Fog Parameters Research Articles

Optimization of the Air Cleaning Properties of Fog

Fog droplets are very often used as a cleaning agent when air pollution can be dangerous for health conditions and ecosystem. This work presents a new system to optimize the cleaning properties of fog by tuning its microphysical parameters. For this purpose, a newly developed system, which is based on the electromagnetic echo effect (EMEE) sensor, is used to detect the most efficient interaction between fog and impurities, i.e., which fog droplets can be used to most effectively clean a certain type of pollutant from the air. Fog droplet spectra controlled by the nozzle pressure system can be used to effectively remove pollutants from the air. For this purpose, an automated system for aerosol generation can allow an accurate control over the fog microphysical parameters and the use of fluids with specific concentrations of pulverized chemical compounds. Fog droplet size distribution is controlled by the feeding gas pressure at the nozzle and chemical simulants. The experimental results showed that the microphysical parameters (MP) are directly related to the impurity of species used in the cleanup simulation process. The MP parameters of fog are liquid water content (LWC), droplet mean radius (Rm), droplet number concentration (Nd), and both aerosol type and mass concentration. In the lab testing, harmless simulants of CBRN (chemical, biological, radiological and nuclear) species were used. During the tests, fog droplet size distribution is controlled by the air pressure at the nozzle and simulants. It is concluded that an integrated fog generator system (IFGS) with EMEE sensor developed in the current work can be utilized broadly to control fog microphysical parameters, leading to an optimum aerosol/chemical species’ cleaning process.

Gradient-Based Metrics for the Evaluation of Image Defogging

Fog, haze, or smoke are standard atmospheric phenomena that dramatically compromise the overall visibility of any scene, critically affecting features such as the illumination, contrast, and contour detection of objects. The decrease in visibility compromises the performance of computer vision algorithms such as pattern recognition and segmentation, some of which are very relevant to decision-making in the field of autonomous vehicles. Several dehazing methods have been proposed that either need to estimate fog parameters through physical models or are statistically based. But physical parameters greatly depend on the scene conditions, and statistically based methods require large datasets of natural foggy images together with the original images without fog, i.e., the ground truth, for evaluation. Obtaining proper fog-less ground truth images for pixel-to-pixel evaluation is costly and time-consuming, and this fact hinders progress in the field. This paper aims to tackle this issue by proposing gradient-based metrics for image defogging evaluation that do not require a ground truth image without fog or a physical model. A comparison of the proposed metrics with metrics already used in the NTIRE 2018 defogging challenge as well as several state-of-the-art defogging evaluation metrics is performed to prove its effectiveness in a general situation, showing comparable results to conventional metrics and an improvement in the no-reference scene. A Matlab implementation of the proposed metrics has been developed and it is open-sourced in a public GitHub repository.

Study on Dust Removal Technology of Explosive Water Mist in Drill and Blast Tunnelling

In view of the problem that high concentration of dust is easily generated during rock tunnel drilling and blasting construction, explosive water mist to reduce dust is given in this paper. Water bag is set up on tunnel face and explosive water mist is used to reduce blasting dust concentration. With the help of numerical simulation software FLUENT and combined with theoretical analysis, The key parameters of explosion fog and dust reduction technology are obtained: water bag spacing, blasting time difference, water bag layout position, etc., which provides a theoretical basis for practical application of the technology. At the same time, combined with the field test of Huangtai tunnel blasting, the dust concentration with and without water mist was measured, respectively. The results show that the maximum dust removal rate of the tunnel section under the dust removal measures with water mist can reach 80.85%, the average dust removal rate can reach 65.16%. So, the dust removal effect is remarkable.

Performance of Opportunistic Beam Selection for OWC System Under Foggy Channel with Pointing Error

Performance of optical wireless communication (OWC) in outdoor environments can be significantly degraded due to the fog and pointing errors. In this letter, we consider a multi-aperture detector which employs a low complexity opportunistic beam selection (OBS) in order to improve the performance of OWC system. We analyze the OBS scheme by deriving computable bounds on the average signal-to-noise ratio (SNR), ergodic rate, and diversity order and compare its performance by deriving exact analytical expressions of a single-aperture system. The derived bounds provide insights on the system behavior depicting significant benefit for OWC systems with small link distances which are typical in foggy environments. We also demonstrate the effect of various parameters of fog and pointing error on the OWC performance and validate the derived analytical expressions using numerical and simulation analysis. A two-aperture OBS achieves an SNR gain of approximately 4 dB and improves the outage performance by more than 20 folds for a half-km OWC link comparing to the single-aperture system without acquiring the channel state information.

