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Journal articles on the topic 'Numerical implementation'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 June 2024

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1

Mikeš, Karel, and Milan Jirásek. "Free Warping Analysis and Numerical Implementation." Applied Mechanics and Materials 825 (February 2016): 141–48. http://dx.doi.org/10.4028/www.scientific.net/amm.825.141.

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This article deals with the mathematical description and numerical implementation of the free warping problem. The solution of the warping problem is given by a warping function obtained by solving the Laplace equation with a corresponding boundary condition. An analytical solution is available only for a limited number of specific cross-sectional shapes such as ellipse or rectangle. For the solution of a general cross section, the Laplace equation must be solved numerically by the finite element method. From a mathematical point of view, the free warping problem can be described in the same way as the heat transfer phenomena, but in the numerical implementation, there are several features specific to warping analysis.The solution algorithm has been implemented in the OOFEM open-source finite element code [1] and verification has been done on several examples with known analytical solutions.

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2

Nairn, John A. "Numerical implementation of imperfect interfaces." Computational Materials Science 40, no. 4 (October 2007): 525–36. http://dx.doi.org/10.1016/j.commatsci.2007.02.010.

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3

Lee, Chun Jin. "The numerical implementation of risk." Korean Journal of Computational & Applied Mathematics 2, no. 2 (September 1995): 53–61. http://dx.doi.org/10.1007/bf03008963.

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4

Linderberg, Jan, So/ren B. Padkjær, Yngve Öhrn, and Behnam Vessal. "Numerical implementation of reactive scattering theory." Journal of Chemical Physics 90, no. 11 (June 1989): 6254–65. http://dx.doi.org/10.1063/1.456342.

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5

Doong, T., and I. Mayergoyz. "On numerical implementation of hysteresis models." IEEE Transactions on Magnetics 21, no. 5 (September 1985): 1853–55. http://dx.doi.org/10.1109/tmag.1985.1063923.

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6

JAUSLIN, H. R. "NUMERICAL IMPLEMENTATION OF A K.A.M. ALGORITHM." International Journal of Modern Physics C 04, no. 02 (April 1993): 317–22. http://dx.doi.org/10.1142/s0129183193000331.

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We discuss a numerical implementation of a K.A.M. algorithm to determine invariant tori, for systems that are quadratic in the action variables. The method has the advantage that the iteration procedure does not produce higher order terms in the actions, allowing thus a systematic control of the convergence.

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7

Einziger, P. D. "Numerical implementation of the Gabor representation." Electronics Letters 24, no. 13 (1988): 810. http://dx.doi.org/10.1049/el:19880551.

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8

Cardelli, E., E. Della Torre, and A. Faba. "Numerical Implementation of the DPC Model." IEEE Transactions on Magnetics 45, no. 3 (March 2009): 1186–89. http://dx.doi.org/10.1109/tmag.2009.2012549.

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9

Low, K. H. "Numerical implementation of structural dynamics analysis." Computers & Structures 65, no. 1 (October 1997): 109–25. http://dx.doi.org/10.1016/s0045-7949(95)00338-x.

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10

Babolian, E., and A. Davari. "Numerical implementation of Adomian decomposition method." Applied Mathematics and Computation 153, no. 1 (May 2004): 301–5. http://dx.doi.org/10.1016/s0096-3003(03)00646-5.

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11

Ledoit, Olivier, and Michael Wolf. "Numerical implementation of the QuEST function." Computational Statistics & Data Analysis 115 (November 2017): 199–223. http://dx.doi.org/10.1016/j.csda.2017.06.004.

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12

Sprecher, David A. "A Numerical Implementation of Kolmogorov's Superpositions." Neural Networks 9, no. 5 (July 1996): 765–72. http://dx.doi.org/10.1016/0893-6080(95)00081-x.

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13

Egorchenkov, R. A., and Yu A. Kravtsov. "Numerical implementation of complex geometrical optics." Radiophysics and Quantum Electronics 43, no. 7 (July 2000): 569–75. http://dx.doi.org/10.1007/bf02677088.

