This report provides an overview on the current state of wind turbine control and introduces a number of active techniques that could be potentially used for control of wind turbine blades. The focus is on research regarding active flow control (AFC) as it applies to wind turbine performance and loads. The techniques and concepts described here are often described as 'smart structures' or 'smart rotor control'. This field is rapidly growing and there are numerous concepts currently being investigated around the world; some concepts already are focused on the wind energy industry and others are intended for use in other fields, but have the potential for wind turbine control. An AFC system can be broken into three categories: controls and sensors, actuators and devices, and the flow phenomena. This report focuses on the research involved with the actuators and devices and the generated flow phenomena caused by each device.
Shock testing was performed on a selected commercial-off-the-shelf - MicroElectroMechanical System (COTS-MEMS) accelerometer to determine the margin between the published absolute maximum rating for shock and the 'measured' level where failures are observed. The purpose of this testing is to provide baseline data for isolating failure mechanisms under shock and environmental loading in a representative device used or under consideration for use within systems and assemblies of the DOD/DOE weapons complex. The specific device chosen for this study was the AD22280 model of the ADXL78 MEMS Accelerometer manufactured by Analog Devices Inc. This study focuses only on the shock loading response of the device and provides the necessary data for adding influence of environmental exposure to the reliability of this class of devices. The published absolute maximum rating for acceleration in any axis was 4000 G for this device powered or unpowered. Results from this study showed first failures at 8000 G indicating a margin of error of two. Higher shock level testing indicated that an in-plane, but off-axis acceleration was more damaging than one in the sense direction.
As part of the U.S. Department of Homeland Security Detect-to-Protect program, a multilab [Sandia National Laboratories (SNL), Lawrence Livermore National Laboratories (LLNL), Pacific Northwest National Laboratory (PNNL), Oak Ridge National Laboratory (ORNL), and Los Alamos National Laboratory (LANL)] effort is addressing the need for useable detect-to-warn bioaerosol sensors for public facility protection. Towards this end, the SNL team is employing rapid fluorogenic staining to infer the protein content of bioaerosols. This is being implemented in a flow cytometry platform wherein each particle detected generates coincident signals of forward scatter, side scatter, and fluorescence. Several thousand such coincident signal sets are typically collected to generate a probability distribution over the scattering and fluorescence values. A linear unmixing analysis is performed to differentiate components in the mixture. After forming a library of pure component distributions from measured pure material samples, the distribution of an unknown mixture of particles is treated as a linear combination of the pure component distributions. The scattering/fluorescence probability distribution data vector a is considered the product of two vectors, the fractional profile f and the scattering/ fluorescence distributions from pure components P. A least squares procedure minimizes the magnitude of the residual vector e in the expression a = fP T + e. The profile f designates a weighting fraction for each particle type included in the set of pure components, providing the composition of the unknown mixture. We discuss testing of this analysis approach and steps we have taken to evaluate the effect of interferents, both known and unknown.
As part of the U.S. Department of Homeland Security Detect-to-Protect program, a multilab [Sandia National Laboratories (SNL), Lawrence Livermore National Laboratories (LLNL), Pacific Northwest National Laboratory (PNNL), Oak Ridge National Laboratory (ORNL), and Los Alamos National Laboratory (LANL)] effort is addressing the need for useable detect-to-warn bioaerosol sensors for public facility protection. Towards this end, the SNL team is employing rapid fluorogenic staining to infer the protein content of bioaerosols. This is being implemented in a flow cytometry platform wherein each particle detected generates coincident signals of forward scatter, side scatter, and fluorescence. Several thousand such coincident signal sets are typically collected to generate a probability distribution over the scattering and fluorescence values. A linear unmixing analysis is performed to differentiate components in the mixture. After forming a library of pure component distributions from measured pure material samples, the distribution of an unknown mixture of particles is treated as a linear combination of the pure component distributions. The scattering/fluorescence probability distribution data vector a is considered the product of two vectors, the fractional profile f and the scattering/ fluorescence distributions from pure components P. A least squares procedure minimizes the magnitude of the residual vector e in the expression a = fP T + e. The profile f designates a weighting fraction for each particle type included in the set of pure components, providing the composition of the unknown mixture. We discuss testing of this analysis approach and steps we have taken to evaluate the effect of interferents, both known and unknown.
