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Sung Min Yoon

Sungkyunkwan University · 工学

研究室紹介

Professor Sung Min Yoon's research lab specializes in digital twin technologies and virtual sensing for intelligent, energy-efficient building operations across the entire building life cycle. The lab focuses on developing in situ model fusion techniques, digital twin frameworks, and advanced sensing methodologies tailored to the unique challenges of the building industry. Research also extends to sustainable construction materials, such as coal combustion by-products, and their performance in civil infrastructure. The lab integrates data-driven modeling, embedded sensing, and smart system design to enable real-time monitoring, calibration, and optimization of built environments.

digital twinvirtual sensingbuilding life cyclesustainable materialsmodel fusion

Research Overview

Papers
169
Total Citations
2,663
Papers (5y)
99
Primary Field
工学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
99total
2022
2023
2024
2025
2026
Citations per year (5y)
1,171total
20222023202420252026

Selected Papers

15
1
Article|80 citations·2016
Extended virtual in-situ calibration method in building systems using Bayesian inference
Sungmin Yoon, Yuebin Yu
SJR Q1Automation in Construction
Control and Systems EngineeringEngineering
2
Article|77 citations·2021
Autoencoder-driven fault detection and diagnosis in building automation systems: Residual-based and latent space-based approaches
Youngwoong Choi, Sungmin Yoon
SJR Q1Building and Environment
Control and Systems EngineeringEngineering
3
Article|74 citations·2023
Building digital twinning: Data, information, and models
Sungmin Yoon
SJR Q1Journal of Building EngineeringOA

This study proposes a novel framework and methodology for building digital twinning (BDT) over the life cycle of a building. It aims to establish an intrinsic digital twin framework and methodology in the building sector, considering the inherent characteristics of the building industry compared with other industries, such as manufacturing. Thus, the framework includes digital twin elements, functional requirements, and enabling techniques and provides in-depth insight into the implementation of

Industrial and Manufacturing EngineeringEngineering
4
Article|70 citations·2022
Virtual sensing in intelligent buildings and digitalization
Sungmin Yoon
SJR Q1Automation in ConstructionOA

Virtual sensing technologies have a huge potential in an informative and reliable sensing environment, which is essential to provide and maintain intelligent services in building life-cycle and digitalization. However, there remains a lack of comprehensive literature reviews and suggestions regarding virtual sensing applications in the building sector. The existing virtual sensing classification affords limited insight into virtual sensor modeling, verification, and calibration in building opera

Building and ConstructionEngineering
5
Article|60 citations·2018
Impacts of HVACR temperature sensor offsets on building energy performance and occupant thermal comfort
Sungmin Yoon, Yuebin Yu, Jiaqiang Wang, Peng Wang
SJR Q1Building Simulation
Building and ConstructionEngineering
6
Article|55 citations·2019
Stack-driven infiltration and heating load differences by floor in high-rise residential buildings
Sungmin Yoon, Doosam Song, Joowook Kim, Hyunwoo Lim
SJR Q1Building and Environment
Building and ConstructionEngineering
7
Article|54 citations·2018
Hidden factors and handling strategies on virtual in-situ sensor calibration in building energy systems: Prior information and cancellation effect
Sungmin Yoon, Yuebin Yu
SJR Q1Applied Energy
Building and ConstructionEngineering
8
Article|52 citations·2021
System-level fouling detection of district heating substations using virtual-sensor-assisted building automation system
Ryunhee Kim, Yejin Hong, Youngwoong Choi, Sungmin Yoon
SJR Q1Energy
Building and ConstructionEngineering
9
Article|51 citations·2020
In-situ sensor calibration in an operational air-handling unit coupling autoencoder and Bayesian inference
Sungmin Yoon
SJR Q1Energy and Buildings
Building and ConstructionEngineering
10
Article|49 citations·2020
Virtual sensor-assisted in situ sensor calibration in operational HVAC systems
Youngwoong Choi, Sungmin Yoon
SJR Q1Building and Environment
Building and ConstructionEngineering
11
Article|47 citations·2018
Strategies for virtual in-situ sensor calibration in building energy systems
Sungmin Yoon, Yuebin Yu
SJR Q1Energy and Buildings
Building and ConstructionEngineering
12
Article|46 citations·2014
A calibration method for whole-building airflow simulation in high-rise residential buildings
Sungmin Yoon, Jungmin Seo, Wanghee Cho, Doosam Song
SJR Q1Building and Environment
Environmental EngineeringEnvironmental Science
13
Article|46 citations·2022
In-situ sensor virtualization and calibration in building systems
Jabeom Koo, Sungmin Yoon
SJR Q1Applied Energy
Building and ConstructionEngineering
14
Article|43 citations·2021
System-level virtual sensing method in building energy systems using autoencoder: Under the limited sensors and operational datasets
Yejin Hong, Sungmin Yoon, Yong-Shik Kim, Hyang-In Jang
SJR Q1Applied Energy
Building and ConstructionEngineering
15
Review|41 citations·2023
In situ modeling methodologies in building operation: A review
Sungmin Yoon
SJR Q1Building and Environment
Building and ConstructionEngineering

Research Areas

Building and ConstructionIndustrial and Manufacturing EngineeringBiomedical EngineeringCivil and Structural EngineeringElectrical and Electronic EngineeringMechanical Engineering

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