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Journal articles on the topic 'Numerical model'

To see the other types of publications on this topic, follow the link: Numerical model.

Author: Grafiati

Published: 4 June 2021

Last updated: 22 June 2024

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1

Jaichuang, Atit, and Wirawan Chinviriyasit. "Numerical Modelling of Influenza Model with Diffusion." International Journal of Applied Physics and Mathematics 4, no. 1 (2014): 15–21. http://dx.doi.org/10.7763/ijapm.2014.v4.247.

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2

CORCAU, Jenica-Ileana, and Liviu DINCA. "MATHEMATICAL MODEL AND NUMERICAL SIMULATIONS FOR PHOTOVOLTAIC PANELS." Review of the Air Force Academy 15, no. 3 (December 14, 2017): 47–56. http://dx.doi.org/10.19062/1842-9238.2017.15.3.5.

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3

Zängl, Günther, Leonhard Gantner, Gisela Hartjenstein, and Heike Noppel. "Numerical errors above steep topography: A model intercomparison." Meteorologische Zeitschrift 13, no. 2 (May 6, 2004): 69–76. http://dx.doi.org/10.1127/0941-2948/2004/0013-0069.

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4

Vasiljević, Rade. "Comparison of the continuous model and the finite element model of the gantry crane carrying structure for modal analysis." Vojnotehnicki glasnik 70, no. 3 (2022): 696–719. http://dx.doi.org/10.5937/vojtehg70-36051.

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Introduction/purpose: To study the adequacy of applying numerical methods in the modal analysis of complex carrying structures of cranes. Methods: Comparative application of the analytical method and the numerical method - FEM. Results: Some comparative values of the modal parameters were obtained both analytically and numerically for the derived solution of a gantry crane carrying structure. Conclusion: It is shown that the numerical method can give a reliable general quality estimate of the structural behaviour of a complex carrying structure from the aspect of modal analysis.

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5

Zahid Saadoon, Mohammed. "Numerical Model of Growth Associated with Epiphyseal Plate Loading." International Journal of Science and Research (IJSR) 13, no. 5 (May 5, 2024): 1734–38. http://dx.doi.org/10.21275/sr24526143043.

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6

Xie, Litong, and Jiazhuang Liu. "ON SMOOTH NUMERICAL MODEL." Acta Mathematica Scientia 14, no. 1 (1994): 43–49. http://dx.doi.org/10.1016/s0252-9602(18)30089-4.

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7

von Bock und Polach, Rüdiger, and Sören Ehlers. "Model scale ice — Part B: Numerical model." Cold Regions Science and Technology 94 (October 2013): 53–60. http://dx.doi.org/10.1016/j.coldregions.2013.06.009.

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8

Li, C. "3D Analytic Model for Testing Numerical Tidal Models." Journal of Hydraulic Engineering 127, no. 9 (September 2001): 709–17. http://dx.doi.org/10.1061/(asce)0733-9429(2001)127:9(709).

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9

Rodríguez Calderón, Wilson, and Myriam Rocío Pallares Muñoz. "A numerical water-hammer model using Scilab." Ingeniería e Investigación 27, no. 3 (September 1, 2007): 98–105. http://dx.doi.org/10.15446/ing.investig.v27n3.14850.

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A water hammer can produce severe consequences regarding pipe integrity; simulation thus becomes an essential requirement for ensuring proper water distribution system design and operation. This article thus tries to demonstrate the importance of numerical methods in resolving such problems. A Scilab code allowing pressure propagation to be represented using the characteristics’ method applied to a case of classic literature was thus developed for numerically simulating this phenomenon. This method uses a finite difference scheme for resolving mass and momentum equations. The article presents equations governing the problem from the numerical point of view, the phenomenon’s behavior is analysed and results obtained by the numerical approach (calculating finite differences) are compared to those obtained with Scilab and the theoretical solution.

