Modeling of natural phenomena has been of particular interest in the graphics ommunity in recent years. This thesis will explore a method for creating and animating orb webs using a coupled spring-mass system. Using a spring-mass system for creating the orb web is ideal as we can represent each web strand using coupled spring-mass pairs. This allows the orb web simulator to be physically based, i.e., the simulation follows the laws that act on objects in the real world. This in turn simplifies the process of animating the web, as the animation emerges from the simulator without anyone having to set it up explicitly. Since this model is physically based, it would allow for realistic visualization of effects such as observing an orb web under a wind. In the children's book ``Charlotte's Web', the spider creates orb webs with words inscribed on them. Charlotte's web is used as an inspiration, in this thesis, to create webs which no real world spider could possibly create, while keeping the model physically based. This involves modifying the orb web such that the target text shows up on the orb web while keeping the web looking as natural as possible.

Reliable hydrological model simulations are the result of numerous complex interactions among hydrological inputs, landscape properties, and initial conditions. Determination of the effects of these factors is one of the main challenges in hydrological modelling. This situation becomes even more difficult in cold regions due to the ungauged nature of subarctic and arctic environments.<p> This research work is an attempt to apply a new approach for modelling snowcover ablation and snowmelt runoff in complex subarctic environments with limited data while retaining integrity in the process representations. The modelling strategy is based on the incorporation of both detailed process understanding and inputs along with information gained from observations of basin-wide streamflow phenomenon; essentially a combination of deductive and inductive approaches. The study was conducted in the Wolf Creek Research Basin, Yukon Territory, using three models, a small-scale physically based hydrological model, a land surface scheme, and a land surface hydrological model. The spatial representation was based on previous research studies and observations, and was accomplished by incorporating landscape units, defined according to topography and vegetation, as the spatial model elements.<p> Comparisons between distributed and aggregated modelling approaches showed that simulations incorporating distributed initial snowcover and corrected solar radiation were able to properly simulate snowcover ablation and snowmelt runoff whereas the aggregated modelling approaches were unable to represent the differential snowmelt rates and complex snowmelt runoff dynamics. Similarly, the inclusion of spatially distributed information in a land surface scheme clearly improved simulations of snowcover ablation. Application of the same modelling approach at a larger scale using the same landscape based parameterisation showed satisfactory results in simulating snowcover ablation and snowmelt runoff with minimal calibration. Verification of this approach in an arctic basin illustrated that landscape based parameters are a feasible regionalisation framework for distributed and physically based models. In summary, the proposed modelling philosophy, based on the combination of an inductive and deductive reasoning, is a suitable strategy for reliable predictions of snowcover ablation and snowmelt runoff in cold regions and complex environments.

Despite the notable progress in physically-based rendering, there is still a long way to go before we can automatically generate predictable images of biological materials. In this thesis, we address an open problem in this area, namely the spectral simulation of light interaction with human skin, and propose a novel biophysically-based model that accounts for all components of light propagation in skin tissues, namely surface reflectance, subsurface reflectance and transmittance, and the biological mechanisms of light absorption by pigments in these tissues. The model is controlled by biologically meaningful parameters, and its formulation, based on standard Monte Carlo techniques, enables its straightforward incorporation into realistic image synthesis frameworks. Besides its biophysicallybased nature, the key difference between the proposed model and the existing skin models is its comprehensiveness, i. e. , it computes both spectral (reflectance and transmittance) and scattering (bidirectional surface-scattering distribution function) quantities for skin specimens. In order to assess the predictability of our simulations, we evaluate their accuracy by comparing results from the model with actual skin measured data. We also present computer generated images to illustrate the flexibility of the proposed model with respect to variations in the biological input data, and its applicability not only in the predictive image synthesis of different skin tones, but also in the spectral simulation of medical conditions.

