Potential recognition of flash flood disasters in China’s southwestern mountainous areas considering source supply conditions

npj natural hazards. · 2026-03-26

This study established a method for the potential recognition of flash flood disasters that is adaptable to different spatial scales considering source supply conditions. Based on digital maps for early potential recognition of flash flood risk, the potential volume of landslide sources in typical high-risk watersheds was estimated through the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS) with slope as the basic unit. The results indicate that: (1) The coupling disaster caused by flash floods and sediment in Aba Prefecture exhibits a certain degree of spatial clustering, with some impact factors demonstrating similar sensitivity patterns towards disaster occurrence. (2) High risks of flash flood disasters are identified in parts of eastern, central-southern, and a small portion of the northwestern watersheds in Aba Prefecture. (3) The Certainty Factor-Adaptive Boosting (CF-AdaBoost) coupling algorithm identifies a coverage of 40.7% for high-susceptibility areas and a coverage of 12.4% for very low-susceptibility areas. (4) Post-processing the results of the slope stability model through the division of slope units estimates that the area of high-risk slopes in the Shouxi River basin during the intense rainfall event on August 20th is 4.99 × 107 m2. The key source supply areas are primarily concentrated in the upper and middle reaches of the basin, with an estimated sediment transport capacity of 1.219 × 107 m³ for each flood event.

Proposed Artificial Intelligence Literacy Curriculum in K–12 Education for Cultivating Competent Users, Smart Learners, and Passionate Thinkers

Springer international handbooks of education · 2026-01-01

EnliveningGS: Active Locomotion of 3DGS

2025-06-10

This paper presents a novel pipeline named EnliveningGS, which enables active locomotion of 3D models represented with 3D Gaussian splatting (3DGS). We are inspired by the fact that real-world lives pose their bodies in a natural and physically meaningful manner by compressing or elongating muscle fibers embedded in the body. EnliveningGS aims to replicate the similar functionality of 3DGS models so that the object within a 3DGS scene acts like a living creature rather than a static shape —they walk, jump, and twist in the scene under provided motion trajectories driven by muscle activations. While the concept is straightforward, many challenging technical difficulties need to be taken care of. Synthesizing realistic locomotion of a 3DGS model embodies an inverse physics problem of very high dimensions. The core challenge is how to efficiently and robustly model frictional contacts between an "enlivened model" and the environment, as it is the composition of contact/collision/friction forces triggered by muscle activation that generates the final movement of the object. We propose a hybrid numerical method mixing LCP and penalty method to tackle this NP-hard problem robustly. Our pipeline also addresses the limitation of existing 3DGS deformation algorithms and inpainting the missing information when models move around.

C ⁵ D: Sequential Continuous Convex Collision Detection Using Cone Casting

ACM Transactions on Graphics · 2025-07-27 · 2 citations

In physics-based simulation of rigid or nearly rigid objects, collisions often become the primary performance bottleneck, particularly when enforcing intersection-free constraints. Previous simulation frameworks rely on primitive-level CCD algorithms. Due to the large number of colliding surface primitives to process, those methods are computationally intensive and heavily dependent on advanced parallel computing resources such as GPUs, which are often inaccessible due to competing tasks or capped threading capacity in applications like policy training for robotics. To address these limitations, we propose a sequential CCD algorithm for convex shapes undergoing constant affine motion. This approach uses the conservative advancement method to iteratively refine a lower-bound estimate of the TOI, exploiting the linearity of affine motion and the efficiency of convex shape distance computation. Our CCD algorithm integrates seamlessly into the ABD framework, achieving a 10-fold speed-up over primitive-level CCD. Its high single-threaded efficiency further enables significant throughput improvements via scene-level parallelism, making it well-suited for resource-constrained environments.

4D Gaussian Videos with Motion Layering

ACM Transactions on Graphics · 2025-07-27 · 2 citations

Online free-view navigation in volumetric videos requires high-quality rendering and real-time streaming in order to provide immersive user experiences. However, existing methods ( e.g. , dynamic NeRF and 3DGS) may not handle dynamic scenes with complex motions, and their models may not be streamable due to storage and bandwidth constraints. In this paper, we propose a novel 4D Gaussian Video (4DGV) approach that enables the creation and streaming of photorealistic, volumetric videos for dynamic scenes over the Internet. The core of our 4DGV is a novel streamable group of Gaussians (GOG) representation based on motion layering. Each GOG consists of static and dynamic points obtained via lifting 2D segmentation into 3D in motion layering, where the deformation of each dynamic point is represented as the temporal offset of its attributes. We also adaptively convert static points back to dynamic points to handle the appearance change, (e.g. , moving shadows and reflections), of static objects through optimization. To support real-time streaming of 4DGVs, we show that by applying quantization on Gaussian attributes and H.265 encoding on deformation offsets, our GOG representation can be significantly compressed (to around 6% of the original model size) without sacrificing the accuracy (PSNR loss less than 0.01dB). Extensive experiments on standard benchmarks demonstrate that our method outperforms state-of-the-art volumetric video approaches, with superior rendering quality and minimum storage overheads.

