Relevant bibliographies by topics / Network Dynamics Simulation

Academic literature on the topic 'Network Dynamics Simulation'

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Published: 14 March 2023

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Journal articles on the topic "Network Dynamics Simulation"

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Levin, Ilya, Mark Korenblit, and Vadim Talis. "STUDY OF SOCIAL NETWORKS’ DYNAMICS BY SIMULATION WITHIN THE NODEXL-EXCEL ENVIRONMENT." Problems of Education in the 21st Century 54, no. 1 (June 20, 2013): 125–37. http://dx.doi.org/10.33225/pec/13.54.125.

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The present study is an analysis of the learning activity, which constitutes simulation of networks and studying their functioning and dynamics. The study is based on using network-like learning environments. Such environments allow building computer models of the network graphs. According to the suggested approach, the students construct dynamic computer models of the networks' graphs, thus implementing various algorithms of such networks’ dynamics. The suggested tool for building the models is the software environment comprising network analysis software NodeXL and a standard spreadsheet Excel. The proposed approach enables the students to visualize the network's dynamics. The paper presents specific examples of network models and various algorithms of the network's dynamics, which were developed based on the proposed approach. Key words: learning environments, modelling, social networks.
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MENDES, R. VILELA. "TOOLS FOR NETWORK DYNAMICS." International Journal of Bifurcation and Chaos 15, no. 04 (April 2005): 1185–213. http://dx.doi.org/10.1142/s0218127405012715.

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Networks have been studied mainly by statistical methods which emphasize their topological structure. Here, one collects some mathematical tools and results which might be useful to study both the dynamics of agents living on the network and the networks themselves as evolving dynamical systems. They include decomposition of differential dynamics, ergodic techniques, estimates of invariant measures, construction of non deterministic automata, logical approaches, etc. A few network examples are discussed as an application of the dynamical tools.
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Zhu, Zhiqiang. "Control Analysis of Propagation Dynamics on Networks." Journal of Physics: Conference Series 2224, no. 1 (April 1, 2022): 012092. http://dx.doi.org/10.1088/1742-6596/2224/1/012092.

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Abstract It is generally the dynamic behavior of multiple information in the network. Based on the principle of propagation dynamics and mathematical model, this paper simulates the dynamic process of information in the network, and analyzes the influence of network structure and propagation dynamics on the dynamic behavior of information in the network through the simulation results. By simulating the dynamic process of communication, we find that the location and release time of intervention information in the network will have an impact, and we can control the dynamic behavior of information in the network by controlling the location and release time of intervention information.
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Kiss, Istvan Z., Luc Berthouze, Timothy J. Taylor, and Péter L. Simon. "Modelling approaches for simple dynamic networks and applications to disease transmission models." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 468, no. 2141 (January 18, 2012): 1332–55. http://dx.doi.org/10.1098/rspa.2011.0349.

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In this paper a random link activation–deletion (RLAD) model is proposed that gives rise to a stochastically evolving network. This dynamic network is then coupled to a simple susceptible-infectious-suceptible ( SIS ) dynamics on the network, and the resulting spectrum of model behaviour is explored via simulation and a novel pairwise model for dynamic networks. First, the dynamic network model is systematically analysed by considering link-type independent and dependent network dynamics coupled with globally constrained link creation. This is done rigorously with some analytical results and we highlight where such analysis can be performed and how these simpler models provide a benchmark to test and validate full simulations. The pairwise model is used to study the interplay between SIS -type dynamics on the network and link-type-dependent activation–deletion. Assumptions of the pairwise model are identified and their implications interpreted in a way that complements our current understanding. Furthermore, we also discuss how the strong assumptions of the closure relations can lead to disagreement between the simulation and pairwise model. Unlike on a static network, the resulting spectrum of behaviour is more complex with the prevalence of infections exhibiting not only a single steady state, but also bistability and oscillations.
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Esser, J., and M. Schreckenberg. "Microscopic Simulation of Urban Traffic Based on Cellular Automata." International Journal of Modern Physics C 08, no. 05 (October 1997): 1025–36. http://dx.doi.org/10.1142/s0129183197000904.

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Saturated capacities in traffic systems evoke increasing interest in simulations of complex networks serving as laboratory environment for developing management strategies. Especially for urban areas questions concerning overall traffic control have to be considered with regard to their impacts on the whole network. Modeling traffic flow dynamics using cellular automata allows us to run large network traffic simulations with only comparatively low computational efforts. We present a traffic simulation tool for urban road networks which is based on the Nagel–Schreckenberg Model. Arbitrary kinds of roads and crossings are modeled as combinations of only a few basic elements. Furthermore parking capacities are considered as well as circulations of public transports. The vehicles are driven corresponding to route plans or at random depending on the available data. The application of this network simulation covers investigations on the field of traffic planning as well as online simulations based on real-time traffic data as basis for dynamic traffic management systems.
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SCHMIDT, G., G. ZAMORA-LÓPEZ, and J. KURTHS. "SIMULATION OF LARGE SCALE CORTICAL NETWORKS BY INDIVIDUAL NEURON DYNAMICS." International Journal of Bifurcation and Chaos 20, no. 03 (March 2010): 859–67. http://dx.doi.org/10.1142/s0218127410026149.

