Browsing by Author "Yurdusev M.A."

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    Development of water-resources planning models in england with special reference to environmental issues
    (American Society of Civil Engineers (ASCE), 1999) Yurdusev M.A.
    History of water-resources planning for England and Wales in England exhibits a good example in terms of both the methods used and their applications. Early modelling studies date back to the sixties. Since then several models have appeared, three of which in this paper have been reviewed. By emphasising how the environmental issues being treated, the applications of the models to the whole country are mentioned. © 1999 American Society of Civil Engineers.
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    Use of zeolite, coal bottom ash and fly ash as replacement materials in cement production
    (2004) Canpolat F.; Yilmaz K.; Köse M.M.; Sümer M.; Yurdusev M.A.
    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. © 2004 Published by Elsevier Ltd.
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    Application of artificial neural networks to the estimation of water quality parameters of River Gediz
    (2004) Demirdag O.; Yurdusev M.A.; Solmaz B.
    In this project, artificial neural networks (ANN) are used for the estimation of water quality parameters of River Gediz in the western part of Turkey. Gediz River basin contains the third largest city of Turkey. Moreover, it is the major agricultural area in the region as well as highly industrialised. There are so many pollution sources although clean water is highly demanded. Therefore, estimation of quality parameters from relatively easily measured river parameters is of great importance to maintain adequate water quality monitoring in the river. Selection of appropriate input parameters to estimate another one is key to use ANN. This is essential to obtain maximum success with minimum error. The input parameters selected must be those which affects most the output one. In this study, therefore, to estimate the amount of total dissolved solid (TDS), the river discharge, the water temperature and PH (acidity) are chosen as input parameters. A generic ANN software was run for different values of input parameters. This comprised training and test phases. For the most successful result of training for each month, the test phase was undertaken. The values passing the test phase successfully showed that ANN could successfully be used for estimation of water quality parameters that are relatively difficult to measure from those easily-measured. The outputs of such studies are essential for river water quality modelling studies. Copyright ASCE 2004.
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    Assessment of retention basin volume and outlet capacity in urban stormwater drainage systems with respect to water quality
    (Indian Academy of Sciences, 2005) Yurdusev M.A.; Kumanlioǧlu A.A.; Soemaz 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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    Environmentally-sensitive water-resources planning: II. A case study
    (2005) Yurdusev M.A.; O'Connell P.E.
    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 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. © Springer Science + Business Media, Inc. 2005.
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    Environmentally-sensitive water resources planning
    (2005) Yurdusev M.A.; O'Connell P.E.
    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. © Springer Science + Business Media, Inc. 2005.
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    Assessment of optimum tip speed ratio of wind turbines
    (Association for Scientific Research, 2005) Çetin N.S.; Yurdusev M.A.; Ata R.; Özdemir A.
    The first thing to do in wind turbine blade design is to select tip speed ratio. Generally speaking, the speed ratio depends on the profile type used and the number of blades. Various speed ratios could be chosen for different types of profiles with different number of blades. Therefore, an optimization procedure should be applied to find the best ratio since this directly affects the energy generated from the turbine and in turn the investment made. This study presents a procedure to assess the optimum speed ratios for various profile types used in practice with various numbers of blades.
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    Assessment of optimum tip speed ratio in wind turbines using artificial neural networks
    (Elsevier Ltd, 2006) Yurdusev M.A.; Ata R.; Çetin N.S.
    [No abstract available]
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    Assessment of optimum tip speed ratio in wind turbines using artificial neural networks
    (Elsevier Ltd, 2006) Yurdusev M.A.; Ata R.; Çetin N.S.
    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. © 2005 Elsevier Ltd. All rights reserved.
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    Sulfate resistance of mortars with and without silica fume and natural pozzolan
    (2007) Canpolat F.; Yurdusev M.A.; Targan S.; Yilmaz K.
