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Journal articles on the topic 'Mathematical modeling and simulation'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Shi, Pei Cheng, and Yang Min Sun. "Hydraulic Fluid Mathematical Modeling." Applied Mechanics and Materials 432 (September 2013): 127–32. http://dx.doi.org/10.4028/www.scientific.net/amm.432.127.

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In hydraulic system, the property of hydraulic fluid will have non-linear behavior change when the temperature and pressure of fluid and the amount of dissolved and undissolved air vary, thus influencing the hydraulic system performance. The authors first studied the property of hydraulic fluid, and then constructed the mathematical expression theoretically, which shows the hydraulic fluid effective density using the fluid pressure, temperature and air content parameters. The computation simulations of the hydraulic fluid non-linear property were carried out using the simulation program based on MATLAB software. Meanwhile the key-factors affecting the hydraulic effective density and fluid bulk modulus were discussed. The study results provide computing foundation for designing quickly responsive, running steady and highly accurate hydraulic transmission system, which have important theory and engineering significance.

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2

Rust, Jon P., and Hector M. Gutierrez. "Mathematical Modeling and Simulation for Carding." Textile Research Journal 64, no. 10 (October 1994): 573–78. http://dx.doi.org/10.1177/004051759406401004.

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3

Kislitsyna, Irina A., and Galina F. Malykhina. "Mathematical modeling of altimeter." ACTA IMEKO 4, no. 4 (December 23, 2015): 16. http://dx.doi.org/10.21014/acta_imeko.v4i4.263.

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The aim of the survey is to simulate photon altimeter designed for a soft landing on the lunar surface. Simulation of the process of scattering of gamma rays from the lunar surface with a typical composition of the lunar soil was implemented.

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JANSE VAN RENSBURG, T., M. A. VAN WYK, and W. H. STEEB. "MATHEMATICAL MODELING OF AN AUTOMATIC DRIVER." International Journal of Modern Physics C 16, no. 06 (June 2005): 895–908. http://dx.doi.org/10.1142/s0129183105007595.

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The design of driving simulators is common practice within the simulation industry. Normally, the focus is on the modeling of realistic vehicle dynamics models. However, the design of a realistic simulation environment is of equal importance. A human driver usually steers one vehicle, but the rest of the vehicles used in the simulation should be managed by a computer program. In this article, an automatic driver model to be used within the simulation environment, is described. The automatic driver uses the same vehicle dynamics model as the human driver would use. It also uses the vehicle characteristics in such a way to obtain the optimal performance of the vehicle.

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5

Skocil, Tomas, and Manuel Pérez Donsión. "Mathematical Modeling and Simulation of Photovoltaic Array." Renewable Energy and Power Quality Journal 1, no. 06 (March 2008): 437–41. http://dx.doi.org/10.24084/repqj06.326.

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6

Rasputina, E. I., and G. S. Osipov. "MATHEMATICAL MODELING AND SIMULATION DYNAMICS OF POPULATIONS." International Journal of Applied and Fundamental Research (Международный журнал прикладных и фундаментальных исследований) 1, no. 3 2017 (2017): 28–33. http://dx.doi.org/10.17513/mjpfi.11392.

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7

S, Sankar, and Yuvaraj . "Mathematical Modeling and Simulation of Computer Programming." i-manager's Journal on Software Engineering 5, no. 1 (September 15, 2010): 29–33. http://dx.doi.org/10.26634/jse.5.1.1206.

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8

sci, global. "Mathematical Modeling and Simulation of Antibubble Dynamics." Numerical Mathematics: Theory, Methods and Applications 13, no. 1 (June 2020): 81–98. http://dx.doi.org/10.4208/nmtma.oa-2019-0082.

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9

Chatterjee, Aveek N., Qing Yu, J. S. Moore, and N. R. Aluru. "Mathematical Modeling and Simulation of Dissolvable Hydrogels." Journal of Aerospace Engineering 16, no. 2 (April 2003): 55–64. http://dx.doi.org/10.1061/(asce)0893-1321(2003)16:2(55).

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Jiang, Bing Hua, Li Fang, and Hang Biao Guo. "The Tapping Machine Mathematical Modeling Simulation Study." Applied Mechanics and Materials 373-375 (August 2013): 2073–77. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.2073.

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Based on the tapping machines special structural features and practices, from both directions of rotation and impact established the tapping machine mechanism rotating borer and impact dynamic mathematical model, analysed the effect of different tapping machines parameters on the model itself, simulated the model with inputting wide pulse signal, the simulation results show that: firstly, the tapping machine model established in this paper is reasonable; secondly, increase the damping coefficient of the blast furnace, the tapping machines rotating borer rotation speed and impact attenuation speed decrease.

