Multi-domain physical system modeling and control based on meta-modeling and graph rewriting
Why this work is in the frame
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Bibliographic record
Abstract
A methodology is presented which enables the specification and synthesis of software tools to aid in plant and controller modeling for multi-domain (electrical, mechanical, hydraulic, and thermal) physical systems. The methodology is based on meta-modeling and graph rewriting. The plant is modeled in a domain-specific formalism called the Real World Visual Model (RWVM). Such a model is successively transformed to an Idealized Physical Model (IPM), to an Acausal Bond Graph (ABG), and finally to a Causal Bond Graph (CBG). A Modelica (www.modelica.org) model, consisting of a Causal (algebraic and differential equation) Block Diagram (CBD), is generated from the CBG. All transformations are explicitly modeled using Graph Grammars. A PID controller model, specified in Modelica as a CBD is subsequently integrated with the plant model. AToM <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> (atom3.cs.mcgill.ca), A Tool for Multi-formalism and Meta Modeling is used to meta-model and synthesize visual modeling environments for the RWVM, IPM, ABG, and CBG formalisms as well as for transformations between them. The entire process of modeling, transformation, and simulation is demonstrated by means of a hoisting device example. Our methodology drastically reduces development time (of the modeling tool an indirectly of the domain-specific models), integrates model checking via Bond Graph causal analysis, and facilitates management and reuse of meta-knowledge by explicitly modeling formalisms and transformations.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| 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 it