A detailed design for a radioactive waste safety management system using ICT technologies

Progress in Nuclear Energy 149 (2022) 104251

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Progress in Nuclear Energy
journal homepage: www.elsevier.com/locate/pnucene

A detailed design for a radioactive waste safety management system using
ICT technologies
Hee-Seoung Park *, Sung-Chan Jang, Il-Sik Kang, Dong-Ju Lee, Jeong-Guk Kim, Jin-Woo Lee
Radwaste Management Center, Korea Atomic Energy Research Institute (KAERI), 111, Daedeok-daero, 989beon-gil, Yuseung-gu, Daejon, 34057, Republic of Korea

A R T I C L E I N F O

A B S T R A C T

Keywords:
Radioactive waste safety management
Radioactive waste repackaged drums
Small-packaged waste
Digital twin
Augmented reality
Internet of things

A Radioactive Waste Information Management System (RAWINGS) currently in operation mainly manages the
inventory and history of the operating waste. The system has the disadvantages of the entered information
needing to be transferred manually from the site to the system, information getting incorrectly entered during the
process or information going missing. Recently, the Nuclear Safety and Security Commission (NSSC) and Korea
Radioactive Waste Agency (KORAD) called for the development of a digital system that can show information
transparently in real-time regarding the preliminary inspections of RAdioactive Waste (RAW) and the assessment
of its suitability for disposal before the radioactive waste is delivered to the disposal site. A Digital Twin (DT)

system is being developed for the safety management of radioactive waste to address the problems that these
systems have and meet the needs of disposal operators. This paper introduces the DT technology that uses
Augmented Reality (AR) technology enabling users to check the contents of small-packaged wastes in radioactive
waste drums without opening them, Internet of Things (IoT) sensor technology that checks the status of the
drums in the radioactive waste storage and the RAWINGS system. Based on the performance of a prototype
Digital Twin consisting of three modules (AR, IoT and RAWINGS), the augmented reality enables users to see the
shape information and filling rate of small-packaged wastes in the radioactive waste drums and includes Quick
Response (QR) code management. The basic data of the radioactive waste used in the augmented reality, as well
as small packaged wastes and repackaged drums, were processed in conjunction with RAWINGS. In addition,
real-time monitoring of radioactive waste drums loaded in the designated space (Y zone: an area where
combustible waste is loaded within radioactive waste storage and TEST area: a section where drums scheduled to
be transported to the disposal site are loaded) of the radioactive waste storage was possible by transmitting IoT
sensor signals attached to the drum to the digital twin. Currently, augmented reality has an important role in
enhancing the visibility and intuitiveness of radioactive waste information for radioactive waste managers and
workers by overlapping digital information about radioactive waste storage. Due to the nature of radioactive
waste, it is difficult to know what waste is inside the enclosed drum. However, the results of this study confirmed
that waste contained in radioactive waste drums can be identified in real time in the Digital Twin rather than in
the radioactive waste storage.
This technology will be useful in determining the conformity of the radioactive waste acceptance criteria
required by KORAD before the delivery of radioactive waste drums to disposal sites.

1. Introduction
The radioactive waste information management system operated by
Korea Atomic Energy Research Institute (KAERI) manages the inventory
and history of dismantled/operated waste. Data may be incorrectly
entered or omitted when transferring information manually entered in
the field to the system. Because it mainly serves as a database, there is a
limit to the safety management of radioactive waste. In addition, when

supervisors from regulatory bodies and agencies check the waste in the

radioactive waste drum, they open the radioactive waste drum and
inspect the waste one by one. In particular, checking the presence or
absence of waste in a radioactive waste drum that has been stored for a
long time takes a lot of time. Moreover, it increases the stress of field
workers, thereby degrading the quality of the radioactive waste man­
agement work. To overcome these limitations, this paper describes the
safety management technology of radioactive waste using the major

* Corresponding author.
E-mail address: (H.-S. Park).
/>Received 17 September 2021; Received in revised form 18 April 2022; Accepted 25 April 2022
Available online 13 May 2022
0149-1970/© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( />

H.-S. Park et al.

