The polygon-mesh approach to 3D modeling was a huge advance, but today its limitations are clear. Longer render times for increasingly complex images effectively cap image complexity, or else stretch ...budgets and schedules to the breaking point. Comprised of contributions from leaders in the development and application of this technology, Point-Based Graphics examines it from all angles, beginning with the way in which the latest photographic and scanning devices have enabled modeling based on true geometry, rather than appearance. From there, it's on to the methods themselves. Even though point-based graphics is in its infancy, practitioners have already established many effective, economical techniques for achieving all the major effects associated with traditional 3D Modeling and rendering. You'll learn to apply these techniques, and you'll also learn how to create your own. The final chapter demonstrates how to do this using Pointshop3D, an open-source tool for developing new point-based algorithms. * The first book on a major development in computer graphics by the pioneers in the field * Shows how 3D images can be manipulated as easily as 2D images are with Photoshop
The current work presents a process that separates hydrogen from mixtures with natural gas transported in the natural gas grid. The aim is to achieve hydrogen at fuel cell quality (99.97% (v/v) ...according to ISO 14687-2:2012). Due to gas grid regulations in Austria the hydrogen content is limited to a maximum of 4% (v/v).
In a hybrid approach based on membrane separation and pressure swing adsorption (PSA) the supplied high pressure hydrogen – natural gas mixture (up to 120 bar) is pre-enriched by membrane technology and further upgraded to the required quality by PSA. The majority of the feed gas is kept at grid pressure, which ensures a high energetic efficiency. The remaining components, separated by PSA, are re-compressed and returned to the grid.
Beside the technological feasibility, the influence of various process parameters (e.g. stage-cut, permeate conditions, PSA hydrogen recovery) is analysed. Based on the results, the required amount of energy of 0.8–1.5 kWh/m3 (fuel-cell quality hydrogen at 25.81 bar(a)) is calculated for the so called HylyPure® process.
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•Process to extract fuel cell quality hydrogen transported with natural gas.•Hybrid process based on membrane technology and pressure swing adsorption.•High pressure gas permeation using a bore side feed hollow fibre membrane module.
We present a robust, unbiased technique for intelligent light‐path construction in path‐tracing algorithms. Inspired by existing path‐guiding algorithms, our method learns an approximate ...representation of the scene's spatio‐directional radiance field in an unbiased and iterative manner. To that end, we propose an adaptive spatio‐directional hybrid data structure, referred to as SD‐tree, for storing and sampling incident radiance. The SD‐tree consists of an upper part—a binary tree that partitions the 3D spatial domain of the light field—and a lower part—a quadtree that partitions the 2D directional domain. We further present a principled way to automatically budget training and rendering computations to minimize the variance of the final image. Our method does not require tuning hyperparameters, although we allow limiting the memory footprint of the SD‐tree. The aforementioned properties, its ease of implementation, and its stable performance make our method compatible with production environments. We demonstrate the merits of our method on scenes with difficult visibility, detailed geometry, and complex specular‐glossy light transport, achieving better performance than previous state‐of‐the‐art algorithms.
This paper presents a novel generative model to synthesize fluid simulations from a set of reduced parameters. A convolutional neural network is trained on a collection of discrete, parameterizable ...fluid simulation velocity fields. Due to the capability of deep learning architectures to learn representative features of the data, our generative model is able to accurately approximate the training data set, while providing plausible interpolated in‐betweens. The proposed generative model is optimized for fluids by a novel loss function that guarantees divergence‐free velocity fields at all times. In addition, we demonstrate that we can handle complex parameterizations in reduced spaces, and advance simulations in time by integrating in the latent space with a second network. Our method models a wide variety of fluid behaviors, thus enabling applications such as fast construction of simulations, interpolation of fluids with different parameters, time re‐sampling, latent space simulations, and compression of fluid simulation data. Reconstructed velocity fields are generated up to 700× faster than re‐simulating the data with the underlying CPU solver, while achieving compression rates of up to 1300×.
Following previous work on an inherently mass‐conserving semi‐implicit (SI) semi‐Lagrangian (SL) discretization of the two‐dimensional (2D) shallow‐water equations and 2D vertical slice equations, ...that approach is here extended to the 3D deep‐atmosphere, non‐hydrostatic global equations. As with the reduced‐dimension versions of this model, an advantage of the approach is that it preserves the same basic structure as a standard, non‐mass‐conserving, SISL version of the model. Additionally, the model is simply switchable to hydrostatic and/or shallow‐atmosphere forms. It is also designed to allow simple switching between various geometries (Cartesian, spherical, spheroidal). The resulting mass‐conserving model is applied to a standard set of test problems for such models in spherical geometry and compared with results from the standard SISL version of the model.
We present a novel approach to video segmentation using multiple object proposals. The problem is formulated as a minimization of a novel energy function defined over a fully connected graph of ...object proposals. Our model combines appearance with long-range point tracks, which is key to ensure robustness with respect to fast motion and occlusions over longer video sequences. As opposed to previous approaches based on object proposals, we do not seek the best per-frame object hypotheses to perform the segmentation. Instead, we combine multiple, potentially imperfect proposals to improve overall segmentation accuracy and ensure robustness to outliers. Overall, the basic algorithm consists of three steps. First, we generate a very large number of object proposals for each video frame using existing techniques. Next, we perform an SVM-based pruning step to retain only high quality proposals with sufficiently discriminative power. Finally, we determine the fore-and background classification by solving for the maximum a posteriori of a fully connected conditional random field, defined using our novel energy function. Experimental results on a well established dataset demonstrate that our method compares favorably to several recent state-of-the-art approaches.
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