Moon Keun Kim

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OsloMet – Oslo Metropolitan University

Norway

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About

Moon Keun Kim is a Professor at OsloMet – Oslo Metropolitan University in Norway. His research areas include advanced techniques for predicting electricity consumption in buildings, numerical analysis of transient burn injury grading, and the optimization of energy-saving measures in retrofitted buildings. He has published several articles focusing on artificial neural networks, hydraulic loss in centrifugal pumps, and ventilation system design to mitigate infection risks in hospital wards.

Recent Grants

Grant: Close

Mode Predictive Control for Grid-Tied Three-level Photovoltaic Inverters

Open Date: 2018-12-01

Close Date: 2022-12-01

Grant: Close

Modeling and Failure Mode Analysis of Power Electronics Devices

Open Date: 2018-01-01

Close Date: 2021-01-01

Grant: Close

Developing an energy building stock model for Jiangsu Province

Open Date: 2017-09-01

Close Date: 2020-08-01

Grant: Close

High-frequency-link DC Solid State Transformer For Flexible DC Distribution

Open Date: 2017-09-01

Close Date: 2020-08-01

Grant: Close

Novel Decentralized Ventilation System with a Hybrid Radiant Panel for Low Exergy and Zero Emission Architecture

Open Date: 2017-03-01

Close Date: 2020-02-01

Articles (15)

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2022

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2022

Collaborators (3)

Jelena Srebric

UNITED STATES

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Yang-Seon Kim

Assistant Professor

Wichita State University

UNITED STATES

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Stephen Sharples

University of Liverpool

UNITED KINGDOM

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Moon Keun Kim

Research Interests

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About

Recent Grants

Articles (15)

Advanced techniques for electricity consumption prediction in buildings using comparative correlation analysis, data normalization, and Long Short-Term Memory (LSTM) networks: A case study of a U.S. commercial building

Numerical Analysis of Transient Burn Injury Grading Through Coupled Heat Transfer and Damage Integral Modeling

Investigating the impact of data normalization methods on predicting electricity consumption in a building using different artificial neural network models

Predicting moisture condensation risk on the radiant cooling floor of an office using integration of a genetic algorithm-back-propagation neural network with sensitivity analysis

Investigating the reliability of estimating real-time air exchange rates in a building by using airborne particles, including PM1.0, PM2.5, and PM10: A case study in Suzhou, China

A Numerical Investigation of the Influence of Diffuser Vane Height on Hydraulic Loss in the Volute for a Centrifugal Water Supply Pump

Multi-objective optimization of energy-saving measures and operation parameters for a newly retrofitted building in future climate conditions: A case study of an office building in Chengdu

Application potential analysis of different control strategies for radiant floor cooling systems in office buildings in different climate zones of China

A Numerical Study on the Exergy Performance of a Hybrid Radiant Cooling System in an Office Building: Comparative Case Study and Analysis

Refined design of ventilation systems to mitigate infection risk in hospital wards: Perspective from ventilation openings setting

Dynamic prediction of the pre-dehumidification of a radiant floor cooling and displacement ventilation system based on computational fluid dynamics and a back-propagation neural network: A case study of an office room

Experimental and numerical analysis of indoor air quality affected by outdoor air particulate levels (PM1.0, PM2.5 and PM10), room infiltration rate, and occupants' behaviour

A review of human thermal plume and its influence on the inhalation exposure to particulate matter

Developing a collaborative control strategy of a combined radiant floor cooling and ventilation system: A PMV-based model

Prediction and correlation analysis of ventilation performance in a residential building using artificial neural network models based on data-driven analysis

Collaborators (3)

Jelena Srebric

Yang-Seon Kim

Stephen Sharples

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