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公开(公告)号:US20210272700A1
公开(公告)日:2021-09-02
申请号:US17307617
申请日:2021-05-04
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik , Shane Cline
IPC: G16H50/50 , G06N20/00 , G16H30/40 , G06F30/17 , G06F30/20 , G06F3/0481 , G05B13/02 , G05B13/04 , G05D7/06 , G06N5/04
Abstract: A multiple fluid model tool for multi-dimensional fluid modeling of a biological structure is presented. For example, a system includes a modeling component, a machine learning component, and a three-dimensional health assessment component. The modeling component generates a three-dimensional model of a biological structure based on multi-dimensional medical imaging data. The machine learning component predicts one or more characteristics of the biological structure based on input data and a machine learning process associated with the three-dimensional model. The three-dimensional health assessment component that provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the biological structure based on the input data and the one or more characteristics of the biological structure on the three-dimensional model.
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公开(公告)号:US20210232732A1
公开(公告)日:2021-07-29
申请号:US17228145
申请日:2021-04-12
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik , Vijay Sethuraman , Berkay Elbir
Abstract: Techniques that facilitate optimization of prototype and machine design within a three-dimensional fluid modeling environment are presented. For example, a system includes a modeling component, a machine learning component, and a graphical user interface component. The modeling component generates three-dimensional model of a mechanical device based on a library of stored data elements. The machine learning component predicts one or more characteristics of the mechanical device based on a first machine learning process associated with the three-dimensional model. The machine learning component also generates physics modeling data of the mechanical device based on the one or more characteristics of the mechanical device. The graphical user interface component provides, via a graphical user interface, a three-dimensional design environment associated with the three-dimensional model and a probabilistic simulation environment associated with optimization of the three-dimensional model.
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3.
公开(公告)号:US11379630B2
公开(公告)日:2022-07-05
申请号:US17174047
申请日:2021-02-11
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik
IPC: G06F30/17 , G06N20/00 , G06F30/20 , G06T15/00 , G06T17/05 , G06F111/10 , G06F119/18
Abstract: A multiple fluid model tool for utilizing a 3D CAD point-cloud to automatically create a fluid model is presented. For example, a system includes a modeling component, a machine learning component, and a three-dimensional design component. The modeling component generates a three-dimensional model of a mechanical device based on point cloud data indicative of information for a set of data values associated with a three-dimensional coordinate system. The machine learning component predicts one or more characteristics of the mechanical device based on input data and a machine learning process associated with the three-dimensional model. The three-dimensional design component that provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the mechanical device based on the input data and the one or more characteristics of the mechanical device on the three-dimensional model.
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公开(公告)号:US11967434B2
公开(公告)日:2024-04-23
申请号:US17307617
申请日:2021-05-04
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik , Shane Cline
IPC: G16H50/50 , G05B13/02 , G05B13/04 , G05D7/06 , G06F3/04815 , G06F30/17 , G06F30/20 , G06N5/04 , G06N20/00 , G16H30/40 , G01F5/00 , G16H50/20
CPC classification number: G16H50/50 , G05B13/0265 , G05B13/041 , G05B13/048 , G05D7/0617 , G06F3/04815 , G06F30/17 , G06F30/20 , G06N5/04 , G06N20/00 , G16H30/40 , G01F5/00 , G16H50/20 , Y02T90/00
Abstract: A multiple fluid model tool for multi-dimensional fluid modeling of a biological structure is presented. For example, a system includes a modeling component, a machine learning component, and a three-dimensional health assessment component. The modeling component generates a three-dimensional model of a biological structure based on multi-dimensional medical imaging data. The machine learning component predicts one or more characteristics of the biological structure based on input data and a machine learning process associated with the three-dimensional model. The three-dimensional health assessment component that provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the biological structure based on the input data and the one or more characteristics of the biological structure on the three-dimensional model.
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公开(公告)号:US11947882B2
公开(公告)日:2024-04-02
申请号:US17228145
申请日:2021-04-12
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik , Vijay Sethuraman , Berkay Elbir
IPC: G06F30/20 , G06N3/043 , G06N3/045 , G06N7/01 , G06N7/02 , G06N20/00 , G06T17/05 , G06F3/04815 , G06F111/08 , G06F111/10 , G06N3/042 , G06N5/00
CPC classification number: G06F30/20 , G06N3/043 , G06N3/045 , G06N7/01 , G06N7/023 , G06N20/00 , G06T17/05 , G06F3/04815 , G06F2111/08 , G06F2111/10 , G06N3/042 , G06N5/00 , G06T2210/21
Abstract: Techniques that facilitate optimization of prototype and machine design within a three-dimensional fluid modeling environment are presented. For example, a system includes a modeling component, a machine learning component, and a graphical user interface component. The modeling component generates three-dimensional model of a mechanical device based on a library of stored data elements. The machine learning component predicts one or more characteristics of the mechanical device based on a first machine learning process associated with the three-dimensional model. The machine learning component also generates physics modeling data of the mechanical device based on the one or more characteristics of the mechanical device. The graphical user interface component provides, via a graphical user interface, a three-dimensional design environment associated with the three-dimensional model and a probabilistic simulation environment associated with optimization of the three-dimensional model.
