The Mechanical Behavior of Optical Fiber as a Function of Dew Point Temperature

1998 ◽  
Vol 531 ◽  
Author(s):  
J. L. Armstrong ◽  
M. J. Matthewson ◽  
C. R. Kurkjian
Keyword(s):  
Optical Fiber ◽  
Reaction Order ◽  
Dew Point ◽  
Condensed Phases ◽  
Test Environment ◽  
Point Temperature ◽  
Dew Point Temperature ◽  
Air Temperatures ◽  
Degradation Reaction ◽  
Kinetics Of

AbstractThe dew point temperature (DPT) is defined as the temperature at which condensation will form from a gas containing moisture. The DPT, which is a measure of the water vapor reactivity, depends on the relative humidity (RH) and the temperature of the gas. The strength of optical fiber has been shown to have a dependence on the humidity and the temperature of the test environment. The results of one study imply that the strength over a range of temperature and humidity can be expressed as a function of the DPT only. While attractive for its simplicity, this idea suggests that the strength depends only on the thermodynamics of the equilibrium between the vapor and condensed phases of water and does not depend on the kinetics of the reaction between water and silica. In the work described here, the strength has been measured at various humidities and temperatures in order to test the dependence on dew point temperature. It was found that the strength degradation is not solely described by the DPT. The strength and dynamic fatigue data were also interpreted by a stress assisted chemical kinetics model. The degradation reaction order with respect to humidity at different air temperatures was found to be approximately two.

scholarly journals DRYING KINETICS OF PEELED COFFEE SUBMITTED TO DIFFERENT TEMPERATURES AND RELATIVE HUMIDITY OF THE AIR OF DRYING AFTER PARTIAL DRYING

2020 ◽  
Vol 28 ◽  
pp. 460-476
Author(s):  
Rodrigo Victor Moreira ◽  
Jefferson Luiz Gomes Correa ◽  
Ednilton Tavares de Andrade ◽  
Roney Alves da Rocha
Keyword(s):  
Relative Humidity ◽  
Effective Diffusivity ◽  
Drying Kinetics ◽  
Dew Point ◽  
Diffusivity Coefficient ◽  
Point Temperature ◽  
Dew Point Temperature ◽  
Different Temperatures ◽  
Kinetics Of

The mathematical modelling is fundamental for the understanding of the related processes the drying, that influences the quality of the coffee drink. The objective of this study was to evaluate the influence of different relative humidity of the drying air after partial drying on drying kinetics of peeled coffees. Coffee fruits were harvested in the cherry stage and processed by wet, resulting in the portion of peeled coffee. Eleven treatments of drying were accomplished, being nine results of the combination of three dry bulb temperatures and three dew point temperatures, more two treatments without the control of the dew point temperatures. The control of the relative humidity by the dew point temperature was made after the grains reached the partial drying. Among the studied models, those of Diffusion Approximation and Modified Midilli were the most adequate for describing the drying process of the first and second part of drying respectively. The effective diffusivity coefficient of water in coffee grains ranged from 0.81 x 10-11 to 1.84 x 10-11 m² .s-1 during the first part of the drying and ranged from 1.49 x 10-11 to 3.29 x 10-11 m² .s-1 during the second part of the drying, increasing significantly with the reduction of the dew point temperature and increase of the dry bulb temperature.

Further Study in Relationship Between Fruit and Air Temperatures

1942 ◽  
Vol 23 (1) ◽  
pp. 16-21
Author(s):  
Philip J. Powell
Keyword(s):  
Air Temperature ◽  
Low Temperatures ◽  
Fruit Juice ◽  
Dew Point ◽  
Petroleum Jelly ◽  
Temperature Index ◽  
Point Temperature ◽  
Dew Point Temperature ◽  
Air Temperatures ◽  
Rate Of Cooling