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10

Minato, Akihiko, Nobuyuki Nakajima, and Takahide Nagahara. "SIMULATION OF FREE SURFACE FLOW BY SP-VOF MODEL(Numerical Simulation)." Proceedings of the International Conference on Jets, Wakes and Separated Flows (ICJWSF) 2005 (2005): 717–20. http://dx.doi.org/10.1299/jsmeicjwsf.2005.717.

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11

Qiao, Yu, Xiwen Zhang, Runpeng Zhang, and Junhui Gao. "Ecological Model and Numerical Research of Gulf of Mexico Hypoxic Zone." International Journal of Environmental Science and Development 7, no. 2 (2016): 122–25. http://dx.doi.org/10.7763/ijesd.2016.v7.753.

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12

Somjaivang, Dussadee, and Settapat Chinviriyasit. "Numerical Modeling of an Influenza Epidemic Model with Vaccination and Diffusion." International Journal of Applied Physics and Mathematics 4, no. 1 (2014): 68–74. http://dx.doi.org/10.7763/ijapm.2014.v4.257.

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13

Fiala, Pavel, Tomas Jirku, and I. Behunek. "Numerical Model of Inductive Flowmeter." PIERS Online 3, no. 5 (2007): 704–8. http://dx.doi.org/10.2529/piers061006093241.

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14

Lan, Ya Mei, Yong Guo Li, and Wen Hua Guo. "Numerical Model of Wave Flume." Applied Mechanics and Materials 138-139 (November 2011): 79–84. http://dx.doi.org/10.4028/www.scientific.net/amm.138-139.79.

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Based on the finite volume method, the Navier-Stokes equations was used as the governing equations to develop a new module of the wave generating and absorbing function. The wave generating was introduced as the man-made source terms into the momentum equations, which was suitable for the volume of fluid method (VOF). Within the numerical wave flume, the reflected waves from the construction could be absorbed effectively. The absorbing section arranged at the end of the wave flume was for absorbing the incident wave, which allows for random and effective working time within the reletively smaller computation domain. Consequently, the computation efficiency was greatly improved. Finally, the validity of the absorbing section arranged at the front and end of the wave flume was investigated individually.

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15

Nielsen, Stefan B., and Albert Tarantola. "Numerical model of seismic rupture." Journal of Geophysical Research 97, B11 (1992): 15291. http://dx.doi.org/10.1029/92jb00205.

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16

Nosov, M. A., and S. V. Kolesov. "Combined Numerical Model of Tsunami." Mathematical Models and Computer Simulations 11, no. 5 (September 2019): 679–89. http://dx.doi.org/10.1134/s2070048219050156.

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17

Jancart, Sylvie, and Anne Lemaitre. "Tridimensional Dissipative Semi-Numerical Model." Earth, Moon, and Planets 92, no. 1-4 (June 2003): 63–71. http://dx.doi.org/10.1023/b:moon.0000031925.96102.be.

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18

Szuchta, Maciej, and Jakub Ośko. "Numerical model of thyroid counter." Nukleonika 61, no. 1 (March 1, 2016): 45–47. http://dx.doi.org/10.1515/nuka-2016-0010.

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Abstract The aim of this study was to develop a numerical model of spectrometric thyroid counter, which is used for the measurements of internal contamination by in vivo method. The modeled detector is used for a routine internal exposure monitoring procedure in the Radiation Protection Measurements Laboratory of National Centre for Nuclear Research (NCBJ). This procedure may also be used for monitoring of occupationally exposed nuclear medicine personnel. The developed model was prepared using Monte Carlo code FLUKA 2011 ver. 2b.6 Apr-14 and FLAIR ver. 1.2-5 interface. It contains a scintillation NaI(Tl) detector, the collimator and the thyroid water phantom with a reference source of iodine 131I. The geometry of the model was designed and a gamma energy spectrum of iodine 131I deposited in the detector was calculated.

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19

Bidal, S., and K. Kayvantash. "Positioning a human numerical model." Journal of Biomechanics 39 (January 2006): S167. http://dx.doi.org/10.1016/s0021-9290(06)83582-7.

