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    <completedYear/>
    <publishedYear>2025</publishedYear>
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    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>153</pageLast>
    <pageNumber/>
    <edition>2025</edition>
    <issue/>
    <volume>NTB-6</volume>
    <type>other</type>
    <publisherName>Americal Society of Mechanical Engineers (ASME)</publisherName>
    <publisherPlace>New York, NY</publisherPlace>
    <creatingCorporation>ASME Special Working Group on Computational Modeling for Explicit Dynamics</creatingCorporation>
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    <title language="eng">Guidance document - Use of explicit finite element analysis for the evaluation of radioactive material transport packages and storge casks in energy-limited impact events</title>
    <abstract language="eng">The purpose of this document is to provide guidance for developing quality finite element models to ensure, with reasonable certainty, that the model produces accurate results for comparison with the strain-based or stress-based acceptance criteria of Section III, Division 3 of the ASME Boiler and Pressure Vessel Code, but could be applicable to other Sections of the Code or other codes. Models developed following the guidance provided in this document meet the definition of a "Quality Model," as described in Paragraph EE 1240 of the Nonmandatory Appendix EE (Strain-Based Acceptance Criteria Definitions and Background Information). It cannot be emphasized enough, however, that the guidance supplied here does not constitute requirements. Rather, the intent of the guidance is to give practical direction to analysts (i.e., this is not a set of regulatory requirements). This guidance document is an "evolving" document. It will undergo revision as computing capability and FEA techniques progress, and as example problems are developed.</abstract>
    <parentTitle language="eng">ASME Standards</parentTitle>
    <identifier type="isbn">978-0-7918-7749-4</identifier>
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    <enrichment key="bibliotheksstandort">Bc 241</enrichment>
    <author>D. J. Ammerman</author>
    <author>J. L. Bignell</author>
    <author>G. S. Bjorkman</author>
    <author>M. R. Breach</author>
    <author>V. A. Broz</author>
    <author>J. Jordan</author>
    <author>S. Kuehner</author>
    <author>D. P. Molitoris</author>
    <author>W. Reinhardt</author>
    <author>A. B. Rigato</author>
    <author>E. S. Rosvall</author>
    <author>P. J. Sakalaukus Jr.</author>
    <author>P. Y.-K. Shih</author>
    <author>D. Siromani</author>
    <author>S. D. Snow</author>
    <author>C.-F. Tso</author>
    <author>M. C. Yaksh</author>
    <author>Uwe Zencker</author>
    <author>X. Zhang</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Computational modeling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Explicit dynamics</value>
    </subject>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="institutes" number="">3 Gefahrgutumschließungen; Energiespeicher</collection>
    <collection role="institutes" number="">3.4 Sicherheit von Lagerbehältern</collection>
    <collection role="themenfelder" number="">Energie</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Physisches Exemplar in der Bibliothek der BAM vorhanden ("Hardcopy Access")</collection>
    <collection role="themenfelder" number="">Kerntechnische Entsorgung</collection>
  </doc>
  <doc>
    <id>65806</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>5</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>International Atomic Energy Agency</publisherName>
    <publisherPlace>Wien</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
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    <title language="eng">Accident-Induced Battery and Hydrogen Fires: Challenges for the Safe Transport of Packages with Dangerous Goods</title>
    <abstract language="eng">The transport of radioactive material is subject to stringent safety requirements defined in the IAEA regulations SSR-6 [1]. These requirements, particularly the thermal and mechanical accident conditions of transport (ACT), are rooted in studies established in the 1960s and have remained largely unchanged, especially regarding thermal boundary conditions. For many decades, the type of propulsion technology used for transporting dangerous goods has remained unchanged. In recent years, however, alternative drive technologies have made their breakthrough and are becoming increasingly established on the market. Since then, the rapid adoption of battery-electric and hydrogen-powered vehicles in heavy-duty freight and dangerous goods transport is altering the conditions under which accidents may occur. This raises a central question: Are current regulatory tests, such as the 800°C and 30-minute thermal test, still sufficiently conservative for ACT involving vehicles with alternative propulsion technologies?&#13;
Battery fires pose specific challenges due to the properties of lithium-ion cells and emerging chemistries such as NMC, LFP, and NCA/LTO. Their highly flammable electrolytes, potential for thermal runaway, release of toxic gases, and long-duration or reigniting fires differ markedly from conventional fuel fires. Such behavior questions whether existing thermal test specifications adequately reflect realistic accident conditions involving electric vehicles.&#13;
Hydrogen-powered vehicles introduce additional hazards. Accidental releases can form explosive mixtures, and ignitions may produce intense jet fires or explosions with high radiative heat fluxes. Near a package, these events can create thermal loads and transient pressures not fully captured by current regulatory test envelopes. Beyond peak temperatures and exposure time, parameters emphasized in IAEA SSG-26 [2], such as emissivity, absorptivity, heat flux, and fuel energy density, are critical for determining net heat input and require assessment with respect to realistic scenarios.&#13;
