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Journal articles on the topic 'Code de simulation électromagnétique'

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Published: 25 May 2024

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1

-Degauque, Professeur Pierre. "Compatibilité électromagnétique : normes, mesures, simulation." Revue de l'Electricité et de l'Electronique -, no. 05 (1995): 12. http://dx.doi.org/10.3845/ree.1995.048.

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2

-JECKO, Bernard. "Simulation numérique et compatibilité électromagnétique." Revue de l'Electricité et de l'Electronique -, no. 05 (1995): 31. http://dx.doi.org/10.3845/ree.1995.052.

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3

-Akoun, Gilles. "Simulation de l'agression électromagnétique sur les composants." Revue de l'Electricité et de l'Electronique -, no. 04 (1997): 91. http://dx.doi.org/10.3845/ree.1997.055.

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4

-SOUBEYRAN, Amaury. "Simulation de l'émission électromagnétique des composants avec le logiciel EMC2000." Revue de l'Electricité et de l'Electronique -, no. 07 (2000): 59. http://dx.doi.org/10.3845/ree.2000.071.

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5

Burais, Noël, and Rémy Prost. "Maillage 3D de structures anatomiques pour la simulation électromagnétique et thermique." European Journal of Electrical Engineering 14, no. 1 (February 2011): 91–122. http://dx.doi.org/10.3166/ejee.14.91-122.

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6

Armenean, Mircea, André Briguet, and Hervé Saint-Jalmes. "Conception de microbobines radiofréquence pour la RMN : apport d’une simulation électromagnétique." Comptes Rendus Biologies 325, no. 4 (April 2002): 457–63. http://dx.doi.org/10.1016/s1631-0691(02)01449-x.

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7

Sundberg, Mikaela. "Organizing Simulation Code Collectives." Science & Technology Studies 23, no. 1 (January 1, 2010): 37–57. http://dx.doi.org/10.23987/sts.55256.

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This article examines the ways researchers develop and use computer programs for numerical simulations and the different social relationships that are involved in creating the frames for these activities. On the basis of ethnographic case studies of numerical simulation practice in astrophysics, oceanography, and meteorology, including climate modelling, the present article discusses how work with simulation codes can be discussed by means of a typology of simulation code collectives. This typology provides a systematic account of how a particular and increasingly important form of software development and use takes place in science. It also contributes to current discussions on the relation between producers and users of technology by suggesting that the defi nition of them as empirical categories can be understood through the social relationships that the people (simulationists) working with them are embedded in.

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8

Senger, Brenda, and Lynn Stapleton. "Multi-institutional Code Simulation Training." Clinical Simulation in Nursing 5, no. 3 (May 2009): e149. http://dx.doi.org/10.1016/j.ecns.2009.04.070.

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9

Zhu, Xiangqian, and Wansuk Yoo. "Verification of a Numerical Simulation Code for Underwater Chain Mooring." Archive of Mechanical Engineering 63, no. 2 (June 1, 2016): 231–44. http://dx.doi.org/10.1515/meceng-2016-0013.

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Abstract Numerical simulation is an economical and effective method in the field of marine engineering. The dynamics of mooring cables has been analysed by a numerical simulation code that was created on a basis of a new element frame. This paper aims at verifying the accuracy of the numerical simulation code through comparisons with both the real experiments and a commercial simulation code. The real experiments are carried out with a catenary chain mooring in a water tank. The experimental results match the simulation results by the numerical simulation code well. Additionally, a virtual simulation of a large size chain mooring in ocean is carried out by both the numerical simulation code and a commercial simulation code. The simulation results by the numerical simulation code match those by the commercial simulation code well. Thus, the accuracy of the numerical simulation code for underwater chain mooring is verified by both the real experiments and commercial simulation code.

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10

Harya Dananjaya, Raden. "Tsunami simulation using particle method." MATEC Web of Conferences 195 (2018): 05013. http://dx.doi.org/10.1051/matecconf/201819505013.

