ISM-hydro: an interface tracking, finite volume code for modeling axisymmetric implosion of a rotating liquid metal liner with free surface
Bibliographic record
Abstract
We present ISM-hydro—an interface tracking, finite volume code for modeling a shaped implosion of a rotating, initially cylindrical, fluid shell (liner) with a free surface. The code is based on a novel implementation of the multilayer shallow water model, extended to a compressible fluid and adapted to an axisymmetric geometry described in cylindrical coordinates (r, ϕ, z). In ISM-hydro, a structured quadrilateral mesh follows fluid elements in the r-direction (radially-Lagrangian) and is fixed in the z-direction (axially-Eulerian). This mixed Lagrangian-Eulerian approach accurately captures the motion of the liner’s free surface, making it an interface tracking method. We derive a finite volume discretization of the axisymmetric Euler equations for a rotating compressible fluid which has an exact balance of kinetic energy, a property usually not satisfied in other finite volume algorithms. ISM-hydro is the purely hydrodynamic component of the Integrated System Model (ISM), a framework developed at General Fusion (GF) for comprehensive predictive modeling of GF’s magnetized target fusion scheme, where an imploding rotating liquid metal liner compresses a magnetized plasma target to fusion conditions. The main advantage of the code is its speed: a full implosion simulation with a coarse mesh takes on the order of one minute on a single core while preserving high accuracy. This makes ISM-hydro a valuable tool for the design optimization of GF’s MTF machines. The methodology, convergence study, and extensive comparison with the open-source software OpenFOAM are detailed in the article "An interface tracking, finite volume code for modeling axisymmetric implosion of a rotating liquid metal liner with free surface" from the same authors. Results for different test cases show very good agreement in simulated implosion trajectories and flow fields.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".