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14

Ling, F. H., and G. W. Bao. "A numerical implementation of Melnikov's method." Physics Letters A 122, no. 8 (June 1987): 413–17. http://dx.doi.org/10.1016/0375-9601(87)90739-0.

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15

Skála, Jan, and Miroslav Bárta. "LSFEM Implementation of MHD Numerical Solver." Applied Mathematics 03, no. 11 (2012): 1842–50. http://dx.doi.org/10.4236/am.2012.331250.

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16

Nairn, John A., Chad C. Hammerquist, and Yamina E. Aimene. "Numerical implementation of anisotropic damage mechanics." International Journal for Numerical Methods in Engineering 112, no. 12 (June 27, 2017): 1848–68. http://dx.doi.org/10.1002/nme.5585.

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17

Darve, Eric. "The Fast Multipole Method: Numerical Implementation." Journal of Computational Physics 160, no. 1 (May 2000): 195–240. http://dx.doi.org/10.1006/jcph.2000.6451.

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18

Umrzoqova, Kommuna Xursanovna. "Numerical Technologies In Economy." American Journal of Interdisciplinary Innovations and Research 03, no. 05 (May 7, 2021): 100–104. http://dx.doi.org/10.37547/tajiir/volume03issue05-18.

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This article deals with the several key technologies of the numerical economy, such as BIMPLM,loT, SRM, BIG DATA.. Analyzed the advantages and the risks of the implementation of numerical technologies in economy and the role of numerical technologies in the development of economy.

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19

Qi, Ai Xue, Cheng Liang Zhang, and Guang Yi Wang. "Memristor Oscillators and its FPGA Implementation." Advanced Materials Research 383-390 (November 2011): 6992–97. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.6992.

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This paper presents a method that utilizes a memristor to replace the non-linear resistance of typical Chua’s circuit for constructing a chaotic system. The improved circuit is numerically simulated in the MATLAB condition, and its hardware implementation is designed using field programmable gate array (FPGA). Comparing the experimental results with the numerical simulation, the two are the very same, and be able to generate chaotic attractor.

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20

Ivanyuk, V. A., and V. A. Fedorchuk. "Vector-Matrix Method of Numerical Implementation of the Polynomial Integral Volterra Operators." Mathematical and computer modelling. Series: Technical sciences 1, no. 20 (September 20, 2019): 40–50. http://dx.doi.org/10.32626/2308-5916.2019-20.40-50.

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21

Grewal, Mohinder S., and James Kain. "Kalman Filter Implementation With Improved Numerical Properties." IEEE Transactions on Automatic Control 55, no. 9 (September 2010): 2058–68. http://dx.doi.org/10.1109/tac.2010.2042986.

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22

Babiuc, M. C., S. Husa, D. Alic, I. Hinder, C. Lechner, E. Schnetter, B. Szilágyi, et al. "Implementation of standard testbeds for numerical relativity." Classical and Quantum Gravity 25, no. 12 (June 2, 2008): 125012. http://dx.doi.org/10.1088/0264-9381/25/12/125012.

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23

Breidbach, J., and L. S. Cederbaum. "Migration of holes: Numerical algorithms and implementation." Journal of Chemical Physics 126, no. 3 (January 21, 2007): 034101. http://dx.doi.org/10.1063/1.2428292.

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24

Mayergoyz, I. D., and A. A. Adly. "Numerical implementation of the feedback Preisach model." IEEE Transactions on Magnetics 28, no. 5 (September 1992): 2605–7. http://dx.doi.org/10.1109/20.179571.

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25

de Freitas, J. A. Teixeira, and C. Cismaşiu. "Numerical implementation of hybrid-Trefftz displacement elements." Computers & Structures 73, no. 1-5 (October 1999): 207–25. http://dx.doi.org/10.1016/s0045-7949(98)00271-5.

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26

Tiwari, R. C. "Simplified Numerical Implementation in Slope Stability Modeling." International Journal of Geomechanics 15, no. 3 (June 2015): 04014051. http://dx.doi.org/10.1061/(asce)gm.1943-5622.0000399.