Addressing these gaps requires a research program focused on vehicle fire scenarios and their implications for the safety assessment of packages for radioactive material. This includes developing conservative accident scenarios for various battery chemistries and performing large-scale experiments with calorimetric reference packages and instrumented setups. Notably, there are currently no experimental investigations of accidents involving transport vehicles with alternative propulsion in which the dangerous goods - the package and its loading - have been the central focus rather than the vehicle itself. A necessary research project must aim to assess the relevance of the IAEA's existing transport testing requirements regarding these new risks and, if necessary, propose changes or supplementary measures. Its methods and datasets should also support assessments for other dangerous goods, ensuring that regulatory measures continue to provide robust protection in an evolving transport landscape.</abstract>
    <parentTitle language="eng">International Conference on the Safe and Secure Transport of Nuclear and Radioactive Material</parentTitle>
    <enrichment key="eventName">International Conference on the Safe and Secure Transport of Nuclear and Radioactive Material</enrichment>
    <enrichment key="eventPlace">Wien, Austria</enrichment>
    <enrichment key="eventStart">23.03.2026</enrichment>
    <enrichment key="eventEnd">27.03.2026</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <author>Tobias Gleim</author>
    <author>Hannes Soderer</author>
    <author>Frank Wille</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>IAEA Regulations</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fire Test Stand</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Accident Scenario</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fire Qualification</value>
    </subject>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="institutes" number="">3 Gefahrgutumschließungen; Energiespeicher</collection>
    <collection role="institutes" number="">3.3 Sicherheit von Transportbehältern</collection>
    <collection role="themenfelder" number="">Energie</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="themenfelder" number="">Kerntechnische Entsorgung</collection>
  </doc>
  <doc>
    <id>65808</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>5</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>International Atomic Energy Agency</publisherName>
    <publisherPlace>Wien</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Ai-Enhanced Documentation Analysis in Regulatory Safety Assessment of Transport Packages</title>
    <abstract language="eng">The transport of radioactive material requires regulatory approval based on the package type, as defined by the regulations of the International Atomic Energy Agency (IAEA). These approvals rely on comprehensive Package Design Safety Reports that evaluate mechanical, thermal, shielding, criticality and transport requirements, supported by specifications, inspections, certificates, drawings, and other technical documentations. Such safety reports contain numerous interconnected documents, and even minor changes, such as component modifications, updated material properties or revised regulations, may affect multiple sections. Although all reports follow the same regulatory framework, each package has unique design features, making every safety assessment distinct. Most documentation exists in digital form but remains largely non–machine-interpretable, limiting automated analysis of dependencies across documents. The extended synopsis argues that overcoming these limitations requires moving from simple digitization toward structured knowledge representation. A multi-stage approach begins with foundational AI technologies, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), which improve information retrieval but cannot capture the full complexity of safety report interrelationships. Building Knowledge Graphs (KGs) offers the necessary next step by transforming heterogeneous, unstructured, and semi-structured documents into a connected, queryable network. KGs enable precise tracing and visualization of dependencies across datasheets, simulations, experimental results, standards, and regulatory requirements. Such structured representations would allow automatic detection of changes, propagation of effects across related documents and validation of conditions using AI-supported tools, reducing manual workload, and improving safety and consistency. Human error remains a significant factor in drafting and reviewing safety reports. A digital quality infrastructure could reduce the number of iterations and further streamline the overall process. Integrating AI into this workflow has the potential not only to optimize assessments but also to improve their robustness by increasing the interpretability of documentation and thereby enhancing overall safety. This preliminary study examines the readiness and requirements for intelligent documentation analysis systems that support regulatory compliance for transport package safety. By analysing current documentation workflows, it demonstrates how LLM-based tools can interpret complex safety reports and identify critical interdependencies, and why KG-based architectures are essential for managing these dependencies reliably.</abstract>
    <parentTitle language="eng">International Conference on the Safe and Secure Transport of Nuclear and Radioactive Material</parentTitle>
