Jinhwan Kim

Mr. Jinhwan Kim

Korea Advanced Institute of Science and Technology (KAIST)
orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

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

Representative Publications

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1 May 2019 in Applied Radiation and Isotopes
Verified
Journal Article
Closed access
JKJinhwan Kim
Jinhwan Kim
KPKyeongjin Park
Kyeongjin Park
GCGyuseong Cho
Gyuseong Cho

1 November 2019 in Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Verified
Journal Article
Closed access
JKJinhwan Kim
Jinhwan Kim
KLKyung Taek Lim
Kyung Taek Lim
JKJunhyeok Kim
Junhyeok Kim
CKChang-Jong Kim
Chang-Jong Kim
BJByoungil Jeon
Byoungil Jeon
GCGyuseong Cho
Gyuseong Cho

1 December 2019 in Nuclear Engineering and Technology
Verified
Journal Article
Open access
KPKyeongjin Park
Kyeongjin Park
JKJinhwan Kim
Jinhwan Kim
KLKyung Taek Lim
Kyung Taek Lim
JKJunhyeok Kim
Junhyeok Kim
HCHojong Chang
Hojong Chang
GCGyuseong Cho
Gyuseong Cho

1 July 2019 in Nuclear Engineering and Technology
Verified
Journal Article
Open access
JKJunhyeok Kim
Junhyeok Kim
KPKyeongjin Park
Kyeongjin Park
JHJisung Hwang
Jisung Hwang
HKHojik Kim
Hojik Kim
JKJinhwan Kim
Jinhwan Kim
GCGyuseong Cho
Gyuseong Cho

19 May 2020 in Sensors
Verified
Journal Article
Open access
PDF file
JKJinhwan Kim
Jinhwan Kim
KLKyung Taek Lim
Kyung Taek Lim
KPKyeongjin Park
Kyeongjin Park
YKYewon Kim
Yewon Kim
GCGyuseong Cho
Gyuseong Cho
Major standard organizations have addressed the issue of reporting uncertainties in dose rate estimations. There are, however, challenges in estimating uncertainties when the radiation environment is considered, especially in real-time dosimetry. This study reports on the implementation of Gaussian process regression based on a spectrum-to-dose conversion operator (i.e., G(E) function), the aim of which is to deal with uncertainty in dose rate estimation based on various irradiation geometries. Results show that the proposed approach provides the dose rate estimation as a probability distribution in a single measurement, thereby increasing its real-time applications. In particular, under various irradiation geometries, the mean values of the dose rate were closer to the true values than the point estimates calculated by a G(E) function obtained from the anterior–posterior irradiation geometry that is intended to provide conservative estimates. In most cases, the 95% confidence intervals of uncertainties included those conservative estimates and the true values over the range of 50–3000 keV. The proposed method, therefore, not only conforms to the concept of operational quantities (i.e., conservative estimates) but also provides more reliable results.

5 December 2019 in Sensors
Verified
Journal Article
Open access
PDF file
JKJinhwan Kim
Jinhwan Kim
KLKyung Taek Lim
Kyung Taek Lim
KPKyeongjin Park
Kyeongjin Park
GCGyuseong Cho
Gyuseong Cho
This study reports on the implementation of Bayesian inference to improve the estimation of remote-depth profiling for low-level radioactive contaminants with a low-resolution NaI(Tl) detector. In particular, we demonstrate that this approach offers results that are more reliable because it provides a mean value with a 95% credible interval by determining the probability distributions of the burial depth and activity of a radioisotope in a single measurement. To evaluate the proposed method, the simulation was compared with experimental measurements. The simulation showed that the proposed method was able to detect the depth of a Cs-137 point source buried below 60 cm in sand, with a 95% credible interval. The experiment also showed that the maximum detectable depths for weakly active 0.94-μCi Cs-137 and 0.69-μCi Co-60 sources buried in sand was 21 cm, providing an improved performance compared to existing methods. In addition, the maximum detectable depths hardly degraded, even with a reduced acquisition time of less than 60 s or with gain-shift effects; therefore, the proposed method is appropriate for the accurate and rapid non-intrusive localization of buried low-level radioactive contaminants during in situ measurement.