Geo-Pile Predictive Software
A custom ground heat exchanger design tool.
Advanced Computation
With accuracy as our top priority, this software was built from computational fluid dynamic simulations of the thermodynamic conditions of the heat exchanger. We then trained a Machine Learning algorithm to understand the multi-dimensional physics of this system.
Built to predict:
- Heat exchange capacity (amount of heating and cooling load supplied)
- Required number of heat exchangers to meet building loads
- Required length of the heat exchangers to meet building loads
- Estimated ground temperature based on heat transfer fluid temperatures
Auto Unit Conversions
Interactive Online Dashboard
Auto Report Generator
Raw Data Download
Predicting hourly and peak results from the ground heat exchangers to the building heat pumps.
How Machine Learning is Evolving the Design of New Technology
Using four ML engines, GPPS can even optimize a design to reduce oversizing. It can predict performance across time, to match a building’s load profile. With our ML Ground Temperature Predictor plug-in, these studies are customized for new locations around the world, with more accurate ground information than we ever had access to before. And, unlike CFD, all of these results are generated from the same tool, without having to make a new model each time.
Umny Inc.
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