First commissioning experiments at DARHT-II
Bibliographic record
Abstract
The second axis of the Dual Axis Radiographic Hydro-Test (DARHT) facility will provide up to four short (< 150 ns) radiation pulses for flash radiography of high-explosive driven implosion experiments. To accomplish this the DARBT-II linear induction accelerator (LIA) will produce a 2-kA electron beam with 18-MeV kinetic energy, constant to within {+-}0.5% for 2-{mu}s. A fast kicker will cleave four short pulses out of the 2-{mu}s flattop, with the bulk of the beam diverted into a dump. The short pulses will then be transported to the final-focus magnet, and focused onto a tantalum target for conversion to bremsstrahlung pulses for radiography. DARHT-II is a collaborative effort between the Los Alamos, Lawrence Livermore, and Lawrence Berkeley National Laboratories of the University of California. The first tests of the second axis accelerator were designed to demonstrate the technology, and to meet the modest performance requirements for closing out. The DARHT-II construction project. These experiments demonstrated that we could indeed produce a 1.2 kA beam with pulse length 0.5-1.2 {mu}s and accelerate it to 12.5 MeV. These de-rated parameters were chosen to minimize risk of damage in these first experiments with this novel accelerator. The beam showed no evidence of the BBU instability for these parameters. In fact, we had to reduce the magnetic guide field by a factor of 5 before BBU was observed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".