Author:
Vishal Nandigana
Affiliation:
Fluid Systems Laboratory (FSL), Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India
Keyword(s):
Artificial Intelligence, Big Data, Visualization, Data Science, Math+Machine Learning, Thermal Convective Transport.
Abstract:
In this paper we propose python code written anaconda terminal run Windows OS usage for visualization and processing of big data having 4 million data points of size 36.2 MB file vector x ⃗ of 4𝑚 𝑏𝑦 4𝑚 𝑏𝑦 4𝑚 uniform meshed 100 points and solver opensource software OpenFOAM to calculate temperature profile of steel whose thermal diffusivity is 14.76 × 10−6 𝑚2/𝑠 by Laplacian partial differential equations. The software in use in AISoft visualization and processing commercial software (Sidharth and Vishal, 2022). Here we also use data driven model for predict match experiments of turbulent flow and low temperature measurements on copper core arrangements and silicon, respectively. The software in use is AISoft Windows 800 commercial software (Luke, Vishal and Jay, 2021). To compile the model train_number.csv vector measurements are uploaded in the software. The model uses RNN-LSTM method and Adam optimization minimization to calculate the learning parameters. We predict the ne
w locations and states vector measurements. The model shows 3-order speed up in computational time compared to unclear traditional turbulence models and conduction additions to the model. Also the predicted solution shows 98% accuracy. Artificial Intelligence for big data, visualization, processing, predict models is in use for AI Agents, AI ethics, cinemas, art, electronics, calendar planner and engineering applications.
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