scholarly journals Minimization of loss in small scale axial air turbine using CFD modeling and evolutionary algorithm optimization

2016 ◽  
Vol 102 ◽  
pp. 841-848 ◽  
Author(s):  
Ali Bahr Ennil ◽  
Raya Al-Dadah ◽  
Saad Mahmoud ◽  
Kiyarash Rahbar ◽  
Ayad AlJubori
Keyword(s):  
Evolutionary Algorithm ◽  
Cfd Modeling ◽  
Small Scale ◽  
Algorithm Optimization ◽  
Air Turbine

CFD Modeling of a Small Scale Solar Pond

2016 ◽  
Author(s):  
Margarida Giestas ◽  
J Milhazes ◽  
D Loureiro ◽  
A Joyce ◽  
P J Coelho
Keyword(s):  
Cfd Modeling ◽  
Small Scale ◽  
Solar Pond

scholarly journals Application of Scaling-Law and CFD Modeling to Hydrodynamics of Circulating Biomass Fluidized Bed Gasifier

2021 ◽  
Author(s):  
Mazda Biglari ◽  
Hui Liu ◽  
Ali Elkamel ◽  
Ali Lohi
Keyword(s):  
Fluidized Bed ◽  
Particle System ◽  
Scaling Law ◽  
Computational Cost ◽  
Cfd Modeling ◽  
Hydrodynamic Characteristics ◽  
Small Scale ◽  
Small Column ◽  
Cfd Models ◽  
Fluidized Bed Gasifier

Two modeling approaches, the scaling-law and CFD (Computational Fluid Dynamics) approaches, are presented in this paper. To save on experimental cost of the pilot plant, the scaling-law approach as a low-computational-cost method was adopted and a small scale column operating under ambient temperature and pressure was built. A series of laboratory tests and computer simulations were carried out to evaluate the hydrodynamic characteristics of a pilot fluidized-bed biomass gasifier. In the small scale column solids were fluidized. The pressure and other hydrodynamic properties were monitored for the validation of the scaling-law application. In addition to the scaling-law modeling method, the CFD approach was presented to simulate the gas-particle system in the small column. 2D CFD models were developed to simulate the hydrodynamic regime. The simulation results were validated with the experimental data from the small column. It was proved that the CFD model was able to accurately predict the hydrodynamics of the small column. The outcomes of this research present both the scaling law with the lower computational cost and the CFD modeling as a more robust method to suit various needs for the design of fluidized-bed gasifiers.

Evolutionary Algorithm Optimization of Staggered Biological or Biomimetic Composites Using the Random Fuse Model

2020 ◽  
Vol 13 (3) ◽  
Author(s):  
Gianluca Costagliola ◽  
Roberto Guarino ◽  
Federico Bosia ◽  
Konstantinos Gkagkas ◽  
Nicola M. Pugno
Keyword(s):  
Evolutionary Algorithm ◽  
Algorithm Optimization

scholarly journals Is There a Future for Small-Scale Cogeneration in Europe? Economic and Policy Analysis of the Internal Combustion Engine, Micro Gas Turbine and Micro Humid Air Turbine Cycles

Energies ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 413 ◽  
Author(s):  
Marina Montero Carrero ◽  
Irene Rodríguez Sánchez ◽  
Ward De Paepe ◽  
Alessandro Parente ◽  
Francesco Contino
Keyword(s):  
Internal Combustion Engine ◽  
Gas Turbine ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Positive Energy ◽  
Small Scale ◽  
Humid Air ◽  
Electrical Efficiency ◽  
Micro Gas Turbine ◽  
Air Turbine

If more widely deployed, small-scale cogeneration could increase energy efficiency in Europe. Of the two main commercially available technologies—the Internal Combustion Engine (ICE) and the micro Gas Turbine (mGT)—the ICE dominates the market due to its higher electrical efficiency. However, by transforming the mGT into a micro Humid Air Turbine (mHAT), the electrical efficiency of this cycle can increase, thus enhancing its operational flexibility. This paper presents an in-depth policy and economic assessment of the the ICE, mGT and mHAT technologies for dwellings based in Spain, France and Belgium. The hourly demands of average households, the market conditions and the subsidies applicable in each region are considered. The aim is twofold: to evaluate the profitability of the technologies and to assess the cogeneration policies in place. The results show that only the ICE in Brussels is economically viable, despite all units providing positive energy savings in all locations (except mHAT in Spain). Of the three different green certificate schemes offered in Belgium, Brussels is the one leading to the best outcome. Spain awards both capital and operational helps, although auto-consumption is not valued. The same applies to the complex French feed-in tariff. Conclusively, with the current policies, investing in small-scale cogeneration is in general not attractive and its potential efficiency gains remain unveiled.

scholarly journals Prediction of turbulence eddy dissipation of water flow in a heated metal foam tube

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Meisam Babanezhad ◽  
Iman Behroyan ◽  
Ali Taghvaie Nakhjiri ◽  
Mashallah Rezakazemi ◽  
Azam Marjani ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Fuzzy Inference System ◽  
Metal Foam ◽  
Fuzzy Inference ◽  
Cfd Modeling ◽  
Coefficient Of Determination ◽  
Small Scale ◽  
Inlet Temperature ◽  
Inference System ◽  
Turbulence Parameters

Abstract The insertion of porous metal media inside the pipes and channels has already shown a significant heat transfer enhancement by experimental and numerical studies. Porous media could make a mixing flow and small-scale eddies. Therefore, the turbulence parameters are attractive in such cases. The computational fluid dynamics (CFD) approach can predict the turbulence parameters using the turbulence models. However, the CFD is unable to find the relation of the turbulence parameters to the boundary conditions. The artificial intelligence (AI) has shown potential in combination with the CFD to build high-performance predictive models. This study is aimed to establish a new AI algorithm to capture the patterns of the CFD results by changing the system’s boundary conditions. The ant colony optimization-based fuzzy inference system (ACOFIS) method is used for the first time to reduce time and computational effort needed in the CFD simulation. This investigation is done on turbulent forced convection of water through an aluminum metal foam tube under constant wall heat flux. The ANSYS-FLUENT CFD software is used for the simulations. The x and y of the fluid nodal locations, inlet temperature, velocity, and turbulent kinetic energy (TKE) are the inputs of the ACOFIS to predict turbulence eddy dissipation (TED) as the output. The results revealed that for the best intelligence of the ACOFIS, the number of inputs, the number of ants, the number of membership functions (MFs) and the rule are 5, 10, 93 and 93, respectively. Further comparison is made with the adaptive network-based fuzzy inference system (ANFIS). The coefficient of determination for both methods was close to 1. The ANFIS showed more learning and prediction times (785 s and 10 s, respectively) than the ACOFIS (556 s and 3 s, respectively). Finding the member function versus the inputs, the value of TED is calculated without the CFD modeling. So, solving the complicated equations by the CFD is replaced with a simple correlation.

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