Semi-Annual Report for Horizontal Compact High Temperature Gas Reactor (HC-HTGR) Development during Performance Period October 2022-March 2023
Bibliographic record
Abstract
Horizontal Compact High Temperature Gas Reactor (HC-HTGR) is being designed by a multi-disciplinary team of nuclear, mechanical, and structural engineers under the support of a DOE-NE Advanced Reactor Demonstration Program’s Advanced Reactor Concepts-20 (ARC-20) award. The objective of this ARC-20 project is to deliver a conceptual design for the proposed HC-HTGR in 3 years and support its commercialization as a safe, low-cost HTGR. Argonne National Laboratory (Argonne) is responsible for the design and analysis of the reactor cavity cooling system (RCCS) as a safety system for passive decay heat removal of the reactor concept. Additionally, Argonne is providing analysis of the primary heat transport system to ensure temperatures in the reactor systems, structures and components with significant safety margins during normal operation and design basis accident scenarios. This third semi-annual report summarized the progress made at Argonne on the two tasks during the first half of FY23. As a part of the RCCS design task, a design process for the water panel and the system configuration was performed to improve the thermal performance of the RCCS. The updated water panel design had achieved enhanced thermal performance with 0.96 MWth capability with major design updates made in structural interfaces with the RPV and initial configuration of the water tanks. The loop configuration of the RCCS has been proposed to have two independently working loops for system redundancy. A water panel material study was performed focusing on the use of carbon steel in water systems. Additional modeling strategies of primary system thermal fluids analyses were developed to meet modeling needs that are not well suited for the 1D-3D assembly level approach. The first of these is a reduced order assembly model, in which fuel centered unit cells are used to represent a fuel assembly. The 2D approach used in this model is much more computationally efficient, making this model useful for full core transient scenarios where fuel to coolant heat transfer is still the dominant flow path. The next model is the 3D core conduction model to be used to analyze decay heat removal in loss of primary system flow scenarios. Because these scenarios require a large domain to be modeled, a homogenized core model is being pursued to reduce the required computational costs. To accurately model decay heat scenarios it is necessary to couple a RCCS model to the 3D core conduction model. A simplified case is presented to demonstrate how the coupling methodology will be applied to the full core 3D conduction model.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".