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Tsunami is a natural disaster that have resulted in dreadful damages over time. Extensive researches have been conducted to scrutinize and counteract the natural hazard using three major research components which are: field monitoring, laboratory tests, and numerical methods. However, laboratory tests are high-priced and arduous. Numerical simulation overcomes these drawbacks and can be utilized in collaboration with laboratory tests. Recently, newly introduced meshless Lagrangian particle method called Smoothed Particle Hydrodynamics (SPH) has gained attention. In this paper, SPH method has been employed to simulate tsunami. A SPH code is developed from scratch. To validate the code, a traditional dam break simulation is conducted. Lastly, a tsunami model is simulated using the developed SPH code and compared with past experimental data. The results indicate that the code is in accordance with previous experimental data and numerical simulation. Whereby, there’s been a slight deviation arises in tsunami simulation. The velocity of the code is relatively less to that of the experimental data. Such inconsistencies could emerge due to a number of reasons, i.e. the choice of the SPH parameters and model simplification. Generally, the developed SPH code had a satisfactory performance to model tsunami and dam-break problem.

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11

More, Richard M. "Particle simulation code for fusion ignition." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 733 (January 2014): 207–10. http://dx.doi.org/10.1016/j.nima.2013.05.067.

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12

Umeda, Takayuki, Naru Tsujine, and Yasuhiro Nariyuki. "Vlasov code simulation of contact discontinuities." Physics of Plasmas 26, no. 10 (October 2019): 102107. http://dx.doi.org/10.1063/1.5100314.

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13

Shishlo, Andrei, Sarah Cousineau, Jeffrey Holmes, and Timofey Gorlov. "The Particle Accelerator Simulation Code PyORBIT." Procedia Computer Science 51 (2015): 1272–81. http://dx.doi.org/10.1016/j.procs.2015.05.312.

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14

Büchner, Jörg, and Nina Elkina. "Vlasov Code Simulation of Anomalous Resistivity." Space Science Reviews 121, no. 1-4 (November 2005): 237–52. http://dx.doi.org/10.1007/s11214-006-6542-6.

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15

Craparo, J. C., and E. F. Thacher. "A solar-electric vehicle simulation code." Solar Energy 55, no. 3 (September 1995): 221–34. http://dx.doi.org/10.1016/0038-092x(95)00037-r.

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16

Yi-Peng, Sun, Gao Jie, and Guo Zhi-Yu. "A Code for Bunch Lengthening Simulation." Chinese Physics Letters 25, no. 2 (February 2008): 462–64. http://dx.doi.org/10.1088/0256-307x/25/2/030.

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17

Siiskonen, T., and R. Pöllänen. "Advanced simulation code for alpha spectrometry." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 550, no. 1-2 (September 2005): 425–34. http://dx.doi.org/10.1016/j.nima.2005.05.045.

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18

Nieter, Chet, and John R. Cary. "VORPAL: a versatile plasma simulation code." Journal of Computational Physics 196, no. 2 (May 2004): 448–73. http://dx.doi.org/10.1016/j.jcp.2003.11.004.

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19

Calder, A. C., B. Fryxell, T. Plewa, R. Rosner, L. J. Dursi, V. G. Weirs, T. Dupont, et al. "On Validating an Astrophysical Simulation Code." Astrophysical Journal Supplement Series 143, no. 1 (November 2002): 201–29. http://dx.doi.org/10.1086/342267.

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20

Springel, Volker. "The cosmological simulation code gadget-2." Monthly Notices of the Royal Astronomical Society 364, no. 4 (December 2005): 1105–34. http://dx.doi.org/10.1111/j.1365-2966.2005.09655.x.

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21

Craparo, J. C., and E. F. Thacher. "A solar-electric vehicle simulation code." Fuel and Energy Abstracts 37, no. 3 (May 1996): 201. http://dx.doi.org/10.1016/0140-6701(96)88796-0.