Progress in Nuclear Energy 149 (2022) 104251

technologies of the Fourth Industrial Revolution (AR, IoT and DT). The
AR is a technology that enables users to check small-packaged wastes in
drums without opening the sealed radioactive waste drums. To this end,
each small-packaged waste should be classified by QR codes according
to the waste classification standard table, and the information already
registered can be checked through augmented reality technology by
recognizing the attached QR code. The IoT technology enables safety
management through real-time monitoring and tracking of radioactive
waste drums.
The DT technology enables the detection and prediction of abnor­
malities in the radioactive waste drums through various disaster sce­
narios. To this end, the IoT sensor data are received in real-time. As a

result, the abnormal status of radioactive waste drums is checked while
simulating them according to response scenarios to solve obstacles to
radioactive waste safety management. Through linked database systems
with major technologies such as AR, IoT, and Digital Twin, it was
confirmed that QR codes for small-packaged wastes in drums could be
generated and managed through augmented reality in a Digital Twin
environment. Basic data used in the AR and IoT (the original drum of
radioactive waste and small-packaged waste and repackaged drums)
were processed by interconnection with the legacy system. In addition,
monitoring the condition of the radioactive waste drums loaded in the
designated space for radioactive waste storage (1 actual space and 1
TEST area) was possible by transmitting data from the IoT sensors
attached to the drums to the digital twins.
If this study establishes a web-based system for all drums loaded in
storage, regulators, disposal operators, and radioactive waste managers
could manage radioactive waste safely and effectively checking the
storage conditions, location and loading history of the radioactive waste
drums in real-time. Because the Digital Twin system for the safety
management of radioactive waste is operated in real-time, it can resolve
any information imbalance between in-situ supervisors and managers
and the loading amount and details of the radioactive waste drum. In
addition, the status condition of the repacked drum (temperature/hu­
midity, whether the lid is opened or not, etc.) can be checked; thus, it is
expected to be used as a useful tool to improve the operation and process
of radioactive waste in the future.

states, etc.) or known limitations of the model (e.g., due to assumptions
like linearity) (Brendan Kochunass et al., 2021). There is a study that
proposed a method of supporting decommissioning operations in Nu­
clear Power Plant (NPP) using augmented reality. Using a stylus pen,

this technology has the advantage of being easier and more effective
than that of the legacy recording method (Hirotake ISHII et al., 2014).
Argonne National Laboratory (ANL) demonstrated applications of AR
techniques for performing telerobotic operations in hazardous envi­
ronments, such as radioactive waste facilities and dismantling sites
(Young Soo Park et al., 2017). Kyoto university developed a distance
information display system based on AR. The system automatically
measures the lengths and gaps of structures by capturing the target
objects with an RGB-D camera (Naoya Miki et al., 2018). To improve the
efficiency of the maintenance work and reduce human errors for a do­
mestic Japanese design for a demonstration Advanced Thermal Reactor
(FUGEN), a prototype AR system was developed (Hiroshi Shimoda et al.,
2005). International Atomic Energy Agency (IAEA) has been considered
a development of Digital Twin to manage the issues associated with the
lifetime of NPPs in terms of aging management and Life Time Man­
agement (LTM) (Alexander et al., 2020). A multidisciplinary team (the
University of Michigan, Idaho National Laboratory and Argonne Na­
tional Laboratory, and Kairos Power and Curtiss-Wright) is developing
digital twins of nuclear reactors to support flexible operations of a NPP
by using an ML-driven Digital Twin that can help understand a complex
operating environment (Poornima Apte, 2021). The development of a
virtual digital NPP and Digital Twin based on optimal control theory,
fuzzy logic and machine learning in the nuclear industry can not only
predict the state of the technological equipment but also solve the
problem of parameter tuning of automatic regulators in the different
operating modes of a NPP unit (V.S. Volodin, 2019). Siemens gave ex­
amples of Digital Twin technology that is not only useful in the design
phase but also can evolve alongside the physical reactor throughout its
operational lifetime. This technology also can be used to control pre­
dictive maintenance and develop full model-based detection systems.

