Environmental Model Development

NextGen modeling techniques for reducing fuel consumption, increasing fuel efficiency, decreasing greenhouse-gas generation and lowering emissions and noise

Metron Aviation researches the modeling techniques and systems addressing fuel consumption, fuel efficiency, greenhouse gas generation, emissions related to local air quality and aircraft noise.  Environmental model development service involves the following activities:

  • Review of underlying mechanisms – Metron Aviation reviews the underlying physics and chemistry for the impacts being modeled to ensure that any key assumptions or limitations in the modeling techniques are well understood.
  • Algorithm development – Development of algorithms is consistent with the underlying mechanisms and technical requirements of the model (accuracy, speed, scope of input data, etc.).  These algorithms are consistent with global best practices.
  • Modeling system development – Metron Aviation integrates algorithms with appropriate data assembly, reporting and work-flow-management software within an integrated architecture.  Testing is performed, user documentation is developed and training materials are prepared as appropriate.

Highlights of these services as applied in some of our projects include:

Aviation Environmental Design Tool (AEDT) – Metron Aviation is a key contributor to the FAA's NextGen environmental tools, including AEDT and is responsible for development of key aspects of the multi-airport, regional component of AEDT, enabling environmental issues to be addressed at the larger scale that is often appropriate when considering the interactions of several airports, effects on regional air quality, etc.

Departure Noise Avoidance Planner (DNAP) – Metron Aviation developed an innovative solution to real-time interaction between an environmental planner and an operational planner.  The ability to interface with operational decision-support tools (i.e. CTAS), to integrate the decision logic across operational and environmental objectives, and to design noise calculations to fit a time budget, determined by this decision-support tool provides a much needed bridge between real-time operational intent and environmental goals.

Model development with an environmental focus