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Implicit models inherently support automatic blending and trivial collision detection which makes them an effective tool for designing complex organic shapes with many applications in various areas of research including surgical simulation systems. However, slow rendering speeds can adversely affect the performance of simulation and modelling systems. In addition, when the models are incorporated in a surgical simulation system, interactive and smooth cutting becomes a required feature for many procedures. In this research, we propose a comprehensive framework for high-performance rendering and physically-based animation of tissues modelled using implicit surfaces. Our goal is to address performance and scalability issues that arise in rendering complex implicit models as well as in dynamic interactions between surgical tool and models. Complex models can be created with implicit primitives, blending operators, affine transformations, deformations and constructive solid geometry in a design environment that organizes all these in a scene graph data structure called the BlobTree. We show that the BlobTree modelling approach provides a very compact data structure which supports the requirements above, as well as incremental changes and trivial collision detection. A GPU-assisted surface extraction algorithm is proposed to support interactive modelling of complex BlobTree models. Using a finite element approach we discretize those models for accurate physically-based animation. Our system provides an interactive cutting ability using smooth intersection surfaces. We show an application of our system in a human skull craniotomy simulation. / Graduate / 0984 / pourya.shirazian@gmail.com

Master-Slave teleoperation systems are designed to extend a human's manipulation capability to remote tasks. Recent applications of these systems are in robotic therapy, telesurgery, and medical simulators. In practice, due to the uncertainties in the operator and environment dynamics, and time delay, stability and performance are compromised. Stability-based and performance-based controllers are introduced for these systems. A major class of the former controllers are based on the passivity theory and suffer from the assumed unbounded range of dynamics which is rather unrealistic. The latter class of controllers are mostly adaptive methods that are based on performance optimization. The theme of this thesis is on the development of new stability analysis methods, control strategies, and implementation techniques for enhanced trade-off between stability and performance. I have developed a less conservative passivity-based robust stability method and introduced, for the first time, the notion of Bounded Impedance Absolute Stability. The method provides mathematical and visual aids to incorporate bounds of the passive environment impedance for less conservative guaranteed stability conditions, promising a better compromise between stability and performance. I have extended the new method to include the dynamic range of the human operator for increased stability margins. I have also used the new method to develop a bilateral controller robust to time delays. Furthermore, I have investigated the effect of sampling position versus velocity for various sampling models to obtain less conservative coupled stability conditions for haptic simulation systems. Estimates of the environment dynamics are required to include their variations. Therefore, I have proposed two new real-time parameter estimation methods for linear and nonlinear contacts and experimentally evaluated and compared them with the available techniques. Finally, I have introduced needle insertion as a task in telerobotic systems to combine the expertise of the surgeon with robotic control. Here, the very first few steps needed to effectively control the targeting needles have been taken. I have developed a mechanics-based dynamic model for bevel-tip flexible needles inserted into soft tissues. Finite element models are used to estimate soft tissue deformation, while the mechanics-based model is used to predict needle deflections due to bevel-tip asymmetry. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2011-12-23 01:19:47.535

INCOSE defines Model-Based Systems Engineering (MBSE) as "the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases." One very important development is the utilization of MBSE to develop distributed and hybrid (discrete-continuous) simulation modeling systems. MBSE can help to describe the systems to be modeled and help make the right decisions and partitions to tame complexity. The ability to embrace conceptual modeling and interoperability techniques during systems specification and design presents a great advantage in distributed and hybrid simulation systems development efforts. Our research is aimed at the definition of a methodological framework that uses MBSE languages, methods and tools for the development of these simulation systems. A model-based composition approach is defined at the initial steps to identify distributed systems interoperability requirements and hybrid simulation systems characteristics. Guidelines are developed to adopt simulation interoperability standards and conceptual modeling techniques using MBSE methods and tools. Domain specific system complexity and behavior can be captured with model-based approaches during the system architecture and functional design requirements definition. MBSE can allow simulation engineers to formally model different aspects of a problem ranging from architectures to corresponding behavioral analysis, to functional decompositions and user requirements (Jobe, 2008).

Digital simulation is a useful tool in many scientific areas. Interactive simulation can provide the user with a better appreciation of a problem area. With the introduction of large scale integrated circuits and in particular the advent of the microprocessor, a large amount of computing power is available at low cost. The aim of this project therefore was to investigate the feasibility of producing a minimum cost, easy to use, interactive digital simulation system. A hardware microcomputer system was constructed to test simulation program concepts and an interactive program was designed and developed for this system. By the use of a set of commands and subsequent interactive dialogue, the program allows the user to enter and perform simulation tasks. The simulation program is unusual in that it does not require a sophisticated operating system or other system programs such as compilers. The program does not require any backup memory devices such as magnetic disc or tape and indeed could be stored in ROM or EPROM. The program is designed to be flexible and extendable and could be easily modified to run with a variety of hardware configurations. The highly interactive nature of the system means that its operation requires very little programming experience. The microcomputer hardware system uses two microprocessors together with specially designed interfaces. One was dedicated to the implementation of the simulation equations, and the other provided an input/output capability including a low cost CRT display.