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Understanding the functional dynamics of the mammalian brain is one of the central aims of modern neuroscience. Mathematical modeling and computational simulations of neural networks can help in this quest. In recent publications, a multilevel model has been presented to simulate the resting-state dynamics of the cortico-cortical connectivity of the mammalian brain. In the present work we investigate how much of the dynamical behavior of the multilevel model can be reproduced by a strongly simplified model. We find that replacing each cortical area by a single Rulkov map recreates the patterns of dynamical correlation of the multilevel model, while the outcome of other models and setups mainly depends on the local network properties, e.g. the input degree of each vertex. In general, we find that a simple simulation whose dynamics depends on the global topology of the whole network is far from trivial. A systematic analysis of different dynamical models and coupling setups is required.
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Kadupitiya, JCS, Geoffrey C. Fox, and Vikram Jadhao. "Machine learning for parameter auto-tuning in molecular dynamics simulations: Efficient dynamics of ions near polarizable nanoparticles." International Journal of High Performance Computing Applications 34, no. 3 (January 14, 2020): 357–74. http://dx.doi.org/10.1177/1094342019899457.

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Simulating the dynamics of ions near polarizable nanoparticles (NPs) using coarse-grained models is extremely challenging due to the need to solve the Poisson equation at every simulation timestep. Recently, a molecular dynamics (MD) method based on a dynamical optimization framework bypassed this obstacle by representing the polarization charge density as virtual dynamic variables and evolving them in parallel with the physical dynamics of ions. We highlight the computational gains accessible with the integration of machine learning (ML) methods for parameter prediction in MD simulations by demonstrating how they were realized in MD simulations of ions near polarizable NPs. An artificial neural network–based regression model was integrated with MD simulation and predicted the optimal simulation timestep and optimization parameters characterizing the virtual system with 94.3% success. The ML-enabled auto-tuning of parameters generated accurate dynamics of ions for ≈ 10 million steps while improving the stability of the simulation by over an order of magnitude. The integration of ML-enhanced framework with hybrid Open Multi-Processing / Message Passing Interface (OpenMP/MPI) parallelization techniques reduced the computational time of simulating systems with thousands of ions and induced charges from thousands of hours to tens of hours, yielding a maximum speedup of ≈ 3 from ML-only acceleration and a maximum speedup of ≈ 600 from the combination of ML and parallel computing methods. Extraction of ionic structure in concentrated electrolytes near oil–water emulsions demonstrates the success of the method. The approach can be generalized to select optimal parameters in other MD applications and energy minimization problems.
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Galizia, Roberto, and Petri T. Piiroinen. "Regions of Reduced Dynamics in Dynamic Networks." International Journal of Bifurcation and Chaos 31, no. 06 (May 2021): 2150080. http://dx.doi.org/10.1142/s0218127421500802.

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We consider complex networks where the dynamics of each interacting agent is given by a nonlinear vector field and the connections between the agents are defined according to the topology of undirected simple graphs. The aim of the work is to explore whether the asymptotic dynamic behavior of the entire network can be fully determined from the knowledge of the dynamic properties of the underlying constituent agents. While the complexity that arises by connecting many nonlinear systems hinders us to analytically determine general solutions, we show that there are conditions under which the dynamical properties of the constituent agents are equivalent to the dynamical properties of the entire network. This feature, which depends on the nature and structure of both the agents and connections, leads us to define the concept of regions of reduced dynamics, which are subsets of the parameter space where the asymptotic solutions of a network behave equivalently to the limit sets of the constituent agents. On one hand, we discuss the existence of regions of reduced dynamics, which can be proven in the case of diffusive networks of identical agents with all-to-all topologies and conjectured for other topologies. On the other hand, using three examples, we show how to locate regions of reduced dynamics in parameter space. In simple cases, this can be done analytically through bifurcation analysis and in other cases we exploit numerical continuation methods.
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Sugiki, Nao, Shogo Nagao, Fumitaka Kurauchi, Mustafa Mutahari, and Kojiro Matsuo. "Social Dynamics Simulation Using a Multi-Layer Network." Sustainability 13, no. 24 (December 13, 2021): 13744. http://dx.doi.org/10.3390/su132413744.

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The analysis and evaluation of urban structure are important while considering sustainable urban policies. It is necessary to develop a method that can easily analyze the social dynamics that are the result of changes over time in urban transportation and land use. Therefore, by describing the relationships between various agents in urban areas as a network, it is possible to analyze them by focusing on their structures. However, since there are few existing studies on social dynamics using network-based methods, it is necessary to examine the validity and effectiveness of these methods. The purpose of this study is to examine the possibility of urban analysis and evaluation focusing on the network shape by describing the urban activities and modeling the dynamics with a multilayer network. In particular, we focus on household composition and individual facility access, examine what kind of interpretation is possible for network indicators, and mention the applicability of complex networks to urban analysis. The model was applied to a two-dimensional grid virtual city, and the household composition and individual facility accessibility were quantified using the centrality index.
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Ng, Desmond. "The social dynamics of diverse and closed networks." Human Systems Management 23, no. 2 (June 3, 2004): 111–22. http://dx.doi.org/10.3233/hsm-2004-23206.

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Inherent to the dynamics of social networks is a paradoxical trade-off between closed networks that promote cooperation and efficiency and diverse networks that are flexible to new resources and ideas. Since actors cannot simultaneously maximize both facets of a network, this has created a sharp debate on the social capital performance of closed and diverse network relationships. Research on this social capital debate has often focused on these described network affects without explaining the origins and dynamics of network performance. This paper advances a cognitive diversity approach that is based upon the subjective and alert behaviors of Austrian entrepreneurs. These are key causal drivers to this paper's theoretical model of social dynamics and performance of closed and diverse networks. Such network behavior is subsequently modeled as a Complex Adaptive system. Using agent-based simulation, an agent-based model of entrepreneurship and social network dynamics is constructed to test the relationships described by the proposed theoretical model. The simulation results support the described hypothesized relationships. These findings also suggest the benefits of closed and diverse networks are logically distinct and, thus, should not be viewed as an either-or phenomenon. Agent-based simulation results show entrepreneurs can construct a balanced network of closed and diverse networks to optimize the benefits of both networks.
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Dissertations / Theses on the topic "Network Dynamics Simulation"

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Georgieva, Kristina Boyanova. "Boolean network simulation for exploring the dynamics of industrial networks." Thesis, Lancaster University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.289295.

