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Briefly, the two basic questions that this research is supposed to answer are: 1. Howmuch fiber is needed and how fibers should be distributed through a fiber reinforced composite (FRC) structure in order to obtain the optimal and reliable structural response? 2. How do uncertainties influence the optimization results and reliability of the structure? Giving answer to the above questions a double stage sequential optimization algorithm for finding the optimal content of short fiber reinforcements and their distribution in the composite structure, considering uncertain design parameters, is presented. In the first stage, the optimal amount of short fibers in a FRC structure with uniformly distributed fibers is conducted in the framework of a Reliability Based Design Optimization (RBDO) problem. Presented model considers material, structural and modeling uncertainties. In the second stage, the fiber distribution optimization (with the aim to further increase in structural reliability) is performed by defining a fiber distribution function through a Non-Uniform Rational BSpline (NURBS) surface. The advantages of using the NURBS surface as a fiber distribution function include: using the same data set for the optimization and analysis; high convergence rate due to the smoothness of the NURBS; mesh independency of the optimal layout; no need for any post processing technique and its non-heuristic nature. The output of stage 1 (the optimal fiber content for homogeneously distributed fibers) is considered as the input of stage 2. The output of stage 2 is the Reliability Index (b) of the structure with the optimal fiber content and distribution. First order reliability method (in order to approximate the limit state function) as well as different material models including Rule of Mixtures, Mori-Tanaka, energy-based approach and stochastic multi-scales are implemented in different examples. The proposed combined model is able to capture the role of available uncertainties in FRC structures through a computationally efficient algorithm using all sequential, NURBS and sensitivity based techniques. The methodology is successfully implemented for interfacial shear stress optimization in sandwich beams and also for optimization of the internal cooling channels in a ceramic matrix composite. Finally, after some changes and modifications by combining Isogeometric Analysis, level set and point wise density mapping techniques, the computational framework is extended for topology optimization of piezoelectric / flexoelectric materials.
Over the last few decades, uncertainty quantification in composite materials and structures has gained a lot of attention from the research community as a result of industrial requirements. This book presents computationally efficient uncertainty quantification schemes following meta-model-based approaches for stochasticity in material and geometric parameters of laminated composite structures. Several metamodels have been studied and comparative results have been presented for different static and dynamic responses. Results for sensitivity analyses are provided for a comprehensive coverage of the relative importance of different material and geometric parameters in the global structural responses.
Over the last few decades, uncertainty quantification in composite materials and structures has gained a lot of attention from the research community as a result of industrial requirements. This book presents computationally efficient uncertainty quantification schemes following meta-model-based approaches for stochasticity in material and geometric parameters of laminated composite structures. Several metamodels have been studied and comparative results have been presented for different static and dynamic responses. Results for sensitivity analyses are provided for a comprehensive coverage of the relative importance of different material and geometric parameters in the global structural responses.
Uncertainty Quantification in Multiscale Materials Modeling provides a complete overview of uncertainty quantification (UQ) in computational materials science. It provides practical tools and methods along with examples of their application to problems in materials modeling. UQ methods are applied to various multiscale models ranging from the nanoscale to macroscale. This book presents a thorough synthesis of the state-of-the-art in UQ methods for materials modeling, including Bayesian inference, surrogate modeling, random fields, interval analysis, and sensitivity analysis, providing insight into the unique characteristics of models framed at each scale, as well as common issues in modeling across scales. - Synthesizes available UQ methods for materials modeling - Provides practical tools and examples for problem solving in modeling material behavior across various length scales - Demonstrates UQ in density functional theory, molecular dynamics, kinetic Monte Carlo, phase field, finite element method, multiscale modeling, and to support decision making in materials design - Covers quantum, atomistic, mesoscale, and engineering structure-level modeling and simulation
Vols. 29-30 contain papers of the International Engineering Congress, Chicago, 1893; v. 54, pts. A-F, papers of the International Engineering Congress, St. Louis, 1904.
This work was compiled with expanded and reviewed contributions from the 7th ECCOMAS Thematic Conference on Smart Structures and Materials, that was held from 3 to 6 June 2015 at Ponta Delgada, Azores, Portugal. The Conference provided a comprehensive forum for discussing the current state of the art in the field as well as generating inspiration for future ideas specifically on a multidisciplinary level. The scope of the Conference included topics related to the following areas: Fundamentals of smart materials and structures; Modeling/formulation and characterization of smart actuators, sensors and smart material systems; Trends and developments in diverse areas such as material science including composite materials, intelligent hydrogels, interfacial phenomena, phase boundaries and boundary layers of phase boundaries, control, micro- and nano-systems, electronics, etc. to be considered for smart systems; Comparative evaluation of different smart actuators and sensors; Analysis of structural concepts and designs in terms of their adaptability to smart technologies; Design and development of smart structures and systems; Biomimetic phenomena and their inspiration in engineering; Fabrication and testing of smart structures and systems; Applications of smart materials, structures and related technology; Smart robots; Morphing wings and smart aircrafts; Artificial muscles and biomedical applications; Smart structures in mechatronics; and Energy harvesting.
Carbon Nanotube-Reinforced Polymers: From Nanoscale to Macroscale addresses the advances in nanotechnology that have led to the development of a new class of composite materials known as CNT-reinforced polymers. The low density and high aspect ratio, together with their exceptional mechanical, electrical and thermal properties, render carbon nanotubes as a good reinforcing agent for composites. In addition, these simulation and modeling techniques play a significant role in characterizing their properties and understanding their mechanical behavior, and are thus discussed and demonstrated in this comprehensive book that presents the state-of-the-art research in the field of modeling, characterization and processing. The book separates the theoretical studies on the mechanical properties of CNTs and their composites into atomistic modeling and continuum mechanics-based approaches, including both analytical and numerical ones, along with multi-scale modeling techniques. Different efforts have been done in this field to address the mechanical behavior of isolated CNTs and their composites by numerous researchers, signaling that this area of study is ongoing. - Explains modeling approaches to carbon nanotubes, together with their application, strengths and limitations - Outlines the properties of different carbon nanotube-based composites, exploring how they are used in the mechanical and structural components - Analyzes the behavior of carbon nanotube-based composites in different conditions
In the last decade the author has been engaged in developing a micromechanical composite model based on the study of interacting periodic cells. In this two-phase model, the inclusion is assumed to occupy a single cell whereas the matrix material occupies several surrounding cells. A prominent feature of the micromechanical method of cells is the transition from a medium, with a periodic microstructure to an equivalent homogeneous continuum which effectively represents the composite material. Of great importance is the significant advantage of the cells model in its capability to analyze elastic as well as nonelastic constituents (e.g. viscoelastic, elastoplastic and nonlinear elastic), thus forming a unified approach in the prediction of the overall behaviour of composite material. This book deals almost exclusively with this unified theory and its various applications.