Browsing by Author "Yurdusev, MA"

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    Using phosphogypsume and boron concentrator wastes in light brick production
    Abali, Y; Yurdusev, MA; Zeybek, MS; Kumanlioglu, AA
    In this study, use of wastes produced in phosphoric acid plants and boron concentrators in producing structural brick has been investigated. There are several parameters involved in using these wastes in brick production namely the rate of added waste, firing speed and firing temperature. The performance of these parameters can be measured by several criteria such as natural drying shortening, water absorption and weight loss. Therefore, so many experiments are needed to investigate the effects of these parameters on the bricks produced with these wastes. To this end, around 220 experiments for three different material combinations namely original waste plus normal brick clay, washed waste plus normal brick clay and normal brick clay with no additive were carried out. The results have shown that the industrial wastes produced by phosphoric acid plants can improve the performance of the bricks in terms of drying shortening, weight loss and water absorption. (c) 2005 Elsevier Ltd. All rights reserved.
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    Adaptive neuro fuzzy inference system approach for municipal water consumption modeling: An application to Izmir, Turkey
    Yurdusev, MA; Firat, M
    In this study. an adaptive neuro fuzzy inference system (ANFIS) is used to forecast monthly water use from several socio-economic and climatic factors including average monthly water bill, population, number of households. gross national product, monthly average temperature observed, monthly total rainfall, monthly average humidity observed and inflation rate. Water consumption modeling in this way will be more consistent than doing it using a single variable as more effective parameter could be incorporated. The ANFIS system is applied to modeling monthly water consumptions of Izmir, Turkey. The results indicated that ANFIS can be successfully applied for monthly water consumption modeling. (c) 2008 Elsevier B.V. All rights reserved.
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    Assessment of retention basin volume and outlet capacity in urban stormwater drainage systems with respect to water quality
    Yurdusev, MA; Kumanlioglu, AA; Solmaz, B
    The quality of river water or other surface waters is detrimentally affected by the contaminants carried by the rainfall runoff in urban areas. The control of pollution moved by rainfall runoff is achieved by installing outlets and small retention basins in stormwater collection systems, thereby allowing only a certain amount of rainfall water to overflow and leading the remaining to treatment plants. This study analyses the effect of concentration time on surface water pollution caused by rainfall runoff. For this purpose, a linear S-curve is assumed for the flow hydrograph arising from the collection system, based on parameters of rainfall considered and the catchment area. An independent code is developed to analyse such a system and this is applied to an urban area using. nine-year single-discrete rainfall records of Izmir Station, Turkey. The system is capable of tackling situations where there is only a basin or a basin with outlet.
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    The Assessment of Irrigation Efficiency in Buyuk Menderes Basin
    Yilmaz, B; Yurdusev, MA; Harmancioglu, NB
    While extending irrigated areas to augment agricultural production, irrigation efficiency should be increased not only to improve the agricultural production but also to obtain the sustainable use of valuable and limited water resources. Through the use of Data Envelopment Analysis (DEA), which is a linear programming technique to determine the relative efficiency of a decision-making unit, it is possible to decide whether the use of water in an irrigation district is efficient or not. In this study, an input oriented DEA model is constituted to focus on the efficient use of inputs, and the method is applied to the irrigation districts having similar types of agriculture in the Buyuk Menderes Basin, Turkey. This paper aims to determine the efficient irrigation district(s), in other words where the application of water is the most profitable, considering two inputs; water volume supplied and the total irrigated area, and one output, the total value of agricultural production. The weight restrictions consistent with decision makers' value judgements are added as constraints into the DEA models to prevent excessive weight flexibility assigned to inputs and outputs. The results have provided the efficiency scores of the irrigation districts and numerically delineated desired features of the irrigation districts for maximum efficiency. The analyses for three study years have inferred the robustness of the results. It is concluded that DEA is a practical tool for detecting local inefficiencies and proposing possible improvements for irrigation districts that could offer the greatest potential for growth.
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    Comparative analysis of fuzzy inference systems for water consumption time series prediction
    Firat, M; Turan, ME; Yurdusev, MA
    Two types of fuzzy inference systems (FIS) are used for predicting municipal water consumption time series. The FISs used include an adaptive neuro-fuzzy inference system (ANFIS) and a Mamdani fuzzy inference systems (MFIS). The prediction models are constructed based on the combination of the antecedent values of water consumptions. The performance of ANFIS and MFIS models in training and testing phases are compared with the observations and the best fit model is identified according to the selected performance criteria. The results demonstrated that the ANFIS model is superior to MFIS models and can be successfully applied for prediction of water consumption time series. (C) 2009 Elsevier B.V. All rights reserved.
