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1

Pham, Kien Huu, and Trang Thi Thuy Giap. "The liquid–amorphous phase transition, slow dynamics and dynamical heterogeneity for bulk iron: a molecular dynamics simulation." RSC Advances 11, no. 51 (2021): 32435–45. http://dx.doi.org/10.1039/d1ra06394d.

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2

Raza, Md Shamim, Nitesh Kumar, and Sourav Poddar. "Combustor Characteristics under Dynamic Condition during Fuel – Air Mixingusing Computational Fluid Dynamics." Journal of Advances in Mechanical Engineering and Science 1, no. 1 (August 8, 2015): 20–33. http://dx.doi.org/10.18831/james.in/2015011003.

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3

STRADTMANN, Hinnerk. "1D14 Examples for European assessment of vehicle's dynamic running behaviour(Vehicles-Dynamics)." Proceedings of International Symposium on Seed-up and Service Technology for Railway and Maglev Systems : STECH 2015 (2015): _1D14–1_—_1D14–12_. http://dx.doi.org/10.1299/jsmestech.2015._1d14-1_.

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4

Li, Jian Jia, and Xin Hua Zhao. "Dynamics Modeling and Simulation of Tracked Five DOF Mobile Manipulator." Advanced Materials Research 433-440 (January 2012): 4817–22. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.4817.

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The dynamical analysis for the tracked moving platform and the manipulator are established based on by Newton-Euler method and Dynamics model is respectively obtained, Moreover, Dynamic simulation is conducted, and reveals the input-output relation for the motion system from dynamical simulation, and plays a solid basic for the further study of dynamic modeling and motion control.
5

SUN, KEHUI, and J. C. SPROTT. "DYNAMICS OF A SIMPLIFIED LORENZ SYSTEM." International Journal of Bifurcation and Chaos 19, no. 04 (April 2009): 1357–66. http://dx.doi.org/10.1142/s0218127409023688.

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A simplified Lorenz system with one bifurcation parameter is investigated by a detailed theoretical analysis as well as dynamic simulation, including some basic dynamical properties, Lyapunov exponent spectra, fractal dimension, bifurcations and routes to chaos. The results show that this system has complex dynamics with interesting characteristics.
6

Mozur, Eve M., and James R. Neilson. "Cation Dynamics in Hybrid Halide Perovskites." Annual Review of Materials Research 51, no. 1 (July 26, 2021): 269–91. http://dx.doi.org/10.1146/annurev-matsci-080819-012808.

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Hybrid halide perovskite semiconductors exhibit complex, dynamical disorder while also harboring properties ideal for optoelectronic applications that include photovoltaics. However, these materials are structurally and compositionally distinct from traditional compound semiconductors composed of tetrahedrally coordinated elements with an average valence electron count of silicon. The additional dynamic degrees of freedom of hybrid halide perovskites underlie many of their potentially transformative physical properties. Neutron scattering and spectroscopy studies of the atomic dynamics of these materials have yielded significant insights into their functional properties. Specifically, inelastic neutron scattering has been used to elucidate the phonon band structure, and quasi-elastic neutron scattering has revealed the nature of the uncorrelated dynamics pertaining to molecular reorientations. Understanding the dynamics of these complex semiconductors has elucidated the temperature-dependent phase stability and origins of defect-tolerant electronic transport from the highly polarizable dielectric response. Furthermore, the dynamic degrees of freedom of the hybrid perovskites provide additional opportunities for application engineering and innovation.
7

Menzies, Dylan. "Composing instrument control dynamics." Organised Sound 7, no. 3 (December 2002): 255–66. http://dx.doi.org/10.1017/s1355771802003059.

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The expression gestural mapping is well imbedded in the language of instrument designers, describing the function from interface control parameters to synthesis control parameters. This function is in most cases implicitly assumed to be instantaneous, so that at any time its output depends only on its input at that time. Here more general functions are considered, in which the output depends on the history of input, especially functions that behave like physical dynamic systems, such as a damped resonator. Acoustic instruments are rich in dynamical behaviour. Introducing dynamics at the control stage of an electronic instrument can help compensate for lack of dynamics in later non-physical synthesis stages. A broadening of the function space offers new aesthetic possibilities for composing instruments. Examples are presented to illustrate the new design/composition mode as well as practical techniques. In this context, it is suggested that the word mapping be updated with the more descriptive expression dynamic control processing.
8

VINCENT, THOMAS L. "THE G-FUNCTION METHOD FOR ANALYZING DARWINIAN DYNAMICS." International Game Theory Review 06, no. 01 (March 2004): 69–90. http://dx.doi.org/10.1142/s0219198904000083.

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Darwinian dynamics refers to the dynamical processes underlying natural selection that drives evolution. We are interested in the evolution of strategies used by biological entities. There are two dynamical processes involved, population dynamics (relationship between population density and the agents affecting density) and strategy dynamics (relationship between strategy values and the agents affecting these values). Darwinian dynamics is a total dynamic obtained through the coupling of these two processes, the modeling of which, involves dynamical systems, optimization, stability, and game theory. Using a method called the G-function approach, we explore how an evolutionary process can take place in a set of differential equations, and we examine some interesting links between evolutionary stability and optimization as embodied in the ESS maximum principle. One of the interesting paradoxes is how a "hill-climbing" algorithm can end up at a stable local minimum and why this might have important implications in understanding speciation (the creation of new species from a homogeneous population). Finally, we will examine how these concepts are currently being applied to model the development of tumors in humans.
9

Beiran, Manuel, Alexis Dubreuil, Adrian Valente, Francesca Mastrogiuseppe, and Srdjan Ostojic. "Shaping Dynamics With Multiple Populations in Low-Rank Recurrent Networks." Neural Computation 33, no. 6 (May 13, 2021): 1572–615. http://dx.doi.org/10.1162/neco_a_01381.

