Abstract: Systems and methods for facilitating virtual operation of a virtual vehicle within a virtual environment are disclosed. According to aspects, a computing device may access a data model indicative of real-life operation of a real-life vehicle by a real-life operator and, based on the data model, generate a set of virtual vehicle movements that are reflective of a performance of the real-life operation of the real-life vehicle by the real-life operator. The computing device may display, in a user interface, the virtual vehicle undertaking the set of virtual vehicle movements such that the real-life operator may review the virtual movements and potentially be motivated to improve his/her real-life vehicle operation.

Abstract: An object of the invention is to efficiently create a 3D model of a plant with attributes from a 3D model of a plant with no attributes. In order to solve the above problems, in the invention, a connection information conversion part 5 converts a connection relationship of parts extracted from a 3D model with no attributes 2 into connection information of a system diagram, an extraction information comparing part 6 compares the connection information with the connection relationship extracted from an attribute system diagram to create an conversion correspondence DB 7, and a 3D model with attributes 9 is created based on the conversion correspondence DB from the 3D model with no attributes 2.

Abstract: Embodiments provide techniques for using data from a select set of wells to develop correlations between surface-measured properties, downhole coring parameters, and properties typically determined from subsurface measurements (e.g., from logging tool responses, core analysis, or other subsurface measurements). When new wells are drilled, the surface data acquired while drilling and coring parameters used downhole may be used as an input to these correlations in order to predict properties associated with subsurface measurements.

Abstract: Determining a quality score for a part manufactured by an additive manufacturing machine based on build parameters and sensor data without the need for extensive physical testing of the part. Sensor data is received from the additive manufacturing machine during manufacture of the part using a first set of build parameters. The first set of build parameters is received. A first algorithm is applied to the first set of build parameters and the received sensor data to generate a quality score. The first algorithm is trained by receiving a reference derived from physical measurements performed on at least one reference part built using a reference set of build parameters. The quality score is output via the communication interface of the device.

Abstract: A vehicle can capture data that can be converted into a synthetic scenario for use in a simulator. Objects can be identified in the data and attributes associated with the objects can be determined. The data can be used to generate a synthetic scenario of a simulated environment. The scenarios can include simulated objects that traverse the simulated environment and perform actions based on the attributes associated with the objects, the captured data, and/or interactions within the simulated environment. In some instances, the simulated objects can be filtered from the scenario based on attributes associated with the simulated objects and can be instantiated and/or destroyed based on triggers within the simulated environment. The scenarios can be used for testing and validating interactions and responses of a vehicle controller within the simulated environment.

Abstract: A vehicle can capture data that can be converted into a synthetic scenario for use in a simulator. Objects can be identified in the data and attributes associated with the objects can be determined. The data can be used to generate a synthetic scenario of a simulated environment. The scenarios can include simulated objects that traverse the simulated environment and perform actions based on the attributes associated with the objects, the captured data, and/or interactions within the simulated environment. In some instances, the simulated objects can be filtered from the scenario based on attributes associated with the simulated objects and can be instantiated and/or destroyed based on triggers within the simulated environment. The scenarios can be used for testing and validating interactions and responses of a vehicle controller within the simulated environment.

Abstract: Disclosed is an apparatus for determining goodness of fit related to microphone placement capable of communicating with other electronic devices and an external server in a 5G communication network, in which an artificial intelligence (AI) algorithm and/or a machine learning algorithm are executed. The apparatus includes an inputter, a communicator, a storage, and a processor. As the apparatus is provided, sound recognition effects can be improved.

Abstract: A drill bit for subterranean drilling operations is disclosed. The drill bit comprises a drill bit body with one or more blades. The drill bit further comprises a plurality of primary cutters, each primary cutter located on at least one blade, and a plurality of secondary cutters, each secondary cutter located on at least one blade other than the blade on which the primary cutters are located.

Abstract: Simulator includes a first core unit corresponding to the first simulation model, a second core unit corresponding to the second simulation model, a slave block unit for communicating with one of the first core unit and the second core unit, the first core unit and the second core unit and a simulation control unit for causing either to execute instructions. The first core unit includes a high-speed mode instruction execution control unit that stops executing subsequent instructions in response to a request for switching from the first simulation model to the second simulation model, and a transaction monitor unit that monitors whether or not the transaction processing between the first core unit and the slave block unit has been completed. The simulation control unit causes the second core unit to execute instructions in response to a notification of completion of the transaction processing from the transaction monitor unit.

Abstract: The present disclosure includes computing device related, systems, and methods for IPR planning as described herein. One method includes identifying a first tooth and a second tooth in a digital dental model with an overlap in a target final position in a treatment plan and identifying a reference line on each of the first tooth and the second tooth; revising the treatment plan wherein a position of each of the first tooth and the second tooth is determined in which the reference line of each of the first tooth and the second tooth are aligned and the first tooth and second tooth are not overlapping; and prescribing IPR based on the determined position of each of the first tooth and the second tooth.

Abstract: Simulating fluid flow in a fractured reservoir includes generating a grid for a fractured reservoir model that includes a fracture and a matrix to obtain a generated grid. Cross-flow equilibrium elements are generated based on the generated grid. A volume expansion parameter is selected for the cross flow equilibrium elements, and used, along with physical properties, pore volume and transmissibility multipliers. The physical properties are included in the cross flow equilibrium elements. A fluid flow in the fractured reservoir model is simulated using the pore volume and transmissibility multipliers and a fracture relative permeability curve to obtain a result, which is presented. The fluid flow is calculated for the cross flow equilibrium elements.

