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Journal articles on the topic 'Simulation of dynamic systems'

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1

Alzbutas, R., and V. Janilionis. "THE SIMULATION OF DYNAMIC SYSTEMS USING COMBINED MODELLING." Mathematical Modelling and Analysis 5, no. 1 (2000): 7–17. http://dx.doi.org/10.3846/13926292.2000.9637123.

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The new approach to the problems of dynamic systems simulation is proposed. The analytical and imitation modelling of non‐linear complex dynamic systems which comprise simulation of continuous and discrete processes with constant and variable parameters, are investigated. The aggregate mathematical modelling scheme [1] and the method of control sequences for discrete systems specification and simulation are used as well as the dynamic mathematical modelling scheme for continuous process formalization and modelling. According to them the investigated systems are presented as the set of interact
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2

Rükgauer, A., and W. Schiehlen. "Simulation of modular dynamic systems." Mathematics and Computers in Simulation 46, no. 5-6 (1998): 535–42. http://dx.doi.org/10.1016/s0378-4754(98)00082-2.

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3

Toby, Sidney, and Frina S. Toby. "The Simulation of Dynamic Systems." Journal of Chemical Education 76, no. 11 (1999): 1584. http://dx.doi.org/10.1021/ed076p1584.

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4

Alzbutas, Robertas, and Vytautas Janilionis. "Dynamic systems simulation using APL2." ACM SIGAPL APL Quote Quad 29, no. 2 (1998): 20–25. http://dx.doi.org/10.1145/379277.312699.

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5

Nishitani, Hirokazu, Eiichi Kunugita, Yuan-Chen Wan, and Masahiro Kujime. "Dynamic simulation of large systems." KAGAKU KOGAKU RONBUNSHU 17, no. 1 (1991): 149–56. http://dx.doi.org/10.1252/kakoronbunshu.17.149.

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6

Skelton, Robert E., Fa Ming Li, and Mauricio de Oliveira. "Optimal Simulation for Large Dynamic Systems." Advances in Science and Technology 56 (September 2008): 147–53. http://dx.doi.org/10.4028/www.scientific.net/ast.56.147.

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Like most engineering design problems, simulation design for large dynamic systems should seek a trade- o® between performance and cost. Here the perfor- mance is de¯ned by simulation accuracy; and the cost is related to computational resource, measured by the total wordlength. The simulation accuracy depends on model complexity, model realization and computational implementation. The optimal simula- tion problem is to determine all these factors to en- sure desired accuracy with available computational resource. When computational cost is the primary concern, one can minimize the computationa
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7

Bhatti, Muhammad Akram, Li Chang Xi ., and Ye lin . "Modeling and Simulation of Dynamic Systems." Journal of Applied Sciences 6, no. 4 (2006): 950–54. http://dx.doi.org/10.3923/jas.2006.950.954.

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8

Deckmann, S. M., V. F. da Costa, and D. A. Alves. "Dynamic Simulation for Interconnected Power Systems." IFAC Proceedings Volumes 18, no. 7 (1985): 261–68. http://dx.doi.org/10.1016/s1474-6670(17)60444-0.

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9

Lubachevsky, Boris D. "Fast simulation of multicomponent dynamic systems." Bell Labs Technical Journal 5, no. 2 (2002): 134–56. http://dx.doi.org/10.1002/bltj.2227.

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10

Rosenberg, Ronald C., Joseph Whitesell, and John Reid. "Extendible simulation software for dynamic systems." SIMULATION 58, no. 3 (1992): 175–83. http://dx.doi.org/10.1177/003754979205800307.

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11

Drab, C. B., H. W. Engl, J. R. Haslinger, G. Offner, R. U. Pfau, and W. Zulehner. "Dynamic simulation of crankshaft multibody systems." Multibody System Dynamics 22, no. 2 (2009): 133–44. http://dx.doi.org/10.1007/s11044-009-9152-8.

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12

Wu, S. Z., D. N. Wormley, D. Rowell, and H. M. Paynter. "Dynamic Modeling and Simulation of Gaseous Systems." Journal of Dynamic Systems, Measurement, and Control 107, no. 4 (1985): 262–66. http://dx.doi.org/10.1115/1.3140733.