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20

Stefanoni, Filippo, Maurizio Ventre, Francesco Mollica, and Paolo A. Netti. "A numerical model for durotaxis." Journal of Theoretical Biology 280, no. 1 (July 2011): 150–58. http://dx.doi.org/10.1016/j.jtbi.2011.04.001.

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21

Schäfer, M., and K. M. Weitzel. "Numerical model for electro-poling." Solid State Ionics 282 (December 2015): 70–75. http://dx.doi.org/10.1016/j.ssi.2015.09.023.

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22

Wallace, G. "A Numerical Fire Simulation-Model." International Journal of Wildland Fire 3, no. 2 (1993): 111. http://dx.doi.org/10.1071/wf9930111.

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An extension of the simple ellipse model of a vegetation fire is presented. This facilitates numerical implementation, and can therefore incorporate irregular topographical features and temporal changes in burning conditions. The model has been encoded into an interactive PC program which gives a visual simulation of the spread of a fire on a graphics screen. The model has considerable potential for fire management.

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23

Hamilton, Douglas P., and William R. Ward. "Tilting Saturn. II. Numerical Model." Astronomical Journal 128, no. 5 (November 2004): 2510–17. http://dx.doi.org/10.1086/424534.

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24

HASSAN, MOHAMED AHMED. "A NUMERICAL CLUSTER MODEL WITH SHELL MODEL ASSUMPTIONS." International Journal of Modern Physics E 18, no. 01 (January 2009): 183–92. http://dx.doi.org/10.1142/s0218301309012136.

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A numerical representation for nuclei is suggested and considered as a basis of a cluster model. The binding energy of the cluster representation of a nucleus is introduced. Basic assumptions of the shell model are obtained as the physical side of the suggested cluster representation. 8 Be 4-decay to two α-particles and 9 B 5 decay to two α-particles and proton are interpreted.

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25

Shen, Xin Pu, and Xiao Chun Wang. "Parameter Identification of a Plastic Damage Model." Applied Mechanics and Materials 599-601 (August 2014): 568–73. http://dx.doi.org/10.4028/www.scientific.net/amm.599-601.568.

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Studies on parameter identification of a plasticity-based damage constitutive model for concrete are presented in this paper. Differences between the stress-strain curves experimentally obtained and the ones numerically obtained at local level were used as the objective functional of a regularized least square method. For solving the inverse problem, the solution of the direct problem at local level obtained by a driver subroutine was embedded in the iterative solution procedure for the inverse problem proposed in this paper. The sensitivity matrix was calculated numerically by the finite difference method. Numerical examples are given for fitting the numerically obtained stress-strain curves on to a set of experimental results. Parameter identifications under various loading cases, which include uniaxial extension and triaxial compression with different confining stresses, were performed. Results indicate that the numerical scheme is stable and has reasonable accuracy.

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26

Markkanen, Tiina, Gerald Steinfeld, Natascha Kljun, Siegfried Raasch, and Thomas Foken. "A numerical case study on footprint model performance under inhomogeneous flow conditions." Meteorologische Zeitschrift 19, no. 6 (December 1, 2010): 539–47. http://dx.doi.org/10.1127/0941-2948/2010/0488.

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27

Mokhlif, Nassir D., Hussain H. Al-Kayiem, and Masri Bin Baharom. "Numerical Model to Predict Wax Crystal Size Distribution in Solvent Dewaxing Unit." International Journal of Chemical Engineering and Applications 5, no. 1 (2014): 73–78. http://dx.doi.org/10.7763/ijcea.2014.v5.354.

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28

Zhang, Junmei, Leok Poh Chua, and Ching Man Simon Yu. "NUMERICAL STUDY OF PULSATILE FLOW FOR A COMPLETE ANASTOMOSIS MODEL(Cardiovascular Mechanics)." Proceedings of the Asian Pacific Conference on Biomechanics : emerging science and technology in biomechanics 2004.1 (2004): 67–68. http://dx.doi.org/10.1299/jsmeapbio.2004.1.67.

