5,258 research outputs found

    State-space model identification and feedback control of unsteady aerodynamic forces

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    Unsteady aerodynamic models are necessary to accurately simulate forces and develop feedback controllers for wings in agile motion; however, these models are often high dimensional or incompatible with modern control techniques. Recently, reduced-order unsteady aerodynamic models have been developed for a pitching and plunging airfoil by linearizing the discretized Navier-Stokes equation with lift-force output. In this work, we extend these reduced-order models to include multiple inputs (pitch, plunge, and surge) and explicit parameterization by the pitch-axis location, inspired by Theodorsen's model. Next, we investigate the na\"{\i}ve application of system identification techniques to input--output data and the resulting pitfalls, such as unstable or inaccurate models. Finally, robust feedback controllers are constructed based on these low-dimensional state-space models for simulations of a rigid flat plate at Reynolds number 100. Various controllers are implemented for models linearized at base angles of attack α0=0,α0=10\alpha_0=0^\circ, \alpha_0=10^\circ, and α0=20\alpha_0=20^\circ. The resulting control laws are able to track an aggressive reference lift trajectory while attenuating sensor noise and compensating for strong nonlinearities.Comment: 20 pages, 13 figure

    Lessons and Prospects from the pMSSM after LHC Run I: Neutralino LSP

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    We study SUSY signatures at the 7, 8 and 14 TeV LHC employing the 19-parameter, R-Parity conserving p(henomenological)MSSM, in the scenario with a neutralino LSP. Our results were obtained via a fast Monte Carlo simulation of the ATLAS SUSY analysis suite. The flexibility of this framework allows us to study a wide variety of SUSY phenomena simultaneously and to probe for weak spots in existing SUSY search analyses. We determine the ranges of the sparticle masses that are either disfavored or allowed after the searches with the 7 and 8 TeV data sets are combined. We find that natural SUSY models with light squarks and gluinos remain viable. We extrapolate to 14 TeV with both 300 fb1^{-1} and 3 ab1^{-1} of integrated luminosity and determine the expected sensitivity of the jets + MET and stop searches to the pMSSM parameter space. We find that the high-luminosity LHC will be powerful in probing SUSY with neutralino LSPs and can provide a more definitive statement on the existence of natural Supersymmetry.Comment: 41 pages, 27 figures. arXiv admin note: substantial text overlap with arXiv:1307.844

    Characterizing and correcting for the effect of sensor noise in the dynamic mode decomposition

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    Dynamic mode decomposition (DMD) provides a practical means of extracting insightful dynamical information from fluids datasets. Like any data processing technique, DMD's usefulness is limited by its ability to extract real and accurate dynamical features from noise-corrupted data. Here we show analytically that DMD is biased to sensor noise, and quantify how this bias depends on the size and noise level of the data. We present three modifications to DMD that can be used to remove this bias: (i) a direct correction of the identified bias using known noise properties, (ii) combining the results of performing DMD forwards and backwards in time, and (iii) a total least-squares-inspired algorithm. We discuss the relative merits of each algorithm, and demonstrate the performance of these modifications on a range of synthetic, numerical, and experimental datasets. We further compare our modified DMD algorithms with other variants proposed in recent literature

    Tracking the spread of the eastern dwarf tree frog (Litoria fallax) in Australia using citizen science

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    An increasing number of species are establishing populations outside of their native ranges, often with negative ecological and economic impacts. The detection and surveillance of invasive species presents a huge logistical challenge, given the large spatial regions in which new populations can appear. However, data collected through citizen science projects are increasingly recognised as a valuable source for detection and monitoring of invasive species. We use data from a national citizen science project, FrogID, to quantify the spread of the eastern dwarf tree frog (Litoria fallax) outside its historical native range in Australia. Of 48 012 records of L. fallax in the FrogID database, 485 were located far outside the historical native range of the species. L. fallax has established geographically large populations hundreds of kilometres away from its native range, and these appear to be spreading in extent over time. These populations have resulted in novel species co-occurrences, with L. fallax now co-occurring with at least two frog species not present in their native range. Although the impacts of the invasive populations of L. fallax remain unknown, our work highlights the value in leveraging citizen science projects to detect and monitor native species that can become invasive far outside their historical range

    Evaluation of Agricultural Statistics for ADAP

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    The Agricultural Development in the American Pacific (ADAP) Directors requested that the USDA, National Agricultural Statistics Service (NASS) extend its statistical program to the ADAP region: American Samoa, the Federated States of Micronesia (FSM), Palau, the Republic of the Marshall Islands (RMI), Guam, and the Commonwealth of the Northern Marianas (CNMI).This is the final report on the feasibility of, and our recommendations on establishing agricultural statistics in the region. The current section presents material that is generally applicable over the region, with separate sections containing relevant notes for each jurisdictionFunded through the US Department of Agriculture Cooperative Extension Service Grant Number 92-EXCA-1-0187

    Projective and Coarse Projective Integration for Problems with Continuous Symmetries

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    Temporal integration of equations possessing continuous symmetries (e.g. systems with translational invariance associated with traveling solutions and scale invariance associated with self-similar solutions) in a ``co-evolving'' frame (i.e. a frame which is co-traveling, co-collapsing or co-exploding with the evolving solution) leads to improved accuracy because of the smaller time derivative in the new spatial frame. The slower time behavior permits the use of {\it projective} and {\it coarse projective} integration with longer projective steps in the computation of the time evolution of partial differential equations and multiscale systems, respectively. These methods are also demonstrated to be effective for systems which only approximately or asymptotically possess continuous symmetries. The ideas of projective integration in a co-evolving frame are illustrated on the one-dimensional, translationally invariant Nagumo partial differential equation (PDE). A corresponding kinetic Monte Carlo model, motivated from the Nagumo kinetics, is used to illustrate the coarse-grained method. A simple, one-dimensional diffusion problem is used to illustrate the scale invariant case. The efficiency of projective integration in the co-evolving frame for both the macroscopic diffusion PDE and for a random-walker particle based model is again demonstrated
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