In this paper we show that the technique for spotlight-mode SAR image formation generally known as "backprojection" or "time- domain" is most easily derived and described in terms of the well-known methods of phased-array beamforming. By contrast, backprojection has been typically developed via analogy to tomographic imaging [1], which restricts this technique to the case of planar wavefronts. We demonstrate how the very simple notion of delay-and-sum beamforming leads directly to the backprojection algorithm for SAR, including the case for curved wavefronts. We further explain why backprojection offers a certain elegant simplicity for SAR imaging, and allows direct one-step computation of several useful SAR products, including an orthographically correct image free of any geometric or defocus effects from wavefront curvature and also free of the effects of terrain-elevation-induced defocus. (This product requires as an input a pre-existing digital elevation map (DEM) of the scene to be imaged.) In addition, we'll demonstrate why beamforming yields a mode-independent SAR image formation algorithm, i.e. one that can just as easily accommodate strip-map or spotlight-mode phase histories collected on an arbitrary flight path.
We investigate the advantages of employing a fiber faceplate in a snapshot polarimetry system. Our previous work at Sandia National Laboratories indicates that diffraction and propagation between the micropolarizer array, the micro-waveplate array, and the Focal Plane Array (FPA) degrade performance, as quantified by the extinction ratio1,2. Crosstalk between adjacent pixels due to diffraction increases uncertainty of the measured polarization states in a scene of interest. These issues are exacerbated in the long-wavelength regime and as FPA pixel dimensions decrease. One solution, since it minimizes propagation distance, is to construct the micropolarizer and micro-waveplate arrays on a single substrate surface and to place this combination on the FPA3. This solution is a significant fabrication challenge and decreases yield due to its serial assembly nature. An alternative solution that would improve yield is to fabricate the micropolarizer on top of a fiber faceplate, place the faceplate on the FPA with the micropolarizer facing away, then place the waveplate array on top of the micropolarizer. The optical field that passes through the plane of the microwaveplate array and the micropolarizer array is guided to the FPA plane, without suffering diffraction effects associated with free-space propagation. We will quantify the utility of these proposed configurations with predicted imaging polarimetric system extinction ratios.
As part of the U.S. Department of Homeland Security Detect-to-Protect (DTP) program, a multilab [Sandia National Laboratories (SNL), Lawrence Livermore National Laboratories (LLNL), Pacific Northwest National Laboratory (PNNL), Oak Ridge National Laboratory (ORNL), and Los Alamos National Laboratory (LANL)] effort is addressing the need for useable detect-to-warn bioaerosol sensors for public facility protection. Towards this end, the SNL team is investigating the use of rapid fluorogenic staining to infer the protein content of bioaerosols. This is being implemented in a flow cytometer wherein each particle detected generates coincident signals of correlated forward scatter, side scatter, and fluorescence. Several thousand such coincident signal sets are typically collected to generate a distribution describing the probability of observing a particle with certain scattering and fluorescence values. These data are collected for sample particles in both a stained and unstained state. A linear unmixing analysis is performed to differentiate components in the mixture. In this paper, we discuss the implementation of the staining process and the cytometric measurement, the results of their application to the analysis of known and blind samples, and a potential instrumental implementations that would use staining.
Sandia National Laboratories, California (SNL/CA) is a government-owned/contractor-operated laboratory. Sandia Corporation, a Lockheed Martin Company, operates the laboratory for the Department of Energy’s National Nuclear Security Administration (NNSA). The NNSA Sandia Site Office oversees operations at the site, using Sandia Corporation as a management and operating contractor. This Site Environmental Report for 2007 was prepared in accordance with DOE Order 231.1A (DOE 2004a). The report provides a summary of environmental monitoring information and compliance activities that occurred at SNL/CA during calendar year 2007. General site and environmental program information is also included.