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An emerging paradigm proposes that neural computations can be understood at the level of dynamic systems that govern low-dimensional trajectories of collective neural activity. How the connectivity structure of a network determines the emergent dynamical system, however, remains to be clarified. Here we consider a novel class of models, gaussian-mixture, low-rank recurrent networks in which the rank of the connectivity matrix and the number of statistically defined populations are independent hyperparameters. We show that the resulting collective dynamics form a dynamical system, where the rank sets the dimensionality and the population structure shapes the dynamics. In particular, the collective dynamics can be described in terms of a simplified effective circuit of interacting latent variables. While having a single global population strongly restricts the possible dynamics, we demonstrate that if the number of populations is large enough, a rank R network can approximate any R-dimensional dynamical system.
10

Mei, Zhuanglin, and Toshiki Oguchi. "Network Structure Identification Based on Measured Output Data Using Koopman Operators." Mathematics 11, no. 1 (December 26, 2022): 89. http://dx.doi.org/10.3390/math11010089.

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This paper considers the identification problem of network structures of interconnected dynamical systems using measured output data. In particular, we propose an identification method based on the measured output data of each node in the network whose dynamic is unknown. The proposed identification method consists of three steps: we first consider the outputs of the nodes to be all the states of the dynamics of the nodes, and the unmeasurable hidden states to be dynamical inputs with unknown dynamics. In the second step, we define the dynamical inputs as new variables and identify the dynamics of the network system with measured output data using Koopman operators. Finally, we extract the network structure from the identified dynamics as the information transmitted via the network. We show that the identified coupling functions, which represent the network structures, are actually projections of the dynamical inputs onto the space spanned by some observable functions. Numerical examples illustrate the validity of the obtained results.
11

Graovac, Stefan, Andjela Rodic, Magdalena Djordjevic, Konstantin Severinov, and Marko Djordjevic. "Effects of Population Dynamics on Establishment of a Restriction-Modification System in a Bacterial Host." Molecules 24, no. 1 (January 7, 2019): 198. http://dx.doi.org/10.3390/molecules24010198.

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In vivo dynamics of protein levels in bacterial cells depend on both intracellular regulation and relevant population dynamics. Such population dynamics effects, e.g., interplay between cell and plasmid division rates, are, however, often neglected in modeling gene expression regulation. Including them in a model introduces additional parameters shared by the dynamical equations, which can significantly increase dimensionality of the parameter inference. We here analyse the importance of these effects, on a case of bacterial restriction-modification (R-M) system. We redevelop our earlier minimal model of this system gene expression regulation, based on a thermodynamic and dynamic system modeling framework, to include the population dynamics effects. To resolve the problem of effective coupling of the dynamical equations, we propose a “mean-field-like” procedure, which allows determining only part of the parameters at a time, by separately fitting them to expression dynamics data of individual molecular species. We show that including the interplay between kinetics of cell division and plasmid replication is necessary to explain the experimental measurements. Moreover, neglecting population dynamics effects can lead to falsely identifying non-existent regulatory mechanisms. Our results call for advanced methods to reverse-engineer intracellular regulation from dynamical data, which would also take into account the population dynamics effects.
12

Aspinall, Richard, Michele Staiano, and Diane Pearson. "Emergent Properties of Land Systems: Nonlinear Dynamics of Scottish Farming Systems from 1867 to 2020." Land 10, no. 11 (November 1, 2021): 1172. http://dx.doi.org/10.3390/land10111172.

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Dynamics of arable and pastoral farming systems in Scotland over the period 1867–2020 are documented using time series analysis methods, including for nonlinear dynamical systems. Results show arable and pastoral farming, at a national scale, are dynamic over a range of timescales, with medium- and short-term dynamics associated with endogenous system forces and exogenous factors, respectively. Medium-term dynamics provide evidence of endogenous systems-level feedbacks between farming sectors responding to change in world and national cereal prices as an economic driver, and act to dampen impacts of exogenous shocks and events (weather, disease). Regime shifts are identified in national cereal prices. Results show change and dynamics as emergent properties of system interactions. Changes in dynamics and strength of endogenous dampening over the duration of the study are associated with dynamical changes from major governmental policy decisions that altered the boundary conditions for interdependencies of arable and pastoral farming.
13

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.
14

Caux, S., and R. Zapata. "Modeling and control of biped robot dynamics." Robotica 17, no. 4 (July 1999): 413–26. http://dx.doi.org/10.1017/s0263574799001411.

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This paper addresses the problem of modeling biped dynamics and the use of such models for the control of walking, running and jumping robots. We describe two approaches to dynamic modeling: the basic Lagrange approach and the non-regular dynamic approach. The new non-regular dynamic approach takes into account discontinuities due to rigid contact between punctual feet and the ground without computing the exact impact time. The contact is close to the physical situation given by non-linear laws (impenetrability, non-smooth contact and real friction cone). Contact dynamics can be well managed with an accurate dynamic model that respects energy consistency during all the phases encountered during a step (0, 1 or 2 contacts). With this model, we can first study the equilibrum of a biped standing on one foot by a linearisation method. In the second stage, the unified modelized equation is used to establish a general control frame based on non-regular dynamical decoupling. A comparison is made and some simulation results are given with a two degree of freedom planar biped robot.
15

Feng, Zengming, Fuliang Suo, and Yabing Cheng. "58793 MESHING MECHANISM AND DYNAMIC ANALYSIS OF NEW SILENT CHAIN(Dynamics of Machine Components)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _58793–1_—_58793–5_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._58793-1_.