In this physically-based tornado simulation, the tornado-scale approach techniques are applied to simulate the tornado formation environment. The three-dimensional Navier-Stokes equations for incompressible viscous fluid flows are used to model the tornado dynamics. The boundary conditions applied in this simulation lead to rotating and uplifting flow movement as found in real tornadoes and tornado research literatures. Moreover, a particle system is incorporated with the model equation solutions to model the irregular tornado shapes. Also, together with appropriate boundary conditions, varied particle control schemes produce tornadoes with different shapes. Furthermore, a modified metaball scheme is used to smooth the density distribution. Texture mapping, antialising, animation and volume rendering are applied to produce realistic visual results. The rendering algorithm is implemented in OpenGL.

Despite the notable progress in physically-based rendering, there is still a long way to go before we can automatically generate predictable images of biological materials. In this thesis, we address an open problem in this area, namely the spectral simulation of light interaction with human skin, and propose a novel biophysically-based model that accounts for all components of light propagation in skin tissues, namely surface reflectance, subsurface reflectance and transmittance, and the biological mechanisms of light absorption by pigments in these tissues. The model is controlled by biologically meaningful parameters, and its formulation, based on standard Monte Carlo techniques, enables its straightforward incorporation into realistic image synthesis frameworks. Besides its biophysicallybased nature, the key difference between the proposed model and the existing skin models is its comprehensiveness, i. e. , it computes both spectral (reflectance and transmittance) and scattering (bidirectional surface-scattering distribution function) quantities for skin specimens. In order to assess the predictability of our simulations, we evaluate their accuracy by comparing results from the model with actual skin measured data. We also present computer generated images to illustrate the flexibility of the proposed model with respect to variations in the biological input data, and its applicability not only in the predictive image synthesis of different skin tones, but also in the spectral simulation of medical conditions.

In this physically-based tornado simulation, the tornado-scale approach techniques are applied to simulate the tornado formation environment. The three-dimensional Navier-Stokes equations for incompressible viscous fluid flows are used to model the tornado dynamics. The boundary conditions applied in this simulation lead to rotating and uplifting flow movement as found in real tornadoes and tornado research literatures. Moreover, a particle system is incorporated with the model equation solutions to model the irregular tornado shapes. Also, together with appropriate boundary conditions, varied particle control schemes produce tornadoes with different shapes. Furthermore, a modified metaball scheme is used to smooth the density distribution. Texture mapping, antialising, animation and volume rendering are applied to produce realistic visual results. The rendering algorithm is implemented in OpenGL.

Modeling of natural phenomena has been of particular interest in the graphics ommunity in recent years. This thesis will explore a method for creating and animating orb webs using a coupled spring-mass system. Using a spring-mass system for creating the orb web is ideal as we can represent each web strand using coupled spring-mass pairs. This allows the orb web simulator to be physically based, i.e., the simulation follows the laws that act on objects in the real world. This in turn simplifies the process of animating the web, as the animation emerges from the simulator without anyone having to set it up explicitly. Since this model is physically based, it would allow for realistic visualization of effects such as observing an orb web under a wind. In the children's book ``Charlotte's Web', the spider creates orb webs with words inscribed on them. Charlotte's web is used as an inspiration, in this thesis, to create webs which no real world spider could possibly create, while keeping the model physically based. This involves modifying the orb web such that the target text shows up on the orb web while keeping the web looking as natural as possible.

