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Publications
2023 Publications
62 | Virtual PMV sensor towards smart thermostats: Comparison of modeling approaches using intrusive data, Energy and Buildings (submitted) |
61 | Surrogate-assisted high-accuracy observation modeling in building digital twins: In situ modeling without sensor observation (Y), Building and Environment (under review) |
60 | In situ model fusion for building digital twinning, Building and Environment (under review) |
59 | Strategies for sensor virtual in-situ calibration in building energy system: Sensor evaluation and data-driven based method, Energy and Buildings (under review)
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58 | Building Digital Twinning: Data, Information, and Models, Journal of Building Engineering (under review) |
57 | Simultaneous in-situ calibration for physical and virtual sensor fusion towards digital twin-enabled building operation, Advanced Engineering Informatics (under review) |
56 | Fault detection and calibration for photovoltaic thermal heat pump system using Bayesian inference and sparse autoencoder, Energy and Buildings (accepted) |
55 | In-situ backup virtual sensor application in building automation systems toward virtual sensing-enabled digital twins, Journal of Industrial Information Integration (under review) |
54 | In situ virtual sensors in building digital twins: framework and methodology, Journal of Industrial Information Integration (under review) |
53 | J. Kim, S. Yoon, J. Koo, J. Bak, J. Lim, In situ virtual sensing for dwelling infiltration rates in multi-unit residential buildings (2023) 106225, https://doi.org/10.1016/j.jobe.2023.106225 |
52 | S. Choi, S. Yoon, Energy signature-based clustering using open data for urban building energy analysis toward carbon neutrality: A case study on electricity change under COVID-19, Sustainable Cities and Society 92 (2023) 104471, https://doi.org/10.1016/j.scs.2023.104471 |
51 | Y. Tian, J. Wang, Z. Qi, C. Yue, P. Wang, S. Yoon, Calibration method for sensor drifting bias in data center cooling system using Bayesian Inference coupling with Autoencoder, Journal of Building Engineering 67 (2023) 105961, https://doi.org/10.1016/j.jobe.2023.105961 |
50 | S. Yoon, In situ modeling methodologies in building operation: A review, Building and Environment (2023) 109982, https://doi.org/10.1016/j.buildenv.2023.109982 |
49 | Y. Choi, S. Yoon, C.Y. Park, K.C. Lee, In-situ observation and calibration in building operation: Comparison of intrusive and nonintrusive approaches, Automation in Construction 145 (2023) 104648. https://doi.org/10.1016/j.autcon.2022.104648 |
48 | J. Li, P. Wang, J. Li, H. Xing, T. Zhao, S. Yoon, Improvement for energy efficiency and control characteristics in variable air volume system using in-situ sensor calibration method based on autoencoder, Journal of Building Engineering 63 (2023) 105559. https://doi.org/10.1016/j.jobe.2022.105559 |
47 | Y. Hong, S. Yoon, S. Choi, Operational signature-based symbolic hierarchical clustering for building energy, operation, and efficiency towards carbon neutrality, Energy 265 (2023) 126276. https://doi.org/10.1016/j.energy.2022.126276 |
2022 Publications
46 | S. Park, S. Park, S. Yoon, D. Song, Predicting airtightness using differential pressure in actual climate conditions: Theory and implementation, Indoor and Built Environment. (2022). https://doi.org/10.1177/1420326X221131949 |