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16

Cho, J. I., J. Y. Kim, and T. W. Park. "62931 DYNAMIC ANALYSIS ON THE NEXT GENERATION HIGH-SPEED RAILWAY VEHICLE(Railroad System Dynamics)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _62931–1_—_62931–6_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._62931-1_.

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17

Dieball, Cai, Diego Krapf, Matthias Weiss, and Aljaž Godec. "Scattering fingerprints of two-state dynamics." New Journal of Physics 24, no. 2 (February 1, 2022): 023004. http://dx.doi.org/10.1088/1367-2630/ac48e8.

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Abstract Particle transport in complex environments such as the interior of living cells is often (transiently) non-Fickian or anomalous, that is, it deviates from the laws of Brownian motion. Such anomalies may be the result of small-scale spatio-temporal heterogeneities in, or viscoelastic properties of, the medium, molecular crowding, etc. Often the observed dynamics displays multi-state characteristics, i.e. distinct modes of transport dynamically interconverting between each other in a stochastic manner. Reliably distinguishing between single- and multi-state dynamics is challenging and requires a combination of distinct approaches. To complement the existing methods relying on the analysis of the particle’s mean squared displacement, position- or displacement-autocorrelation function, and propagators, we here focus on ‘scattering fingerprints’ of multi-state dynamics. We develop a theoretical framework for two-state scattering signatures—the intermediate scattering function and dynamic structure factor—and apply it to the analysis of simple model systems as well as particle-tracking experiments in living cells. We consider inert tracer-particle motion as well as systems with an internal structure and dynamics. Our results may generally be relevant for the interpretation of state-of-the-art differential dynamic microscopy experiments on complex particulate systems, as well as inelastic or quasielastic neutron (incl. spin-echo) and x-ray scattering probing structural and dynamical properties of macromolecules, when the underlying dynamics displays two-state transport.
18

Cheng, Jun, Shusheng Bi, Chang Yuan, Lin Chen, Yueri Cai, and Yanbin Yao. "A Graph Theory-Based Method for Dynamic Modeling and Parameter Identification of 6-DOF Industrial Robots." Applied Sciences 11, no. 22 (November 19, 2021): 10988. http://dx.doi.org/10.3390/app112210988.

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At present, the absolute positioning accuracy and control accuracy of industrial serial robots need to be improved to meet the accuracy requirements of precision manufacturing and precise control. An accurate dynamic model is an important theoretical basis for solving this problem, and precise dynamic parameters are the prerequisite for precise control. The research of dynamics and parameter identification can greatly promote the application of robots in the field of precision manufacturing and automation. In this paper, we study the dynamical modeling and dynamic parameter identification of an industrial robot system with six rotational DOF (6R robot system) and propose a new method for identifying dynamic parameters. Our aim is to provide an accurate mathematical description of the dynamics of the 6R robot and to accurately identify its dynamic parameters. First, we establish an unconstrained dynamic model for the 6R robot system and rewrite it to obtain the dynamic parameter identification model. Second, we establish the constraint equations of the 6R robot system. Finally, we establish the dynamic model of the constrained 6R robot system. Through the ADAMS simulation experiment, we verify the correctness and accuracy of the dynamic model. The experiments prove that the result of parameter identification has extremely high accuracy and the dynamic model can accurately describe the 6R robot system mathematically. The dynamic modeling method proposed in this paper can be used as the theoretical basis for the study of 6R robot system dynamics and the study of dynamics-based control theory.
19

d’Addese, Gianluca, Salvatore Magrì, Roberto Serra, and Marco Villani. "Exploring the Dynamic Organization of Random and Evolved Boolean Networks." Algorithms 13, no. 11 (October 28, 2020): 272. http://dx.doi.org/10.3390/a13110272.

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The properties of most systems composed of many interacting elements are neither determined by the topology of the interaction network alone, nor by the dynamical laws in isolation. Rather, they are the outcome of the interplay between topology and dynamics. In this paper, we consider four different types of systems with critical dynamic regime and with increasingly complex dynamical organization (loosely defined as the emergent property of the interactions between topology and dynamics) and analyze them from a structural and dynamic point of view. A first noteworthy result, previously hypothesized but never quantified so far, is that the topology per se induces a notable increase in dynamic organization. A second observation is that evolution does not change dramatically the size distribution of the present dynamic groups, so it seems that it keeps track of the already present organization induced by the topology. Finally, and similarly to what happens in other applications of evolutionary algorithms, the types of dynamic changes strongly depend upon the used fitness function.
20

Sun, Ao, and Ting Qiang Yao. "Modeling and Analysis of Planar Multibody System Containing Deep Groove Ball Bearing with Slider-Crank Mechanism." Advanced Materials Research 753-755 (August 2013): 918–23. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.918.

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With the rotating machinery system developing toward high speed, high precision, and high reliability direction, ball bearing dynamic performance have a critical impact to dynamics characteristics of support system. Based on multibody dynamics theory and contact dynamics method,and considering the ball and ring raceway 3 d dynamic contact relationship, using ADAMS dynamics analysis software to establish the multibody dynamics model of crank slider mechanism containing ball bearing dynamic contact relationship.The simulation analysis of the dynamic performance of the ball bearing and the crank slider mechanism dynamics response, and the influence of dynamic performance for considering ball bearing rotating mechanical system dynamics analysis provides a reference method.The simulation analysts the influence of dynamic performance of the ball bearing to the crank slider mechanism dynamics response. It provides a reference method for rotating mechanical system dynamics analysis considering the dynamic performance of the ball bearing.
21

Varona, Pablo, and Mikhail I. Rabinovich. "Hierarchical dynamics of informational patterns and decision-making." Proceedings of the Royal Society B: Biological Sciences 283, no. 1832 (June 15, 2016): 20160475. http://dx.doi.org/10.1098/rspb.2016.0475.

