Browsing by Author "Bozkuş, Zafer"

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Citation - Scopus: 1
Air Gun With Water Bullet
(Eindhoven University of Technology, 2023) Bozkuş, Zafer; Dinçer, A. Ersin; Tijsseling, A. S.; van de Ven, Alphons A.F.
The gun is a 12 m long inclined pipe of 0.1 m diameter which is connected to a charge of compressed air contained in a 0.5 m3 vessel. The bullet is a slug of water sitting in the upstream lower end of the pipe. The trigger is a hand-operated valve. The target is an elbow at the upstream higher end of the pipe. The smoking gun effect is created by a mist of water coming out of the pipe after each shot. The apparatus is not a toy but meant for serious research. When steam lines are out of operation and/or lack thermal insulation, liquid water collects in the lower parts of the system. System restart may accelerate the water slugs to velocities as high as 50 m/s, and subsequent slug impacts on elbows and orifices may cause pressure peaks with magnitudes only encountered in water-hammer events. The experimental programme consists of water slugs fired towards an elbow with an open end, a closed end, and an orifice end. The varied parameters are air pressure, water mass, outlet condition (open, closed, orifice). Upstream driving pressure and downstream impact pressure are measured in each experimental run. Pressure peaks up to 50 bar have been observed. Experimental results are compared with preliminary predictions from basic one-dimensional models. © 2024 Elsevier B.V., All rights reserved.
Citation - Scopus: 2
Developing Empirical Formulae for Scour Depth in Front of Inclined Bridge Piers
(Croatian Association of Civil Engineers, 2023) Fedakar, Halil Ibrahim; Dinçer, A. Ersin; Bozkuş, Zafer
Because of the complex flow mechanism around inclined bridge piers, previous studies have proposed different empirical correlations to predict the scouring depth in front of piers, which include regression analysis developed from laboratory measurements. However, because these correlations were developed for particular datasets, a general equation is still required to accurately predict the scour depth in front of inclined bridge piers. The aim of this study is to develop a general equation to predict the local scour depth in front of inclined bridge pier systems using multilayer perceptron (MLP) and radial-basis neural-network (RBNN) techniques. The experimental datasets used in this study were obtained from previous research. The equation for the scour depth of the front pier was developed using five variables. The results of the artificial neural-network (ANN) analyses revealed that the RBNN and MLP models provided more accurate predictions than the previous empirical correlations for the output variables. Accordingly, analytical equations derived from the RBNN and MLP models were proposed to accurately predict the scouring depth in front of inclined bridge piers. Moreover, from the sensitivity analyses results, we determined that the scour depths in front of the front and back piers were primarily influenced by the inclination angle and flow intensity, respectively. © 2023 Elsevier B.V., All rights reserved.