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29

Albi, Giacomo, and Lorenzo Pareschi. "Selective model-predictive control for flocking systems." Communications in Applied and Industrial Mathematics 9, no. 2 (December 1, 2018): 4–21. http://dx.doi.org/10.2478/caim-2018-0009.

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Abstract In this paper the optimal control of alignment models composed by a large number of agents is investigated in presence of a selective action of a controller, acting in order to enhance consensus. Two types of selective controls have been presented: an homogeneous control filtered by a selective function and a distributed control active only on a selective set. As a first step toward a reduction of computational cost, we introduce a model predictive control (MPC) approximation by deriving a numerical scheme with a feedback selective constrained dynamics. Next, in order to cope with the numerical solution of a large number of interacting agents, we derive the mean-field limit of the feedback selective constrained dynamics, which eventually will be solved numerically by means of a stochastic algorithm, able to simulate effciently the selective constrained dynamics. Finally, several numerical simulations are reported to show the effciency of the proposed techniques.

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30

Telečki, Igor, Ivan Trajić, Biljana Jovanović, and Petar Beličev. "Numerical model of proton beam transport through electric scanner." Tehnika 73, no. 5 (2018): 667–74. http://dx.doi.org/10.5937/tehnika1805667t.

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31

Son, Moorak, and Edward J. Cording. "Numerical model tests of building response to excavation-induced ground movements." Canadian Geotechnical Journal 45, no. 11 (November 2008): 1611–21. http://dx.doi.org/10.1139/t08-074.

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Distortion and damage to masonry and frame structures on shallow foundations subjected to excavation-induced ground movements have been investigated using numerical model tests. The numerical tests were modeled using the two-dimensional (2-D) universal distinct element code (UDEC) version 3.1 in which each masonry unit was modeled as a block, with the contacts between blocks having stiffness and strength characteristics of mortar. The soil was modeled elastically with a stiffness selected to provide the same pressure–displacement relation for the 2-D model as that for the three-dimensional (3-D) foundation condition. To give a justifiable basis for the numerical tests, two physical model tests were simulated numerically, and the results from the numerical tests were compared with those from the physical model tests. The good agreements between the numerical simulations and physical model tests led to extended numerical studies. The studies included the effect of cracking in structures and structural types (brick and frame structures) on the building response, considering soil–structure interaction. The numerical studies indicated that the structural response to excavation-induced ground movements is highly dependent on both cracking in structures and structural types, and therefore their effects should be considered for better assessing the building response to excavation-induced ground movements.

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32

Loktionov, A. P. "Numerical differentiation in the measurement model." Izmeritel`naya Tekhnika, no. 8 (2019): 14–19. http://dx.doi.org/10.32446/0368-1025it.2019-8-14-19.

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33

Du, Z. Z., R. M. McMeeking, and A. C. F. Cocks. "A Numerical Model of Grain Growth." Zeitschrift für Metallkunde 94, no. 4 (April 2003): 368–76. http://dx.doi.org/10.3139/146.030368.

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34

Ellwood, Kevin R. J., John Baldwin, and David R. Bauer. "Numerical Model for Nitrogen Tire Inflation5." Tire Science and Technology 35, no. 4 (December 1, 2007): 300–316. http://dx.doi.org/10.2346/1.2802612.

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Abstract The scope of this study was twofold: (1) to quantify the contribution nitrogen inflation would have on oxidative aging of tires and (2) measure the improvement nitrogen tire inflation may have on inflation pressure retention. A previously developed tool for diffusion-limited oxidation was used to simulate aging behavior at 25 and 60 °C. Oven-accelerated tire aging (60 °C) data for different inflation media was used for successful validation of the model, and it was shown that aging rates for higher oxygen concentrations tend toward a constant value. For lower temperatures, the use of nitrogen was shown to produce lower oxygen concentration in the wedge and bead regions of the tire geometry considered when compared to air inflation. By using 95% pure nitrogen (that is, the actual nitrogen concentration in the tire cavity), a 25% reduction in aging rate (for the tire wedge) and a 35% reduction in the initial flux of mass out of the tire (a measure of inflation pressure retention) were calculated.

