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![Schematic of the SFEA framework [58].](publication/344135056/figure/fig1/AS:11431281211200639@1702373381231/Schematic-of-the-SFEA-framework-58_Q320.jpg)
![A schematic illustrating the Random Number Generator (RNG) module [58].](publication/344135056/figure/fig3/AS:11431281211200642@1702373381672/A-schematic-illustrating-the-Random-Number-Generator-RNG-module-58_Q320.jpg)
![Schematic illustrating the algorithm for the FEA module [58].](publication/344135056/figure/fig4/AS:11431281211200644@1702373381945/Schematic-illustrating-the-algorithm-for-the-FEA-module-58_Q320.jpg)
Properties such as low specific gravity and cost make polymers attractive for many engineering applications, yet their mechanical, thermal, and electrical properties are typically inferior compared to other engineering materials. Material designers have been seeking to improve polymer properties, which may be achieved by adding suitable particulate...
Citations
... For the simulation regimes of the uncertainty, the solutions of probabilistic theory could be divided into two types: (1) the direct simulative approach and (2) the non-simulative approach. For the direct simulative approach, the Monte-Carlo simulation method is the most representative one which calculates each possible realization of structural response by using a direct sampling technique [151][152][153][154]. For the non-simulative approach, the desired uncertain structural outputs need to be acquired through established mathematical or numerical approaches [155][156][157][158]. Several typical probabilistic analysis methods including both direct simulative and non-simulative techniques are listed and introduced as follows. ...
Structural systems are consistently encountering the variabilities in material properties, undesirable defects and loading environments, which may potentially shorten their designed service life. To ensure a reliable structural performance, it is vital to track and quantify the effects of different random/uncertainty factors upon the structural fracture performance. In this research, a critical review of the past, current and future computational modelling of the non-deterministic fracture mechanics is presented. By considering the variously numerical solutions tackling the fracture problems, they are mainly categorized into the discrete and continuous approaches. This study discusses the quantification performance of the extended finite element method, the crack band method and the phase-field approaches combined with different sources of uncertainties. These well-known computational techniques are typical representatives of the common fracture modelling philosophies including the embedded, smeared and regularized ones. The essence of this work is to compare the main differences of the uncertainty quantification models (i.e., probabilistic, non-probabilistic) at the fracture formulation levels and investigate the major progress and challenges existing in the real-life applications for the past and future decades. Some critical remarks, which are denoting the advantages and major issues of various non-deterministic fracture models, are provided and explained in the practical structural failure conditions. Different fracture simulation cases are implemented with comparative results amongst analytical, numerical and experimental methods, and the corresponding fracture quantification ability is evaluated through the standards of the random fracture capacity, load–deflection plots, crack propagation, crack mechanisms, and computational efficiency, etc.
... The Finite Element Method, combined with stochastic modelling, has also been used to predict the electrical properties of composites based on randomly distributed populations of conductive particles [28,29]. However, little such analysis is evident of conductive weft yarn composites and this forms the basis of the first part of the present study. ...
... An equivalent circuit model based on rule-of-mixtures analysis proposed for low resistivity Z-filaments composites [24] is adapted to predict the TTEC of conductive weft yarn composites. To process the complex circuit network, a Monte Carlo method was employed [29][30][31] and an SONM is proposed to predict the TTEC. To verify the conductive mechanism and the validity of the model, two types of conductive weft yarn composites were manufactured based on IWWF. ...
Conductive weft yarn composites were developed and studied by both computational and experimental methods. A simulation based on a stochastic overlap network model (SONM) was developed in MATLAB to predict the through-thickness electrical conductivity (TTEC) for conductive weft yarn composites. Conductive weft yarn composites based on Inter-Woven Wire Fabric (IWWF) were manufactured and investigated. The results confirm that the technique can be used to increase the TTEC in a controlled manner by forming a continuous electrically conductive network with a comparatively low volume fraction of conductors. The TTEC of typical cross-ply conductive weft yarn composites reached 446 S/m, which is three orders of magnitude times higher than the control laminate. The simulated data are consistent with the experimental results, offering good scope for predictive design work.
... Moghaddam and Mertiny [39][40][41] employed stochastic finite element analysis and introduced effective means to predict material properties of particulate modified polymer composites for elucidating experimental studies and guiding the design of this class of hybrid materials. ...
Crashworthiness, energy absorption capacity and safety are important factors in the design of light-weight vehicles made of fiber-reinforced polymer composite (FRP) components. The relatively recent emergence of the nanotechnology industry has presented a novel means to augment the mechanical properties of various materials. Also, uncontrolled vibration in mechanical systems (e.g. aircraft, trains, and automobiles) may result in undesirable noise and eventually, cause mechanical failure. As a result, recent attempts have contemplated the use of nanoparticles to further improve the resiliency of resins, especially when resins are used for mating FRP components as well as three-dimensional fiber metal laminates (3D-FMLs). 3D-FMLs are a class of novel lightweight hybrid material systems with great potential for use in the aforementioned applications. Therefore, a comprehensive understanding of the response of nano-reinforced polymer composites, subjected to various rates of loading, as well as exploring parameters that govern and affect the frequency response of 3D-FMLs is vital for developing reliable structures. In this study, the effects of nano-reinforcement on the mechanical response of a commonly used epoxy resin subjected to different strain rates were systematically investigated. The results were then compared to those of the neat resin. To characterize the mechanical properties of the nanocomposite, a combination of the strain rate-dependent mechanical (SRDM) model of Goldberg and his co-workers, and Halpin-Tsai’s micromechanical approach was employed. Subsequently, a parametric study was conducted in addition to a statistical approach, to ascertain the influences of various parameters (i.e., the particle type, their weight percentage). Then, the numerical results, as well as statistical results were compared to the experimental data obtained from testing of the neat and the nano-reinforced epoxy resin.
Further, the vibration characteristics of the two more commonly used configurations of 3D-FMLs were experimentally investigated by nontraditional and conventional approaches. The study explored the material damping by the inclusion of two different types of nanocarbon particles (NCPs) within the core and/or interfaces of the hybrid system. The results were presented and compared. The inclusion of NCPs increased the fundamental frequency of the system slightly; however, material damping was enhanced significantly when only 1 wt% NCP was used in the interfacial sections of the system at room temperature.
Polymer composites containing magnetic fillers are promising materials for a variety of applications, such as in energy storage and medical fields. To facilitate the engineering design of respective components, a comprehensive understanding of the mechanical behavior of such inhomogeneous and potentially highly anisotropic materials is important. Therefore, the authors created magnetic composites by compression molding. The epoxy polymer matrix was modified with a commercial-grade thickening agent. Isotropic magnetic particles were added as the functional filler. The microstructural morphology, especially the filler distribution, dispersion, and alignment, was characterized using microscopy techniques. The mechanical properties of the composites were experimentally characterized and studied by stochastic finite element analysis (SFEA). Modeling was conducted employing four cases to predict the elastic modulus: fully random distribution, randomly aligned distribution, a so-called “rough” interface contact, and a bonded interface contact. Results from experiments and SFEA modeling were compared and discussed.
