Radial Pressure Wave Behavior in Transient Laminar Pipe Flows Under Different Flow Perturbations

The study of transient pressure waves in both low- and high-frequency domains has become a new research area to provide potentially high-resolution pipe fault detection methods. In previous research works, radial pressure waves were evidently observed after stopping the laminar pipe flows by valve closures, but the generation mechanism and components of these radial pressure waves are unclear. This paper intends to clarify this phenomenon. To this end, this study first addresses the inefficiencies of the current numerical scheme for the full two-dimensional (full-2D) water hammer model. The modified efficient full-2D model is then implemented into a practical reservoir-pipeline-valve (RPV) system, which is validated by the well-established analytical solutions. The generation mechanism and components of the radial pressure waves, caused by different flow perturbations from valve operations, in transient laminar flows are investigated systematically using this efficient full-2D model. The results indicate that nonuniform changes in the initial velocity profile form pressure gradients along the pipe radius. The existence of these radial pressure gradients is the driving force of the formation of radial flux and radial pressure waves. In addition, high radial modes can be excited, and the frequency of flow perturbations by valve oscillation can redistribute the energy entrapped in each high radial mode.

Download Full-text

Modelling community structure and temporal spreading on complex networks

Computational Social Networks ◽

10.1186/s40649-021-00094-z ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Vesa Kuikka

Keyword(s):

Community Structure ◽

Complex Networks ◽

Community Detection ◽

Network Structure ◽

Network Connectivity ◽

Network Models ◽

Building Blocks ◽

Detection Algorithm ◽

Research Area ◽

Detection Methods

AbstractWe present methods for analysing hierarchical and overlapping community structure and spreading phenomena on complex networks. Different models can be developed for describing static connectivity or dynamical processes on a network topology. In this study, classical network connectivity and influence spreading models are used as examples for network models. Analysis of results is based on a probability matrix describing interactions between all pairs of nodes in the network. One popular research area has been detecting communities and their structure in complex networks. The community detection method of this study is based on optimising a quality function calculated from the probability matrix. The same method is proposed for detecting underlying groups of nodes that are building blocks of different sub-communities in the network structure. We present different quantitative measures for comparing and ranking solutions of the community detection algorithm. These measures describe properties of sub-communities: strength of a community, probability of formation and robustness of composition. The main contribution of this study is proposing a common methodology for analysing network structure and dynamics on complex networks. We illustrate the community detection methods with two small network topologies. In the case of network spreading models, time development of spreading in the network can be studied. Two different temporal spreading distributions demonstrate the methods with three real-world social networks of different sizes. The Poisson distribution describes a random response time and the e-mail forwarding distribution describes a process of receiving and forwarding messages.

Download Full-text

Radial pressure forces in Euler-Euler simulations of turbulent bubbly pipe flows

Nuclear Engineering and Design ◽

10.1016/j.nucengdes.2021.111079 ◽

2021 ◽

Vol 374 ◽

pp. 111079

Author(s):

Roland Rzehak ◽

Yixiang Liao ◽

Richard Meller ◽

Fabian Schlegel ◽

Ronald Lehnigk ◽

...

Keyword(s):

Radial Pressure ◽

Pipe Flows

Download Full-text

Recognition of Position Group Relationship in Dynamic Social Networks

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.l2510.1081219 ◽

2019 ◽

Vol 8 (12) ◽

pp. 118-121

Keyword(s):

News Media ◽

Online Social Network ◽

Research Area ◽

Detection Methods ◽

Support Vector ◽

Vector Method ◽

Detection Algorithms ◽

Network Intrusion ◽

Dynamic Social Networks ◽

Network Anomaly Detection

Mental stress is turning into a threat to people's health currently days. With the last step of life, a lot of and a lot of folks are feeling stressed. A novel hybrid model combined with Convolution Neural Network (CNN) to control tweet content and social interaction information for stress detection effectively. Network anomaly detection is an important and dynamic research area. Many network intrusion detection methods and systems (NIDS) have been proposed in the literature. Fake news detection on social media presents unique characteristics and challenges that make existing detection algorithms from traditional news media ineffective or not applicable. Based on the information that is provided by the online social network, the conditions are limited. This method can opinion investigation of Facebook post after Formation of point utilizing Support Vector Method (SVM). After grouping client is in pressure or not k-closest neighbor calculation (KNN) is utilized for proposal emergency clinic on a guide just as Admin can send letters of precautionary measure list for the client for end up solid and upbeat throughout everyday life

Download Full-text

The success of using trained dogs to locate sparse rodents in pest-free sanctuaries

Wildlife Research ◽

10.1071/wr09117 ◽

2010 ◽

Vol 37 (1) ◽

pp. 39 ◽

Cited By ~ 24

Author(s):

Anna Gsell ◽

John Innes ◽

Pim de Monchy ◽

Dianne Brunton

Keyword(s):

