PATENT CLAIM ANALYSIS

Application Number: 16517154
Application Type: Utility
Filing Date: 2019-07
Publication Date: 2019-11
Patent Classification: ["345", "419000"]

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.

Claim (Index 15):
The method of  claim 14 , further comprising:\n in response to the modification of the computer aided design data associated with the mechanical device, updating, by the system, the control volume based on the identification data.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 100.0
- Lexical Diversity: 2.52542
- Patent Class: 345.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15630939', '15196713', '15224000', '16018622', '14298370']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5977098353183699
- 35 USC 102 Novelty (BERT): 0.5577973878920186
- Combined Prediction Score: 0.5937185905757347
- Mean Citation Score: 256.754564
- Max Citation Score: 436.2615
- Similarity Product: 308.59254321438067

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 0

Dataset: test