The “Show” menu provides commands to show or hide different types of graphic objects. The first three commands (Solid, Isosurface, None) respectively control the display of scalar data. The user may select one of the three command to display a solid, a set of isosurfaces, or to hide the scalar data. The remaining nine commands (Vectors, Pathlines, Model Features, Grid Shell, GridLines, Axes Symbol, Bounding box, Time, and Color Bar) alternately show and hide the corresponding graphic objects. A check mark next to a command indicates that the corresponding graphic object is shown. Selecting this command will hide the graphic object. The absence of a check mark next to a command indicates that the corresponding graphic object is hidden. Selecting the command will toggle the check mark and thus either show or hide the graphic object.
The backdrop for each figure is a grid that is used as a reference for its correct size, shape, and location. The figures are drawn on a grid 100 units high and 200 units wide–100 units on either side of the horizontal center of the window. The size of a grid unit varies with the length of the flying line used. With 38-meter (125-foot) lines, a grid unit is about 0.3 meter (1 foot). Each 10- unit square on the grid with 38-meter (125-foot) lines would have roughly 3-meter (10-foot) sides. Gridlines at 10-unit intervals are shown in the diagrams, but only where they are necessary to locate the figure within the grid.
10. Click on the circle before you beginning drawing the line. NOTE: if you are modifying an object, you must click to select your object before starting any function so that the program knows that you are modifying the object and not starting a new one. Therefore, in this case, click on the circle before sketching to indicate that you are adding the line to the sketch and not drawing a separate unrelated line. 11. From the point on the circle that is directly to the right of the centre point or the circle, count 3 vertical gridlines to the left. Then, move up this vertical grid line and count 3 horizontal gridlines above the point where the circle intersects with this vertical gridline. Click this point to indicate the start of your polyline. Note: each grid line represents 5mm.
It can be seen that there are two values of u at each top corner of the cavity making the solution singular. In the well-known paper by Ghia et al. , the flow was simulated by the finite-difference scheme and a multigrid method using very fine grids (i.e. 129 × 129 and 257 × 257). The obtained results are very accurate and they have been considered as a benchmark of finite-difference methods. In the later work by Botella and Peyret , the regular and singular parts of the solution are handled by a Chebyshev collocation and an analytic method respectively. Benchmark spectral results for the flow at Re = 100 and Re = 1000 were reported. In the present study, the set of 2-node IRBFEs is generated from gridlines that pass through interior grid nodes. As a result, the set of interpolation points does not include the top corners of the cavity and hence corner singularities do not explicitly enter the discrete system.
This paper is based on the exploration of the generation mechanism of three-phase unbalanced current in a ring network transmission line, according to the line parameters, the simulation and calculation of three-phase unbalanced current of the 220kV lines of Fenghuang-East Shihezi/West Shihezi-Manasi power plant-third stage engineering of Manasi power plant with more towers are carried out by using software ATPDraw and PSASP, the factors affecting the three-phase unbalanced current of the special double loop transmission line connecting two power plants are analyzed and the corresponding solutions and suggestions are given.
Figure 1 Design-based stereological methods using systematic uniform random sampling and vertical sections were used to study the undecalcified human femoral heads. (A) The vertical arrow represents the vertical axis (VA) of the femoral head and the rotated arrow represents the random rotation of the femoral head around the VA. The red line indicates the location of the medial part of the femoral head. (B) The femoral head was cut in 7 mm thick slices in a random orientation and parallel to the VA to get vertical uniform random sections. (C) The 7 mm thick slices were halved and alternating left and right half slices were sampled randomly resulting in a sampling fraction of one-half. (D) From each femoral head, all the sampled 7 mm thick halved parallel slices were embedded in methylmethacrylate, and 7 µm thick histological sections were cut from each slice and stained with May-Grünwald toluidine blue. In all histological sections, the joint surface was sampled systematically uniform random as every intersection (yellow dots) between the superimposed cycloid grids (black curved lines) and the joint surface. (E) For each random sampling point, the Osteoarthritis Research Society International (OARSI) grade was determined, and a line was drawn perpendicular to the joint surface. Along the line drawn perpendicular to the joint surface, the Th AC , Th CC and Th SCB were measured. To increase the precision of the Th SCB , two lines separated
Comprehensive no-go theorems show that information encoded over local two-dimensional topo- logically ordered systems cannot support macroscopic energy barriers, and hence will not maintain stable quantum information at finite temperatures for macroscopic timescales. However, it is still well motivated to study low-dimensional quantum memories due to their experimental amenability. Here we introduce a grid of defect lines to Kitaev’s quantum double model where different any- onic excitations carry different masses. This setting produces a complex energy landscape which entropically suppresses the diffusion of excitations that cause logical errors. We show numerically that entropically suppressed errors give rise to super-exponential inverse temperature scaling and polynomial system size scaling for small system sizes over a low-temperature regime. Curiously, these entropic effects are not present below a certain low temperature. We show that we can vary the system to modify this bound and potentially extend the described effects to zero temperature.
