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The drag characteristics of eight radial-engine cowlings have been determined over a wide speed range in the N.A.C.A. 8-foot high-speed wind tunnel. The pressure distribution over all cowlings was measured, to and above the speed of the compressibility burble, as an aid in interpreting the force tests. One-fifth-scale models of radial-engine cowlings on a wing-nacelle combination mere used in the tests.
Past studies have shown that the use of coarse resolution SST products such as from the real-time global (RTG) SST analysis[1] or other coarse resolution once-a-day products do not properly portray the diurnal variability of fluxes of heat and moisture from the ocean that drive the formation of low level clouds and precipitation over the ocean. For example, the use of high resolution MODIS SST composite [2] to initialize the Advanced Research Weather Research and Forecast (WRF) (ARW) [3] has been shown to improve the prediction of sensible weather parameters in coastal regions [4][5}. In an extend study, [6] compared the MODIS SST composite product to the RTG SST analysis and evaluated forecast differences for a 6 month period from March through August 2007 over the Florida coastal regions. In a comparison to buoy data, they found that that the MODIS SST composites reduced the bias and standard deviation over that of the RTG data. These improvements led to significant changes in the initial and forecasted heat fluxes and the resulting surface temperature fields, wind patterns, and cloud distributions. They also showed that the MODIS composite SST product, produced for the Terra and Aqua satellite overpass times, captured a component of the diurnal cycle in SSTs not represented in the RTG or other one-a-day SST analyses. Failure to properly incorporate these effects in the WRF initialization cycle led to temperature biases in the resulting short term forecasts. The forecast impact was limited in some situations however, due to composite product inaccuracies brought about by data latency during periods of long-term cloud cover. This paper focuses on the forecast impact of an enhanced MODIS/AMSR-E composite SST product designed to reduce inaccuracies due data latency in the MODIS only composite product.
This paper summarizes the recent development of an adaptive aeroelastic wing shaping control technology called variable camber continuous trailing edge flap (VCCTEF). As wing flexibility increases, aeroelastic interactions with aerodynamic forces and moments become an increasingly important consideration in aircraft design and aerodynamic performance. Furthermore, aeroelastic interactions with flight dynamics can result in issues with vehicle stability and control. The initial VCCTEF concept was developed in 2010 by NASA under a NASA Innovation Fund study entitled "Elastically Shaped Future Air Vehicle Concept," which showed that highly flexible wing aerodynamic surfaces can be elastically shaped in-flight by active control of wing twist and bending deflection in order to optimize the spanwise lift distribution for drag reduction. A collaboration between NASA and Boeing Research & Technology was subsequently funded by NASA from 2012 to 2014 to further develop the VCCTEF concept. This paper summarizes some of the key research areas conducted by NASA during the collaboration with Boeing Research and Technology. These research areas include VCCTEF design concepts, aerodynamic analysis of VCCTEF camber shapes, aerodynamic optimization of lift distribution for drag minimization, wind tunnel test results for cruise and high-lift configurations, flutter analysis and suppression control of flexible wing aircraft, and multi-objective flight control for adaptive aeroelastic wing shaping control.
NREL's Power Electronic Grid Interface (PEGI) Workshop, held October 13, 2020, focused on the research challenges of operating power systems with ever-higher levels of inverter-based generation and power-electronic-based load. This presentation provides an overview of ARIES research projects involving inverter-based resources.
A simple two-dimensional model is developed to examine the composition of the cometary ion coma in the region outside the ionopause which is strongly affected by the solar wind. Two-dimensional ion distributions are obtained assuming a cylindrically symmetric ion coma which accounts for the dynamic effects of the mass-loaded solar wind flow around the cometary ionosphere. The results of this model are discussed in the context of analyzing the GIOTTO ion data.
