation’s research landscape are shifting responsibility for soil stewardship from national and state government backed entities to public-private partnerships. As a result, it is critical to ensure that the data needed to assess soil health are generated by reproducible methods selected through a transparent process, and that data are readily available for public and private sector use. Appropriate methods for engagement need to be applied by public-private research partnerships as they establish and expand coordinated research enterprises that can deliver fact-based interpretation of soil quality indicators within the type of normative soil health framework conceived by USDA over 20 years ago. We look to existing examples as we consider how to put soil health information into the hands of practitioners in a manner that protects soils’ services