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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. 

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.

 

Hydrazine‐assisted water electrolysis offers a feasible path for low‐voltage green hydrogen production. Herein, the design and synthesis of ultrathin RhRu_0.5‐alloy wavy nanowires as bifunctional electrocatalysts for both the anodic hydrazine oxidation reaction (HzOR) and the cathodic hydrogen evolution reaction (HER) is reported. It is shown that the RhRu_0.5‐alloy wavy nanowires can achieve complete electrooxidation of hydrazine with a low overpotential and high mass activity, as well as improved performance for the HER. The resulting RhRu_0.5bifunctional electrocatalysts enable, high performance hydrazine‐assisted water electrolysis delivering a current density of 100 mA cm⁻²at an ultralow cell voltage of 54 mV and a high current density of 853 mA cm⁻²at a cell voltage of 0.6 V. The RhRu_0.5 electrocatalysts further demonstrate a stable operation at a high current density of 100 mA cm⁻²for 80 hours of testing period with little irreversible degradation. The overall performance greatly exceeds that of the previously reported hydrazine‐assisted water electrolyzers, offering a pathway for efficiently converting hazardous hydrazine into molecular hydrogen.

 

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.

 

Proton‐exchange‐membrane fuel cells (PEMFCs) are of considerable interest for direct chemical‐to‐electrical energy conversion and may represent an ultimate solution for mobile power supply. However, PEMFCs today are primarily limited by the sluggish kinetics of the cathodic oxygen reduction reaction (ORR), which requires a significant amount of Pt‐based catalyst with a substantial contribution to the overall cost. Hence, promoting the activity and stability of the needed catalyst and minimizing the amount of Pt loaded are central to reducing the cost of PEMFCs for commercial deployment. Considerable efforts have been devoted to improving the catalytic performance of Pt‐based ORR catalysts, including the development of various Pt nanostructures with tunable sizes and chemical compositions, controlled shapes with selectively displayed crystallographic surfaces, tailored surface strains, surface doping, geometry engineering, and interface engineering. Herein, a brief introduction of some fundamentals of fuel cells and ORR catalysts with performance metrics is provided, followed by a detailed description of a series of strategies for pushing the limit of high‐performance Pt‐based catalysts. A brief perspective and new insights on the remaining challenges and future directions of Pt‐based ORR catalysts for fuel cells are also presented.