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International Journal for Multiscale Computational Engineering

Published 6 issues per year

ISSN Print: 1543-1649

ISSN Online: 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

Toward Coupled-Field Characterization and Design Optimization of Single-Wall Nanotube Composites for Hydrogen Storage Systems

Volume 4, Issue 3, 2006, pp. 351-361
DOI: 10.1615/IntJMultCompEng.v4.i3.50
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ABSTRACT

We present an examination of the feasibility for simultaneous characterization and design optimization of various aspects of reactive systems under concurrent heat and mass transport presence. The analysis described in this paper is of a carbon nanotube composite system potentially usable for hydrogen storage applications. Three distinct activities were employed for this analysis. First, the forward continuum model of a multispecies diffusing system under simultaneous exposure to mass diffusion with chemical reactivity and to heat conduction was generated. Second, the problem of hydrogen storage was defined within a pragmatic product-design context where the appropriate design parameters of the system are determined via appropriate optimization methods, utilizing extensive experimental data encoding the systemic behavior. Third, this methodology is applied on a hydrogen storage nanocomposite reactor system and appropriate systemic parameter estimation is performed. Thus, the context of the work presented is defined by a data-driven characterization of coupled heat and mass diffusion models of hydrogen storage systems from a multifield perspective at the macro length scale. In particular, a single-wall nanotube (SWNT) based composite is modeled by coupled partial differential equations representing spatiotemporal evolution of distributions of temperature and hydrogen concentration. Analytical solutions of these equations are adopted for an inverse analysis that defines a nonlinear optimization problem for determining the parameters of the model by objective function minimization. Experimentally acquired and model-produced data are used to construct this objective function. Simulations demonstrating the applicability of the methodology and a discussion of its potential extension to multiscale and manufacturing process optimization are presented.

CITED BY
  1. Brieño-Enriquez K.M., Ledesma-García J., Perez-Bueno J.J., Godinez Luis A., Terrones H., Ángeles-Chavez C., Bonding titanium on multi-walled carbon nanotubes for hydrogen storage: An electrochemical approach, Materials Chemistry and Physics, 115, 2-3, 2009. Crossref

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