983 resultados para water escape structures
Resumo:
Design of liquid retaining structures involves many decisions to be made by the designer based on rules of thumb, heuristics, judgment, code of practice and previous experience. Various design parameters to be chosen include configuration, material, loading, etc. A novice engineer may face many difficulties in the design process. Recent developments in artificial intelligence and emerging field of knowledge-based system (KBS) have made widespread applications in different fields. However, no attempt has been made to apply this intelligent system to the design of liquid retaining structures. The objective of this study is, thus, to develop a KBS that has the ability to assist engineers in the preliminary design of liquid retaining structures. Moreover, it can provide expert advice to the user in selection of design criteria, design parameters and optimum configuration based on minimum cost. The development of a prototype KBS for the design of liquid retaining structures (LIQUID), using blackboard architecture with hybrid knowledge representation techniques including production rule system and object-oriented approach, is presented in this paper. An expert system shell, Visual Rule Studio, is employed to facilitate the development of this prototype system. (C) 2002 Elsevier Science Ltd. All rights reserved.
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An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.
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Sample contains well dispersed clasts ranging from small to medium in size. They are sub-angular to sub-rounded in shape. Organic rich domains can be seen throughout the sample with clear boundaries. It also contains water escape structures, seen mainly through clay. Lineations are also present.
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Brown sediment with well dispersed clasts. Clasts range from small to medium in size and angular to sub-rounded in shape. Some appear to have been weathered. Water escape structures can be seen, mainly in finer, clay rich sediment. Lineations can also be seen throughout the sample. Minor grain stacking and crushing are also present.
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Fine grained, dark brown sediment. Minor amounts of lineations can be seen. Faint water escape structures are also abundant.
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Dark brown sediment with clasts ranging from small to large. Grains are sub-angular in shape. Faint water escape structures are present.
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Dark brown sediment with scattered amounts of small clasts and medium clasts as well. Clast shape ranges from sub-angular to sub-rounded. Lineations and water escape structures are abundant in this sample.
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Dark brown sample with clasts that range from small to large. The clast shape ranges from angular to sub-rounded. Grain crushing is present in this sample along with some lineations. Faint water escape structures can also be seen.
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Brown sediment with clasts that range from small to large. The clast shape ranges from angular to sub-rounded. Lineations and water escape structures are present. Grain crushing and minor amounts of rotation are also present.
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Brown sediment with clasts ranging from small to medium in size. The clast shape ranges from angular to sub-rounded. Lineations are abundant in this sample. Faint water escape structures can also be seen as well as grain crushing/stacking.
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Brown sediment with a coarse grained domain and a fine grained domain. The coarse grained domain contains clasts that are small to medium in size. The clast shape ranges from sub-angular to sub-rounded. The coarse grained domain is abundant in lineations. The fine grained domain contains many faint water escape structures. A few rotation structures can also be seen throughout the sample.
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Light brown sample with clasts ranging from small to large. The clast shape ranges from sub-angular to sub-rounded. Grain crushing is common in this sample and mainly involves the larger clasts. Many grains are also crushed into one another. The larger grains are also fractured. Lineations and faint water escape structures can also be seen. This sample also contains a finer grained domain, darker in colour.
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Dark brown sediment, with clasts ranging from small to large. The sample mainly contained smaller clasts. The clast shape ranges from sub-angular to sub-rounded. Lineations were common throughout the sample. It also contained areas with dark organic material, and a few faint water escape structures.
Resumo:
Brown sediment with grains ranging from small to medium in size. The sample mainly contains smaller clasts. Clast shape ranges from sub-angular to sub-rounded. Water escape structures and lineations can be seen in this sample. Grains stacking and comet structures are also present in minor amounts.
Resumo:
Dark brown, fine grained sediment. Mainly structure less with organic content. A few faint water escape structures can also be seen.