Bibliographic record
Abstract
The Next Generation Very Large Array (ngVLA) project to replace the VLA telescope in New Mexico is just beginning. As a part of the initial Community Studies phase, we have contributed the concept design of a 15m feed-low wheel and track design. This telescope, the Next Generation Dish Verification Antenna 15m (ngDVA-15) follows on from the DVA-1 and DVA-2 antennas developed at the Dominion Radio Astrophysical Observatory (DRAO) between 2012 and the present day. This paper will concentrate on the design and optimization process for the ngDVA-15 back-up structure. Topology and free-size optimization were used to develop the initial design concepts. Both methods helped to steer the back-up structure in the initial design phase, but ultimately engineering intuition also played a role. Topology optimization can lead directly to useful solutions in some cases but hardware and software limitations still limit the physical size of the model. Also, topological routines cannot yet correctly model truss-type networks with no moment transfer at the joints, and optimizing structures with only gravitational loads proved to be challenging for the current generation of optimization routines. Size optimization was also used once the design was sufficiently refined. The initial stage of design involved minimization of reflector surface deflections under gravitational loads only. FEA modelling of surface deflections together with in-house developed fitting algorithms were used to determine primary surface accuracy. Surface accuracies of better than 80 microns RMS were achieved which met the initial design goal for telescope operation at 120GHz.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".