Flume

The phenomenon of Big Data refers to the exponential growth in the volume of data available in digital form as well as in business on the internet. This is a set of technologies and algorithms to sort in real time a considerable amount of data on the Web, and to identify more subtle user behavior. Each individual involved in this phenomenon by dispersing data on their actions accumulated by social networks, applications, mobile or connected objects. The increment in information accumulation over the social network has increment from a modest KB to PB. This data collection has no positive mass for memory request for storage. The current graphs from various sites show great variations for data collection. So we can't stick to one particular technique to resolve the data storage issue. We need to compress on various level. In this paper, I am clarifying different progressing pattern for Big-data handling over the Social networks.

In coastal and estuarine environments, sand-mud mixtures are often formed due to supply of various types of sediment discharge from rivers. For better prediction of the sediment transport patterns and the resultant bathymetry changes in these areas, it is important to apply a sediment transport model that can represent the behavior of sand-mud mixtures depending on the mud content to the simulation. This study aims at elucidating the effect of the mud content on the erosion processes of sand-mud mixtures under the combined wave and current forces through a field observation and flume experiments. A sand-mud mixture transport model was validated based on the field and experimental results.

The proper understanding of gravel-bed river dynamics is a crucial issue for the effective protection against related natural hazards, design of hydraulic structures, and preservation of their high ecological value in mountain regions. However, despite more than one century of research in the field, most available models fail to accurately predict bedload transport rates in such alluvial rivers because of the complex relationships between the flow, channel morphology, and sediment transport. It is now recognized that spatio-temporal variability is an inherent property of bedload transport in gravel-bed rivers which results in its pulsating character even under steady flow conditions. This experimental study aims to better understand the physical mechanisms involved in sediment transport in gravel-bed channels characterized by alternate bars. More specifically, it is concerned with the origins of the pulsating nature of bedload transport under steady external conditions in relation t...