Fuelled by a desire for greater connectivity, networked systems now pervade our society at an unprecedented level that will affect it in ways we do not yet understand. In contrast, nature has already developed efficient networks that can instigate rapid response and consensus when key elements are stimulated. We present a technique for identifying these key elements by investigating the relationships between a system’s most dominant eigenvectors. This approach reveals the most effective vertices for leading a network to rapid consensus when stimulated, as well as the communities that form under their dynamical influence. In applying this technique, the effectiveness of starling flocks was found to be due, in part, to the low outdegree of every bird, where increasing the number of outgoing connections can produce a less responsive flock. A larger outdegree also affects the location of the birds with the most influence, where these influentially connected birds become more centrally located and in a poorer position to observe a predator and, hence, instigate an evasion manoeuvre. Finally, the technique was found to be effective in large voxel-wise brain connectomes where subjects can be identified from their influential communities.
Flood resilience has been rising up the political, economic and social agendas. Taking an integrated systems approach, using the right design guidance and tools and ensuring that education is in place for all stakeholders are three themes which are intrinsically linked to delivering flood resilience. This paper reviews these themes across the academic research, policy landscape and practitioner approaches, drawing conclusions on the way forward to increase our societies resilience to floods. The term 'flood resilience' is being increasingly used, however, it remains to be clearly defined and implemented. The UK, USA and Australia are leading the way in considering what flood resilience really means, but our review has found few examples of action underpinned by an understanding of systems and complexity. This review investigates how performance objectives & indicators are currently interpreted in guidance documents. It provides an in-depth exploration of the methods, that although developed through European and US expertise, can be used for worldwide application. Our analysis highlights that resilience is often embedded in engineering education and frequently linked to risk. This may however, mask the importance of resilience and where it differs from risk. With £2.6 billion to be spent in the UK over the next 6 years on strengthening the country's flood and coastal defences, this is the opportunity to rethink resilience from a systems approach, and embed that learning into education and professional development of engineers. Our conclusions indicate how consolidating flood resilience knowledge between and within critical infrastructure sectors is the way forward to deliver flood resilience engineering.
Consensus and decision-making are often analysed in the context of networks, with many studies focusing attention on ranking the nodes of a network depending on their relative importance to information routing. Dynamical influence ranks the nodes with respect to their ability to influence the evolution of the associated network dynamical system. In this study it is shown that dynamical influence not only ranks the nodes, but also provides a naturally optimised distribution of effort to steer a network from one state to another. An example is provided where the “steering” refers to the physical change in velocity of self-propelled agents interacting through a network. Distinct from other works on this subject, this study looks at directed and hence more general graphs. The findings are presented with a theoretical angle, without targeting particular applications or networked systems; however, the framework and results offer parallels with biological flocks and swarms and opportunities for design of technological networks.
This position article addresses resilience in complex engineering and engineered systems (CES). It offers a synthesis of academic thinking with an empirical analysis of the challenge. This article puts forward argumentations and a conceptual framework in support of a new understanding of CES resilience as the product of continuous learning in between disruptive events. CES are in continuous evolution and with each generation they become more complex as they adapt to their environment. While this evolution takes place, new failure modes arise with the engineering of their resilience having to evolve in parallel to cope with them. Our position supports the role of an overarching complexity science framework to investigate the resilience of CES, including their temporal evolution, resilience features, the management and decision layers, and the transparency of boundaries between interconnected systems. The conclusion identifies the value of a complexity perspective to address CES resilience. Extending the latest understanding of resilience, we propose a circular framework where features of CES are related to a resilience event and complexity science explains the importance of interconnections with external systems, the increasingly fast system evolution and the stratification of heterogeneous layers.
This version is available at https://strathprints.strath.ac.uk/65072/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the Strathprints administrator: strathprints@strath.ac.ukThe Strathprints institutional repository (https://strathprints.strath.ac.uk) is a digital archive of University of Strathclyde research outputs. It has been developed to disseminate open access research outputs, expose data about those outputs, and enable the management and persistent access to Strathclyde's intellectual output. Consensus Speed Optimisation with Finite Leadership Perturbation in k-Nearest Neighbour Networks Ruaridh Clark, Giuliano Punzo and Malcolm MacdonaldAbstract-Near-optimal convergence speeds are found for perturbed networked systems, with N interacting agents that conform to k-nearest neighbour (k-NNR) connection rules, by allocating a finite leadership resource amongst selected nodes. These nodes continue averaging their state with that of their neighbours while being provided with the resources to drive the network to a new state. Such systems are represented by a directed graph Laplacian with two newly presented semianalytical approaches used to maximise the consensus speed. The two methods developed typically produce near-optimal results and are highly efficient when compared with conventional numerical optimisation, where the asymptotic computational complexity is O(n 3 ) and O(n 4 ) respectively. The upper limit for the convergence speed of a perturbed k-NNR network is identified as the largest element of the first left eigenvector (FLE) of a graph's adjacency matrix. The first semi-analytical method exploits this knowledge by distributing leadership resources amongst the most prominent nodes highlighted by this FLE. The second method relies on the FLEs of manipulated versions of the adjacency matrix to expose different communities of influential nodes. These are shown to correspond with the communities found by the Leicht-Newman detection algorithm, with this method enabling optimal leadership selection even in low outdegree (< 12 connections) graphs, where the first semianalytical method is less effective.
The mechanical operation of a biologically inspired robot hopper is presented. This design is based on the hind leg dynamics and jumping gait of a desert locust (schistocerca gregaria). The biological mechanism is represented as a lumped mass system. This emulates the muscle activation sequence and gait responsible for the long, coordinated jump of locusts, whilst providing an engineering equivalent for the design of a biological inspired hopper for planetary exploration.Despite the crude simplification, performance compares well against biological data found in the literature and scaling towards size more typical of robotic realisation are considered from an engineering point of view. This 1 aspect makes an important contribution to knowledge as it quantifies the balance between biological similarity and efficiency of the biomimetic hopping mechanism. Further, this work provides useful information towards the biomimetic design of a hopper vehicle whilst the analysis uncover the range maximisation conditions for powered flight at constant thrust by analytic means. The proposed design bridges concepts looking at the gait dynamics and designs oriented to extended, full powered trajectories.
This version is available at https://strathprints.strath.ac.uk/44352/ Strathprints is designed to allow users to access the research output of the University of Strathclyde. Unless otherwise explicitly stated on the manuscript, Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Please check the manuscript for details of any other licences that may have been applied. You may not engage in further distribution of the material for any profitmaking activities or any commercial gain. You may freely distribute both the url (https://strathprints.strath.ac.uk/) and the content of this paper for research or private study, educational, or not-for-profit purposes without prior permission or charge.Any correspondence concerning this service should be sent to the AbstractIn this work a formation flying based architecture is presented within the context of a distributed antenna array.An artificial potential function method is used to control the formation whereby deviation from an all-to-all interaction scheme and swarm shaping are enabled through a self-similar connection network. Introduction of an asymmetric term in the potential function formulation results in the emergence of structures with a central symmetry. The connection network then groups these identical structures through a hierarchical scheme. This produces a fractal shape which is considered for the first time as a distributed antenna array exploiting the recursive arrangement of its elements to augment performance. A 5-element Purina fractal is used as the base formation which is then replicated a number of times increasing the antenna-array aperture and resulting in a highly directional beam from a relatively low number of elements. Justifications are provided in support of the claimed benefits for distributed antenna arrays exploiting fractal geometries. The formation deployment is simulated in Earth orbit together with analytical proofs completing the arguments aimed to demonstrate feasibility of the concept and the advantages provided by grouping antenna elements into coherent structures.
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