scholarly journals Critical Flow Centrality Measures on Interdependent Networks with Time-Varying Demands

2019 ◽  
Author(s):  
James Williams
Keyword(s):  
Flow Analysis ◽  
Network Capacity ◽  
Scale Model ◽  
Centrality Measures ◽  
Critical Flow ◽  
Degradation Analysis ◽  
Standard Component ◽  
Novel Method ◽  
Critical Components ◽  
Support Decision Making

This paper describes a novel method for allowing urban planners and municipal engineers to identify critical components of interdependent infrastructure networks whose attributes vary over time. The method is based on critical flow analysis, wherein system components are ranked by their role in facilitating the flow of resources to critical locations. The intent of the method is to support decision making by providing a means by which stakeholders can reason about the way in which changes in supply, demand, or network capacity can alter the distribution of critical flows within an urban environment. Individual infrastructure systems are modeled as networks that can be linked to one another by physical and geospatial dependencies. A simple instantiation of the method is presented and evaluated on a district-scale model of a city that contains water and electricity networks. The paper also discusses two forms of reliability analysis based on critical flows: a composite measure incorporating edge reliability, and a variation on standard component failure/degradation analysis.

scholarly journals Identifying Sensitive Components in Infrastructure Networks via Critical Flows

2019 ◽  
Author(s):  
James Williams
Keyword(s):  
Reliability Analysis ◽  
Critical Infrastructure ◽  
Urban Systems ◽  
Centrality Measures ◽  
Critical Flow ◽  
Infrastructure Networks ◽  
Component Importance ◽  
Infrastructure System ◽  
Critical Components ◽  
The Impact

This paper introduces a novel set of component importance measures that are based on the concept of critical flow. Various research communities have developed techniques for identifying critical components of networks. The methods in this paper extend previous work on flow-based centrality measures by adapting them to the assessment of critical infrastructure in urban systems. The motivation is to provide municipalities with a means of reasoning about the impact of urban interventions. An infrastructure system is represented as a flow network in which demand nodes are assigned both demand values and criticality ratings. Sensitive elements in the network are those that carry critical flows, where a flow is deemed critical to the extent that it satisfies critical demand. A method for computing these flows is presented, and its utility is demonstrated by comparing the new measures to existing flow centrality measures. The paper also shows how the method may be combined with standard approaches to reliability analysis.

scholarly journals Additively Manufactured Parts Made of a Polymer Material Used for the Experimental Verification of a Component of a High-Speed Machine with an Optimised Geometry—Preliminary Research

Polymers ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 137
Author(s):  
Artur Andrearczyk ◽  
Bartlomiej Konieczny ◽  
Jerzy Sokołowski
Keyword(s):  
Polymer Material ◽  
High Speed ◽  
Numerical Models ◽  
Flow Analysis ◽  
Experimental Tests ◽  
Strength Analysis ◽  
Compressor Wheel ◽  
Operational Characteristics ◽  
3D Printed ◽  
Novel Method

This paper describes a novel method for the experimental validation of numerically optimised turbomachinery components. In the field of additive manufacturing, numerical models still need to be improved, especially with the experimental data. The paper presents the operational characteristics of a compressor wheel, measured during experimental research. The validation process included conducting a computational flow analysis and experimental tests of two compressor wheels: The aluminium wheel and the 3D printed wheel (made of a polymer material). The chosen manufacturing technology and the results obtained made it possible to determine the speed range in which the operation of the tested machine is stable. In addition, dynamic destructive tests were performed on the polymer disc and their results were compared with the results of the strength analysis. The tests were carried out at high rotational speeds (up to 120,000 rpm). The results of the research described above have proven the utility of this technology in the research and development of high-speed turbomachines operating at speeds up to 90,000 rpm. The research results obtained show that the technology used is suitable for multi-variant optimization of the tested machine part. This work has also contributed to the further development of numerical models.

scholarly journals Comments on “Is the Faroe Bank Channel Overflow Hydraulically Controlled?”

2009 ◽  
Vol 39 (6) ◽  
pp. 1534-1538 ◽  
Author(s):  
Linda Enmar ◽  
Karin Borenäs ◽  
Iréne Lake ◽  
Peter Lundberg
Keyword(s):  
Froude Number ◽  
Water Transport ◽  
Cross Section ◽  
Deep Water ◽  
Flow Analysis ◽  
Critical Flow ◽  
Hydraulic Theory

Abstract In a recent paper Girton et al., due to what appears to be a misunderstanding, stated that a critical-flow analysis of the deep-water transport through the Faroe Bank Channel had been undertaken by Lake et al. on the basis of rotating hydraulic theory for a channel of parabolic cross section. In fact, this quoted investigation dealt with a rectangular passage. In the present comment it is demonstrated how the use of parabolic bathymetry leads to significant improvements of the Froude number results.

