A solution algorithm for the numerical calculation of isothermal fluid flow inside gas turbine combustors is presented. The finite‐volume method together with curvilinear…
Abstract
A solution algorithm for the numerical calculation of isothermal fluid flow inside gas turbine combustors is presented. The finite‐volume method together with curvilinear non‐orthogonal coordinates and a non‐staggered grid arrangement is employed. Cartesian velocity components are chosen as dependent variables in the momentum equations. The turbulent flow inside the combustor is modelled by the k—ε turbulence model. The grid is generated by solving elliptic equations. This solution algorithm, which can be used on both can‐type and annular combustors, is tested on a water model can‐type combustor because of the availability of geometrical and experimental data for comparison.
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Mohammad Reza Pakatchian, Hossein Saeidi and Alireza Ziamolki
This study aims at enhancing the performance of a 16-stage axial compressor and improving the operating stability. The adopted approaches for upgrading the compressor are…
Abstract
Purpose
This study aims at enhancing the performance of a 16-stage axial compressor and improving the operating stability. The adopted approaches for upgrading the compressor are artificial neural network, optimization algorithms and computational fluid dynamics.
Design/methodology/approach
The process starts with developing several data sets for certain 2D sections by means of training several artificial neural networks (ANNs) as surrogate models. Afterward, the trained ANNs are applied to the 3D shape optimization along with parametrization of the blade stacking line. Specifying the significant design parameters, a wide range of geometrical variations are considered by implementation of appropriate number of design variables. The optimized shapes are analyzed by applying computational fluid dynamic to obtain the best geometry.
Findings
3D optimal results show improvements, especially in the case of decreasing or elimination of near walls corner separations. In addition, in comparison with the base geometry, numerical optimization shows an increase of 1.15 per cent in total isentropic efficiency in the first four stages, which results in 0.6 per cent improvement for the whole compressor, even while keeping the rest of the stages unchanged. To evaluate the numerical results, experimental data are compared with obtained data from simulation. Based on the results, the highest absolute relative deviation between experimental and numerical static pressure is approximately 7.5 per cent.
Originality/value
The blades geometry of an axial compressor used in a heavy-duty gas turbine is optimized by applying artificial neural network, and the results are compared with the base geometry numerically and experimentally.
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Shijo J.S. and Niranjana Behera
The purpose of this paper is to focus on predicting the pressure drop in fluidized dense phase pneumatic conveying of fine particles through pipelines by modelling the solids…
Abstract
Purpose
The purpose of this paper is to focus on predicting the pressure drop in fluidized dense phase pneumatic conveying of fine particles through pipelines by modelling the solids friction factor in terms of non-dimensional parameters using experimental data of definite pipeline configuration. Finally, the model is to be tested for a different pipeline configuration.
Design/methodology/approach
Solids friction factor has been expressed in terms of certain non-dimensional parameters such as density ratio, solids loading ratio and mean particle diameter to pipe diameter ratio, and a certain number of coefficients and exponents. Experimental data of five conveying materials (two types of fly ash, two types of alumina and one type of cement meal) for a pipeline configuration of diameter 53 mm and length 173 m and another conveying material EPS dust for two pipeline configurations (69-mm diameter, 168-m long; 105-mm diameter, 168-m long) have been used to calculate the unknown coefficients or exponents of the mathematical model for solids friction factor.
Findings
The developed model gives the best results in predicting the pressure drop for the pipelines that are less than 173-m long, but the model shows a large error for the pipelines more than 173-m long.
Research limitations/implications
Current research will be helpful for the researchers to model the process of pneumatic conveying through long distances.
Practical implications
The method will be helpful in conveying powder materials through long distances in cement or brick industry, alumina industry.
Social implications
Fly ash piles over at the nearby places of thermal power plants. Pneumatic conveying is the best method for transporting the fly ash from the location of power plants to the nearby brick industries or cement industries.
Originality/value
Solid friction factor has been presented in terms of four non-dimensional parameters and evaluated the accuracy in predicting the pressure drop for two different pipeline configurations.