    <enrichment key="eventName">International Conference on the Safe and Secure Transport of Nuclear and Radioactive Material</enrichment>
    <enrichment key="eventPlace">Wien, Austria</enrichment>
    <enrichment key="eventStart">23.03.2026</enrichment>
    <enrichment key="eventEnd">27.03.2026</enrichment>
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    <author>Tobias Gleim</author>
    <author>Kutlualp Tazefidan</author>
    <author>Frank Wille</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Knowledge Graph</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>AI</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>RAG</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>LLM</value>
    </subject>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="institutes" number="">3 Gefahrgutumschließungen; Energiespeicher</collection>
    <collection role="institutes" number="">3.3 Sicherheit von Transportbehältern</collection>
    <collection role="themenfelder" number="">Energie</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Graue Literatur</collection>
    <collection role="themenfelder" number="">Kerntechnische Entsorgung</collection>
  </doc>
  <doc>
    <id>65807</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>lecture</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
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    <completedDate>--</completedDate>
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    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Accident-Induced Battery and Hydrogen Fires: Challenges for the Safe Transport of Packages with Radioactive Material</title>
    <abstract language="eng">The transport of radioactive material is subject to stringent safety requirements defined in the IAEA regulations SSR-6 [1]. These requirements, particularly the thermal and mechanical accident conditions of transport (ACT), are rooted in studies established in the 1960s and have remained largely unchanged, especially regarding thermal boundary conditions. For many decades, the type of propulsion technology used for transporting dangerous goods has remained unchanged. In recent years, however, alternative drive technologies have made their breakthrough and are becoming increasingly established on the market. Since then, the rapid adoption of battery-electric and hydrogen-powered vehicles in heavy-duty freight and dangerous goods transport is altering the conditions under which accidents may occur. This raises a central question: Are current regulatory tests, such as the 800°C and 30-minute thermal test, still sufficiently conservative for ACT involving vehicles with alternative propulsion technologies?&#13;
Battery fires pose specific challenges due to the properties of lithium-ion cells and emerging chemistries such as NMC, LFP, and NCA/LTO. Their highly flammable electrolytes, potential for thermal runaway, release of toxic gases, and long-duration or reigniting fires differ markedly from conventional fuel fires. Such behavior questions whether existing thermal test specifications adequately reflect realistic accident conditions involving electric vehicles.&#13;
Hydrogen-powered vehicles introduce additional hazards. Accidental releases can form explosive mixtures, and ignitions may produce intense jet fires or explosions with high radiative heat fluxes. Near a package, these events can create thermal loads and transient pressures not fully captured by current regulatory test envelopes. Beyond peak temperatures and exposure time, parameters emphasized in IAEA SSG-26 [2], such as emissivity, absorptivity, heat flux, and fuel energy density, are critical for determining net heat input and require assessment with respect to realistic scenarios.&#13;
Addressing these gaps requires a research program focused on vehicle fire scenarios and their implications for the safety assessment of packages for radioactive material. This includes developing conservative accident scenarios for various battery chemistries and performing large-scale experiments with calorimetric reference packages and instrumented setups. Notably, there are currently no experimental investigations of accidents involving transport vehicles with alternative propulsion in which the dangerous goods - the package and its loading - have been the central focus rather than the vehicle itself. A necessary research project must aim to assess the relevance of the IAEA's existing transport testing requirements regarding these new risks and, if necessary, propose changes or supplementary measures. Its methods and datasets should also support assessments for other dangerous goods, ensuring that regulatory measures continue to provide robust protection in an evolving transport landscape.</abstract>
    <enrichment key="eventName">International Conference on the Safe and Secure Transport of Nuclear and Radioactive Material</enrichment>
    <enrichment key="eventPlace">Vienna, Germany</enrichment>
    <enrichment key="eventStart">23.03.2026</enrichment>
    <enrichment key="eventEnd">27.03.2026</enrichment>
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    <author>Tobias Gleim</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fire Test Stand</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Accident Scenario</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>IAEA Regu-lations</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Fire Qualification</value>
    </subject>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="institutes" number="">3 Gefahrgutumschließungen; Energiespeicher</collection>
    <collection role="institutes" number="">3.3 Sicherheit von Transportbehältern</collection>
    <collection role="themenfelder" number="">Energie</collection>
    <collection role="fulltextaccess" number="">Datei im Netzwerk der BAM verfügbar ("Closed Access")</collection>
