Saad Ahmed

An Experimental Investigation of a Cold Thermal Energy Storage System

This research work investigates the heat transfer characteristics of a direct contact heat exchanger. A cold two phase refrigerant R134a is injected into water stored in an evaporator to exchange directly heat with the water and form clathrates during the charging mode of the operation. The clathrate is used later for obtaining chilled water for air-conditioning purposes. It was found that the performance of the system depends on the refrigerant, its ratio to water, compressor speed and the mass flow rate of the refrigerant.

Performance Evaluation of a Thermal Energy Storage

The direct contact heat transfer technique gives better heat transfer rates. In this paper, the operation of a simple system was simulated under different operating conditions. During the charging mode of the operation, refrigerant R134a is injected into water stored in an evaporator to exchange directly heat with the water and form clathrates. Later, the clathrate is used to cool water which is used for air-conditioning purposes. Direct contact charging and/or discharging eliminate the necessity of a heat exchanger inside the storage tank and leads to an effective heat transfer method. The results indicate that the performance of the system depends on the refrigerant type, compressor speed and the mass flow rate of the refrigerant.

Numerical analysis of free vortex flow in a combustor model

Swirling flow in gas turbine combustors is a very common tradition in aerospace and/or industrial applications. This is because, swirl flows help to anchor flames, and cause better air-fuel mixing which enhance combustion efficiency and reduce harmful emissions. As a result, it is of a high interest to be able to predict the behavior of swirling turbulent flows in order to better design combustors. Therefore, this study performs a numerical simulation of an isothermal swirling turbulent flow of air at room temperature in a combustor model, created using a 0.4 free vortex swirler. The simulation was performed via a computational fluid dynamics (CFD) software. Results of three different turbulence models were compared against experimental measurements found in the open literature for the same swirler and same all flow specifications upstream of the swirler. Consequently, it was found that the k-ε turbulence model best predicts the actual swirl flow behavior and exhibits superior prediction quality compared to the other tested models.

Numerical Analysis of Boundary Layer Separation Control

The flow field of a NACA 0024 airfoil is investigated using ANSYS CFX 14. The airfoil used is equipped with a rotating cylinder mounted at its leading edge. Shear Stress Transport (SST) k-ω turbulence model is used in accordance with time dependent simulations. The numerical results are compared with published experimental data. The mean lift coefficient, the pressure coefficient and the velocity profiles at different sections of the airfoil surface are obtained and compared with Experimental results. Both cases of rotation and no rotation of the cylinder are presented. The maximum lift coefficient as well as the stall angle is increased when the cylinder rotation is present. The numerical data of lift coefficient values compared well with the experimental data.

Thermodynamic Evaluation of a Small Wind Turbine

A small personal use wind turbine (PWT) is studied and tested for power, exergy and energy evaluation under different operating conditions. The wind turbine incorporates non-twisted blades of 1.5 m span and 0.27 m chord, using NACA 63418 airfoil. Using the earlier test results at pitch angles of 22°, 34° and 38° between the wind speeds of 4 m/s to 7 m/s, torque produced by each blade is determined. It is desired to calculate the torque as it is difficult to measure it for a small wind turbine. Using the governing equations and available computational fluid dynamics software, the total torque on each blade is determined. The resultant torque yielded the mechanical power output of the PWT. Using the available power, energy and exergy in the air flow, corresponding efficiencies are determined. To determine the changes in energy and exergy with respect to the wind speed, wind-chill factor expression is utilized. Results are collected for a wide range of wind speeds and pitch angles. Power, energy, exergy and their corresponding efficiency is evaluated to determine the optimal use pitch angle and ambient conditions. The pitch angles of 22° and 38o yielded high efficiencies although 22° produced the higher rotational speed as compared to 38°. The result suggests better performance for continuous wind speed conditions at low pitch angles — with respect to the rotating plane. For non-continuous wind conditions, higher pitch angles appeared beneficial.Copyright