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Traditional studies on the interaction of cognitive functions in healthy and disordered brains have used the analyses of the connectivity of several specialized brain networks—the functional connectome. However, emerging evidence suggests that both brain networks and functional spontaneous brain-wide network communication are intrinsically dynamic. In the light of studies investigating the cooperation between different cognitive functions, we consider here the dynamics of hierarchical networks in cognitive space. We show, using an example of behavioural decision-making based on sequential episodic memory, how the description of metastable pattern dynamics underlying basic cognitive processes helps to understand and predict complex processes like sequential episodic memory recall and competition among decision strategies. The mathematical images of the discussed phenomena in the phase space of the corresponding cognitive model are hierarchical heteroclinic networks. One of the most important features of such networks is the robustness of their dynamics. Different kinds of instabilities of these dynamics can be related to ‘dynamical signatures’ of creativity and different psychiatric disorders. The suggested approach can also be useful for the understanding of the dynamical processes that are the basis of consciousness.
22

Cheng, Zai Bin, Wei Jiang, Ge Xue Ren, Jian Liang Zhou, Shi Quan Jiang, Cai Jin Yang, and Bao Sheng He. "A Multibody Dynamical Model for Full Hole Drillstring Dynamics." Applied Mechanics and Materials 378 (August 2013): 91–96. http://dx.doi.org/10.4028/www.scientific.net/amm.378.91.

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The research on drillstring dynamics is necessary for improving drilling efficiency and safety. In this investigation, a multibody dynamical model for 3D full hole drillstring system is presented based on the Absolute Nodal Coordinate Formulation (ANCF). The drillstring is modeled with the ANCF beam element. The absolute nodal coordinate formulation of the beam element as well as the boundary conditions at the top-drive and drill-bit, and the contact/friction model between drillstring and wellbore are also investigated. The dynamic governing equation for full hole drillstring system is given and solved by the backward differentiation formulation (BDF) for differential algebraic equations (DAEs). The developed multibody dynamic solver is capable of analyzing full coupled vibration for the full hole drillstring system. It can play a certain role in drillstring dynamics researches and engineering applications.
23

Heitmann, Stewart, and Michael Breakspear. "Putting the “dynamic” back into dynamic functional connectivity." Network Neuroscience 2, no. 2 (June 2018): 150–74. http://dx.doi.org/10.1162/netn_a_00041.

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The study of fluctuations in time-resolved functional connectivity is a topic of substantial current interest. As the term “dynamic functional connectivity” implies, such fluctuations are believed to arise from dynamics in the neuronal systems generating these signals. While considerable activity currently attends to methodological and statistical issues regarding dynamic functional connectivity, less attention has been paid toward its candidate causes. Here, we review candidate scenarios for dynamic (functional) connectivity that arise in dynamical systems with two or more subsystems; generalized synchronization, itinerancy (a form of metastability), and multistability. Each of these scenarios arises under different configurations of local dynamics and intersystem coupling: We show how they generate time series data with nonlinear and/or nonstationary multivariate statistics. The key issue is that time series generated by coupled nonlinear systems contain a richer temporal structure than matched multivariate (linear) stochastic processes. In turn, this temporal structure yields many of the phenomena proposed as important to large-scale communication and computation in the brain, such as phase-amplitude coupling, complexity, and flexibility. The code for simulating these dynamics is available in a freeware software platform, the Brain Dynamics Toolbox.
24

Demuth, Dominik, Matthias Sattig, Elisa Steinrücken, Max Weigler, and Michael Vogel. "2H NMR Studies on the Dynamics of Pure and Mixed Hydrogen-Bonded Liquids in Confinement." Zeitschrift für Physikalische Chemie 232, no. 7-8 (July 26, 2018): 1059–87. http://dx.doi.org/10.1515/zpch-2017-1027.

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Abstract2H NMR is used to ascertain dynamical behaviors of pure and mixed hydrogen-bonded liquids in bulk and in confinement. Detailed comparisons of previous and new results in broad dynamic and temperature ranges reveal that confinement effects differ for various liquids and confinements. For water, molecular reorientation strongly depends on the confinement size, with much slower and less fragile structural relaxation under more severe geometrical restriction. Moreover, a dynamical crossover occurs when a fraction of solid water forms so that the dynamics of the fraction of liquid water becomes even more restricted and, as a consequence, changes from bulk-like to interface-dominated. For glycerol, by contrast, confinement has weak effects on the reorientation dynamics. Mixed hydrogen-bonded liquids show even more complex dynamical behaviors. For aqueous solutions, the temperature dependence of the structural relaxation becomes discontinuous when the concentration changes due to a freezing of water fractions. This tendency for partial crystallization is enhanced rather than reduced by confinement, because different liquid-matrix interactions of the molecular species induce micro-phase segregation, which facilitates ice formation in water-rich regions. In addition, dynamical couplings at solvent-protein interfaces are discussed. It is shown that, on the one hand, solvent dynamics are substantially slowed down at protein surfaces and, on the other hand, protein dynamics significantly depend on the composition and, thus, the viscosity of the solvent. Furthermore, a protein dynamical transition occurs when the amplitude of water-coupled restricted backbone dynamics vanishes upon cooling.
25

Gough, Craig A., Takashi Gojobori, and Tadashi Imanishi. "1P563 Consistent dynamic phenomena in amyloidogenic forms of transthyretin : a molecular dynamics study(27. Molecular dynamics simulation,Poster Session,Abstract,Meeting Program of EABS & BSJ 2006)." Seibutsu Butsuri 46, supplement2 (2006): S287. http://dx.doi.org/10.2142/biophys.46.s287_3.