The Digital Twin is the only solution that can eliminate the enormous
cost of full-scale testing (Stephen Ferguson, 2020). PRE-DISposal man­
agement of radioactive waste (PREDIS: the objective of the PREDIS-WP7
project on “Innovations in cemented waste handling and pre-disposal
storage” is understanding and tracking the State of The Art (SoTA) of
current methods and procedures used for cemented waste management
with specific focus on monitoring during long-term storage) introduces
the representation of a cemented radioactive waste package using a
Digital Twin based on machine-learning algorithms and neural networks
which will be trained with data produced by numerical tools for
geochemical and mechanical integrity modelling (Stefania Uras, 2021).

2. Related works
There is an example of a Digital Twin platform as a strategy for
digitization to study the dynamic simulation of thermal processes in
nuclear power plants. That study explored the requirements and ad­
vantages of performing dynamic simulations in real-time on the Digital
Twin platform (JOKELAINEN Miikka et al., 2018). AR research is
actively underway in the nuclear industry as a way to reduce working
hours and human error. In particular, research confirms that this tech­
nology is superior to existing technologies in maintenance support, ra­
diation visualization, and decommissioning support (ISHII, 2010). The
Worksite Visualization System (WVS), which is a part of DEXUS
(Decommissioning Engineering Support System to help planning of the
optimal dismantling process and for carrying out the dismantling work
safely and efficiently), describes AR as a technology that enables field
workers to process information about decommissioning facilities easily
and intuitively (IZUMI Masanori et al., 2010). In the CHERNOBYL NPPs,
requirement analysis and possibilities related to Computational Fluid
Dynamic (CFD) monitoring developed to analyze, predict and control

radiation states are addressed using DT (P.G. Krukovskyi et al., 2020).
Even though the application of DT in the nuclear field is appropriate for
nuclear systems, there are still many aspects that are insufficient. As a
study to overcome this, the incorporation of the uncertainty quantifi­
cation (UQ) and forward UQ was proposed enabling the propagation of
the uncertainty from the digital representation to predict the behavior of
the physical asset. Uncertainties present in physical assets are found in
changes in the model coefficients due to physical asset’s natural evo­
lution of the physical asset (e.g., burnup, lower power states, high power

3. Prototyping of the RAW safety management technology
3.1. Digital twin of RAW
3.1.1. Definition of the digital twin and benefits
Digital Twin technology can achieve safe management of radioactive
waste through various simulations of the operation status of the radio­
active waste storage facility in a virtual storage facility identical to the
real one. The basic elements for implementing a Digital Twin are as
follows:
- Simulation: All the physics models that define the product/simulate
operations/reconfigure system and test using DT
- IoT: Monitor the systems of the physical product via physical data/
pressure conditions, temperatures, component stress/use of algo­
rithms to make reasonable projections about the future
- Visualization: Dashboard/Augmented Reality
Digital Twin Benefits and Use Cases are as follows:

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Progress in Nuclear Energy 149 (2022) 104251

server manages input values (information for original drum, smallpackaged waste and repackaged drums) and IoT sensor values (tem­
perature, humidity and opening/closing of the lid) received on the
Digital Twin and the data values transmitted from RAWINGS. Field
workers at radioactive waste storage sites can directly input the details
of the radioactive waste treatment (data on small-packaged waste and
repackaged drums) in-situ using augmented reality applications. Infor­
mation on radioactive wastes entered in this way can intuitively identify
the contents of new registrations and the revision history of radioactive
wastes in the digital twins.