Summary Summarizing, the following points are emphasized as being important considerations in the proper heating of orange groves in Florida to protect the fruit against low temperatures:1.) With a fast drop of the air temperature, the fruit temperature tends to parallel it closely. With slowly falling or stationary air temperature, the fruit temperature invariably drops lower than the air temperature, except occasionally when freezing of the fruit has already begun. On dry nights, exposed oranges tend to maintain a temperature as much as 3° or more lower than a stationary or slowly falling air temperature. On nights when dew and frost form on the fruit, this temperature difference is usually reduced to from 1° to 2°. The factors believed responsible for this radically different characteristic of Florida oranges, as compared with California oranges, are the thinner rind and the greater amount of moisture in the rind of the Florida orange. Both these properties cause a faster rate of cooling by allowing more rapid conduction of heat from within the orange to the surface than does the thicker, drier skin of the California orange.2.) The proper use of fruit thermometers provides the best temperature index in scientific grove heating. On nights of dry cold, unshielded fruit thermometer records are representative of true grove conditions. From experimental data, however, it appears that to obtain reliable records on nights when the dew point temperature is high and frost forms, the puncture in the fruit made by the thermometer must be sealed with petroleum jelly, or some other suitable substance, to prevent the frost particles from coming in contact with the fruit juice at this point; otherwise, premature crystallization in the fruit will occur.

scholarly journals Improving efficiency and lowering operating costs of evaporative cooling

2021 ◽  
Vol 338 ◽  
pp. 01027
Author(s):  
Jan Taler ◽  
Bartosz Jagieła ◽  
Magdalena Jaremkiewicz
Keyword(s):  
Electricity Consumption ◽  
Open Circuit ◽  
Dew Point ◽  
Operating Costs ◽  
Water Evaporation ◽  
Total Water ◽  
Point Temperature ◽  
Dew Point Temperature ◽  
Adiabatic Cooling ◽  
Positive Effect

Cooling towers, or so-called evaporation towers, use the natural effect of water evaporation to dissipate heat in industrial and comfort installations. Water, until it changes its state of aggregation, from liquid to gas, consumes energy (2.257 kJ/kg). By consuming this energy, it lowers the air temperature to the wet-bulb temperature, thanks to which the medium can be cooled below the ambient temperature. Evaporative solutions are characterized by continuous water evaporation (approx. 1.5% of the total water flow) and low electricity consumption (high EER). Evaporative (adiabatic) cooling also has a positive effect on the reduction of electricity consumption of cooled machines. Lowering the relative humidity (RH) by approx. 2% lowers the wet-bulb temperature by approx. 0.5°C, which increases the efficiency of the tower, operating in an open circuit, expressed in kW, by approx. 5%, while reducing water consumption and treatment costs. The use of the M-Cycle (Maisotsenko cycle) to lower the temperature of the wet thermometer to the dew point temperature will reduce operating costs and increase the efficiency of cooled machines.

scholarly journals Estimating Daily Dew Point Temperature Using Machine Learning Algorithms

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 582 ◽  
Author(s):  
Sultan Noman Qasem ◽  
Saeed Samadianfard ◽  
Hamed Sadri Nahand ◽  
Amir Mosavi ◽  
Shahaboddin Shamshirband ◽  
...  
Keyword(s):  
Meteorological Parameters ◽  
Gene Expression Programming ◽  
Machine Learning Algorithms ◽  
Dew Point ◽  
Coefficient Of Determination ◽  
Support Vector ◽  
M5 Model Tree ◽  
Point Temperature ◽  
Dew Point Temperature ◽  
Input Parameters

In the current study, the ability of three data-driven methods of Gene Expression Programming (GEP), M5 model tree (M5), and Support Vector Regression (SVR) were investigated in order to model and estimate the dew point temperature (DPT) at Tabriz station, Iran. For this purpose, meteorological parameters of daily average temperature (T), relative humidity (RH), actual vapor pressure (Vp), wind speed (W), and sunshine hours (S) were obtained from the meteorological organization of East Azerbaijan province, Iran for the period 1998 to 2016. Following this, the methods mentioned above were examined by defining 15 different input combinations of meteorological parameters. Additionally, root mean square error (RMSE) and the coefficient of determination (R2) were implemented to analyze the accuracy of the proposed methods. The results showed that the GEP-10 method, using three input parameters of T, RH, and S, with RMSE of 0.96°, the SVR-5, using two input parameters of T and RH, with RMSE of 0.44, and M5-15, using five input parameters of T, RH, Vp, W, and S with RMSE of 0.37 present better performance in the estimation of the DPT. As a conclusion, the M5-15 is recommended as the most precise model in the estimation of DPT in comparison with other considered models. As a conclusion, the obtained results proved the high capability of proposed M5 models in DPT estimation.

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