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A general computer-based mathematical modeling system for analyzing air/gas system dynamics has been developed. A set of generic lumped and distributed elements are interconnected by generalized junction structures to represent system configurations. The dynamic response of pressure, flow, temperature, and heat transfer rate at any point in a system, due to control actions, or fluid, thermal, or mechanical disturbances can be determined. The model has been used to analyze furnace implosion and disturbance propagation problems in fossil fuel power plants. To illustrate the modeling techniques,
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13

Jin, Yong Fu. "Simulation Research on Dynamic Tribological Systems of Plain Bearing." Advanced Materials Research 426 (January 2012): 297–302. http://dx.doi.org/10.4028/www.scientific.net/amr.426.297.

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The research method of the inner friction and wear characteristics of plain bearing which is mainly conducted currently, is to analyze the all factors that affect the friction and wear of plain bearing from the perspective of wear, and to build friction and wear model, and then to conduct the research on the model. The article establishes the friction and wear dynamics model on base of the tribological systems approach, and on the base of analyzing the internal friction system and inner process of Tribology system of plain bearing. The article conducts the research on the friction and wear cha
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14

Dinkelbach, Jan, Ghassen Nakti, Markus Mirz, and Antonello Monti. "Simulation of Low Inertia Power Systems Based on Shifted Frequency Analysis." Energies 14, no. 7 (2021): 1860. http://dx.doi.org/10.3390/en14071860.

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New types of power system transients with lower time constants are emerging due to the replacement of synchronous generation with converter interfaced generation and are challenging the modeling approaches conventionally applied in power system simulation. Quasi-stationary simulations are based on classical phasor models, whereas EMT simulations calculate the instantaneous values of models in the time domain. In addition to these conventional modeling approaches, this paper investigates simulation based on dynamic phasor models, as has been proposed by the Shifted Frequency Analysis. The simul
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15

Vanhooren, H., Z. Yuan, and P. A. Vanrolleghem. "Benchmarking nitrogen removal suspended-carrier biofilm systems using dynamic simulation." Water Science and Technology 46, no. 1-2 (2002): 327–32. http://dx.doi.org/10.2166/wst.2002.0497.

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We are witnessing an enormous growth in biological nitrogen removal from wastewater. It presents specific challenges beyond traditional COD (carbon) removal. A possibility for optimised process design is the use of biomass-supporting media. In this paper, attached growth processes (AGP) are evaluated using dynamic simulations. The advantages of these systems that were qualitatively described elsewhere, are validated quantitatively based on a simulation benchmark for activated sludge treatment systems. This simulation benchmark is extended with a biofilm model that allows for fast and accurate
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16

Peasgood, Mike, Eric Kubica, and John McPhee. "Stabilization of a Dynamic Walking Gait Simulation." Journal of Computational and Nonlinear Dynamics 2, no. 1 (2006): 65–72. http://dx.doi.org/10.1115/1.2389230.

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Forward dynamic simulations of human walking gait have typically simulated and analyzed a single step of the walking cycle, assuming symmetric and periodic gait. To enable simulations over many steps, a stabilizer is required to maintain the balance of the walking model, ideally mimicking the human balance control mechanism. This paper presents a feedback control system that stabilizes the torso orientation during a human walking gait dynamic simulation, enabling arbitrarily long simulations. The model is a two-dimensional mechanical simulation, in which the desired joint trajectories are defi
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17

Manzano, Wallace, Valdemar Vicente Graciano Neto, and Elisa Yumi Nakagawa. "Dynamic-SoS: An Approach for the Simulation of Systems-of-Systems Dynamic Architectures." Computer Journal 63, no. 5 (2019): 709–31. http://dx.doi.org/10.1093/comjnl/bxz028.

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Abstract Systems-of-Systems (SoS) combine heterogeneous, independent systems to offer complex functionalities for highly dynamic smart applications. Besides their dynamic architecture with continuous changes at runtime, SoS should be reliable and work without interrupting their operation and with no failures that could cause accidents or losses. SoS architectural design should facilitate the prediction of the impact of architectural changes and potential failures due to SoS behavior. However, existing approaches do not support such evaluation. Hence, these systems have been usually built witho
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18

Djitog, Ignace, Hamzat Olanrewaju Aliyu, and Mamadou Kaba Traoré. "Multi-Perspective Modeling of Healthcare Systems." International Journal of Privacy and Health Information Management 5, no. 2 (2017): 1–20. http://dx.doi.org/10.4018/ijphim.2017070101.