Smart connected products
Virtual Prototyping
Continuous data-driven optimization
Real-world usage/conditions data
Predictive models
Reduce downtime and maintenance costs

3.1.2. Configuration of the digital twin
To reflect the real-time status of radioactive waste in the digital twin,
the storage and drums are organized into component layouts of the 3D
model. The WebClient screen improves the page rendering speed and
reduces the server load by improving the simultaneous processing per­
formance with the Web server. The advantage of WebClient Screen is
that it does not require additional software installation on the client PC
for digital twin use and that it can refer to open-source materials and

source codes when improving features related to page rendering and
concurrent processing. It is also designed to map the current location of
the storage and drum to the coordinate value to monitor the condition of
the drum with an IoT sensor (tracking history according to the current
loading location and taking out situations). Radioactive waste Digital
Twin includes AR technology and IoT technology in a virtual environ­
ment shown in Fig. 1. The radioactive waste is transported to the
disposal site as procedures;

3.2. Augmented reality for the RAW and QR code
Augmented reality has been used in various fields (manufacturing,
logistics, management, medical care, broadcasting, gaming, advertising,
etc.) by providing a large amount of digital data in the actual environ­
ment that users are seeing, enabling them to acquire intuitive
information.
The method of identifying radioactive wastes using QR codes was
designed so that tablet PCs can read the radioactive waste data entered
into the server when they recognize the QR codes attached to small
packages and repackaged drums. Fig. 2 shows the generation and
registration procedures for the QR codes as follows: 1) QR codes are
tagged to register the drum information; 2) small-packaged waste codes
that have been registered are tagged, and 3) radioactive waste infor­
mation (repackaged drums and small-packaged drums information) is
checked using tablet PCs. Google’s AR Core was used to obtain location
information after QR code recognition and augment information in that
location. In addition, QR codes can be generated and printed on QR
management pages on the Digital Twin web pages, and radioactive
waste information can be checked by linking them in real-time. Because
QR codes can be checked on the QR management page of the digital
twins at any time, QR codes for management can be printed and used

even if QR codes are damaged in-situ. DT designed the repackaged drum
number of the RAWINGS system to match the QR code used in the
Digital Twin and augmented the reality programs, and specific data
properties are as follows:

- The radioactive waste that is generated from nuclear fuel facilities
and laboratories has been collected and managed history through insitu inspection.
- A small-packaged waste, a requirement of the Korea Institute of
Nuclear Safety (KINS) is to be treated as small packaging after being
selected as waste with the same characteristics based on the gener­
ation history.
- A reclassified disposal drum is loaded into the temporary storage
after identifying the characteristics of the waste package, radionu­
clides, and radioactive concentrations.
- When the Korea Atomic Energy Research Institute submits data
related to the disposal of radioactive waste to KORAD, the KORAD
determines the suitability of the disposal after a preliminary
inspection.
- The waste disposal drum, which has been judged to be suitable, is
loaded into a container and transported to a cave disposal site of the
KORAD.

- Original drum information: Number, Date of generation, Facility of
generation, Surface Dose Rate, Loading Position, Major Nuclide
- Waste information of the small-packaged waste: Number, Packaged
drums or Repackaged Drums, Weight, Contents, Amount of repre­
sentative specimen quantity (g)
- Drum information of the repackaged Drums: Number (linked with
QR code), Facility of generation, Date of generation, Date of Work,
Contents, Drum or special Drum, Surface Dose Rate (μSv/h), Dose

Rate by 1 m (μSv/h), Date of measured, Drum (L), Weight (kg),
Loading Position, Amount of representative specimen quantity (g),

3.1.3. Digital twin server system
The Digital Twin system was designed to operate as a data server and
web server. Web servers operating on a single-threaded event loopbased asynchronous (Non-Blocking I/O) are relatively fast platforms
associated with web clients using JavaScript languages and have the
advantage of expanding web servers into clusters as needed. The data

Fig. 1. Configuration of RAW Digital Twin includes AR and IoT.
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Progress in Nuclear Energy 149 (2022) 104251

Fig. 2. The procedures of generation and registration for QR codes.

Major Nuclide, Sensor ID (Linked with IoT sensor), Zone (Linked
with IoT sensor) Augmented.

area of the waste storage is transmitted to the Digital Twin system
and the status information of the drums is monitored in real-time.

3.3. IoT for RAW

IoT sensors attached to radioactive waste drums are designed to
minimize the impact of drum transport and operation and maximize the
radio communication performance. Fig. 3 shows the prototype geometry

of the radioactive waste drum IoT, and the following requirements were
considered.

