Physics-based fluid simulation has played an increasingly important role in the computer graphics community. Recent methods in this area have greatly improved the generation of complex visual effects and its computational efficiency. Novel techniques have emerged to deal with complex boundaries, multiphase fluids, gas–liquid interfaces, and fine details. The parallel use of machine learning, image processing, and fluid control technologies has brought many interesting and novel research perspectives. In this survey, we provide an introduction to theoretical concepts underpinning physics-based fluid simulation and their practical implementation, with the aim for it to serve as a guide for both newcomers and seasoned researchers to explore the field of physics-based fluid simulation, with a focus on developments in the last decade. Driven by the distribution of recent publications in the field, we structure our survey to cover physical background; discretization approaches; computational methods that address scalability; fluid interactions with other materials and interfaces; and methods for expressive aspects of surface detail and control. From a practical perspective, we give an overview of existing implementations available for the above methods.

As an important autumn feature, scenes with large numbers of falling leaves are common in movies and games. However, it is a challenge for computer graphics to simulate such scenes in an authentic and efficient manner. This paper proposes a GPU based approach for simulating the falling motion of many leaves in real time. Firstly, we use a motion-synthesis based method to analyze the falling motion of the leaves, which enables us to describe complex falling trajectories using low-dimensional features. Secondly, we transmit a primitive-motion trajectory dataset together with the low-dimensional features of the falling leaves to video memory, allowing us to execute the appropriate calculations on the GPU.