    <collection role="literaturgattung" number="">Präsentation</collection>
    <collection role="themenfelder" number="">Kerntechnische Entsorgung</collection>
  </doc>
  <doc>
    <id>65754</id>
    <completedYear/>
    <publishedYear>2026</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>8</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
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    <type>article</type>
    <publisherName>Royal Society of Chemistry (RSC)</publisherName>
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    <title language="eng">Contribution of Mg-templated porosity to activity and durability in Fe–N–C O                    &lt;sub&gt;2&lt;/sub&gt;                    reduction catalysts</title>
    <abstract language="eng">Atomically dispersed Fe in N-doped carbon (Fe–N–C) catalysts are leading platinum-group-metal-free candidates for the O2 reduction reaction in proton exchange membrane fuel cells (PEMFCs). Zeolitic imidazolate framework (ZIF-8) derived Fe–N–C present the most promising performance; however, they possess a narrow distribution of small micropores, which limits active site accessibility. Here, to induce hierarchical porosity in Fe–N–C, we report a systematic study on MgCl2·6H2O-templated ZIF-8-derived Fe–N–C catalysts for the O2 reduction reaction. MgCl2·6H2O addition induced complete Zn removal, collapse of the ZIF-8 framework, and formation of large micro- and mesopores, with graphene-like structures. N content was markedly reduced, with conversion from pyridinic to pyrrolic N species. Rotating disc electrode tests showed a progressive increase in O2 reduction activity with MgCl2·6H2O, which is strongly correlated (R2 = 0.98) to the formation of large micropores and small mesopores (1–4 nm). This introduces an indirect structure–activity design principle for Fe–N–Cs. The enhanced Fe–N–C porosity also leads to increased degradation rates under accelerated stress test conditions, which we attributed to the oxidation of disordered carbon domains and active Fe loss. This study highlights a key trade-off between porosity-driven O2 reduction activity and durability in Fe–N–C catalysts.</abstract>
    <parentTitle language="eng">Materials Advances</parentTitle>
    <identifier type="issn">2633-5409</identifier>
    <identifier type="doi">10.1039/d5ma01488c</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-657549</identifier>
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    <title language="eng">Accident-Induced Battery and Hydrogen Fires: Challenges for the Safe Transport of Packages with Dangerous Goods</title>
    <abstract language="eng">The transport of radioactive material is subject to stringent safety requirements defined in the IAEA regulations SSR-6 [1]. These requirements, particularly the thermal and mechanical accident conditions of transport (ACT), are rooted in studies established in the 1960s and have remained largely unchanged, especially regarding thermal boundary conditions. For many decades, the type of propulsion technology used for transporting dangerous goods has remained unchanged. In recent years, however, alternative drive technologies have made their breakthrough and are becoming increasingly established on the market. Since then, the rapid adoption of battery-electric and hydrogen-powered vehicles in heavy-duty freight and dangerous goods transport is altering the conditions under which accidents may occur. This raises a central question: Are current regulatory tests, such as the 800°C and 30-minute thermal test, still sufficiently conservative for ACT involving vehicles with alternative propulsion technologies?&#13;
Battery fires pose specific challenges due to the properties of lithium-ion cells and emerging chemistries such as NMC, LFP, and NCA/LTO. Their highly flammable electrolytes, potential for thermal runaway, release of toxic gases, and long-duration or reigniting fires differ markedly from conventional fuel fires. Such behavior questions whether existing thermal test specifications adequately reflect realistic accident conditions involving electric vehicles.&#13;
Hydrogen-powered vehicles introduce additional hazards. Accidental releases can form explosive mixtures, and ignitions may produce intense jet fires or explosions with high radiative heat fluxes. Near a package, these events can create thermal loads and transient pressures not fully captured by current regulatory test envelopes. Beyond peak temperatures and exposure time, parameters emphasized in IAEA SSG-26 [2], such as emissivity, absorptivity, heat flux, and fuel energy density, are critical for determining net heat input and require assessment with respect to realistic scenarios.&#13;
Addressing these gaps requires a research program focused on vehicle fire scenarios and their implications for the safety assessment of packages for radioactive material. This includes developing conservative accident scenarios for various battery chemistries and performing large-scale experiments with calorimetric reference packages and instrumented setups. Notably, there are currently no experimental investigations of accidents involving transport vehicles with alternative propulsion in which the dangerous goods - the package and its loading - have been the central focus rather than the vehicle itself. A necessary research project must aim to assess the relevance of the IAEA's existing transport testing requirements regarding these new risks and, if necessary, propose changes or supplementary measures. Its methods and datasets should also support assessments for other dangerous goods, ensuring that regulatory measures continue to provide robust protection in an evolving transport landscape.</abstract>
