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Journal articles on the topic 'Simulation and Modelling'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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1

Troy, Amy-Jane, and Joe Bogue. "Simulation modelling." British Food Journal 117, no. 2 (February 2, 2015): 943–62. http://dx.doi.org/10.1108/bfj-12-2013-0363.

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Purpose – The purpose of this paper is to utilise market-oriented methodologies and simulation analysis to generate information regarding consumers’ attitudes, opinions and preferences towards novel β-glucan-enriched breads. Design/methodology/approach – Focus Groups and In-depth interviews were used to generate consumer information on potentially suitable attributes that would maximise consumer acceptance. The approach involved the creation of a set of realistic product concepts from a combination of attribute levels and the presentation of these product concepts to consumers. A fractional factorial design generated an orthogonal array of 22 hypothetical products that were presented to consumers for rating while K-means cluster analysis was used to segment consumers into four specific consumer segments. The simulation analysis then identified β-glucan-enriched bread concepts targeted specifically at these four market segments. Findings – The simulation analysis identified β-glucan-enriched bread concepts targeted specifically at these four market segments. Originality/value – This research can assist manufacturers who wish to optimally design foods with novel ingredients and aid in the development of product concepts which maximise consumer acceptance and increase the likelihood of product success.

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2

Taylor, Simon J. E., and Stewart Robinson. "Simulation Modelling." OR Insight 14, no. 4 (October 2001): 2. http://dx.doi.org/10.1057/ori.2001.13.

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3

Szántó, András, and Sándor Hajdu. "Vehicle Modelling and Simulation in Simulink." International Journal of Engineering and Management Sciences 4, no. 1 (March 3, 2019): 260–65. http://dx.doi.org/10.21791/ijems.2019.1.33.

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In this paper a vehicle dynamics model is presented, which is an example that contains all the necessary aspects of making a decent vehicle model. Several examples show the use of such a model: basic vehicle dynamics phenomena can be recognized with the simulation of a detailed vehicle model. We are dealing with the connection between downforce and under/oversteer in this paper. In addition, the use of numerical simulations in the field of control systems is pointed out by an example of simulating an ABS control for the vehicle.

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4

Vasileva, Svetlana, and Aleksandar Milev. "Simulation Studies of Distributed Two-phase Locking in Distributed Database Management Systems." Information Technologies and Control 13, no. 1-2 (June 1, 2015): 46–55. http://dx.doi.org/10.1515/itc-2016-0010.

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Abstract This paper considers algorithms simulating the implementation of distributed two-phase locking (2PL) protocols in distributed database systems and simulation results. It describes specifically the simulations of two-version 2PL and 2PL with integrated timestamp ordering mechanism. Integrated modelling algorithms for deadlock avoiding are suggested in the paper: twoversion architecture of database and timestamp ordering strategy “wait-die”. The results of the simulations of these two variants of the 2PL method at different scales of the networks for data transmission and at different intensities of inflow transactions are also presented. Modelling algorithms are developed by means of the system for simulation modelling GPSS World Personal Version.

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5

Gohil, Mehul D., Praful G. Patil, and U. V. Shah U.V. Shah. "Modelling and Simulation of Parallel Motion Fender." International Journal of Scientific Research 2, no. 5 (June 1, 2012): 263–64. http://dx.doi.org/10.15373/22778179/may2013/87.

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6

HAGEN, HANS, SIEGFRIED HEINZ, MICHAEL THESING, and THOMAS SCHREIBER. "SIMULATION BASED MODELLING." International Journal of Shape Modeling 04, no. 03n04 (September 1998): 143–64. http://dx.doi.org/10.1142/s0218654398000118.

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7

Kompare, Boris. "Modelling and simulation." Ecological Modelling 98, no. 2-3 (May 1997): 245–47. http://dx.doi.org/10.1016/s0304-3800(96)01916-3.

