Abstract
This paper proposes a digital twin (DT) framework for point source applications in environmental sensing (ES). The DT concept has become quite popular among process and manufacturing industries for improving performance and estimating remaining useful life (RUL). However, environmental behavior, such as in gas dispersion, is ever changing and hard to model in real-time. The DT framework is applied to the point source environmental monitoring problem, through the use of hybrid modeling and optimization techniques. A controlled release case study is overviewed to illustrate our proposed DT framework and several spatial interpolation techniques are explored for source estimation. Future research efforts and directions are discussed.
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Acknowledgements
The authors would like to thank Jairo Viola for his helpful discussions on digital twins. The authors also thank the reviewers for helpful comments in improving this manuscript.
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DH was supported in part by the National Science Foundation Research Traineeship Grant DGE - 1633722. DH and YQC were supported in part by State of California’s Strategic Growth Council grant “Mobile Biochar Production For Methane Emission Reduction And Soil Amendment” (SGC#2019CCR20014, 2019–2023).
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Hollenbeck, D., Chen, Y. A Digital Twin Framework for Environmental Sensing with sUAS. J Intell Robot Syst 105, 1 (2022). https://doi.org/10.1007/s10846-021-01542-8
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DOI: https://doi.org/10.1007/s10846-021-01542-8