In recent years, the fabrication of nanoparticles and exploration of their properties have attracted the attention of physicists, chemists, biologists and engineers. Interest in nanoparticles arise from the fact that the mechanical, chemical, electrical, optical, magnetic, electro-optical and magneto-optical properties of these particles are different from their bulk properties and depend on the particle size. There are numerous areas where nanoparticulate systems are of scientific and technological interest. This book reviews research on the various components of superparamagnetic iron oxide nanoparticles.

This book explains methods and coding to create FEM-based models to optimize process variables and predict dimensional distortions during the manufacture of thermoplastic matrix composite parts. After investigating defects, such as spring-in, caused by thermal inconsistencies during manufacture, the text offers a step-by-step approach to simulating and predicting the magnitude of distortion via readily available FE codes. Models are validated by testing using the example of a multi-staged roll-formed continuous thermoplastic woven laminate, which can be readily extended to a variety of mold geometries. Information in this book is intended to reduce the need for costly and time-consuming re-tooling in thermoplastic parts design. It includes models and experiments for faster, less expensive manufacture of thermoplastic parts. It is focused on simulating thermal defects in thermoplastics. It covers: techniques for better molds, tooling and equipment; Material Property Testing; Thermoplastic Matrix Composite Manufacturing Methods; and, Process Characterization of Roll Forming.It looks at: Case Study Modeling Approaches and Results; Using Elastic Mechanical Properties; Using Viscoelastic Mechanical Properties; and, Pseudo Meso-Level Decomposition.

Numerical simulation of forming processes has become an important means for material selection, tool design, and process optimization. A critical component of simulation is an accurate material constitutive model, describing the response of the material under possible modes of deformation. The accuracy, in turn, is linked to the tests and techniques applied for the identification of constitutive models. This book elaborates on the identification of textile composite models using a new inverse method by means of a signal-to-noise weighting scheme, and two constitutive equations based on a phenomenological invariant-based approach. A full identification of the models for a typical woven fabric is applied using sets of data from standard testing methods, including a modified picture frame test. The identification framework makes it possible to include all sets of data from several deformation modes, along with their given test non-repeatabilities. The method has been presented in a general manner and it can be applied in other applications, where non-repeatability of measurements and the lack of agreement between identification parameters in different modes are practical problems.