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8

Catlow, C. R. A. "Modelling and simulation." Current Opinion in Solid State and Materials Science 7, no. 1 (February 2003): 1–2. http://dx.doi.org/10.1016/s1359-0286(03)00030-5.

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9

Blundell, M. V. "The modelling and simulation of vehicle handling Part 3: Tyre modelling." Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics 214, no. 1 (March 1, 2000): 1–32. http://dx.doi.org/10.1243/1464419001544115.

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This is the third in a series of four papers (Parts 1 to 4) looking at the application of computer-based analysis methods to model vehicles and simulate vehicle handling. The material contained in these papers is based on a study carried out in order to investigate the influence of suspension and tyre modelling on the outputs predicted by vehicle handling simulations. The papers deal with analysis methods, vehicle modelling (both in the previous Issue), tyre modelling and handling simulation. In this paper an overview of the use of tyre models in vehicle dynamics is provided. This is followed by a more detailed description of three tyre modelling approaches that can be used for handling simulations. A description is also provided of a computer-based modelling system where FORTRAN routines represent the various models and a computer model of a tyre test rig is used to interrogate the models and data before integrating these into a full vehicle handling simulation. The use of this system to compare the accuracy of the tyre models under consideration is also presented. The examples used to illustrate the concepts explained throughout this series of papers have been generated using the ADAMS (Automatic Dynamic Analysis of Mechanical Systems) program.

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10

Marcelino, Maria. "HME: a Handheld Model Editor for Educational Contexts." JUCS - Journal of Universal Computer Science 13, no. (7) (July 28, 2007): 1012–21. https://doi.org/10.3217/jucs-013-07-1012.

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Handheld devices are becoming more and more popular in education. Educational simulation and modelling are not new soil, but for handhelds they are still much under explored. Due to the difficulties teachers usually face in developing computer models and simulations and the lack of adequate tools for building them, we developed an authoring-tool for handheld educational simulation and modelling, called Sim-H (SIMulation for Handhelds). Sim-H is made by several modules each one relating to a type of simulation application that can be used in an educational context. One of these modules, that we describe thoroughly herein, is the Handheld Model Editor, a modelling tool for handheld devices that can be used to build models to use as such or as the core of educational handheld simulations.

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11

Haigh, John, and Hamdy A. Taha. "Simulation Modelling and SIMNET." Mathematical Gazette 73, no. 463 (March 1989): 62. http://dx.doi.org/10.2307/3618231.

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12

Paul, Ray J., and Francis Neelamkavil. "Computer Simulation and Modelling." Journal of the Operational Research Society 38, no. 11 (November 1987): 1092. http://dx.doi.org/10.2307/2582236.

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13

Žagar, Dušan. "Ecohydraulics Modelling and Simulation." Water 13, no. 16 (August 8, 2021): 2172. http://dx.doi.org/10.3390/w13162172.

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Ecohydraulics, the interdiscipline of ecology and hydraulics, has been rapidly developing and receiving ever-growing attention both in hydraulic research efforts and in environmentally oriented professional and lay communities in recent years [...]

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14

Masic, Zlatan, Konny Lajhner, and Haris Pandza. "Computer Modelling and Simulation." International Journal on Biomedicine and Healthcare 9, no. 3 (2021): 173. http://dx.doi.org/10.5455/ijbh.2021.9.173-182.

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15

Dave, U., and L. Oakshott. "Business Modelling and Simulation." Journal of the Operational Research Society 49, no. 2 (February 1998): 180. http://dx.doi.org/10.2307/3009986.

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16

Paul, Ray J. "Computer Simulation and Modelling." Journal of the Operational Research Society 38, no. 11 (November 1987): 1092–93. http://dx.doi.org/10.1057/jors.1987.181.

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17

DePriest, Douglas J. "Computer Simulation and Modelling." Technometrics 30, no. 4 (November 1988): 463–64. http://dx.doi.org/10.1080/00401706.1988.10488458.