3.3.1. Definition of IoT and functionality
The dictionary definition of IoT is an object-space connection
network that forms intelligent relationships such as sensing, networking,
and information processing in cooperation with humans, objects, and
services in three distributed environment elements without human
intervention. IoT technology is required to minimize inconsistency and
human error in drum position information due to frequent changes in
loading position due to reclassification of waste drums.
To improve the difficulties of such radioactive waste storage, the IoT
technology introduced in this study was designed to have the following
specialized characteristics:

(1) Positioning the sensor in the center of the radioactive waste drum
screw
- Loosen the screw in the middle of the yellow ring and pull the
ring up and insert it into the drum screw.
- Lower the hook and assemble the central screw. At this point,
the button inside the main body is lowered by the drum screw.
- The button going down presses the inner switch.
(2) Assembly of radioactive waste drum screws
(3) When replacing the battery, open the grey lid and replace it.

- When radioactive small-packaged waste & drums are out of a specific
area, alarms are generated to prevent theft and loss and the depar­
ture of transport trucks.
- Real-time check of radioactive small-packaged waste & drum loading
location and condition

- Tracking the path of movement by the identification of radioactive
small-packed wastes and by drum movements
- Provide data such as the amount, generation and inventory of
radioactive waste drums by monitoring radioactive small-packed
wastes and drums. IoT sensor data attached to the drum at the test

The main functions of this prototype are checking the temperature
and humidity of the radioactive waste drums and whether the lids are
open, and monitoring the situation for drum entry and exit in the MESH
network environment is possible. In addition, when a radioactive waste
drum is going to transfer to a radioactive waste disposal site, the
movement of the radioactive waste drum can be checked in real-time
using Global Positioning System (GPS) and Long-Term Evolution
(LTE) communication.

Fig. 3. Prototype geometry of IoT attached on the drums.
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Progress in Nuclear Energy 149 (2022) 104251

3.3.2. Monitoring the status (lid on/off) of the radioactive waste drums and
their temperature and humidity

Table 2
Specification of temperature/humidity and MCU.
Surface contamination rates
(permit range)

3.3.2.1. Detecting lid engagement. A bolt-on rim used to assemble the
drum lid was used to detect whether the drum lid is engaged. When
installing the sensor after the bolt assembly, the screw tab of the bolt can
determine the assembly status by pressing the sensor’s button, and a
limit switch is used as the push switch. The microcontroller unit (MCU)
inside the sensor is responsible for transmitting information that detects
whether the drum is coupled or not. The limit switch specifications are
shown in Table 1.
3.3.2.2. Detecting the temperature and humidity of the drum. MicroElectro-Mechanical Systems (MEMS) sensors were selected to monitor
the temperature and humidity conditions around the radioactive waste
drum. The MCU inside the sensor obtains the information and transmits
the information through the network and acquires signal data related to
the opening/closing of the drum lid and information on temperature and
humidity. The sensor is capable of miniaturizing the design and is
located outside the drum, which has advantages in use and manage­
ment. Table 2 shows the MEMS sensor and MCU specifications. The
network related to the IoT of the radioactive waste is the MESH
network/Wirepas, for which the Bluetooth Low Energy (BLE) sensor of
the drum is connected to the MESH network in the storage. The BLE
sensor means one of the features of the CPU (nRF 52832: ARM Cortex
M4) of the MCU.

Operation
temperature

− 40 ◦ C ~
85 ◦ C

Core

Temperature
error
Operation
humidity
Humidity error

0.3 ◦ C

Wireless sender/
reception
Operation
temperature

0–100 RH
%
2% on the
25 ◦ C

ARM® Cortex®-M4 32-bit
processor with FPU, 64
MHz
2.4 GHz transceiver
− 40 ◦ C ~ 85 ◦ C

mesh networks to define areas where radioactive waste drums are
loaded. The left in Fig. 4 is a diagram of the Clearance Level Waste
Storage where the experiment was conducted. The details of the drum
location detection system installed in this facility for the experiment are
as follows.

