flowing stream
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2021 ◽  
pp. 178-185
Author(s):  
Evgenia V. Zubkova ◽  
Alexandr N. Klementev ◽  
Vasilii A. Undalov

The purpose of this work is to compare the results of calculating the velocities of the flow around the ship's hull when it enters the lock chamber using various methods. The article presents the mathematical dependences obtained by various authors in the course of their research depending on the coefficient of constraint of the lock chamber by the ship's hull. An attempt to determine the influence of the height of the wave that arises in front of the stem in the process of entry which creates a slope of the water surface and the effect of this factor on the speed of the flowing stream is made. It was found that the values ​​of the flow velocities calculated by various methods have discrepancies. And the methods themselves do not allow determining the speed of the flow around when large-tonnage vessels enter the lock chamber of an extremely small width. The authors proposed a simple technique for calculating the flow velocity for cases of large values ​​of the constraint coefficient using an auxiliary graph.


2021 ◽  
Author(s):  
Izabela Bujak ◽  
Andrea Rinaldo ◽  
Ilja van Meerveld ◽  
Florian Käslin ◽  
Jana von Freyberg

<p>Many headwater catchments are characterized by temporary streams that flow only seasonally or during rainfall events. As a result, the network of flowing streams is a dynamic system that periodically expands and contracts. This dynamic is likely to affect water flow and composition: the expansion of the stream network enhances the hydrologic connectivity of hillslopes to the streams, which facilitates shorter transit times. Also, the onset of flow in previously dry streambeds can cause flushing of sediments and nutrients. However, our knowledge of the relationships between flowing stream network dynamics and water quantity and quality in headwater catchments is still limited because experimental data remain sparse.</p><p>Within the TempAqua project we investigate the processes that drive stream network dynamics by relating measurements of stream network geometry to changes in catchment water storage and stream water quality. For this, we monitored the flow state, discharge, groundwater levels, soil moisture, and precipitation in three (3-7 ha) headwater catchments in the northern Swiss pre-Alps (Alptal catchment) in summer and fall 2020 using a wireless sensor network. To obtain high-resolution data of the dynamic stream network, we did multiple mapping surveys using a self-developed mobile phone application. Moreover, we sampled streamwater and precipitation at an hourly resolution during rainfall events at multiple locations to quantify the short-term changes in water quality when the stream network expands. We will present our research activities in the Alptal catchment and discuss the initial results obtained from the combined monitoring of the flowing stream network and hydrometric and hydrochemical variables.</p>


2020 ◽  
Vol 68 ◽  
pp. 641-646
Author(s):  
Majid Emami-Meibodi ◽  
Mohammadreza Elahifard ◽  
Fatemeh Abyar

2020 ◽  
Vol 21 ◽  
pp. 100715
Author(s):  
Zahra Abdelmalek ◽  
Khalil Ur Rehman ◽  
Qasem M. Al-Mdallal ◽  
Wael Al-Kouz ◽  
M.Y. Malik

2020 ◽  
Vol 60 (4) ◽  
pp. 840-851
Author(s):  
Mary Kate O’Donnell ◽  
Stephen M Deban

Synopsis Animals clinging to natural surfaces have to generate attachment across a range of surface roughnesses in both dry and wet conditions. Plethodontid salamanders can be aquatic, semi-aquatic, terrestrial, arboreal, troglodytic, saxicolous, and fossorial and therefore may need to climb on and over rocks, tree trunks, plant leaves, and stems, as well as move through soil and water. Sixteen species of salamanders were tested to determine the effects of substrate roughness and wetness on maximum cling angle. Substrate roughness had a significant effect on maximum cling angle, an effect that varied among species. Substrates of intermediate roughness (asperity size 100–350 µm) resulted in the poorest attachment performance for all species. Small species performed best on smooth substrates, while large species showed significant improvement on the roughest substrates (asperity size 1000–4000 µm), possibly switching from mucus adhesion on a smooth substrate to an interlocking attachment on rough substrates. Water, in the form of a misted substrate coating and a flowing stream, decreased cling performance in salamanders on smooth substrates. However, small salamanders significantly increased maximum cling angle on wetted substrates of intermediate roughness, compared with the dry condition. Study of cling performance and its relationship to surface properties may cast light onto how this group of salamanders has radiated into the most speciose family of salamanders that occupies diverse habitats across an enormous geographical range.


Author(s):  
Sankalp Nilekar ◽  
Sudeep Rawat ◽  
Rahul Verma ◽  
Pravin Rahate

The community of users participating in social media tends to share common interests at the same time, giving rise to what are known as social trends. A social trend reflects the voice of a large number of users which, for some reason, becomes popular in a specific moment. Through social trends, users, therefore, suggest that some occurrence of wide interest is taking place and subsequently triggering the trend. In this work, we explore the types of triggers that spark trends on the microblogging site Twitter and introduce a typology that includes the following four types: news, ongoing events, memes, and commemoratives. The user will be allowed to search for the latest trends by inputting a keyword into the search field. Based on user- provided keyword, the system will search for similar keywords in database and summarize the total count to provide the trending tweets on twitter. The trending tweets with the hashtag (#) will be displayed first and then the rest words will be displayed. By clicking on every trending tweet, the user commented tweets will be displayed. User can view all the tweets from the searched keyword. One of the main features on the homepage of Twitter shows a list of top terms so called trending topics at all times. These terms reflect the topics that are being discussed most at the very moment on the site’s fast-flowing stream of tweets. In order to avoid topics that are popular regularly (e.g., good morning or goodnight on certain times of the day), Twitter focuses on topics that are being discussed much more than usual, i.e., topics that recently suffered an increase of use, so that it trended for some reason


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