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35

Fox, N. I., and Ch G. Collier. "Physical disaggregation of numerical model rainfall." Hydrology and Earth System Sciences 4, no. 3 (September 30, 2000): 419–24. http://dx.doi.org/10.5194/hess-4-419-2000.

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Abstract. A methodology is presented for the disaggregation of numerical model fields of convective rainfall using a physically based procedure. The scheme uses surface sensible heat flux values derived from high-resolution multichannel satellite radiometer observations. The sensible heat flux values initialise a simple convective model to calculate the convective disaggregation parameter (CDP), which is theoretically proportional to the convective rainfall rate. The CDP diagnostic parameter can be derived as a one-time field if the surface characteristics are invariant, as a seasonal value may be, or it may be evaluated on a case by case basis. Once found, the CDP can be used to disaggregate numerical weather prediction (NWP) convective rainfall fields for as far ahead as such fields are produced.

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36

ASHIDA, Yasumasa, Ikkoh FUNAKI, Hiroshi YAMAKAWA, Yoshihiro KAJIMURA, and Hirotsugu KOJIMA. "Numerical Model for Pure Magnetic Sail." JOURNAL OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES 59, no. 688 (2011): 126–31. http://dx.doi.org/10.2322/jjsass.59.126.

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37

Thompson, Alex C. "NUMERICAL MODEL OF BREAKWATER WAVE FLOWS." Coastal Engineering Proceedings 1, no. 21 (January 29, 1988): 149. http://dx.doi.org/10.9753/icce.v21.149.

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A mathematical model of flow on a sloping breakwater face is described and results of calculations compared with some experimental results to show how the model can be calibrated. Flow above the surface of the slope is represented by the shallow water wave equations solved by a finite difference method. Flow within the breakwater is calculated by one of two methods. A solution of the linear seepage flow equations, again using finite differences or a simplified model of inflow can be used. Experimental results for runup and reflection coefficient are from tests performed at HRL Wallingford.

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38

Du, Z. Z., R. M. McMeeking, and A. C. F. Cocks. "A numerical model of grain growth." International Journal of Materials Research 94, no. 4 (April 1, 2003): 368–76. http://dx.doi.org/10.1515/ijmr-2003-0067.

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Abstract A numerical model for grain growth has been developed. The governing equations for the model are derived from a variational principle that enforces the balance between energy dissipation and changes of internal energy. This approach significantly simplifies previous modelling of grain growth by replacing a curved grain boundary with several straight lines and relaxing constraints on triple point angles. Such simplifications provide a basis for a finite element method by reducing the analysis of a complex network of interconnected curved lines to the motion of interacting points. In the finite element formulation two approaches are used, namely an element based formulation and a node based formulation. In the latter case, the properties of the elements are lumped together at their common nodes. Such an approach allows the nodal velocity to be determined independently of the forces on other nodes in a lumped mobility methodology, leading to a further reduction of computer time. Several planar grain networks of Voronoi polygons have been studied. The evolution of the grain structures determined from these two approaches is found to exhibit the same trends as those obtained using other models published in the literature. Owing to its simplicity, the node based formulation is recommended.

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39

Asanov, E. E., S. A. Zuyev, G. V. Kilessa, and N. I. Slipchenko. "NUMERICAL MODEL FOR METAL-SEMICONDUCTOR CONTACT." Telecommunications and Radio Engineering 72, no. 17 (2013): 1575–87. http://dx.doi.org/10.1615/telecomradeng.v72.i17.30.

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40

Donnelly, C., M. Larson, and H. Hanson. "A numerical model of coastal overwash." Proceedings of the Institution of Civil Engineers - Maritime Engineering 162, no. 3 (September 2009): 105–14. http://dx.doi.org/10.1680/maen.2009.162.3.105.

