We introduce a new wire-mesh sensor based on capacitance (permittivity) measurements. The sensor can be used to measure transient phase fraction distributions in a flow cross-section, such as in a pipe or other vessel, and is able to discriminate fluids having different relative permittivity (dielectric constant) values in a multiphase flow. We designed and manufactured a prototype sensor which comprises two planes of 16 wires each. The wires are evenly distributed across the measuring cross-section, and measurement is performed at the wire crossings. Time resolution of the prototype sensor is 625 frames per second. Sensor and measuring electronics were evaluated showing good stability and accuracy in the capacitance measurement. The wire-mesh sensor was tested in a silicone oil/water two-phase bubbly flow.

Keyframe animation is a common technique to generate animations of deformable characters and other soft bodies. With spline interpolation, however, it can be difficult to achieve secondary motion effects such as plausible dynamics when there are thousands of degrees of freedom to animate. Physical methods can provide more realism with less user effort, but it is challenging to apply them to quickly create specific animations that closely follow prescribed animator goals. We present a fast space-time optimization method to author physically based deformable object simulations that conform to animator-specified keyframes. We demonstrate our method with FEM deformable objects and mass-spring systems.Our method minimizes an objective function that penalizes the sum of keyframe deviations plus the deviation of the trajectory from physics. With existing methods, such minimizations operate in high dimensions, are slow, memory consuming, and prone to local minima. We demonstrate that significant computational speedups and robustness improvements can be achieved if the optimization problem is properly solved in a low-dimensional space. Selecting a low-dimensional space so that the intent of the animator is accommodated, and that at the same time space-time optimization is convergent and fast, is difficult. We present a method that generates a quality low-dimensional space using the given keyframes. It is then possible to find quality solutions to difficult space-time optimization problems robustly and in a manner of minutes.

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Animating natural human motion in dynamic environments is difficult because of complex geometric and physical interactions. Simulation provides an automatic solution to parts of this problem, but it needs control systems to produce lifelike motions. This paper describes the systematic computation of controllers that can reproduce a range of locomotion styles in interactive simulations. Given a reference motion that describes the desired style, a derived control system can reproduce that style in simulation and in new environments. Because it produces high-quality motions that are both geometrically and physically consistent with simulated surroundings, interactive animation systems could begin to use this approach along with more established kinematic methods.

Controllers are necessary for physically-based synthesis of character animation. However, creating controllers requires either manual tuning or expensive computer optimization. We introduce linear Bellman combination as a method for reusing existing controllers. Given a set of controllers for related tasks, this combination creates a controller that performs a new task. It naturally weights the contribution of each component controller by its relevance to the current state and goal of the system. We demonstrate that linear Bellman combination outperforms naive combination often succeeding where naive combination fails. Furthermore, this combination is provably optimal for a new task if the component controllers are also optimal for related tasks. We demonstrate the applicability of linear Bellman combination to interactive character control of stepping motions and acrobatic maneuvers.

Animating natural human motion in dynamic environments is difficult because of complex geometric and physical interactions. Simulation provides an automatic solution to parts of this problem, but it needs control systems to produce lifelike motions. This paper describes the systematic computation of controllers that can reproduce a range of locomotion styles in interactive simulations. Given a reference motion that describes the desired style, a derived control system can reproduce that style in simulation and in new environments. Because it produces high-quality motions that are both geometrically and physically consistent with simulated surroundings, interactive animation systems could begin to use this approach along with more established kinematic methods.

Three-phase gas–liquid–liquid flows are very common in petroleum extraction, production, and transport. In this work a dual-modality measuring technique is introduced which may be well applied for three-phase flow visualization. The measuring principle is based on simultaneous excitation with two distinct frequencies to interrogate each crossing point of a mesh sensor, which in turn are linked to conductive and capacitive parts of fluid impedance. The developed system can operate eight transmitter and eight receiver electrodes at a frame repetition frequency up to 781 Hz. The system has been evaluated by measuring reference components. The overall measurement uncertainty was 8.4%, which considering the fast repetition frequency of measurements is suitable for flow investigation. Furthermore, a model-based method to fuse the data from the dual-modality wire-mesh sensor and to obtain individual phase fraction of gas–oil–water flow is introduced. Here a parametrized model is fitted to the measured conductivity and permittivity distributions enabling one to obtain phase fraction from measured data. The method has been applied and tested to the acquired data from a mesh sensor in static and dynamic three-phase mixtures of gas, oil, and water. Fused images and quantitative values show good agreement with reference values. The newly developed dual-modality wire-mesh sensor has the potential to investigate three-phase flows to a good degree of detail, being a valuable tool to investigate such flows.