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This paper presents a multi-perspective approach to Modeling and Simulation (M&S) of Healthcare Systems (HS) such that different perspectives are defined and integrated together. The interactions between the isolated perspectives are done through dynamic update of models output-to-parameter integration during concurrent simulations. Most often, simulation-based studies of HS in the literature focus on specific problem like allocation of resources, disease propagation, and population dynamics that are studied with constant parameters from their respective experimental frames throughout the
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19

Ranky, Paul G. "Dynamic Simulation of Flexible Manufacturing Systems (FMS)." Applied Mechanics Reviews 39, no. 9 (1986): 1339–44. http://dx.doi.org/10.1115/1.3149523.

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The simulation method to be used in FMS should be multilevel and dynamic and should incorporate solid modeling techniques. This means that operation control simulation in FMS should rely on information sources provided from different levels of the organization; thus there should be an overall planning level and a dynamic, or real-time, level. One should also conclude from this article that, without understanding the design principles and operating rules of FMS, the simulation model created will be inadequate and in most cases misleading. Because of this, FMS simulation should be performed by a
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20

Yuan, Qiong. "Efficient Simulation for Dynamic Systems with Discontinuities." Advanced Materials Research 989-994 (July 2014): 2515–18. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2515.

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In many techneques for handling discontinuities, the presence of a discontinuity is detected by a change of sign in the value of a discontinuity function. This paper discusses the problems caused by this sign rule of detecting discontinuities for some engineering applications, and describes an alternative which uses a change of the state marker value .The modified program with Runge-Kutta-Merson and Gear integration subroutines have been successfully applied to the simulation for mechanical, electrical and other dynamic systems with discontinuities for which the original program is inefficient
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21

Shevtsov, Alexandr Nikolayevich. "SOME QUESTIONS SIMULATION OF INTERACTIVE DYNAMIC SYSTEMS." Theoretical & Applied Science 9, no. 01 (2014): 5–22. http://dx.doi.org/10.15863/tas.2014.01.9.2.

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22

Pan, W., and E. J. Haug. "Dynamic Simulation of General Flexible Multibody Systems∗." Mechanics of Structures and Machines 27, no. 2 (1999): 217–51. http://dx.doi.org/10.1080/08905459908915697.

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23

Paiva, H. M., and R. K. H. Galvao. "Simulation of Dynamic Systems With Output Saturation." IEEE Transactions on Education 47, no. 3 (2004): 385–88. http://dx.doi.org/10.1109/te.2004.825533.

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24

Sacks, Elisha. "A dynamic systems perspective on qualitative simulation." Artificial Intelligence 42, no. 2-3 (1990): 349–62. http://dx.doi.org/10.1016/0004-3702(90)90058-8.

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25

Leonov, A. S. "Optimal simulation of nonlinear deterministic dynamic systems." Computational Mathematics and Modeling 7, no. 3 (1996): 333–37. http://dx.doi.org/10.1007/bf01128165.

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26

Dalle Molle, D. T., B. J. Kuipers, and T. F. Edgar. "Qualitative modeling and simulation of dynamic systems." Computers & Chemical Engineering 12, no. 9-10 (1988): 853–66. http://dx.doi.org/10.1016/0098-1354(88)87013-3.

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27

Mollazadeh, Shirin, Amirhossein Sahebkar, Mohsen Shahlaei, and Sajad Moradi. "Nano drug delivery systems: Molecular dynamic simulation." Journal of Molecular Liquids 332 (June 2021): 115823. http://dx.doi.org/10.1016/j.molliq.2021.115823.

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28

Toyama, Shigeki, and Yasuo Murakuki. "Dynamic Autonomous Car Mobile Analysis Simulating Mechanical Systems Analysis – First Dynamic Characteristics of Running Mouse –." Journal of Robotics and Mechatronics 10, no. 6 (1998): 488–93. http://dx.doi.org/10.20965/jrm.1998.p0488.