-

Server for control service and database storage: 1
LTE wireless router for receiving a location of an external vehicle:
Gateway for receiving sensor access location information: 2
Anchor node for zone classification: 18 (indicated in green in Figure)
TAG for distinguishing drums: 100

3.4. Legacy system of RAW

3.3.3. Definition of the radioactive waste drum zone and network design
A test area was selected to experiment with the IoT sensors of
radioactive waste drums, and 100 drums were used. The requirements
considered for the design of the network systems were as follows.

Fig. 5 shows the RAWINGS, which is a system that manages the full
life cycle of low and intermediate-level radioactive waste. The system
consists of several modules such as operational waste generated within
the KAERI, dismantled waste generated from decommissioning Korean
Research Reactor (KRR) and Uranium Conversion Plants (UCP), clear­
ance level waste, and Legacy waste. The system allows the entire process
to be tracked until radioactive waste generated from nuclear fuel cycle
facilities is transported to the waste disposal site via the waste disposal
facility and provides basic data for analyzing the nuclides contained in
the waste. The combustible waste data uploaded from the RAWINGS and
used for the Digital Twin is shown in Table 3.

- Devices and servers that use LTE networks should be able to
communicate in two directions
- Sensor servers use LTE routers for communication with external LTE

communication terminals
- LTE routers should be given fixed IPs to collect LTE data from GPS
terminals and provide endpoints to access the Digital Twin system.
- Wireless LTE networks themselves are difficult to hack, but con­
nections that transmit GPS data to servers must ensure secure
communication using Secure Sockets Layer (SSL), which refers to an
Internet encryption communication protocol for securely trans­
mitting data on the Internet.
- A mesh network is a network that is easy to install and set up using
RSSI, which means an estimated measure of power level that an RF
client device is receiving from an access point or router, between
devices that communicate. The mesh network configured in this
system was as follows.
⧉ Anchor: A fixed node that knows its location in advance.
⧉ Tag: A device attached to a drum as a moving node.
⧉ Sink: Physically connected to a gateway as a node that receives
data from an anchor and tag and passes it to the gateway.
⧉ Gateway: Responsible for data exchange between the mesh
network and backend. Models used in the storage and those on
the vehicle must be distinguished because of the different
communication channels used to connect to the backend.

4. Case study
A couple of experiments were conducted to verify that the waste in
the drums and the condition monitoring of the drums are normally
performed on the digital twins using the technical background of AR and
IoT and the collected radioactive waste datasets. The experimental fa­
cility for the case study was selected as a clearance level radioactive
waste storage and tested using 100 RAW drums.
4.1. Identification of the RAW in the drums

If you select ’ Check Waste In-situ ’ on the menu screen, you can
check the information that corresponds to the QR codes generated by the
digital twins and registered by the AR visualization app. Additionally, if
the QR code is the QR code of the repackaged drum, the information of
the repackaged drum can be checked, and if the QR code is the QR code
of the small-packaged wastes, the information of the small-packaged
wastes can be checked. Fig. 6 shows the information on small pack­
ages in drums (AR-1990-B01-0606) to be transported to the disposal site
using Tablet PC with augmented reality technology and informs that the
filling rate of drums is 85%. Previously, in order to check the wastes in
the drum, the drum lid was opened and the wastes were checked one by
one. This technology has the advantage to identify various kinds of
characterization of the RAW as follows;

Fig. 4 shows a network of radioactive waste storage drawings and
Table 1
Description of limit switch.
Ratings
Insulation Resistance
Contact Resistance
Operation force

MCU

3A/125VAC/250VAC
10 Mohm
50 mohm
0.26N

5

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Progress in Nuclear Energy 149 (2022) 104251

Fig. 4. Drawings of experiment facility and configuration of RAW network.