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Dickson, Scott M. "Stochastic neural network dynamics : synchronisation and control." Thesis, Loughborough University, 2014. https://dspace.lboro.ac.uk/2134/16508.

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Biological brains exhibit many interesting and complex behaviours. Understanding of the mechanisms behind brain behaviours is critical for continuing advancement in fields of research such as artificial intelligence and medicine. In particular, synchronisation of neuronal firing is associated with both improvements to and degeneration of the brain's performance; increased synchronisation can lead to enhanced information-processing or neurological disorders such as epilepsy and Parkinson's disease. As a result, it is desirable to research under which conditions synchronisation arises in neural networks and the possibility of controlling its prevalence. Stochastic ensembles of FitzHugh-Nagumo elements are used to model neural networks for numerical simulations and bifurcation analysis. The FitzHugh-Nagumo model is employed because of its realistic representation of the flow of sodium and potassium ions in addition to its advantageous property of allowing phase plane dynamics to be observed. Network characteristics such as connectivity, configuration and size are explored to determine their influences on global synchronisation generation in their respective systems. Oscillations in the mean-field are used to detect the presence of synchronisation over a range of coupling strength values. To ensure simulation efficiency, coupling strengths between neurons that are identical and fixed with time are investigated initially. Such networks where the interaction strengths are fixed are referred to as homogeneously coupled. The capacity of controlling and altering behaviours produced by homogeneously coupled networks is assessed through the application of weak and strong delayed feedback independently with various time delays. To imitate learning, the coupling strengths later deviate from one another and evolve with time in networks that are referred to as heterogeneously coupled. The intensity of coupling strength fluctuations and the rate at which coupling strengths converge to a desired mean value are studied to determine their impact upon synchronisation performance. The stochastic delay differential equations governing the numerically simulated networks are then converted into a finite set of deterministic cumulant equations by virtue of the Gaussian approximation method. Cumulant equations for maximal and sub-maximal connectivity are used to generate two-parameter bifurcation diagrams on the noise intensity and coupling strength plane, which provides qualitative agreement with numerical simulations. Analysis of artificial brain networks, in respect to biological brain networks, are discussed in light of recent research in sleep theory.
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Corradini, Daniele. "Computational study of resting state network dynamics." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14524/.

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Lo scopo di questa tesi è quello di mostrare, attraverso una simulazione con il software The Virtual Brain, le più importanti proprietà della dinamica cerebrale durante il resting state, ovvero quando non si è coinvolti in nessun compito preciso e non si è sottoposti a nessuno stimolo particolare. Si comincia con lo spiegare cos’è il resting state attraverso una breve revisione storica della sua scoperta, quindi si passano in rassegna alcuni metodi sperimentali utilizzati nell’analisi dell’attività cerebrale, per poi evidenziare la differenza tra connettività strutturale e funzionale. In seguito, si riassumono brevemente i concetti dei sistemi dinamici, teoria indispensabile per capire un sistema complesso come il cervello. Nel capitolo successivo, attraverso un approccio ‘bottom-up’, si illustrano sotto il profilo biologico le principali strutture del sistema nervoso, dal neurone alla corteccia cerebrale. Tutto ciò viene spiegato anche dal punto di vista dei sistemi dinamici, illustrando il pionieristico modello di Hodgkin-Huxley e poi il concetto di dinamica di popolazione. Dopo questa prima parte preliminare si entra nel dettaglio della simulazione. Prima di tutto si danno maggiori informazioni sul software The Virtual Brain, si definisce il modello di network del resting state utilizzato nella simulazione e si descrive il ‘connettoma’ adoperato. Successivamente vengono mostrati i risultati dell’analisi svolta sui dati ricavati, dai quali si mostra come la criticità e il rumore svolgano un ruolo chiave nell'emergenza di questa attività di fondo del cervello. Questi risultati vengono poi confrontati con le più importanti e recenti ricerche in questo ambito, le quali confermano i risultati del nostro lavoro. Infine, si riportano brevemente le conseguenze che porterebbe in campo medico e clinico una piena comprensione del fenomeno del resting state e la possibilità di virtualizzare l’attività cerebrale.
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Quijada, Sergio. "A HYBRID SIMULATION METHODOLOGY TO EVALUATE NETWORK CENTRICDECISION MAKING UNDER EXTREME EVENTS." Doctoral diss., University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2348.