Influencia del deterioro cognitivo en el test freezing of gait-score: un estudio piloto

Objectiveto verify if cognitive impairment can affect the total score obtained on the Freezing of Gait score (FOG-score) test in patients with Parkinson's disease (PD). Material and methodA sectional, correlational non-exploratory study was carried out on thirty-four subjects, with mild to moderate PD disease. The participants carried out the FOG-score test and cognitive evaluation: the Mini-Mental State Examination (MMSE), the Frontal Assessment Battery (FAB) and the Fuld Object Memory Evaluation (FOME). Motor function was assessed by the motor subscale of Unified Parkinson's Disease Rating Scale (UPDRS) (part III). Resultsthere was a significant negative correlation between the FOG-score test and global cognition (MMSE) (r=.68; p<.001), memory-related parameters (FOME) (r=.64; P<.001) and executive functions (FAB) (r=.57; P<.001). The motor scores held lower relation with FOG parameters (r=.35; P>.005). Conclusionsthe results of this study suggest that cognitive impairment can strongly affect task performance of the FOG-score test. This suggests the need to adjust the cut-off point when assessing PD patients suffering from cognitive dysfunction. This could prevent the examiner from overestimating the existence and recurrence of freezing episodes in this population.

Distribution function approach to redshift space distortions. Part V: perturbation theory applied to dark matter halos

Numerical simulations show that redshift space distortions (RSD) introduce strong scale dependence in the power spectra of halos, with ten percent deviations relative to linear theory predictions even on relatively large scales (k < 0.1h/Mpc) and even in the absence of satellites (which induce Fingers-of-God, FoG, effects). If unmodeled these effects prevent one from extracting cosmological information from RSD surveys. In this paperwe use Eulerian perturbation theory (PT) and Eulerian halo biasing model and apply it to the distribution function approach to RSD, in which RSD is decomposed into several correlators of density weighted velocity moments. We model each of these correlators using PT and compare the results to simulations over a wide range of halo masses and redshifts. We find that with an introduction of a physically motivated halo biasing, and using dark matter power spectra from simulations,we can reproduce the simulation results at a percent level on scales up to k ∼ 0.15h/Mpc at z = 0, without the need to have free FoG parameters in the model.

Examining the impacts of ethanol (E85) versus gasoline photochemical production of smog in a fog using near-explicit gas- and aqueous-chemistry mechanisms

This study investigates the air quality impacts of using a high-blend ethanol fuel (E85) instead of gasoline in vehicles in an urban setting when a morning fog is present under summer and winter conditions. The model couples the near-explicit gas-phase Master Chemical Mechanism (MCM v. 3.1) with the extensive aqueous-phase Chemical Aqueous Phase Radical Mechanism (CAPRAM 3.0i) in SMVGEAR II, a fast and accurate ordinary differential equation solver. Summer and winter scenarios are investigated during a two day period in the South Coast Air Basin (SCAB) with all gasoline vehicles replaced by flex-fuel vehicles running on E85 in 2020. We find that E85 slightly increases ozone compared with gasoline in the presence or absence of a fog under summer conditions but increases ozone significantly relative to gasoline during winter conditions, although winter ozone is always lower than summer ozone. A new finding here is that a fog during summer may increase ozone after the fog disappears, due to chemistry alone. Temperatures were high enough in the summer to increase peroxy radical (RO2) production with the morning fog, which led to the higher ozone after fog dissipation. A fog on a winter day decreases ozone after the fog. Within a fog, ozone is always lower than if no fog occurs. The sensitivity of the results to fog parameters like droplet size, liquid water content, fog duration and photolysis are investigated and discussed. The results support previous work suggesting that E85 and gasoline both enhance pollution with E85 enhancing pollution significantly more at low temperatures. Thus, neither E85 nor gasoline is a ‘clean-burning’ fuel.

Application of Fog Monitoring with FY-3A Data

Fog is a type of weather phenomenon with great damage which has serious influence on human activities such as transportation and so on.It is of great significance for fog monitoring.Fog area can be monitored by satellite remote sensing technology,according to the spectral characteristics among fogs,clouds and underlying surface in visible,mid-infrared and thermal-infrared channels.The daytime fog experiment has been made by multi-channel threshold method with the VIRR data of FY-3A satellite in the east China on April 5,2010.And the characteristic parameters of fog,such as the optical thickness,the vertical thickness and the visibility have also been estimated in this paper.The result shows the feasibility of fog monitoring with FY-3A satellite data,and that the method is suitable for promoting operation of fog detection.