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22

Xu, Zhiqian, Cui Meng, Yunsheng Jiang, Ping Wu, and Maoxing Zhang. "A Code Verification for the Cavity SGEMP Simulation Code LASER-SGEMP." IEEE Transactions on Nuclear Science 68, no. 6 (June 2021): 1251–57. http://dx.doi.org/10.1109/tns.2021.3078739.

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23

Tamura, Shinichi, Yoshi Nishitani, Chie Hosokawa, Tomomitsu Miyoshi, and Hajime Sawai. "Simulation of Code Spectrum and Code Flow of Cultured Neuronal Networks." Computational Intelligence and Neuroscience 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/7186092.

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It has been shown that, in cultured neuronal networks on a multielectrode, pseudorandom-like sequences (codes) are detected, and they flow with some spatial decay constant. Each cultured neuronal network is characterized by a specific spectrum curve. That is, we may consider the spectrum curve as a “signature” of its associated neuronal network that is dependent on the characteristics of neurons and network configuration, including the weight distribution. In the present study, we used an integrate-and-fire model of neurons with intrinsic and instantaneous fluctuations of characteristics for performing a simulation of a code spectrum from multielectrodes on a 2D mesh neural network. We showed that it is possible to estimate the characteristics of neurons such as the distribution of number of neurons around each electrode and their refractory periods. Although this process is a reverse problem and theoretically the solutions are not sufficiently guaranteed, the parameters seem to be consistent with those of neurons. That is, the proposed neural network model may adequately reflect the behavior of a cultured neuronal network. Furthermore, such prospect is discussed that code analysis will provide a base of communication within a neural network that will also create a base of natural intelligence.

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24

Qiu, Qinglai, Bingjia Xiao, Yong Guo, Lei Liu, Zhe Xing, and D. A. Humphreys. "Simulation of EAST vertical displacement events by tokamak simulation code." Nuclear Fusion 56, no. 10 (August 23, 2016): 106029. http://dx.doi.org/10.1088/0029-5515/56/10/106029.

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25

Guo, Y., A. Pironti, L. Liu, B. J. Xiao, R. Albanese, R. Ambrosino, Z. P. Luo, et al. "Simulation of EAST quasi-snowflake discharge by tokamak simulation code." Fusion Engineering and Design 101 (December 2015): 101–10. http://dx.doi.org/10.1016/j.fusengdes.2015.10.010.

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26

Ricci, P., F. D. Halpern, S. Jolliet, J. Loizu, A. Mosetto, A. Fasoli, I. Furno, and C. Theiler. "Simulation of plasma turbulence in scrape-off layer conditions: the GBS code, simulation results and code validation." Plasma Physics and Controlled Fusion 54, no. 12 (November 21, 2012): 124047. http://dx.doi.org/10.1088/0741-3335/54/12/124047.

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27

Vögler, A., S. Shelyag, M. Schüssler, F. Cattaneo, T. Emonet, and T. Linde. "Simulation of Solar Magnetoconvection." Symposium - International Astronomical Union 210 (2003): 157–67. http://dx.doi.org/10.1017/s0074180900133339.

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We present a new 3D MHD code for the simulation of solar magnetoconvection. The code is designed for use on parallel computers and in the choice of methods emphasis has been laid on efficient parallelization. We give a description of the numerical methods and discuss the non-local and non-grey treatment of the radiative transfer. Test calculations underlining the importance of non-grey effects and first results of the simulation of a solar plage region are shown.

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28

Williams, Dan, and Luc Bauwens. "Simulation of Compressible Flow on a Massively Parallel Architecture." Scientific Programming 4, no. 3 (1995): 193–201. http://dx.doi.org/10.1155/1995/453684.

