Systems and method for securely sharing and executing data and models

    公开(公告)号:US10262127B2

    公开(公告)日:2019-04-16

    申请号:US15479906

    申请日:2017-04-05

    Abstract: A simulation computer device for securely executing a model includes at least one processor in communication with at least one memory device. The simulation computer device is configured to store a smart container including a model and a usage policy. The simulation computer device is also configured to receive a plurality of inputs for the model and determine whether to validate the model based on the usage policy. The simulation computer device is further configured to execute the model with the plurality of inputs if the model was validated. Moreover, the simulation computer device is configured to transmit at least one output.

    PROBABILISTIC METHOD AND SYSTEM FOR TESTING A MATERIAL
    3.
    发明申请
    PROBABILISTIC METHOD AND SYSTEM FOR TESTING A MATERIAL 有权
    用于测试材料的概率方法和系统

    公开(公告)号:US20140278310A1

    公开(公告)日:2014-09-18

    申请号:US13840785

    申请日:2013-03-15

    CPC classification number: G06F17/5009

    Abstract: A method implemented using a processor based device for simulation based testing of materials, includes selecting a first set of points from a data generated from a design space and generating a stochastic metamodel based on the first set of points. The method also includes determining an uncertainty value based on the stochastic metamodel. The method also includes identifying a second set of points different from the first set of points, from the data generated from the design space, based on the uncertainty value. The method further includes combining the second set of points with the first set of points to generate a third set of points, assigning the third set of points to the first set of points. The method also includes iteratively generating, determining, identifying, combining, and assigning steps till the uncertainty value is less than or equal to a predetermined threshold value.

    Abstract translation: 使用基于处理器的设备实现的用于基于模拟的材料测试的方法包括从从设计空间生成的数据中选择第一组点并基于第一组点生成随机元模型。 该方法还包括基于随机元模型来确定不确定性值。 该方法还包括基于不确定性值从与设计空间生成的数据中识别不同于第一组点的第二组点。 该方法还包括将第二组点与第一组点组合以产生第三组点,将第三组点分配给第一组点。 该方法还包括迭代地生成,确定,识别,组合和分配步骤,直到不确定性值小于或等于预定阈值。

    SYSTEM AND METHOD FOR ESTIMATION AND CONTROL OF CLEARANCE IN A TURBO MACHINE
    6.
    发明申请
    SYSTEM AND METHOD FOR ESTIMATION AND CONTROL OF CLEARANCE IN A TURBO MACHINE 审中-公开
    用于涡轮机间隙的估计和控制的系统和方法

    公开(公告)号:US20150169811A1

    公开(公告)日:2015-06-18

    申请号:US14132313

    申请日:2013-12-18

    CPC classification number: G06F17/5018

    Abstract: A method implemented using at least one processor includes receiving a plurality of measured operational parameters of a turbo machine having a rotor and a stator. The plurality of measured operational parameters includes a plurality of real-time operational parameters and a plurality of stored operational parameters. The method further includes generating a finite element model of the turbo machine and generating a plurality of snapshots based on the finite element model and the plurality of stored operational parameters. The method further includes generating a reduced order model based on the plurality of snapshots. The method also includes determining an estimated clearance between the rotor and the stator during operation of the turbo machine, based on the reduced order model and the plurality of real-time operational parameters.

    Abstract translation: 使用至少一个处理器实现的方法包括接收具有转子和定子的涡轮机的多个测量的操作参数。 多个测量的操作参数包括多个实时操作参数和多个存储的操作参数。 该方法还包括生成涡轮机的有限元模型,并且基于有限元模型和多个存储的操作参数生成多个快照。 该方法还包括基于多个快照生成缩减订单模型。 所述方法还包括基于所述降序模型和所述多个实时操作参数来确定所述涡轮机的操作期间所述转子和所述定子之间的估计间隙。

    Framework for rapid additive design with generative techniques

    公开(公告)号:US11079738B2

    公开(公告)日:2021-08-03

    申请号:US15678653

    申请日:2017-08-16

    Abstract: According to some embodiments, a system may include a design experience data store containing electronic records associated with prior industrial asset item designs. A deep learning model platform, coupled to the design experience data store, may include a communication port to receive constraint and load information from a designer device. The deep learning platform may further include a computer processor adapted to automatically and generatively create boundaries and geometries, using a deep learning model associated with an additive manufacturing process, for an industrial asset item based on the prior industrial asset item designs and the received constraint and load information. According to some embodiments, the deep learning model computer processor is further to receive design adjustments from the designer device. The received design adjustments might be for example, used to execute an optimization process and/or be fed back to continually re-train the deep learning model.

    Systems and method for dynamic combustion tests

    公开(公告)号:US10706189B2

    公开(公告)日:2020-07-07

    申请号:US15445334

    申请日:2017-02-28

    Abstract: A testing system computer device for dynamically updating a test plan of an apparatus includes at least one processor in communication with at least one memory device. The testing system computer device is configured to store a plurality of historical data and generate a simulation model of the apparatus based in part on the historical data. The simulation model includes a plurality of inputs and a plurality of outputs of the apparatus. The testing system computer device is also configured to determine a plurality of tests to perform on the apparatus based on the simulation model and the plurality of historical data. The testing system computer device is further configured to receive a plurality of desirability ratings from a user, rank the plurality of tests to perform based on the plurality of desirability ratings, and present the ranked plurality of tests to the user.

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