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26

YAN, YONG-HONG, CHANG-QIN WU, and BAO-WEN LI. "BIPOLARON DYNAMICS IN NON-DEGENERATE POLYMERS." International Journal of Modern Physics B 21, no. 23n24 (September 30, 2007): 4190–95. http://dx.doi.org/10.1142/s0217979207045396.

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Bipolaron dynamics in non-degenerate polymers are discussed using the nonadiabatic dynamic method. First, charge injection process from metal electrode to a nondegenerate polymer in a metal/polymer/metal structure has been investigated. We demonstrate that the dynamical formation of a bipolaron sensitively depends on the work function of metal electrode. We also study the bipolaron dissociation process. It is found that the electric field that can dissociate the bipolaron is up to 106 V/cm, which is consistent with experiments.
27

Hirsch, Morris W. "Mathematics of Hebbian attractors." Behavioral and Brain Sciences 18, no. 4 (December 1995): 633–34. http://dx.doi.org/10.1017/s0140525x00040243.

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AbstractThe concept of an attractor in a mathematical dynamical system is reviewed. Emphasis is placed on the distinction between a cell assembly, the corresponding attractor, and the attractor dynamics. The biological significance of these entities is discussed, especially the question of whether the representation of the stimulus requires the full attractor dynamics, or merely the cell assembly as a set of reverberating neurons. Comparison is made to Freeman's study of dynamic patterns in olfaction.
28

Chetverikov, Aleksandr, and Werner Ebeling. "Nonlinear problems of molecular physics." Izvestiya VUZ. Applied Nonlinear Dynamics 10, no. 3 (September 30, 2002): 3–21. http://dx.doi.org/10.18500/0869-6632-2002-10-3-3-21.

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A survey оn investigations of some nonlinear problems оf molecular physics carried out by molecular dynamics simulations is given. Among them there are problems of elementary excitations in fluids, the dynamics оf chemical reactions in solutions, dynamical properties of dilute plasma, dynamic phenomena in phase transitions in mesoscopic systems, structural properties of chains оf nonlinear oscillators. Several new results about the distribution оf clusters and of а method of identification of clusters are presented.
29

Rui, Zhou, and Qi Guijie. "A System Dynamics Model for Open Innovation Community." International Journal of Enterprise Information Systems 14, no. 4 (October 2018): 78–88. http://dx.doi.org/10.4018/ijeis.2018100106.

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In order to promote the development speed of the open innovation community, a dynamical system model of it is constructed, and the simulation is carried out to find out the rules of the running rules for the open innovation community. First, the basic characteristics of open innovation community are summarized. Second, the system dynamics model of open innovation community is constructed. Finally, the simulation analysis based on dynamic system model of the open innovation community is carried out, and the effect of different factors on the variables of the open innovation community is obtained. Results show that system dynamics is an effective tool for analyzing the open innovation community.
30

Nechaev, Yu I. "Ontological synthesis of non-stationary dynamics models of on-board intelligence systems." Ontology of designing 11, no. 1 (March 30, 2021): 117–25. http://dx.doi.org/10.18287/2223-9537-2021-11-1-117-125.

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An ontological synthesis of models for interpreting non-stationary dynamics in onboard intelligence systems operating in the emergency computing mode (Urgent Computing - UC) is considered. The ontological system of a dynamic knowledge base is formulated on the basis of theoretical models of the modern catastrophe theory (СT). The analysis and forecast of the evolutionary dynamics of a non-stationary object is implemented in a multiprocessor computing environment. Within the framework of the ontological system, an approach to the interpretation of non-stationary dy-namics using fractal geometry and the theory of dynamical systems stability is formulated. The practical application of the developed ontology model is discussed in relation to the interpretation of the interaction of a marine dynamic object (MDO) with the external environment at a given time interval. The dynamic СT model determines the motion of the MDO system to the target attractor and in case of stability loss. Examples of the implementation of the ontological synthesis of non-stationary dynamics in safety systems for navigation and landing of ship-based aircraft are given.
31

Serletis, Apostolos. "INTRODUCTION TO MACROECONOMIC DYNAMICS SPECIAL ISSUE ON COMPLEXITY IN ECONOMIC SYSTEMS." Macroeconomic Dynamics 20, no. 2 (June 17, 2014): 461–65. http://dx.doi.org/10.1017/s1365100514000261.

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In the aftermath of the global financial crisis, questions have been raised regarding the value and applicability of modern macroeconomics. Motivated by these developments and recent advances in dynamical systems theory, the papers in this special issue of Macroeconomic Dynamics deal with specific aspects of the economy as a complex evolving dynamic system.
32

Jaiswal, Abhishek, and Yang Zhang. "Robustness of Dynamical Cluster Analysis in a Glass-Forming Metallic Liquid using an Unsupervised Machine Learning Algorithm." MRS Advances 1, no. 26 (2016): 1929–34. http://dx.doi.org/10.1557/adv.2016.52.