Fig. 5. Systematic diagram of RAWINGS.
Table 3
Combustible waste data linked to Digital Twin from RAWINGS.
Waste by Generated Facilities (Original Drums)

Repackaged Drums Treatment

Drum No.
Drum generated facility
Drum generated date
Surface Dose Rate (mSv/hr)
Small-packaged No.
Repackaging: Yes/No
Original drum location
Small-packaged waste
Small-packaged weight (kg)

Drum No.
Drum generated facility
Drum generated date
Repackaging Date
Drum waste

Special drum: Yes/No
Surface Dose Rate (mSv/hr)
1m Dose Rate(mSv/hr)
Measure date of drum dose rate
Drum location
Amount of specimen sampling (kg)

2019–005
Dept. Dismantled Waste
18.05.04
0.8
2019-005-FT1
No
D-3-5-6
Filter
50

Concentration Value by Nuclide (Bq/g)

Waste by Generated Facilities (Original Drums)

Repackaged Drums Treatment

Drum No.
Drum generated facility
Drum generated date
Surface Dose Rate (mSv/hr)
Small-packaged No.
Repackaging: Yes/No
Original drum location

Small-packaged waste
Small-packaged weight (kg)

Drum No.
Drum generated facility
Drum generated date
Repackaging Date
Drum waste
Special drum: Yes/No
Surface Dose Rate (mSv/hr)
1m Dose Rate(mSv/hr)
Measure date of drum dose rate
Drum location
Amount of specimen sampling (kg)

2019–005
Dept. Dismantled Waste
18.05.04
0.8
2019-005-FT1
No
D-3-5-6
Filter
50

- Characteristics of radiological requirements: nuclides and radioac­
tivity concentrations, surface dose rates, and surface contamination.
- Characteristics of physical requirements: fill rate, and free-standing
water properties.

AR-2019-B01-001
Dept. Chemical Research
19.03.01
19.04.05
Paper
No
0.002
0.0001
19.04.05
C-2-2-3
0.1

Amount of specimen analysis (g)
Gross Alpha
H-3
C-14
Cr-51
Fe-55
Co-58
Ni-59
Co-60
Ni-63
Nuclide (18)

10
4.85E+00
4.75E+00
1.03E+00
6.73E-03
2.46E-02

6.99E-03
3.01E-01
2.28E-01
4.19E+00

Concentration Value by Nuclide (Bq/g)
AR-2019-B01-001
Dept. Chemical Research
19.03.01
19.04.05
Paper
No
0.002
0.0001
19.04.05
C-2-2-3
0.1

Amount of specimen analysis (g)
Gross Alpha
H-3
C-14
Cr-51
Fe-55
Co-58
Ni-59
Co-60
Ni-63
Nuclide (18)

10
4.85E+00
4.75E+00
1.03E+00
6.73E-03
2.46E-02
6.99E-03
3.01E-01
2.28E-01
4.19E+00

- Characteristics of chemical requirements: disposal-restricted sub­
stances (corrosive, explosive, flammable, ignitable substances, gasgenerating substances, biohazard substances, etc.).

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Progress in Nuclear Energy 149 (2022) 104251

Fig. 6. Identification of filling rate information within the RAW drum.

4.2. Monitoring of the RAW drum condition

IoT sensor value attached to the drum AR-2019-B01-0002 is normally
linked to the DT. The right figure shows the results of confirming the IoT
sensor value stored in the DB through Structured Query Language (SQL)
Query. The data that organized in the DB is Facility ID, Facility Name,
Zone ID, Temperature, Humidity, and On/Off on the Lid of the Drum.

After a drum (TR-2017-801-0232) was loaded into the radioactive waste
storage, its lid was tested to determine if it was recognizable directly on
a Digital Twin when it was opened for work or other purposes. Based on
the results, the opening and closing status of the drum could be checked
in real-time shown in Fig. 8. The left in Fig. 8 shows the normal state of
the drum as sealed, and the right figure shows the fact that the drum lid
is open. The green colour in the left picture indicates that the lid of the
drum is normally closed. When someone opens the drum’s lid, the sensor
detects it and appears in red like the picture on the right, and the alarm
goes off. The temperature and humidity were 16.63 ◦ C and 65.15%,
respectively.
Through the above experiments, it was confirmed that the moni­
toring experiment of drums loaded into radioactive waste storage
(temperature and humidity and opening and closing of the drum lid) was
completed normally.