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P. Koutmos, C. Mavridis and D. Papailiou
A two dimensional time‐dependent Navier Stokes formulation that encompasses aspects from both the LES formalism and the conventional k‐ε approaches was employed to calculate a…
Abstract
A two dimensional time‐dependent Navier Stokes formulation that encompasses aspects from both the LES formalism and the conventional k‐ε approaches was employed to calculate a range of reacting bluff‐body flows exhibiting high or low level large scale structure activity. Extensive regions of local flame extinction found in these bluff‐body flame configurations were treated with a partial equilibrium/two‐scalar exponential PDF combustion submodel combined with a local extinction criterion based on a comparison of the turbulent Damkohler number against the ratio of the scalar scale to the reaction zone thickness. A dual‐mode description, burning/ non‐burning, of combustion provided the local gas state. Comparisons between calculations and measurements indicated the ability of the method to capture all the experimentally observed variations in the momentum and reactive scalar mixing fields over a range of operating conditions from the lean to the rich blow‐out limit.
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The purpose of this paper is to describe a model that can be used in the estimation of thermal fatigue limited service life of induction coils.
Abstract
Purpose
The purpose of this paper is to describe a model that can be used in the estimation of thermal fatigue limited service life of induction coils.
Design/methodology/approach
Previous work indicates that the temperature of the cross section of an induction coil can be used to estimate thermal fatigue limited service life. This paper presents a model for estimating these temperatures based on a coupled model. Joule losses modelled in Flux2D are coupled with cooling modelled in Fluent3D. These models are controlled and combined by Python scripts that iterate the heat transfer and temperatures of heat exchange regions between the two domains.
Findings
The combined model is shown to converge nicely. The model is also applied to an optimization problem where a high power loss, copper region is surrounding a wedge‐shaped cooling channel. The point of the wedge was replaced by a radius that was optimized. The optimum was considered where the thermal fatigue service life is maximized, i.e. where the peak deviation from mean temperature in the cross section was at a minimum. The results show that the optimum corner radii are small, typically 0.25‐0.5 mm.
Originality/value
This is the first paper where the full model is presented and used to optimize specific cases.
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O. Korostynska, A. Mason and A. Al-Shamma'a
This paper aims to discuss the general principles behind the microwave sensing and demonstrates the potential of cavity microwave resonator device in real-time monitoring for…
Abstract
Purpose
This paper aims to discuss the general principles behind the microwave sensing and demonstrates the potential of cavity microwave resonator device in real-time monitoring for: environmental monitoring with the focus on wastewater pollution, a system for oil/gas/water content evaluation in a dynamic pipeline, a system for real-time determination of bacteria concentration and a method for non-invasive glucose determination.
Design/methodology/approach
Microwave sensing is a rapidly developing technology which has been successfully used for various industrial applications including water level measurements, material moisture content, in construction industry for non-invasive evaluation of structures and even in the healthcare industry for non-invasive real-time monitoring of glucose in diabetic patients. Novel microwave cavities designed and tested for specific applications are presented.
Findings
The paper provides experimental results of testing the novel microwave sensing systems in a range of industrial and healthcare applications and discusses the potential of these systems for real-time monitoring of processes and parameters.
Research limitations/implications
The concept of real-time microwave sensing was successfully tested, but further experiments are required to account for possible interference mechanisms before it can be used commercially on a large-scale.
Practical implications
It is suggested that a novel approach to wastewater monitoring, namely using specially designed microwave cavity sensors, could lead to a successful development of an advanced platform capable of providing for a real-time detection of water content with superior sensitivity. Also, a system for real-time multiphase fluid composition monitoring is reported, which is essential for sustainable oil industry operation.
Originality/value
The paper illustrated the potential of microwave sensing as a real-time monitoring platform for a broad spectrum of commercial applications, with a focus on system developed by the authors, namely, for the monitoring of a multiphase fluid flow in a dynamic oil pipeline, for real-time monitoring of nutrients concentration in wastewater and for healthcare industry, in particular for real-time non-invasive determination of the glucose levels and bacteria concentration.