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Currently the network centric operation and network centric warfare have generated a new area of research focused on determining how hierarchical organizations composed by human beings and machines make decisions over collaborative environments. One of the most stressful scenarios for these kinds of organizations is the so-called extreme events. This dissertation provides a hybrid simulation methodology based on classical simulation paradigms combined with social network analysis for evaluating and improving the organizational structures and procedures, mainly the incident command systems and plans for facing those extreme events. According to this, we provide a methodology for generating hypotheses and afterwards testing organizational procedures either in real training systems or simulation models with validated data. As long as the organization changes their dyadic relationships dynamically over time, we propose to capture the longitudinal digraph in time and analyze it by means of its adjacency matrix. Thus, by using an object oriented approach, three domains are proposed for better understanding the performance and the surrounding environment of an emergency management organization. System dynamics is used for modeling the critical infrastructure linked to the warning alerts of a given organization at federal, state and local levels. Discrete simulations based on the defined concept of "community of state" enables us to control the complete model. Discrete event simulation allows us to create entities that represent the data and resource flows within the organization. We propose that cognitive models might well be suited in our methodology. For instance, we show how the team performance decays in time, according to the Yerkes-Dodson curve, affecting the measures of performance of the whole organizational system. Accordingly we suggest that the hybrid model could be applied to other types of organizations, such as military peacekeeping operations and joint task forces. Along with providing insight about organizations, the methodology supports the analysis of the "after action review" (AAR), based on collection of data obtained from the command and control systems or the so-called training scenarios. Furthermore, a rich set of mathematical measures arises from the hybrid models such as triad census, dyad census, eigenvalues, utilization, feedback loops, etc., which provides a strong foundation for studying an emergency management organization. Future research will be necessary for analyzing real data and validating the proposed methodology.
Ph.D.
Other
Engineering and Computer Science
Modeling and Simulation
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Rhomberg, Patrick. "On the parallelization of network diffusion models." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5831.

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In this thesis, we investigate methods by which discrete event network diffusion simulators may execute without the restriction of lockstep or near lockstep synchronicity. We develop a discrete event simulator that allows free clock drift between threads, develop a differential equations model to approximate communication cost of such a simulator, and propose an algorithm by which we leverage information gathered in the natural course of simulation to redistribute agents to parallel threads such that the burden of communication is lowered during future replicates.
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Tiefert, Brian E. "Modeling control channel dynamics of the SAAM Architecture using the NS network simulation tool." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1999. http://handle.dtic.mil/100.2/ADA371825.

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Dewan, Leslie. "Molecular dynamics simulation and topological analysis of the network structure of actinide-bearing materials." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/86266.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Nuclear Science and Engineering, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references.
Actinide waste production and storage is a complex problem, and a whole-cycle approach to actinide management is necessary to minimize the total volume of waste. In this dissertation, I examine three actinide-bearing materials relevant to both the front end and back end of the nuclear fuel cycle: light water reactor (LWR) spent fuel stored in a crystalline ceramic medium (zircon), LWR spent fuel stored in a glassy medium (alkali borosilicate glass), and three molten salt systems (LiF-BeF2, LiF-ThF4 , and LiF-UF4). I model these materials using molecular dynamics (MD) simulations, and then perform a range of material-dependent analyses - including structural evaluation, species segregation, solubility limits, and assessment of transport properties - to examine their suitability as actinide-bearing materials. The initial portion of this work focuses on actinide waste storage media, examining the microstructural changes induced in zircon and alkali borosilicate glass doped with uranium. Alpha-decay of the uranium changes the structure of the host material, inducing amorphousness, recrystallization, and microcracking, among other structural changes. My work on actinide waste storage shows the utility of topological methods for quantifying the intermediate-range structure of amorphous systems. In many cases, the intermediate-range structure correlates with larger-scale properties, such as density and viscosity. I then identify three molten salt systems of interest - LiF-BeF2 , LiF-ThF4, and LiUF4 - as a focus for analysis. LiF-BeF2 is a coolant salt, and LiF-ThF4 and LiF-UF4 are fuel salts used on the front end of the nuclear fuel cycle in molten salt reactors (MSRs). MSRs can, in some configurations, achieve extremely high actinide bum-ups. Some molten salt reactors can also be fueled by the actinides in spent fuel produced by LWRs. While MSRs have many advantages, research into new designs often proceeds slowly because of gaps in available experimental data for the molten fuel and coolant salts. I use MD simulations to evaluate the transport properties and structure of these salts, and show that these simulations can be used reliably to augment the existing body of experimental data describing the salts' material properties. Furthermore, I examine how the structure of the salt correlates with its material properties, in particular its viscosity. I use network topology-based algorithms to describe the amorphous structure quantitatively. Network-based topological methods have never before been applied to molten salts, and many new insights can be gained from the analysis.
by Leslie Dewan.
Ph. D.
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Sorichetti, Valerio. "Nanoparticle dynamics in polymer solutions and gels : a simulation approach." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTS113.