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18

J. Schriber, Thomas. "Business modelling and simulation." Simulation Practice and Theory 5, no. 6 (August 1997): p30. http://dx.doi.org/10.1016/s0928-4869(97)84255-3.

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19

Raffo, David, and Paul Wernick. "Software Process Simulation Modelling." Journal of Systems and Software 59, no. 3 (December 2001): 223–25. http://dx.doi.org/10.1016/s0164-1212(01)00063-2.

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20

Gani, J. "Epidemic modelling and simulation." Mathematics and Computers in Simulation 32, no. 1-2 (April 1990): 3–12. http://dx.doi.org/10.1016/0378-4754(90)90211-z.

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21

Grover, D. J. "Computer simulation and modelling." Computer-Aided Design 20, no. 4 (May 1988): 222. http://dx.doi.org/10.1016/0010-4485(88)90281-3.

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22

Handel, Andreas, Nicole L. La Gruta, and Paul G. Thomas. "Simulation modelling for immunologists." Nature Reviews Immunology 20, no. 3 (December 5, 2019): 186–95. http://dx.doi.org/10.1038/s41577-019-0235-3.

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23

Dave, U. "Business Modelling and Simulation." Journal of the Operational Research Society 49, no. 2 (February 1998): 180–81. http://dx.doi.org/10.1057/palgrave.jors.2600005.

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24

Dave, U. "Business Modelling and Simulation." Journal of the Operational Research Society 49, no. 2 (1998): 180–81. http://dx.doi.org/10.1038/sj.jors.2600005.

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25

Hou, Jennifer C., and P. R. Kumar. "Network modelling and simulation." Computer Networks 50, no. 12 (August 2006): 1885–86. http://dx.doi.org/10.1016/j.comnet.2005.10.025.

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26

Crookes, J. G. "Computer simulation and modelling." European Journal of Operational Research 36, no. 3 (September 1988): 422–23. http://dx.doi.org/10.1016/0377-2217(88)90141-5.

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27

Pidd, M. "Simulation modelling with pascal." European Journal of Operational Research 47, no. 3 (August 1990): 397–98. http://dx.doi.org/10.1016/0377-2217(90)90228-4.

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28

Myrtveit, Magne, and Michael Bean. "Business modelling and simulation." Wirtschaftsinformatik 42, no. 2 (April 2000): 156–60. http://dx.doi.org/10.1007/bf03250730.

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29

Xie, Shengkun, Anna T. Lawniczak, and Junlin Hao. "Modelling Autonomous Agents’ Decisions in Learning to Cross a Cellular Automaton-Based Highway via Artificial Neural Networks." Computation 8, no. 3 (July 8, 2020): 64. http://dx.doi.org/10.3390/computation8030064.

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A lot of effort has been devoted to mathematical modelling and simulation of complex systems for a better understanding of their dynamics and control. Modelling and analysis of computer simulations outcomes are also important aspects of studying the behaviour of complex systems. It often involves the use of both traditional and modern statistical approaches, including multiple linear regression, generalized linear model and non-linear regression models such as artificial neural networks. In this work, we first conduct a simulation study of the agents’ decisions learning to cross a cellular automaton based highway and then, we model the simulation data using artificial neural networks. Our research shows that artificial neural networks are capable of capturing the functional relationships between input and output variables of our simulation experiments, and they outperform the classical modelling approaches. The variable importance measure techniques can consistently identify the most dominant factors that affect the response variables, which help us to better understand how the decision-making by the autonomous agents is affected by the input factors. The significance of this work is in extending the investigations of complex systems from mathematical modelling and computer simulations to the analysis and modelling of the data obtained from the simulations using advanced statistical models.

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30

Kurin, M. O., O. O. Horbachov, A. V. Onopchenko, and T. V. Loza. "Modelling and Simulation of the Plastic Flows in Metal." METALLOFIZIKA I NOVEISHIE TEKHNOLOGII 44, no. 6 (September 6, 2022): 785–806. http://dx.doi.org/10.15407/mfint.44.06.0785.