Pathfinding is critical to virtual simulation applications. One of the most prominent pathfinding challenges is the fast computation of path plans in large and realistic virtual terrain environments. To tackle this problem, this work proposes the exploration of a quadtree structure in the navigation map representation of large real-world virtual terrains. Exploring a hierarchical approach for virtual terrain representation, we detail how a global hierarchical pathfinding algorithm searches for a path in a coarse initial navigation map representation. Then, during execution time, the pathfinding algorithm refines regions of interest in this terrain representation in order to compute paths with a higher quality in areas where a large amount of navigation obstacles is found. The computational time of such hierarchical pathfinding algorithm is systematically measured in different hierarchical and non-hierarchical terrain representation structures that are instantiated in the modeling of a small real-world terrain scenario. Then, similar experiments are developed in a large real-world virtual terrain that is inserted in a real-life simulation system for the development of military tactical training exercises. The results show that the computational time required to generate pathfinding answers can be optimized when the proposed hierarchical pathfinding algorithm along with the easy and reliable implementation of the quadtree-based navigation map representation of the large virtual terrain are explored in the development of simulation systems.

Over the course of this thesis we will build and develop a model for the dynamics of an environmentally transmitted disease such as cholera. We will also develop methods to analyse and understand that model. The dynamics of a disease in a heterogeneous developing world city have not yet been fully explored, particularly when those dynamics are affected by a natural disaster. Yet, natural disasters such as floods alter infrastructure and population characteristics in a manner that affects disease transmission. Therefore, we shall address this omission from the literature. We will also develop a novel model analysis framework for 'systems epidemiology' where we combine systems biology techniques with epidemiological modelling.

The failure of many System of Systems (SoS) enterprises can be attributed to the inappropriate application of traditional Systems Engineering (SE) processes within the SoS domain, because of the mistaken belief that a SoS can be regarded as a single large, or complex, system. SoS Engineering (SoSE) is a sub-discipline of SE; Risk Management and Modelling and Simulation (M&S) are key areas within SoSE, both of which also lie within the traditional SE domain. Risk Management of SoS requires a different approach to that currently taken for individual systems; if risk is managed for each component system then it cannot be assumed that the aggregated affect will be to mitigate risk at the SoS level. A literature review was undertaken examining three themes: (1) SoS Engineering (SoSE), (2) M&S and (3) Risk. Theme 1 of the literature provided insight into the activities comprising SoSE and its difference from traditional SE with risk management identified as a key activity. The second theme discussed the application of M&S to SoS, providing an output, which supported the identification of appropriate techniques and concluding that, the inherent complexity of a SoS required the use of M&S in order to support SoSE activities. Current risk management approaches were reviewed in theme 3 as well as the management of SoS risk. Although some specific examples of the management of SoS risk were found, no mature, general approach was identified, indicating a gap in current knowledge. However, it was noted most of these examples were underpinned by M&S approaches. It was therefore concluded a general approach SoS risk management utilising M&S methods would be of benefit. In order to fill the gap identified in current knowledge, this research proposed a new model based approach to Risk Management where risk identification was supported by a framework, which combined SoS system of interest dimensions with holistic risk types, where the resulting risks and contributing factors are captured in a causal network. Analysis of the causal network using a model technique selection tool, developed as part of this research, allowed the causal network to be simplified through the replacement of groups of elements within the network by appropriate supporting models. The Bayesian Belief Network (BBN) was identified as a suitable method to represent SoS risk. Supporting models run in Monte Carlo Simulations allowed data to be generated from which the risk BBNs could learn, thereby providing a more quantitative approach to SoS risk management. A method was developed which provided context to the BBN risk output through comparison with worst and best-case risk probabilities. The model based approach to Risk Management was applied to two very different case studies: Close Air Support mission planning and the Wheat Supply Chain, UK National Food Security risks, demonstrating its effectiveness and adaptability. The research established that the SoS SoI is essential for effective SoS risk identification and analysis of risk transfer, effective SoS modelling requires a range of techniques where suitability is determined by the problem context, the responsibility for SoS Risk Management is related to the overall SoS classification and the model based approach to SoS risk management was effective for both application case studies.

Please read the abstract in the section 00front of this document / Dissertation (M Eng (Mechanical Engineering))--University of Pretoria, 2007. / Mechanical and Aeronautical Engineering / unrestricted

Socially coupled systems are comprised of inter-dependent social, organizational, economic, infrastructure and physical networks. Today's urban regions serve as an excellent example of such systems. People and institutions confront the implications of the increasing scale of information becoming available due to a combination of advances in pervasive computing, data acquisition systems as well as high performance computing. Integrated modeling and decision making environments are necessary to support planning, analysis and counter factual experiments to study these complex systems. Here, we describe SIMFRASTRUCTURE -- a computational infrastructure that supports high performance computing oriented decision and analytics environments to study socially coupled systems. Simfrastructure provides a middleware with multiplexing mechanism by which modeling environments with simple and intuitive user-interfaces can be plugged in as front-end systems, and high-end computing resources -- such as clusters, grids and clouds -- can be plugged in as back-end systems for execution. This makes several key aspects of simulation systems such as the computational complexity, data management and resource management and allocation completely transparent to the users. The decoupling of user interfaces, data repository and computational resources from simulation execution allows users to run simulations and access the results asynchronously and enables them to add new datasets and simulation models dynamically.  Simfrastructure enables implementation of a simple yet powerful modeling environment with built-in analytics-as-aservice platform, which provides seamless access to high end computational resources, through an intuitive interface for studying socially coupled systems. We illustrate the applicability of Simfrastructure in the context of an integrated modeling environment to study public health epidemiology and network science. / Master of Science