In this paper, a near-zero-index metamaterial is proposed by the composite I-shaped unit cell and the refraction index of this metamaterial is close to zero from 6.12GHz to 6.19 GHz. To study the characteristics and application of this near-zero-index metamaterial, especially the ability of focusing energy, a microstrip antenna is designed. According to the formulations for designing microstrip patch antenna, the conventional microstrip antenna, which resonance at 6.19GHz, is designed and optimized. This metamaterial is placed right above the conventional microstrip antenna and this system is tested by the finite element method (FEM). Simulation results show that the maximum radiation gain in H-plane of the microstrip antenna with this near-zero-index metamaterial is 9.24dB, while the maximum radiation gain in H-plane of the conventional microstrip antenna is 2.63dB, improving about 6.61dB than conventional microstrip antenna; the maximum radiation gain in E-plane of the microstrip antenna with this near-zero-index metamaterial is 9.24dB, while the maximum radiation gain in E-plane of the conventional microstrip antenna is 5.12dB, improving about 4.12dB than conventional microstrip antenna. Simulation results also show that the directivity of the microstrip antenna with this near-zero-index metamaterial is much higher, compared with the conventional microstrip antenna. Radiation gain at other frequencies, from 6.12GHz to 6.19GHz, is also obtained, the value is much higher than the conventional microstrip antenna at the corresponding frequency. The results indicate that near-zero-index metamaterials can improve the radiation gain and the directivity of the conventional microstrip antenna.
KEYWORDS: Solar radiation models, Vegetation, Data modeling, Thermal modeling, Infrared radiation, Temperature metrology, Thermography, Infrared imaging, Solar radiation, Carbon dioxide
To simulate vegetation temperature is an important part in the thermal infrared simulation. In previous physical models, the
physiological characteristics of vegetation has only considered the influence of transpiration to temperature, but without
respiration, and the aerodynamics model which has been used before needs more model parameters and they are difficult
to obtain. In the present paper, a transpiration rate model has been used, in which the latent heat component of the
vegetation has been optimized and the respiration component has been joined. Then the physiological model of vegetation
temperature simulation has been established which improves the original vegetation energy budget theory. Experimental
verification and comparison shows that the maximum simulation error of physiological model is within 2℃, the average
error is within 1℃. It seems that the simulation accuracy is significantly better than the previous physical model that will
improve the overall thermal infrared simulation accuracy.
Detection probability is an important index to represent and estimate target viability, which provides basis for
target recognition and decision-making. But it will expend a mass of time and manpower to obtain detection probability
in reality. At the same time, due to the different interpretation of personnel practice knowledge and experience, a great
difference will often exist in the datum obtained. By means of studying the relationship between image features and
perception quantity based on psychology experiments, the probability model has been established, in which the process
is as following.Firstly, four image features have been extracted and quantified, which affect directly detection. Four
feature similarity degrees between target and background were defined. Secondly, the relationship between single image
feature similarity degree and perception quantity was set up based on psychological principle, and psychological
experiments of target interpretation were designed which includes about five hundred people for interpretation and two
hundred images. In order to reduce image features correlativity, a lot of artificial synthesis images have been made which
include images with single brightness feature difference, images with single chromaticity feature difference, images with
single texture feature difference and images with single shape feature difference. By analyzing and fitting a mass of
experiments datum, the model quantitys have been determined. Finally, by applying statistical decision theory and
experimental results, the relationship between perception quantity with target detection probability has been found. With
the verification of a great deal of target interpretation in practice, the target detection probability can be obtained by the
model quickly and objectively.
A quantitative numerical modeling of laser-induced Lamb waves in thin unidirectional fiber-reinforced composite plate,
transversely isotropic, is established by using finite element method (FEM). Taking into account the effects of thermal
conduction, optical penetration as well as the finite width and duration of laser source, the transient temperature
distributions are calculated. Applying the temperature distributions induced by the absorbed laser energy to structure
analyses as thermal loading, the stress fields, the deformations of plate and the laser-induced Lamb waveforms are
obtained. The mechanical generation process of Lamb wave is presented intuitively by analyzing the stress field
propagation and the deformations of plate. The characteristics of Lamb waveforms caused by the anisotropic nature of
specimen material, including amplitude and dispersive nature, are analyzed. This method provides insight to the
generation and propagation of the laser-induced Lamb waves in thin unidirectional fiber-reinforced composite plate and
establishes the quantitative relationship between the laser-induced Lamb waveforms and the laser input as well as the
specimen parameters.
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