Large Scale ◽

Research Area ◽

Detection Methods ◽

Wild Rodents ◽

Conservation Areas ◽

Laboratory Rats ◽

Scent Trails ◽

The Cost ◽

Rats And Mice ◽

Norway Rats

Context. Better techniques to detect small numbers of mammalian pests such as rodents are required both to complete large-scale eradications in restoration areas and to detect invaders before they become abundant or cause serious impacts on biodiversity. Aims. To evaluate the ability of certified rodent dogs (Canis familiaris) to locate Norway rats (Rattus norvegicus) and mice (Mus musculus) or their scent trails at very low densities in field conditions. Methods. We experimentally tested two rodent dogs by releasing small numbers of laboratory rats and mice in a 63 ha rodent-free forest sanctuary and then determining if the dogs and their handlers could find the rodents and their scent trails. We divided the enclosure into two halves, east and west of the midpoint, and alternated releases daily between the two areas to minimise residual scent between consecutive trials. Radio-tagged rats or mice were released a total of 96 times at random locations that were unknown to handlers, followed for 50–100 m, then caught and either placed in hidden cages at the end of the scent trail or removed from the forest. Handlers and their dogs had up to 6 h to search for rodents. Key Results. Despite the extremely low density of rodents in the effective research area of 32 ha, both dogs were highly successful at finding rodents, together locating 87% of rats and 80% of mice. Handlers reported few false positive detections. We found that well-trained dogs can effectively cover 30–40 ha of steep forested habitat in half a day (6 h). Conclusions. Despite the limitations of our study design, we conclude that well-trained rodent dogs may be able to locate wild rodents at low densities in forest situations. Implications. Our results support the ongoing use of certified dogs to detect rodent survivors and invaders in conservation areas in New Zealand and elsewhere. Additional research is required to trial dogs on experimentally released wild rodents and to compare the cost-effectiveness of dogs with other detection methods.

Download Full-text

A Universal Fast Algorithm for Sensitivity-Based Structural Damage Detection

The Scientific World JOURNAL ◽

10.1155/2013/235820 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Q. W. Yang ◽

J. K. Liu ◽

C.H. Li ◽

C.F. Liang

Keyword(s):

Damage Detection ◽

Fast Algorithm ◽

Structural Damage ◽

Research Area ◽

Detection Methods ◽

Structural Damage Detection ◽

Response Data ◽

Flexibility Matrix ◽

New Research ◽

Measured Response

Structural damage detection using measured response data has emerged as a new research area in civil, mechanical, and aerospace engineering communities in recent years. In this paper, a universal fast algorithm is presented for sensitivity-based structural damage detection, which can quickly improve the calculation accuracy of the existing sensitivity-based technique without any high-order sensitivity analysis or multi-iterations. The key formula of the universal fast algorithm is derived from the stiffness and flexibility matrix spectral decomposition theory. With the introduction of the key formula, the proposed method is able to quickly achieve more accurate results than that obtained by the original sensitivity-based methods, regardless of whether the damage is small or large. Three examples are used to demonstrate the feasibility and superiority of the proposed method. It has been shown that the universal fast algorithm is simple to implement and quickly gains higher accuracy over the existing sensitivity-based damage detection methods.

Download Full-text

Influence of radial pressure gradients on solute exchange in stirred benthic chambers

Marine Ecology Progress Series ◽

10.3354/meps141303 ◽

1996 ◽

Vol 141 ◽

pp. 303-311 ◽

Cited By ~ 42

Author(s):

RN Glud ◽

S Forster ◽

M Huettel

Keyword(s):

Radial Pressure ◽

Pressure Gradients ◽

Solute Exchange ◽

Benthic Chambers

Download Full-text

Air pressure propagation through Wind Cave and Jewel Cave: How do pressure waves travel through barometric caves?

International Journal of Speleology ◽

10.5038/1827-806x.50.3.2393 ◽

2021 ◽

Vol 50 (3) ◽

pp. 263-273

Author(s):

Annika Gomell ◽

Daniel Austin ◽

Marc Ohms ◽

Andreas Pflitsch

Keyword(s):

Response Times ◽

External Pressure ◽

Black Hills ◽

Air Pressure ◽

Pressure Waves ◽

Pressure Gradients ◽

Pressure Data ◽

Almost All ◽

Pressure Changes ◽

Pressure Propagation

In barometric caves, air pressure gradients between the outside atmosphere and the cave induce strong bidirectional compensating currents, which control almost all elements of speleoclimatology, including air temperature, humidity, and CO2 dynamics. Therefore, this study set out to investigate air pressure propagation through Wind Cave and Jewel Cave – two major barometric cave systems in the Black Hills of South Dakota, USA. Based on high-resolution air pressure data from both the surface and several measurement sites inside the caves, four systematic changes of pressure waves during their journey through the caves and their related speleoclimatological processes were identified and discussed: Compared to the outside atmosphere, the pressure signals within Wind Cave and Jewel Cave showed (1) an absolute displacement due to different altitudes of the measuring sites, (2) a delay related to the travel times of the pressure wave to the measuring sites, (3) a smoothing effect, and (4) a damping effect due to long response times of the caves to external pressure changes. The spatial distribution of the changes observed in this study shows that for Wind Cave, the cave opening and the narrow entrance area represent the main obstacle for pressure propagation, while for Jewel Cave, the deep areas have the greatest influence on the development of air pressure gradients. Our analyses provide completely new insights into the processes and mechanisms inside barometric caves, which will significantly contribute to the understanding of pressure-related airflow dynamics and all related elements of speleoclimatology.

Download Full-text