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31

Gramatikov, Pavlin. "GALLIUM NITRIDE POWER ELECTRONICS FOR AEROSPACE - MODELLING AND SIMULATION." Journal Scientific and Applied Research 15, no. 1 (March 3, 2019): 11–21. http://dx.doi.org/10.46687/jsar.v15i1.250.

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32

Miltényi, Máté, and Levente Czégé. "Simulation of production processes with Plant Simulation." International Journal of Engineering and Management Sciences 4, no. 4 (December 12, 2019): 10–16. http://dx.doi.org/10.21791/ijems.2019.4.2.

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This article presents the modelling of interconnected companies’ logistic processes with Tecnomatix Plant Simulation by Siemens. It has two main parts. The first contains the details of recognition including simulation. The second part presents the modelling with Tecnomatix Plant Simulation. My publication is supported by the EFOP3.6.1-16-2016-00022 project. The project is co-financed by the European Union and the European Social Fund.

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33

Ormrod, David, and Benjamin Turnbull. "The Modelling and Simulation of Integrated Battlefield Cyber-Kinetic Effects." International Journal of Cyber Warfare and Terrorism 9, no. 4 (October 2019): 1–26. http://dx.doi.org/10.4018/ijcwt.2019100101.

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Despite the academic and military interest in the use of combined cyber-kinetic effects in future warfare, there is little that seeks to scientifically analyse the impact of combined cyber and kinetic military action. Current approaches to simulation focus on either the physical or cyber, but there are no current simulation approaches that combine these two domains. Military simulations in particular favor physical domains over cyber ones, relegating the uniqueness and nuances of cyber a second order consideration. Future warfare will incorporate a combined multi-domain conflict, and this includes cyber. To effectively simulate this, the uniqueness of each domain must be considered, including the interaction between domains to produce combined effects. This work introduces the Battlespace Integrated Cyber-Kinetic Effects (BICKE) simulation framework. The BICKE framework is designed specifically to combine the cyber and physical domains for the purposes of simulating mission impact. There is a requirement for researchers to measure the synergistic effects across domains.

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34

Vesa, Dumitru Claudiu, and Ilie Gligorea. "Creating Modeling and Simulation Scenarios Using Dedicated Tools." International conference KNOWLEDGE-BASED ORGANIZATION 26, no. 1 (June 1, 2020): 172–75. http://dx.doi.org/10.2478/kbo-2020-0027.

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AbstractSimulating military actions has been an important element since ancient times, the fighting ability being intricately connected to training and exercises simulating real combat. The paper describes the steps followed to create a scenario used for online teaching activities during the pandemic, using the facilities of the Centre for Modelling and Simulation of Military Actions. The scenarios were created by using two modelling and simulation software - JCATS (Joint Conflict and Tactical Simulation) for constructive simulation and the VBS (Virtual Battlespace) for virtual simulation.

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35

Vashisht, Bhavya, Ahmad Belal Anwar, and Gaurav Gautam. "Modelling and Simulation of Solar Panel." International Journal of Advance Research and Innovation 2, no. 2 (2014): 96–102. http://dx.doi.org/10.51976/ijari.221414.

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This paper aims to model a solar photovoltaic system with built in MPPT(Maximum Power Point Tracker) for Photovoltaic (PV) system. It provides theoretical study of PV systems and modelling techniques using equivalent electric circuits. MATLAB simulations verify each individual block as well as combined simulation of model containing solar panel, MPPT and Cuk converter. The results validate that MPPT can significantly increase the efficiency and the performance of PV system.

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36

Bazaz, Mohammad Abid, Mashuq un Nabi, and S. Janardhanan. "Modelling and simulation strategy for parametric transient electromagnetic simulations." International Journal of Modelling, Identification and Control 18, no. 3 (2013): 251. http://dx.doi.org/10.1504/ijmic.2013.052819.

