In some examples, a method for determining weldable and unweldable portions of a seam comprises receiving a representation of a part including the seam. The method also includes discretizing a representation of the seam into a plurality of waypoints. The method also includes evaluating each waypoint from the plurality of waypoints for feasibility of welding. The method further includes generating a weld path through at least a subset of the plurality of waypoints in accordance with the feasibility of welding.

A system uses machine learning models, such as neural networks for generating mask design from a circuit design. The machine learning models have inputs and outputs which are localized to a small region of the circuit design. The machine learning model takes as input features describing the circuit design in the neighborhood of a location and generates an offset distance as output. The system uses the offset distance to generate features of the mask design, for example, main features or assist features corresponding to a circuit design polygon. The system may use the offset distance for target optimization by modifying the circuit design polygon to obtain a circuit design polygon that has improved manufacturability.

A method comprises creating an electronic circuit design having a plurality of electronic components, defining a fault condition imposable during a simulation of the electronic circuit design, and generating a simulation model based on the electronic circuit design. The method also comprises generating a simulation fault model representing the fault condition and executing a simulation of the simulation model to simulate operation of the electronic circuit design. During the execution of the simulation, the method comprises controlling the simulation fault model to begin an imposition of the fault condition within the simulation model, simulating circuit behavior of the simulation model in response to the imposition of the fault condition, controlling the simulation fault model to cease the imposition of the fault condition within the simulation model, and simulating circuit behavior of the simulation model in response to the cessation of the imposition of the fault condition.

Disclosed is a digital twinning method for monitoring an operation state of a tower of a wind turbine generator system online. The method includes: 1) constructing a simplified model of the tower of the wind turbine generator system, and discretizing the simplified model according to a finite element method to obtain a finite element model; 2) reducing an order of the finite element model of the tower according to proper orthogonal decomposition, analyzing precision of a reduced-order model under different orders, and selecting the reduced-order model having a smallest reduced order as a final reduced-order model on the premise that the precision satisfies actual engineering requirements; and 3) programming upper computer software in a computer, deploying the reduced-order model to the upper computer software, further building a physical entity of the tower, and monitoring a stress and a strain of the physical entity online through the reduced-order model.

A method and apparatus for evaluating vulnerability of monopile foundations of offshore wind turbines are provided. The method includes collecting offshore wind farm location data and wind-wave characteristic data, and simulating a wind-wave time course according to the offshore wind farm location data and the wind-wave characteristic data; determining a wind-wave dynamic load based on the wind-wave course; obtaining lateral soil resistance data of monopile foundations with a plurality of rock-soil strength parameters, and inputting the wind-wave dynamic load into a 3D finite element model; using the lateral soil resistance data of monopile foundations with a plurality of rock-soil strength parameters as boundary conditions of the 3D finite element model; and giving a limit state of monopile foundations, and determining vulnerability of monopile foundations on basis of the dynamic response result of the monopile foundations and the limit state of monopile foundations.

A method of determining a repair method for a defect in a bladed rotor can comprise comparing the defect in a three-dimensional model of an inspected integrally bladed rotor (IBR) to a plurality of known defects from a repair database; determining the defect is matching a known defect in the plurality of known defects in the repair database; and generating a repair process associated with the known defect in response to determining the defect is matching the known defect. A method can also comprise determining a potential repair process; performing a structural simulation of a finite element model for the inspected IBR with the potential repair; performing an aerodynamic simulation of an aerodynamic model for the inspected IBR with the potential repair; and generating the potential repair process for the defect in response to determining the inspected IBR with the potential repair meets structural and the aerodynamic criteria.

A computer system may receive a layout of a data center, the layout of the data center identifying physical locations of a plurality of server racks, electrical distribution feeds, and uninterruptible power supplies. The computer system may receive a fault domain configuration for the datacenter, the fault domain configuration identifying virtual locations of a plurality of logical fault domains for distributing one or more instances so that the instances are stored on independent physical hardware devices within a single availability fault domain. The computer system may determine the configuration for the data center by assigning the plurality of fault domains to a plurality of electrical zones, wherein each electrical zone provides a redundant electrical power supply across the plurality of logical fault domains in an event of a failure of one or more electrical distribution feeds. The computer system may display the configuration for the data center on a display.

An information processing apparatus has an output data acquisition unit configured to acquire an output value obtained by performing an experiment or simulation based on an input parameter of a predetermined number of dimensions, an evaluation value calculation unit configured to calculate and output an evaluation value of the output value, an outlier processing unit configured to output a converted evaluation value including a specified value obtained by converting the evaluation value that does not satisfy a predetermined criterion, a next input parameter determination unit configured to determine a next input parameter based on the input parameter and the converted evaluation value corresponding to the input parameter, and an iteration determination unit configured to repeat processing of the output data acquisition unit, the evaluation value calculation unit, the outlier processing unit, and the next input parameter determination unit until a predetermined condition is satisfied.

A processing method, a processing apparatus for circuit reliability, a storage medium, and an electronic device are disclosed. The method includes: obtaining a failure rate and a corresponding failure coefficient for each of components; determining a failure expectation value for each of the components based on the failure rate and the corresponding failure coefficient; and comparing a plurality of failure expectation values to identify a component to be modified, and reducing the failure expectation value of the component to be modified based on the failure coefficient of the component to be modified.

Techniques for generating simulations to evaluate a performance of an object controller. The controller may be configured to control one or more functionalities of a simulated object (e.g., a smart object) in a simulation, such as make the smart object operate like a human in a given scenario. A simulation system may generate one or more simulations based on log data captured by a vehicle operating in a physical environment. The simulation system may cause the object controller to control at least one smart object in the simulation, the smart object being representative of an actual object detected in the physical environment. The simulation system may compare a smart object trajectory to an actual object trajectory of the object to determine a performance metric associated with the object controller. Based on a determination that the performance metric satisfies a threshold, the simulation system may validate the object controller.