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公开(公告)号:US10977397B2
公开(公告)日:2021-04-13
申请号:US15630941
申请日:2017-06-22
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik , Vijay Sethuraman , Berkay Elbir
IPC: G06F30/20 , G06T17/00 , G06T17/05 , G06N3/04 , G06N7/02 , G06N20/00 , G06N7/00 , G06F3/0481 , G06N5/00 , G06F111/08 , G06F111/10
Abstract: Techniques that facilitate optimization of prototype and machine design within a three-dimensional fluid modeling environment are presented. For example, a system includes a modeling component, a machine learning component, and a graphical user interface component. The modeling component generates three-dimensional model of a mechanical device based on a library of stored data elements. The machine learning component predicts one or more characteristics of the mechanical device based on a first machine learning process associated with the three-dimensional model. The machine learning component also generates physics modeling data of the mechanical device based on the one or more characteristics of the mechanical device. The graphical user interface component provides, via a graphical user interface, a three-dimensional design environment associated with the three-dimensional model and a probabilistic simulation environment associated with optimization of the three-dimensional model.
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公开(公告)号:US11538591B2
公开(公告)日:2022-12-27
申请号:US15630931
申请日:2017-06-22
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik
IPC: G06N5/04 , G16H50/50 , G06N20/00 , G16H30/40 , G06F30/17 , G06F30/20 , G06F3/04815 , G05B13/02 , G05B13/04 , G05D7/06 , G16H50/20 , G01F5/00
Abstract: A multiple fluid model tool for training and/or refining of fluid models using disparate and/or aggregated machine data is presented. For example, a system includes a modeling component, a machine learning component, a three-dimensional design component and a data collection component. The modeling component generates a three-dimensional model of a mechanical device based on a library of stored data elements. The machine learning component predicts one or more characteristics of the mechanical device based on a machine learning process associated with the three-dimensional model. The three-dimensional design component provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the mechanical device on the three-dimensional model based on the one or more characteristics of the mechanical device. The data collection component collects machine data via a communication network to update the three-dimensional model associated with the three-dimensional design environment.
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8.
公开(公告)号:US20220292231A1
公开(公告)日:2022-09-15
申请号:US17829673
申请日:2022-06-01
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik
Abstract: A multiple fluid model tool for utilizing a 3D CAD point-cloud to automatically create a fluid model is presented. Fr example, a system includes a modeling component, a machine learning component, and a three-dimensional design component. The modeling component generates a three-dimensional model of a mechanical device based on point cloud data indicative of information for a set of data values associated with a three-dimensional coordinate system. The machine learning component predicts one or more characteristics of the mechanical device based on input data and a machine learning process associated with the three-dimensional model. The three-dimensional design component that provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the mechanical device based on the input data and the one or more characteristics of the mechanical device on the three-dimensional model.
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9.
公开(公告)号:US20210232721A1
公开(公告)日:2021-07-29
申请号:US17174047
申请日:2021-02-11
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik
Abstract: A multiple fluid model tool for utilizing a 3D CAD point-cloud to automatically create a fluid model is presented. For example, a system includes a modeling component, a machine learning component, and a three-dimensional design component. The modeling component generates a three-dimensional model of a mechanical device based on point cloud data indicative of information for a set of data values associated with a three-dimensional coordinate system. The machine learning component predicts one or more characteristics of the mechanical device based on input data and a machine learning process associated with the three-dimensional model. The three-dimensional design component that provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the mechanical device based on the input data and the one or more characteristics of the mechanical device on the three-dimensional model.
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10.
公开(公告)号:US11714933B2
公开(公告)日:2023-08-01
申请号:US17829673
申请日:2022-06-01
Applicant: Altair Engineering, Inc.
Inventor: Zain S. Dweik
IPC: G06F30/17 , G06N20/00 , G06F30/20 , G06T15/00 , G06T17/05 , G06F111/10 , G06F119/18
CPC classification number: G06F30/17 , G06F30/20 , G06N20/00 , G06T15/005 , G06T17/05 , G06F2111/10 , G06F2119/18
Abstract: A multiple fluid model tool for utilizing a 3D CAD point-cloud to automatically create a fluid model is presented. For example, a system includes a modeling component, a machine learning component, and a three-dimensional design component. The modeling component generates a three-dimensional model of a mechanical device based on point cloud data indicative of information for a set of data values associated with a three-dimensional coordinate system. The machine learning component predicts one or more characteristics of the mechanical device based on input data and a machine learning process associated with the three-dimensional model. The three-dimensional design component that provides a three-dimensional design environment associated with the three-dimensional model. The three-dimensional design environment renders physics modeling data of the mechanical device based on the input data and the one or more characteristics of the mechanical device on the three-dimensional model.
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