Perceived Causal Problem Networks: Reliability, Central Problems, and Clinical Utility for Depression

Assessment ◽  
2021 ◽  
pp. 107319112110392
Author(s):  
Lars Klintwall ◽  
Martin Bellander ◽  
Matti Cervin
Keyword(s):  
Clinical Utility ◽  
Treatment Success ◽  
Centrality Measures ◽  
Retest Reliability ◽  
Causal Relations ◽  
Future Studies ◽  
Causal Networks ◽  
Novel Method ◽  
The Individual ◽  
Test Retest Reliability

Personalized case conceptualization is often regarded as a prerequisite for treatment success in psychotherapy for patients with comorbidity. This article presents Perceived Causal Networks, a novel method in which patients rate perceived causal relations among behavioral and emotional problems. First, 231 respondents screening positive for depression completed an online Perceived Causal Networks questionnaire. Median completion time (including repeat items to assess immediate test–retest reliability) was 22.7 minutes, and centrality measures showed excellent immediate test–retest reliability. Networks were highly idiosyncratic, but worrying and ruminating were the most central items for a third of respondents. Second, 50 psychotherapists rated the clinical utility of Perceived Causal Networks visualizations. Ninety-six percent rated the networks as clinically useful, and the information in the individual visualizations was judged to contain 47% of the information typically collected during a psychotherapy assessment phase. Future studies should individualize networks further and evaluate the validity of perceived causal relations.

scholarly journals An Intelligent Complex Event Processing withDNumbers under Fuzzy Environment

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Fuyuan Xiao
Keyword(s):  
Complex Event Processing ◽  
Event Processing ◽  
The Novel ◽  
Human Beings ◽  
Topsis Method ◽  
Fuzzy Environment ◽  
Novel Method ◽  
Efficient Matching ◽  
Processing Engine ◽  
Support Decision Making

Efficient matching of incoming mass events to persistent queries is fundamental to complex event processing systems. Event matching based on pattern rule is an important feature of complex event processing engine. However, the intrinsic uncertainty in pattern rules which are predecided by experts increases the difficulties of effective complex event processing. It inevitably involves various types of the intrinsic uncertainty, such as imprecision, fuzziness, and incompleteness, due to the inability of human beings subjective judgment. Nevertheless,Dnumbers is a new mathematic tool to model uncertainty, since it ignores the condition that elements on the frame must be mutually exclusive. To address the above issues, an intelligent complex event processing method withDnumbers under fuzzy environment is proposed based on the Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS) method. The novel method can fully support decision making in complex event processing systems. Finally, a numerical example is provided to evaluate the efficiency of the proposed method.

Design and Testing of an Airbag System for High-Mass, High-Velocity Deceleration

1997 ◽  
Vol 119 (4) ◽  
pp. 631-637 ◽  
Author(s):  
T. Snyder ◽  
J. Sitter ◽  
J. N. Chung
Keyword(s):  
Impact Velocity ◽  
Flow Analysis ◽  
High Mass ◽  
Scale Model ◽  
Small Scale ◽  
Overall Performance ◽  
And Performance ◽  
Design And Testing ◽  
Small Scale Model ◽  
The Ideal

The design and performance evaluation of an airbag system capable of decelerating masses in the range of hundreds to thousands of kilograms with impact velocities in the range of tens to hundreds of kilometers per hour is presented. First, a simplified incompressible flow analysis of the airbag is utilized to derive the orifice venting area corresponding to the ideal deceleration for a given impact velocity and package mass. Second, testing with a small-scale model found three distinct control intervals during the deceleration. Finally, a full-scale airbag system was constructed and data is presented on the deceleration, deceleration force, deceleration velocity, airbag stopping power, and overall performance. The deceleration was experimentally optimized for a single impact velocity and package mass and an approximate correction factor was developed to predict the actual air venting required for each of the three control intervals in order to achieve the optimum deceleration for any impact velocity and package mass.

scholarly journals Identifying critical higher-order interactions in complex networks

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mehmet Emin Aktas ◽  
Thu Nguyen ◽  
Sidra Jawaid ◽  
Rakin Riza ◽  
Esra Akbas
Keyword(s):  
Complex Networks ◽  
Higher Order ◽  
Power Grids ◽  
Giant Component ◽  
Centrality Measures ◽  
First Order ◽  
Pairwise Interactions ◽  
Size Of Giant Component ◽  
Novel Method ◽  
Structure And Functions

AbstractDiffusion on networks is an important concept in network science observed in many situations such as information spreading and rumor controlling in social networks, disease contagion between individuals, and cascading failures in power grids. The critical interactions in networks play critical roles in diffusion and primarily affect network structure and functions. While interactions can occur between two nodes as pairwise interactions, i.e., edges, they can also occur between three or more nodes, which are described as higher-order interactions. This report presents a novel method to identify critical higher-order interactions in complex networks. We propose two new Laplacians to generalize standard graph centrality measures for higher-order interactions. We then compare the performances of the generalized centrality measures using the size of giant component and the Susceptible-Infected-Recovered (SIR) simulation model to show the effectiveness of using higher-order interactions. We further compare them with the first-order interactions (i.e., edges). Experimental results suggest that higher-order interactions play more critical roles than edges based on both the size of giant component and SIR, and the proposed methods are promising in identifying critical higher-order interactions.

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