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  1. Abstract

    Road network design, as an important part of landscape modeling, shows a great significance in automatic driving, video game development, and disaster simulation. To date, this task remains labor‐intensive, tedious and time‐consuming. Many improved techniques have been proposed during the last two decades. Nevertheless, most of the state‐of‐the‐art methods still encounter problems of intuitiveness, usefulness and/or interactivity. As a rapid deviation from the conventional road design, this paper advocates an improved road modeling framework for automatic and interactive road production driven by geographical maps (including elevation, water, vegetation maps). Our method integrates the capability of flexible image generation models with powerful transformer architecture to afford a vectorized road network. We firstly construct a dataset that includes road graphs, density map and their corresponding geographical maps. Secondly, we develop a density map generation network based on image translation model with an attention mechanism to predict a road density map. The usage of density map facilitates faster convergence and better performance, which also serves as the input for road graph generation. Thirdly, we employ the transformer architecture to evolve density maps to road graphs. Our comprehensive experimental results have verified the efficiency, robustness and applicability of our newly‐proposed framework for road design.

     
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  2. Abstract

    As a usual component in virtual scenes, water surface plays an important role in various graphical applications, including special effects, video games, and virtual reality. Although recent years have witnessed significant progress based on Navier–Stokes equations and simplified water models, large‐scale water surface waves with high‐frequency visual details remain computationally expensive for interactive applications. This article proposes a novel frequency‐aware neural network to synthesize consistent and detailed water surface waves from low‐resolution input. At its core, our approach leverage the wavelet transformation theory over space, frequency and direction, and incremental supervision to decompose the 4D amplitude function into multiple smaller subproblems. Specifically, we first customize four subnetworks and corresponding loss functions for super‐resolution of spatial resolution, temporal evolution, wave direction subdivision, and wave number, respectively. Then, to enforce the upsampling along each dimension orthogonal to each other, we introduce a cooperative training scheme to fine‐tune and integrate the proposed subnetworks with carefully designed training dataset. Our method can visually enhance high‐resolution spatial details, temporal coherence, interactions with complex boundaries, and various wave patterns with flexible control along multiple dimensions. Through extensive experiments, our method arrives at 13 speedup for 32 upsampling of various simulation scenarios. We also validate the effectiveness and robustness of our method to produce realistic water surface waves toward artistic innovation.

     
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  3. null (Ed.)
    To date, large-scale fluid simulation with more details employing the Smooth Particle Hydrodynamics (SPH) method or its variants is ubiquitous in computer graphics and digital entertainment applications. Higher accuracy and faster speed are two key criteria evaluating possible improvement of the underlying algorithms within any available framework. Such requirements give rise to high-fidelity simulation with more particles and higher particle density that will unavoidably increase computational cost significantly. In this paper, we develop a new general GPGPU acceleration framework for SPH-centric simulations founded upon a novel neighbor traversal algorithm. Our novel parallel framework integrates several advanced characteristics of GPGPU architecture (e.g., shared memory and register memory). Additionally, we have designed a reasonable task assignment strategy, which makes sure that all the threads from the same CTA belong to the same cell of the grid. With this organization, big bunches of continuous neighboring data can be loaded to the shared memory of a CTA and used by all its threads. Our method has thus low global-memory bandwidth consumption. We have integrated our method into both WCSPH and PCISPH, that are two improved variants in recent years, and demonstrated its performance with several scenarios involving multiple-fluid interaction, dam break, and elastic solid. Through comprehensive tests validated in practice, our work can exhibit up to 2.18x speedup when compared with other state-of-the-art parallel frameworks. 
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  4. Abstract

    In this paper, we articulate a novel plastic phase‐field (PPF) method that can tightly couple the phase‐field with plastic treatment to efficiently simulate ductile fracture with GPU optimization. At the theoretical level of physically‐based modeling and simulation, our PPF approach assumes the fracture sensitivity of the material increases with the plastic strain accumulation. As a result, we first develop a hardening‐related fracture toughness function towards phase‐field evolution. Second, we follow the associative flow rule and adopt a novel degraded von Mises yield criterion. In this way, we establish the tight coupling of the phase‐field and plastic treatment, with which our PPF method can present distinct elastoplasticity, necking, and fracture characteristics during ductile fracture simulation. At the numerical level towards GPU optimization, we further devise an advanced parallel framework, which takes the full advantages of hierarchical architecture. Our strategy dramatically enhances the computational efficiency of preprocessing and phase‐field evolution for our PPF with the material point method (MPM). Based on our extensive experiments on a variety of benchmarks, our novel method's performance gain can reach 1.56× speedup of the primary GPU MPM. Finally, our comprehensive simulation results have confirmed that this new PPF method can efficiently and realistically simulate complex ductile fracture phenomena in 3D interactive graphics and animation.

     
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  5. Abstract

    In this article, we propose a novel hybrid framework by combining smoothed particle hydrodynamics and adaptive narrow band fluid implicit particle method (NB‐FLIP) to faithfully model the multiphysical processes involving heat transfer and phase transition, and to precisely simulate the dynamics of condensed droplets moving along intricate objects. We first formulate a governing physical model built upon an improved phase transition model and an augmented on‐surface drop analysis method to achieve realistic condensation effects over intricate hydrophilic/hydrophobic interface. To achieve both high‐fidelity interactions and high‐resolution visual effects, we further develop an adaptive NB‐FLIP solver with octree‐dictated background grid in order to further enhance the performance of our framework. Experimental results have shown that our approach can be used to efficiently and realistically simulate the small‐scale interaction details between condensed drops and complex objects with arbitrary geometry.

     
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  6. Abstract

    Generating realistic spray details in liquid simulations remains computationally expensive. This paper proposes a data‐driven method to simulate high‐resolution sprays on low‐resolution grids by retrieving details with the most compatible details from a precomputed repository efficiently. We first employ a random forest‐based distance (RFD) to measure the similarity of liquid regions. In consideration of spatiotemporal relationships between one liquid region and its neighbors, we define a multinary label for RFD instead of the original binary one. Our improved RFD enables us to retrieve details that fit ground truth the best. To ensure temporal continuity of our result and to generate new details from existing ones, we formulate a series of forests with a training set from different time steps. Then, we synthesize results of each forest according to their distances. Finally, we put the synthesis result in correct positions to generate desired sprays motion. In our method, a state‐of‐the‐art cascade forest is employed for a higher accuracy. Several experiments with various grid resolutions validate our method both in visual effect and computational cost.

     
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