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    <title language="eng">Ai-Enhanced Documentation Analysis in Regulatory Safety Assessment of Transport Packages</title>
    <abstract language="eng">The transport of radioactive material requires regulatory approval based on the package type, as defined by the regulations of the International Atomic Energy Agency (IAEA). These approvals rely on comprehensive Package Design Safety Reports that evaluate mechanical, thermal, shielding, criticality and transport requirements, supported by specifications, inspections, certificates, drawings, and other technical documentations. Such safety reports contain numerous interconnected documents, and even minor changes, such as component modifications, updated material properties or revised regulations, may affect multiple sections. Although all reports follow the same regulatory framework, each package has unique design features, making every safety assessment distinct. Most documentation exists in digital form but remains largely non–machine-interpretable, limiting automated analysis of dependencies across documents. The extended synopsis argues that overcoming these limitations requires moving from simple digitization toward structured knowledge representation. A multi-stage approach begins with foundational AI technologies, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), which improve information retrieval but cannot capture the full complexity of safety report interrelationships. Building Knowledge Graphs (KGs) offers the necessary next step by transforming heterogeneous, unstructured, and semi-structured documents into a connected, queryable network. KGs enable precise tracing and visualization of dependencies across datasheets, simulations, experimental results, standards, and regulatory requirements. Such structured representations would allow automatic detection of changes, propagation of effects across related documents and validation of conditions using AI-supported tools, reducing manual workload, and improving safety and consistency. Human error remains a significant factor in drafting and reviewing safety reports. A digital quality infrastructure could reduce the number of iterations and further streamline the overall process. Integrating AI into this workflow has the potential not only to optimize assessments but also to improve their robustness by increasing the interpretability of documentation and thereby enhancing overall safety. This preliminary study examines the readiness and requirements for intelligent documentation analysis systems that support regulatory compliance for transport package safety. By analysing current documentation workflows, it demonstrates how LLM-based tools can interpret complex safety reports and identify critical interdependencies, and why KG-based architectures are essential for managing these dependencies reliably.</abstract>
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    <title language="eng">AI-Enhanced Documentation Analysis in Regulatory Safety Assessment of Dangerous Goods Packages</title>
    <abstract language="eng">The transport of radioactive material requires regulatory approval based on the package type, as defined by the regulations of the International Atomic Energy Agency (IAEA). These approvals rely on comprehensive Package Design Safety Reports that evaluate mechanical, thermal, shielding, criticality and transport requirements, supported by specifications, inspections, certificates, drawings, and other technical documentations. Such safety reports contain numerous interconnected documents, and even minor changes, such as component modifications, updated material properties or revised regulations, may affect multiple sections. Although all reports follow the same regulatory framework, each package has unique design features, making every safety assessment distinct. Most documentation exists in digital form but remains largely non–machine-interpretable, limiting automated analysis of dependencies across documents. The extended synopsis argues that overcoming these limitations requires moving from simple digitization toward structured knowledge representation. A multi-stage approach begins with foundational AI technologies, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), which improve information retrieval but cannot capture the full complexity of safety report interrelationships. Building Knowledge Graphs (KGs) offers the necessary next step by transforming heterogeneous, unstructured, and semi-structured documents into a connected, queryable network. KGs enable precise tracing and visualization of dependencies across datasheets, simulations, experimental results, standards, and regulatory requirements. Such structured representations would allow automatic detection of changes, propagation of effects across related documents and validation of conditions using AI-supported tools, reducing manual workload, and improving safety and consistency. Human error remains a significant factor in drafting and reviewing safety reports. A digital quality infrastructure could reduce the number of iterations and further streamline the overall process. Integrating AI into this workflow has the potential not only to optimize assessments but also to improve their robustness by increasing the interpretability of documentation and thereby enhancing overall safety. This preliminary study examines the readiness and requirements for intelligent documentation analysis systems that support regulatory compliance for transport package safety. By analysing current documentation workflows, it demonstrates how LLM-based tools can interpret complex safety reports and identify critical interdependencies, and why KG-based architectures are essential for managing these dependencies reliably.</abstract>
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