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ABSTRACTWe performed dynamical cluster analysis in a Cu-Zr-Al based glass-forming metallic liquid using an unsupervised machine learning algorithm. The size of the dynamical clusters is used to quantify the onset of cooperative dynamics as the underlying mechanism leading to the Arrhenius dynamic crossover in transport coefficients of the metallic liquid. This technique is useful to directly visualize dynamical clusters and quantify their sizes upon cooling. We demonstrate the robustness of this algorithm by performing sensitivity analysis against two key parameters: number of mobility groups and inconsistency coefficient of the hierarchical cluster tree. The results elucidate the optimized range of values for both of these parameters that capture the underlying physical picture of increasing cooperative dynamics appropriately.
33

Fang, Angbo. "Dynamical effective field model for interacting ferrofluids: II. The proper relaxation time and effects of dynamic correlations." Journal of Physics: Condensed Matter 34, no. 11 (December 31, 2021): 115103. http://dx.doi.org/10.1088/1361-648x/ac4346.

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Abstract The recently proposed dynamical effective field model (DEFM) is quantitatively accurate for ferrofluid dynamics. It is derived in paper I within the framework of dynamical density functional theory (DDFT) along with a phenomenological description of nonadiabatic effects. However, it remains to clarify how the characteristic rotational relaxation time of a dressed particle, denoted by τ r , is quantitatively related to that of a bare particle, denoted by τ r 0 . By building macro-micro connections via two different routes, I reveal that under some gentle assumptions τ r can be identified with the mean time characterizing long-time rotational self-diffusion. I further introduce two simple but useful integrated correlation factors, describing the effects of quasi-static (adiabatic) and dynamic (nonadiabatic) inter-particle correlations, respectively. In terms of both the dynamic magnetic susceptibility is expressed in an illuminating and elegant form. Remarkably, it shows that the macro-micro connection is established via two successive steps: a dynamical coarse-graining with nonadiabatic effects accounted for by the dynamic factor, followed by equilibrium ensemble averaging captured by the static factor. By analyzing data from Brownian dynamics simulations on monodisperse interacting ferrofluids, I find τ r / τ r 0 is, somehow unexpectedly, insensitive to changes of particle volume fraction. A physical picture is proposed to explain it. Furthermore, an empirical formula is proposed to characterize the dependence of τ r / τ r 0 on dipole-dipole interaction strength. The DEFM supplemented with this formula leads to parameter-free predictions in good agreement with results from Brownian dynamics simulations. The theoretical developments presented in this paper may have important consequences to studies of ferrofluid dynamics in particular and other systems modeled by DDFTs in general.
34

Wang, Jianhong, Teik C. Lim, and Liding Yuan. "Spur gear multi-tooth contact dynamics under the influence of bearing elasticity and assembly errors." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 227, no. 11 (February 19, 2013): 2440–55. http://dx.doi.org/10.1177/0954406213477816.

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A numerical model is formulated to analyze the tooth contact dynamic load distribution and dynamic transmission error of a pair of spur gears under the influence of bearing elasticity and gearbox assembly errors. In the proposed model, the deformation of the tooth is computed by applying a combination of finite elements and contact mechanics. The elasticity of the bearings is represented with infinitesimal linear spring elements, while the shafts and gears except the teeth that are in engagement are assumed to be rigid bodies. Applying those assumptions, three sets of highly coupled governing equations representing the meshing teeth flexible behavior, gear-bearing assembly translation dynamics and gear rotation dynamics are derived. The resultant model is then used to predict the dynamical behaviors of the geared rotor system, tooth contact dynamic load, and dynamic transmission error. A set of parametric studies is also performed to analyze the gear dynamic response.
35

Cui, Ling Zhi, Gao Min Li, Yi Ting He, Qin Liao, and Fei Luo. "Status Analysis of the Frozen Soil’s Dynamics Parameter Study." Advanced Materials Research 941-944 (June 2014): 2626–30. http://dx.doi.org/10.4028/www.scientific.net/amr.941-944.2626.

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In this paper, the author points out several key problems needed to be solved about the dynamics of frozen soil by reviewing related literatures about hysteretic curve of frozen soil ,dynamic constitutive relation and dynamical parameter. The problems are the insufficient understanding on morphological characteristics of hysteretic curve and how to transform qualitative understanding into quantitative understanding about morphological characteristics of hysteretic curve. The problem is the rationality of selecting the dynamic constitutive model, namely how to establish the engineering applicable model which conforms to the actual soil mechanics performance.The problem is the rationality of the calculation method about dynamic elastic modulus and damping ratio, namely how to define dynamic modulus of elasticity of frozen soil correctly and the limitation of using the classical method to calculate the damping.
36

Ma, Yi-An, and Hong Qian. "A thermodynamic theory of ecology: Helmholtz theorem for Lotka–Volterra equation, extended conservation law, and stochastic predator–prey dynamics." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 471, no. 2183 (November 2015): 20150456. http://dx.doi.org/10.1098/rspa.2015.0456.

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We carry out mathematical analyses, à la Helmholtz’s and Boltzmann’s 1884 studies of monocyclic Newtonian dynamics, for the Lotka–Volterra (LV) equation exhibiting predator–prey oscillations. In doing so, a novel ‘thermodynamic theory’ of ecology is introduced. An important feature, absent in the classical mechanics, of ecological systems is a natural stochastic population dynamic formulation of which the deterministic equation (e.g. the LV equation studied) is the infinite population limit. Invariant density for the stochastic dynamics plays a central role in the deterministic LV dynamics. We show how the conservation law along a single trajectory extends to incorporate both variations in a model parameter α and in initial conditions: Helmholtz’s theorem establishes a broadly valid conservation law in a class of ecological dynamics. We analyse the relationships among mean ecological activeness θ , quantities characterizing dynamic ranges of populations A and α , and the ecological force F α . The analyses identify an entire orbit as a stationary ecology, and establish the notion of an ‘equation of ecological states’. Studies of the stochastic dynamics with finite populations show the LV equation as the robust, fast cyclic underlying behaviour. The mathematical narrative provides a novel way of capturing long-term dynamical behaviours with an emergent conservative ecology .
37

Roy, Dipanjan, and Lucina Q. Uddin. "Atypical core-periphery brain dynamics in autism." Network Neuroscience 5, no. 2 (2021): 295–321. http://dx.doi.org/10.1162/netn_a_00181.