Turbulent Flow Energy Budget Calculations in a Dump Combustor Model

Turbulent statistics and energy budgets were calculated for a swirling turbulent flow using Generalized Feed Forward Neural Network (GFFNN) in a dump combustor model. Knowledge of turbulent statistics and energy budgets of fluid flow inside a combustor model is very useful and essential for better and/or optimum designs of gas turbine combustors. Several experimental techniques utilizing two dimensional (2D) or three dimensional (3D) Laser Doppler Velocimetry (LDV) measurements provide only limited discrete information at given points; especially, for the cases of complex flows such as dump combustor swirling flows. For these flows, numerical interpolating schemes are unsuitable. Recently, neural networks proved to be viable means of expanding a finite set of experimental measurements in order to enhance the understanding of complex phenomenon. This investigation showed that artificial neural networks are suitable for the prediction of turbulent swirling flow characteristics in a model dump combustor. These techniques are proposed for better designs and/or optimum performance of dump combustors.Copyright

Control of Unstable Flow Using Rough Surfaces

The function of centrifugal blowers/compressors is limited at low-mass flow rates by fluid flow instabilities leading to rotating stall. These instabilities limit the flow range in which they can operate. An experimental investigation was conducted to investigate a model of radial vaneless diffuser at stall as well as stall-free operating conditions. The speed of the blower was kept constant at 2000 RPM, while the mass flow rate was reduced gradually to investigate the steady and unsteady flow characteristics of the diffuser. These measurements were reported for diffuser diameter ratios, Do / Di, of 1.5, 1.75 and 2.0 with diffuser width ratio, b / Di, of 0.055. The rotating stall pattern with one stall cell was dominant over the pattern with two cells which appeared at flow rates lower than the critical. In addition, the instability in the diffuser was delayed to a lower flow coefficient when rough surfaces were attached to one or both walls of the diffuser with the lowest values achieved by attaching the rough surface to the shroud wall. Results show that the roughness has no significant effect on stall cell frequencies.

Free Vortex Turbulent Swirling Flow Reconstruction Using a Neural Network

Experimental data of the continuous evolution of fluid flow characteristics in a dump combustor is very useful and essential for better and optimum designs of gas turbine combustors and ramjet engines. Unfortunately, experimental techniques such as 2D LDV measurements provide only limited discrete information at given points; especially, for the cases of complex flows such as free vortex dump combustor swirling flows. For this type of flows, usual numerical interpolating schemes appear to be unsuitable. Recently, neural networks have emerged as viable means of expanding a finite data set of experimental measurements to enhance better understanding of a particular complex phenomenon. This study showed that artificial neural networks are suitable for the prediction of free vortex turbulent swirling flow characteristics in a model dump combustor. These techniques are proposed for optimum designs of dump combustors and ramjet engines.© 2012 ASME

Reconstruction of turbulence statistics in a dump combustor using neural networks

Artificial Neural networks are utilized to predict flow properties of a confined, isothermal, and swirling flowfield in an axisymmetric sudden expansion combustor using a two-component laser Doppler velocimetry capable of measuring the mean velocity components and their statistics. Generalized feedforward, radial basis function, and coactive neuro-fuzzy inference system neural networks are tested and the results are compared in the reconstruction of the axial, tangential velocity profiles, and their root mean squares of their fluctuating velocity components. The results showed that generalized feed forward networks give the best prediction with the highest correlation coefficients for most of the flow profiles.

Predictions of Turbulence Intensity in a Combustor Model Using Neural Network Analysis

Predictions of turbulence intensity and continuous evolution of fluid flow characteristics in a combustor model are useful and essential for better and optimum design of gas turbine combustors. Many experimental techniques such as Laser Doppler Velocimetry (LDV) measurements provide only limited discrete information at given points; especially, for the cases of complex flows such as dump combustor swirling flows. For this type of flow, usual numerical interpolating schemes appear to be unsuitable. Neural Network Analysis (ANN) is proposed and the results are presented in this paper and are compared with the experimental data used for training purposes. This pilot study showed that artificial neural network is an appropriate method for predicting swirl flow characteristics in a model of a dump combustor. These techniques are proposed for better designs and optimization of dump combustors.Copyright