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Application of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) in Modeling the Effects of Selected Input Variables on the Period of Oscillation in an Unsteady Flow Through Surge Chamber
Current Issue
Volume 1, 2014
Issue 3 (May)
Pages: 15-23   |   Vol. 1, No. 3, May 2014   |   Follow on         
Paper in PDF Downloads: 37   Since Aug. 28, 2015 Views: 1832   Since Aug. 28, 2015
Authors
[1]
Ilaboya, I. R., University of Benin; Department of Civil Engineering, Faculty of Engineering, PMB 1154, Benin City, Nigeria.
[2]
Oti, E. O., University of Benin; Department of Civil Engineering, Faculty of Engineering, PMB 1154, Benin City, Nigeria.
[3]
Atikpo E., Department of Civil Engineering, Igbinedion University, Okada, Edo State, Nigeria.
[4]
Enamuotor, B. O., Department of Civil Engineering, Delta State University, Abraka, Nigeria.
[5]
Umukoro, L. O., Department of Civil Engineering, Igbinedion University, Okada, Edo State, Nigeria.
Abstract
In this research paper, an attempt was made to model the significant effects and the interactions of some selected input variables on the period of oscillation in an unsteady flow through surge chambers using adaptive neuro-fuzzy techniques. The choice of adaptive neuro-fuzzy technique is based on the fact that, it is a hybrid modeling algorithm that combines both neural network and fuzzy logic to obtain better result. The inlet valve to the reservoir was opened and adjusted to give a steady level of discharge from an overflow weir for a predetermined period of time. The flow rate of the water was thereafter computed using the volume against time relationship. A surge was then initiated following a sudden closure of the valve and the dynamics of flow behaviour was studied based on the period of oscillation. Statistical studies on the effects of selected input variables such as surge tower diameter, time of flow, velocity of flow, and rate of flow on the operational dynamics of unsteady flow in surge chambers was done using design of experiment (DOE) employing the 2-level factorial design with 3 central points’ and one replication. Results obtained were then modeled using Adaptive Neuro-Fuzzy Inference Technique (ANFIS) incorporated into MATLAB in fuzzy logic toolbox to determine the input variable (s) that possess the highest significant effects on the response variable (period of oscillation) and also to develop a Fuzzy Inference Systems (FIS) structure which can be employed to study the adequacy of results from similar experiment. Results obtained from the modeling shows that surge tower diameter with a root mean square error of 0.7360 appears to be the single variable with the highest significant effects on the amplitude of displacement. More also, for the combine variable effects, surge (tower diameter and velocity of flow) having a combine root mean square error of 0.4410 were seen to possess the highest significant effects on the amplitude of displacement.
Keywords
Period of Oscillation, Design of Experiment, 2-Level Factorial Design, Unsteady Flow, and Adaptive Neuro-Fuzzy Technique
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