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Your search keyword '"Hwang, In-Guk"' showing total 251 results
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251 results on '"Hwang, In-Guk"'

3. The Immune-Stimulating and Anti-Diabetic Effects of Allium hookeri Leaves Grown in a Plant Factory with Artificial Lights in Immunosuppressed Obese C57BL/6 Mice

Author

Jung, Jieun, primary, Kim, Ji-Su, additional, Jeong, Un-Yul, additional, Bae, Ui-Jin, additional, Kim, Mina, additional, Park, Shin-Young, additional, Hwang, In-Guk, additional, Heo, Jeong-Wook, additional, Shim, Chang-Ki, additional, Ham, Jun-Sang, additional, and Lee, Sung-Hyen, additional

Published
2024
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5. Artificial Neural Network Modeling to Predict Thermal and Electrical Performances of Batteries with Direct Oil Cooling.

Author

Garud, Kunal Sandip, Han, Jeong-Woo, Hwang, Seong-Guk, and Lee, Moo-Yeon

Subjects
ELECTRIC batteries, HEAT transfer coefficient, THERMAL batteries, DATABASE design, PETROLEUM, ARTIFICIAL neural networks
Abstract

The limitations of existing commercial indirect liquid cooling have drawn attention to direct liquid cooling for battery thermal management in next-generation electric vehicles. To commercialize direct liquid cooling for battery thermal management, an extensive database reflecting performance and operating parameters needs to be established. The development of prediction models could generate this reference database to design an effective cooling system with the least experimental effort. In the present work, artificial neural network (ANN) modeling is demonstrated to predict the thermal and electrical performances of batteries with direct oil cooling based on various operating conditions. The experiments are conducted on an 18650 battery module with direct oil cooling to generate the learning data for the development of neural network models. The neural network models are developed considering oil temperature, oil flow rate, and discharge rate as the input operating conditions and maximum temperature, temperature difference, heat transfer coefficient, and voltage as the output thermal and electrical performances. The proposed neural network models comprise two algorithms, the Levenberg–Marquardt (LM) training variant with the Tangential-Sigmoidal (Tan-Sig) transfer function and that with the Logarithmic-Sigmoidal (Log-Sig) transfer function. The ANN_LM-Tan algorithm with a structure of 3-10-10-4 shows accurate prediction of thermal and electrical performances under all operating conditions compared to the ANN_LM-Log algorithm with the same structure. The maximum prediction errors for the ANN_LM-Tan and ANN_LM-Log algorithms are restricted within ±0.97% and ±4.81%, respectively, considering all input and output parameters. The ANN_LM-Tan algorithm is suggested to accurately predict the thermal and electrical performances of batteries with direct oil cooling based on a maximum determination coefficient (R2) and variance coefficient (COV) of 0.99 and 1.65, respectively. [ABSTRACT FROM AUTHOR]

Published
2023
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13. A Review of Advanced Cooling Strategies for Battery Thermal Management Systems in Electric Vehicles.

Author

Garud, Kunal Sandip, Tai, Le Duc, Hwang, Seong-Guk, Nguyen, Nghia-Huu, and Lee, Moo-Yeon

Subjects
BATTERY management systems, PHASE transitions, PHASE change materials, THERMAL batteries, LITHIUM-ion batteries
Abstract

Electric vehicles (EVs) offer a potential solution to face the global energy crisis and climate change issues in the transportation sector. Currently, lithium-ion (Li-ion) batteries have gained popularity as a source of energy in EVs, owing to several benefits including higher power density. To compete with internal combustion (IC) engine vehicles, the capacity of Li-ion batteries is continuously increasing to improve the efficiency and reliability of EVs. The performance characteristics and safe operations of Li-ion batteries depend on their operating temperature which demands the effective thermal management of Li-ion batteries. The commercially employed cooling strategies have several obstructions to enable the desired thermal management of high-power density batteries with allowable maximum temperature and symmetrical temperature distribution. The efforts are striving in the direction of searching for advanced cooling strategies which could eliminate the limitations of current cooling strategies and be employed in next-generation battery thermal management systems. The present review summarizes numerous research studies that explore advanced cooling strategies for battery thermal management in EVs. Research studies on phase change material cooling and direct liquid cooling for battery thermal management are comprehensively reviewed over the time period of 2018–2023. This review discusses the various experimental and numerical works executed to date on battery thermal management based on the aforementioned cooling strategies. Considering the practical feasibility and drawbacks of phase change material cooling, the focus of the present review is tilted toward the explanation of current research works on direct liquid cooling as an emerging battery thermal management technique. Direct liquid cooling has the potential to achieve the desired battery performance under normal as well as extreme operating conditions. However, extensive research still needs to be executed to commercialize direct liquid cooling as an advanced battery thermal management technique in EVs. The present review would be referred to as one that gives concrete direction in the search for a suitable advanced cooling strategy for battery thermal management in the next generation of EVs. [ABSTRACT FROM AUTHOR]

Published
2023
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18. Frankle-McCann Retinex by Shuffling

Author

Hwang, Dong-Guk, Lee, Woo-Ram, Oh, Young-Jin, Jun, Byoung-Min, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Lee, Geuk, editor, Howard, Daniel, editor, Kang, Jeong Jin, editor, and Ślęzak, Dominik, editor

Published
2012
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22. Design of a Reversible PLD Architecture

Author

Lee, Jae-Jin, Hwang, Dong-Guk, Song, Gi-Yong, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Rangan, C. Pandu, editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Diniz, Pedro C., editor, Marques, Eduardo, editor, Bertels, Koen, editor, Fernandes, Marcio Merino, editor, and Cardoso, João M. P., editor

Published
2007
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47. Platycodon grandiflorum Extract Ameliorates Cyclophosphamide-Induced Immunosuppression in Mice

Author

Lee, Eun Byeol, primary, Lee, Sung Hyen, additional, Park, Yang-Gyu, additional, Choi, Ji-Hye, additional, Lee, Hye Kyung, additional, Jang, Hwan Hee, additional, Hwang, Gyeong-A, additional, Choe, Jung-Suk, additional, Park, Shin Young, additional, Choi, Ae Jin, additional, Hwang, In Guk, additional, Kim, Ji Soo, additional, Lee, Hae Jeung, additional, Lee, Sung-Jin, additional, and Jeong, Hyun-Cheol, additional

Published
2019
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