45 | Y. Choi, S. Yoon, In-situ observation virtual sensor in building systems toward virtual sensing-enabled digital twins, Energy and Buildings (2022) 112766. https://doi.org/10.1016/j.enbuild.2022.112766 |
44 | J. Koo, S. Yoon, In-situ sensor virtualization and calibration in building systems, Applied Energy 325 (2022) 119864. https://doi.org/10.1016/j.apenergy.2022.119864 |
43 | S. Yoon, Virtual sensing in intelligent buildings and digitalization, Automation in Construction. 143 (2022) 104578. https://doi.org/10.1016/j.autcon.2022.104578 |
42 | Y. Hong, S. Yoon, Holistic Operational Signatures for an energy-efficient district heating substation in buildings, Energy. 250 (2022) 123798. https://doi.org/10.1016/j.energy.2022.123798. |
41 | T. Lee, S. Yoon, K. Won, Delta-T-based operational signatures for operation pattern and fault diagnosis of building energy systems, Energy and Buildings. 257 (2022). https://doi.org/10.1016/j.enbuild.2021.111769. |
40 | J. Koo, S. Yoon, J. Kim, Virtual In Situ Calibration for Operational Backup Virtual Sensors in Building Energy Systems, Energies (Basel). 15 (2022). https://doi.org/10.3390/en15041394. |
39 | J. Bak, J. Koo, S. Yoon, H. Lim, Thermal Draft Load Coefficient for Heating Load Differences Caused by Stack-Driven Infiltration by Floor in Multifamily High-Rise Buildings, Energies (Basel). 15 (2022). https://doi.org/10.3390/en15041386. |
38 | T. Zhao, J. Li, P. Wang, S. Yoon, J. Wang, Improvement of virtual in-situ calibration in air handling unit using data preprocessing based on Gaussian mixture model, Energy and Buildings. 256 (2022). https://doi.org/10.1016/j.enbuild.2021.111735. |
37 | J. Wang, Z. Huang, Z. Liu, C. Yue, P. Wang, S. Yoon, In-situ sensor correction method for data center cooling systems using Bayesian Inference coupling with autoencoder, Sustainable Cities and Society. 76 (2022). https://doi.org/10.1016/j.scs.2021.103514. |
36 | S. Yoon, Y. Yu, H. Li, Y. Choi, Y. Hong, Improved energy balance calculation of unitary air conditioners via virtual in-situ calibration, Journal of Building Engineering. 45 (2022). https://doi.org/10.1016/j.jobe.2021.103464. |
35 | J. Li, P. Wang, T. Zhao, S. Yoon, J. Wang, The effects of multidimensional data clustering on the accuracy of virtual in-situ calibration in the photovoltaic/Thermal heat pump system, Journal of Building Engineering. 45 (2022). https://doi.org/10.1016/j.jobe.2021.103500. |
2021 Publications
34 | J. Bak, S. Yoon, Dwelling infiltration and heating energy demand in multifamily high-rise and low-energy buildings in Korea, Renewable and Sustainable Energy Reviews. 148 (2021). https://doi.org/10.1016/j.rser.2021.111284. |
33 | Y. Choi, S. Yoon, Autoencoder-driven fault detection and diagnosis in building automation systems: Residual-based and latent space-based approaches, Building and Environment. 203 (2021). https://doi.org/10.1016/j.buildenv.2021.108066. |
32 | Y. Hong, S. Yoon, Y.S. Kim, H. Jang, System-level virtual sensing method in building energy systems using autoencoder: Under the limited sensors and operational datasets, Applied Energy. 301 (2021). https://doi.org/10.1016/j.apenergy.2021.117458. |
31 | Z. Liu, Z. Huang, J. Wang, C. Yue, S. Yoon, A novel fault diagnosis and self-calibration method for air-handling units using Bayesian Inference and virtual sensing, Energy and Buildings. 250 (2021). https://doi.org/10.1016/j.enbuild.2021.111293. |
30 | J. Kim, S. Yoon, J. Koo, J. Bak, Y.S. Kim, TDC-based horizontal leakage area estimation in multiunit residential buildings: Three correction factors, Building and Environment. 192 (2021). https://doi.org/10.1016/j.buildenv.2021.107630. |