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Les nanocomposites de polymères, systèmes de polymères contenant des nanoparticules (NP), sont des systèmes fascinants qui ont de nombreuses applications en science des matériaux, en biologie et en médecine, mais qui posent également des défis en physique théorique. L'un des problèmes fondamentaux de la physique des nanocomposites est de comprendre comment la structure et la dynamique du système dépendent de paramètres clés, tels que la taille et la fraction volumique des NP et la taille typique du maillage polymère. Dans cette thèse, nous utilisons des simulations de dynamique moléculaire pour étudier les propriétés structurelles et dynamiques des NP incorporées dans des nanocomposites de polymères liquides et solides. Nous observons que lorsque des NP faiblement attractives et bien dispersées sont ajoutées à une solution de polymères dense, les polymères et les NP subissent un ralentissement dynamique. Nous trouvons que, en accord qualitatif avec les expériences, ce ralentissement dynamique est capturé par un paramètre de confinement sous la forme h/λ, où h est la distance moyenne entre les surfaces des NP voisines (interparticle distance). Nous pouvons montrer que pour les NP lambda peut être interprété comme le rayon hydrodynamique des NP, alors que pour les polymères il se comporte comme une échelle de longueur de coopérativité. En simulant des réseaux de polymères polydispersés désordonnés contenant des NP purement répulsives, nous constatons que les petites NP peuvent diffuser librement à travers le maillage d'enchevêtrement, tandis que les grosses NP sont piégées de façon transitoire et ne peuvent se déplacer que par une séquence de ``sauts'' (mouvement de hopping). Nous constatons que le paramètre contrôlant la localisation des NP est le rapport entre le diamètre des NP et la longueur de localisation des crosslinks. Enfin, nous proposons une nouvelle méthode pour caractériser le maillage géométrique dans les liquides de polymères, une quantité importante pour décrire la diffusion des NP dans un milieu désordonné
Polymer nanocomposites, systems of polymers containing nanoparticles (NPs), are fascinating systems that have many applications in material science, biology and medicine, but also pose challenges to theoretical physics. One of the fundamental problems in the physics of nanocomposites is to understand how the structure and dynamics of the system depends on key parameters, such as NP size and volume fraction and the typical size of the polymeric mesh. In this thesis we use molecular dynamics simulations to study the structural and dynamic properties of NPs embedded in liquid and solid polymer-nanocomposites. We observe that when weakly attractive, well dispersed NPs are added to a dense polymer solution, both the polymers and the NPs experience a dynamical slowing down. We find that, in qualitative agreement with experiments, this dynamical slowing down is captured by a confinement parameter in the form h/λ, where h is the average distance between the surfaces of neighboring NPs (interparticle distance). We are able to show that for the NPs, λ can be interpreted as the hydrodynamic radius of the NP, whereas for the polymers it behaves as a cooperativity length scale. Simulating disordered, polydisperse polymer networks containing purely repulsive NPs, we find that small NPs can freely diffuse through the entanglement mesh, while large NPs are transiently trapped and can only move through a sequence of ``jumps'' (hopping motion). We find that the parameter controlling NP localization is the ratio between the NP diameter and the localization length of the crosslinks. Finally, we propose a new method to characterize the geometrical mesh size in polymer liquids, a quantity that is important to describe the diffusion of NP in a disordered medium
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Ahlstrom, Logan Sommers. "Molecular Dynamics Simulation of the Effect of the Crystal Environment on Protein Conformational Dynamics and Functional Motions." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/255200.

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Proteins are dynamic and interconvert between different conformations to perform their biological functions. Simulation methodology drawing upon principles from classical mechanics - molecular dynamics (MD) simulation - can be used to simulate protein dynamics and reconstruct the conformational ensemble at a level of atomic detail that is inaccessible to experiment. We use the dynamic insight achieved through simulation to enhance our understanding of protein structures solved by X-ray crystallography. Protein X-ray structures provide the most important information for structural biology, yet they depict just a single snapshot of the solution ensemble, which is under the influence of the confined crystal medium. Thus, we ask a fundamental question - how well do static X-ray structures represent the dynamic solution state of a protein? To understand how the crystal environment affects both global and local protein conformational dynamics, we consider two model systems. We first examine the variation in global conformation observed in several solved X-ray structures of the λ Cro dimer by reconstructing the solution ensemble using the replica exchange enhanced sampling method, and show that one X-ray conformation is unstable in solution. Subsequent simulation of Cro in the crystal environment quantitatively assesses the strength of packing interfaces and reveals that mutation in the lattice affects the stability of crystal forms. We also evaluate the Cro models solved by nuclear magnetic resonance spectroscopy and demonstrate that they represent unstable solution states. In addition to our studies of the Cro dimer, we investigate the effect of crystal packing on side-chain conformational dynamics through solution and crystal MD simulation of the HIV microbicide Cyanovirin-N. We find that long, polar surface side-chains can undergo a strong reduction in conformational entropy upon incorporation into crystal contacts, which supports the application of surface engineering to facilitate protein crystallization. Finally, we outline a general framework for using network visualization to aid in the functional interpretation of conformational ensembles generated from MD simulation. Our results will enhance the understanding of X-ray data in establishing protein structure-function-dynamics relationships.
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Rao, Balappa Shrisha. "Fine structure in cortical connectivity : effects on network dynamics and function Dynamics and orientation selectivity in a cortical model of rodent V1 with excess bidirectional connections Theory of orientation selectivity in random binary networks." Thesis, Sorbonne Paris Cité, 2018. https://wo.app.u-paris.fr/cgi-bin/WebObjects/TheseWeb.woa/wa/show?t=2401&f=17357.

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The local cortical network connectivity significantly deviates from a random network, giving rise to fine structure at the neuron-to-neuron level. In this study, we have investigated the effects of these fine structures on network dynamics and function. We have investigated two types of fine structure, namely, excess bidirectionality and feature specific connectivity. The study of the effects of excess bidirectionality was conducted in a conductance-based model of layer 2/3 in rodent V1. Through large scale numerical simulations, we showed that excess bidirectional connections in the inhibitory population leads to slower dynamics. Remarkably, we found that bidirectional connections between inhibitory cells are more efficacious in slowing down the dynamics than those between the excitatory cells. Additionally, bidirectional connections between inhibitory cells increases the trial-to-trial variability, while between the excitatory and inhibitory populations it reduces the variability leading to improved coding efficiency. Our results suggest that the strong reciprocal connections between excitatory and PV+ cells that have been experimentally reported can improve coding efficiency by reducing the signal-to-noise ratio. The second part of this work involved an analytical study of a model of layer 2/3 rodent V1 with binary neurons. In our study, we assumed that neurons in layer 4 were selective to stimuli orientation. Our results account for the changes in tuning properties observed during the critical period in mouse V1. Prior to the critical period, the connectivity between pyramidal neurons in the mouse V1 is non-specific. Following previous studies of spiking networks, we analytically demonstrated that with such connectivity, layer 2/3 neurons in our model develop orientation selectivity. A small fraction of strong feature specific connections between pyramidal cells have been reported in the mouse V1 after the critical period. We showed that, in spite of their small number, such connections can substantially impact the tuning of layer 2/3 cells to orientation: excitatory neurons become more selective and through non-specific global changes in their synaptic strengths, the inhibitory cells become more broadly tuned
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Books on the topic "Network Dynamics Simulation"

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Systems biology: Simulation of dynamic network states. Cambridge, UK: Cambridge University Press, 2011.

