A method for generating visual representations of interactions between two different materials is provided. The method can be performed using a computing device operated by a computer user or artist. The method includes modeling a primary material as a plurality of first particles and modeling a layer portion of a secondary material as a fluid volume. The secondary material can include a layer portion positioned between the plurality of first particles and an outer portion. At least one boundary condition might be assigned to a boundary positioned between the layer portion and the outer portion, the at least one boundary condition includes at least one pressure value. Values of motion parameters might be determined by applying the at least one boundary condition at the boundary and generating one or more visual representations of the primary material interacting with the secondary material based on the values of the motion parameters.

Approaches in accordance with various embodiments provide for fluid simulation with substantially reduced time and memory requirements with respect to conventional approaches. In particular, various embodiments can perform time and energy efficient, large scale fluid simulation on processing hardware using a method that does not solve for the Navier-Stokes equations to enforce incompressibility. Instead, various embodiments generate a density tensor and rigid body map tensor for a large number of particles contained in a sub-domain. Collectively, the density tensor and rigid body map may represent input channels of a network with three spatial-dimensions. The network may apply a series of operations to the input channels to predict an updated position and updated velocity for each particle at the end of a frame. Such approaches can handle tens of millions of particles within a virtually unbounded simulation domain, as compared to classical approaches that solve for the Navier-Stokes equations.

A computer-implemented method for inverse simulation of a plurality of fibers. The method comprises: providing a computational model for describing mechanical behavior of fibers; obtaining target geometry information describing a target configuration or dynamical behavior of the plurality of fibers; and inverse simulating the behavior of the plurality of fibers, using the computational model and the target geometry information, to calculate a target set of fiber mechanical parameters for the plurality of fibers. Fibers with the calculated target set of fiber mechanical parameters exhibit the target configuration or dynamical behavior. In some embodiments, the inverse simulation comprises using analysis-by-synthesis to help derive the target set of fiber mechanical parameters. In some embodiments, the inverse simulation uses a neural network to infer information about fiber mechanical parameters from the target geometry information. The invention also provides a method of training the neural network.

An apparatus for assessing a patient's vasculature and a corresponding method are provided, in which the bifurcations in a vessel of interest are identified on the basis of a local change in at least one geometric parameter value of the vessel of interest and the fluid dynamics inside the vessel of interest are adjusted to take account for said bifurcations.

Provided are a virtual scene-based rendering method and apparatus, an electronic device, a computer-readable storage medium, and a computer program product. The virtual scene-based rendering method includes: resolving, by a graphics processing unit (GPU), vertex fluctuation data corresponding to each vertex to be rendered in a model to be rendered to obtain a vertex fluctuation data set corresponding to the model to be rendered; dividing, by a central processing unit (CPU), the model to be rendered into a plurality of grids to be rendered, and resolving grid fluctuation data corresponding to each of the grids to be rendered to obtain a grid fluctuation data set corresponding to the plurality of grids to be rendered; rendering, by the GPU, a liquid surface to be rendered in a virtual scene-based on the vertex fluctuation data set; and rendering, by the CPU, a virtual object for interacting with the liquid surface to be rendered based on the grid fluctuation data set.

A three-dimensional graphical user interface (3D GUI) configured to be used by a computer, a display system, an electronic system, or an electro-mechanical system. The 3D GUI provides an enhanced user-engaging experience while enabling a user to manipulate the motion of an object of arbitrary size and a multiplicity of independent degrees of freedom, using sufficient degrees of freedom to represent the motion. The 3D GUI is configured to process the kinematics of objects interacting with vector fields by using the analytics of Stokes' law. The 3D GUI is also configured to process distributed neural networks by methods including combining the actions of individual nodes and storing the result as a T matrix product in a central cluster node.

Surface features might represent features of a virtual fluid and a method might include obtaining a digital representation of the virtual fluid defined at least in part by an implicit surface, obtaining a digital representation of a collection of points defined relative to the implicit surface whereat the surface features are to be determined. A point of the collection of points might have associated therewith a plurality of attribute values specifying a property of the surface features. For an input point, a corresponding implicit surface point might be determined, along with, for the corresponding implicit surface point, a subset of the points within a search region. Interpolated attribute values might be obtained from attribute values associated with points of the subset, and a surface displacement value computed from interpolated attribute values. A dataset corresponding to the surface features might be generated.

Computer-implemented methods and systems are provided for quantitative hemodynamic flow analysis, which involves retrieving patient specific image data. A 3D reconstruction of a vessel of interest can be created from the patient specific image data. Geometric information can be extracted from the 3D reconstruction. A lesion position can be determined. Patient specific data can be obtained. Hemodynamic results can be calculated based on the geometric information, the lesion position and the patient specific data.

A method for generating one or more visual representations of a porous media submerged in a fluid is provided. The method can be performed using a computing device operated by a computer user or artist. The method includes defining a field comprising fluid parameter values for the fluid, the fluid parameter values comprising fluid velocity values and pore pressures. The method includes generating a plurality of particles that model a plurality of objects of the porous media, the plurality of objects being independently movable with respect to one another, determining values of motion parameters based at least in part on the field when the plurality of particles are submerged in the fluid, buoyancy and drag forces being used to determine relative motion of the plurality of particles and the fluid, and generating the one or more visual representations of the plurality of objects submerged in the fluid based on the values of the motion parameters.

Provided are a dynamic fluid display method and apparatus, an electronic device, and a readable medium. The method includes: detecting a target object on a user display interface; obtaining attribute information of the target object; determining, on the user display interface based on the attribute information of the target object, a change of a parameter of a fluid at each target texture pixel associated with the target object; and displaying a dynamic fluid on the user display interface based on the change of the parameter of the fluid.