The present disclosure belongs to the field of petroleum engineering, and specifically relates to a subsea Christmas tree re-prediction method integrating Kalman filter and Bayesian network. The subsea Christmas tree re-prediction method integrating Kalman filter and Bayesian network includes three steps: digital twin model establishment, degradation process re-prediction model establishment, and remaining useful life calculation model establishment. The subsea Christmas tree re-prediction system integrating Kalman filter and Bayesian network includes a subsea distribution unit information acquisition subsystem mounted on an subsea distribution unit, a subsea control module information acquisition subsystem mounted on a subsea control module, a subsea valve bank information acquisition subsystem mounted on a subsea valve bank, a wellhead mechanical module information acquisition subsystem mounted on a wellhead mechanical module, a subsea environmental information acquisition module mounted on a subsea control module, and a subsea Christmas tree digital twin subsystem mounted in an overwater control station.

The present disclosure belongs to the field of petroleum engineering, and specifically relates to a subsea Christmas tree re-prediction method integrating Kalman filter and Bayesian network. The subsea Christmas tree re-prediction method integrating Kalman filter and Bayesian network includes three steps: digital twin model establishment, degradation process re-prediction model establishment, and remaining useful life calculation model establishment. The subsea Christmas tree re-prediction system integrating Kalman filter and Bayesian network includes a subsea distribution unit information acquisition subsystem mounted on an subsea distribution unit, a subsea control module information acquisition subsystem mounted on a subsea control module, a subsea valve bank information acquisition subsystem mounted on a subsea valve bank, a wellhead mechanical module information acquisition subsystem mounted on a wellhead mechanical module, a subsea environmental information acquisition module mounted on a subsea control module, and a subsea Christmas tree digital twin subsystem mounted in an overwater control station.

A modal superposition method using a response dependent non-linear mode concept for a vibration analysis of non-linear engineering structures is provided. The modal superposition method is provided to find steady state response of non-linear systems in frequency domain. The modal superposition method is used in many mechanical structures, especially in design of aerospace and automotive structures, defense industry platforms, steam and gas turbines and mechanical structures containing non-linear forces such as gas turbine engines and jet engines.

A computer-implemented method for designing a product to be manufactured. The method includes obtaining a first subpart and a second subpart of the product. Each subpart is represented by a semantic representation having one or more semantic nodes. Each semantic representation has, for each semantic node of the semantic representation, a respective procedural graph and a respective semantic description of the semantic node. The respective semantic description comprises at least one semantic publication and at least one reference. The method includes assembling the first subpart with the second subpart by pointing one or more semantic references of the first subpart each to a respective semantic publication of the second subpart. The method comprises executing the procedural graphs of the semantic representations of the first and second subparts according to the pointed one or more semantic references. The method improves the designing of the product.

Mechanisms to increase level of detail in sets of model objects in a model for a construction product are disclosed, the mechanism utilizing a collection comprising a plurality of collection sets with details in metadata. For example, to increase level of detail in a set of model objects, content of a first metadata is determined. The first metadata comprises information indicating at least a type and geometry of the set of model objects. The collection sets are sorted to a suitability order based on compatibility of the first metadata to metadata of the collection sets. If the most suitable collection set is approved, the level of detail of the set of model objects is increased by adding to the first metadata copies of one or more details in the metadata of the most suitable collection set.

Systems and methods are provided for generating a design for a gliding board. The methods involve operating a processor to: define a desired carved turn of the gliding board; define a desired global curvature profile; generate a desired deformed shape of the gliding board during the desired carved turn; generate a sidecut profile of the gliding board; generate a width profile of the gliding board; generate a camber profile of the gliding board; generate at least one stiffness design variable profile; generate a total load profile; modify at least the width profile, the sidecut profile and at least one of the at least one stiffness design variable profile at least once; and define the design for the gliding board based at least on the width profile, the camber profile, and the at least one stiffness design variable profile.

Systems and methods are provided for generating a design for a gliding board. The methods involve operating a processor to: define a desired carved turn of the gliding board; define a desired global curvature profile; generate a desired deformed shape of the gliding board during the desired carved turn; generate a sidecut profile of the gliding board; generate a width profile of the gliding board; generate a camber profile of the gliding board; generate at least one stiffness design variable profile; generate a total load profile; modify at least the width profile, the sidecut profile and at least one of the at least one stiffness design variable profile at least once; and define the design for the gliding board based at least on the width profile, the camber profile, and the at least one stiffness design variable profile.

A machine learning pipeline inspection method and system using caliper pig data is disclosed herein. The machine learning pipeline inspection method and system are configured to use one or more machine learning models to automatically identify pipeline features of interest for a pipeline inspection. The machine learning model may be included on a caliper pig to provide pipeline feature identification in real-time or near real-time. Alternatively, the machine learning model may be provided on a computer that is separate from a caliper pig. In these alternative embodiments, caliper pig data is downloaded or otherwise transferred to the computer for processing by the machine learning model.

A machine learning pipeline inspection method and system using caliper pig data is disclosed herein. The machine learning pipeline inspection method and system are configured to use one or more machine learning models to automatically identify pipeline features of interest for a pipeline inspection. The machine learning model may be included on a caliper pig to provide pipeline feature identification in real-time or near real-time. Alternatively, the machine learning model may be provided on a computer that is separate from a caliper pig. In these alternative embodiments, caliper pig data is downloaded or otherwise transferred to the computer for processing by the machine learning model.

A method includes: accessing a part model comprising a three-dimensional representation of a part; accessing a material profile relating exposure energy and three-dimensional polymerization geometry of a material selected for the part; segmenting the part model into a set of model layers; detecting a first upward-facing surface in the part model; defining a first model volume in a first model layer, adjacent the first upward-facing surface, and fully contained within the part model; based on the material profile, calculating a first exposure energy predicted to yield a first three-dimensional polymerization geometry approximating a first contour of the first upward-facing surface when projected onto the material during a build; populating a first print image with the first exposure energy in a first image area corresponding to the first model volume in the first model layer; and storing the first print image in a print file for the part.