Wind vector change with respect to time at Cape Kennedy, Florida, is examined according to the theory of multivariate normality. The joint distribution of the four variables represented by the components of the wind vector at an initial time and after a specified elapsed time is hypothesized to be quadravariate normal; the fourteen statistics of this distribution, calculated from fifteen years of twice daily Rawinsonde data are presented by monthly reference periods for each month from 0 to 27 km. The hypotheses that the wind component changes with respect to time is univariate normal, the joint distribution of wind component changes is bivariate normal, and the modulus of vector wind change is Rayleigh, has been tested by comparison with observed distributions. Statistics of the conditional bivariate normal distributions of vector wind at a future time given the vector wind at an initial time are derived. Wind changes over time periods from one to five hours, calculated from Jimsphere data, are presented.
An aerodynamic investigation was conducted in the MSFC High Reynolds Number Wind Tunnel to determine the pressure distribution over the foresection of the current 146 inch diameter shuttle SRB. The test model consisted of a 0.0137 scale version of the SRB nose cone and a forward portion of the cylindrical body which was approximately 2.7 calibers in length. The pressure distributions are plotted as a function of longitudinal station ratioed to body diameter and circumferential location for each angle of attack and Mach number. A Reynolds number variation study was made for Mach numbers of 0.4 and 0.6 at an angle of attack of 270 deg and roll angle of 180 deg.
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Recent data sets for three meteorological phenomena with the potential to inflict damage on SRS facilities – tornadoes, straight-line winds, and heavy precipitation – are analyzed using appropriate statistical techniques to estimate the occurrence probabilities for these events in the future. Summaries of the results for DOE-mandated return periods and comparisons to similar calculations performed in 2013 by Werth et al. (W2013) are given. Using tornado statistics for i) the combined states of Georgia and South Carolina, and ii) a 2⁰ square area surrounding SRS, we calculated the probability per year of any location at SRS being struck by a tornado (the ‘strike’ probability) and the probability that any point will experience winds above set thresholds. The strike probability was calculated to be 7.04E-4 (1 chance in 1420) per year and tornadic wind speeds for DOE mandated return periods of 50,000 years (corresponding to wind design category 3 (WDC-3), and 125,000 years (meeting WDC-4) (USDOE, 2016) were estimated to be 132 mph and 147 mph, respectively. By contrast, default tornado wind speeds taken from ANSI/ANS-2.3-2011 are somewhat higher: 161 mph for return periods of 50,000 years and 173 mph every 125,000 years (ANS, 2011). Although the ANS and the SRS evaluation used the same basic model (Ramsdell and Rishel, 2007), the region defined in ANS 2.3 that encompasses the SRS also includes areas of the Great Plains and lower Midwest, regions with much higher occurrence frequencies of strong tornadoes. The SRS straight-line wind values associated with various return periods were calculated by fitting existing wind data to a GEV1 distribution and extrapolating the values for any return period from the tail of that function. For the DOE mandated return periods, we expect straight-line winds of 117 mph every 2500 years (the required WDC-3 standard) and 125 mph every 6250 years (WDC-4) at any point within the SRS. These values are similar to those from the ANS-2.3-2011 report, which has wind speeds of 125mph and 133 mph for return periods of 2500 years and 6250 years, respectively. For extreme precipitation, we compared the fits of two different theoretical extreme-value distributions and applied the one that fit the data best for each of several accumulation periods. The DOE mandated 6-hr accumulated rainfall for return periods of 10,000 years (corresponding to precipitation design category 3 (PDC-3) and 25,000 years (PDC-4) were estimated as 9.1 inches and 10.1 inches, respectively. For the 24-hr rainfall return periods of 10,000 years and 25,000 years, total rainfall estimates were 12.02 inches and 13.17 inches, respectively, higher than comparable values provided in the W2013 report.
An analysis is presented of high resolution wind profile measurements recorded at the NASA 150-m ground winds tower facility, showing wind speed shear frequency and magnitude distributions for six vertical layers of the atmosphere and one vertical distance. Vertical wind shear is defined as the change of wind speed with height, and its magnitudes were derived by algebraically subtracting lower level wind speeds from those of higher levels and dividing the distance between levels. Horizontal wind shear is understood to be change of wind speed with horizontal distance, and its magnitudes were derived by algebraically subtracting the wind speed at a short tower from that at a tall one and dividing by the distance between towers.
