HE receiving antenna directivity patterns and gain for ionospheric propagation model predictions for shortwave broadcasting

1988 ◽  
Vol 34 (2) ◽  
pp. 221-229 ◽  
Author(s):  
G.H. Hagn
Keyword(s):  
Propagation Model ◽  
Ionospheric Propagation ◽  
Antenna Directivity ◽  
Receiving Antenna ◽  
Model Predictions ◽  
Directivity Patterns

scholarly journals Assimilating Global Wave Model Predictions and Deep-Water Wave Observations in Nearshore Swell Predictions

2017 ◽  
Vol 34 (8) ◽  
pp. 1823-1836 ◽  
Author(s):  
Sean C. Crosby ◽  
Bruce D. Cornuelle ◽  
William C. O’Reilly ◽  
Robert T. Guza
Keyword(s):  
Wave Propagation ◽  
High Resolution ◽  
Wave Energy ◽  
Propagation Model ◽  
Linear Wave ◽  
Time Lags ◽  
Energy Propagation ◽  
Nearshore Processes ◽  
Model Predictions ◽  
Linear Wave Propagation

AbstractNearshore wave predictions with high resolution in space and time are needed for boating safety, to assess flood risk, and to support nearshore processes research. This study presents methods for improving regional nearshore predictions of swell-band wave energy (0.04–0.09 Hz) by assimilating local buoy observations into a linear wave propagation model with a priori guidance from global WAVEWATCH III (WW3) model predictions. Linear wave propagation, including depth-induced refraction and shoaling, and travel time lags, is modeled with self-adjoint backward ray tracing techniques. The Bayesian assimilation yields smooth, high-resolution offshore wave directional spectra that are consistent with WW3, and with offshore and local buoy observations. Case studies in the Southern California Bight (SCB) confirm that the nearshore predictions at independent (nonassimilated) buoy sites are improved by assimilation compared with predictions driven with WW3 or with a single offshore buoy. These assimilation techniques, valid in regions and frequency bands where wave energy propagation is mostly linear, use significantly less computational resources than nonlinear models and variational methods, and could be a useful component of a larger regional assimilation program. Where buoy locations have historically been selected to meet local needs, these methods can aid in the design of regional buoy arrays by quantifying the regional skill improvement for a given buoy observation and identifying both high-value and redundant observations. Assimilation techniques also identify likely forward model error in the Santa Barbara Channel, where permanent observations or model corrections are needed.

IMPROVING THE VARIOUS PROPERTIES OF THE UDA-YAGI ANTENNA

2021 ◽  
pp. 64-67
Author(s):  
С.М. Фёдоров ◽  
Е.А. Ищенко ◽  
И.А. Зеленин ◽  
Е.В. Папина ◽  
А.В. Бунина ◽  
...  
Keyword(s):  
High Speed ◽  
Optimal Number ◽  
Maximum Value ◽  
Yagi Antenna ◽  
Television Signal ◽  
Half Wave ◽  
Antenna Directivity ◽  
Directivity Patterns ◽  
Accuracy Of Results ◽  
To Receive

Рассматривается антенна Уда-Яги, которая предназначена для приема сигнала наземного телевещания в 57 частотном канале. Самыми важными характеристиками для антенны Уда-Яги являются коэффициент направленного действия, передне-заднее отношение (коэффициент защитного действия), при этом данные характеристики сильно зависят от числа директоров, применяемых в конструкции антенны. На основе произведенного электродинамического моделирования было определено, как изменятся характеристики диаграмм направленности антенны на частоте 762 МГц при применении различного числа директоров - от 1 (3-элементная антенна Уда-Яги) до 12 (14-элементная антенна Уда-Яги), при этом определено оптимальное количество директоров для ситуации, когда требуется достижение максимальной помехозащищенности (максимальное значение передне-заднего отношения). Приводятся диаграммы направленности при различном числе директоров на частоте 762 МГц, графики коэффициентов защитного действия (ПЗО) от числа директоров и от частоты, таблицы со сравнительными характеристиками диаграмм направленности. Моделирование производилось с использованием метода моментов, так как при его применении достигаются высокая скорость расчетов, а также высокая точность результатов. При моделировании антенна имела один рефлектор и активный элемент в виде полуволнового диполя The article considers the Uda-Yagi antenna, which is designed to receive a terrestrial television signal in a 57-frequency channel. The most important characteristics for an Uda-Yagi antenna are directivity, front-to-back ratio, and these characteristics are highly dependent on the number of directors used in the antenna design. On the basis of the electrodynamic simulation, we determined how the characteristics of the antenna directivity patterns at a frequency of 762 MHz will change when using a different number of directors - from 1 (3-element Uda-Yagi antenna) to 12 (14-element Uda-Yagi antenna), at the same time, we determined the optimal number of directors for the situation when the achievement of maximum noise immunity is required (the maximum value of the front-to-back ratio). The article gives directivity patterns for different numbers of directors at a frequency of 762 MHz, dependencies of directivity coefficients on the number of directors and on the frequency, tables with comparative characteristics of directivity patterns. We carried out the simulation using the method of moments, since it achieves a high speed of calculations, as well as high accuracy of results. During simulation, the antenna had one reflector and an active element in the form of a half-wave dipole

scholarly journals Modeling of Liquid Injectivity in Surfactant-Alternating-Gas Foam Enhanced Oil Recovery