Abstract: Methods and apparatus for managing fluid flow in pipes. An exemplary method includes initializing models of at least two fluid pads and one or more pipe elements, the models of the fluid pads comprising material points; for each of the material points, determining: an integration weight; and a material state; (a) for each of the fluid pads, discretizing governing fluid flow equations on a numerical grid, wherein the numerical grid is constrained within the pipe elements; (b) solving the discretized equations to generate nodal solutions; (c) constructing material point solutions from the nodal solutions; and until end criteria are met: updating the models of the fluid pads with the material point solutions; and repeating (a)-(c). An exemplary fluid flow data analysis system includes a processor and a display configured to display graphical representations of a fluid flow model, wherein the system is configured to manage fluid flow in pipes.

Abstract: A fractional-order KiBaM battery model considering nonlinear capacity characteristics and a parameter identification method includes a temporary capacity portion and an available capacity portion for describing nonlinear capacity characteristics of a battery, wherein the temporary capacity portion represents the power that can be directly obtained during the discharge, indicating the state of charge (SOC) of the battery; the available capacity portion represents the power that cannot be directly obtained, and such two portions are connected; when the battery is discharged, the load current i flows out from the temporary capacity portion, and a power passing rate coefficient of such capacity portions is obtained; and the nonlinear capacity effect and recovery effect of the battery are denoted by the height ratio of the temporary capacity and available capacity portions in view of the magnitude of the fractional order of battery capacity characteristics.

Abstract: A method, apparatus and system is provided for assessing risk for well completion, comprising: obtaining, using an input interface, a Below Rotary Table hours and a plurality of well-field parameters for one or more planned runs, determining, using at least one processor, one or more non-productive time values that correspond to the one or more planned runs based upon the well-field parameters, developing, using at least one processor, a non-productive time distribution and a Below Rotary Table distribution via one or more Monte Carlo trials; and outputting, using a graphic display, a risk transfer model results based on a total BRT hours from the Below Rotary Table and the non-productive time distribution produced from the one or more Monte Carlo trials.

Abstract: A method for modeling slug flow includes receiving a fluid flow model including a representation of a conduit and a multiphase fluid flow therein. A slug bubble birth rate is determined in the multiphase fluid flow. The slug bubble birth rate is determined based at least partially on a difference between a slug front velocity and a slug tail velocity. A slug bubble is initiated in the fluid flow model based at least partially on the slug bubble birth rate. Data representative of the slug flow is displayed in the fluid flow model after the slug bubble is initiated.

Abstract: Methods and systems for optimizing additive process parameters for an additive manufacturing process. In some embodiments, the process includes receiving initial additive process parameters, generating an uninformed design of experiment utilizing a specified sampling protocol, next generating, based on the uninformed design of experiment, response data, and then generating, based on the response data and on previous design of experiment that includes at least one of the uninformed design of experiment and informed design of experiment, an informed design of experiment by using the machine learning model and the intelligent sampling protocol. The last process step is repeated until a specified objective is reached or satisfied.

Abstract: Methods and systems of the present disclosure integrate time-lapse gravimetric data with dynamic reservoir modeling, whereby petrophysical constraints are applied to the inversion of the gravimetric data to constrain the resulting dynamic reservoir simulations.

Abstract: Methods and systems of evaluating a performance of an entity are described. A processor may obtain first data indicating tier attributes of resources of the entity, second data indicating function attributes of the resources, and third data indicating productivity attributes of the resources. The processor may train a model based on the first data, the second data, and the third data, the model may represent transitions of the resources over time. The processor may receive a set of controls including at least an objective to optimize a performance of the entity. The processor may generate a controlled model by integrating the set of controls into the model. The processor may determine a set of outcomes from the controlled model that includes at least a set of transitions relating to the resources that may optimize the performance of the entity.

Abstract: The disclosure relates to testing software for operating an autonomous vehicle. In one instance, a simulation may be run using log data collected by a vehicle operating in an autonomous driving mode. The simulation may be run using the software to control a simulated vehicle and by modifying a characteristic of an agent identified in the log data. During the running of the simulation, that a first type of interaction between the first simulated vehicle and the modified agent will occur may be determined. In response to determining that the particular type of interaction will occur, the modified agent may be replaced by a interactive agent that simulates a road user corresponding to the modified agent that is capable of responding to actions performed by simulated vehicles. That the particular type of interaction between the simulated vehicle and the interactive agent has occurred in the simulation may be determined.

Abstract: A reflection full waveform inversion method updates separately a density model and a velocity model of a surveyed subsurface formation. The method includes generating a model-based dataset corresponding to the seismic dataset using a velocity model and a density model to calculate an objective function measuring the difference between the seismic dataset and the model-based dataset. A high-wavenumber component of the objective function's gradient is used to update the density model of the surveyed subsurface formation. The model-based dataset is then regenerated using the velocity model and the updated density model, to calculate an updated objective function. The velocity model of the surveyed subsurface formation is then updated using a low-wavenumber component of the updated objective function's gradient. A structural image of the subsurface formation is generated using the updated velocity model.