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27

Foote, W., J. Kraemer, and G. Foster. "APL2 implementation of numerical asset pricing models." ACM SIGAPL APL Quote Quad 18, no. 2 (December 1987): 120–25. http://dx.doi.org/10.1145/377719.55643.

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28

Sprecher, David A. "A Numerical Implementation of Kolmogorov's Superpositions II." Neural Networks 10, no. 3 (April 1997): 447–57. http://dx.doi.org/10.1016/s0893-6080(96)00073-1.

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29

Litvinov, G. L., and E. V. Maslova. "Universal numerical algorithms and their software implementation." Programming and Computer Software 26, no. 5 (September 2000): 275–80. http://dx.doi.org/10.1007/bf02759321.

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30

Stock, J. D. R., I. H. Dunbar, S. A. Ramsdale, S. Simons, and M. M. R. Williams. "The numerical implementation of multicomponent aerosol modelling." Annals of Nuclear Energy 14, no. 1 (January 1987): 1–8. http://dx.doi.org/10.1016/0306-4549(87)90034-x.

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31

Benad, Justus. "FAST NUMERICAL IMPLEMENTATION OF THE MDR TRANSFORMATIONS." Facta Universitatis, Series: Mechanical Engineering 16, no. 2 (August 1, 2018): 127. http://dx.doi.org/10.22190/fume180526023b.

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In the present paper a numerical implementation technique for the transformations of the Method of Dimensionality Reduction (MDR) is described. The MDR has become, in the past few years, a standard tool in contact mechanics for solving axially-symmetric contacts. The numerical implementation of the integral transformations of the MDR can be performed in several different ways. In this study, the focus is on a simple and robust algorithm on the uniform grid using integration by parts, a central difference scheme to obtain the derivatives, and a trapezoidal rule to perform the summation. The results are compared to the analytical solutions for the contact of a cone and the Hertzian contact. For the tested examples, the proposed method gives more accurate results with the same number of discretization points than other tested numerical techniques. The implementation method is further tested in a wear simulation of a heterogeneous cylinder composed of rings of different material having the same elastic properties but different wear coefficients. These discontinuous transitions in the material properties are handled well with the proposed method.

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32

Sgró, Mario A., Dante J. Paz, and Manuel Merchán. "Anisotropic halo model: implementation and numerical results." Monthly Notices of the Royal Astronomical Society 433, no. 1 (May 29, 2013): 787–95. http://dx.doi.org/10.1093/mnras/stt773.

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33

Alamir, M., and N. Marchand. "Numerical Stabilisation of Non-linear Systems: Exact Theory and Approximate Numerical Implementation." European Journal of Control 5, no. 1 (January 1999): 87–97. http://dx.doi.org/10.1016/s0947-3580(99)70143-3.

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34

Akat, M., R. Kosker, and A. Sirma. "On the numerical schemes for Langevin-type equations." BULLETIN OF THE KARAGANDA UNIVERSITY-MATHEMATICS 99, no. 3 (September 30, 2020): 62–74. http://dx.doi.org/10.31489/2020m3/62-74.

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In this paper, a numerical approach is proposed based on the variation-of-constants formula for the numerical discretization Langevin-type equations. Linear and non-linear cases are treated separately. The proofs of convergence have been provided for the linear case, and the numerical implementation has been executed for the non-linear case. The order one convergence for the numerical scheme has been shown both theoretically and numerically. The stability of the numerical scheme has been shown numerically and depicted graphically.

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35

Murawski, K., K. Murawski, and P. Stpiczyński. "Implementation of MUSCL-Hancock method into the C++ code for the Euler equations." Bulletin of the Polish Academy of Sciences: Technical Sciences 60, no. 1 (March 1, 2012): 45–53. http://dx.doi.org/10.2478/v10175-012-0008-7.

