3. Mühendislik Fakültesi / Faculty of Engineeringhttps://hdl.handle.net/11147/52020-02-23T20:52:06Z2020-02-23T20:52:06ZArtificial neural networks for estimating daily total suspended sediment in natural streamsTayfur, GökmenGüldal, Veyselhttps://hdl.handle.net/11147/77022020-02-19T07:01:26Z2006-01-01T00:00:00ZArtificial neural networks for estimating daily total suspended sediment in natural streams
Tayfur, Gökmen; Güldal, Veysel
Estimates of sediment loads in natural streams are required for a wide spectrum of water resources engineering problems from optimal reservoir design to water quality in lakes. Suspended sediment constitutes 75-95% of the total load. The nonlinear problem of suspended sediment estimation requires a nonlinear model. An artificial neural network (ANN) model has been developed to predict daily total suspended sediment (TSS) in rivers. The model is constructed as a three-layer feedforward network using the back-propagation algorithm as a training tool. The model predicts TSS rates using precipitation (P) data as input. For network training and testing 240 sets of data sets were used. The model successfully predicted daily TSS loads using the present and past 4 days precipitation data in the input vector with R2 = 0.91 and MAE = 34.22 mg/L. The performance of the model was also tested against the most recently developed non-linear black box model based upon two-dimensional unit sediment graph theory (2D-USGT). The comparison of results revealed that the ANN has a significantly better performance than the 2D-USGT. Investigation results revealed that the ANN model requires a period of more than 75 d of measured P-TSS data for training the model for satisfactory TSS estimation. The statistical parameter range (xmin - xmax) plays a major role for optimal partitioning of data into training and testing sets. Both sets should have comparable values for the range parameter.
2006-01-01T00:00:00ZElectrocaloric properties of Ba0. 8Sr0. 2Ti1-xZrxO3 (0≤ x≤ 0.1) system: The balance between the nature of the phase transition and phase coexistenceŞanlı, KerimanAdem, Umuthttps://hdl.handle.net/11147/76942020-02-12T15:00:11Z2020-02-01T00:00:00ZElectrocaloric properties of Ba0. 8Sr0. 2Ti1-xZrxO3 (0≤ x≤ 0.1) system: The balance between the nature of the phase transition and phase coexistence
Şanlı, Keriman; Adem, Umut
We investigate the electrocaloric effect of Ba0.8Sr0.2Ti1-xZrxO3 (0 ≤ x ≤ 0.1) system by comparing the electrocaloric temperature change (ΔT) of different compositions belonging to the different regions of the phase diagram. We show that as the amount of Zr increases, electrocaloric temperature change initially decreases as the phase transition gets diffuse then increases again as the composition of the samples are located closer to the critical point where different ferroelectric phases coexist. Since the critical point is reached at relatively low Zr substitution levels (i.e. around x = 0.07), the phase transition doesn't get too diffuse and thefore the compositions between x = 0 and x = 0.10 (which contains higher Zr than the critical point composition) have comparable ΔT values. Electrocaloric efficiency of these compositions (x = 0.03, 0.05 and 0.07) is around 0.20 K mm/kV at 20 kV/cm. We discuss the results in terms of the balance between the nature of the phase transition and proximity to the critical point, based on the phase diagram.
2020-02-01T00:00:00ZConstructal structures with and without high-conductivity inserts for self-coolingÇetkin, Erdalhttps://hdl.handle.net/11147/76912020-02-12T09:00:07Z2016-01-01T00:00:00ZConstructal structures with and without high-conductivity inserts for self-cooling
Çetkin, Erdal
Here we show how a heat generating domain can be gained self-cooling capability with embedded cooling channels and with and without high-conductivity fins. The volume of the heat generating domain is fixed, so is the overall volume of the cooling channels and high-conductivity inserts. Even though the coolant volume decreases with embedded high-conductivity fins, the peak temperature also decreases with high-conductivity inserts. The peak temperature is affected by the location, shape and complexity of the fins and the volume fraction. This paper documents how these degrees of freedoms should be changed in order to minimize peak temperature. This paper also discusses how the volume fraction affects each fin shape in order to minimize the peak temperature. This paper uncovers that the fins should be distributed non-equidistantly, and that high-conductivity material should be inserted as fins (bulks of high-conductivity materials) rather than uniform distribution in the domain. This paper concludes that the overall thermal conductance of a heat generating domain can be maximized by freely morphing the shape of the high-conductivity material. The optimal design exists for given conditions and assumptions, and this design should be morphed when conditions and assumptions change. This conclusion is in accord with the constructal law. Each optimal design for given conditions and assumptions is the constructal design
2016-01-01T00:00:00ZSurface charge-dependent transport of water in graphene nano-channelsÇelebi, Alper TungaBarışık, MuratBeşkök, Alihttps://hdl.handle.net/11147/76622020-02-05T13:00:14Z2018-01-01T00:00:00ZSurface charge-dependent transport of water in graphene nano-channels
Çelebi, Alper Tunga; Barışık, Murat; Beşkök, Ali
Deionized water flow through positively charged graphene nano-channels is investigated using molecular dynamics simulations as a function of the surface charge density. Due to the net electric charge, Ewald summation algorithm cannot be used for modeling long-range Coulomb interactions. Instead, the cutoff distance used for Coulomb forces is systematically increased until the density distribution and orientation of water atoms converged to a unified profile. Liquid density near the walls increases with increased surface charge density, and the water molecules reorient their dipoles with oxygen atoms facing the positively charged surfaces. This effect weakens away from the charged surfaces. Force-driven water flows in graphene nano-channels exhibit slip lengths over 60 nm, which result in plug-like velocity profiles in sufficiently small nano-channels. With increased surface charge density, the slip length decreases and the apparent viscosity of water increases, leading to parabolic velocity profiles and decreased flow rates. Results of this study are relevant for water desalination applications, where optimization of the surface charge for ion removal with maximum flow rate is desired.
2018-01-01T00:00:00Z