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34. On the development of a multi-scale modelling framework to study plasticity and damage through the coupling of finite element crystal plasticity and discrete dislocation plasticity

Author

Xu, Yilun, Dini, Daniele, and Balint, Daniel

Subjects
620.1
Abstract

The microstructure of polycrystalline materials crucially determines their mechanical performance in engineering applications. A multi-scale modelling approach is capable of representing the microstructure and thus capturing the material performance for various resolution requirement at different scales. Besides, the application of multi-scale modelling effectively reduces expense and improves efficiency of computations without loss of accuracy at sensitive zones. A method of concurrent coupling of planar discrete dislocation plasticity (DDP) and a crystal plasticity finite element (CPFE) method was devised for simulating plastic deformation in large polycrystals with discrete dislocation resolution in a single grain or cluster of grains for computational efficiency; computation time using the coupling method can be reduced by an order of magnitude compared to DDP. The method is based on an iterative scheme initiated by a sub-model calculation, which ensures displacement and traction compatibility at all nodes at the interface between the DDP and CPFE domains. The proposed coupling approach is demonstrated using two plane strain problems: (i) uniaxial tension of a bi-crystal film and (ii) indentation of a thin film on a substrate. The latter demonstrated that the rigid substrate assumption used in earlier discrete dislocation plasticity studies is inadequate for indentation depths that are large compared to the film thickness, i.e. the effect of the polycrystalline plastic substrate modelled using CPFE becomes important. The coupling method can be used to study a wider range of indentation depths than previously possible using DDP alone, without sacrificing the indentation size effect regime captured by DDP. A comprehensive indentation pressure formula has been developed by applying the proposed multi-scale modelling approach on a polycrystalline coating system. Planar nano-sliding and fretting calculations have been performed on thin films modelling by CPFE and DDP at different scales. Results of CPFE simulations provide an understanding of the role of microstructure on the plasticity and crack initiation during a contact problem. Beside, a new DDP computational framework has been proposed for a nano-fretting problem which is able to capture the contact size effect, simulate the dislocation evolution and predict the surface profile variation of thin films. Calculations of DDP simulations potentially provide CPFE simulations with fatigue parameters that is of more physical significance. The method is general and can be applied to any problem where finer resolution of dislocation mediated plasticity is required to study the mechanical response of polycrystalline materials, e.g. to capture size effects locally within a larger elastic/plastic boundary value problem. Also, the model described here will provide further opportunities for directly coupled, three-tiered multi-scale models compromising an overall macroscopic continua having embedded crystal plasticity and discrete dislocation plasticity models, respectively, as the length scale decreases in the area of interest. Finally, the methodology of the proposed coupling method will shed light on archiving a general compatibility of sub-regions and thus benefit other researchers who are working on coupling methods among other scales.

Published
2016
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48. Spatiotemporal Evolution and Influencing Factors of Tourism Economic Resilience under the Impact of COVID-19—A Case Study of Coastal Cities in China.

Author

Cai, Xiaolin and Xu, Yilun

Abstract

The COVID-19 pandemic has had a significant impact on the economic operations of many cities worldwide. Because tourism depends on migratory qualities, it has been severely constrained by the pandemic, which has affected the tourism business in several places. The research period for this paper is 2019–2021, and a comprehensive analysis of the spatiotemporal evolution pattern and influencing factors of the tourism economic resilience of China's coastal cities is conducted using the resistance index, Theil index, spatial autocorrelation analysis, and geographic detector model with the goal of deepening the theory of tourism economic resilience and providing a reference for the sustainable development of tourism. The results revealed several trends. First, in terms of temporal changes, the fluctuation trend of tourism's economic resilience in each city before and after the pandemic had a certain degree of stability and convergence, with only a few cities showing significant differences in their amplitude of fluctuations in 2021. Second, in the spatial pattern, the regions with high resilience and relatively high resilience were mainly concentrated in the western, northeastern, and eastern regions, and the northeastern-eastern regions with relatively high resilience were gradually developed in the agglomeration and a contiguous pattern. Third, the influencing factors of tourism's economic resilience before and after the pandemic, despite differences, are still largely affected by the combined influence of the city's economic level, industrial structure, tourism resource endowment, and other factors. [ABSTRACT FROM AUTHOR]

Published
2023
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50. GenPhys: From Physical Processes to Generative Models

Author

Liu, Ziming, Luo, Di, Xu, Yilun, Jaakkola, Tommi, and Tegmark, Max

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Quantum Physics, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, Physics - Data Analysis, Statistics and Probability, FOS: Physical sciences, Computational Physics (physics.comp-ph), Quantum Physics (quant-ph), Physics - Computational Physics, Data Analysis, Statistics and Probability (physics.data-an), Machine Learning (cs.LG)
Abstract

Since diffusion models (DM) and the more recent Poisson flow generative models (PFGM) are inspired by physical processes, it is reasonable to ask: Can physical processes offer additional new generative models? We show that the answer is yes. We introduce a general family, Generative Models from Physical Processes (GenPhys), where we translate partial differential equations (PDEs) describing physical processes to generative models. We show that generative models can be constructed from s-generative PDEs (s for smooth). GenPhys subsume the two existing generative models (DM and PFGM) and even give rise to new families of generative models, e.g., "Yukawa Generative Models" inspired from weak interactions. On the other hand, some physical processes by default do not belong to the GenPhys family, e.g., the wave equation and the Schr\"{o}dinger equation, but could be made into the GenPhys family with some modifications. Our goal with GenPhys is to explore and expand the design space of generative models.

Published
2023

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