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Implementation of MUSCL-Hancock method into the C++ code for the Euler equationsIn this paper we present implementation of the MUSCL-Hancock method for numerical solutions of the Euler equations. As a result of the internal complexity of these equations solving them numerically is a formidable task. With the use of the original C++ code, we developed and presented results of a numerical test that was performed. This test shows that our code copes very well with this task.

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36

KESICI, EMINE, BEATRICE PELLONI, TRISTAN PRYER, and DAVID SMITH. "A numerical implementation of the unified Fokas transform for evolution problems on a finite interval." European Journal of Applied Mathematics 29, no. 3 (November 23, 2017): 543–67. http://dx.doi.org/10.1017/s0956792517000316.

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We present the numerical solution of two-point boundary value problems for a third-order linear PDE, representing a linear evolution in one space dimension. To our knowledge, the numerical evaluation of the solution so far could only be obtained by a time-stepping scheme, that must also take into account the issue, generically non-trivial, of the imposition of the boundary conditions. Instead of computing the evolution numerically, we evaluate the novel solution representation formula obtained by the unified transform, also known as Fokas transform. This representation involves complex line integrals, but in order to evaluate these integrals numerically, it is necessary to deform the integration contours using appropriate deformation mappings. We formulate a strategy to implement effectively this deformation, which allows us to obtain accurate numerical results.

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37

Adytia, Didit. "Performansi Implementasi Numerik Metode Pseudo Spectral pada Model Gelombang 1D Boussinesq." Indonesian Journal on Computing (Indo-JC) 2, no. 1 (September 14, 2017): 101. http://dx.doi.org/10.21108/indojc.2017.2.1.164.

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<p>In the design of a numerical wave tank, it is necessary to use an accurate wave model as well as to choose an accurate and efficient numerical scheme for implementing the model. In this paper, we use a Pseudo-Spectral (PS) implementationfor a wave model so called Variational Boussinesq Model. The implementation is aimed to obtain a higher time efficiency in the calculation of wave simulations. The performance of the PS implementation is compared in CPU-time with a Finite Element (FE) implementation of the wave model for simulating a focusing wave group. Results of both implementations give a good agreement with wave data from laboratory experiment. The PS-implementation gives more efficient CPU-time compared to the FE-implementation.</p>

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38

He, Cuiyu, Weiwei Hu, and Lin Mu. "Optimal control of convection-cooling and numerical implementation." Computers & Mathematics with Applications 92 (June 2021): 48–61. http://dx.doi.org/10.1016/j.camwa.2021.03.020.

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39

Neulybin, Sergey, Gleb Permyakov, Dmitry Trushnikov, Iuri Shchitsyn, Vladimir Belenkiy, and Dmitry Belinin. "PLASMA SURFACING: MATHEMATICAL MODEL, NUMERICAL IMPLEMENTATION AND VERIFICATION." PNIPU Bulletin. The mechanical engineering, materials science., no. 4 (December 30, 2017): 7–23. http://dx.doi.org/10.15593/2224-9877/2017.4.01.

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40

Chibiryakov, Valerii, Anatolii Stankevich, Olexandr Kosheviy, Dmitriy Levkivskiy, Anna Krasneеva, Dmitriy Poshivach, Anton Chubarev, Oleksyi Shorin, Maryna Yansons, and Yuliia Sovich. "NUMERICAL IMPLEMENTATION OF THE MODIFIED METHOD OF LINES." Urban development and spatial planning, no. 74 (June 4, 2020): 341–59. http://dx.doi.org/10.32347/2076-815x.2020.74.341-359.

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41

Rosca, V. E., and V. M. A. Leitāo. "Numerical Implementation of Meshless Methods for Beam Problems." Archives of Civil Engineering 58, no. 2 (June 1, 2012): 175–84. http://dx.doi.org/10.2478/v.10169-012-0010-3.