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41

Manakova, N. A., and K. V. Vasyuchkova. "Numerical investigation of thegeneralized Hoﬀ model." Vestnik of Samara University. Natural Science Series 21, no. 6 (May 17, 2017): 93–97. http://dx.doi.org/10.18287/2541-7525-2015-21-6-93-97.

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The work is devoted to the numerical investigation of the generalized Hoﬀ model. Hoﬀ equation models the dynamics of buckling construction of I-beams under a constant load. Result of existence and uniqueness of solution to the Showalter - Sidorov problem for the investigated model is formulated. This equation is a semilinear Sobolev type equation. Sobolev type equations constitute a vast area of non-classical equations of mathematical physics. Based on the theoretical results there was developed the algorithm of numerical solution of the problem.

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42

Hukuda, Hisashi, Xinyu Guo, and Toshio Yamagata. "A Numerical Model Study of "Furiwakeshio"." Oceanography in Japan 11, no. 5 (2002): 513–27. http://dx.doi.org/10.5928/kaiyou.11.513.

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43

Kantha, Lakshmi H. "A numerical model of Arctic leads." Journal of Geophysical Research 100, no. C3 (1995): 4653. http://dx.doi.org/10.1029/94jc02348.

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44

Dietrich, Felix, Gerta Köster, and Hans-Joachim Bungartz. "Numerical Model Construction with Closed Observables." SIAM Journal on Applied Dynamical Systems 15, no. 4 (January 2016): 2078–108. http://dx.doi.org/10.1137/15m1043613.

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45

Demenkov, A. G., B. B. Ilyushin, and G. G. Chernykh. "Numerical model of round turbulent jets." Journal of Engineering Thermophysics 18, no. 1 (March 2009): 49–56. http://dx.doi.org/10.1134/s1810232809010068.

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46

Boellinghaus, Th, and H. Hoffmeister. "Numerical Model for Hydrogen-Assisted Cracking." CORROSION 56, no. 6 (June 2000): 611–22. http://dx.doi.org/10.5006/1.3280564.

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47

Holz, Richard G., Ahmed A. Hassan, and Helen L. Reed. "Numerical model for circulation-control flows." AIAA Journal 32, no. 4 (April 1994): 701–7. http://dx.doi.org/10.2514/3.12042.

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48

Baldonedo, Jacobo, José R. Fernández, and Abraham Segade. "Numerical Analysis of an Osseointegration Model." Mathematics 8, no. 1 (January 5, 2020): 87. http://dx.doi.org/10.3390/math8010087.

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In this work, we study a bone remodeling model used to reproduce the phenomenon of osseointegration around endosseous implants. The biological problem is written in terms of the densities of platelets, osteogenic cells, and osteoblasts and the concentrations of two growth factors. Its variational formulation leads to a strongly coupled nonlinear system of parabolic variational equations. An existence and uniqueness result of this variational form is stated. Then, a fully discrete approximation of the problem is introduced by using the finite element method and a semi-implicit Euler scheme. A priori error estimates are obtained, and the linear convergence of the algorithm is derived under some suitable regularity conditions and tested with a numerical example. Finally, one- and two-dimensional numerical results are presented to demonstrate the accuracy of the algorithm and the behavior of the solution.

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49

Dalík, Josef, Josef Daněčcek, and Jiří Vala. "Numerical Solution of the Kiessl Model." Applications of Mathematics 45, no. 1 (February 2000): 3–17. http://dx.doi.org/10.1023/a:1022232632054.

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50

Moczulak, Bartosz, Wojciech Miąskowski, Krzysztof Nalepa, and Jakub Jasiński. "Numerical model of liquid phase mixer." Mechanik 91, no. 7 (July 9, 2018): 555–57. http://dx.doi.org/10.17814/mechanik.2018.7.82.

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Presented is the course of conduct during modeling of phenomena occurring in a mixer intended for mixing liquids. Issues related to the numerical description of phenomena occurring in this type of constructions are discussed, the method of modeling the mixing process for one type of liquid by the analysis of several types of mixing arms is presented and the results of simulation research are discussed.

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