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Gilbert, Nigel, Petra Ahrweiler, and Andreas Pyka, eds. Simulating Knowledge Dynamics in Innovation Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43508-3.

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Lamers, Eugen. Contributions to Simulation Speed-Up: Rare Event Simulation and Short-Term Dynamic Simulation for Mobile Network Planning. Wiesbaden: Vieweg+Teubner / GWV Fachverlage GmbH, Wiesbaden, 2008.

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Nuzzolo, Agostino. Transit network modelling: The schedule- based dynamic approach. Milano: F. Angeli, 2003.

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A, Abrahamsen Adele, ed. Connectionism and the mind: Parallel processing, dynamics, and evolution in networks. 2nd ed. Malden, MA: Blackwell, 2002.

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Desideri, Umberto, Giampaolo Manfrida, and Enrico Sciubba, eds. ECOS 2012. Florence: Firenze University Press, 2012. http://dx.doi.org/10.36253/978-88-6655-322-9.

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The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology.
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Liu, Jinkun. Radial Basis Function (RBF) Neural Network Control for Mechanical Systems: Design, Analysis and Matlab Simulation. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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United States. National Aeronautics and Space Administration., ed. The coupling of fluids, dynamics, and controls on Advanced Architecture Computers. [Washington, DC: National Aeronautics and Space Administration, 1995.

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Magnus, Nørgaard, ed. Neural networks for modelling and control of dynamic systems: A practitioner's handbook. Berlin: Springer, 2000.

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Astrophysics School (6th 1993 Thessalonikē, Greece). Galactic dynamics and n-body simulations: Lectures held at the Astrophysics School VI, organized by the European Astrophysics Doctoral Network (EADN) in Thessaloniki, Greece, 13-23 July 1993. Berlin: Springer-Verlag, 1994.

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Book chapters on the topic "Network Dynamics Simulation"

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Wu, Shiquan, and Xun Gu. "Gene Network: Model, Dynamics and Simulation." In Lecture Notes in Computer Science, 12–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11533719_4.

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Czachórski, Tadeusz, Erol Gelenbe, and Dariusz Marek. "Software Defined Network Dynamics via Diffusions." In Modelling, Analysis, and Simulation of Computer and Telecommunication Systems, 29–47. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68110-4_2.

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Bommel, Pierre, Nicolas Becu, Christophe Le Page, and François Bousquet. "Cormas: An Agent-Based Simulation Platform for Coupling Human Decisions with Computerized Dynamics." In Simulation and Gaming in the Network Society, 387–410. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0575-6_27.

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Geiger, Alfons, and Peter Mausbach. "Molecular Dynamics Simulation Studies of the Hydrogen Bond Network in Water." In Hydrogen-Bonded Liquids, 171–83. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3274-9_14.

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Goto, Hayato, Hideki Takayasu, and Misako Takayasu. "Empirical Analysis of Firm-Dynamics on Japanese Interfirm Trade Network." In Proceedings of the International Conference on Social Modeling and Simulation, plus Econophysics Colloquium 2014, 195–204. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20591-5_18.

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Montagna, Sara, Michele Braccini, and Andrea Roli. "The Impact of Self-loops in Random Boolean Network Dynamics: A Simulation Analysis." In Communications in Computer and Information Science, 104–15. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78658-2_8.

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Kaneko, Yoshihisa, S. Hirota, and Satoshi Hashimoto. "Discrete Dislocation Dynamics Simulation on Strengths of Dislocation Network Stacks in Multilayered Structures." In Key Engineering Materials, 1086–89. Stafa: Trans Tech Publications Ltd., 2007. http://dx.doi.org/10.4028/0-87849-456-1.1086.

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Rüttgers, Mario, Seong-Ryong Koh, Jenia Jitsev, Wolfgang Schröder, and Andreas Lintermann. "Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning." In Lecture Notes in Computer Science, 81–101. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59851-8_6.

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Abstract Using traditional computational fluid dynamics and aeroacoustics methods, the accurate simulation of aeroacoustic sources requires high compute resources to resolve all necessary physical phenomena. In contrast, once trained, artificial neural networks such as deep encoder-decoder convolutional networks allow to predict aeroacoustics at lower cost and, depending on the quality of the employed network, also at high accuracy. The architecture for such a neural network is developed to predict the sound pressure level in a 2D square domain. It is trained by numerical results from up to 20,000 GPU-based lattice-Boltzmann simulations that include randomly distributed rectangular and circular objects, and monopole sources. Types of boundary conditions, the monopole locations, and cell distances for objects and monopoles serve as input to the network. Parameters are studied to tune the predictions and to increase their accuracy. The complexity of the setup is successively increased along three cases and the impact of the number of feature maps, the type of loss function, and the number of training data on the prediction accuracy is investigated. An optimal choice of the parameters leads to network-predicted results that are in good agreement with the simulated findings. This is corroborated by negligible differences of the sound pressure level between the simulated and the network-predicted results along characteristic lines and by small mean errors.
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Vashishta, Priya, Donald L. Greenwell, Rajiv K. Kalia, and Aiichiro Nakano. "Computer Simulation of Network Glasses and Molecular Dynamics Algorithm on SIMD and MIMD Machines." In Recent Progress in Many-Body Theories, 481–92. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3466-2_34.