A round table discussion of problems of solar and stellar spindown and theory is presented. Observational evidence of the angular momentum of the solar wind is included, emphasizing the distribution of angular velocity inside the sun and stars.
Results from the performance and test section flow calibration of the 80- by 120-Foot Wind Tunnel are presented. Measurements indicating the 80- by 120-ft test section flow quality were obtained throughout the tunnel operational envelope and for atmospheric wind speeds up to approximately 20 knots. Tunnel performance characteristics and a dynamic pressure system calibration were also documented during the process of mapping the test section flow field. Experimental results indicate that the test section flow quality is relatively insensitive to dynamic pressure and the level of atmospheric winds experienced during the calibration. The dynamic pressure variation in the test section is within +/-75 percent of the average. The axial turbulence intensity is less than 0.5 percent up to the maximum test section speed of 100 knots, and the vertical and lateral flow angle variations are within +/-5 deg and +/-7 deg, respectively. Atmospheric winds were found to affect the pressure distribution in the test section only at high ratios of wind speed to test section speed.
The velocity distribution function of He(+) in the solar wind at 1 AU is calculated with the assumption that the source is photoionization of a cold (T = 100 K), neutral interstellar wind. If the spiral magnetic field is noise free, the velocity distribution is diffuse and would not produce a peak at 4(E over Q) sub H in an E over Q particle spectrum. If the velocity of the interstellar wind with respect to the sun lies in the ecliptic, a large variation of the He(+) number density with respect to ecliptic longitude is expected.
The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.
A two-dimensional wind-tunnel investigation of the pressure distributions over several NACA 16-series airfoils with thicknesses of 4, 6, 9, and 12 percent of the chord and design lift coefficients of 0, 0.2, 1 and 0.5 has been conducted in the Langley airfoil test apparatus at transonic Mach numbers from 0.7 to 1.25. The tests ranged in Reynolds number from 2.4 x 10 (exp 6) to 2.8 x 10 (exp 6) and in angle of attack from -10 to 12 degrees. Chordwise pressure distributions and schlieren flow photographs are presented without analysis.
Empirical evidence is presented that solar wind thermal electrons obey a polytrope law with polytrope index gamma = 1.175 plus or minus 0.03. The Voyager 2 and Mariner 10 data used as evidence are compared and discussed. The theoretical predictions that solar wind thermal electrons in the asymptotic solar wind should obey a polytrope law with polytrope index gamma = 1.16 plus or minus. The widespread impressions in the literature that solar wind electrons behave more like an isothermal than adiabatic gas, and the arguments that Coulomb collisions are the dominant stochastic process shaping observed electron distribution functions in the solar wind are reexamined, reviewed and evaluated. The assignment of the interplanetary potential as equal to approximately seven times the temperature of the thermal electrons is discussed.
Distributions and average values for the proton speed, azimuthal and polar flow directions, and the proton temperature and density in the solar wind are presented. The data are obtained from the Ames plasma probes on Pioneers 6 and 7. The time periods covered include Dec. 18, 1965 to mid-February 1966, and mid-August to mid-October 1966. The distributions of the parameters, except for the polar flow direction, are skewed, partially because of stream-stream interactions in the solar wind. The average values of the basic plasma parameters from the two spacecraft are different which could be due partially to different solar activity at the two times, and partially to sector and beam structure dependence.
The main sensor of the Vogager plasma experiment consists of a cluster of three, modulated-grid Faraday cups whose normals are arranged symmetrically about the symmetry axis of the cluster at an angle of 20 degrees to that axis. In interplanetary space, each cup explores the positive ion distribution by accepting particles from contiguous slices in velocity space. The slices are narrow in the direction of the normal to the modulating grid but are broad in planes parallel to that grid. The resulting three sets of measurements can be combined to yield the three-dimensional distribution function in the following way: the distribution function is assumed to be gyrotropic. For each value of speed in a frame of reference moving with the bulk velocity of the solar wind, the variation of the distribution function with angle from the field direction is represented by a series of Legendre polynomials. Effects such as double-streaming and heat flow can be well represented by using only the first three terms of the series which are fully specified by the measurements. Examples of the use of this method in the analysis of Voyager data are shown.