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Modeling and Optimization of EDM-Based Hybrid Machining Processes
Published in Basil Kuriachen, Jose Mathew, Uday Shanker Dixit, Electric Discharge Hybrid-Machining Processes, 2022
Sanghamitra Das, Shrikrishna Nandkishor Joshi, Uday Shanker Dixit
Multiscale modeling is applied to systems with complex behavior by tackling physical, chemical, and mechanical aspects at different length and time scales. The method is suitable for hybrid machining where different phenomena are responsible for machining. Multiscale modeling approaches for a hybrid process allow the coupling of different parts of a system into a single solution. There are different types of coupling (a) manual coupling, where the output of a part of model is manually input to another part of the model at a different scale, (b) loose coupling, where the global model and all the sub models are solved separately with different sets of equations and (c) tight coupling, where all the sub models are integrated and solved by a single set of equations. Another classification of modelling approaches can be in the following way: (a) sequential modeling, where a macroscopic model is defined first by constitutive relations that are derived from a different scale model, (b) concurrent modeling, where all the constitutive relations of the system on different scales are coupled concurrently into a single comprehensive solution. Wang and Zhang [21] briefly demonstrated the hybrid approach to multiscale modeling technologies. The correlation between the models on different scales is developed by the coupling of different conditions. Zeng and Qin [22] explained the application of multiscale modeling to hybrid machining processes and they also discussed the various modeling strategies. Table 14.1 depicts the different modeling methodologies adopted at various time and length scales.
Application of Finite Element Method for the Design of Nanocomposites
Published in Sarhan M. Musa, Computational Finite Element Methods in Nanotechnology, 2013
Multiscale modeling involves the application of modeling techniques at two or more different scales, which are often, dissimilar in their theoretical character due to the change in scale. A distinction is made between the hierarchical approach, [9–11], which involves running separate models with some sort of parametric coupling, and the hybrid approach, [12–15] in which models are run concurrently over different spatial regions of a simulation. The relationships between different categories of methods commonly used in the multiscale modeling hierarchy are shown in Figure 7.1. Although some techniques have been known for a long time and are now widely used, such as molecular dynamics (MD) and Monte Carlo (MC) methods, others such as mesoscale modeling and some more advanced methods of atomistic simulations are not as common. We have therefore included the technical summary for the benefit of nonspecialists.
Efficiency and accuracy of a multiscale domain activation approach for modeling masonry failure
Published in Jan Kubica, Arkadiusz Kwiecień, Łukasz Bednarz, Brick and Block Masonry - From Historical to Sustainable Masonry, 2020
C. Driesen, H. Degée, B. Vandoren
A viable solution to the problem of computationally intensive micro- and mesoscale models, or of inaccurate macroscale models, is the use of scale embedded multiscale modeling techniques (Weinan, 2011). In the global multiscale modeling methods one attempts to achieve the advantages of both scales by combining their working methods, while trying to avoid their drawbacks. In this contribution, the concurrent approach is favored. The three major aspects in this concurrent model are the inter-element connections, the refinement criteria, and the homogenization techniques.
Studies of frictional sliding contact by molecular dynamics assisted continuum mechanics
Published in Mechanics of Advanced Materials and Structures, 2022
Mohsen Motezaker, Shaoping Xiao, Amir R. Khoei, Jabbar Ali Zakeri
However, a full atomistic simulation of a contact system could be time-consuming and impractical. One of the solutions is multiscale modeling [21, 22], which has been applied to study the mechanics of materials in the materials science community. A general hierarchical multiscale method [23] passes the effective material properties or the material-behavior predictive models from a small scale to a large scale. Thus, a similar approach can be employed to study the physical phenomena of lubrication at the nanoscale and simulate the contact mechanisms at the macroscale [24]. Such a multiscale model that bridges MD to continuum mechanics for evaluating contact mechanics can consider the friction phenomena from its origin along with the advantages of classical continuum theory. Ghaffari et al. [12] used a multiscale modeling approach to calculate the rolling contact fatigue (RCF) lifetime with a friction coefficient obtained from MD. However, they considered octane hydrocarbon at room temperature only to model an elastohydrodynamic lubricated rolling system. It is vital to study the effects of lubricant chemical formulation and temperature on the friction coefficient and the sliding contact mechanisms.
A review on proppant transport in complex fracture geometries
Published in Petroleum Science and Technology, 2023
Zhicheng Wen, Liehui Zhang, Huiying Tang, Yulong Zhao, Jianfa Wu, Haoran Hu
The hydraulic fracturing optimizing for practical applications necessities a large-scale proppant transport model. However, most of existing numerical studies focused on the proppant transport in a laboratory-scale fracture due to the limitation of huge computational cost. In general, a high-resolution proppant transport model needs more computer resources to detailly capture fluid–particle and particle–particle interactions, such as the CFD–DEM (Zhang et al. 2022a). However, this kind of numerical methods are difficult to apply to filed-scale problems for the foreseeable future (Wang et al. 2023). On the other hand, a relatively low-resolution proppant transport model, including the mixture model (Tang et al. 2016), MP–PIC method (Mao et al. 2021a) and coarse–grained CFD–DEM framework (Zeng, Li, and Zhang 2016), is capable of modeling large-scale proppant transport comparable to field treatments and offers an enormous saving in computational resources (Zeng, Li, and Zhang 2019). However, these models have to simplify several physical mechanisms, especially for the particle–particle interaction. Therefore, it may be necessary to use a multiscale modeling framework to reach a compromise between computational cost and modeling accuracy. The multiscale framework refers to that a relatively coarse model uses the sub-scale laws that are extracted from the results obtained by a refined numerical model. This framework has been used to study novel-shaped proppant transport in a single field-scale fracture (Zeng et al. 2022). For proppant transport in field-scale fracture networks, there are several important aspects that need to be considered, including proppant diversion at interactions considering particle inertia, phase slip and wall friction.
Modeling nanomaterial physical properties: theory and simulation
Published in International Journal of Smart and Nano Materials, 2019
Tanujjal Bora, Adrien Dousse, Kunal Sharma, Kaushik Sarma, Alexander Baev, G. Louis Hornyak, Guatam Dasgupta
To analyze optical properties of materials of interest one has to transform information obtained at the quantum level to relevant macroscopic properties for using with the Maxwellian constitutive relations. In general, three different tiers of theoretical modeling can be applied to undertake this non-trivial task: (i) modeling of intermolecular interactions and their influence on the property; (ii) linear scaling methodology, and (iii) multiscale modeling. The first approach involves models based on reaction field theory and polarizable continuum methods. Linear scaling is more elaborate method in which rigorous quantum mechanics is transcended by successive enlargements of the molecular models (the number of atoms) until the property value is converged. Ideally linear scaling methods can be implemented to be proportional to the system size, thereby extending the applicability range into the nanoscale regime, beyond ten thousand atoms. This is not achieved merely through high-performance computing, but rests critically on the development and adaptation of new computational schemes. Another, conceptually different approach to close the gaps between micro- and macro-scales is offered by multiscale modeling technology. The most important variation of contemporary multiscale modeling from atomic size elements to macroscopic homogenous media is given by the combination of quantum mechanics and extended classical physics models. This theoretical framework endows various models with rigorous insights extracted from the quantum nature of materials at the atomic scale and builds them into equations that are solved by advanced numerical techniques. In particular, joining quantum mechanics (QM) with molecular mechanics (MM) has become an important and popular area in ‘in silico’ research across a wide variety of fields (QM/MM). The multiscale modeling paradigm is sketched in Figure 11.