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iFLOW: A Framework and GUI to Quantify Effective Thermal Diffusivity and Advection in Permeable Materials From Temperature Time Series.

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Title: iFLOW: A Framework and GUI to Quantify Effective Thermal Diffusivity and Advection in Permeable Materials From Temperature Time Series.
Authors: Bertagnoli, A., Luce, C., van Kampen, R., Schneidewind, U., van Berkel, M., Tranmer, A. W., Vandersteen, G., Krause, S., Tonina, D.
Source: Water Resources Research; Nov2024, Vol. 60 Issue 11, p1-19, 19p
Subject Terms: TIME series analysis, THERMAL diffusivity, GRAPHICAL user interfaces, THERMAL properties, HEAT flux
Abstract: iFLOW is a free, open‐source, and python‐based framework and graphical user interface to visualize and analyze temperature time series, and extract one dimensional thermal velocity, vT, and bulk effective thermal diffusivity, ke. Information of thermal properties of the sediment‐water mixture (bulk) and water allows quantifying the one‐dimensional Darcian flux, q, and seepage velocity, v, from vT. Available software packages were developed to quantify q and ke only based on a specific mathematical model or focused on specific data processing or parameter estimation techniques, and all these steps were lumped together preventing users to identify potential source of errors. iFLOW proposes a novel organizational philosophy with a modular framework that parses the analysis process into three fundamental steps: (a) the mathematical model, (b) signal processing, and (c) parameter estimation. iFLOW houses a suite of models and analysis techniques. This suite can be readily added to and expanded through its modular framework. iFLOW contains a wizard to guide users through the selection process with respect to the three fundamental steps. Users can analyze and visualize intermediate results to identify problematic issues in the time series data and improve data interpretation. Here, we present iFLOW and summarize its performance using a set of one‐dimensional synthetic heat transport simulations. Plain Language Summary: iFLOW is a free, open‐source computer application to help users visualize and analyze temperature data. It calculates the water velocity within sediment along with thermal diffusivity from measured temperature data. Unlike other applications, iFLOW is flexible, allowing users to check for errors by breaking down the analysis into three parts: mathematical model selection, signal processing, and estimating parameters. It includes various models and methods that users can easily expand on. iFLOW also guides users through the analysis and in choosing options for these three analysis stages. We introduce iFLOW through a set of examples with simulated heat transport data. Key Points: iFLOW is a novel framework for temperature time series analysisiFLOW helps users estimate advective flux and effective thermal diffusivity with their uncertaintyThe analysis is parsed into the mathematical model selection, signal processing, and parameter estimation steps [ABSTRACT FROM AUTHOR]
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Database: Biomedical Index
Description
Abstract:iFLOW is a free, open‐source, and python‐based framework and graphical user interface to visualize and analyze temperature time series, and extract one dimensional thermal velocity, vT, and bulk effective thermal diffusivity, ke. Information of thermal properties of the sediment‐water mixture (bulk) and water allows quantifying the one‐dimensional Darcian flux, q, and seepage velocity, v, from vT. Available software packages were developed to quantify q and ke only based on a specific mathematical model or focused on specific data processing or parameter estimation techniques, and all these steps were lumped together preventing users to identify potential source of errors. iFLOW proposes a novel organizational philosophy with a modular framework that parses the analysis process into three fundamental steps: (a) the mathematical model, (b) signal processing, and (c) parameter estimation. iFLOW houses a suite of models and analysis techniques. This suite can be readily added to and expanded through its modular framework. iFLOW contains a wizard to guide users through the selection process with respect to the three fundamental steps. Users can analyze and visualize intermediate results to identify problematic issues in the time series data and improve data interpretation. Here, we present iFLOW and summarize its performance using a set of one‐dimensional synthetic heat transport simulations. Plain Language Summary: iFLOW is a free, open‐source computer application to help users visualize and analyze temperature data. It calculates the water velocity within sediment along with thermal diffusivity from measured temperature data. Unlike other applications, iFLOW is flexible, allowing users to check for errors by breaking down the analysis into three parts: mathematical model selection, signal processing, and estimating parameters. It includes various models and methods that users can easily expand on. iFLOW also guides users through the analysis and in choosing options for these three analysis stages. We introduce iFLOW through a set of examples with simulated heat transport data. Key Points: iFLOW is a novel framework for temperature time series analysisiFLOW helps users estimate advective flux and effective thermal diffusivity with their uncertaintyThe analysis is parsed into the mathematical model selection, signal processing, and parameter estimation steps [ABSTRACT FROM AUTHOR]
ISSN:00431397
DOI:10.1029/2024WR037370