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This article describes the porting and optimization of an explicit, time-dependent, computational fluid dynamics code on an 8,192-node MasPar MP-1. The MasPar is a very fine-grained, single instruction, multiple data parallel computer. The code uses the flux-corrected transport algorithm. We describe the techniques used to port and optimize the code, and the behavior of a test problem. The test problem used to benchmark the flux-corrected transport code on the MasPar was a two-dimensional exploding shock with periodic boundary conditions. We discuss the performance that our code achieved on the MasPar, and compare its performance on the MasPar with its performance on other architectures. The comparisons show that the performance of the code on the MasPar is slightly better than on a CRAY Y-MP for a functionally equivalent, optimized two-dimensional code.

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29

Mora, Adan, Avery Smith, Shawna Robertson, Christine Renfro, and Cristie Columbus. "Does Simulation Training in Obstetric Code Blue Improve Code Team Comfort Levels?" Chest 148, no. 4 (October 2015): 476A. http://dx.doi.org/10.1378/chest.2257675.

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30

Krassilnikov, Mikhail, Alexandre Novokhatski, and Thomas Weiland. "TTF Beam dynamics simulation by V-code." International Journal of Applied Electromagnetics and Mechanics 14, no. 1-4 (December 20, 2002): 249–53. http://dx.doi.org/10.3233/jae-2002-494.

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31

Faisal, Shafiqul Islam, and Abi Muttaquin Bin Jalal Bayar. "Gamma Shielding Experiment Simulation utilizing MCNPX Code." Journal of Engineering Science 12, no. 2 (July 8, 2021): 11–21. http://dx.doi.org/10.3329/jes.v12i2.54627.

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Experimental investigation requires materials, radiation sources, and test arrangements with a high monetary financial plan. Furthermore, radiation exposure involves people during the experiment. On the contrary, the simulation technique for examining radiation interactions is radio-logically safer, less timeconsuming, cost-effective, and applicable for all desired radiation sources. Through 48.86 mCi 662 keV Caesium-137 gamma-ray source; shielding experiment as well as simulation of it with MCNPX were performed for three shielding materials Lead, Copper, and Aluminum. These materials were placed in front of the gamma source and the emergent radiation was counted in a Geiger- Muller detector to understand the attenuation quality of these materials to each other. These courses of action were simulated utilizing the MCNPX code version 2.7.0 and the results likewise gave and looked at that of the experiment. There are huge similarities of shielding behavior between MCNPX simulation and experiments for the three absorbing materials. The modeled geometry of this MCNPX simulation could be used for future approaches of new designs and structures of radiation shielding, especially where no analogous experimental data exist Journal of Engineering Science 12(2), 2021, 11-21

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32

Morey, I. J., and C. K. Birdsall. "Traveling-wave-tube simulation: The IBC code." IEEE Transactions on Plasma Science 18, no. 3 (June 1990): 482–89. http://dx.doi.org/10.1109/27.55918.

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33

Campos, Isabel, Patrick Fritzsch, Martin Hansen, Marina Krstić Marinković, Agostino Patella, Alberto Ramos, and Nazario Tantalo. "openQ*D simulation code for QCD+QED." EPJ Web of Conferences 175 (2018): 09005. http://dx.doi.org/10.1051/epjconf/201817509005.

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The openQ*D code for the simulation of QCD+QED with C* boundary conditions is presented. This code is based on openQCD-1.6, from which it inherits the core features that ensure its efficiency: the locally-deflated SAP-preconditioned GCR solver, the twisted-mass frequency splitting of the fermion action, the multilevel integrator, the 4th order OMF integrator, the SSE/AVX intrinsics, etc. The photon field is treated as fully dynamical and C* boundary conditions can be chosen in the spatial directions. We discuss the main features of openQ*D, and we show basic test results and performance analysis. An alpha version of this code is publicly available and can be downloaded from http://rcstar.web.cern.ch/.

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34

Prigarin, Vladimir, Dmitry Karavaev, and Viktor Protasov. "The cuFFT code for N-body simulation." Journal of Physics: Conference Series 1336 (November 2019): 012023. http://dx.doi.org/10.1088/1742-6596/1336/1/012023.