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11

Tanaka, Martin L., Shane D. Ross, and Maury A. Nussbaum. "Mathematical modeling and simulation of seated stability." Journal of Biomechanics 43, no. 5 (March 2010): 906–12. http://dx.doi.org/10.1016/j.jbiomech.2009.11.006.

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12

Pojman, John A. "Mathematical modeling of frontal polymerization." Mathematical Modelling of Natural Phenomena 14, no. 6 (2019): 604. http://dx.doi.org/10.1051/mmnp/2019059.

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Frontal polymerization is way to convert liquid resin into a solid material with a self-propagating reaction. The reaction spreads like a flame from the heat of the reaction that diffuses into neighboring regions, starting more reaction. The frontal velocity has been accurately modeled for free-radical polymerization systems. The dynamics of fronts have been studied theoretically and experimentally. If the viscosity of the initial medium is low, then fronts can become unstable due to buoyancy-driven convection. A fascinating aspect of frontal polymerization is that fronts often do not propagate as a plane waves but exhibit complex modes such as “spin modes” and chaos. The kinetics of the polymerization significantly affects the onset of these modes. Multifunctional acrylates exhibit more complex dynamics than monoacrylates. Using multifunctional acrylates and inorganic fillers, 3P LLC created “cure-on demand” systems that do not require mixing before use, have a long shelf life and can be hardened in seconds to minutes. We consider two commercial products using frontal polymerization. The first is a wood filler that can be applied to a damaged section of wood and hardened in a few seconds by the application of heat to the surface. The second product is QuickCure Clay (QCC). QCC has an unlimited working time during which it can be sculpted. QCC is then cured by heating part of the object to 100 °C, setting off the propagating curing front. The modeling of frontal polymerization helped guide the development of these products.

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13

Čiegis, R., T. Leonavičiene, V. Skakauskas, and O. Suboč. "MATHEMATICAL MODELING OF GRAIN DRYING." Mathematical Modelling and Analysis 8, no. 2 (June 30, 2003): 103–12. http://dx.doi.org/10.3846/13926292.2003.9637215.

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In this paper we consider the mathematical model which describes the grain drying process. The air and grain moisture and temperature are described by a system of PDE. A finite difference scheme is proposed for finding a numerical solution. The convergence of the discrete solution is proved for a simplified model, when the temperature is assumed to be given a priori. Results of numerical experiments are presented.

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14

Ribeiro, R. L. L., A. B. Mariano, J. A. Souza, and J. V. C. Vargas. "TRANSIENT MODELING AND SIMULATION OF COMPACT PHOTOBIOREACTORS." Revista de Engenharia Térmica 7, no. 2 (December 31, 2008): 66. http://dx.doi.org/10.5380/reterm.v7i2.61780.

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In this paper, a mathematical model is developed to make possible the simulation of microalgae growth and its dependency on medium temperature and light intensity. The model is utilized to simulate a compact photobioreactor response in time with physicochemical parameters of the microalgae Phaeodactylum tricornutum. The model allows for the prediction of the transient and local evolution of the biomass concentration in the photobioreactor with low computational time. As a result, the model is expected to be a useful tool for simulation, design, and optimization of compact photobioreactors. Numerical solutions of the mathematical model are presented for the visualization of biomass concentration and total production. Several simulations were performed with temperatures ranging from 274 K to 300 K , and the maximum biomass production was achieved with an operating temperature of 294 K.

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15

Panferov, Alexander I., Alexander V. Nebylov, and Sergey A. Brodsky. "Mathematical Modeling, Simulation and Control of Flexible Vehicles." IFAC Proceedings Volumes 41, no. 2 (2008): 16071–76. http://dx.doi.org/10.3182/20080706-5-kr-1001.02716.

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16

Mohd, T. A. T., M. K. Hassan, and WMK A. Aziz. "MATHEMATICAL MODELING AND SIMULATION OF AN ELECTRIC VEHICLE." Journal of Mechanical Engineering and Sciences 8 (June 30, 2015): 1312–21. http://dx.doi.org/10.15282/jmes.8.2015.6.0128.

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17

Baum, H., K. Mcgrattan, and R. Rehm. "Mathematical Modeling And Computer Simulation Of Fire Phenomena." Fire Safety Science 4 (1994): 185–93. http://dx.doi.org/10.3801/iafss.fss.4-185.

