O. García-Valladares

The evaluation of a small capacity shell and tube ammonia evaporator

Abstract The use of ammonia as refrigerant is widespread in vapour compression and ammonia/water absorption systems. Ammonia is not actually used in low capacity applications mainly because of the lack of economical available equipment. For this reason, the objective of this study is the numerical and experimental evaluation of a small capacity ammonia shell and tube evaporator with enhanced heat transfer surfaces. An experimental system to evaluate small capacity heat exchangers was developed. A shell and tube evaporator with external low fin tubes was successfully tested. The experimental uncertainty for the evaporator capacity has been estimated within ±5.5%. The experimental results were used to validate a heat exchanger numerical tool that predicts reasonably well the cooling capacity and load outlet temperatures. The methodology presented in this work can be applied to evaluate other refrigerants in similar shell and tube evaporators and to optimize the design of an evaporator for a specific application.

Evaluation of Void Fraction Correlations for the Statistical and Numerical Analysis of Two-Phase Flows Inside Producing Geothermal Wells

The modeling of heat and fluid flow inside two-phase geothermal wells is a vital task required for the study of the production performance. Gas void fraction is one of the crucial parameters required for a better prediction of pressure and temperature gradients in two-phase geothermal wells. This parameter affects the correct matching between simulated and measured data. Modeling of two-phase flow inside wells is complex because two phases exist concurrently (exhibiting various flow patterns that depend on their relative concentrations, the pipe geometry, and the mass flowrate). A reliable modeling requires the precise knowledge of the two-phase flow patterns (including their transitions and some flow parameters). In this work, ten empirical correlations were used to estimate the gas void fraction in vertical-inclined pipes, and to evaluate their effect on the prediction of two-phase flow characteristics of some Mexican geothermal wells. High quality downhole pressure/ temperature logs collected from four producing geothermal wells were studied [Los Azufres, Mich. (Az-18); Los Humeros, Pue. (H-1), and Cerro Prieto, B.C. (M-90 and M-201)]. The pressure/ temperature gradients were simulated using an improved version of the wellbore simulator GEOPOZO, and the gas void fraction correlations. The simulated results were statistically compared with measured field data.Copyright

Evaluation of the Thermal Performance of a Solar Water Heating Thermosyphon Versus a Two-Phase Closed Thermosyphon Using Different Working Fluids

A water heating closed two-phase thermosyphon solar system was designed and built. The system consists of a flat plate solar collector coupled to a thermotank by a continuous copper tubing in which the working fluid circulates. The working fluid evaporates in the collector and condensates in the thermotank transferring its latent heat to the water through a coil heat exchanger. The tested fluids are acetone and R134a. The thermal performance of the proposed systems is compared with a conventional solar water thermosyphon under the same operating conditions. Advantages of a two-phase system include the elimination of freezing, fouling, scaling and corrosion. Geometry and construction materials are the same except for the closed circuit presented in the two-phase system. Data were collected from temperature and pressure sensors throughout the two systems. Early results suggest that R134a may provide a better performance than acetone for this kind of systems.

Development of a New Void Fraction Correlation for Modeling Two-Phase Flow in Producing Geothermal Wells Using Artificial Neural Networks

An artificial neural network (ANN) was used to develop a new empirical correlation to estimate void fractions for modeling two-phase flows in geothermal wells. Flowing pressure, wellbore diameter, steam quality, fluid density and viscosity, and Reynolds numbers were used as input data. An explicit relationship among the input data was obtained from an ANN model. A computational architecture based on, the Levenberg-Marquardt optimization algorithm, the hyperbolic tangent sigmoid transfer-function, and the linear transfer-function, was designed. A geothermal database containing thirty-two data sets logged in production well tests were used both to train and to validate the ANN. The best training results were obtained for an ANN architecture of five neurons in the hidden layer, which made possible to predict void fractions with a satisfactory efficiency (R2 = 0.992). From this ANN training pattern, a new empirical correlation was developed and coupled into a wellbore simulator for modeling two-phase flows in other geothermal wells (to avoid bias). Four well-known engineering correlations for calculating the void fraction were simultaneous evaluated. The simulated results (obtained with the five void fraction correlations) were statistically compared with measured field data. A better agreement between simulated and field data was systematically obtained for the new ANN correlation with matching errors less than 3%. These results suggest that the new empirical correlation can be reliable used to estimate void fractions in two-phase geothermal wellbores.Copyright