Experimental investigation of solidification in metal foam enhanced phase change material

A major challenge for the use of phase change materials (PCMs) in thermal energy storage (TES) is overcoming the low thermal conductivity of PCM’s. The low conductivity gives rise to limited power during charging and discharging TES. Impregnating metal foam with PCM, however, has been found to enhance the heat transfer. On the other hand, the effect of foam parameters such as porosity, pore size and material type has remained unclear. In this paper, the effect of these foam parameters on the solidification time is investigated. Different samples of PCM-impregnated metal foam were experimentally tested and compared to one without metal foam. The samples varied with respect to choice of material, porosity and pore size. They were placed in a rectangular cavity and cooled from one side using a coolant flowing through a cold plate. The other sides of the rectangular cavity were Polymethyl Methacrylate (PM) walls exposed to ambient. The temperature on the exterior walls of the cavity was monitored as well as the coolant flow rate and its temperature. The metal foam inserts reduced the solidification times by at least 25 %. However, the difference between the best performing and worst performing metal foam is about 28 %. This shows a large potential for future research.This study has received funding from European Union’s Horizon 2020 research and innovation programme under grant agreement Nº 657466 (INPATH-TES)

Probabilistic flow regime classification of horizontal refrigerant flow based on capacitive void fraction measurements

Paper presented at the 7th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Turkey, 19-21 July, 2010.A capacitive void fraction sensor was developed to study the objectivity in flow pattern mapping of horizontal refrigerant two-phase flow in macro-scale tubes. Sensor signals were gathered with R410A and R134a in an 8mm I.D. smooth tube at a saturation temperature of 15°C in the mass velocity range of 200 to 500 kg/m2s and vapour quality range from 0 to I in steps of 0.025. A visual classification based on high speed camera images is made for comparison reasons. A statistical analysis of the sensor signals shows that the average, the variance and a high frequeNcy contribution parameter are suitable for flow regime classification into slug flow, intermittent flow and annular flow by using a the fuzzy c-means clustering algorithm. This soft clustering algorithm perfectly predicts the slug/intermittent flow transition compared to our visual observations. The intermittent/annular flow transition is found at slightly higher vapour qualities for R410A compared to the prediction of [Barbieri et al., 2008, Flow patterns in convective boiling of refrigerant R-134a in smooth tubes of several diameters, 5th European Thermal-Sciences Conference, The Netherlands]. An excellent agreement was obtained with R134a. This intermittent/annular flow transition is very gradual. A probability approach can therefore better describe such a transition. The membership grades of the cluster algorithm can be interpreted as flow regime probabilities. Probabilistic flow pattern maps are presented for R41OA and R134a in an 8mm I.D. tube.ej201

Probabilistic flow regime classification of horizontal refrigerant flow based on capacitive void fraction measurements

Paper presented at the 7th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Turkey, 19-21 July, 2010.A capacitive void fraction sensor was developed to study the objectivity in flow pattern mapping of horizontal refrigerant two-phase flow in macro-scale tubes. Sensor signals were gathered with R410A and R134a in an 8mm I.D. smooth tube at a saturation temperature of 15°C in the mass velocity range of 200 to 500 kg/m2s and vapour quality range from 0 to I in steps of 0.025. A visual classification based on high speed camera images is made for comparison reasons. A statistical analysis of the sensor signals shows that the average, the variance and a high frequeNcy contribution parameter are suitable for flow regime classification into slug flow, intermittent flow and annular flow by using a the fuzzy c-means clustering algorithm. This soft clustering algorithm perfectly predicts the slug/intermittent flow transition compared to our visual observations. The intermittent/annular flow transition is found at slightly higher vapour qualities for R410A compared to the prediction of [Barbieri et al., 2008, Flow patterns in convective boiling of refrigerant R-134a in smooth tubes of several diameters, 5th European Thermal-Sciences Conference, The Netherlands]. An excellent agreement was obtained with R134a. This intermittent/annular flow transition is very gradual. A probability approach can therefore better describe such a transition. The membership grades of the cluster algorithm can be interpreted as flow regime probabilities. Probabilistic flow pattern maps are presented for R41OA and R134a in an 8mm I.D. tube.ej201