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    Survey-based estimation of domestic water saving potential in the case of manisa city
    Yurdusev, MA; Kumanlioglu, AA
    In this paper, domestic water saving potential in the case of Manisa, Turkey has been investigated. Firstly, domestic water use forms are analyzed in an attempt to estimate how much water is used by a particular use in total domestic use. Then, the water conservation measures for each water practice are examined and some easy-to-apply measures proposed. Finally, an experimental study was conducted to determine if the domestic water conservation measures proposed were applicable for the city considered. For this purpose, a questionnaire was developed and 200 respondents were asked to fill it in. The respondents were chosen from different people based on education level, financial status and size of the family to represent the society living in the city. Based on the results of the study, it is shown that the measures proposed are quite applicable and around 27% saving is manageable if the proposed measures are publicized adequately and applied effectively.
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    Assessment of optimum tip speed ratio in wind turbines using artificial neural networks
    Yurdusev, MA; Ata, R; Çetin, NS
    Wind turbine blade design depends on several factors, such as turbine profile used, blade number, power factor, and tip speed ratio. The key to designing a wind turbine is to assess the optimal tip speed ratio (TSR). This will directly affect the power generated and, in turn, the effectiveness of the investment made. TSR is suggested to be taken between 7 and 8 and in practice generally taken as 7 for a 3-blade network-connected wind turbine. However, the optimal TSR is dependent upon the profile type used and the blade number and could fall out of the boundaries suggested. Therefore, it has to be assessed accordingly. In this study, the optimal TSR and the power factor of a wind turbine are predicted using artificial neural networks (ANN) based on the parameters involved for NACA 4415 and LS-1 profile types with 3 and 4 blades. The ANN structure built is found to be more successful than the conventional approach in estimating the TSR and power factor. (c) 2005 Elsevier Ltd. All rights reserved.
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    Evaluation of Artificial Neural Network Techniques for Municipal Water Consumption Modeling
    Firat, M; Yurdusev, MA; Turan, ME
    Various Artificial Neural Network techniques such as Generalized Regression Neural Networks (GRNN), Feed Forward Neural Networks (FFNN) and Radial Basis Neural Networks (RBNN) have been evaluated based on their performance in forecasting monthly water consumptions from several socio-economic and climatic factors, which affect water use. The data set including total 108 data records is divided into two subsets, training and testing. The models consisting of the combination of the independent variables are constructed and the best fit input structure is investigated. The performance of ANN models in training and testing stages are compared with the observed water consumption values to identify the best fit forecasting model. For this purpose, some performance criteria such as Normalized Root Mean Square Error (NRMSE), efficiency (E) and correlation coefficient (CORR) are calculated for all models. The best fit models are also trained and tested by Multiple Linear Regression (MLR). The results indicated that GRNN outperforms all other methods in modeling monthly water consumptions.
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    MONTHLY WATER DEMAND FORECASTING BY ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM APPROACH
    Firat, M; Yurdusev, MA; Mermer, M
    In this study, an adaptive Neuro-Fuzzy inference system (ANFIS) is used to forecast monthly water use from several socio-economic and climatic factors, which affect water use. Totally 108 data sets are collected and data sets are divided into two subsets, training and testing. The models consisting of the combination of the independent variables are constructed and the best fit input structure is investigated. The performance of ANFIS models in training and testing sets are compared with the observations and the best fit model forecasting model is identified. For this purpose, some criteria of performance evaluation such as, Root Mean Square Error (RMSE), efficiency (E) and correlation coefficient (CORR) are calculated for all models. Then, the best fit models are also trained and tested by Multiple Regression (MR). The results of models are compared to get more reliable comparison. The results indicated that ANFIS can be applied successfully for monthly water demand forecasting
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    Comparative analysis of neural network techniques for predicting water consumption time series
    Firat, M; Turan, ME; Yurdusev, MA
    Monthly water consumption time series have been predicted using a series of Artificial Neural Network (ANN) techniques including Generalized Regression Neural Networks (GRNN), Cascade Correlation Neural Network (CCNN) and Feed Forward Neural Networks (FFNN). One hundred and eight data sets for the city of Izmir, Turkey are used for a number of ANN modeling exercises. Several ANN models depending on the combination of antecedent values of water consumption records are constructed and the best fit input structure is investigated. The performance of ANN models in training and testing stages are compared with the observed water consumption values to identify the best fit forecasting model based upon a number of selected performance criteria. (C) 2010 Elsevier B.V. All rights reserved.
