Interactive computational models of particle dynamics using virtual reality

An increasing number of industrial applications rely on computational models to reduce costs in product design, development, and testing cycles. Here, the authors discuss an interactive environment for the visualization, analysis, and modification of computational models used in industrial settings. In particular, they focus on interactively placing massless, massed, and evaporating particulate matter in computational fluid dynamics applications.they discuss the numerical model used to compute the particle pathlines in the fluid flow for display and analysis. They briefly describe the toolkits developed for vector and scalar field visualization, interactive particulate source placement, and a three-dimensional GUI interface. This system is currently used in two industrial applications, and they present the tools in the context of these applications. They summarize the current state of the project and offer directions for future research

Analytic streamline calculations on linear tetrahedra

Analytic solutions for streamlines within tetrahedra are used to define operators that accurately and efficiently compute streamlines. The method presented here is based on linear interpolation, and therefore produces exact results for linear velocity fields. In addition, the method requires less computation than the forward Euler numerical method. Results are presented that compare accuracy measurements of the method with forward Euler and fourth order Runge-Kutta applied to both a linear and a nonlinear velocity field

Interactive simulation and analysis of emission reduction systems in commercial boilers

In this paper the authors describe an interactive virtual environment developed to model an emission reduction system for commercial boilers. The interactive environment is used to optimize the performance of the reduction system through the spatial adjustment and spray reconfiguration of reagent injectors. They describe the three principal components of the system: a computational model for the particle dynamics, a three-dimensional display device and graphics environment, and the communication layer that allows the interaction of the user in the visualization environment with the computational model. Timing results for each component are given for three hardware configurations that demonstrate the real-time performance of this tool

Design Optimization of Vena Cava Filters: An application to dual filtration devices

Pulmonary embolism (PE) is a significant medical problem that results in over 300,000 fatalities per year. A common preventative treatment for PE is the insertion of a metallic filter into the inferior vena cava that traps thrombi before they reach the lungs. The goal of this work is to use methods of mathematical modeling and design optimization to determine the configuration of trapped thrombi that minimizes the hemodynamic disruption. The resulting configuration has implications for constructing an optimally designed vena cava filter. Computational fluid dynamics is coupled with a nonlinear optimization algorithm to determine the optimal configuration of trapped model thrombus in the inferior vena cava. The location and shape of the thrombus are parameterized, and an objective function, based on wall shear stresses, determines the worthiness of a given configuration. The methods are fully automated and demonstrate the capabilities of a design optimization framework that is broadly applicable. Changes to thrombus location and shape alter the velocity contours and wall shear stress profiles significantly. For vena cava filters that trap two thrombi simultaneously, the undesirable flow dynamics past one thrombus can be mitigated by leveraging the flow past the other thrombus. Streamlining the shape of thrombus trapped along the cava wall reduces the disruption to the flow, but increases the area exposed to abnormal wall shear stress. Computer-based design optimization is a useful tool for developing vena cava filters. Characterizing and parameterizing the design requirements and constraints is essential for constructing devices that address clinical complications. In addition, formulating a well-defined objective function that quantifies clinical risks and benefits is needed for designing devices that are clinically viable