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18

Arora, Ruchi, Dharmendra Kumar, Ishita Jhamb, and Avina Kaur Narang. "Mathematical Modeling of Chikungunya Dynamics: Stability and Simulation." Cubo (Temuco) 22, no. 2 (August 2020): 177–201. http://dx.doi.org/10.4067/s0719-06462020000200177.

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19

Faré,, N., and A. Brillard,. "Mathematical Modeling and Numerical Simulation of Fabric Drape." Journal of the Mechanical Behavior of Materials 19, no. 4 (August 2009): 225–32. http://dx.doi.org/10.1515/jmbm.2009.19.4.225.

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20

., Ravinder Kumar. "MATHEMATICAL MODELING, SIMULATION AND VALIDATION OF PHOTOVOLTAIC CELLS." International Journal of Research in Engineering and Technology 03, no. 10 (October 25, 2014): 170–74. http://dx.doi.org/10.15623/ijret.2014.0310025.

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21

Kongto, Abhijart, Sunun Limtrakul, Kanokwan Ngaowsuwan, Palghat A. Ramachandran, and Terdthai Vatanatham. "Mathematical modeling and simulation for gas–liquid reactors." Computers & Chemical Engineering 29, no. 11-12 (October 2005): 2461–73. http://dx.doi.org/10.1016/j.compchemeng.2005.05.025.

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22

Ataullakhanov, Fazoil I., and Mikhail A. Panteleev. "Mathematical Modeling and Computer Simulation in Blood Coagulation." Pathophysiology of Haemostasis and Thrombosis 34, no. 2-3 (2005): 60–70. http://dx.doi.org/10.1159/000089927.

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23

Smoljan, B., D. Iljkić, S. Smokvina Hanza, M. Jokić, L. Štic, and A. Borić. "Mathematical Modeling and Computer Simulation of Steel Quenching." Materials Performance and Characterization 8, no. 2 (June 1, 2018): 20180040. http://dx.doi.org/10.1520/mpc20180040.

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24

Aklilu, B. T., and S. I. Gilani. "Mathematical modeling and simulation of a cogeneration plant." Applied Thermal Engineering 30, no. 16 (November 2010): 2545–54. http://dx.doi.org/10.1016/j.applthermaleng.2010.07.005.

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25

Kelemen, A., M. Crivii, and V. Trifa. "Mathematical modeling and simulation of stepping motor systems." Mathematical Modelling 8 (1987): 544–49. http://dx.doi.org/10.1016/0270-0255(87)90641-5.

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26

Shaikh, Nazrul I., and Vittal Prabhu. "Mathematical modeling and simulation of cryogenic tunnel freezers." Journal of Food Engineering 80, no. 2 (May 2007): 701–10. http://dx.doi.org/10.1016/j.jfoodeng.2006.04.065.

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27

Baum, H. R., O. A. Ezekoye, K. B. McGrattan, and R. G. Rehm. "Mathematical modeling and computer simulation of fire phenomena." Theoretical and Computational Fluid Dynamics 6-6, no. 2-3 (April 1994): 125–39. http://dx.doi.org/10.1007/bf00312345.

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28

Li, Yong Xiang, and Jin Hai Zhang. "Research on Mathematical Modeling of Ship Simulation System." Applied Mechanics and Materials 299 (February 2013): 64–67. http://dx.doi.org/10.4028/www.scientific.net/amm.299.64.

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With the rapid development of science and technology, mathematical models more and more present in modern production, work and social activities. Must be established to control the production process of mathematical models, use this model on design and calculation of control devices accordingly in order to achieve effective process control. Ship handling Simulator as an advanced teaching method applied in the teaching and training of crews sailing in China have a long history. By driving simulation of ship navigation, training students to train and ship very similar environment.

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29

Cao, Fei, Qing Yun Liu, and Fan Wu. "The Cross-Eye Jamming Mathematical Modeling." Applied Mechanics and Materials 344 (July 2013): 125–28. http://dx.doi.org/10.4028/www.scientific.net/amm.344.125.

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A rigorous mathematical analysis of cross-eye jamming in a radar system scenario and an expression for the induced angular error due to the cross-eye jammer are presented. The simulation results show that there is a Doppler difference between jamming and target return. The Doppler difference increases with the decrease of the distance between the monopulse radar and the platform protected by cross-eye jammer. When the power of target return is not small enough with respect to the power of jamming transmitted by one of the two sources, maybe the sign of the indicated angle is uncontrollable. The simulation results also show that although the cross-eye gain is maximized if two jamming signals are equal amplitude and antiphase, it is not a reasonable choice.