High-performance CPU Cloth Simulation Using Domain-decomposed Projective Dynamics

ACM Transactions on Graphics · 2025-07-27 · 3 citations

Whenever the concept of high-performance cloth simulation is brought up, GPU acceleration is almost always the first that comes to mind. Leveraging immense parallelization, GPU algorithms have demonstrated significant success recently, whereas CPU methods are somewhat overlooked. Indeed, the need for an efficient CPU simulator is evident and pressing. In many scenarios, high-end GPUs may be unavailable or are already allocated to other tasks, such as rendering and shading. A high-performance CPU alternative can greatly boost the overall system capability and user experience. Inspired by this demand, this paper proposes a CPU algorithm for high-resolution cloth simulation. By partitioning the garment model into multiple (but not massive) sub-meshes or domains, we assign per-domain computations to individual CPU processors. Borrowing the idea of projective dynamics that breaks the computation into global and local steps, our key contribution is a new parallelization paradigm at domains for both global and local steps so that domain-level calculations are sequential and lightweight. The CPU has much fewer processing units than a GPU. Our algorithm mitigates this disadvantage by wisely balancing the scale of the parallelization and convergence. We validate our method in a wide range of simulation problems involving high-resolution garment models. Performance-wise, our method is at least one order faster than existing CPU methods, and it delivers a similar performance compared with the state-of-the-art GPU algorithms in many examples, but without using a GPU.

Multiphysics Simulation Methods in Computer Graphics

Computer Graphics Forum · 2025-04-17 · 7 citations

Abstract Physics simulation is a cornerstone of many computer graphics applications, ranging from video games and virtual reality to visual effects and computational design. The number of techniques for physically‐based modeling and animation has thus skyrocketed over the past few decades, facilitating the simulation of a wide variety of materials and physical phenomena. This report captures the state‐of‐the‐art of multiphysics simulation for computer graphics applications. Although a lot of work has focused on simulating individual phenomena, here we put an emphasis on methods developed by the computer graphics community for simulating various physical phenomena and materials, as well as the interactions between them. These include combinations of discretization schemes, mathematical modeling frameworks, and coupling techniques. For the most commonly used methods we provide an overview of the state‐of‐the‐art and deliver valuable insights into the various approaches. A selection of software frameworks that offer out‐of‐the‐box multiphysics modeling capabilities is also presented. Finally, we touch on emerging trends in physics‐based animation that affect multiphysics simulation, including machine learning‐based methods which have become increasingly popular in recent years.

Fast Physics-Based Modeling of Knots and Ties using Templates

2025-07-23 · 1 citations

LLM-enabled generative cultural product design with symbolic semantic representation

Advanced Engineering Informatics · 2025-11-05 · 1 citations

Real-Time Knit Deformation and Rendering

ACM Transactions on Graphics · 2025-07-27 · 1 citations

The knit structure consists of interlocked yarns, with each yarn comprising multiple plies comprising tens to hundreds of twisted fibers. This intricate geometry and the large number of geometric primitives present substantial challenges for achieving high-fidelity simulation and rendering in real-time applications. In this work, we introduce the first real-time framework that takes an animated stitch mesh as input and enhances it with yarn-level simulation and fiber-level rendering. Our approach relies on a knot-based representation to model interlocked yarn contacts. The knot positions are interpolated from the underlying mesh, and associated yarn control points are optimized using a physically inspired energy formulation, which is solved through a GPU-based Gauss-Newton scheme for real-time performance. The optimized control points are sent to the GPU rasterization pipeline and rendered as yarns with fiber-level details. In real-time rendering, we introduce several decomposition strategies to enable realistic lighting effects on complex knit structures, even under environmental lighting, while maintaining computational and memory efficiency. Our simulation faithfully reproduces yarn-level structures under deformations, e.g., stretching and shearing, capturing interlocked yarn behaviors. The rendering pipeline achieves near-ground-truth visual quality while being 120,000× faster than path tracing reference with fiber-level geometries. The whole system provides real-time performance and has been evaluated through various application scenarios, including knit simulation for small patches and full garments and yarn-level relaxation in the design pipeline.