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37

Jakubiak, Krzysztof, Jun Liang, Liana Cipcigan, Chuanyue Li, and Jingzhe Wu. "Simplified Modelling Techniques for Dynamic Wireless Power Transfer." Electronics 13, no. 21 (October 31, 2024): 4300. http://dx.doi.org/10.3390/electronics13214300.

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Recent advancements in Dynamic Wireless Power Transfer (DWPT) have highlighted the need for further research, particularly in the area of modelling and simulation techniques. As the power transferred between charging pads depends on vehicle position, the load profile of the DWPT is therefore a function of the vehicle’s movement which is dependent on user behaviour and is inherently stochastic. For DWPT, these events involve high instantaneous power and are short in duration. To better understand the impact of DWPT, accurate models are required to test control systems and potential solutions. Additionally, these systems require high-frequency simulation for DWPT, which results in long simulation times during development. This paper presents a simplified model for circuit components that eliminates high-frequency switching elements, enabling the use of larger simulation time steps and significantly reducing simulation time. By applying circuit analysis and calculating equivalent impedances, the model provides average circuit values that effectively represent waveform amplitudes without the need to simulate instantaneous, high-frequency variations. To ensure the efficiency of grid-connected simulations and achieve a level of accuracy that reflects the internal dynamics of wireless charging, subsystem simulations demonstrated significant time improvements at the cost of minimal accuracy loss. For DC/DC converters operating at 2 kHz, simulation time was reduced by 3× with only a 1% error. The DWPT subsystem, operating at 85 kHz, achieved an 18× reduction in simulation time with a 2.5% deviation. When combined, the full system resulted in a 30-fold reduction in simulation time with only a 6% deviation from the base model.

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38

Ruan, Mingchaun, and Jan B. M. Wiggers. "Modelling sewer emission using simulink." Water Science and Technology 36, no. 5 (September 1, 1997): 185–92. http://dx.doi.org/10.2166/wst.1997.0194.

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A dynamic programming package SIMULINK has been used to develop a conceptual emission model named SEWSIM for both event-based and continuous simulations of urban sewer systems. The model variables are mostly vectorized for simulation efficiency. The impervious catchment and the sewer network are schematised as two linear dynamic reservoirs. The physical processes that are conceptually modelled include solids buildup and washoff (catchment surface) and sediment erosion and deposition (sewer network). The conceptual model calibrated using measurements or simulation results of hydrodynamic models is able to predict the sewer emission using a long series of historical rainfall records.

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39

Madear, Gelu, and Camelia Madear. "Environmental modelling - a modern tool towards sustainability." MATEC Web of Conferences 342 (2021): 03013. http://dx.doi.org/10.1051/matecconf/202134203013.

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One way to solve environmental problems is through modelling. Humankind developed a series of models, from mental models, physical models to computer simulation models. Building a model assumes abstraction, simplifying the natural system by considering only the essential details and discarding irrelevant ones. Mapping the real worlds to the world of models is done by choosing an abstraction level and the corresponding modelling tool. The right abstraction level is paramount for any modelling project, depending on the real problem being analysed. In modern simulation modelling, there are three methods, each having a particular range of abstraction levels: system dynamics, discrete event (process-centric modelling) and agent-based models. Ecosystems and generally any environmental problems (real world) are complex dynamics that challenge our comprehension. Understanding the significant environmental challenges is vital to adopt adequate policies for a sustainable environment through modelling and simulation. Since our cognitive abilities are limited, we need a simulation of the environmental systems to see the dynamic patterns and how humans interact with the environment. Environmental modelling helps us understand complex systems by building mathematical models and running simulations using a high abstraction level. The system dynamics method of modelling and simulation is used to clarify the representation of the stocks and flows and the feedback process that control the flows and describe the dynamic behaviour (growth, decay, or oscillations) of complex systems over time. Modelling for prediction, understanding across time and spatial scales, and environmental systems disciplines is key for a sustainable future.