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30

Mureşan, Vlad, Mihail Abrudean, Tiberiu Colosi, Cristian Bondici, Iulia Clitan, Mihaela Ligia Ungureşan, and Mihai Secară. "Modeling and Simulation of a Hydroelectric Process." Applied Mechanics and Materials 811 (November 2015): 133–41. http://dx.doi.org/10.4028/www.scientific.net/amm.811.133.

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In this paper, a solution for the mathematical modeling and simulation of the technological process associated to a turbine – synchronous generator group, belonging to a small hydroelectric power plant. In order to determine the parameters of the treated technological process, some experimental identification procedures are applied. The experimental identification procedures are applied to the experimental data obtained from the real plant. The validity of the obtained mathematical model is proved through the comparison of the experimental data with the data obtained after the model simulation. The technological importance of having a valid mathematical model of the hydroelectric process consists in the possibility to study the plant behavior for different working regimes using the results of the model simulation and in the possibility of including the process in an automatic control structure.

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31

Čiegis, R., and V. Starikovičius. "MATHEMATICAL MODELING OF WOOD DRYING PROCESS." Mathematical Modelling and Analysis 7, no. 2 (December 15, 2002): 177–90. http://dx.doi.org/10.3846/13926292.2002.9637190.

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This work focuses on the development of mathematical models describing moisture movement in wood, when the wood is considered as porous medium. Main moisture transport mechanisms are discussed. It is shown how the wood can be described as a two‐ or three‐phase system. Summaries of several multiphase flow models are presented in the hierarchical order: from the most general models to more simple examples. The approximation steps are described explicitly, and all assumptions are given in detail. It shown how models for specific applications in wood drying or saturation can be obtained.

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32

Xu, Hui, Hai Qiao Xu, and Bi Yin Zhang. "Characteristics Modeling and Simulation of Ship-Radiated Noise." Advanced Materials Research 546-547 (July 2012): 143–48. http://dx.doi.org/10.4028/www.scientific.net/amr.546-547.143.

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Since the importance of ship-radiated noise simulation in onshore simulation training and digital sonar development, we establish a mathematical model of ship-radiated noise on the basis of analyzing the causes and characteristics for each of its components, and then apply the model on simulating each signal component in turn. Additionally, for improving the versatility of the model while reducing the complexity of the simulation, a design method for specific frequency response filter based on window function is used to realize the simulation. The simulation results demonstrate the effectiveness of the approach.

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33

ARALOVA, N. I. "MATHEMATICAL MODELLING OF IMMUNE PROCESSES AND ITS APPLICATION." Biotechnologia Acta 13, no. 5 (October 2020): 5–18. http://dx.doi.org/10.15407/biotech13.05.005.

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The aim of the study was to develop a mathematical model to research hypoxic states in case of simulation of an organism infectious lesions. The model is based on the methods of mathematical modeling and the theory of optimal control of moving objects. The processes of organism damage are simulated with the mathematical model of immune response developed by G.I. Marchuk and the members of his scientific school, adapted to current conditions. This model is based on Burnet’s clone selection theory of the determining role of antigen. Simulation results using the model are presented. The dependencies of infectious courses on the volumetric velocity of systemic blood flow is analyzed on the complex mathematical model of immune response, respiratory and blood circulation systems. The immune system is shown to be rather sensitive to the changes in blood flow via capillaries. Thus, the organ blood flows can be used as parameters for the model by which the respiratory, immune response, and blood circulation systems interact and interplay.

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34

Yang, Xing Hua, Ji Dai Wang, Jia Zhen Pan, and Xin Jun Liang. "Mathematical Modeling and Experimental Research on Scroll Expander." Applied Mechanics and Materials 229-231 (November 2012): 1900–1903. http://dx.doi.org/10.4028/www.scientific.net/amm.229-231.1900.

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A scroll expander is applied to a compressed air energy storage system in order to improve the energy conversion efficiency. Based on the geometric model, mass conservation equation, ideal gas equation and energy conservation equation, a mathematical model of the scroll expander is developed in order to describe the variation mechanism of the volume, mass, pressure and temperature of the air in different chambers. A prototype is constructed and tested to verify the simulation model. The mathematical model is implemented in Matlab and verified by comparing the simulation with the experimental results. The simulation agrees well with the experimental results.