    An investigation was carried out on the effect of sulfate attack on the sulfate durability of mortars produced with natural zeolite and silica fume having pozzolanic character. Experiments were accomplished on the standard Rilem sand and portland cement mortars where the cement was replaced by various rates of natural zeolite (Z) and silica fume (SF) separately and together. 5% sodium sulfate solution and 5% magnesium sulfate solution were 5% sulfate exposures of mortars were initiated after 28 days of lime saturated water curing, compressive strength and density were determined at the beginning of exposure and at the 2nd, 7th, 28th, 90th days. Water and solutions were renewed after each period of experimental time, 14 days. Mass changes were determined at the time of renewing the solutions. The effects of sodium sulfate solutions on the properties of mortars were related to the zeolite and silica fume ratio. It is found that zeolite and silica fume replacement had caused significant increase in sulfate durability of mortars even at the highest sulfate concentration up to 90 days of exposure. The durability to sulfate attack was obtained with silica fume replacement 5-10%, but strength loss of 10-15% can be expected. Mortars with SF and Z were damaged in magnesium sulfate solution. The compressive strengths decreased with increasing SF and Z content. The test results showed that the use of Z and SF in concrete exposed to magnesium sulfate environment is not recommended. © 2007 Taylor & Francis Group, London.
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    Extending experimental data to investigate phosphogypsume use in light brick by Artificial Neural Networks
    (2007) Yurdusev M.A.; Kumanlioǧlu A.A.; Abali Y.; Zeybek M.S.; 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. © 2007 Taylor & Francis Group, London.
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    Using phosphogypsume and boron concentrator wastes in light brick production
    (2007) Abali Y.; Yurdusev M.A.; Zeybek M.S.; Kumanlioǧlu A.A.
    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. © 2005 Elsevier Ltd. All rights reserved.
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    Survey-based estimation of domestic water saving potential in the case of Manisa City
    (2008) Yurdusev M.A.; Kumanlioǧlu A.A.
    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. © Springer Science+Business Media, Inc. 2007.
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    Monthly water demand forecasting by adaptive neuro-fuzzy inference system approach; [Uyarlamali si̇ni̇rsel bulanik mantik yaklaşimi i̇le aylik su tüketi̇mi̇ni̇n tahmi̇ni̇]
    (2008) Firat M.; Yurdusev M.A.; 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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    Adaptive neuro fuzzy inference system approach for municipal water consumption modeling: An application to Izmir, Turkey
    (2009) Yurdusev M.A.; 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. © 2008 Elsevier B.V. All rights reserved.
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    River flow estimation from upstream flow records by artificial intelligence methods
    (2009) Turan M.E.; Yurdusev M.A.
    Water resources management has become more and more crucial by the depletion of available water resources to use as opposed to the increase of the water consumption. An effective management relies on accurate and complete information about the river on which a project will be constructed. Artificial intelligence techniques are often and successfully used to complete the unmeasured data. In this study, feed forward back propagation neural networks, generalized regression neural network, fuzzy logic are used to estimate unmeasured data using the data of the four runoff gauge station on the Birs River in Switzerland. The performances of these models are measured by the mean square error, determination coefficients and efficiency coefficients to choose the best fit model. © 2009 Elsevier B.V. All rights reserved.
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    Water use prediction by radial and feed-forward neural nets
    (2009) Yurdusev M.A.; Firat M.; Mermer M.; Turan M.E.
    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. © 2009 Thomas Telford.
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    Neural extension of experimental data to investigate using phosphogypsume in light brick production
    (2009) Yurdusev M.A.; Kumanlioǧlu A.A.; Abali Y.; Zeybek M.S.
    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. © 2008 Elsevier Ltd. All rights reserved.
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    Comparative analysis of fuzzy inference systems for water consumption time series prediction
    (2009) Firat M.; Turan M.E.; Yurdusev M.A.
    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. © 2009 Elsevier B.V. All rights reserved.