Gianluca Coccia

Mathematical modeling of a prototype of parabolic trough solar collector

In this paper, a mathematical model of a parabolic trough collector (PTC) is described in detail and tested by comparing the efficiency predicted by the model with the efficiency measured through outdoor tests on a PTC prototype. The model accounts for optical and thermal losses, thus allowing the calculation of optical, thermal, and global efficiencies, and of all working parameters such as temperatures or heat fluxes on all parts of the receiver. The model is presented in detail and its implementation in a specific ambient for technical computation is also described. The application of the model to a specific prototype of parabolic trough collector is described: this prototype has been developed and tested at Universita Politecnica delle Marche and is intended for industrial process heat production. The comparison between experimental and calculated results shows an average error of about 3.82% and a maximum error of 14% on global efficiencies for tests with water in the temperature range 25–75 °C.

New Equation for the Liquid Viscosity of Silanes

This work presents a new formula to calculate the liquid viscosity of the inorganic family of silicon-based molecules. As a first step, the raw viscosity experimental data of silanes were collected...

Artificial neural network modelling of liquid thermal conductivity for alcohols

ABSTRACT This study investigates the applicability of artificial neural networks (ANNs) as an efficient tool for the description of thermal conductivity of liquid alcohols for a broad range of temperatures. The proposed multilayer perceptron has 1 hidden layer with 43 neurons, determined according to the constructive approach. The model developed was trained and validated on the set of data gathered, showing that the accuracy of the ANN model is higher than that of other approaches proposed in the literature. The experimental or experimental and predicted thermal conductivity data of alcohols were taken from the database due to the ‘DIPPR Database’. The ability of the ANN method to reproduce the original data was tested for 26 alcohols in the liquid phase at reduced temperatures ranging from 0.30 to 0.90. The maximum absolute deviations between experimental and calculated thermal conductivity data points are generally less than 0.0110%, while the average absolute deviations are usually less than 0.0016%. This study shows that the model used is a good alternative to estimating thermal conductivity of alcohols with excellent precision.

A modified Kardos equation for the thermal conductivity of refrigerants

This work presents a modification of the Kardos equation specifically oriented to refrigerants. The proposed equation was tested for both liquid and vapor thermal conductivities along saturation of the main refrigerants. In the Kardos equation, the thermal conductivity of liquids is a function of the density of the liquid, heat capacity at constant pressure, speed of sound in the liquid and average distance between the centers of the molecules. In the present version, the liquid molar volume and the distance between the surfaces of adjacent molecules were replaced by two constant parameters widely available for all the fluids: the critical density and radius of gyration. In this way, the resulting equation is much simpler, still being a scaled equation. In the proposed equations, an adimensional factor was regressed to minimize the deviations. The final equations were able to predict the thermal conductivity with AADL=3.6% for liquids and AADV=9.8% for vapors.

Artificial neural network for the second virial coefficient of organic and inorganic compounds: An ANN for B of organic and inorganic compounds

ABSTRACT An artificial neural network (ANN) to estimate the second virial coefficient, valid for organic and inorganic compounds, is presented. First, we statistically analyzed 6,531 experimental points, belonging to 234 fluids, collected from literature. The data were investigated with a factor analysis approach to identify the most significant parameters that influence the second virial coefficient. The factor analysis, combined with physical considerations, allowed to find four (Tr, Tc, Pc, ω) or five (μr) parameters as input variables for the ANN, according to the specific chemical family. The architecture of the proposed multi-layers perceptron (MLP) neural network consists of one input layer with five input variables (Tr, Tc, Pc, ω, μr), one output layer with one neuron (B) and two-hidden-layers with 19 neurons each. We trained, validated and tested several configurations of the neural network to obtain this network topology that minimizes the deviations between experimental and calculated points. Results show that the ANN is able to calculate the second virial coefficient with greater accuracy (RMSE = 29.38 cm3/mol) than that of correlations available in literature. To identify the outliers and applicability domain of the proposed MLP neural network, an outlier diagnosis based on the Leverage approach was performed. This analysis shows that the model is statistically valid.

Experimental characterization of a solar cooker with thermal energy storage based on solar salt

High temperature solar cooking allows to cook food fast and with good efficiency. An unavoidable drawback of this technology is that it requires nearly clear-sky conditions. In addition, evening cooking is difficult to be accomplished, particularly on the winter season during which solar radiation availability is limited to a few hours in the afternoon in most of countries. These restrictions could be overcome using a cooker thermal storage unit (TSU). In this work, a TSU based on solar salt was studied. The unit consists of two metal concentric cylindrical vessels, connected together to form a double-walled vessel. The volume between walls was filled with a certain amount of nitrate based phase change material (solar salt). In order to characterize the TSU, a test bench used to assess solar cooker performance was adopted. Experimental load tests with the TSU were carried out to evaluate the cooker performance. The obtained preliminary results show that the adoption of the solar salt TSU seems to allow both the opportunity of evening cooking and the possibility to better stabilize the cooker temperature when sky conditions are variable.

Standards and Testing

The performance of solar thermal collectors such as PTCs can be assessed by performing specific procedures described in standards. Standards generally followed in the solar energy field are the ISO 9806, the ANSI/ASHRAE 93 and the EN 12975-1, which will be presented in this chapter. The measurements and the procedures required for testing PTCs will be discussed in detail, in particular focusing the attention on the three most important parameters of a solar collector: the time constant, the thermal efficiency and the incident angle modifier. Due to its importance, uncertainty in thermal efficiency testing will be described extensively. Also, quality test methods will be briefly discussed.