We encounter granular materials on a daily basis. We walk up a gravel path or we eat our breakfast cereals. When handling granular materials on an industrial scale it is important to do so efficiently, to avoid unnecessary energy losses, wear and tear. To help designing efficient tools for handling these materials engineers uses numerical simulations. This project investigates the difference between the two main approaches to simulation of granular materials, the Smooth- and Non-smooth Discrete Element Methods by implementing the Smooth method into AgX dynamics were the Non-smooth method already is implemented, and then setup and execute a range of experiments to investigate their differences. The investigation shows both advantages and weaknesses for both methods. The result of simulations with smooth discrete element method are more consistent than with the nonsmooth discrete element method with respect to choice of time step and other parameters that can be chosen for the simulation. Smooth discrete element method have problems when it comes to extreme situations. The relative simulation time for system as large as treated by this project (more than1000) can not be shown to depend on the size of the system.

Sand is an appropriate material to embody and make visible the impulses which may pass through the moving hand and also permeate the universe. Its ability to absorb impressions means it can take on the full range of material states, solid, liquid or vapour, and allows it to speak with the rhythmic language the whole of nature itself uses. Developing a language of forms which more closely speaks this rhythmic language of nature requires an intimate knowledge of the processes of nature. Sand experiments undertaken show the formation a rich array of dazzling patterns. Chaos theory explains this self organizing capacity, and reveals the depth of interdependence of systems within nature. The aspect of self-similarity is also of central significance in appreciating how nature looks and function, and thus how it might be imaged. Drawings from nature were developed using sand as a parameter, starting with the single grain and translating the dynamism of moving sand into mark. Field trips involved looking for waves and repeated lines in nature, and observing how marks form in nature. Chaos theory provides a ground to bring together different spheres of knowledge ?? science, theology and art. It reveals the peculiarities of a material??s behaviour as being of critical importance in the mechanism of evolution. It also provides fresh insight into an incarnational Christian theological perspective, and the relational dynamic within the Trinity. The unity of far and near is also reflected in chaos theory in the self similarity of images. Romantic artists Turner and Van Gogh both engage in the search for a visual language of transcendence through nature using the use of the themes of chaos and order, with an emphasis on physicality and movement. Contemporary artists Goldsworthy, Blanchflower and Kirkeby ground their work in knowledge of material. Changes from solid and rigid to shifting and open show in the development of my work. The immediacy and dynamism of mark making in drawing and staining, ripping and sanding in painting gives process and materiality greater weight. The significance of relationality has reinforced the integrity of horizontal and vertical as expressed in nature and allowed for flexible repositioning of the image within a grid

Sand is an appropriate material to embody and make visible the impulses which may pass through the moving hand and also permeate the universe. Its ability to absorb impressions means it can take on the full range of material states, solid, liquid or vapour, and allows it to speak with the rhythmic language the whole of nature itself uses. Developing a language of forms which more closely speaks this rhythmic language of nature requires an intimate knowledge of the processes of nature. Sand experiments undertaken show the formation a rich array of dazzling patterns. Chaos theory explains this self organizing capacity, and reveals the depth of interdependence of systems within nature. The aspect of self-similarity is also of central significance in appreciating how nature looks and function, and thus how it might be imaged. Drawings from nature were developed using sand as a parameter, starting with the single grain and translating the dynamism of moving sand into mark. Field trips involved looking for waves and repeated lines in nature, and observing how marks form in nature. Chaos theory provides a ground to bring together different spheres of knowledge ?? science, theology and art. It reveals the peculiarities of a material??s behaviour as being of critical importance in the mechanism of evolution. It also provides fresh insight into an incarnational Christian theological perspective, and the relational dynamic within the Trinity. The unity of far and near is also reflected in chaos theory in the self similarity of images. Romantic artists Turner and Van Gogh both engage in the search for a visual language of transcendence through nature using the use of the themes of chaos and order, with an emphasis on physicality and movement. Contemporary artists Goldsworthy, Blanchflower and Kirkeby ground their work in knowledge of material. Changes from solid and rigid to shifting and open show in the development of my work. The immediacy and dynamism of mark making in drawing and staining, ripping and sanding in painting gives process and materiality greater weight. The significance of relationality has reinforced the integrity of horizontal and vertical as expressed in nature and allowed for flexible repositioning of the image within a grid

This dissertation describes efforts to evaluate a recently proposed continuum model for the dense flow of dry granular materials (Jop, Forterre & Pouliquen, 2006, Nature, 441, 167-192). The model, based upon a generalisation of Coulomb sliding friction, is known to perform well when modelling certain simple free surface flows. We extend the application of this model to a wide range of flow configurations, beginning with six simple flows studied in detailed experiments (GDR MiDi, 2004, Eur. Phys. J. E, 14, 341-366). Two-dimensional shearing flows and problems of linear stability are also addressed. These examples are used to underpin a thorough discussion of the strengths and weaknesses of the model. In order to calculate the behaviour of granular material in more complicated configurations, it is necessary to undertake a numerical solution. We discuss several computational techniques appropriate to the model, with careful attention paid to the evolution of any shear-free regions that may arise. In addition, we develop a numerical scheme, based upon a marker-and-cell method, that is capable of modelling two-dimensional granular flow with a moving free surface. A detailed discussion of our unsuccessful attempt to construct a scheme based upon Lagrangian finite elements is presented in an appendix. We apply the marker-and-cell code to the key problem of granular slumping (Balmforth & Kerswell, 2005, J. Fluid Mech., 538, 399-428), which has hitherto resisted explanation by modelling approaches based on various reduced (shallow water) models. With our numerical scheme, we are able to lift the assumptions required for other models, and make predictions in good qualitative agreement with the experimental data. An additional chapter describes the largely unrelated problem of contact between two objects separated by a viscous fluid. Although classical lubrication theory suggests that two locally smooth objects converging under gravity will make contact only after infinite time, we discuss several physical effects that may promote contact in finite time. Detailed calculations are presented to illustrate how the presence of a sharp asperity can modify the approach to contact.

The current simulation method for granular dynamics used by the physics engine AGX Dynamics is a nonsmooth variant of the popular Discrete Element Method (DEM). While powerful, there is a need for close to real time simulations of a higher spatial resolution than currently possible. In this thesis a data-driven model reduction approach using machine learning was considered. A data-driven simulation pipeline was presented and partially implemented. The method consists of sampling the velocity and density field of the granular particles and teaching a machine learning algorithm to predict the particles' interaction with a bulldozer blade as well as predicting the time evolution of its velocity field. A procedure for producing training scenarios and training data for the machine learning algorithm was implemented as well as several machine learning algorithms; a linear regressor, a multilayer perceptron and a convolutional neural network. The results showed that the method is promising, however further work will need to show whether or not the pipeline is feasible to implement in a simulation.