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Has files: YesSubject: search.filters.subject.460207 Modelling and simulation

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    Computationally generating and simulating plant-life using parametric L-systems : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Science in Computer Science at Massey University, Albany, New Zealand
    (Massey University, 2020) Crankshaw, Matthew Halen
    Producing and simulating realistic-looking plant-life assets for 3D applications is a challenging task. An important contributing factor in the realism of plant models in modern graphics applications is its motion, but creating plant assets that both look and move realistically is a tedious and time-consuming process. Lindenmayer systems are a useful tool for producing a set of instructions that represent the structures of organic life, such as algae, flora, and trees. These instructions can be interpreted using turtle graphics to render realistic models. A class of L-system known as parametric L-systems can provide extra information through the rewriting process using parameters. The use of parametric L-systems is investigated to provide both the physical and geometric properties of a plant, such that a model can be rendered and physically simulate the effects of gravity and wind. The relationship between the L-systems’ rewriting mechanism and the interpreter system is investigated and discussed. The parametric class of L-system is a grammar similar to that of a recursive programming language. A compiler-like software solution is developed, that is capable of taking L-system language as input and producing instructions and information to the interpreter system. A three-stage 3D graphics software system is implemented to interpret the L-system instructions and information in order to display complex plant models. A separate physics system is also developed to simulate the motion of the resulting plant models under gravity or wind. There is a trade-off between the complexity of the rewriting system and the interpreting system. Consideration as to the advantages and disadvantages of these trade-offs is discussed. It is shown that parametric L-systems can create plant structures that have variations in their branching structure and physical features, which can provide the physical properties of branches necessary to simulate forces like gravity and wind. There is considerable benefit to having a software system produce both the geometry of a plant model and the information necessary for simulation, as it allows a plant to be defined in a single definition in the form of an L-system.
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    Parallel simulation methods for large-scale agent-based predator-prey systems : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at Massey University, Albany, New Zealand
    (Massey University, 2019) Quach, Dara (Minh) Quang
    The Animat is an agent-based artificial-life model that is suitable for gaining insight into the interactions of autonomous individuals in complex predator-prey systems and the emergent phenomena they may exhibit. Certain dynamics of the model may only be present in large systems, and a large number of agents may be required to compare with macroscopic models. Large systems can be infeasible to simulate on single-core machines due to processing time required. The model can be parallelised to improve the performance; however, reproducing the original model behaviour and retaining the performance gain is not straightforward. Parallel update strategies and data structures for multi-core CPU and graphical processing units (GPUs) are developed to simulate a typical predator-prey Animat model with improved perfor- mance while reproducing the behaviour of the original model. An analysis is presented of the model to identify dependencies and conditions the parallel update strategy must satisfy to retain original model behaviour. The parallel update strategy for multi-core CPUs is constructed using a spatial domain decomposition approach and supporting data structure. The GPU implementation is developed with a new update strategy that consists of an iterative conflict resolution method and priority number system to simultaneously update many agents with thousands of GPU cores. This update method is supported by a compressed sparse data structure developed to allow for efficient memory transactions. The performance of the Animat simulation is improved with parallelism and without a change in model behaviour. The simulation usability is considered, and an internal agent definition system using a CUDA device Lambda feature is developed to improve the ease of configuring agents without significant changes to the program and loss of performance.