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35

Li, Ke, Peng Liu, and Nu Chen. "Modeling and Simulation of Engagement Process of Antiaircraft Missile for Training Simulation." Applied Mechanics and Materials 541-542 (March 2014): 1304–8. http://dx.doi.org/10.4028/www.scientific.net/amm.541-542.1304.

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Aiming at requirements to depict engagement process of the hardware in loop simulation system of antiaircraft missile based on industrial computers for operational training simulation, the paper establishes the guidance and trajectory mathematical models for the process of antiaircraft missile attacking target. According to the result of missile velocity simulation by means of a trajectory simulation system of six degrees of freedom of an antiaircraft missile, a realistic mathematical model of the missile velocity parameter is established; a realistic mathematical model of a missile single shot kill probability (SSKP) is established with relative kill area data of a missile. The simulation model of the missile engagement process is implemented with VC++, which could be used to really simulate a whole engagement process of a missile flying and destroying a target. The experiments indicate the model is correct, the result is credible, the method is effective, and the thought solving the mentioned problem is very helpful for improving operational ability of personnel with similar training simulation system.

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36

Mikula, Jan, Pavol Palička, and Jan Kerekanic. "SIMULATION ANALYSIS OF PREHEATER CHARGE TO THE ROTARY FURNACE." Acta Polytechnica 55, no. 4 (August 31, 2015): 247. http://dx.doi.org/10.14311/ap.2015.55.0247.

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Mathematical modeling of heat aggregates is one of the fundamental methods of the mathematical modelling research. A mathematical model based on the method of elementary balances was created for the thermal treatment of granular and lumpy materials. The adaptation of the selected aggregate model is based on prior knowledge and experiments. The paper presents an adaptation of the mathematical model for the magnesite processing rotary furnace using the mode of caustic and clinker production. A simulation of the charge preheater impact based on the thin layer principle is implemented into the model. The main advantages of using this type of preheater of rotary furnace are smaller dimensions for a large exchange surface and low pressure losses.

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37

Na, Liu. "MATHEMATICAL MODELING OF HYBRID VEHICLE’S RECUPERATION BRAKING MODE." Management of Development of Complex Systems, no. 44 (November 30, 2020): 182–87. http://dx.doi.org/10.32347/2412-9933.2020.44.182-187.

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The paper considers the synthesis of mathematical model of recuperation braking mode for hybrid vehicle as a complex control object. The results of computer simulation as diagrams of transients of different operating parameters of hybrid vehicle power system are obtained on the basis of developed model. The analysis of simulation results confirms the adequacy of the mathematic model of the recuperation braking mode of hybrid vehicle to real processes. The developed model can be used for synthesis of automatic control systems of the electric motors, power converters, power supplies and chargers for hybrid vehicles. Hematical and simulation models of the hybrid vehicle’s recuperation braking mode is carried out. The presented models are based on equations of physics of processes and allow to study the recuperation braking mode of the different types hybrid vehicles under various conditions and parameters values (initial linear vehicle’s speed, electrical power of generator, inclination angle and the quality of the road surface, etc.). The designed mathematical model has a rather high adequacy to the real processes, which take place in the hybrid vehicles in the recuperation braking mode, that is confirmed by the obtained simulation results in the form of graphs of transients of the main variables changes. Further research should be conducted towards the development of the functional structures, control devices as well as software and hardware for automatic control systems of the different types hybrid vehicles on the basis of the obtained mathematical and simulation models.

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38

Voliansky, Roman, and Andri Pranolo. "Parallel mathematical models of dynamic objects." International Journal of Advances in Intelligent Informatics 4, no. 2 (July 31, 2018): 120. http://dx.doi.org/10.26555/ijain.v4i2.229.

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The paper deals with the developing of the methodological backgrounds for the modeling and simulation of complex dynamical objects. Such backgrounds allow us to perform coordinate transformation and formulate the algorithm of its usage for transforming the serial mathematical model into parallel ones. This algorithm is based on partial fraction decomposition of the transfer function of a dynamic object. Usage of proposed algorithms is one of the ways to decrease calculation time and improve PC usage while a simulation is being performed. We prove our approach by considering the example of modeling and simulating of fourth order dynamical object with various eigenvalues. This example shows that developed parallel model is stable, well-convergent, and high-accuracy model. There is no defined any calculation errors between well-known serial model and proposed parallel one. Nevertheless, the proposed approach’s usage allows us to reduce calculation time by more than 20% by using several CPU’s cores while calculations are being performed.

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39

Smith, J. M. "Mathematical Modeling and digital Simulation for Engineers and Scientists." Biometrics 44, no. 2 (June 1988): 632. http://dx.doi.org/10.2307/2531888.

