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Micromechanics: Overall Properties of Heterogeneous Materials
Open accessAbstract
The section on variational methods includes some new elements which should prove useful for application to advanced modeling, as well as solutions of composites and related heterogeneous bodies. A brief modern version of elements in vector and tensor algebra is provided which is particularly tailored to provide a background for the rest of this book. The data contained in this volume as Part 1 includes new results on many basic issues in micromechanics, which will be helpful to graduate students and researchers involved with rigorous physically-based modeling of overall properties of heterogeneous solids
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Cited by
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Olivito, R. S., & Zuccarello, F. A. (2010) · Composites Part B: Engineering · doi:10.1016/j.compositesb.2009.12.003 · Cited by 385
Shape memory alloys, Part II: Modeling of polycrystals
Lagoudas, D. C., Entchev, P. B., Popov, P., Patoor, E., Brinson, L. C., & Gao, X. (2006) · Mechanics of Materials · doi:10.1016/j.mechmat.2005.08.003 · Cited by 358
Quantification of uncertainty modelling in stochastic analysis of FRP composites
Sriramula, S., & Chryssanthopoulos, M. K. (2009) · Composites Part A: Applied Science and Manufacturing · doi:10.1016/j.compositesa.2009.08.020 · Cited by 318
Metadata
- Authors
- Nemat-Nasser, S., Lori, M., & Datta, S. K.
- Venue
- Journal of Applied Mechanics
- Publisher
- ASME International
- Published
- 1996-06-01
- Volume
- 63
- Issue
- 2
- Pages
- 561-561
- ISSN
- 0021-8936 (ISSN-L)
- 1528-9036
- OpenAlex
- W2145856055
- Cited by
- 2,202
- References
- 0
- FWCI
- 98.47
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Nemat-Nasser, S., Lori, M., & Datta, S. K. (1996). Micromechanics: Overall Properties of Heterogeneous Materials. Journal of Applied Mechanics. https://doi.org/10.1115/1.2788912
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