4.2.1. Definition of RAW storage ID and zone ID
The radioactive waste facility ID and zone ID are defined as shown in
Table 4 to monitor the condition of the radioactive waste drum in the
digital twin. This table means to ID values to define the location of the
IoT sensor to be linked to the facility where IoT devices will be installed
and the Digital Twin system. In the ID column of this table, 1225 means
zone Y, which is an experimental section in the radioactive waste 1
storage. As a result of the experiment, open/close, temperature, hu­
midity, and zone information (located/not in the relevant area) of the
repackaged drum could be checked on the Digital Twin through the
Application Programming Interface (API) provided by the IoT
application.
4.2.2. IoT sensor data reception and visualization
Using the IoT sensor values transmitted from the IoT servers, it was

tested whether the values are normally received on the digital twins, and
it was confirmed that the API linkage for receiving the IoT sensor values
is successful shown in Fig. 7. The left figure in Fig. 7 describes that the

5. Conclusion

Table 4
Combustible waste data linked to Digital Twin from RAWINGS.
Facility
No.

Facility Name

Facility
ID

Zone

Zone ID

ID

B5

RAW 1 StorageSubsidiary

11

RAW 1 Storage

12

B7

RAW 2 Storage

13

B8

Take-out Storage

14

B24

Metal Molten
Experiment

15

B26

Combustible
Waste Treatment

16

B27

Dismantled
Waste Storage-1

17

F1

Dismantled
Waste Storage-2

18

⋅
D4

⋅
Clearance Level
Waste Storage

⋅
20

01,
03,
26
01,
03,
05,
25
01,

03,
26
01,
03,
26
01,
03,
05,
01,
03,
05,
01,
03,
05,
01,
03,
05,
⋅
01

Facility
+ Zone

B6

A, B, C,
D, E … …
…, Z
A, B, C,
D, E … …

…, Z
Y
A, B, C,
D, E … …
…, Z
A, B, C,
D, E … …
…, Z
A, B, C,
D, E … …
…, Z
A, B, C,
D, E … …
…, Z
A, B, C,
D, E … …
…, Z
A, B, C,
D, E … …
…, Z
⋅
Test

02,
04, 0,
02,
04,
26
02,
04, 0,

A Prototype of the Digital Twin system was completed by monitoring
the condition of drums using IoT sensors attached to radioactive waste
drums, checking small-packaged wastes in the drums using augmented
reality technology, and linking data stored in the legacy systems. The
Digital Twin can monitor the condition of drums in real-time through
the Web without restrictions on the storage space of radioactive waste,
check the loading location and the history of small packages in the
drums. In the future, the data accumulated from the Digital Twin
operation can be used as a tool for radioactive waste pattern analysis.
Furthermore, they can be used as learning data when building an
intelligent storage management model based on deep learning. In
addition, as an alternative to the accuracy of the IoT sensor and the exact
location of the drum in the radioactive waste storage, we plan to conduct
a localization study using deep learning.

1225

02,
04, 0,
02,
04,
26
02,
04,
26
02,
04,
26
02,

04,
26

Credit author statement
Hee-Seoung Park: Supervision, Conceptualization, Methodology,
Writing-original draft, Visualization. Sung-Chan Jang:, Il-Sik Kang:
Resources, Investigation, Data curation. Dong-Ju Lee: Resources,
Investigation, Data curation. Jeong-Guk Kim: Data curation. Jin Woo
Lee: Writing – review & editing, Project administration.
Declaration of competing interest

⋅
2001

The authors declare that they have no known competing financial
7


H.-S. Park et al.

Progress in Nuclear Energy 149 (2022) 104251

Fig. 7. Identification of IoT sensor data and check of temperature/humidity.

Fig. 8. Monitoring of repackaged drums conditions: Left-normal, Right-Abnormal.

interests or personal relationships that could have appeared to influence
the work reported in this paper.
Fig. 4 shows a network of radioactive waste storage drawings and
mesh networks to define areas where radioactive waste drums are

loaded.

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Acknowledgements
This work was supported by the Nuclear Research & Development
Program (2019M2C9A1059067) through the National Research Foun­
dation of South Korea (NRF) funded by the Ministry of Science ICT
(MIST), Republic of Korea.
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8


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