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Showing 1 to 11 of 11 for “"nuclear energy systems"”.

  1. Materials Design for Advanced Nuclear Energy Systems: Refractory High Entropy Alloys and Metallic Multilayer Composites

    Advanced nuclear reactors present a multitude of materials challenges due to high op- erating temperatures, corrosive environments, and neutron radiation damage. In this thesis, I focus on two approaches to designing better materials for advanced reactors, high entropy alloys (HEAs) and metallic …

    mit Repository record for Materials Design for Advanced Nuclear Energy Systems: Refractory High Entropy Alloys and Metallic Multilayer Composites (opens in a new tab)

  2. A Preliminary Design of Two Nuclear Energy Systems for Emergency On-Site Power Generation at Ballistic Missile Defense Installation

    Made available in DSpace on 2017-07-06T18:55:10Z (GMT). No. of bitstreams: 2 Linnard_Jon_W_MS.pdf: 33799749 bytes, checksum: 101ccadaba983c9cdd9a6f9b07d684b9 (MD5) license.txt: 4813 bytes, checksum: 715c4321821a960fa1a1e91d2ac7ebce (MD5) Previous issue date: 1975

    uiuc Repository record for A Preliminary Design of Two Nuclear Energy Systems for Emergency On-Site Power Generation at Ballistic Missile Defense Installation (opens in a new tab)

  3. A unified risk-Informed framework to assess the proliferation risk and license the proliferation performance of nuclear energy systems

    … that use, store, produce, or reprocess special nuclear materials (SNM). The current surge of interest in nuclear energy requires resolution of concerns about the appropriateness of the current nuclear non-proliferation regulatory framework for the threats challenging nuclear energy systems

    mit Repository record for A unified risk-Informed framework to assess the proliferation risk and license the proliferation performance of nuclear energy systems (opens in a new tab)

  4. Artificial Neural Network and Dynamic Probabilistic Risk Assessment for passive safety systems

    … for the safety assessment of passive safety systems, particularly in mitigating Loss of Coolant Accidents (LOCAs). While using the BWRX-300 SMR, the study highlights the broader applicability of these techniques to enhance traditional Probabilistic Safety Assessment (PSA). ANNs were employed …

    uoit Repository record for Artificial Neural Network and Dynamic Probabilistic Risk Assessment for passive safety systems (opens in a new tab)

  5. An integrated methodology for quantitative assessment of proliferation resistance of advanced nuclear systems using probabilistic methods

    … to evaluate proliferation resistance of nuclear energy systems is outlined and demonstrated focusing upon the proliferation competition. The methodology consists of four steps: actor characterization, proliferation competition model development, model input evaluation, and pathway …

    mit Repository record for An integrated methodology for quantitative assessment of proliferation resistance of advanced nuclear systems using probabilistic methods (opens in a new tab)

  6. Nuclear Fuel Requirements For the American Economy - A Model

    … of various fuel streams required to supply energy from planned and projected nuclear plant operations, including new builds. Flexible, user-defined scenarios can be constructed with respect to energy requirements, choices of reactors and choices of fuels. The model includes interactive …

    south-carolina Repository record for Nuclear Fuel Requirements For the American Economy - A Model (opens in a new tab)

  7. On the use of high performance annular fuel in PWRs

    Recently, MIT's Center for Advanced Nuclear Energy Systems developed a new high burnup annular fuel that features both internal and external cooling. Implementation of this fuel design in current pressurized water reactors (PWRs) will allow power uprates up to 50% while maintaining or improving its …

    mit Repository record for On the use of high performance annular fuel in PWRs (opens in a new tab)

  8. A Structure-based Machine Learning Approach for Spatiotemporal Fluctuations in Nuclear Thermal Fluids

    In nuclear energy systems, flow-assisted damage can arise at locations where complex turbulent structure interaction drives enhanced mechanical loads and mixing of different temperature flows drives thermal-induced mechanical failures. Thermal striping is a such phenomenon characterized by the …

    mit Repository record for A Structure-based Machine Learning Approach for Spatiotemporal Fluctuations in Nuclear Thermal Fluids (opens in a new tab)

  9. Analyzing the proliferation resistance of advanced nuclear fuel cycles : in search of an assessment methodology for use in fuel cycle simulations

    … to assess proliferation resistance of advanced nuclear energy systems is investigated. The framework, based on Multi-Attribute Utility Theory (MAUT), is envisioned for use within early-stage fuel cycle simulations. Method assumptions and structure are explained, and reference technology cases …

    mit Repository record for Analyzing the proliferation resistance of advanced nuclear fuel cycles : in search of an assessment methodology for use in fuel cycle simulations (opens in a new tab)

  10. CFD Modeling and Simulation of Natural Circulation in Helium- Cooled Very High Temperature Reactors

    … Very High Temperature Reactor (VHTR) systems, focusing on the performance and validation of passive safety features under Pressurized or Depressurized Loss of Forced Cooling (P-LOFC or D-LOFC) events. An experimental facility inspired by the General Atomics 350 MWt Modular High …

    cuny Repository record for CFD Modeling and Simulation of Natural Circulation in Helium- Cooled Very High Temperature Reactors (opens in a new tab)

  11. The influence of temporal detail and inter-annual resource variability on energy planning models

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms

    uiuc Repository record for The influence of temporal detail and inter-annual resource variability on energy planning models (opens in a new tab)