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    Environmentally-sensitive water-resources planning: II. A case study
    Yurdusev, MA; O'Connell, PE
    The ENRES environmentally-sensitive water resources planning model is demonstrated in a case study covering the whole of England and Wales, thereby repeating the national planning exercise completed in 1994. Prior to running the model, all the components involved are environmentally assessed using Environment Agency personnel from different regions, by filling in a questionnaire for each scheme. Several model runs were undertaken in an attempt to find the best solution for the region. It was concluded that some M pound 28.0 (in 1991 prices) of additional investment would be required if the plan based on environmental concerns were to be adopted. This premium can be regarded as the quantification of environmental impacts of the schemes proposed. The results of this exercise indicated that the model is capable of selecting more environmentally-friendly options based on surrogate environmental costs as well as incorporating environmental concerns in water resources planning even on a national scale.
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    Environmentally-sensitive water resources planning
    Yurdusev, MA; O'connell, PE
    In this paper, the traditional problem of matching supplies to competing demands, referred to as water resources planning (WRP), is re-visited. With the pressure of continuing growth in the world's population, efficient development and management of available water resources are of greater importance than ever before. It is equally important in today's world that the environmental implications of any activity should be minimised. The aim of this research is to develop a methodology for including environmental considerations in the WRP process. This is achieved by weighting the costs of the various water resource options (both constructional and operating) to reflect their environmental impacts, prior to their inclusion in an economic planning model. The effect of such a weighting procedure is to encourage the selection of environmentally-friendly schemes at the expense of environmentally-damaging ones. The objective function of the combined methodology is to minimise the total environmentally-adjusted costs, discounted to a base year. A comprehensive planning tool named ENRES has been developed to carry out this task. The model allows the environmental impact assessment of all development options, either source components or transfer structures, to be undertaken prior to running the allocation procedure which is carried out by means of an optimisation technique. With the help of all the facilities provided, the model can be used in a planning exercise both with and without environmental considerations. In this way, it is possible to quantify the cost of environmental impacts in the planning process.
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    Use of zeolite, coal bottom ash and fly ash as replacement materials in cement production
    Canpolat, F; Yilmaz, K; Köse, MM; Sümer, M; Yurdusev, MA
    In this research, the effects of zeolite, coal bottom ash and fly ash as Portland cement replacement materials on the properties of cement are investigated through three different combinations of tests. These materials are substituted for Portland cement in different proportions, and physical properties such as setting time, volume expansion, compressive strength and water consistency of the mortar are determined. Then, these physical properties are compared with those of PC 42.5. The results showed that replacement materials have some effects on the mechanical properties of the cement. The inclusion of zeolite up to the level of 15% resulted in an increase in compressive strength at early ages, but resulted in a decrease in compressive strength when used in combination with fly ash. Also, setting time was decreased when zeolite was substituted. The results obtained were compared with Turkish Standards (TS), and it was found that they are above the minimum requirements. (C) 2004 Published by Elsevier Ltd.
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    Extending experimental data to investigate phosphogypsume use in light brick by Artificial Neural Networks
    Yurdusev, MA; Kumanlioglu, AA; Abali, Y; Zeybek, MS; Canpolat, F
    In this study, usability of wastes produced in phosphoric acid plants in structural brick manufacture has been investigated. A series of experiments for three different material combinations namely original waste plus normal brick clay, washed waste plus normal brick clay and normal brick clay with no additive were carried out to achieve this end. The results have shown that the industrial wastes considered improve the performance of the bricks. However, the results have also shown that further investigations are needed to explore the effects of interim or outer values on the performance of the bricks. To active that end, a neural experimental study is adopted. The outcome of these artificial tests have provided the appropriate values for the waste addition rate, firing speed and firing temperature.
