A plurality of scanned prints of a product part and a scan-path are received. A shape of a minimum printable feature of the product part is determined by analyzing the respective prints in a scan-path representation. A manufacturing error of the minimum printable feature is determined based on the analysis. A manufacturing error of a shape of the part is determined based on the determined manufacturing error of the minimum printable feature. An estimated manufactured shape of the part is produced based on the determined manufacturing error of the part.

System analysis by receiving a model of a complex system design. The model includes at least one layer. The analysis includes performing a plurality of simulations of the performance of the layer. The number of simulations is determined according to a number of system components associated with the layer. The analysis further includes determining a worst-case result for a set of simulations from the plurality of simulations and assigning the worst-case result to an overall system simulation.

The current invention concerns a computer-implemented method, a computer system, and a computer program product for the semantic classification of an entity in a building information model (BIM). The BIM comprises multiple target entities. Update data is obtained. For each target entity, geometric information about the target entity is obtained from the BIM. For each target entity, an initial probability distribution of semantic classification is determined based on the obtained geometric information about the target entity. Relative geometric information about the target entities is obtained from the BIM. For each target entity, an updated probability distribution of semantic classification is determined based on the obtained relative geometric information, the initial probability distributions of all target entities, and the update data. For each target entity, a semantic classification is selected based on the updated probability distribution of the target entity.

A computer-implemented method for material extrusion detection in a portion of a mechanical part having a distribution of material. The method includes obtaining a CAD 3D model of the mechanical part including a skin portion representing an outer surface of the portion of the mechanical part and an extrusion axis. The method further includes computing a ratio of an area of an orthogonal projection of the skin portion over an area of the skin portion. The method further includes determining whether or not the distribution of material is arranged as an extrusion based on the ratio and a ratio threshold. The outer surface is determined to be an extrusion surface when the ratio is lower than the ratio threshold. This forms an improved solution for processing a CAD 3D model of a mechanical part.

A differentiable simulator for simulating the cutting of soft materials by a cutting instrument is provided. In accordance with one aspect of the disclosure, a method for simulating a cutting operation includes: receiving a mesh for an object, modifying the mesh to add virtual nodes associated with a predefined cutting plane, optimizing a set of parameters associated with a simulator based on ground-truth data, and running a simulation via the simulator to generate outputs that include trajectories associated with a cutting instrument. Optimizing the set of parameters can include performing inference based on a set of ground-truth trajectories captured using sensors to measure real-world cutting operations. The inference techniques can employ stochastic gradient descent, stochastic gradient Langevin dynamics, or a Bayesian approach. In an embodiment, the simulator can be utilized to generate control signals for a robot based on the simulated trajectories.

A design engine implements a probabilistic approach to generating designs that exposes automatically-generated design knowledge to the user during operation. The design engine interactively generates successive populations of designs based on a problem definition associated with a design problem and/or a previously-generated population of designs. During the above design process, the design engine generates a design knowledge graphical user interface (GUI) that graphically exposes various types of design knowledge to the user. In particular, the design engine generates a design variable dependency GUI that visualizes various dependencies between designs variables. The design engine also generates a design evolution GUI that animates the evolution of designs across the successive design populations. Additionally, the design engine generates a design exploration GUI that facilitates the user exploring various statistical properties of automatically-generated designs.

A circuit simulation method includes the following operations: performing Monte Carlo simulations in parallel according to a first netlist file and process model data, in order to generate a performance simulation result, in which the first netlist file is configured to indicate a basic circuit in a circuitry; selecting component parameters lower than a predetermined yield rate according to the performance simulation result; and determining whether an estimated yield rate of the circuitry meets the predetermined yield rate according to the component parameters.

A method and system including identifying, via at least one processor, a user role; configuring, via the at least one processor, an interface for the user role, wherein configuring the interface includes determining an interface view for the user role; and displaying, via the at least one processor, the interface with the interface view.

Provided is a particle behavior simulation method and a particle behavior simulation system for representing behavior of each particle in a large-scale particle system quickly and accurately. The particle behavior simulation system is configured to execute a coarse-graining processing of reconstituting a plurality of particles that mix with each other and constitute a predetermined powder as a particle system into a plurality of particle groups each including a plurality of the particles, an acting force calculation processing of calculating an acting force acting on each of the particle groups, and a mixing state calculation processing of calculating a parameter representing a mixing state of constituent particles of each of the particle groups after a predetermined time based on the calculated acting force.

Systems and methods are disclosed for generating subsurface feature prediction probability distributions from a subsurface feature as a function of position in a subsurface volume of interest. For example, a computer-implemented method may include: obtaining subsurface data and well data, generating subsurface feature values, generating subsurface feature realizations, generating subsurface feature realization uncertainty values, generating subsurface parameter values, generating subsurface parameter realizations, generating subsurface feature prediction probability distributions, generating a first representation of likelihoods of the subsurface feature values, and displaying the first representation.