The detailed flow field and heat transfer were experimentally investigated in a channel with a circular cross section and equipped with a helical rib of low blockage ratio. Stereoscopic Particle Image Velocimetry (S-PIV) was applied in order to measure the three components of the mean and turbulent velocities in the symmetry plane of the channel. Additionally, steady-state Liquid Crystal Thermography (LCT) and Infrared Thermography (IRT) were employed in order to study the convective heat transfer coefficient on the wall. Measurements were carried out more than six pitches downstream of the rib origin, presenting periodic velocity and heat transfer fields from this location on. The resulting velocity and heat transfer fields show similarities with those present in channels of plane walls, such as low momentum and heat transfer areas upstream and downstream of the obstacle, and high kinetic energy and heat transfer a few rib heights downstream of the obstacle. On the other hand, the shape of the rib induces a swirling motion with the same sense as the rib. The azimuthal mean velocity is negligible in the core of the pipe, but it shows considerable levels close to the wall.
The detailed flow field and heat transfer were experimentally investigated in a channel with a circular cross section and equipped with a helical rib of low blockage ratio. Stereoscopic particle image velocimetry (S-PIV) was applied in order to measure the three components of the mean and turbulent velocities in the symmetry plane of the channel. Additionally, steady-state liquid crystal thermography (LCT) and infrared thermography were employed in order to study the convective heat transfer coefficient on the wall. Measurements were carried out more than six pitches downstream of the rib origin, presenting periodic velocity and heat transfer fields from this location on. The resulting velocity and heat transfer fields show similarities with those present in channels of plane walls, such as low momentum and heat transfer areas upstream and downstream of the obstacle, and high kinetic energy and heat transfer a few rib heights downstream of the obstacle. On the other hand, the shape of the rib induces a swirling motion with the same sense as the rib. The azimuthal mean velocity is negligible in the core of the pipe, but it increases considerably close to the wall.
Although the positive impact of cycle humidification on the performance of micro Gas Turbines (mGTs) has already been proven numerically and experimentally, very detailed modeling of the system performance remains challenging, especially the determination of the recuperator effectiveness, which has the highest impact on the final cycle performance. Indeed, the recuperator performance depends strongly on the mass flow rate of the air stream and its humidification level, two parameters that are difficult to measure accurately. Accurate modeling of the recuperator performance under both dry and humidified conditions is thus essential for correct assessment of the potential of humidified mGT cycles. In this paper, we present a detailed analysis of the recuperator performance under humidified conditions using averaged experimental data, extended with the application of a Support Vector Regression (SVR) on a time series to improve noise-modeling of the output signal, and thus enhance the accuracy of the monitoring process. In a first step, the missing experimental parameters were obtained indirectly, using experimental data in combination with the compressor map. Despite the low accuracy, some general trends could be observed, indicating that the recuperator, despite having an increased total exchanged heat flux, is too small to exploit the full potential of the humidification. In a second step, by means of the SVR model, a first attempt was made to improve the accuracy and reduce the scatter on the recuperator performance determination. The predicted results with the SVR indicated indeed a reduced scatter, opening a pathway towards online recuperator performance prediction.
The micro Humid Air Turbine (mHAT) has been proven to be the most effective route for cycle humidification; however, so far, all research efforts focused on optimizing the mHAT performance at nominal electrical load, and no thermal load. Nevertheless, in a DES context, the thermal and electrical load of the mGT needs to be changed depending on the demand, requiring both optimal nominal and part load performances. To address this need, in this paper, we present the first step towards the development of a control strategy for a Turbec T100 mGT-mHAT test rig. First, using experimental data, the global performance, depending on the operating point as well as the humidity level, has been assessed. Second, the performance of the saturation tower is analyzed to assess the optimal water injection system control parameter settings. Results show that optimal mHAT performance can only be obtained when the working fluid leaving the saturation tower is fully saturated, but does not contain a remaining liquid fraction. Under these conditions, a maximal amount of waste heat is transferred from the water to the mGT working fluid in the saturation tower. From these data, some general observations can be made to optimize the performance; being maximizing injection pressure and aiming for a water flow rate of ≈5 m3/h . However, having a specific control matrix, that allows setting the saturation tower control parameters for any set of operational setpoint and the inlet conditions would be of more interest.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.