AUTOMATIC RESTARTING AND RECONFIGURATION OF PHYSICS-BASED MODELS IN EVENT OF MODEL FAILURE

    公开(公告)号:US20200233747A1

    公开(公告)日:2020-07-23

    申请号:US16253267

    申请日:2019-01-22

    Abstract: A simulation model recovery method, system, and computer program product include initiating a simulation model, during an operation of a model, periodically writing a solution space of the model to a checkpoint restart file, during an operation of the model, periodically writing diagnostic information on model progression to a log file, detecting a failure of the model, based on the log of the model, determining a time of the failure, based on the model outputs and restart files, determining a period of a numerical instability preceding the failure, selecting a checkpoint of the model preceding the period of the numerical instability, based on the numerical instability and diagnostic information in log files, modifying a configuration of the model, and restarting the model based on the selected checkpoint and the modified configuration.

    Synthetic bathymetry generation using one or more fractal techniques

    公开(公告)号:US11914043B2

    公开(公告)日:2024-02-27

    申请号:US17151514

    申请日:2021-01-18

    CPC classification number: G01S17/89

    Abstract: Method, apparatus, and computer program product are provided for generating synthetic bathymetry using one or more fractal techniques. In some embodiments, real terrain data generated from sensor-based measurement of terrain associated with but outside a water body are received. This data may include, for example, real terrain data generated from sensor-based measurement (e.g., LiDAR) of at least a portion of an area proximate the water body. One or more fractal dimensions is/are extracted from the real terrain data, and synthetic bathymetry of the water body is generated based on the one or more fractal dimensions using one or more fractal terrain generation techniques. In some embodiments, one or more simulated geological processes is/are applied to the synthetic bathymetry. For example, a simulated sedimentation process and/or a simulated erosion process may be applied to soften the synthetic bathymetry.

    NOTIFYING PASSENGERS OF IMMINENT VEHICLE BRAKING

    公开(公告)号:US20210001771A1

    公开(公告)日:2021-01-07

    申请号:US16458249

    申请日:2019-07-01

    Abstract: A method, a computer program product, and a computer system notify passengers of an imminent brake event of a vehicle. The method includes determining that the imminent brake event is about to occur. The method includes determining a delay value to be applied to a brake system of the vehicle. The method includes determining a safety threshold associated with the imminent brake event based on at least one of conditions of the vehicle and surroundings of the vehicle. As a result of the delay value being less than the safety threshold, the method includes postponing use of the brake system for a duration corresponding to the delay value. The method includes broadcasting a notification to the passengers of the imminent brake event.

    WEATHER FORECASTING USING TELECONNECTIONS
    10.
    发明公开

    公开(公告)号:US20230408726A1

    公开(公告)日:2023-12-21

    申请号:US17807815

    申请日:2022-06-20

    CPC classification number: G01W1/10

    Abstract: A method, computer system, and a computer program for weather prediction are provided. The method may include receiving a first weather event associated with a first location. The present invention may further include inputting the first weather event into a machine learning model generated via mapping historical weather data into a latent space and via identifying, in the latent space, climate teleconnections amongst historical weather events at various locations. The method may further include in response to the inputting, receiving by the computing device a weather prediction for a second location, the weather prediction being based on a predicted climate teleconnection between the first location and the second location with respect to the first weather event, wherein the teleconnections machine learning model maps the first weather event into latent code for the latent space in order to generate the weather prediction for the second location.

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