Reliable hydrological model simulations are the result of numerous complex interactions among hydrological inputs, landscape properties, and initial conditions. Determination of the effects of these factors is one of the main challenges in hydrological modelling. This situation becomes even more difficult in cold regions due to the ungauged nature of subarctic and arctic environments.<p> This research work is an attempt to apply a new approach for modelling snowcover ablation and snowmelt runoff in complex subarctic environments with limited data while retaining integrity in the process representations. The modelling strategy is based on the incorporation of both detailed process understanding and inputs along with information gained from observations of basin-wide streamflow phenomenon; essentially a combination of deductive and inductive approaches. The study was conducted in the Wolf Creek Research Basin, Yukon Territory, using three models, a small-scale physically based hydrological model, a land surface scheme, and a land surface hydrological model. The spatial representation was based on previous research studies and observations, and was accomplished by incorporating landscape units, defined according to topography and vegetation, as the spatial model elements.<p> Comparisons between distributed and aggregated modelling approaches showed that simulations incorporating distributed initial snowcover and corrected solar radiation were able to properly simulate snowcover ablation and snowmelt runoff whereas the aggregated modelling approaches were unable to represent the differential snowmelt rates and complex snowmelt runoff dynamics. Similarly, the inclusion of spatially distributed information in a land surface scheme clearly improved simulations of snowcover ablation. Application of the same modelling approach at a larger scale using the same landscape based parameterisation showed satisfactory results in simulating snowcover ablation and snowmelt runoff with minimal calibration. Verification of this approach in an arctic basin illustrated that landscape based parameters are a feasible regionalisation framework for distributed and physically based models. In summary, the proposed modelling philosophy, based on the combination of an inductive and deductive reasoning, is a suitable strategy for reliable predictions of snowcover ablation and snowmelt runoff in cold regions and complex environments.

This work presents an approach to effectively integrate into one unified modular fire simulation framework the major processes related to fire, namely: a burning process, chemical combustion, heat distribution, decomposition and deformation of burning solids, and rigid body simulation of the residue. Simulators for every stage are described, and the modular structure enables switching to different simulators if more accuracy or more interactivity is desired. A “Stable Fluids” based three gas system is used to model the combustion process, and the heat generated during the combustion is used to drive the flow of the hot air. Objects, if exposed to enough heat, ignite and start burning. The decomposition of the burning object is modeled as a level set method, driven by the pyrolysis process, where the burning object releases combustible gases. Secondary deformation effects, such as bending burning matches and crumpling burning paper, are modeled as a proxy based deformation. Physically based simulation, done at interactive rates, enables the user to ef- ficiently test different setups, as well as interact and change the conditions during the simulation. The graphics card is used to generate additional frames for real-time visualization. This work further proposes a method for controlling and directing high resolution simulations. An interactive coarse resolution simulation is provided to the user as a “preview” to control and achieve the desired simulation behavior. A higher resolution “final” simulation that creates all the fine scale behavior is matched to the preview simulation such that the preview and final simulations behave in a similar manner. In this dissertation, we highlighted a gap within the CG community for the simulation of fire. There has not previously been a physically based yet interactive simulation for fire. This dissertation describes a unified simulation framework for physically based simulation of fire and burning. Our results show that our implementation can model fire, objects catching fire, burning objects, decomposition of burning objects, and additional secondary deformations. The results are plausible even at interactive frame rates, and controllable.

Tornado simulations in the visual effects industry have always been an interesting problem. Developing tools to provide more control over such effects is an important and challenging task. Current methods to achieve these effects use either particle systems or fluid simulation. Particle systems give a lot of control over the simulation but do not take into account the fluid characteristics of tornadoes. The other method which involves fluid simulation models the fluid behavior accurately but does not give control over the simulation. In this thesis, a novel method to model tornado behavior is presented. A tool based on this method was also created. The method proposed in this thesis uses a hybrid approach that combines the flexibility of particle systems while producing interesting swirling motions inherent in the fluids. The main focus of the research is on providing easy-to-use controls for art directors to help them achieve the desired look of the simulation effectively. A variety of controls is provided which include the overall shape, path, rotation, debris, surface, swirling motion, and interaction with the environment. The implementation was done in Houdini, which is a 3D animation software whose node based system allows an algorithmic approach to the problem and integrates well with the current tools. The tool allows the user to create animations that reflect the visual characteristics of real tornadoes. The usefulness of the tool was evaluated among participants who had some experience in 3D animation software. The results from the simulation and evaluation feedback reveal that the tool successfully allowed the users to create tornadoes of their choice efficiently.