Ali Osman Pektas

Computational modeling with sensitivity analysis: case study velocity distribution of natural rivers

Determining the velocity profile of an open channel is essential in many hydraulic workspaces such as channel improvement studies, sediment modeling, and energy and turbidity calculations. Since the field observations are labor intensive and time-consuming, many empirical equations have been used for many years. Additionally, many data-based modeling studies have been conducted for both natural rivers and experimental channels. There are two objectives of this study. The first one consists of developing accurate models and criticizing the model performances based on the observational velocity dataset. Hence, classification and regression tree (C&RT), artificial neural network (ANN), and multilinear stepwise regression models are used with different input sets and the models are compared. The second objective is to gain a brief insight about the relationships of the velocity distribution model parameters and determining the significant variables for usage of further modeling studies by considering the co-linearity effects. The relative importance of input variables is investigated on settled models by using sensitivity analysis. The results of the sensitivity analysis indicated that for low-slope natural river studies, instead of using superfluous variables, using only four parameters (Ush, z/H, y/T and z/Y) is adequate to obtain accurate models. The predictive performances of C&RT model and the ANN model were found to be very close to each other, while the multilinear models appeared insufficient. The four variable input set is found superior to other input sets, and the variable water surface velocity is found the most significant parameter across all models.

Security of energy supply in Japan: a key strategy and solutions

Energy is essential for goods and services. Japans economy is dependent on imported energy which is 85% per year, the highest percentage among industrialised nations. The study measures energy supply security (ESS). Four indices; dependency index, intensity index, local production index and composite index are constructed and statistical models are formed out to investigate the significance and the sensitivities between the ESS indexes and the input parameters that are; petroleum prices (PP), gross domestic products (GDP), total primary energy supply (TPES), energy consumption (PCEC), renewable energy (REN), CO2 emissions (CEM), population (P), traffic volume (TV), human development index (HDI) and mean of democracy indexes of energy suppliers (DI). A comprehensive methodology is used with five statistical procedures including simple correlation analysis, multiple linear regression models, stepwise multiple linear regression model, principal component analysis and cluster analysis. Empirical results indicate that PCEC, P and HDI have significant effect on ESS.

Nonlinear surface fit stability formula without any transition region for conventional breakwater design

ABSTRACT Determining the optimum weight of the armor blocks is of vital importance in the design of conventional breakwaters. The widely used formulae in the literature include the transition region from plunging to surging waves. In this paper, it is aimed to investigate a new design formula without any transition region as an alternative to widely used Van der Meer formulae. The dimensionless parameters of Van der Meer formulae as well as newly generated variables are used as inputs. Nonlinear surface fit best subset regression model is used to find the optimum input combination that keeps the nonlinear relationships. All the input parameters, their second powers, and their two-way interactions are included in the regression analyses to obtain a nonlinear surface fit. Various goodness of fit statistics are applied to check the different perspectives of the model accuracy. It is demonstrated that the proposed model gives a realistic prediction of the stability number for critical data range. Especially for high values of stability number the proposed formula outperforms the benchmark formulae of Van der Meer and Etemad-Shahidi and Bonakdar. The other advantage is that it does not contain any transition region that depends on wave conditions. Besides, there is no need to include “number of waves” and “permeability” parameters into the equation.

The energy security of Japan: Causality analyses

ABSTRACT Energy is one of the important elements in the production of goods and satisfies the required services. The economy of Japan is basically dependent on imported energy resources for 97% of its total domestic energy consumption per year, the highest percentage of any major industrialized nations. Thus, reducing dependency and import expenditures are always main issues in the energy policy of Japan. In this study, four indices are constructed to measure Energy Supply Security: Dependency Index, Intensity Index, Local Production Index, and Composite Index. This paper investigates the causal relationship between aggregated and disaggregated levels of energy supply security indices and the input parameters that are: petroleum prices, total primary energy supply, energy consumption per capita, share of renewable energy sources, carbon dioxide emissions, human development index, and the mean of democracy indices of energy supplier countries of Japan for the period of 1975–2007.