SPE Journal ◽  
2019 ◽  
Vol 24 (03) ◽  
pp. 1123-1138 ◽  
Author(s):  
J.. Gong ◽  
S.. Vincent-Bonnieu ◽  
R. Z. Kamarul Bahrim ◽  
C. A. Che Mamat ◽  
R. D. Tewari ◽  
...  
Keyword(s):  
Oil Recovery ◽  
Flow Model ◽  
Radial Flow ◽  
Gas Injection ◽  
Small Region ◽  
Propagation Model ◽  
Injection Well ◽  
Wellbore Pressure ◽  
Model Predictions ◽  
Experimental Findings

Summary Surfactant alternating gas (SAG) is often the injection strategy used for injecting foam into a reservoir. However, liquid injectivity can be very poor in SAG, and fracturing of the well can occur. Coreflood studies of liquid injectivity directly following foam injection have been reported. We conducted a series of coreflood experiments to study liquid injectivity under conditions more like those near an injection well in a SAG process in the field (i.e., after a period of gas injection). Our previous experimental results suggest that the injectivity in a SAG process is determined by propagation of several banks. However, there is no consistent approach to modeling liquid injectivity in a SAG process. The Peaceman equation is used in most conventional foam simulators for estimating the wellbore pressure and injectivity. In this paper, we propose a modeling approach for gas and liquid injectivity in a SAG process on the basis of our experimental findings. The model represents the propagation of various banks during gas and liquid injection. We first compare the model predictions for linear flow with the coreflood results and obtain good agreement. We then propose a radial-flow model for scaling up the core-scale behavior to the field. The comparison between the results of the radial-propagation model and the Peaceman equation shows that a conventional simulator based on the Peaceman equation greatly underestimates both gas and liquid injectivities in a SAG process. The conventional simulator cannot represent the effect of gas injection on the subsequent liquid injectivity, especially the propagation of a relatively small region of collapsed foam near an injection well. The conventional simulator's results can be brought closer to the radial-flow-model predictions by applying a constant negative skin factor. The work flow described in this study can be applied to future field applications. The model we propose is based on a number of simplifying assumptions. In addition, the model would need to be fitted to coreflood data for the particular surfactant formulation, porous medium, and field conditions of a particular application. The adjustment of the simulator to better fit the radial-flow model also would depend, in part, on the grid resolution of the near-well region in the simulation.

scholarly journals Ionospheric specification from GPS data and the RIBG ionospheric propagation model

Radio Science ◽  
1997 ◽  
Vol 32 (4) ◽  
pp. 1671-1679 ◽  
Author(s):  
Michael H. Reilly ◽  
Malkiat Singh
Keyword(s):  
Propagation Model ◽  
Gps Data ◽  
Ionospheric Propagation

Shipping Noise Predictions: Capabilities and Limitations

2003 ◽  
Vol 37 (4) ◽  
pp. 54-65 ◽  
Author(s):  
Richard M. Heitmeyer ◽  
Stephen C. Wales ◽  
Lisa A. Pflug
Keyword(s):  
Deep Water ◽  
Ambient Noise ◽  
Classical Model ◽  
Propagation Model ◽  
Environmental Data ◽  
Noise Model ◽  
Propagation Models ◽  
Littoral Region ◽  
Model Predictions ◽  
Noise Models

This paper addresses shortcomings in the ability to predict either current levels of the ambient noise generated by shipping or future trends in those levels that might result from changes in the world's shipping fleet. In particular, experimental evidence is presented that predictions of increases in the sound generated by the world's ships based on increases in their speeds and lengths are not justified. This is because, contrary to the classical model of shipping source levels (Ross, 1976), there is a negligible correlation between the source levels of an ensemble of ships and the speeds and lengths of those ships. We also present two examples of noise model predictions that result in large errors. The first shows that two state-of-the-art noise models can yield significantly different noise predictions (5 dB) for the same deep-water, open ocean site. About two dB of this difference is attributed to an approximation inherent in the acoustic propagation model of one of the noise models that is acceptable in some deep-water regions, but not in others. The remaining discrepancy is attributed to differences in the acoustic environmental databases (sound speeds, bathymetries, and geo-acoustic models) between the two noise models. The second example shows that neglecting the local shipping component in a littoral region near a port can result in a noise prediction that is over 15 dB less than a measured value. Taken together, these examples indicate that large errors can result because of inappropriate propagation models or incomplete or inaccurate shipping and environmental data bases. [Work supported by ONR.]

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