A New Approach to Modeling System Dynamics—In the Case of a Piezoelectric Actuator With a Host System
Bibliographic record
Abstract
With increasing sophistication in the structure and behavior of engineered plants, the system dynamics are becoming more complicated than ever before. This paper presents a new approach to model the dynamics of complex plants, and the new approach is rendered through a novel application of the axiomatic design theory (ADT). In particular, the dynamics to be modeled are analogous to the functional requirement of ADT, while the model structure (i.e., model) is analogous to the design parameter of ADT. In this way, the model development becomes to find a mapping from the functional requirement domain to the design parameter domain. The parameters of the model are further determined by decoupling the design matrix of ADT-an important formalism of ADT. To illustrate its effectiveness, the proposed approach is applied to a host system that is driven by a piezoelectric actuator (PEA). In particular, there is a bonding layer between the host system and the PEA, and sensors are embedded within the host system. To compare the proposed approach to other reported approaches, experiments were conducted, which suggested that the proposed approach is promising.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".