G. Gutierrez*, P. Rodriguez, A. Lecuona, M. Venegas, J. Nogueira

Universidad Carlos III de Madrid (UC3M). Departamento de Ingenieria Termica y de Fluidos. Avda.
Universidad 30, 28911 Leganes, Madrid, Spain

* Corresponding Author, glgutier@ing. uc3m. es

Abstract

An experimental facility applying the concept of adiabatic absorption has been designed and built in Universidad Carlos III de Madrid. Plate heat exchangers are incorporated in the design functioning as generator, condenser, sub-cooler and solution heat exchanger. Other components include a separator and two fin-coiled tubes as evaporators. Trials were carried out in order to characterize components and performance. The range of controlled hot fluid temperature corresponds to a solar thermal energy source (below 100°C). Performance parameters, cooling capacity and COP, are expressed in terms of an ideal absorption model and compared with experimental results. The differences observed between ideal and experimental results help to identify the influence of components performances on the overall performance of the facility. The evaluation of the ideal and experimental cooling powers allows detecting a low performance of evaporators as both dry operation and overflow. Other influence factors are described and their effect is included in the thermodynamic analysis of the absorption cycle.

Keywords: Adiabatic absorption, Lithium bromide, Chillers.

Greek letter:

П efficiency

1. Introduction

Absorption machines offer the possibility of amortizing thermal solar installations during summer, at the same time avoiding polluting emissions to atmosphere and increasing sustainability.

The adiabatic process is being investigated as a method for improving absorption in a chiller. It consists on dispersing the solution inside an adiabatic chamber. The resulting heat is extracted downstream using a compact heat exchanger. Thus, the mass and heat transfer processes are split in separated apparatus. Ref. [1-3] summarizes state of the art, including experimental and theoretical studies concerning adiabatic absorption. Further works on adiabatic absorption using aqueous LiBr, focus on experimental work [4] and simulation or theoretical studies [5, 6].

Interpretation of experimental data must include the particular features, in both design and operation, of the facility here presented. For this duty, diagnostic versions of the models are of much help. A basic thermodynamic model, including such features is presented and compared with experimental results, resulting from this the detection of some operational difficulties.

2. Experimental facility

The highly flexible experimental facility forms a single-effect water — lithium bromide absorption cooling system. The test facility design incorporates compact PHEs, due to the well-known benefits regarding to high heat transfer capacity in a reduced volume.

The absorption process takes place in an adiabatic chamber and the heat is extracted in an external PHE (subcooler). Because the solution absorbs less vapour as its temperature is higher, it is necessary to re-circulate part of the solution to the absorber after it has been cooled in the PHE (mr). Both the solution coming from the generator mstrong and the re-circulated solution mr flow

inside the absorber as free falling drops. The experimental setup configuration, the data acquisition system and the experimental procedure were described in detail in a previous work [7]. Fig. 1 shows a diagram of the experimental facility.

The facility is highly instrumented, such that individual component performance can de evaluated.

Data of temperature, pressure and mass flow rates in every component were recorded in intervals of 0.5 seconds in order to accurately determine steady state periods. The experimental setup was configured to allow determining COP and thermal powers exchanged in the different components.

A complete calibration process is periodically carried out for all instruments showed in Fig.1. This way, measurement errors can be reduced as far as possible. The uncertainty for an experimental result R, which is function of n different parameters x, is calculated as:

R = f(X1, X2,k xn )
Ur =	(1)

The uncertainty of performance parameters reached 16% at the worst case, see Fig. 4.