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Abstract The intrinsic function of the human brain is dynamic, giving rise to numerous behavioral subtypes that fluctuate distinctively at multiple timescales. One of the key dynamical processes that takes place in the brain is the interaction between core-periphery brain regions, which undergoes constant fluctuations associated with developmental time frames. Core-periphery dynamical changes associated with macroscale brain network dynamics span multiple timescales and may lead to atypical behavior and clinical symptoms. For example, recent evidence suggests that brain regions with shorter intrinsic timescales are located at the periphery of brain networks (e.g., sensorimotor hand, face areas) and are implicated in perception and movement. On the contrary, brain regions with longer timescales are core hub regions. These hubs are important for regulating interactions between the brain and the body during self-related cognition and emotion. In this review, we summarize a large body of converging evidence derived from time-resolved fMRI studies in autism to characterize atypical core-periphery brain dynamics and how they relate to core and contextual sensory and cognitive profiles.
38

Kortelainen, Samuli, Antero Kutvonen, and Lauri Lättilä. "Technology Portfolio Dynamics." Journal of Innovation Management 1, no. 2 (December 31, 2013): 125–39. http://dx.doi.org/10.24840/2183-0606_001.002_0009.

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Innovations are significant source of competitive advantage for firms. They are also a major source of dynamics that forces firms to adapt their capabilities to sustain competitiveness. In this study we analyzed how firms manage their technological portfolio in mobile phone industry. Our first finding is that firms have focused differently their technology portfolios. Then we identified that most firms change their technology portfolio over time. And finally we conclude that firms in mobile phone industry have different levels of dynamics where some firms change their technology portfolio faster than others. This research identifies new challenges in dynamic capabilities research related to the appropriate level of dynamics in technology management. This information is crucial in practice in order to correctly manage the firm’s dynamic processes.
39

Huang, Qianwen, Xinping Yan, and Cong Zhang. "Numerical calculation and experimental research on the ship dynamics of the fluid–structure interaction." Advances in Mechanical Engineering 10, no. 7 (July 2018): 168781401878234. http://dx.doi.org/10.1177/1687814018782347.

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Accurate predictive method for ship dynamic is a keynote precondition for structural design and an important consideration for strength evaluation. A wave-ship coupling model focusing on the estimating of ship dynamics is numerically established to solve the fluid–structure interaction. Numerical calculation based on the presented algorithm is carried out, and the dynamical response for both ship and fluid is thus investigated with MATLAB. The dynamical responses including the structural force, deformation, velocity, and energy with different ship mass and stiffness are obtained. Experiment is conducted in the towing tank to investigate the peak frequency and transient amplitude with different wave speeds. It is found that the ship dynamics is closely related to the quality and stiffness of the structure, as well as the wave velocity of the fluid. An appropriate estimating method for ship dynamics is thus proposed through series of discussion on numerical results and experimental data.
40

Biyani, Manish, T. Aoyama, and K. Nishigaki. "1M1330 Solution structure dynamics of single-stranded oligonucleotides : Experiments and molecular dynamics." Seibutsu Butsuri 42, supplement2 (2002): S76. http://dx.doi.org/10.2142/biophys.42.s76_2.

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41

Mureithi, Njuki W. "Karman Wake Dynamics and Vortex Induced Vibration Control : A Nonlinear Dynamics Perspective." Proceedings of the Dynamics & Design Conference 2008 (2008): _B1–1_—_B1–6_. http://dx.doi.org/10.1299/jsmedmc.2008._b1-1_.

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42

HIDAI, MASATAKA, KENJIRO GODA, KATSUYUKI IWASAKI, and TAKAO WATANABE. "1D24 Coupled Simulation of Vehicle Dynamics and Aerodynamics for Train(Vehicles-Dynamics)." Proceedings of International Symposium on Seed-up and Service Technology for Railway and Maglev Systems : STECH 2015 (2015): _1D24–1_—_1D24–6_. http://dx.doi.org/10.1299/jsmestech.2015._1d24-1_.

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43

Schwab, A. L., and J. D. G. Kooijman. "58786 Controllability of a bicycle(Vehicle Dynamics & Control including Tire Dynamics)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _58786–1_—_58786–7_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._58786-1_.

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44

SATOH, Keita, Ryotaro OHKAWA, Hironori A. FUJII, Kenji UCHIYAMA, and Kazuhiro IIJIMA. "63695 STUDY ON FUNDAMENTAL DYNAMICS OF VERY LONG TETHER SYSTEM(Aerospace Dynamics)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _63695–1_—_63695–7_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._63695-1_.

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45

Glushkov, A. V., E. R. Gubanova, O. Yu Khetselius, G. P. Prepelitsa, A. A. Svinarenko, Yu Ya Bunyakova, and V. V. Buyadzhi. "Analysis and forecast of the environmental radioactivity dynamics based on methods of chaos theory: general scheme and some application." Ukrainian hydrometeorological journal, no. 16 (October 29, 2017): 40–45. http://dx.doi.org/10.31481/uhmj.16.2015.05.