29 | Y. Choi, D. Song, S. Yoon, J. Koo, Comparison of factorial and latin hypercube sampling designs for meta-models of building heating and cooling loads, Energies (Basel). 14 (2021). https://doi.org/10.3390/en14020512. |
28 | R. Kim, Y. Hong, Y. Choi, S. Yoon, System-level fouling detection of district heating substations using virtual-sensor-assisted building automation system, Energy. 227 (2021). https://doi.org/10.1016/j.energy.2021.120515. |
27 | P. Wang, K. Han, R. Liang, L. MA, S. Yoon, The virtual in-situ calibration of various physical sensors in air handling units, Science and Technology for the Built Environment. 27 (2021) 691–713. https://doi.org/10.1080/23744731.2020.1798175. |
2020 Publications
26 | S. Yoon, D. Song, J. Kim, J. Kim, H. Lim, J. Koo, Identifying stack-driven indoor environmental problems and associated pressure difference in high-rise residential buildings: Airflow noise and draft, Building and Environment. 168 (2020). https://doi.org/10.1016/j.buildenv.2019.106483. |
25 | H. Lim, J. Seo, D. Song, S. Yoon, J. Kim, Interaction analysis of countermeasures for the stack effect in a high-rise office building, Building and Environment. 168 (2020). https://doi.org/10.1016/j.buildenv.2019.106530. |
24 | S. Yoon, In-situ sensor calibration in an operational air-handling unit coupling autoencoder and Bayesian inference, Energy and Buildings. 221 (2020). https://doi.org/10.1016/j.enbuild.2020.110026. |
23 | P. Wang, J. Li, S. Yoon, T. Zhao, Y. Yu, The detection and correction of various faulty sensors in a photovoltaic thermal heat pump system, Applied Thermal Engineering. 175 (2020). https://doi.org/10.1016/j.applthermaleng.2020.115347. |
22 | Y. Choi, S. Yoon, Virtual sensor-assisted in situ sensor calibration in operational HVAC systems, Building and Environment. 181 (2020). https://doi.org/10.1016/j.buildenv.2020.107079. |
21 | J. Bak, S. Yoon, D. Song, H. Lim, Y.S. Kim, Weather-driven infiltration and interzonal airflow in a multifamily high-rise building: Dwelling infiltration distribution, Building and Environment. 181 (2020). https://doi.org/10.1016/j.buildenv.2020.107098. |
20 | P. Wang, J. Li, S. Yoon, T. Zhao, Y. Yu, The detection and correction of various faulty sensors in a photovoltaic thermal heat pump system, Applied Thermal Engineering. 175 (2020). https://doi.org/10.1016/j.applthermaleng.2020.115347. |
19 | J. Li, T. Zhao, P. Wang, S. Yoon, Y. Yu, Effects of various partitions on the accuracy of virtual in-situ calibration in building energy systems, Journal of Building Engineering. 32 (2020). https://doi.org/10.1016/j.jobe.2020.101538. |
18 | S. Yoon, Y. Choi, J. Koo, Y. Hong, R. Kim, J. Kim, Virtual sensors for estimating district heating energy consumption under sensor absences in a residential building, Energies (Basel). 13 (2020). https://doi.org/10.3390/en13226013. |
2019 Publications
17 | S. Yoon, Y. Yu, J. Wang, P. Wang, Impacts of HVACR temperature sensor offsets on building energy performance and occupant thermal comfort, Building Simulation. 12 (2019) 259–271. https://doi.org/10.1007/s12273-018-0475-3. |
16 | P. Wang, S. Yoon, Y. Yu, Z. Shen, Experimental study on the active enhancement mechanisms of heat and mass transfer in an absorption chiller (RP-1462), Science and Technology for the Built Environment. 25 (2019) 58–68. https://doi.org/10.1080/23744731.2018.1498668. |
