Juhee Lee

Ms. Juhee Lee

orcid

Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 October 2025 in Agriculture
Verified
Journal Article
Open access
PDF file
JLJuhee Lee
Juhee Lee
SKSeokho Kang
Seokho Kang
YHYujin Han
Yujin Han
JSJinho Son
Jinho Son
YHYushin Ha
Yushin Ha
As the development of electric tractors progresses, battery systems have become a key component, accounting for a significant portion of the vehicle’s total weight. With rollover accidents remaining a leading cause of fatal injuries in agricultural machinery, the stability of electric tractors is drawing increasing attention. In particular, battery placement may critically affect the overall mass distribution and rollover behavior, highlighting the need for safety-focused design optimization. This study evaluates the static rollover stability of a 55 kW electric tractor by analyzing the effect of battery mounting position and comparing it with a conventional tractor. Three tractor models were considered: an electric tractor with a front-mounted battery, one with a center-mounted battery, and a conventional tractor. Multibody dynamic simulations were conducted using RecurDyn, and a total of 24 orientations, at 15° intervals, were simulated to determine the tipping angles in all directions. The results revealed that battery placement had a significant impact on rollover stability. The front-mounted battery type exhibited up to 30% higher tipping angles than the conventional tractor in the forward pitch direction near 90°, indicating improved stability. In contrast, the center-mounted battery type showed a tipping angle distribution generally similar to that of the conventional tractor, with smaller variations across directions. These findings demonstrate the influence of mass distribution on rollover safety and provide valuable insight for structural design of electric tractors.

23 February 2026 in Journal of Biosystems Engineering
Verified
Journal Article
Closed access
PDF file
JSJinho Son
Jinho Son
YHYujin Han
Yujin Han
HPHyung-Gyu Park
Hyung-Gyu Park
SKSeokho Kang
Seokho Kang
JLJuhee Lee
Juhee Lee
YHYushin Ha
Yushin Ha

9 September 2026 in Agriculture
Verified
Journal Article
Open access
PDF file
JSJinho Son
Jinho Son
YKYongsik Kwon
Yongsik Kwon
JJJihyeon Jung
Jihyeon Jung
SJSeongjun Jung
Seongjun Jung
JLJuhee Lee
Juhee Lee
YHYushin Ha
Yushin Ha
Garlic bulb yield formation depends on thermal-time availability, source–sink coordination, and field management, but their integrated effects under field-scale conditions remain unclear. This study evaluated garlic growth and final bulb weight (BW) during the 2024–2025 season across 26 field plots in Uiseong, Korea, using cumulative growing degree days (GDD), longitudinal canopy and bulb measurements, correlation analysis, PCA, and exploratory Random Forest (RF)-based variable importance. Delayed sowing reduced cumulative GDD at harvest by approximately 45 °C·d and was associated with lower final BW. Total plant weight (TPW) peaked around 692.2 °C·d, whereas BW continued to increase toward harvest, indicating temporal separation between whole-plant biomass accumulation and bulb filling. At harvest, BW was most strongly associated with bulb diameter (BD), while canopy traits showed weaker or stage-dependent relationships. RF analysis using the harvest-stage BW subset (n = 78) suggested that early canopy and structural traits, particularly LN, PH, SL, and SD, were associated with BW variance partitioning; however, importance values were interpreted as exploratory rankings rather than causal evidence. Overall, garlic bulb yield formation under the present field conditions appeared to be associated with thermal-time availability, sink morphology, early structural status, and localized management conditions; however, plot-level treatment comparisons did not detect significant independent treatment effects, indicating that these patterns should be interpreted as descriptive field-based trends.