Model estimates of the fog parameters on the coasts of the Siberian reservoirs

Features are considered of using a two-dimensional model of the atmospheric boundary layer for estimation of coastal fog parameters for the Siberian reservoirs, based on reanalysis and on output data of a regional climate model. The model fog characteristics are compared with observations at the reservoirs of Surgut power plants. Examples are given of the fog characteristic calculation for the projected Evenki hydrosystem. It is shown that the data of regional climate model can be used if the changes are taken into account of background climate in the area of the projected reservoir.

Millimeter-Wave Attenuation Due to Fog and Clouds

The parameters of gamma drop size distribution model of fog and clouds are derived based on the liquid water content and optical visibility, the attenuation are calculated and discussed with this model and empirical relations of the liquid water content and the visibility or other parameters of fog and clouds. A new empirical formula to estimate fog and clouds attenuation is presented based on the Reyleigh absorption approximation, which is more accurate in general and can be used in wider frequency and temperature range than other empirical formulas.

Acoustic sounding of fog and rain

The coefficients and phase functions of sound scattering by a single rigid spherical particle whose parameter Mie changes in a wide range have been calculated with the use of exact formulas of the Mie scattering theory. Analytical expressions are given for the dependence of sound attenuation on the parameters of fog and rain and acoustic frequency. The acoustic scattering cross section of a single particle has been derived. New methods of acoustic sounding of fog and rain have been suggested and theoretically analyzed. Experimental data on the transformation of raindrop size distribution have been obtained by processing of raw spectra of acoustic signals recorded in rain for 20 s and 1, 2, 3, 5, and 25 min with cw bistatic sodars operating at frequencies of 5 and 40 kHz. The bimodal character of the raindrop size spectra was established. The position of the second maximum in the raindrop size spectrum was shifted with time toward larger raindrop sizes, from 0.3 to 1 mm. The estimated rain intensity varied from 0.5 to 1.9 mm per hour. The obtained results demonstrate that high-frequency cw bistatic sodars are very promising for measurements of fog and rain.

Influence of fog parameters on the aging of HTV silicone rubber

Testing of outdoor insulators in a fog chamber is universally used. Many factors affect the generation of fog. Fog parameters such as the pressure of the compressed air and the water flow rate feeding the nozzles to form the fog, as well as the size and the speed of the fog droplets impinging on the surface of the insulators, play a major role in the outcome of electrical performance tests. In order to be able to compare test results from different laboratories, the conditions of fog generation should be defined unambiguously and clearly. In the present paper relationships between air pressure, water flow rate and air speed which are related to the distribution and the speed of the fog droplets, are determined as a function of distance from the IEEE-IEC standard nozzles forming the fog. The distribution of different fog droplet sizes is measured. The influence of the fog parameters on the aging characteristics of surface resistance, surface roughness, leakage current and surface hydrophobicity of high temperature vulcanized (HTV) silicone rubber are presented.

Influence of Fog Parameters on Withstand Voltage of Contaminated Insulators

This paper describes the investigation results of fog parameters which affect the withstand voltage of contaminated insulators. As a result, the guideline is proposed on fog conditions such as density, droplet size distribution, temperature rise in the fog room, and so on, basing upon the comparison between natural and artificial fog conditions and the relation between fog condition and power-frequency withstand voltage.

Influence of Fog Parameters on Withstand Voltage of Contaminated Insulators

Influence of Fog Parameters on Withstand Voltage of Contaminated Insulators

AC Fog Withstand Test on Contaminated Insulators by Steam Fog

This paper describes the results of an investigation into how steam fog parameters affect the withstand voltage of artificially contaminated insualtors by the fog withstand method. We established the correlation between the steam flow rate and liquid water content of the fog. The fog withstand voltage showed a lower value with little dispersion at about 3 to 10 g/m3 of the maximum liquid water content. The minimum fog withstand voltage agreed well with the minimum flashover voltage obtained under natural conditions. We suggest that, for the fog withstand test using steam fog, the ideal fog condition would be about 3 to 7 g/m3 of the maximum liquid water content of the fog.

The effect of fog parameters on the testing of artificially contaminated insulators in a fog chamber

The paper analyzes the wetting process during the testing of artificially contaminated insulators. A calculation method is developed to determine the rate of wetting by condensation and by the collision of water droplets with the insulator surface. Series of tests show that the flashover voltage, the washing effect of fog and the leakage current all depend on the fog conditions. Different fog-generation methods (cold, warm, steam) are compared on the basis of calculations and experimental results. The paper concludes that the pollution test results for an artificially contaminated insulator depend on the fog parameters and the fog generation method. The operation of the fog chamber can be optimized by adjusting the fog parameters to achieve the minimum flashover voltage.