ANSYS, INC.

Computational fluid dynamics simulations of objects with many similar but distinct flow boundary regions on a larger surface can use an approach that creates geometries and meshes for the larger surface (e.g., a first mesh) independently of geometries and meshes for the distinct flow boundary regions (second mesh). The second mesh can be imprinted onto the first mesh prior to a CFD simulation, and if a revision to the design of the regions is desired, a revised mesh for the regions (based on a revised geometry for the regions) can be imprinted on the first mesh without having to redo the first mesh. Thus, revisions of the design can avoid recreating the first mesh.

Systems and methods for automated resource allocation during a computational simulation are described herein. An example method includes analyzing a set of simulation inputs to determine a first set of computing resources for performing a simulation, and starting the simulation with the first set of computing resources. The method also includes dynamically analyzing at least one attribute of the simulation to determine a second set of computing resources for performing the simulation, and performing the simulation with the second set of computing resources. The second set of computing resources is different than the first set of computing resources.

Systems and methods calculate Voronoi cells in a space subdivided into octants represented by an octree. Calculation of a Voronoi cell for a given seed point starts with the neighboring octants by determining the bisectors between the neighboring seed points and given seed point as well as the vertices where the bisectors meet. Additional octants are identified that (i) are adjacent to a neighboring octant and (ii) include any portion of the space that is no farther from a vertex than [(the distance between the vertex and the given seed point)+(additional distance ε)], such additional octants are added to the set of neighboring octants, and the sets of bisectors and vertices are updated using robust geometric predicates. This repeats until no additional octants are identified, and the bisectors and vertices are (optionally compressed, then) output as the Voronoi cell. Multiple cells can be determined in parallel, then combined into a Voronoi mesh.

Systems and methods are provided for A computer-implemented method for simulating behavior of an electrical circuit across a range of frequencies from 0 to f max . A base function is determined that outputs magnitudes across the range of frequencies. A correction function is determined that outputs magnitudes across the range of frequencies. The base function is combined with the correction function to generate a circuit behavior model that provides magnitudes across the range of frequencies. Behavior of the electrical circuit is simulated using the circuit behavior model.

Systems and methods for automatically training a machine learning model are described herein. An example method includes performing a set of computational simulations; and assembling a data set associated with the set of computational simulations. The data set includes data associated with at least one simulation result for at least one computational simulation in the set of computational simulations. The method also includes training a machine learning model with the data set. At least one feature and at least one target for the machine learning model are part of the data set.

This disclosure provides modelling techniques for accurately and reliably analyzing printed parts. More specifically, a model with a powder representation may be used for the thermal analysis, the powder representation may then be removed from the model for performing the structural analysis. Although the powder representation is removed from the model for the structural analysis, the structural analysis still factors in the thermal effects of the powder on the part determined by the thermal analysis. The computer-based techniques of the current disclosure improve the functioning of a computer system as compared to conventional approaches by facilitating analyses (e.g., thermal, mechanical, design, and heat treatment analyses) that are more accurate, more efficient (e.g., faster, smaller memory requirements, etcetera), and/or have a reduced processing burden versus conventional approaches.

Computer-implemented systems and methods are described herein for determining additive manufacturing parameters in a simulation. Input data regarding a product to be generated via additive manufacturing and a beam diameter are received. Based on the input data, a characteristic dimension is determined. The beam diameter is normalized based on the characteristic dimension. Additive manufacturing parameters, such as penetration depth and absorptivity, are determined based on the normalized beam diameter and experimentally-determined trends. The manufacturing of the product is then simulated according to the additive manufacturing parameters.

Provided is an improved method, system, and computer program product to implement simulation for photonic devices. A composite, multi-domain simulation model is disclosed, with connected domain-specific representations that allow the use of the most relevant simulator technology for a given domain. The model has external connection points either expressed as actual ports or virtual ones, embodied by simulator API calls in the model.

Methods and systems for improved simulation of thermal characterization and thermal modeling of devices, such as smart phones, are described. In one embodiment, a method can characterize center, edge, and corner thermal decay behavior at different locations on a simulated IC. For each location, near and far field thermal effects are captured at the same time. A simulation system can generate a steady state thermal decay curve for each selected location that shows how the temperature changes with distance to a heat source. The system can then use a set of location dependent thermal decay curves to compute, based on an inputted power profile for the IC, a steady state thermal profile of the IC.

In one embodiment, use of virtual thermal cameras in simulations systems can rapidly increase the deployment of vehicles with autonomous driving systems that include thermal cameras as a part of the sensor systems that detect people, other cars, etc. This use can be achieved by calibrating virtual thermal cameras using a virtual object or scenes with predetermined temperatures of objects (humans) in the scenes. The virtually calibrated thermal camera can then be used in virtual simulations of driving scenarios to generate learning data, such as virtual thermal images, to test autonomous driving systems and autonomous driving algorithms. The calibration can use a temperature conversion process, and the generation of the learning data can also use this temperature conversion process that includes the addition of noise, represented by temperature values.