Cellular automaton model of precipitation/dissolution coupled with solute transport

Precipitation/dissolution reactions coupled with solute transport are modelled as a cellular automaton in which solute molecules perform a random walk on a regular lattice and react according to a local probabilistic rule. Stationary solid particles dissolve with a certain probability and, provided solid is already present or the solution is saturated, solute particles have a probability to precipitate. In our simulation of the dissolution of a solid block inside uniformly flowing water we obtain solid precipitation downstream from the original solid edge, in contrast to the standard reaction-transport equations. The observed effect is the result of fluctuations in solute density and diminishes when we average over a larger ensemble. The additional precipitation of solid is accompanied by a substantial reduction in the relatively small solute concentration. The model is appropriate for the study of the r\^ole of intrinsic fluctuations in the presence of reaction thresholds and can be employed to investigate porosity changes associated with the carbonation of cement.Comment: LaTeX file, 13 pages. To appear in Journal of Statistical Physics (Proceedings of Lattice Gas'94, June 1994, Princeton). Figures available from author. Requests may be submitted by E-mail ([email protected]) or ordinary mail (Paul Scherrer Institute, CH-5232 Villigen PSI, Switzerland

Multiscale, Data-Driven and Nonlocal Modeling of Granular Materials

Granular materials are ubiquitous in both nature and technology. They play a key role in many applications ranging from storing food and energy to building reusable habitats and soft robots. Yet, predicting the continuum mechanical response of granular materials continues to present extraordinary challenges, despite the apparently simple laws that govern particle-scale interactions. This is largely due to the complex history dependence arising from the continuous rearrangement of their internal structure, and the nonlocality emerging from their self-organization. There is clearly an urge to develop methods that adequately address these two aspects, while bridging the long-standing divide between the grain- and the continuum scale. This dissertation introduces novel theoretical and computational approaches for behavior prediction in granular solids. To begin with, we develop a framework for investigating their incremental behavior from the perspective of plasticity theory. It relies on systematically probing, through level-set discrete element calculations, the response of granular assemblies from the same initial state to multiple directions is stress space. We then extract the state- and history-dependent elasticity and plastic flow, and investigate the evolution of pertinent internal variables. We specifically study assemblies of sand particles characterized by X-ray computed tomography, as well as morphologically simpler counterparts of the same systems. Naturally arising from this investigation is the concept of a granular genome. Next, inspired by the abundance of generated high-fidelity micromechanical data, we develop an alternative data-driven approach for behavior prediction. This new multiscale modeling paradigm completely bypasses the need to define a constitutive law. Instead, the problem is directly formulated on a material data set, generated by grain-scale calculations, while pertinent constraints and conservation laws are enforced. We particularly focus on the sampling of the mechanical phase space, and develop two methods for parametrizing material history, one thermodynamically motivated and one statistically inspired. In the remainder of the thesis, we direct our attention to the understanding and modeling of nonlocality. We base our investigation on data derived from a discrete element simulation of a sample of sand subjected to triaxial compression and undergoing shear banding. By representing the granular system as a complex network, we study the self-organized and cooperative evolution of topology, kinematics and kinetics within the shear band. We specifically characterize the evolution of fundamental topological structures called force cycles, and propose a novel order parameter for the system, the minimal cycle coefficient. We find that this coefficient governs the stability of force chains, which succumb to buckling as they grow beyond a characteristic maximum length. We also analyze the statistics of nonaffine kinematics, which involve rotational and vortical particle motion. Finally, inspired by these findings, we extend the previously introduced data-driven paradigm to include nonaffine kinematics within a weakly nonlocal micropolar continuum description. By formulating the problem on a phase space augmented by higher-order kinematics and their conjugate kinetics, we bypass for the first time the need to define an internal length scale, which is instead discovered from the data. By carrying out a data-driven prediction of shear banding, we find that this nonlocal extension of the framework resolves the ill-posedness inherent to the classical continuum description. Finally, by comparing with available experimental data on the same problem, we are able to validate our theoretical developments.</p

Data-Driven Multiscale Modeling in Mechanics

We present a Data-Driven framework for multiscale mechanical analysis of materials. The proposed framework relies on the Data-Driven formulation in mechanics (Kirchdoerfer and Ortiz 2016), with the material data being directly extracted from lower-scale computations. Particular emphasis is placed on two key elements: the parametrization of material history, and the optimal sampling of the mechanical state space. We demonstrate an application of the framework in the prediction of the behavior of sand, a prototypical complex history-dependent material. In particular, the model is able to predict the material response under complex nonmonotonic loading paths, and compares well against plane strain and triaxial compression shear banding experiments

A discretization-convergent Level-Set-DEM

The recently developed level-set-DEM is able to seamlessly handle arbitrarily shaped grains and their contacts through a discrete level-set representation of grains' volume and a node-based discretization of their bounding surfaces. Heretofore, the convergence properties of LS-DEM with refinement of these discretizations have not been examined. Here, we examine these properties and show that the original LS-DEM diverges upon surface discretization refinement due to its force-based discrete contact formulation. Next, we fix this issue by adopting a continuum-based contact formulation wherein the contact interactions are traction-based, and show that the adapted LS-DEM is fully discretization convergent. Lastly, we discuss the significance of convergence in capturing the physical response, as well as a few other convergence-related topics of practical importance

A reaction-diffusion model for the hydration/setting of cement

We propose a heterogeneous reaction-diffusion model for the hydration and setting of cement. The model is based on diffusional ion transport and on cement specific chemical dissolution/precipitation reactions under spatial heterogeneous solid/liquid conditions. We simulate the spatial and temporal evolution of precipitated micro structures starting from initial random configurations of anhydrous cement particles. Though the simulations have been performed for two dimensional systems, we are able to reproduce qualitatively basic features of the cement hydration problem. The proposed model is also applicable to general water/mineral systems.Comment: REVTeX (12 pages), 4 postscript figures, tarred, gzipped, uuencoded using `uufiles', coming with separate file(s). Figure 1 consists of 6 color plates; if you have no color printer try to send it to a black&white postscript-plotte

Conceptualising the geographic world: the dimensions of negotiation in crowdsourced cartography

In crowdsourced cartographic projects, mappers coordinate their efforts through online tools to produce digital geospatial artefacts, such as maps and gazetteers, which were once the exclusive territory of professional surveyors and cartographers. In order to produce meaningful and coherent data, contributors need to negotiate a shared conceptualisation that defines the domain concepts, such as road, building, train station, forest, and lake, enabling the communi- cation of geographic knowledge. Considering the OpenStreetMap Wiki website as a case study, this article investigates the nature of this negotiation, driven by a small group of mappers in a context of high contribution inequality. De- spite the apparent consensus on the conceptualisation, the negotiation keeps unfolding in a tension between alternative representations, which are often in- commensurable, i.e., hard to integrate and reconcile. In this study, we identify six complementary dimensions of incommensurability that recur in the nego- tiation: (i) ontology, (ii) cartography, (iii) culture and language, (iv) lexical definitions, (v) granularity, and (vi) semantic overload and duplication

Responsible governance in science and technology policy: Reflections from Europe, China and India

This Issues and Opinions Essay provides insights on developments and challenges related to responsible governance in the field of science and technology (S&T) across Europe, China and India. The Essay presents an overview of policy debates and some key public policy documents in these three geopolitical areas, exploring how responsibility is viewed and outlined in the policy domain. Considerations on the range of processes and actors affecting the relationship between science and society in China and India are also presented. Finally, the Essay introduces ‘responsiveness’ as a possible area for comparative research work on responsibility in S&T and relevant policy collaboration amongst the three regions