Design and Optimization of Irrigation Distribution Networks PDF Download
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Author: Y. Labye
Publisher: Food & Agriculture Org.
ISBN: 9789251026663
Category : Technology & Engineering
Languages : en
Pages : 266
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Book Description
Author: Y. Labye
Publisher: Food & Agriculture Org.
ISBN: 9789251026663
Category : Technology & Engineering
Languages : en
Pages : 266
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Book Description
Author: W. H. van der Molen
Publisher: Food & Agriculture Org.
ISBN: 9789251056707
Category : Technology & Engineering
Languages : en
Pages : 252
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Book Description
The aim of this paper is to facilitate the planning and design of land drainage systems for sound land and water management for engineers and other professionals. It considers the integration of technical, socio-economic and environmental factors and the need for system users' participation in the planning, design, operation and maintenance processes. The text provides guidelines for the appropriate identification of drainage problems, for the planning and design of field drainage systems (surface and subsurface) and the main drainage and disposal systems. The annexes provide more detailed information with technical background, appropriate equations, some cross-references for finding appropriate methodologies, and computer programs for calculation of extreme values, of permeability and some land drainage system parameters. --Publisher's description.
Author: Pramod R. Bhave
Publisher: Alpha Science Int'l Ltd.
ISBN: 9781842651322
Category : Science
Languages : en
Pages : 472
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Book Description
Design of water distribution networks is traditionally based on trial-and-approach in which the designer assumes, based on experience and judgment, sizes of different elements and successively modifies them until a network with satisfactory hydraulic performance is obtained. This text covers: Essential hydraulic, economic optimization principles. Theory is developed gradually for optimal design of simple, single-source branched networks subjected to single loading to complex, multiple-source looped networks subjected to multiple loading. Strengthening and expansion of existing networks and also reliability-based design. Several illustrative examples enabling the reader to apply them in practice- approximately 100 line drawings.
Author: Bolaji Fatai Sule
Publisher:
ISBN: 9789975341127
Category :
Languages : en
Pages : 68
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Book Description
A Water distribution system connects consumers to sources of water, using hydraulic components, such as pipes, valves, and reservoirs. The engineer faced with the design of such a system, or of additions to an existing system, has to select the sizes of its components. Also he has to consider the way in which the operational components, pumps and valves, will be used to supply the required demands with adequate pressures. The network has to perform adequately under varying demand loads, hydraulic and operational conditions. Operational decisions for these loads are essentially part of the design process, since one cannot separate the so-called design decisions, i.e. the sizing of components, from the operational decisions; they are two inseparable parts of one problem. This work has therefore presented a method for optimizing the design of a water distribution network system using pipe diameter as decision variable under the required demand loading and hydraulic conditions. It has been established that increasing the minimum pressure will lead to the reduction in the required pipe diameter which will in turn reduce the cost of installation. The modelling approach developed can be used by engineers and planners to obtain economical pipe sizes for a network designed to serve newly planned layouts.
Author: Richard Peter Jones
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Mohamed Abdel Moneim
Publisher:
ISBN:
Category : Computers
Languages : en
Pages :
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Book Description
Modelling Reliability Based Optimization Design for Water Distribution Networks.
Author: Hatem Khaled El-Sayegh
Publisher:
ISBN:
Category : Water
Languages : en
Pages : 204
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Book Description
Author: Grant S. Cooper
Publisher:
ISBN:
Category : Water-supply engineering
Languages : en
Pages : 292
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Book Description
Author:
Publisher:
ISBN:
Category : Drainage
Languages : en
Pages : 470
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Book Description
Author: Manuel Alejandro Andrade-Rodriguez
Publisher:
ISBN:
Category :
Languages : en
Pages : 208
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Book Description
The burdensome capital cost of urban water distribution systems demands the use of efficient optimization methods capable of finding a relatively inexpensive design that guarantees a minimum functionality under all conditions of operation. The combinatorial and nonlinear nature of the optimization problem involved accepts no definitive method of solution. Adaptive search methods are well fitted for this type of problem (to which more formal methods cannot be applied), but their computational requirements demand the development and implementation of additional heuristics to find a satisfactory solution. This work seeks to employ adaptive search methods to enhance the search process used to find the optimal design of any water distribution system. A first study presented here introduces post-optimization heuristics that analyze the best design obtained by a genetic algorithm--arguably the most popular adaptive search method--and perform an ordered local search to maximize further cost savings. When used to analyze the best design found by a genetic algorithm, the proposed post-optimization heuristics method successfully achieved additional cost savings that the genetic algorithm failed to detect after an exhaustive search. The second study herein explores various ways to improve artificial neural networks employed as fast estimators of computationally intensive constraints. The study presents a new methodology for generating any large set of water supply networks to be used for the training of artificial neural networks. This dataset incorporates several distribution networks in the vicinity of the search space in which the genetic algorithm is expected to focus its search. The incorporation of these networks improved the accuracy of artificial neural networks trained with such a dataset. These neural networks consistently showed a lower margin of error than their counterparts trained with conventional training datasets populated by randomly generated distribution networks.
