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A Model-Based Computer Simulation of Anesthesia Machine Gas Flows
Edwin B. Liem, M.D.; David Lizdas, B.S.M.E.; Samsun Lampotang, Ph.D.
Department of Anesthesiology, University of Florida, Gainesville, Florida, United States
Introduction: We previously implemented Web-based animations of gas flows in an anesthesia machine [1]. Several problems were identified with the depiction of the gas flows in these prior versions: instantaneous appearance or disappearance of anesthetic gases, inability to show appropriate volumetric responses of the breathing bag, scavenging bag, bellows, and lungs to different flow rates, inability to show many different combinations of gas flow rates in each section of the machine and inability to demonstrate the effect of changes in ventilation rate, tidal volume or I:E ratio.

Objectives: The short-term objectives for the latest version of the Virtual Anesthesia Machine (VAM) 7.0 were (a) to continue emphasizing concepts and mental models rather than create a dimensionally accurate representation of the anesthesia machine, (b) address the problems with the depiction of the gas flows in previous versions (c) minimize the file size of the downloadable animation. Longer-term objectives were to develop generic methods to simulate gas flows in different anesthesia machine designs and during failure modes.

Methods: Because the pictorial representation of the pneumatic circuits was deliberately simplified to emphasize mental models and make most effective use of the available display area on the computer screen, a pure mathematical model of the gas flows in an actual anesthesia machine could not be used to drive the gas flow animation. However, using hard-coded scripts for every combination and permutation of ventilator settings and fresh gas flows would have been impractical and time consuming and increased the file size of the animation significantly. Therefore, we opted to use a semi-quantitative mathematical model that gives the flexibility of a mathematical model while retaining the simplified schematic of an anesthesia machine. Using Director 8 (Macromedia, San Francisco, CA), we made use of software abstraction layers to define the behaviors of objects that are influenced by multiple controls, e.g., the O2 and N2O flowmeter bobbins that are affected by the status of the O2 and N2O pipelines, cylinders and flowmeter knobs. In order to relate the icons on the schematic to the actual components, a photograph of each component pops-up in a window when the cursor is on the component.

Results: The user can manipulate controls such as the flowmeter and selector knobs and ventilator settings. Mathematical models drive the animation of the gas molecules and handle the user-initiated events that affect gas flow. User adjustment of the ventilator and anesthesia machine controls results in semi-quantitative changes in gas flow rates with corresponding changes in volumes of the breathing bag, scavenging bag, lungs and bellows. The absorption of CO2 in the soda lime canister and the influence of fresh gas flow, O2 flush and minute ventilation on the wash-in and washout of gases and vapors from different parts of the system are also demonstrated. Gas and agent molecules are phased in and out in a realistic manner.

Discussion: To our knowledge, no previous attempts to model the gas flows inside the entire anesthesia machine have been published. Goldman developed a mathematical model for gas flows in the circle system only [3].

Conclusions: VAM 7.0 demonstrates that it is possible to use mathematical models for semi-quantitative simulation of gas flows inside the entire anesthesia machine and lays the groundwork for generic simulation of gas flows in different anesthesia machine designs.


1. Lampotang S, Dobbins W, Good ML, Gravenstein N, Gravenstein D: Interactive, Web-based, educational simulation of an anesthesia machine, abstracted. J Clin Monit Comput 16:56-57, 2000.

2. Lampotang S, Lizdas D, Gravenstein N, Liem EB: Web-based educational animation of an anesthesia machine. ASA 2001 asbtract (submitted)

3. Goldman JM, Ward DR, Daniel LC, Squire CJ: Understanding the circle breathing circuit - An educational computer simulation. ASA scientific exhibit, page 530, 1995 ASA Annual Meeting Program.

Anesthesiology 2001; 95:A511