3D computational steering with parametrized geometric objects

Computational Steering is the ultimate goal of interactive simulation: researchers change parameters of their simulation and immediately receive feedback on the effect. We present a general and flexible graphics tool that is part of an environment for Computational Steering developed at CWI. It enables the researcher to interactively develop his own interface with the simulation. This interface is constructed with 3D Parametrized Geometric Objects. The properties of the objects are parametrized to output data and input parameters of the simulation. The objects visualize the output of the simulation while the researcher can steer the simulation by direct manipulation of the objects. Several applications of 3D Computational Steering are presented

Interactive exploration and modeling of large data sets: a case study with Venus light scattering data

We present a system where visualization and the control of the simulation are integrated to facilitate interactive exploration and modeling of large data sets. The system was developed to estimate properties of the atmosphere of Venus from comparison between measured and simulated data. Reuse of results, distributed computing, and multiple views on the data were the major ingredients to create an effective environment

Porting a visualization package from IRIX to NT : what will I get, what will I pay?

We discuss our experiences in porting a moderately large scientific visualization environment from IRIX to NT~4.0. Two porting strategies have been taken: a port via a POSIX emulation layer and a native NT port. POSIX compliant code can be ported to NT with relatively little effort if the code adheres to general accepted programming principles, such as modularity and encapsulation. The performance of a modern 3D Wintel machine is quite satisfactory for a variety of scientific desktop tasks. We have compared the performance of a 2 CPU Dell OptiPlex with FireGL 4000 graphics option to various SGI desktop workstations

Parametrizable cameras for 3D computational steering

We present a method for the definition of multiple views in 3D interfaces for computational steering. The method uses the concept of a point-based parametrizable camera object. This concept enables a user to create and configure multiple views on his custom 3D interface in an intuitive graphical manner. Each view can be coupled to objects present in the interface, parametrized to (simulation) data, or adjusted through direct manipulation or user defined camera controls. Although our focus is on 3D interfaces for computational steering, we think that the concept is valuable for many other 3D graphics applications as well

Computational steering in the CAVE

Scientists can gain much more insight from their simulations if they are enabled to change simulation parameters on the fly while observing the results immediately. A crucial aspect of such {em computational steering/ is an intuitive user interface. We have developed an environment that enables researchers to construct such interfaces efficiently and effectively for graphical workstations. In this paper we report on our next step towards more intuitive user-interfaces: We have modified our system for use in the CAVE. The CAVE is a projection-based virtual environment. Virtual environments are designed to provide the effect of immersion in an interactive three-dimensional computer-generated environment. We show that the use of virtual environments for computational steering interfaces can improve interaction with the simulation and immersion in the computational process. We present our system, the methods we have developed for improved 3D interaction, and describe three applications

Bringing computational steering to the user

Computational steering is a technique that combines simulation and visualization. The user is continuously provided with visual feedback about the state of the simulation, and can change parameters on the fly. Designers can vary parameters to optimize their product, users can detect errors in the input early, researchers can do qualitative sensitivity analyses easily. The implementation of computational steering is very tedious. It requires knowledge of the simulation, visualization, user interfacing, and data communication. In this paper we discuss an environment that enables users to implement and use computational steering effectively without much support from user interface experts. We show how the environment is applied to various applications

A model for strategy in constraint solving

The use of constraints for the definition of graphical user interfaces has been recognized as a great concept. However, often many valuations of the variables will satisfy the constraints, and which particular valuation matches best with the expectation of the user cannot be decided without further information. Three typical examples of user interfaces are presented where this occurs, and from these, requirements on a more cooperative constraint solver are derived. A new method for the definition and implementation of the strategy to decide which variables to adapt is presented. The model is based on two notions: hierarchy and grouping. Variables are divided into groups, and for each group three parameters are set. These are used to determine the level of variables, dependent on which group they belong, and which variables are modified. These levels are used in turn to select the variables to be adapted. An implementation of this method is described, as part of the Computational Steering Environment (CSE) developed at CWI. The resulting constraint solver can handle simultaneous sets of non-linear, multi-way constraints; and can handle a high-level definition of the strategy to be followed. Finally, the results are discussed, and suggestions for further work are done

Bringing computational steering to the user

Computational steering is a technique that combines simulation and visualization. The user is continuously provided with visual feedback about the state of the simulation, and can change parameters on the fly. Designers can vary parameters to optimize their product, users can detect errors in the input early, researchers can do qualitative sensitivity analyses easily. The implementation of computational steering is very tedious. It requires knowledge of the simulation, visualization, user interfacing, and data communication. In this paper we discuss an environment that enables users to implement and use computational steering effectively without much support from user interface experts. We show how the environment is applied to various applications

A survey of computational steering environments

Computational steering is a powerful concept that allows scientists to interactively control a computational process during its execution. In this paper, a survey of computational steering environments for the on-line steering of ongoing scientific and engineering simulations is presented. These environments can be used to create steerable applications for model exploration, algorithm experimentation, or performance optimization. For each environment the scope is identified, the architecture is summarized, and the concepts of the user interface is described. The environments are compared and conclusions and future research issues are given

3D computational steering with parametrized geometric objects

Computational Steering is the ultimate goal of interactive simulation: researchers change parameters of their simulation and immediately receive feedback on the effect. We present a general and flexible graphics tool that is part of an environment for Computational Steering developed at CWI. It enables the researcher to interactively develop his own interface with the simulation. This interface is constructed with 3D Parametrized Geometric Objects. The properties of the objects are parametrized to output data and input parameters of the simulation. The objects visualize the output of the simulation while the researcher can steer the simulation by direct manipulation of the objects. Several applications of 3D Computational Steering are presented