International Publications

2024 Publications

Num	Title
93	DT-BEMS: Digital twin-enabled building energy management system for building energy efficiency and operational informatics (working paper)
92	GPT-based intelligent digital twins for building operations and maintenance (working paper)
91	Nonintrusive in-situ modeling for unobserved virtual models in digital twin-enabled building HVAC systems: A one-year comparison of physics-based and data-driven approaches in a living laboratory (working paper)
90	Virtual in-situ calibration for building digital twins (working paper)
89	GPT-based Urban Building Energy Modeling (GPT-UBEM): Concept, Methodology, and Case Studies, Energy and Buildings (submitted)
88	AIM: Autonomous In-situ Modeling for Virtual Building Models in Digital Twins, Building and Environment (submitted)
87	Demonstrating the use of absolute pressure sensors for monitoring stack-driven pressure differences in high-rise buildings, Building and Environment (under review)
86	GPT-based building performance simulation and assessment: Ontology-assisted approach, Energy and Buildings (under review)
85	VIM: Virtual In-situ Modeling between Digital Twin and BIM for Advanced Building Operations and Maintenance, Automation in Construction (under review)
84	Multi-source data fusion-driven urban building energy modeling, Information Fusion (under review)
83	Metadata schema for virtual sensors in digital twin-enabled building systems using Brick schema, Applied Energy (under review)
82	Enhancing 1D Convolutional Neural Network for Fault Detection and Diagnosis of Fan Coil Unit Using Multiple Datasets and Models, Engineering Applications of Artificial Intelligence (submitted)
81	Research on the sensor fault diagnosis and abnormal data repair of environmental control system in a terminal, Journal of Building Engineering (under review)
80	In-situ sensor calibration and fault-tolerant building HVAC control: an EnergyPlus-Python co-simulation testbed, Building and Environment (under review)
79	A digital twin platform-based sensor fault prediction and reverse traceability approach for smart energy systems, Energy and Buildings (under review)
78	Enhancing In-situ model accuracy in building systems with augmentation-based synthetic operation data, Journal of Building Engineering (under review)
77	Sensor fault diagnosis and calibration based on voting mechanism for online application using virtual in-situ calibration and time series prediction, Building and Environment (under review)
76	Model fusion algorithms for digital twinning in built environments, Sustainable Cities and Society (under review)
75	J. Jing, K.H. Ji, S. Yoon, J.H. Jo, A novel method for evaluating stack pressure in real high-rise buildings: optimization of measurement points, Building and Environment 259 (2024) 111661. https://doi.org/10.1016/j.buildenv.2024.111661
74	VB Schema: Metadata schema for virtual building models in digital twins, Energy and Buildings (under review)
73	S. Yoon, Virtual Building Models in Built Environments, Developments in the Built Environment 18 (2024) 100453. https://doi.org/10.1016/j.dibe.2024.100453
72	G. Li, Y. Wu, S. Yoon*, X. Fang, Comprehensive transferability assessment of short-term cross-building-energy prediction using deep adversarial network transfer learning, Energy 299 (2024) 131395, https://doi.org/10.1016/j.energy.2024.131395
71	S. Choi, S. Yoon, Change-point model-based clustering for urban building energy analysis: A case study on electricity energy data in commercial buildings, Renewable and Sustainable Energy Reviews 199 114514, https://doi.org/10.1016/j.rser.2024.114514.
70	In-situ backup virtual sensor application in building automation systems toward virtual sensing-enabled digital twins, Case Studies in Thermal Engineering (submitted)
69	J. Wang, Y. Tian, Z. Qi, L. Zeng, P. Wang, S. Yoon, Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference, Building and Environment 249 (2024) 111124, https://doi-org-ssl.sa.skku.edu/10.1016/j.buildenv.2023.111124.
68	J. Li, P. Wang, Y. Li, Y. Rezgui, S. Yoon, T. Zhao, Analysis of sensor offset characteristics in building energy systems based on redundant sensors: A case study on variable air volume system, Energy and Buildings 306 (2024) 113957. https://doi.org/10.1016/j.enbuild.2024.113957
67	S. Choi, H. Lim, J. Lim, S. Yoon, Retrofit building energy performance evaluation using an energy signature-based symbolic hierarchical clustering method, Building and Environment 251 (2024) 111206. https://doi.org/10.1016/j.buildenv.2024.111206
66	S. Yoon, J. Lee, Perspective for waste upcycling-driven zero energy buildings, Energy 289 (2024) 130029, https://doi.org/10.1016/j.energy.2023.130029.
65	J. Koo, S. Yoon, Neural network-based nonintrusive calibration for an unobserved model in digital twin-enabled building operations, Automation in Construction 159 (2024). https://doi.org/10.1016/j.autcon.2023.105261
64	P. Wang, J. Sun, S. Yoon, L. Zhao, R. Liang, A global optimization method for data center air conditioning water systems based on predictive optimization control, Energy 295 (2024) 130925, https://doi.org/10.1016/j.energy.2024.130925
63	J. Koo, S. Yoon, Simultaneous in-situ calibration for physical and virtual sensors towards digital twin-enabled building operations, Advanced Engineering Informatics 59 (2024) 102239, https://doi.org/10.1016/j.aei.2023.102239

