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Towards a Qualitative Lagrangian Theory of Fluid Flow

Conference Paper Representation and Reasoning: Qualitative Artificial Intelligence

Abstract

Choosing between multiple ontological perspectives is crucial for reasoning about the physical world. Choosing the wrong perspective can make a reasoning task impossible. This paper introduces a Lagrangian plug flow ontology (PF) for reasoning about thermodynamic fluid flow. We show that this ontology captures continuously changing behaviors of flowing fluids not represented in currently implemented ontologies. These behaviors are essential for understanding thermodynamic applications such as power cycles, refrigeration, liquefaction, throttling and flow through nozzles. We express the ontology within the framework of Qualitative Process (QP) theory. To derive our QP theory for plug flow, we use the method of causal clustering to find causal interpretations of thermodynamic equations. We also incorporate qualitative versions of standard thermodynamic relations, including the second law of thermodynamics and Clapeyron’s equation.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
96066026281431593
v2026.09.13