Collects sample data using Near-Infrared Spectroscopy to authenticate raw materials. It sends data to a server for machine learning model training. Users can predict material quality based on trained models.
Calculate loss in transmission systems by selecting type, pipe material, and dimensions. Input pipe schedule and size to determine energy loss. Compare initial and operational costs for optimal pipe selection.
Calculate rates for liquids and gases using plates. Select from fifteen common industrial fluids. Input standard parameters to compute based on industry models. View results for design and analysis purposes.