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This paper dynamically simulates a small running 2DW2C automobile (mouse) and simulates path tracking control. Our purpose was to optimize mouse design using simulation results. We added tire force and DC motor force to A1 Motion, a simulator for analyzing mechanical systems developed in our laboratory, and improved the simulator simulating a running automobile. Experiments with a small 2DW2C automobile compared experimental and simulation results involving dynamic characteristics of an actual mouse. We got correct simulation results using this model and simulator. We studied its running perfo
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29

Yoon, Sugjoon, and Hyounjoo Kang. "Dynamic-window search for real-time simulation of dynamic systems." Communications in Numerical Methods in Engineering 19, no. 11 (2003): 877–86. http://dx.doi.org/10.1002/cnm.637.

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30

Park, Gwangmin, Seonghun Lee, Sung Ho Jin, and Sangshin Kwak. "Modeling and Analysis for Powertrain Dynamics of Electric Vehicle Systems." Applied Mechanics and Materials 110-116 (October 2011): 2426–31. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.2426.

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This paper provides presents the dynamic analysis and computer simulation results of electric vehicle (EV) powertrain performance systems. The generic simulation platform of an electric vehicle is developed using based on the SimPowerSystems/SimDriveline of MATLAB. Individual components of the model are constructed based on real vehicle data and mathematical dynamic model equations. The analytic results obtained from the mathematical modeling are verified with electric vehicle dynamics using generic simulation platform.
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31

Balakrishna, Ramachandran, Haris N. Koutsopoulos, Moshe Ben-Akiva, Bruno M. Fernandez Ruiz, and Manish Mehta. "Simulation-Based Evaluation of Advanced Traveler Information Systems." Transportation Research Record: Journal of the Transportation Research Board 1910, no. 1 (2005): 90–98. http://dx.doi.org/10.1177/0361198105191000111.

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Traveler information has the potential to reduce travel times and improve their reliability. Studies have verified that driver overreaction from the dissemination of information can be eliminated through prediction-based route guidance that uses short-term forecasts of network state. Critical off-line tests of advanced dynamic traffic assignment–based prediction systems have been limited, since the system being evaluated has also been used as the test bed. This paper outlines a detailed simulation-based laboratory for the objective and independent evaluation of advanced traveler information sy
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32

Felez, J., C. Vera, I. San Jose, and R. Cacho. "BONDYN: A Bond Graph Based Simulation Program for Multibody Systems." Journal of Dynamic Systems, Measurement, and Control 112, no. 4 (1990): 717–27. http://dx.doi.org/10.1115/1.2896200.

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This paper presents the BONDYN program (BONd graph DYNamics) as a procedure for simulating dynamic systems. It is based on bond graph theory and provides a means for treating dynamic systems that simultaneously include various physical domains. The program makes use of the bond graph module handling facility in order to build a general model starting from simple submodels. Although the latter can be defined by the user, a library has been appended to the preprocessor which includes some of these submodels. Special developments for simulating multibody systems can be found among them. Once the
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33

Schindlerová, Vladimíra, Ivana Šajdlerová, and Dominika Lehocká. "Dynamic simulation for optimisation solution of manufacturing processes." MATEC Web of Conferences 244 (2018): 01010. http://dx.doi.org/10.1051/matecconf/201824401010.

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One way how to study the real behaviour of industrial processes or systems in practice is to use computer simulations. We can simulate different conditions and find optimal parameters without increased risk. The right application of these parameters in practice can produce the desired results. The advantage is not only the safe verification of various variants of the simulated parameters, but also the possibility of their use in different areas of industrial practice. This article deals with an example of the use of simulation in the production of the selected automobile cooling system compone
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34

Tian, Fu Yang, Yu Dao Li, Zhen Wang, and Fa De Li. "Efficient Recursive Dynamics and Real Time Simulation of Flexible Space Robots System." Advanced Materials Research 842 (November 2013): 546–52. http://dx.doi.org/10.4028/www.scientific.net/amr.842.546.

