A Low-Cost High-Performance Alternative for Controlling a Servo-Hydraulic System for Triaxial Resilient Modulus Apparatus
Bibliographic record
Abstract
A triaxial test apparatus for the characterization of pavement materials was designed and built at the Pavement Research Center (PRC) at the University of California, Berkeley (UCB). The system was designed for high quality testing of unbound, stabilized, and asphaltic materials. The design process included the design of the hardware and the servo-controlling systems. An important step in the design of the system was the design of the controller for the servo-hydraulic system. Alternatives for controllers of servo-hydraulic systems for waveform generation included the use of the data acquisition system along with proportional, integral, and derivative (PID) algorithms for setting the minimum and maximum loads/displacement. Software programming for these solutions was very complex with limited satisfactory consistency. Commercial ready-to-use controllers are expensive and limited to the specifications of the manufacturer. Therefore, a commercially available programmable motion controller PIC card was implemented for controlling the servo-hydraulic system. The motion controller required only one PID controller to generate repeated waveforms or monotonic loading. An available commercial test solution software compatible with the motion controller card was used to program the motion controller and data acquisition system. This capability was preferable to provide flexibility in modifying the system based on research needs. Software programming was simple. In addition, the cost of the new system was reduced by about 80 percent with respect to the ready-to-use motion controllers. The paper describes the implementation of the motion controller, the philosophy of the software program, and the success obtained with the new system. The system meets all the quality control provision of the LTTP Protocol P-46. Currently the triaxial apparatus is being use to investigate the resilient response and permanent deformation performance of typical California aggregate base and subbases.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".