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35

Shin, Jihye, Juhan Kim, Sungsoo S. Kim, and Changbom Park. "EUNHA: A NEW COSMOLOGICAL HYDRODYNAMIC SIMULATION CODE." Journal of The Korean Astronomical Society 47, no. 3 (June 30, 2014): 87–98. http://dx.doi.org/10.5303/jkas.2014.47.3.87.

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36

Ozeki, T., N. Aiba, N. Hayashi, T. Takizuka, M. Sugihara, and N. Oyama. "Integrated Simulation Code for Burning Plasma Analysis." Fusion Science and Technology 50, no. 1 (July 2006): 68–75. http://dx.doi.org/10.13182/fst06-a1221.

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37

Bosso, N., and N. Zampieri. "Long train simulation using a multibody code." Vehicle System Dynamics 55, no. 4 (December 23, 2016): 552–70. http://dx.doi.org/10.1080/00423114.2016.1267373.

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38

Digesu, P., and D. Laforgia. "Diesel Electro-injector: A Numerical Simulation Code." Journal of Engineering for Gas Turbines and Power 117, no. 4 (October 1, 1995): 792–98. http://dx.doi.org/10.1115/1.2815466.

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A simulation code of an electro-injector for diesel engines is presented with the preliminary parametric analysis carried out with the code. The simulation code is based upon the concentrated volume method as for the chambers of the system. Energy and flow rate conservation equations and dynamic equations are used for the movable parts of the system under stress or friction. The magnetic force acting on the electro-injector actuator has been calculated by means of a finite element simulation. The one-dimensional code simulated the propagation in feeding pipes and the control of the electro-injector. The program, in fact, uses the method of the characteristic equations to solve conservation equations, simulating the propagation in a pipe between two chambers. The sensitivity analysis has pointed out that the parameters that are influenced by the propagation in the pipes are: needle lift, injected flow rate, pressure in each chamber, and volume. The perturbations reduce the effective pressure of injection and are influenced by pipe lengths and diameters.

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39

González-Morales, Pedro A., Rekha Jain, and Michael J. Thompson. "Helioseismic Tests With the FLASH Simulation Code." Journal of Physics: Conference Series 271 (January 1, 2011): 012013. http://dx.doi.org/10.1088/1742-6596/271/1/012013.

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40

Matsumoto, Masaaki, and Takahiko Tanahashi. "Verification of simulation code for Marangoni convection." Proceedings of the Fluids engineering conference 2000 (2000): 52. http://dx.doi.org/10.1299/jsmefed.2000.52.

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41

Baelmans, M., P. Börner, K. Ghoos, and G. Samaey. "Efficient code simulation strategies for B2-EIRENE." Nuclear Materials and Energy 12 (August 2017): 858–63. http://dx.doi.org/10.1016/j.nme.2016.10.028.

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42

Dipace, A., and E. Sabia. "A 3D simulation code for FEL amplifiers." Il Nuovo Cimento A 106, no. 12 (December 1993): 1765–70. http://dx.doi.org/10.1007/bf02780576.

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43

Simko, Lynn C., Kathleen A. McGinnis, Rosanna Henry, and Amber Lerach Kolesar. "Use of Simulation in Mock Code Participation." Clinical Simulation in Nursing 5, no. 3 (May 2009): S13—S14. http://dx.doi.org/10.1016/j.ecns.2009.03.234.

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44

Tagliafico, Luca A., and Maurizio Senarega. "A simulation code for batch heat treatments." International Journal of Thermal Sciences 43, no. 5 (May 2004): 509–17. http://dx.doi.org/10.1016/j.ijthermalsci.2003.09.005.

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45

Penna, T. J. P., and P. M. C. de Oliveira. "Fully parallel code for Monte Carlo simulation." Journal of Statistical Physics 61, no. 3-4 (November 1990): 933–41. http://dx.doi.org/10.1007/bf01027313.