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    Neural extension of experimental data to investigate using phosphogypsume in light brick production
    Yurdusev, MA; Kumanhoglu, AA; Abali, Y; Zeybek, MS
    In this study, usability of wastes produced in phosphoric acid plants in structural brick manufacture has been investigated. There are several parameters involved in using these wastes in brick production namely the rate of added waste, firing speed and firing temperature. The performance of these parameters can be measured by several criteria such as natural drying shortening, water absorption and weight loss. Therefore, so many experiments are needed to investigate the effects of these parameters on the bricks produced with these wastes. The result of a series of experiments were utilized to achieve this end. The results have shown that the industrial wastes considered improve the performance of the bricks in terms of the criteria mentioned above. However, the results have also shown that further investigations are needed to explore the effects of interim values on the performance of the bricks. To achieve that end, a neural experimental study is adopted. For this purpose, the results of the experiments conducted were used to construct an artificial neural network. The trained and tested network was then used to check the effects of 280 different combinations for each type of material mixtures mentioned. The outcome of these artificial tests have provided the optimal values for the waste addition rate, firing speed and firing temperature based on the four criteria mentioned previously. (c) 2008 Elsevier Ltd. All rights reserved.
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    Investigation of scaffolding accident in a construction site: A case study analysis
    Dogan, E; Yurdusev, MA; Yildizel, SA; Calis, G
    The construction sector is one of the few high-risk businesses due to occupational accidents, their rate of frequencies, and related serious consequences, sometimes even resulting in the death of individuals. Therefore, it is a vital necessity and priority for employers and employees during the course of a project to comply with occupational safety rules under any circumstances. Nothing should deter or compromise the safety of any individual working in a potential risk environment. Within the scope of this study, the analysis addresses a scaffolding accident that occurred on a construction site. Once the information about how the accident possibly happened was received, the scaffolding in question identified at the construction was kept for an investigation to carry out the corrective and renovation works. In this paper the suspended scaffoldings are firstly categorized. Then how the accident happened was examined and theorized. The examination and analysis were supported by the results. This study is intended to prevent similar accidents and establish necessary precautions as a matter of procedure.
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    Water use prediction by radial and feed-forward neural nets
    Yurdusev, MA; Firat, M; Mermer, M; Turan, ME
    In this study, applicability of feed-forward and radial-basis neural networks for monthly water consumption prediction from several socio-economic and climatic factors affecting water use is investigated. A data set including a total of 108 data records is divided into two subsets: training and testing. Firstly, the models based on a single input variable are trained and tested by feed-forward and radial methods and feed-forward and radial performances of the models are compared. Then, the models based on multiple input variables are constructed according to performances of the models based on a single input variable. The performances of feed-forward and radial models in training and testing phases are compared with the observations and the best-fit model is identified. For this purpose, several criteria such as normalised root mean square error, efficiency and correlation coefficient are calculated for all models. Subsequently, the best-fit models are also trained and tested by multiple linear regression for comparison. The results indicated that feed-forward and radial methods can be applied successfully for monthly water consumption prediction.
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    Design of siphonic rainwater drainage system
    Dogaroglu, B; Yurdusev, MA
    Today, conventional systems are commonly used for roof rainwater drainage. In recent years, the use of siphonic drainage systems has become widespread, based on the principle that the pipes are full flow. With the full flow principle in the siphonic system, pipe diameters are reduced compared to traditional (conventional) systems. Thanks to a number advantageous features, especially in industrial and office buildings, this system has started to be used more in widely. In this study, a design example of a siphonic rainwater drainage system was evaluated. The same system has traditionally been calculated and the results compared in terms of cost.
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    Genetic algorithm for networks with dynamic mutation rate
    Cetin, T; Yurdusev, MA
    A genetic algorithm based on hydraulic optimization is applied in the paper in order to achieve the lowest possible costs, the most appropriate pipe diameter, and the most favourable longitudinal slope values. A new algorithm for mutation operation, called the dynamic mutation rate method, is proposed as a means to reduce the number of trials for genetic algorithm parameters, especially for mutation rates, and to obtain an optimum value in the shortest possible time.
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    Predicting Monthly River Flows by Genetic Fuzzy Systems
    Turan, ME; Yurdusev, MA
    Reliable flow forecasts are key to developing river regulation schemes such as reservoirs. River flow prediction has conventionally been undertaken by physical and black-box models. Several black-box type models have been employed to achieve this end. Of these, genetic fuzzy systems have been used in this study as they have relatively attracted limited attention to date. Genetic-fuzzy systems are the fuzzy systems that have the capability of learning and tuning by Genetic Algorithms. Employing two different fuzzy inference systems, a case study on Gediz river basin has been performed in an attempt to find a suitable genetic fuzzy system for flow prediction.