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Wu, Fred, Tejaswi Jonnalagadda, Colmenares-diaz Eduardo, Sailaja Peruka, Poojitha Chapala, and Pooja Sonmale. "Long Short-Term Memory Neural Network on the Trajectory Computing of Direct Dynamics Simulation." In Advances in Parallel & Distributed Processing, and Applications, 217–33. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69984-0_17.

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Conference papers on the topic "Network Dynamics Simulation"

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Semakhin, Andrei M. "Network Simulation of Information System in Conditions Of Uncertainty." In 2018 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2018. http://dx.doi.org/10.1109/dynamics.2018.8601500.

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Monakhov, Yuri M., Mikhail Yu Monakhov, and Andrey V. Telny. "Simulation of routing in an ad-hoc network in conditions of limited availability." In 2017 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2017. http://dx.doi.org/10.1109/dynamics.2017.8239487.

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Kuhlman, Chris, Bryan Lewis, Richard Beckman, Stephen Eubank, and Tridib Dutta. "Clustering method incorporating network topology and dynamics." In the 2010 Spring Simulation Multiconference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1878537.1878552.

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Pluhacek, Michal, Roman Senkerik, Jakub Janostik, Adam Viktorin, and Ivan Zelinka. "Study On Swarm Dynamics Converted Into Complex Network." In 30th Conference on Modelling and Simulation. ECMS, 2016. http://dx.doi.org/10.7148/2016-0252.

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Zarembo, A. "Molecular Dynamics Simulation of Liquid Crystalline Polymer Networks and Flexible Polymer Network in Liquid Crystal Solution." In SLOW DYNAMICS IN COMPLEX SYSTEMS: 3rd International Symposium on Slow Dynamics in Complex Systems. AIP, 2004. http://dx.doi.org/10.1063/1.1764203.

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Liu, Ying, and Yuxiao Li. "Simulation on the Dynamics of Interpersonal Communication Network." In 2011 IEEE 9th International Conference on Dependable, Autonomic and Secure Computing (DASC). IEEE, 2011. http://dx.doi.org/10.1109/dasc.2011.157.

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Kharlamov, Viktor V., Yuriy V. Moskalev, and Viktor S. Lysenko. "Simulation of The Electrical Phase Converter Connecting a Three-Phase Motor to A Single-Phase Network." In 2020 Dynamics of Systems, Mechanisms and Machines (Dynamics). IEEE, 2020. http://dx.doi.org/10.1109/dynamics50954.2020.9306160.

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Fiala, Petr, and Martina Kuncová. "Simulation model of supply networks development." In The 19th International Conference on Modelling and Applied Simulation. CAL-TEK srl, 2019. http://dx.doi.org/10.46354/i3m.2019.mas.003.

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The paper is dedicated to network development in the network economy. The current economy needs to look not only at networks with only dynamic flows and with a fixed structure, but as a dynamic system its structure evolves and changes. Structure and behaviour dynamics of network systems can be modelled as complex adaptive systems and use agent-oriented simulation to demonstrate origin, perturbation effects, and sensitivity with regard to initial conditions. Survival of firms is associated with the value of so-called fitness function. Firms whose fitness value falls below a certain threshold will be extinguished. In this way, it is possible to partially model network growth. A simulation model in SIMUL8 is proposed.
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"Modelling the structure and dynamics of network-based social systems." In 19th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2011. http://dx.doi.org/10.36334/modsim.2011.plenary.pattison.

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Shuai, Zhibin, Hui Zhang, Junmin Wang, Jianqiu Li, and Minggao Ouyang. "Network Control of Vehicle Lateral Dynamics With Control Allocation and Dynamic Message Priority Assignment." In ASME 2013 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/dscc2013-3890.

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In this paper we study the lateral motion control and torque allocation for four-wheel-independent-drive electric vehicles (4WID-EVs) with combined active front steering (AFS) and direct yaw moment control (DYC) through in-vehicle networks. It is well known that the in-vehicle networks and x-by-wire technologies have considerable advantages over the traditional point-to-point communications, and bring great strengths to 4WID-EVs. However, there are also bandwidth limitations which would lead to message time delays in network communication. We propose a method on effectively utilizing the limited bandwidth resources and attenuating the adverse influence of in-vehicle network-induced time delays, based on the idea of dynamic message priority assignment according to the vehicle states and control signals. Simulation results from a high-fidelity vehicle model in CarSim® show that the proposed vehicle lateral control and torque allocation algorithm can improve the 4WID-EV lateral motion control performance, and the proposed message priority dynamic assignment algorithm can significantly reduce the adverse influence of the in-vehicle network-induced time delays.
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Reports on the topic "Network Dynamics Simulation"

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Wang, Chaojie, Yu Wang, and Srinivas Peeta. Development of Dynamic Network Traffic Simulator for Mixed Traffic Flow under Connected and Autonomous Vehicle Technologies. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317564.

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Wu, Yingjie, Selim Gunay, and Khalid Mosalam. Hybrid Simulations for the Seismic Evaluation of Resilient Highway Bridge Systems. Pacific Earthquake Engineering Research Center, University of California, Berkeley, CA, November 2020. http://dx.doi.org/10.55461/ytgv8834.