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40

Pullar, David. "Simulation Modelling Applied to Runoff Modelling Using MapScript." Transactions in GIS 7, no. 2 (March 2003): 267–83. http://dx.doi.org/10.1111/1467-9671.00144.

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41

Menter, F. "Turbulence Modelling for Technical Flows." NAFEMS International Journal of CFD Case Studies 5 (April 2006): 41–49. http://dx.doi.org/10.59972/zy8s6eve.

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The paper describes the need for turbulence modelling in industrial flow simulations. It will describe the general problem in the simulation of turbulent flows and the required averaging procedures to arrive at a manageable equation system. The principal concepts behind turbulence models will be described and some current model formulations will be described briefly. Simulations will be shown for generic testcases and industrial applications.

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42

Sugano, Kiyohiko. "Lost in modelling and simulation?" ADMET and DMPK 9, no. 2 (March 20, 2021): 75–109. http://dx.doi.org/10.5599/admet.923.

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Over the past few decades, physiologically-based pharmacokinetic modelling (PBPK) has been anticipated to be a powerful tool to improve the productivity of drug discovery and development. However, recently, multiple systematic evaluation studies independently suggested that the predictive power of current oral absorption (OA) PBPK models needs significant improvement. There is some disagreement between the industry and regulators about the credibility of OA PBPK modelling. Recently, the editorial board of AMDET&DMPK has announced the policy for the articles related to PBPK modelling (Modelling and simulation ethics). In this feature article, the background of this policy is explained: (1) Requirements for scientific writing of PBPK modelling, (2) Scientific literacy for PBPK modelling, and (3) Middle-out approaches. PBPK models are a useful tool if used correctly. This article will hopefully help advance the science of OA PBPK models.

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43

Halaška, Michal, and Roman Šperka. "Is there a Need for Agent-based Modelling and Simulation in Business Process Management?" Organizacija 51, no. 4 (December 1, 2018): 255–69. http://dx.doi.org/10.2478/orga-2018-0019.

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AbstractBackground and Purpose: Agent-based modelling and simulation (ABS) is growing in many areas like, e.g., management, social and computer sciences. However, the similar trend does not seem to occur within the field of business process management (BPM), even though simulation approaches like discrete event simulation or system dynamics are well established and widely used. Thus, in our paper we investigate the advantages and disadvantages of agent-based modelling and simulation in the field of BPM in simulation experiments.Design/Methodology/Approach: In our research, we investigate if there is a necessity for ABS in the field of BPM with our own simulation experiments to compare traditional and ABS models. For this purpose, we use simulation framework MAREA, which is a simulation environment with integrated ERP system. Our model is a complex system of a trading company selling computer cables. For the verification of our model, we use automated process discovery techniques.Results: In our simulations, we investigated the impact of changes in resources’ behavior on the outcome of company’s order to cash process (O2C). Simulations experiments demonstrated that even small changes might have statistically significant effect on outcomes of the processes and decisions based on such outcomes. Simulation experiments also demonstrated that the impact of randomly distributed fluctuations of well-being have a diminishing tendency with the increasing number of sales representatives involved in the process.Conclusions: Our research revealed several advantages and disadvantages of using ABS in business process modelling. However, as we show, many of them were at least partially addressed in the recent years. Thus, we believe that ABS will get more attention in the field of BPM similarly to other fields like, e.g., social sciences. We suggested areas in BPM simulations, e.g., modelling of resources, be it human or technological resources, where there is a need for ABS.

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44

LINDBERG, ERIK. "MODELLING AND SIMULATION OF CHUA'S CIRCUIT." Journal of Circuits, Systems and Computers 03, no. 02 (June 1993): 537–52. http://dx.doi.org/10.1142/s0218126693000332.

