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The average temperature of Earth is the subject of much current discussion. Earth is in radiative contact with both the Sun and dark space; it receives almost all its energy from the radiation of the Sun and reflects some of it into outer space. Dark space is very cold, about 3 K, so Earth radiates energy into it. For instance, heat transfer occurs from soil and grasses, the rate of which can be so rapid that frost can occur on clear summer evenings, even in warm latitudes.
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The radiation pressure applied by an electromagnetic wave on a perfectly absorbing surface equals the energy density of the wave. The wave's momentum also gets transferred to the surface when an electromagnetic wave is entirely absorbed by it. The rate at which momentum is transmitted to an absorbing surface perpendicular to the propagation direction equals the force on the surface.
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Intelligent assistant in radiation protection based on large language model with knowledge base.

Ankang Hu1,2, Kaiwen Li3, Zhen Wu1

  • 1Department of Engineering Physics, Tsinghua University, Beijing, 100084, China.

Radiation and Environmental Biophysics
|July 2, 2025
PubMed
Summary

A new intelligent assistant for radiation protection, utilizing a Large Language Model (LLM), provides accurate answers with references. This tool enhances efficiency in radiation protection tasks by offering reliable, domain-specific information.

Keywords:
Artificial intelligenceLarge language modelRadiation protectionRetrieval-augmented generation

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Area of Science:

  • Nuclear Science and Engineering
  • Artificial Intelligence
  • Information Technology

Background:

  • Radiation protection is essential for nuclear energy and technologies.
  • Existing knowledge and experience in radiation protection are vast and complex.
  • A comprehensive understanding of radiation protection is challenging for individuals and committees.

Purpose of the Study:

  • To develop an intelligent assistant for radiation protection using a Large Language Model (LLM).
  • To provide reliable, referenced answers to professional queries in radiation protection.
  • To address privacy and data security concerns through local deployment and private datasets.

Main Methods:

  • Development of an LLM-based intelligent assistant with a knowledge base.
  • Utilizing open-source toolkits and LLMs for assistant development.
  • Implementation of a web-based user interface (UI) for user interaction.
  • Local deployment with private datasets for enhanced security.

Main Results:

  • The assistant provides reliable answers with references from authoritative publications.
  • Demonstrated satisfying performance on professional radiation protection queries.
  • Outperformed web search-based LLM applications in precision and relevance.
  • Achieved superior results with a smaller number of model parameters.

Conclusions:

  • The LLM-based intelligent assistant shows significant potential for improving efficiency in radiation protection tasks.
  • This work represents a preliminary step towards intelligent systems in radiation protection.
  • The assistant offers a secure and effective solution for accessing radiation protection knowledge.