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Bridges often serve as key links in local and national transportation networks. Bridge closures can result in severe costs, not only in the form of repair or replacement, but also in the form of economic losses related to medium- and long-term interruption of businesses and disruption to surrounding communities. In addition, continuous functionality of bridges is very important after any seismic event for emergency response and recovery purposes. Considering the importance of these structures, the associated structural design philosophy is shifting from collapse prevention to maintaining functionality in the aftermath of moderate to strong earthquakes, referred to as “resiliency” in earthquake engineering research. Moreover, the associated construction philosophy is being modernized with the utilization of accelerated bridge construction (ABC) techniques, which strive to reduce the impact of construction on traffic, society, economy and on-site safety. This report presents two bridge systems that target the aforementioned issues. A study that combined numerical and experimental research was undertaken to characterize the seismic performance of these bridge systems. The first part of the study focuses on the structural system-level response of highway bridges that incorporate a class of innovative connecting devices called the “V-connector,”, which can be used to connect two components in a structural system, e.g., the column and the bridge deck, or the column and its foundation. This device, designed by ACII, Inc., results in an isolation surface at the connection plane via a connector rod placed in a V-shaped tube that is embedded into the concrete. Energy dissipation is provided by friction between a special washer located around the V-shaped tube and a top plate. Because of the period elongation due to the isolation layer and the limited amount of force transferred by the relatively flexible connector rod, bridge columns are protected from experiencing damage, thus leading to improved seismic behavior. The V-connector system also facilitates the ABC by allowing on-site assembly of prefabricated structural parts including those of the V-connector. A single-column, two-span highway bridge located in Northern California was used for the proof-of-concept of the proposed V-connector protective system. The V-connector was designed to result in an elastic bridge response based on nonlinear dynamic analyses of the bridge model with the V-connector. Accordingly, a one-third scale V-connector was fabricated based on a set of selected design parameters. A quasi-static cyclic test was first conducted to characterize the force-displacement relationship of the V-connector, followed by a hybrid simulation (HS) test in the longitudinal direction of the bridge to verify the intended linear elastic response of the bridge system. In the HS test, all bridge components were analytically modeled except for the V-connector, which was simulated as the experimental substructure in a specially designed and constructed test setup. Linear elastic bridge response was confirmed according to the HS results. The response of the bridge with the V-connector was compared against that of the as-built bridge without the V-connector, which experienced significant column damage. These results justified the effectiveness of this innovative device. The second part of the study presents the HS test conducted on a one-third scale two-column bridge bent with self-centering columns (broadly defined as “resilient columns” in this study) to reduce (or ultimately eliminate) any residual drifts. The comparison of the HS test with a previously conducted shaking table test on an identical bridge bent is one of the highlights of this study. The concept of resiliency was incorporated in the design of the bridge bent columns characterized by a well-balanced combination of self-centering, rocking, and energy-dissipating mechanisms. This combination is expected to lead to minimum damage and low levels of residual drifts. The ABC is achieved by utilizing precast columns and end members (cap beam and foundation) through an innovative socket connection. In order to conduct the HS test, a new hybrid simulation system (HSS) was developed, utilizing commonly available software and hardware components in most structural laboratories including: a computational platform using Matlab/Simulink [MathWorks 2015], an interface hardware/software platform dSPACE [2017], and MTS controllers and data acquisition (DAQ) system for the utilized actuators and sensors. Proper operation of the HSS was verified using a trial run without the test specimen before the actual HS test. In the conducted HS test, the two-column bridge bent was simulated as the experimental substructure while modeling the horizontal and vertical inertia masses and corresponding mass proportional damping in the computer. The same ground motions from the shaking table test, consisting of one horizontal component and the vertical component, were applied as input excitations to the equations of motion in the HS. Good matching was obtained between the shaking table and the HS test results, demonstrating the appropriateness of the defined governing equations of motion and the employed damping model, in addition to the reliability of the developed HSS with minimum simulation errors. The small residual drifts and the minimum level of structural damage at large peak drift levels demonstrated the superior seismic response of the innovative design of the bridge bent with self-centering columns. The reliability of the developed HS approach motivated performing a follow-up HS study focusing on the transverse direction of the bridge, where the entire two-span bridge deck and its abutments represented the computational substructure, while the two-column bridge bent was the physical substructure. This investigation was effective in shedding light on the system-level performance of the entire bridge system that incorporated innovative bridge bent design beyond what can be achieved via shaking table tests, which are usually limited by large-scale bridge system testing capacities.
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Event-Triggered Adaptive Robust Control for Lateral Stability of Steer-by-Wire Vehicles with Abrupt Nonlinear Faults. SAE International, July 2022. http://dx.doi.org/10.4271/2022-01-5056.

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Because autonomous vehicles (AVs) equipped with active front steering have the features of time varying, uncertainties, high rate of fault, and high burden on the in-vehicle networks, this article studies the adaptive robust control problem for improving lateral stability in steer-by-wire (SBW) vehicles in the presence of abrupt nonlinear faults. First, an upper-level robust H∞ controller is designed to obtain the desired front-wheel steering angle for driving both the yaw rate and the sideslip angle to reach their correct values. Takagi-Sugeno (T-S) fuzzy modeling method, which has shown the extraordinary ability in coping with the issue of nonlinear, is applied to deal with the challenge of the changing longitudinal velocity. The output of the upper controller can be calculated by a parallel distributed compensation (PDC) scheme. Then an event-triggered adaptive fault-tolerant lower controller (ET-AFTC) is proposed to drive the whole SBW system driving the desired steering angle offered by the upper controller with fewer communication resources and strong robustness. By employing a backstepping technique, the tracking performance is improved. The dynamic surface control (DSC) approach is used to avoid the problem of repeated differentiations, and Nussbaum function is adopted to overcome the difficulty of unknown nonlinear control gain. Both the stability of the upper and lower controllers can be guaranteed by Lyapunov functions. Finally, the simulations of Matlab/Simulink are given to show that the proposed control strategy is effectively able to deal with the abrupt nonlinear fault via less communication resources and perform better in ensuring the yaw stability of the vehicle.
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