ABSTRACT: This paper presents the dynamic stability improvement of the offshore wind farm(OWF) connected to power grid using a static synchronous compensator(STATCOM) .The offshore wind farm is simulated by taking the four parallel operated permanent magnet generators(PMSG) of 5MW and the onshore power system is simulated by synchronous generator fed to an infinite bus through two parallel transmission lines. The STATCOM controller is implemented using two types of controllers: conventional PID controller and Fuzzy logic controller(FLC). The PID controller is designed using pole placement approach and the fuzzy logic controller is implemented using sugeno type fuzzy interface system. At the end the response with respect to both are compared.
capturing the image of the scene with the grid system included, it is vital that the edge of the grid closest to the camera is parallel to the bottom sensor plane of the camera. If this condition is not met, the extrapola- tion of the grid system will be skewed such that one side of the expanded grid will con- dense while the other increases in area1.
Figure 7. (a) Moving e-folding timescales estimated for the ice volume anomaly time series from the GECCO reanalysis. The window length varies from 5 to 59 years, and it is stepped forward by 1 month over a total period of 64 years (January 1948–December 2011). (b) Moving e-folding timescales for the 15-year window length case. The red stars in (a) and (b) indicate the 15-year overlapping period (January 1993– December 2007, center time mid-June 2000). (c) Wavelet power spectrum of (b), with Morlet as the mother wavelet. The black lines denote the 95 % significance levels above a red noise background spectrum, while the crosshatched areas indicate the cone of influence, in which the edge effects become important. The color bar is omitted in panel (c) since we are not interested in the power’s magnitude but in the frequencies outstanding as significant in the spectrum. (d) Time-integrated power spectrum from the wavelet analysis, where the dashed line corresponds to the 95 % significance level. The bands of significant periods (4.4–6.1 years and > 10.7 years) are highlighted by the gray horizontal bars. (e)–(h) Same as (a)–(d), respectively, but for the MOVE-CORE ice volume anomaly which has a spanning period of 60 years (January 1948–December 2007). The horizontal gray bar in (h) highlights the only period band of significant variability, defined by periods longer than 12.7 years.
The Kehrer Bielan webcast was aimed primarily at banks and their advisory businesses. A bank or brokerage firm earns fees on assets under management and commissions on product sales. Advisors receive 20% to 50% of the fee and commission revenue they produce, as determined by the grid. The more revenue, the greater the advisor’s
IN general, to be same phase at the time of synchronization is one of the requirements for two power generation systems with almost equal frequency. Phase angle detection of three- phase systems is carried by phase locked loops (PLLs). In order to synchronize two systems, the frequency of one system is considered a little higher than the other one's to achieve equal phase angles at one point. And then two systems are synchronized. PLLs show good phase detection with noiseless and non-disturbed input. When an input is disturbed, for example input is unbalanced, then PLLs cannot detect input phase angle. Offered solutions by [1-2] and [3-6] have improved PLLs. This study has developed a method using neural network controller, leading to optimal PLL performance. The coincidence of different sections in the power systems is of major importance in the system. To synchronize a part of the system with the power system, first the phase estimation must be done and then based on this estimation, the synchronization is achieved[7,8]. The phase estimation is performed by phase lock loops, and these systems are implemented when there is a necessity to connect to a structure to the grid for energy exchange.
known, it involves dropping a needle of length l at random on a plane grid of parallel lines of width d > l units apart and determining the probability of the needle crossing one of the lines. The desired probability is directly related to the value of p, which can then be estimated by Monte Carlo experiments. This point is one of the major aspects of its appeal. When p is treated as an unknown param- eter, Buffon’s needle experiments can be seen as valuable tools in applying the concepts of statistical estimation theory, such as efficiency, completeness, and sufficiency. For instance, in order to obtain better estimators of p, Kendall and Moran  and Diaconis  examine several aspects of the problem with a long needle (l > d). Morton  and Solomon  provide the general extension of the problem. Perlman and Wishura  investigate a number of statistical estimation procedures for p for the single, double, and triple grids. In their study, they show that moving from single to double to triple grid, the asymptotic variances of the estimators get smaller and hence more efficient estimators can be obtained. Wood and Robertson  introduce the concept of grid density and provide an alternative idea. They show that Buffon’s original single grid is actually the most efficient if the needle length is held constant (at the distance between lines on the of grid material per unit area). In , Wood and Robertson investigate the ways of maximizing the information in Buffon’s experiments.
In multiscale method,to optimize the accuracy of a pressure or transport equation calculation, the coarsened grid should generally adapt to the flow patterns predicted by the different indicator based on flow solver or permability. In this model we have used the permeability indicator which maps the high and low flow zones in the reservoir. In a permeability based indicator method, the grid is aligned to capture high-flow regions and (clearly) distinguish between regions of high and low flow.