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.
Progress in Nuclear Energy 149 (2022) 104251 Contents lists available at ScienceDirect 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 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: parkhs@kaeri.re.kr (H.-S Park) https://doi.org/10.1016/j.pnucene.2022.104251 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 (http://creativecommons.org/licenses/bync-nd/4.0/) 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 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) 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 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: H.-S Park et al - 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 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 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 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 Configuration of RAW Digital Twin includes AR and IoT H.-S Park et al Progress in Nuclear Energy 149 (2022) 104251 Fig 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 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 Prototype geometry of IoT attached on the drums H.-S Park et al 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 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 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 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 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: LTE wireless router for receiving a location of an external vehicle: Gateway for receiving sensor access location information: 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 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 - 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 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 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 shows a network of radioactive waste storage drawings and Table Description of limit switch Ratings Insulation Resistance Contact Resistance Operation force MCU 3A/125VAC/250VAC 10 Mohm 50 mohm 0.26N H.-S Park et al Progress in Nuclear Energy 149 (2022) 104251 Fig Drawings of experiment facility and configuration of RAW network Fig Systematic diagram of RAWINGS Table 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.) H.-S Park et al Progress in Nuclear Energy 149 (2022) 104251 Fig 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 The left in Fig 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 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 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 The left figure in Fig describes that the Conclusion Table Combustible waste data linked to Digital Twin from RAWINGS Facility No Facility Name Facility ID Zone Zone ID ID B5 RAW StorageSubsidiary 11 RAW Storage 12 B7 RAW 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 H.-S Park et al Progress in Nuclear Energy 149 (2022) 104251 Fig Identification of IoT sensor data and check of temperature/humidity Fig 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 shows a network of radioactive waste storage drawings and mesh networks to define areas where radioactive waste drums are loaded Jokelainen, Miikka, Porkholm, Kari, Juslin, Kaj, 2018 Requirements and experiences on a sustainable digital twin platform for dependable studies of thermal processes dynamics Nucl Saf Simul Number 2, December Krukovskyi, P.G., Diadiushko, YeV., Garin, V.O., Tryfonov, O.V., Kabanov, YuYu, 2020 CFD MODEL AS A DIGITAL TWIN OF THE RADIATION STATE OF THE NEW SAFE CONFINEMENT OF THE CHERNOBYL NPP ISSN 1562-6016 PASТ, pp 54–62 No (128) Miki, Nagoya, et al., 2018 In: Distance Information Display System Using Augmented Reality for Supporting Decommissioning Work", CHIRA 2018 – 2nd International Conference on Computer-Human Interaction Research and Applications Park, YoungSoo, et al., 2017 Augmented Reality System for Remote Operation NPIC & HMIT, San Francisco, CA June 11-15, 2017 Stefania Uras, et al., “PREDIS: Deliverable 7.1 State of the Art in Packaging, Storage, and Monitoring of Cemented Wastes”, Dissemination Level: Public Volodin, V.S., 2019 Concept of Instrumentation of Digital Twins of Nuclear Power Plants Units as Observers for Digital NPP I&C System, p 1391, 012083, 8th International Conference on Mathematical Modeling in Physical Science, 2019 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 References Further reading Alexander, Arzhaev, et al., 2020 NPP unit life management based on digital twin application E3S Web Conf 209, 03006 https://doi.org/10.1051/e3sconf/ 202020903006 ENERGY-21 Apte, Poornima, 2021 Digital Twins of Nuclear Power Plants ASME May 11 https ://www.asme.org/topics-resources/content/digital-twins-of-nuclear-power-plants Brendan, Kochunas, Xun, Huan, 2021 Digital twin concepts with uncertainty for nuclear power applications Appl Energies 14, 4235 Ferguson, Stephen, 2020 White Paper: the Virtual Nuclear Reactor”, Siemens Digital Industries Software siemens.com/software Ishii, Hirotake, 2010 Augmented Reality: Fundamentals and Nuclear Related Applications” December https://www.researchgate.net/publication/241686793 Ishii, Hirotake, et al., 2008 Proposal and Evaluation of a Supporting Method for NPP Decommissioning Work by Augmented Reality January https://www.researchgate net/publication/238561860 Izumi, Masanori, Shimoda, Hiroshi, Ishii, Hirotake, 2010 A Feasibility Study on Worksite Visualization System Using Augmented Reality for Fugen NPP” January https://www.researchgate.net/publication/229009361 Concetta, Semeraro, et al., 2021 Digital twin paradigm: a systematic literature review Comput Ind 130, 103469 https://doi.org/10.1016/j.compind.2021.103469 CORA-CALCOM, 2011 Program System for Nuclear Facility Decommissioning www siempelkamp-nis.com Iguchi, Yukihiro, et al., 2004 Development of decommissioning engineering support system (DEXUS) of the FUGEN nuclear power station J Nucl Sci Technol 41 (3), 367–375 Park, Seung Kook, et al., 2011 Unit Productivity Calculating System for Decommissioning Work, vol 38 Korean Institute of Information Scientists and Engineers No 1(C) Park, Jin Ho, et al., 2007 Development of the Decommissioning Project Management System KAERI/TR-3401/ H.-S Park et al Progress in Nuclear Energy 149 (2022) 104251 UKAEA’s Decommissioning Strategy, 2001 The Management of Nuclear Liabilities in UKAEA-PART Technology Development, vol Usui, Hideo, et al., 2012 In: Study on Evaluation of Project Management Data for Decommissioning of Uranium Refining and Conversion Plant, WM2012 Conference February 26 March 1, Phoenix, Arizona, USA Yanagihara, Satoshi, 1993 COSMARD: the code system for management of JPDR decommissioning J Nucl Sci Technol 30 (9), 890–899 ... 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... condition of the radioactive waste drums loaded in the designated space for radioactive waste storage (1 actual space and TEST area) was possible by transmitting data from the IoT sensors attached to... 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