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As space robots gain more and more importance in space operations, it was becoming imperative to understand their distinctive dynamics. The dynamics model of the space flexible robots is very complex, and the differential equation derived from dynamics was solved difficultly and slowly. In this paper the efficient recursive O(n) dynamics algorithm of space flexible robots systems with rigid base and flexible manipulators was discussed, and the fast efficient integration method was used to solve this dynamics equation for real time simulation. Simulations results show that the dynamic modeling
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35

Richard, M. J. "Dynamic Simulation of Multibody Mechanical Systems Using the Vector-Network Model." Transactions of the Canadian Society for Mechanical Engineering 12, no. 1 (1988): 21–30. http://dx.doi.org/10.1139/tcsme-1988-0004.

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Pressing technological problems have created a growing interest in the development of dynamic models for the digital simulation of multibody systems. This paper describes a new approach to the problem of motion prediction. An extension of the “vector-network” method to rigid body systems in three-dimensional space is introduced. The entire procedure is a basic application of concepts of graph theory in which laws of vector dynamics are combined. The analytical procedure was successfully implemented within a general-purpose digital simulation program since, from a minimal definition of the mech
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36

BUTLER, ALUN, MOH IBRAHIM, KEITH RENNOLLS, and LIZ BACON. "Composing simulation architectures for autonomic systems." Knowledge Engineering Review 21, no. 3 (2006): 249–59. http://dx.doi.org/10.1017/s0269888906000919.

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Simulation has long played a part in testing new configurations and new functionality in a diverse range of software. Through such simulations, the boundaries of the system state are explored and the relationship of that state to other applications tested — sometimes to destruction. A critical differentiator between a simulation and a live, deployed application is that simulations are allowed to fail. As truly autonomous applications evolve, this capacity for simulation must be built in from the ground up or the benefits of experience — including the ability to tolerate failure — will be lost.
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37

Mills, J. K., and C. V. Nguyen. "Robotic Manipulator Collisions: Modeling and Simulation." Journal of Dynamic Systems, Measurement, and Control 114, no. 4 (1992): 650–59. http://dx.doi.org/10.1115/1.2897737.

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In this paper, a new formulation of the dynamics of a robotic manipulator work environment is presented. The work environment is modeled in a way that permits the robot transition to and from contact with the work environment to be effectively simulated. This method circumvents the discontinuities inherent in previously proposed models of work environment dynamic models that have, until now, prevented researchers from considering that phase of manipulation. Combined with an existing model of the manipulator dynamics, the overall model of the manipulator-work environment system is such that the
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38

Karnopp, Dean. "Computer Simulation of Stick-Slip Friction in Mechanical Dynamic Systems." Journal of Dynamic Systems, Measurement, and Control 107, no. 1 (1985): 100–103. http://dx.doi.org/10.1115/1.3140698.

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Stick-slip friction is present to some degree in almost all actuators and mechanisms and is often responsible for performance limitations. Simulation of stick-slip friction is difficult because of strongly nonlinear behavior in the vicinity of zero velocity. A straightforward method for representing and simulating friction effects is presented. True zero velocity sticking is represented without equation reformulation or the introduction of numerical stiffness problems.
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39

Smith, Jeremy C., Pan Tan, Loukas Petridis, and Liang Hong. "Dynamic Neutron Scattering by Biological Systems." Annual Review of Biophysics 47, no. 1 (2018): 335–54. http://dx.doi.org/10.1146/annurev-biophys-070317-033358.

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Dynamic neutron scattering directly probes motions in biological systems on femtosecond to microsecond timescales. When combined with molecular dynamics simulation and normal mode analysis, detailed descriptions of the forms and frequencies of motions can be derived. We examine vibrations in proteins, the temperature dependence of protein motions, and concepts describing the rich variety of motions detectable using neutrons in biological systems at physiological temperatures. New techniques for deriving information on collective motions using coherent scattering are also reviewed.
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40

Xu, Zhenlong, Michael Accorsi, and John Leonard. "Simulation of Dynamic Contact Problems in Parachute Systems." Journal of Aerospace Computing, Information, and Communication 1, no. 7 (2004): 288–307. http://dx.doi.org/10.2514/1.7787.