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Experiments with modelling and simulation of Chua's circuit are presented in order to transfer a simple explanation of its behaviour from the wonderful fairy-tale world of mathematicians to the marvellous physical world of electronic engineers. It is demonstrated that the behaviour of the circuit is based on the interaction (superposition) of two different kinds of energy balance: (1) Chaotic behaviour based on the interaction of two unstable DC-states and (2) stable limit cycle behaviour based on the balance between the energy lost in the regions with mainly positive losses and the energy gained in the regions with mainly negative losses. Convergence problems observed in connection with simulation of the ideal piecewise-linear model are solved by means of a smooth continuous model of the nonlinear element based on the ideal operational amplifier model instead of a polynomial approximation. The preliminary results are presented. The NAP2 program made by the late Thomas Rübner-Petersen has been used for the simulations.

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45

Paul, Ray J., and Sew Tee Chew. "Simulation Modelling Using an Interactive Simulation Program Generator." Journal of the Operational Research Society 38, no. 8 (August 1987): 735. http://dx.doi.org/10.2307/2582845.

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46

Törn, Aimo. "The simulation net approach to modelling and simulation." SIMULATION 57, no. 3 (September 1991): 196–98. http://dx.doi.org/10.1177/003754979105700311.

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47

Paul, Ray J., and Sew Tee Chew. "Simulation Modelling Using an Interactive Simulation Program Generator." Journal of the Operational Research Society 38, no. 8 (August 1987): 735–52. http://dx.doi.org/10.1057/jors.1987.122.

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48

Koňár, Radoslav, Miloš Mičian, and Andrej Zrak. "Lap weld joint modelling and simulation of welding in programme SYSWELD." MATEC Web of Conferences 157 (2018): 02018. http://dx.doi.org/10.1051/matecconf/201815702018.

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Simulations of the welding process for applications of practice using SYSWELD are presented. This paper presents simulation of welding in the repair of high-pressure gas pipeline with steel sleeve with composite filling. Material of experimental sample was steel S355. The simulations in SYSWELD divided in to two parts: the thermal simulation followed by the mechanical simulation. The results of the numerical model, which are listed in article are compared to real experiments.

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49

De Stefano, G., and O. V. Vasilyev. "A fully adaptive wavelet-based approach to homogeneous turbulence simulation." Journal of Fluid Mechanics 695 (February 8, 2012): 149–72. http://dx.doi.org/10.1017/jfm.2012.6.

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AbstractThe ability of wavelet multi-resolution analysis to detect and track the energy-containing motions that govern the dynamics of a fluid flow offers a unique hierarchical framework for modelling and simulating turbulence. In this paper, the role of the wavelet thresholding level in wavelet-based modelling and simulation of turbulent flows is systematically examined. The thresholding level controls the relative importance of resolved energetic structures and residual unresolved background flow and, thus, the achieved turbulence resolution. A fully adaptive eddy capturing approach is developed that allows variable-fidelity numerical simulations of turbulence to be performed. The new method is based on wavelet filtering with time-varying thresholding. The thresholding level automatically adapts to the desired turbulence resolution during the simulation. The filtered governing equations supplemented by a localized dynamic energy-based closure model are solved numerically using the adaptive wavelet collocation method. The approach is successfully tested in the numerical simulation of both linearly forced and freely decaying homogeneous turbulence.

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Junker, Björn H., Dirk Koschützki, and Falk Schreiber. "Kinetic Modelling with the Systems Biology Modelling Environment SyBME." Journal of Integrative Bioinformatics 3, no. 1 (June 1, 2006): 11–20. http://dx.doi.org/10.1515/jib-2006-18.

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Abstract:

Summary Kinetic modelling and simulation is an important approach in systems biology. While the focus of current modelling tools is on simulation, model development is a highly iterative process which is currently only partly supported. To support the development of biochemical models, their simulation, and graphical understanding, we designed and implemented SyBME, the Systems Biology Modelling Environment. Here we present the architecture and the main components of SyBME and show its use by modelling sucrose breakdown in developing potato tubers.

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