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We present firstly a new whole technique of analysis, processing and forecasting environmental radioactivity dynamics, which has been earlier developed for the atmospheric pollution dynamics analysis and investigation of chaotic feature sin dynamics of the typical hydroecological systems. The general formalism include: a) A general qualitative analysis of dynamical problem of the environmental radioactivity dynamics (including a qualitative analysis from the viewpoint of ordinary differential equations, the “Arnold-analysis”); b) checking for the presence of a chaotic (stochastic) features and regimes (the Gottwald-Melbourne’s test; the method of correlation dimension); c) Reducing the phase space (choice of the time delay, the definition of the embedding space by methods of correlation dimension algorithm and false nearest neighbor points); d) Determination of the dynamic invariants of a chaotic system (Computation of the global Lyapunov dimension λa; determination of the Kaplan-York dimension dL and average limits of predictability Prmax on the basis of the advanced algorithms; e) A non-linear prediction (forecasting) of an dynamical evolution of the system. The last block indeed includes new (in a theory of environmental radioactivity dynamics) methods and algorithms of nonlinear prediction such as methods of predicted trajectories, stochastic propagators and neural networks modelling, renorm-analysis with blocks of the polynomial approximations, wavelet-expansions etc.
46

Cilione, Pier Alberto Porceddu. "La Potenza della Musica: La Questione della Dynamis tra Musica e Filosofia." Philosophy of Music 74, no. 4 (December 30, 2018): 957–82. http://dx.doi.org/10.17990/rpf/2018_74_4_0957.

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This article examines the conceptual relationship between the notion of dynamics in music and the idea of ​​dynamics as “power” and “potentiality” in metaphysics. What is implicit in both notions is the idea of “force”, as configured in a philosophical tradition from Aristotle to Nietzsche, Heidegger and Deleuze. It is no coincidence that the system of signs that, in music, indicates the intensity of sound, its strength and its expression, takes its name from this philosophical concept. What follows tries to understand in which sense the term dynamics, as a theory of force and potentiality, steps into the field of music. The Aristotelian concept of dynamis, Leibniz’s theory of vis activa and the Nietzschean “Will to Power” reveal their profound meaning when related to the specific dynamic ontology realized by music. Two contemporary musical examples, taken from flute works by Sciarrino and Hosokawa, show with particular evidence how to understand a metaphysical idea of ​​musical dynamics.
47

LIU, YUBIN, and GANGFENG LIU. "RESEARCH ON RIGID BODY INVERSE DYNAMICS OF A NOVEL 6-PRRS PARALLEL ROBOT." Journal of Mechanics in Medicine and Biology 18, no. 08 (December 2018): 1840037. http://dx.doi.org/10.1142/s0219519418400377.

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A systematic methodology for solving the inverse dynamics of a 6-PRRS parallel robot is presented. Based on the principle of virtual work and the Lagrange approach, a methodology for deriving the dynamical equations of motion is developed. To resolve the inconsistency between complications of established dynamic model and real-time control, a simplifying strategy of the dynamic model is presented. The dynamic character of the 6-PRRS parallel robot is analyzed by example calculation, and a full and precise dynamic model using simulation software is established. Verification results show the validity of the presented algorithm, and the simplifying strategies are practical and efficient.
48

WANG, L., J. B. ZHANG, H. P. YING, and D. R. JI. "SHORT-TIME CRITICAL DYNAMICS OF MULTISPIN INTERACTION ISING MODEL IN TWO DIMENSIONS." Modern Physics Letters B 13, no. 28 (December 10, 1999): 1011–18. http://dx.doi.org/10.1142/s021798499900124x.

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We investigated the short-time dynamics of a multispin model in two dimensions. A dynamical Monte Carlo simulation which avoids the critical slowing down is performed at critical temperature and the short-time dynamic scaling behavior is found. By using the universal power-law scaling features, the critical exponents θ, z and 2β/ν are estimated in our calculations.
49

Mamatov, Mashrabjon, and Xakimjon Alimov. "Mathematical Modeling and Functional Order Pursuits with Separated Dynamics." Journal of Physics: Conference Series 2068, no. 1 (October 1, 2021): 012002. http://dx.doi.org/10.1088/1742-6596/2068/1/012002.

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Abstract This work is devoted to the study of the pursuit problem in controlled systems described by a fractional-order equation with divided dynamics. For fixed player controls, representations of solutions are established in the form of analogs of the Cauchy formula using generalized matrix functions. Sufficient conditions are obtained for the possibility of completing the pursuit. Specific types of fractional differential equations and models of fractional dynamical systems are considered. The qualitative dynamics, issues of stability and controllability of such systems are discussed. Considered, try which, the motion of the equation is described with irrational orders. Problems of the type under study are encountered in modeling the processes of economic growth and in problems of stabilizing dynamic systems.
50

Xiong, Qiao, and Han Bin Xiao. "Inverse Kinematics and Dynamics Simulation of a Dredging Clamshell." Applied Mechanics and Materials 364 (August 2013): 107–11. http://dx.doi.org/10.4028/www.scientific.net/amm.364.107.

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This paper proposes a problem of flat dredging because of the phenomenon of overdredging casuing bottom roughness in dredging engineering and presents the formulation of the inverse kinematics and dynamics simulation of a dredging clamshell. A dynamical model of dredging clamshell is built based on Adams and the position analysis is firstly performed by adding a general point motion to the dredging clamshell. By analyzing and solving kinematics equations in inverse, movement curves of the steel wire ropes are obtained, and the pulling force curves are acquired by dynamics simulation. The results show that the method automatically generates inverse dynamic solutions and the movement curves are intuitive and can offer help to the flat dredging control scheme effectively.

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