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46

Benaskeur, N., M. Hachouf, F. Kharfi, H. Benkharfia, and A. Khalfallah. "Neutron tomography simulation by MAVRIC/Monaco code." Applied Radiation and Isotopes 135 (May 2018): 160–65. http://dx.doi.org/10.1016/j.apradiso.2018.01.023.

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47

Bagdonat, T., and U. Motschmann. "3D Hybrid Simulation Code Using Curvilinear Coordinates." Journal of Computational Physics 183, no. 2 (December 2002): 470–85. http://dx.doi.org/10.1006/jcph.2002.7203.

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48

null, Vadim Levchenko, and Anastasia Perepelkina. "Heterogeneous LBM Simulation Code with LRnLA Algorithms." Communications in Computational Physics 33, no. 1 (June 2023): 214–44. http://dx.doi.org/10.4208/cicp.oa-2022-0055.

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49

Figueroa Garcia, Juan Carlos, and Jhoan Sebastian Tenjo García. "FRand: MATLAB Toolbox for Fuzzy Random Number Simulation." Ingeniería 25, no. 1 (March 12, 2020): 38–49. http://dx.doi.org/10.14483/23448393.15620.

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Context: This paper presents a MATLAB code implementation and the GUI (General User Interface) for fuzzy random variable generation. Based on previous theoretical results and applications, a MATLAB toolbox has been developed and tested for selected membership functions. Method: A two–step methodology was used: i) a MATLAB toolbox was implemented to be used as interface and ii) all .m functions are available to be used as normal code. The main goal is to provide graphical and code–efficient tools to users. Results: The main obtained results are the MATLAB GUI and code. In addition, some experiments were ran to evaluate its capabilities and some randomness statistical tests were successfully performed. Conclusions: Satisfactory results were obtained from the implementation of the MATLAB code/toolbox. All randomness tests were accepted and all performed experiments shown stability of the toolbox even for large samples (>10.000). Also, the code/toolbox are available online. Acknowledgements: The authors would like to thank to the Prof. M Sc. Miguel Melgarejo and Prof. Jos´e Jairo Soriano–Mendez sincerely for their interest and invaluable support, and a special gratefulness is given to all members of LAMIC.

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50

Ullum Azhari, M. Husnul, Nyoman Pramaita, and I. Gst A. Komang Diafari Djuni H. "DESAIN PROGRAM SIMULASI PENERAPAN KODE BOSE CHAUDHURI HOCQUENGHEM PADA DIRECT SEQUENCE SPREAD SPECTRUM." Jurnal SPEKTRUM 7, no. 4 (December 5, 2020): 60. http://dx.doi.org/10.24843/spektrum.2020.v07.i04.p8.

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This study proposes a design of simulation program for implementing Bose ChaudhuriHocquenghem (BCH) code on Direct Sequence Spread Specterum (DSSS) to knowing theperformance of the effect of DSSS with flat fading channel and AWGN without BCH code (7,4)with the application of BCH code (7,4) on DSSS with flat fading and AWGN channel. Thissimulation consist of simulation of BER application of BCH code (7,4) on DSSS with flat fadingand AWGN channel, simulation of BER application code BCH (7,4) on DSSS with AWGNchannel, simulation of the effect of Eb/No on noise variance in the DSSS system, and BERsimulation as a function of noise variance on the DSSS system. Simulation of application BCHcode (7,4) on DSSS with flat fading and AWGN channel analyzed based on Bit Error Rate(BER) versus Energy Bit per Noise (Eb/No). The application of BCH code (7,4) on DSSS withflat fading channel and AWGN shows better performance than DSSS with flat fading channelsand AWGN without BCH coding (7,4). On the Eb/No value 10 dB, simulation application BCHcode (7,4) on DSSS with flat fading channel and AWGN generate BER value which isapproaching 0 with BER value 0.0188, while the DSSS simulation with flat fading channel andAWGN without BCH code (7.4) generate a BER value of 0.0228.

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