2022 Publications

Num.	Title
45	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
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.

2023 Publications

Num	Title
62	Y. Choi, S. Yoon, In-situ observation virtual sensor in building systems toward virtual sensing-enabled digital twins, Energy and Buildings (2023) 112766. https://doi.org/10.1016/j.enbuild.2022.112766
61	P. Wang, C.Li, M.N. Hossain, S. Yoon, L. Zhao, R. Liang, H. Guan, Research on designated calibration method of fault sensor in PVT heat pump system based on fault detection and virtual calibration, Journal of Building Engineering 76 (2023) 107237, https://doi.org/10.1016/j.jobe.2023.107237
60	R. Liang, C. Wang, P. Wang, S. Yoon, Realization of rule-based automated design for HVAC duct layout, Journal of Building Engineering 80 (2023) 107946, https://doi-org-ssl.sa.skku.edu/10.1016/j.jobe.2023.107946
59	J. Kim, S. Yoon, Virtual PMV sensor towards smart thermostats: Comparison of modeling approaches using intrusive data, Energy and Buildings 301 (2023) 113695, https://doi.org/10.1016/j.enbuild.2023.113695
58	Y. Choi, S. Yoon, Surrogate-assisted high-accuracy observation modeling in building digital twins: In situ modeling without sensor observation (Y), Building and Environment 242 (2023) 110584, https://doi.org/10.1016/j.buildenv.2023.110584
57	S. Yoon, J. Koo, In situ model fusion for building digital twinning, Building and Environment, Building and Environment 243 (2023) 110652, https://doi.org/10.1016/j.buildenv.2023.110652
56	J. Li, P. Wang, X. Han, T. Zhao, S. Yoon, Strategies for sensor virtual in-situ calibration in building energy system: Sensor evaluation and data-driven based method, Energy and Buildings 294 (2023) 113274, https://doi.org/10.1016/j.enbuild.2023.113274
55	S. Yoon, Building Digital Twinning: Data, Information, and Models, Journal of Building Engineering, Journal of Building Engineering (2023) 107021, https://doi.org/10.1016/j.jobe.2023.107021
54	P. Wang, C. Li, R. Liang, S. Yoon, S. Mu, Y. Liu, Fault detection and calibration for building energy system using Bayesian inference and sparse autoencoder: A case study in photovoltaic thermal heat pump system, Energy and Buildings 290 (2023) 113051, https://doi.org/10.1016/j.enbuild.2023.113051
53	S. Yoon, Y. Choi, J. Koo, In situ virtual sensors in building digital twins: framework and methodology, Journal of Industrial Information Integration 36 (2023) 100532, https://doi.org/10.1016/j.jii.2023.100532
52	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
51	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
50	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
49	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
48	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
47	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
46	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

2021 Publications

Num.	Title
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

Num.	Title
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

Num.	Title
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

Num.	Title
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.