ANSYS has patented a method and apparatus for generating a simulation object for a physical system. The system includes a trained computing structure with input and output units to predict future output data in real-time. The structure is trained using input and output data of the physical system to improve accuracy. GlobalData’s report on ANSYS gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on ANSYS, Capillary blood collection devices was a key innovation area identified from patents. ANSYS's grant share as of February 2024 was 57%. Grant share is based on the ratio of number of grants to total number of patents.
Real-time simulation object generation for physical systems
A recently granted patent (Publication Number: US11922314B1) discloses a computer-implemented method for predicting the dynamic rate of change of input data in a physical system over a period of time. The method involves obtaining input and output data of the system, training a computing structure with a neural network, and generating a predicted dynamic rate of change based on the input and output data. The computing structure is configured with regular input and output units, as well as additional free input and output units to improve prediction accuracy. By comparing the predicted rate of change with the actual data, a prediction residual is obtained to assess accuracy. The trained computing structure is then used to create a simulation object for real-time prediction of future output data.
Furthermore, the patent also includes claims related to the configuration of the computing structure, the use of a physical solver to model system properties, and the training process involving neural networks and free input/output units. The method aims to enhance the accuracy of predicting dynamic changes in input data by incorporating additional elements in the computing structure. The system described in the patent includes one or more processors executing instructions stored in memory to perform the method, highlighting the practical application of the innovative predictive technology in real-world scenarios. Overall, the patent provides a detailed framework for improving the prediction of dynamic changes in input data in physical systems, with potential applications in various industries requiring real-time data analysis and forecasting.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