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40

Muhammad, Hari, Huynh Thien, and Taufiq Mulyanto. "MATHEMATICAL MODELING, SIMULATION AND IDENTIFICATION OF MICRO COAXIAL HELICOPTER." Journal of KONES. Powertrain and Transport 19, no. 2 (January 1, 2015): 353–64. http://dx.doi.org/10.5604/12314005.1138226.

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41

Scotton, Jaque W., Zardo Becker, Darci L. Savicki, and Antonio Goulart. "Mathematical Modeling and Numerical Simulation of Atmospheric Pollutant Dispersion." Defect and Diffusion Forum 372 (March 2017): 180–87. http://dx.doi.org/10.4028/www.scientific.net/ddf.372.180.

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This work presents a mathematical modeling and numerical solution of dispersion of pollutants in the atmosphere. The equations of conservation of mass, amount of movement, energy and a chemical species are solved by the Finite Volume Method in Cartesian coordinates and the turbulence closure is based on the Reynolds averages (RANS models), using the model k-ε for the determination of the fields of velocity, temperature and, in a specific case, concentration of pollutant. The numerical results are compared with data from the classic Prairie Grass experiment, showing excellent agreement.

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42

Bärwolff, Günter. "Mathematical Modeling and Simulation of the COVID-19 Pandemic." Systems 8, no. 3 (July 13, 2020): 24. http://dx.doi.org/10.3390/systems8030024.

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The current pandemic is a great challenge for several research areas. In addition to virology research, mathematical models and simulations can be a valuable contribution to the understanding of the dynamics of the pandemic and can give recommendations to physicians and politicians. Based on actual data of people infected with COVID-19 from the European Center for Disease Prevention and Control (ECDC), input parameters of mathematical models will be determined and applied. These parameters will be estimated for the UK, Italy, Spain, and Germany and used in an S I R -type model. As a basis for the model’s calibration, the initial exponential growth phase of the COVID-19 pandemic in the named countries is used. Strategies for the commencing and ending of social and economic shutdown measures are discussed.

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43

Mohite, Saurabh U., Abhishek P. Patil, Shreyas D. Patil, and D. N. Pawar. "Mathematical Modeling and Simulation of Multi Loop Pilot Plant." International Journal of Computer Sciences and Engineering 7, no. 6 (June 30, 2019): 769–74. http://dx.doi.org/10.26438/ijcse/v7i6.769774.

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44

Pladis, Prokopis, Aleck H. Alexopoulos, and Costas Kiparissides. "Mathematical Modeling and Simulation of Vinylidene Fluoride Emulsion Polymerization." Industrial & Engineering Chemistry Research 53, no. 18 (March 6, 2014): 7352–64. http://dx.doi.org/10.1021/ie403548m.

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45

Calzetta Resio, A., R. J. Aguerre, and C. Suarez. "The drying of amaranth grain: mathematical modeling and simulation." Brazilian Journal of Chemical Engineering 22, no. 2 (June 2005): 303–9. http://dx.doi.org/10.1590/s0104-66322005000200019.

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46

Hamel, S., and W. Krumm. "Mathematical modeling and simulation of bubbling fluidized bed gasifiers." Fuel and Energy Abstracts 43, no. 4 (July 2002): 249. http://dx.doi.org/10.1016/s0140-6701(02)86190-2.

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47

Yih-O Tu. "Mathematical modeling and computer simulation spin coating of ferrofluid." IEEE Transactions on Magnetics 24, no. 6 (1988): 3129–31. http://dx.doi.org/10.1109/20.92357.

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48

Patwardhan, Samarth D., Fatemeh Famoori, Radhika G. Gunaji, and Suresh Kumar Govindarajan. "Simulation and Mathematical Modeling of Stimulated Shale Gas Reservoirs." Industrial & Engineering Chemistry Research 53, no. 51 (December 2014): 19788–805. http://dx.doi.org/10.1021/ie501116j.

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Attaullah and Muhammad Sohaib. "Mathematical modeling and numerical simulation of HIV infection model." Results in Applied Mathematics 7 (August 2020): 100118. http://dx.doi.org/10.1016/j.rinam.2020.100118.

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Nifong, Thomas P., Michael B. Bongiovanni, and Glenn S. Gerhard. "Mathematical modeling and computer simulation of erythrocytapheresis for SCD." Transfusion 41, no. 2 (February 2001): 256–63. http://dx.doi.org/10.1046/j.1537-2995.2001.41020256.x.

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