15 | J. Wang, Q. Zhang, S. Yoon, Y. Yu, Impact of uncertainties on the supervisory control performance of a hybrid cooling system in data center, Building and Environment. 148 (2019) 361–371. https://doi.org/10.1016/j.buildenv.2018.11.026. |
14 | J. Wang, Q. Zhang, S. Yoon, Y. Yu, Reliability and availability analysis of a hybrid cooling system with water-side economizer in data center, Building and Environment. 148 (2019) 405–416. https://doi.org/10.1016/j.buildenv.2018.11.021. |
13 | S. Yoon, D. Song, J. Kim, H. Lim, Stack-driven infiltration and heating load differences by floor in high-rise residential buildings, Building and Environment. 157 (2019) 366–379. https://doi.org/10.1016/j.buildenv.2019.05.006. |
12 | D. Song, S. Yoon, C. Jeong, J. Kim, H. Lim, Heat, vapor, and CO2 transportation caused by airflow in high-rise residential buildings, Building and Environment. 160 (2019). https://doi.org/10.1016/j.buildenv.2019.106176. |
11 | P. Wang, S. Yoon, J. Wang, Y. Yu, Automated reviving calibration strategy for virtual in-situ sensor calibration in building energy systems: Sensitivity coefficient optimization, Energy and Buildings. 198 (2019) 291–304. https://doi.org/10.1016/j.enbuild.2019.06.014. |
~2018 Publications
10 | J. Wang, Q. Zhang, Y. Yu, X. Chen, S. Yoon, Application of model-based control strategy to hybrid free cooling system with latent heat thermal energy storage for TBSs, Energy and Buildings. 167 (2018) 89–105. https://doi.org/10.1016/j.enbuild.2018.02.036. |
9 | Y. Wang, P. Wang, S. Yoon, Y. Yu, M. Bai, Characteristics of flow and heat transfer of nanofluids under laminar states, Numerical Heat Transfer; Part A: Applications. 73 (2018) 1–16. https://doi.org/10.1080/10407782.2017.1420298. |
8 | P. Wang, K. Han, S. Yoon, Y. Yu, M. Liu, The gas-liquid two-phase flow in reciprocating enclosure with piston cooling gallery application, International Journal of Thermal Sciences. 129 (2018) 73–82. https://doi.org/10.1016/j.ijthermalsci.2018.02.028. |
7 | S. Yoon, Y. Yu, Strategies for virtual in-situ sensor calibration in building energy systems, Energy and Buildings. 172 (2018) 22–34. https://doi.org/10.1016/j.enbuild.2018.04.043. |
6 | S. Yoon, Y. Yu, Hidden factors and handling strategy for accuracy of virtual in-situ sensor calibration in building energy systems: Sensitivity effect and reviving calibration, Energy and Buildings. 170 (2018) 217–228. https://doi.org/10.1016/j.enbuild.2018.04.017. |
5 | S. Yoon, Y. Yu, Hidden factors and handling strategies on virtual in-situ sensor calibration in building energy systems: Prior information and cancellation effect, Applied Energy. 212 (2018) 1069–1082. https://doi.org/10.1016/j.apenergy.2017.12.077. |
4 | S. Yoon, Y. Yu, A quantitative comparison of statistical and deterministic methods on virtual in-situ calibration in building systems, Building and Environment. 115 (2017) 54–66. https://doi.org/10.1016/j.buildenv.2017.01.013. |
3 | S. Yoon, Y. Yu, Extended virtual in-situ calibration method in building systems using Bayesian inference, Automation in Construction. 73 (2017) 20–30. https://doi.org/10.1016/j.autcon.2016.10.008. |
2 | W. Cho, D. Song, S. Hwang, S. Yun, Energy-efficient ventilation with air-cleaning mode and demand control in a multi-residential building, Energy and Buildings. 90 (2015) 6–14. https://doi.org/10.1016/j.enbuild.2015.01.002. |
1 | S. Yoon, J. Seo, W. Cho, D. Song, A calibration method for whole-building airflow simulation in high-rise residential buildings, Building and Environment. 85 (2015) 253–262. https://doi.org/10.1016/j.buildenv.2014.12.004. |
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