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Abstract For solving a partial different equation by a numerical method, a possible alternative may be either to use a mesh method or a meshless method. A flexible computational procedure for solving 1D linear elastic beam problems is presented that currently uses two forms of approximation function (moving least squares and kernel approximation functions) and two types of formulations, namely the weak form and collocation technique, respectively, to reproduce Element Free Galerkin (EFG) and Smooth Particle Hydrodynamics (SPH) meshless methods. The numerical implementation for beam problems of these two formulations is discussed and numerical tests are presented to illustrate the difference between the formulations.

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42

Gevorkyan, M. N., A. V. Demidova, T. R. Velieva, A. V. Korol’kova, and D. S. Kulyabov. "Analytical-Numerical Implementation of Polyvector Algebra in Julia." Programming and Computer Software 48, no. 1 (February 2022): 49–58. http://dx.doi.org/10.1134/s0361768822010054.

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43

Abbasbandy, Saeid, and Mohammad Ali Fariborzi Araghi. "Numerical Solution of Improper Integrals with Valid Implementation." Mathematical and Computational Applications 7, no. 1 (April 1, 2002): 83–91. http://dx.doi.org/10.3390/mca7010083.

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44

Predescu, Cristian, Dubravko Sabo, and J. D. Doll. "Numerical implementation of some reweighted path integral methods." Journal of Chemical Physics 119, no. 9 (September 2003): 4641–54. http://dx.doi.org/10.1063/1.1595640.

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45

Cardelli, E., E. Della Torre, and E. Pinzaglia. "Numerical implementation of the radial vector hysteresis model." IEEE Transactions on Magnetics 42, no. 4 (April 2006): 527–30. http://dx.doi.org/10.1109/tmag.2006.871945.

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46

Vajda, F., and E. Della Torre. "Efficient numerical implementation of complete-moving-hysteresis models." IEEE Transactions on Magnetics 29, no. 2 (March 1993): 1532–37. http://dx.doi.org/10.1109/20.250695.

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47

Sandiford, Dan, and Louis Moresi. "Improving subduction interface implementation in dynamic numerical models." Solid Earth 10, no. 3 (June 28, 2019): 969–85. http://dx.doi.org/10.5194/se-10-969-2019.

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Abstract. Numerical subduction models often implement an entrained weak layer (WL) to facilitate decoupling of the slab and upper plate. This approach is attractive in its simplicity, and can provide stable, asymmetric subduction systems that persist for many tens of millions of years. In this study we undertake a methodological analysis of the WL approach, and use these insights to guide improvements to the implementation. The issue that primarily motivates the study is the emergence of significant spatial and temporal thickness variations within the WL. We show that these variations are mainly the response to volumetric flux gradients, caused by the change in boundary conditions as the WL material enters and exits the zone of decoupling. The time taken to reach a quasi-equilibrium thickness profile will depend on the total plate convergence, and is around 7 Myr for the models presented here. During the transient stage, width variations along the WL can exceed 4×, which may impact the effective strength of the interface, through physical effects if the rheology is linear, or simply if the interface becomes inadequately numerically resolved. The transient stage also induces strong sensitivity to model resolution. By prescribing a variable-thickness WL at the outset of the model, and by controlling the limits of the layer thickness during the model evolution, we find improved stability and resolution convergence of the models.

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48

Bratov, V. A., N. A. Kazarinov, and Y. V. Petrov. "Numerical implementation of the incubation time fracture criterion." Journal of Physics: Conference Series 653 (November 11, 2015): 012049. http://dx.doi.org/10.1088/1742-6596/653/1/012049.

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49

Prieur, Jean, and Gilles Rahier. "Aeroacoustic integral methods, formulation and efficient numerical implementation." Aerospace Science and Technology 5, no. 7 (October 2001): 457–68. http://dx.doi.org/10.1016/s1270-9638(01)01123-3.

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50

Herrmann, Leonard R., Victor Kaliakin, C. K. Shen, Kyran D. Mish, and Zheng‐Yu Zhu. "Numerical Implementation of Plasticity Model for Cohesive Soils." Journal of Engineering Mechanics 113, no. 4 (April 1987): 500–519. http://dx.doi.org/10.1061/(asce)0733-9399(1987)113:4(500).

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