A Deep Learning Approach for Thermal Plume Prediction of Groundwater Heat Pumps

• URL: http://arxiv.org/abs/2203.14961v1
• Date: Tue, 29 Mar 2022 07:12:28 GMT
• Title: A Deep Learning Approach for Thermal Plume Prediction of Groundwater Heat Pumps
• Abstract summary: We develop a novel data-driven approach for building small-scale surrogates for modelling the thermal plumes generated by groundwater heat pumps in the surrounding subsurface water. We show that compared to existing models ours can capture more complex dynamics while still being quick to compute.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Climate control of buildings makes up a significant portion of global energy consumption, with groundwater heat pumps providing a suitable alternative. To prevent possibly negative interactions between heat pumps throughout a city, city planners have to optimize their layouts in the future. We develop a novel data-driven approach for building small-scale surrogates for modelling the thermal plumes generated by groundwater heat pumps in the surrounding subsurface water. Building on a data set generated from 2D numerical simulations, we train a convolutional neural network for predicting steady-state subsurface temperature fields from a given subsurface velocity field. We show that compared to existing models ours can capture more complex dynamics while still being quick to compute. The resulting surrogate is thus well-suited for interactive design tools by city planners.

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