MODELING OF SUBSURFACE HORIZONTAL POROUS PIPE IRRIGATION UNDER DIFFERENT CONDITIONS

Horizontal porous pipe method is one of the most efficient systems of irrigation in arid and semi-arid areas. The main aim of this study is to simulate the subsurface horizontal porous pipe irrigation under different conditions. By this method of irrigation, an optimum amount of water is reached to the crop. Moreover, it saves more water than the other irrigation systems. Simulation models by HYDRUS/2D are described the distribution of wetting shapes in two different soil textures through the system of United States Department of Agriculture, USDA, namely as loam and silt soils. The system is designed for three diameters of 6, 7, and 8 cm installed at 15, 20, and 25 cm below the soil surface under three application heads of 25, 50, and 75 cm. Horizontal and vertical advance of the wetting front shapes in loam are greater than silt soil. The numerical values of horizontal and vertical advance are compared with those of predicted by the formulas, showing that average relative error values not more than 2 %. This indicated that the formulas may be used as a tool for designing and investigating the subsurface horizontal porous pipe irrigation system.

Velocity prediction of nanofluid in a heated porous pipe: DEFIS learning of CFD results

Utilizing artificial intelligence algorithm of adaptive network-based fuzzy inference system (ANFIS) in combination with the computational lfuid dynamics (CFD) has recently revealed great potential as an auxiliary method for simulating challenging fluid mechnics problems. This research area is at the beginning, and needs sophisticated algorithms to be developed. No studies are available to consider the efficiency of the other trainers like differential evolution (DE) integrating with the FIS for capturing the pattern of the simulation results generated by CFD technique. Besides, the adjustment of the tuning parameters of the artificial intelligence (AI) algorithm for finding the highest level of intelligence is unavailable. The performance of AI algorithms in the meshing process has not been considered yet. Therfore, herein the Al2O3/water nanofluid flow in a porous pipe is simulated by a sophisticated hybrid approach combining mechnsitic model (CFD) and AI. The finite volume method (FVM) is employed as the CFD approach. Also, the differential evolution-based fuzzy inference system (DEFIS) is used for learning the CFD results. The DEFIS learns the nanofluid velocity in the y-direction, as output, and the nodes coordinates (i.e., x, y, and z), as inputs. The intelligence of the DEFIS is assessed by adjusting the methd’s variables including input number, population number, and crossover. It was found that the DEFIS intelligence is related to the input number of 3, the crossover of 0.8, and the population number of 120. In addition, the nodes increment from 4833 to 774,468 was done by the DEFIS. The DEFIS predicted the velocity for the new dense mesh without using the CFD data. Finally, all CFD results were covered with the new predictions of the DEFIS.

Pressure and temperature predictions of Al2O3/water nanofluid flow in a porous pipe for different nanoparticles volume fractions: combination of CFD and ACOFIS

Artificial intelligence (AI) techniques have illustrated significant roles in finding general patterns of CFD (Computational fluid dynamics) results. This study is conducted to develop combination of the ant colony optimization (ACO) algorithm with the fuzzy inference system (ACOFIS) for learning the CFD results of a physical case study. This binary join of the ACOFIS and CFD was used for pressure and temperature predictions of Al2O3/water nanofluid flow in a heated porous pipe. The intelligence of ACOFIS is investigated for different input numbers and pheromone effects, as the ant colony tuning parameter. The results showed that the intelligence of the ACOFIS could be found for three inputs (x and y nodes coordinates and nanoparticles fraction) and the pheromone effect of 0.1. At the system intelligence, the ACOFIS could predict the pressure and temperature of the nanofluid on any values of the nanoparticles fraction between 0.5 and 2%. Comparing the ANFIS and the ACOFIS, it was shown that both methods could reach the same accuracy in predictions of the nanofluid pressure and temperature. The root mean square error (RMSE) of the ACOFIS (~ 1.3) was a little more than that of the ANFIS (~ 0.03), while the total process time of the ANFIS (~ 213 s) was a bit more than that of the ACOFIS (~ 198 s). The AI algorithms process time (less than 4 min) shows their ability in the reduction of CFD modeling calculations and expenses.

Detailed comparison of the performance between a simple and a modified mono-block-layer-built type solid oxide fuel cell

A detailed comparison of the performance between a simple Mono-Block-Layer-Build (MOLB) type Solid Oxide Fuel Cell (SOFC) geometry and a MOLB type SOFC with an embedded porous pipe in the air supply channel is carried out. The study considers constant and variable porosities along the porous pipe, fed with an airflow in a counter-flow arrangement. Four cases are analyzed: a) without the porous pipe, b) with a pipe of constant porosity, c) with two different porosities, and d) with four variable porosities. This work is based in a three-dimensional Computational Fluid Dynamics (CFD) model that considers the phenomena of mass transfer, heat transfer, species transport and electrochemical reactions. Detailed comparisons of the voltage, temperature and species concentration are illustrated. The electrode-electrolyte interface contours of species concentration, temperature and electric fields are compared. The results show that there is approximately twice the current density in the geometry that considers the two different porosities compared to the simple geometry. The consumption of hydrogen has the same behavior for the entire tested current density, while the availability of oxygen at the cathode-electrolyte interface is improved in cases with porous pipe compared to the simple MOLB-type geometry. The use of a porous pipe embedded in the air channel showed that it is possible to have a wider operating range of a MOLB-type SOFC, and allowed to obtain a more homogeneous temperature distribution on the electrode-electrolyte interface of the SOFC, consequently, there is the possibility of reducing the thermal stress in the SOFC.

Thermal Performance of a Heated Pipe in the Presence of a Metal Foam and Twisted Tape Inserts

To meet the demand for more efficient ways of cooling and heating, new designs and further development of heat exchangers is essential in industry. The present study focuses on the thermal performance of a circular pipe with two inserts. The first insert consists of a porous medium having a porosity of 0.91, and the second one consists of a single twist solid insert. Different ranges of heating conditions have been applied for different flow rates. Water and titanium dioxide (TiO2) nanofluid 1% vol are the liquid media used for cooling. Laminar flow is assumed for two different Reynolds numbers of 1000 and 2000. The results of the study have shown that the twisted tape insert increases the thermal efficiency of the pipe more than the porous media insert and the plain pipe. In addition, different temperature readings in the cross section of the pipe have indicated that the twisted tape helps mixing up the fluid and provides a constant temperature in the overall volume of the fluid, whereas for the porous media insert and plain pipe the fluid temperature increases in the fluid particles close to the pipe inner surface. TiO2 nanofluid exhibited an enhancement when compared to water for a plain and porous pipe. However, this enhancement was absent when a twisted insert is used.