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41

Regan, Amelia C., Hani S. Mahmassani, and Patrick Jaillet. "Evaluation of Dynamic Fleet Management Systems: Simulation Framework." Transportation Research Record: Journal of the Transportation Research Board 1645, no. 1 (1998): 176–84. http://dx.doi.org/10.3141/1645-22.

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The problem of dynamic fleet management for truckload carrier fleet operations is introduced, and the principal elements of a simulation framework for the evaluation of dynamic fleet management systems are described. The application of the simulated framework to the investigation of the performance of a family of real-time fleet operational strategies, which include load acceptance, assignment, and reassignment strategies, also is described. The simulation framework described is an example of a first-generation tool for the evaluation of dynamic fleet management systems. Selected experimental
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42

Yang, Qi, Haris N. Koutsopoulos, and Moshe E. Ben-Akiva. "Simulation Laboratory for Evaluating Dynamic Traffic Management Systems." Transportation Research Record: Journal of the Transportation Research Board 1710, no. 1 (2000): 122–30. http://dx.doi.org/10.3141/1710-14.

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Advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS) are promising technologies for achieving efficiency in the operation of transportation systems. A simulation-based laboratory environment, MITSIMLab, is presented that is designed for testing and evaluation of dynamic traffic management systems. The core of MITSIMLab is a microscopic traffic simulator (MITSIM) and a traffic management simulator (TMS). MITSIM represents traffic flows in the network, and the TMS represents the traffic management system under evaluation. An important feature of MITSIMLab i
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43

Polack, Fiona, and Kieran Alden. "On Developing and Validating Dynamic Systems: Simulation Engineering." Journal of Object Technology 19, no. 3 (2020): 3:1. http://dx.doi.org/10.5381/jot.2020.19.3.a6.

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44

Lee, Chun-Woo, Ju-Hee Lee, Bong-Jin Cha, Hyun-Young Kim, and Ji-Hoon Lee. "Physical modeling for underwater flexible systems dynamic simulation." Ocean Engineering 32, no. 3-4 (2005): 331–47. http://dx.doi.org/10.1016/j.oceaneng.2004.08.007.

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45

Ding, Shuiting, Tian Qiu, Xiaofeng Liu, and Shuguang Zhang. "Dynamic Coupled Systems FHA: A Simulation-aided Approach." Procedia Engineering 80 (2014): 479–93. http://dx.doi.org/10.1016/j.proeng.2014.09.106.

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46

Schülke, L., and B. Zheng. "Monte Carlo simulation of critical dynamic spin systems." Nuclear Physics B - Proceedings Supplements 53, no. 1-3 (1997): 712–14. http://dx.doi.org/10.1016/s0920-5632(96)00762-1.

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47

Lu, S. "Dynamic modelling and simulation of power plant systems." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 213, no. 1 (1999): 7–22. http://dx.doi.org/10.1243/0957650991537392.

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48

Ben-Akiva, Moshe E., Haris N. Koutsopoulos, Rabi G. Mishalani, and Qi Yang. "Simulation Laboratory for Evaluating Dynamic Traffic Management Systems." Journal of Transportation Engineering 123, no. 4 (1997): 283–89. http://dx.doi.org/10.1061/(asce)0733-947x(1997)123:4(283).

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49

Wilke, David, and Carsten Obenaus. "Design of Pneumatic Brake Systems by Dynamic Simulation." ATZ worldwide eMagazine 113, no. 5 (2011): 24–29. http://dx.doi.org/10.1365/s38311-011-0052-1.

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50

Mankala, Kalyan K., and Sunil K. Agrawal. "Dynamic Modeling and Simulation of Satellite Tethered Systems." Journal of Vibration and Acoustics 127, no. 2 (2004): 144–56. http://dx.doi.org/10.1115/1.1891811.

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The objective of this paper is to study the dynamic simulation of a tether as it is deployed or retrieved by a winch on a satellite orbiting around earth. In an effort to understand the problem incrementally, the following three models were developed: (a) Model 1: A tether with constant length moves on earth in the plane of constant gravity; (b) Model 2: A tether is deployed from a drum on earth in the plane of constant gravity, i.e., length of the cable changes during deployment; (c) Model 3: A tether is deployed from a drum on an orbiting satellite. These models have been chosen to bring dif
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