방사선 작업 종사자 안전 증대를 위한 피폭 선량예측 관리시스템 개발
Development of a Radiation Dose Prediction and Management System for Enhancing the Safety of Radiation Workers
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This study presents the development of a radiation dose prediction and management system (DoseSim)aimed at enhancing the safety of radiation workers. The system is designed to systematically predict, evaluate, andoptimize radiation exposure based on accumulated data, supporting the implementation of the ALARA (As LowAs Reasonably Achievable) principle. The DoseSim system integrates diverse datasets, including 3D modeling,radiological source information, and previous exposure records, to provide a comprehensive framework for radiationprotection. By enabling detailed simulations of radiation exposure scenarios, the system assists in minimizing dosevariations among workers and improving the overall efficiency of radiation management. Key features include dosesimulation, comparative analysis, and data visualization, which facilitate decision-making and training processes. Theresults demonstrate the potential of DoseSim to enhance radiation safety practices in environments such as nuclearpower plants. Future research will focus on refining the system with real-world data and expanding its applicabilityto various radiological work environments. This work contributes to advancing data-driven radiation protectionstrategies and improving worker safety in the radiological industry.
Abstract
This study presents the development of a radiation dose prediction and management system (DoseSim)aimed at enhancing the safety of radiation workers. The system is designed to systematically predict, evaluate, andoptimize radiation exposure based on accumulated data, supporting the implementation of the ALARA (As LowAs Reasonably Achievable) principle. The DoseSim system integrates diverse datasets, including 3D modeling,radiological source information, and previous exposure records, to provide a comprehensive framework for radiationprotection. By enabling detailed simulations of radiation exposure scenarios, the system assists in minimizing dosevariations among workers and improving the overall efficiency of radiation management. Key features include dosesimulation, comparative analysis, and data visualization, which facilitate decision-making and training processes. Theresults demonstrate the potential of DoseSim to enhance radiation safety practices in environments such as nuclearpower plants. Future research will focus on refining the system with real-world data and expanding its applicabilityto various radiological work environments. This work contributes to advancing data-driven radiation protectionstrategies and improving worker safety in the radiological industry.