Sunglok Do

Assistant Professor

Hanbat National University

South Korea

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About

Dr. Sunglok Do is an Assistant Professor at Hanbat National University in South Korea. His research primarily focuses on energy efficiency and control systems in HVAC applications, data center cooling, and innovative manufacturing technologies such as 3D printing. Recent publications include studies on economizer control optimization, fault detection in chilled water systems, and facility condition monitoring techniques.

Articles (13)

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2025

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2025

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2024

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2023

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2022

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2022

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2022

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2022

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2022

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2021

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2021

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2021

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2021

Collaborators (3)

Donghoon Lee

Hanbat National University

SOUTH KOREA

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Sungjin Kim

Assistant Professor

Hanbat National University

SOUTH KOREA

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Heejin Cho

Professor

University of Nevada

UNITED STATES

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Sunglok Do

Research Interests

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About

Articles (13)

Determining the Outdoor Air Intake Dry-Bulb Temperature Range for Economizer Applications in Data Centers

Optimized Economizer Control with Maximum Limit Set-Point to Enhance Cooling Energy Performance in Korean Climate

Development of Virtual Sensor Based on LSTM-Autoencoder to Detect Faults in Supply Chilled Water Temperature Sensor

Development of Free-Form Assembly-Type Mold Production Technology Using 3D Printing Technology

A Synthetic Review of UAS-Based Facility Condition Monitoring

An Analytical Study of the Latest Trends of Free-Form Molds

Energy Modeling and Model Predictive Control for HVAC in Buildings: A Review of Current Research Trends

Indoor Thermal Environment and Energy Characteristics with Varying Cooling System Capacity and Restart Time

Development of Flow-Based Heating Supply Water Temperature Control for Apartment Building Using District Heating System

Development of Key Performance Indicators for Measuring the Management Performance of Small Construction Firms in Korea

Evaluation of Building Energy Performance with Optimal Control of Movable Shading Device Integrated with PV System

In Situ Evaluation of the U-Value of a Window Using the Infrared Method

Prediction Performance Analysis of Artificial Neural Network Model by Input Variable Combination for Residential Heating Loads

Collaborators (3)

Donghoon Lee

Sungjin Kim

Heejin Cho

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