Civil Engineering
https://hdl.handle.net/20.500.12511/4163
İnşaat Mühendisliği2024-03-29T08:43:39ZA new innovative method for model efficiency performance
https://hdl.handle.net/20.500.12511/10119
A new innovative method for model efficiency performance
Şen, Zekai; Şişman, Eyüp; Kızılöz, Burak
In every aspect of scientific research, model predictions need calibration and validation as their representativity of the record measurement. In the literature, there are a myriad of formulations, empirical expressions, algorithms and software for model efficiency assessment. In general, model predictions are curve fitting procedures with a set of assumptions that are not cared for sensitively in many studies, but only a single value comparison between the measurements and predictions is taken into consideration, and then the researcher makes the decision as for the model efficiency. Among the classical statistical efficiency formulations, the most widely used ones are bias (BI), mean square error (MSE), correlation coefficient (CC) and Nash-Sutcliffe efficiency (NSE) procedures all of which are embedded within the visual inspection and numerical analysis (VINAM) square graph as measurements versus predictions scatter diagram. The VINAM provides a set of verbal interpretations and then numerical improvements embracing all the previous statistical efficiency formulations. The fundamental criterion in the VINAM is 1:1 (45 degrees) main diagonal along which all visual, science philosophical, logical, rational and mathematical procedures boil down for model validation. The application of the VINAM approach is presented for artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS) model predictions.
2022-01-01T00:00:00ZClimate change impact on water structures
https://hdl.handle.net/20.500.12511/10098
Climate change impact on water structures
Şen, Zekai
The literature is full of global warming and climate change impact studies on the environment, ecosystem, and different components of hydrological cycle. Unfortunately, these impacts on engineering structure design, maintenance, and operation and management studies are rather rare. Climate change impact started to play significant role since the last three decades almost in every aspects of life especially on meteorological and climatological events and their impacts on water resources, which are managed by engineering structures. Its effects on hydrometeorological records are searched with objective methodologies quantitatively, but the same is not valid for engineering water structures performances among which are dams, weirs, reservoirs, culverts, channels, bridges, wells, highways and their side drainages, levees, etc. This paper provides the review of the necessary adaptation, combat and mitigation activities against the climate change and variability for protection, construction or augmentation of the engineering water structures design capacity. Land use practices and geomorphological changes also trigger the climate change impacts on the engineering water structures. The main aim of this paper is to present the impact of such changes on the engineering water structure capacity, operation and maintenance.
2022-01-01T00:00:00ZWet and dry period identification method through serial correlation decomposition
https://hdl.handle.net/20.500.12511/10095
Wet and dry period identification method through serial correlation decomposition
Şen, Zekai
The serial correlation coefficient is the linear dependence procedure used most frequently to identify the short-memory dependence in a given hydrometeorology time series. The serial correlation formulation can be decomposed into four hydrometeorologically important parts: the wet (surplus) spell and dry (deficit) spell (drought) durations in addition to up-crossing and down-crossing components. The only negative values are available for up-crossing and down-crossing cases in the two successive standard variate multiplications, which implies that the first-order serial correlation coefficient has a lower dependence value with more contributions from the up- and down-crossing components. The difference between this methodology and those available in the literature is in the explicit use of the correlation coefficient for the identification of the abovementioned drought features. The validity of this new methodology is revealed through extensive Monte Carlo simulation and actual application to lengthy (1840-2003) Danube River monthly and annual discharges.
2022-01-01T00:00:00ZHydroelectric energy potential classification via hypsographical curve concept
https://hdl.handle.net/20.500.12511/10014
Hydroelectric energy potential classification via hypsographical curve concept
Şen, Zekai
Human activities are directly related to fossil fuel consumption and cause global warming and climate change effects by emitting greenhouse gas into the lower atmosphere. To reduce and adapt to such effects, renewable energy sources such as surface dams, including hydroelectric energy (HE) generation units, are gaining importance. In the current literature, HE potential calculations are based on formulations that are quite simple, clear and do not distinguish between different situations. In this paper, two classification methodologies are proposed for better assessment of HE production. The first one is based on the concept of the hypsographic curve to distinguish different drainage basin features into "Young," "Mature" and "Old." The second classification takes into account the newly defined energy index (EI) principle, which helps to classify the HE generation capability of drainage basins into "Very low," "Low," "Normal," "High" and "Very high." The application of the proposed methodology is presented for three drainage basins from the upstream sub-basins of the Tigris River in Turkey. A comparison of the results shows that the proposed methodologies not only give numerical values but also sets linguistically rational and logical rules for the HE potential of a drainage basin. In the upstream basin of the Tigris River, the EI values vary between 0.705 and 0.122, corresponding to the "High" and "Low" categories, respectively. It is recommended that these two classification procedures be considered before the construction of any dam for HE production.
2022-01-01T00:00:00Z