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International Journal for Multiscale Computational Engineering

Publicado 6 números por año

ISSN Imprimir: 1543-1649

ISSN En Línea: 1940-4352

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.4 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.3 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 2.2 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00034 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.46 SJR: 0.333 SNIP: 0.606 CiteScore™:: 3.1 H-Index: 31

Indexed in

Domain Decomposition Methodology with Robin Interface Matching Conditions for Solving Strongly Coupled Fluid-Structure Problems

Volumen 7, Edición 1, 2009, pp. 29-38
DOI: 10.1615/IntJMultCompEng.v7.i1.50
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SINOPSIS

The inverse energy deposition problem represents a particular subclass of the more general inverse heat conduction problem, where certain features that are associated with upstreamto- downstream spatial weighting of the temperature field diffusion pattern dominate. The present paper focuses on the case of rapid energy deposition processes, where it is shown that the influence of windage can be correlated with the extremely strong filtering of spatial and temporal structure within the associated diffusion pattern. This strong filtering tends to establish conditions where system identification, or in particular, reconstruction of detailed features of the energy source, based on data-driven inverse analysis is not well posed. Similarly, the strong filtering conditions associated with very rapid energy deposition imply consequences with respect to qualitative analysis using numerical simulations based on basic principles or the direct problem approach. That is to say, any experiment or basic theoretical information that is available concerning the coupling of energy into a spatial region of interest from a surface or interface, that is, the site of deposition, will be difficult to correlate with experimental observations of the associated energy diffusion pattern. Finally, it has been established that the primary implication of the analysis and simulations is that rapid energy deposition processes should be characterized by two distinctly separate scales for both spatial and temporal structures. The results of the analysis presented here indicate that the inverse rapid energy deposition problem requires a formulation with respect to system identification and parameterization that should be cast in terms of two separate sets of parameters. One should represent energy source characteristics on spatial and temporal scales commensurate with that of thermal diffusivity within the material. The other parameter set should represent energy source characteristics on spatial and temporal scales commensurate with those of surface phenomena.

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CITADO POR
  1. Errera Marc-Paul, Chemin Sébastien, Optimal solutions of numerical interface conditions in fluid–structure thermal analysis, Journal of Computational Physics, 245, 2013. Crossref

  2. Yu Yue, Baek Hyoungsu, Karniadakis George Em, Generalized fictitious methods for fluid–structure interactions: Analysis and simulations, Journal of Computational Physics, 245, 2013. Crossref

  3. Errera Marc-Paul, Baqué Bénédicte, A quasi-dynamic procedure for coupled thermal simulations, International Journal for Numerical Methods in Fluids, 72, 11, 2013. Crossref

  4. Yu Yue, Xie Fangfang, Yan Hongmei, Constantinides Yiannis, Oakley Owen, Karniadakis George Em, Suppression of vortex-induced vibrations by fairings: A numerical study, Journal of Fluids and Structures, 54, 2015. Crossref

  5. Errera M.-P., Duchaine F., Comparative study of coupling coefficients in Dirichlet–Robin procedure for fluid–structure aerothermal simulations, Journal of Computational Physics, 312, 2016. Crossref

  6. Meng F., Banks J.W., Henshaw W.D., Schwendeman D.W., A stable and accurate partitioned algorithm for conjugate heat transfer, Journal of Computational Physics, 344, 2017. Crossref

  7. Chen Sheng, Simulation of conjugate heat transfer between fluid-saturated porous media and solid wall, International Journal of Thermal Sciences, 124, 2018. Crossref

  8. Yu Yue, Fluid-Structure Interaction Modeling in 3D Cerebral Arteries and Aneurysms, in Biomedical Technology, 84, 2018. Crossref

  9. Yu Yue, Bargos Fabiano F., You Huaiqian, Parks Michael L., Bittencourt Marco L., Karniadakis George E., A partitioned coupling framework for peridynamics and classical theory: Analysis and simulations, Computer Methods in Applied Mechanics and Engineering, 340, 2018. Crossref

  10. Yu Yue, Kamensky David, Hsu Ming-Chen, Lu Xin Yang, Bazilevs Yuri, Hughes Thomas J. R., Error estimates for projection-based dynamic augmented Lagrangian boundary condition enforcement, with application to fluid–structure interaction, Mathematical Models and Methods in Applied Sciences, 28, 12, 2018. Crossref

  11. Errera Marc-Paul, Moretti Rocco, Salem Rami, Bachelier Yohann, Arrivé Thomas, Nguyen Minh, A single stable scheme for steady conjugate heat transfer problems, Journal of Computational Physics, 394, 2019. Crossref

  12. Gimenez G., Errera M., Baillis D., Smith Y., Pardo F., A coupling numerical methodology for weakly transient conjugate heat transfer problems, International Journal of Heat and Mass Transfer, 97, 2016. Crossref

  13. Cheng Lin, Wagner Gregory J., An optimally-coupled multi-time stepping method for transient heat conduction simulation for additive manufacturing, Computer Methods in Applied Mechanics and Engineering, 381, 2021. Crossref

  14. Zhang Hong, Liu Zhengyu, Constantinescu Emil, Jacob Robert, Stability Analysis of Interface Conditions for Ocean–Atmosphere Coupling, Journal of Scientific Computing, 84, 3, 2020. Crossref

  15. Gelain Matteo, Errera Marc-Paul, Gicquel Olivier, Assessment and numerical validation of a normal mode stability analysis for conjugate heat transfer, International Journal of Heat and Mass Transfer, 191, 2022. Crossref

  16. Koren Chai, Vicquelin Ronan, Gicquel Olivier, Self-adaptive coupling frequency for unsteady coupled conjugate heat transfer simulations, International Journal of Thermal Sciences, 118, 2017. Crossref

  17. Viguerie Alex, Carraturo Massimo, Reali Alessandro, Auricchio Ferdinando, A spatiotemporal two-level method for high-fidelity thermal analysis of laser powder bed fusion, Finite Elements in Analysis and Design, 210, 2022. Crossref

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