Efficiency calculations of air-cooled gas turbines with intercooling

Paper presented at the 5th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, South Africa, 1-4 July, 2007.The working temperature of a gas turbine, necessary to achieve high efficiency, makes cooling of the first turbine stages unavoidable. Air and steam can be used for cooling. A model for an air-cooled gas turbine based on the work of Young and Wilcock [J.B. Young, R.C. Wilcock, ASME J. Turbomachinery 124 (2002) 207–221] is implemented in AspenTM. Simple cycle calculations with realistic parameters of current machines are made and confirm the results of Wilcock et al. [R.C. Wilcock, J.B. Young, J.H. Horlock, ASME J. Eng. Gas Turb. Power 127 (2005) 109–120] that increasing the turbine inlet temperature no longer means an increase in gas turbine cycle efficiency. This conclusion has important consequences for gas turbines because it breaks with the general accepted trend of increasing the TIT. An intercooled gas turbine cycle is intensively investigated, taking the turbine cooling into account. Intercooling not only lowers the work of compression, but also lowers cooling air temperatures. The major influences of the intercooling on the gas turbine cycle are mapped and explained. Optimum intercooling pressure for maximum gas turbine cycle efficiency is much lower than halfway compression. A simulation of the LMS100, the most recent gas turbine on the market from GE Energy, is made to verify the simulation methodology. The claimed intercooled cycle efficiency of 46% is confirmed. Further increasing the pressure ratio and TIT can still improve the performance of the intercooled gas turbine cycle.cs201

Horizontal two-phase flow characterization and classification based on capacitance measurements

Paper presented at the 5th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, South Africa, 1-4 July, 2007.Two-phase flow regime prediction is of great importance for designing evaporators and condensers because the influence of the heat transfer coefficients is strongly related to the flow regimes. These flow regimes are often presented in flow pattern maps. As most flow pattern maps are based on visual observations or transition models fitted to data obtained by visual observations, these maps still lack of objectivity in defining the flow regime transitions. In order to refine the flow regime maps and to add objective flow characteristics to the transitions boundaries, a two-phase flow sensor was developed. The sensor measures the capacitance of the two-phase flow. Because of the difference in dielectric constant of liquid and vapour and the dependency of the capacitance to the internal distribution of liquid and vapour in the cross-section of the tube, the sensor is able to characterize two-phase flow regimes. Measures were taken to improve the accuracy and reliability of the measurements. A charge/discharge transducer with a fast response was built to dynamically measure capacitance differences in the picofarad range. A large number of experiments was done with air-water flow. The setup was able to cover all flow regimes for horizontal flow in a 9mm tube. The sensor can be used as a flow regime detector. Important for obtaining good classification results, information about vapour-liquid distribution in the cross-section of the tube should be combined with time-dependent information at the measurement location. To obtain both spatial and time information, statistical parameters of the probability density function and the power spectral distributions of the signals were selected to build up a statistical classification model. Decision trees and support vector machines were used for this purpose. A high-speed camera was used as a comparison for the results of the flow detector. More than 90% of the test runs were correctly classified by both statistical techniques.cs201

Experimental investigation of solidification in metal foam enhanced phase change material

A major challenge for the use of phase change materials (PCMs) in thermal energy storage (TES) is overcoming the low thermal conductivity of PCM’s. The low conductivity gives rise to limited power during charging and discharging TES. Impregnating metal foam with PCM, however, has been found to enhance the heat transfer. On the other hand, the effect of foam parameters such as porosity, pore size and material type has remained unclear. In this paper, the effect of these foam parameters on the solidification time is investigated. Different samples of PCM-impregnated metal foam were experimentally tested and compared to one without metal foam. The samples varied with respect to choice of material, porosity and pore size. They were placed in a rectangular cavity and cooled from one side using a coolant flowing through a cold plate. The other sides of the rectangular cavity were Polymethyl Methacrylate (PM) walls exposed to ambient. The temperature on the exterior walls of the cavity was monitored as well as the coolant flow rate and its temperature. The metal foam inserts reduced the solidification times by at least 25 %. However, the difference between the best performing and worst performing metal foam is about 28 %. This shows a large potential for future research